WorldWideScience

Sample records for ground sensor fusion

  1. Robust Ground Target Detection by SAR and IR Sensor Fusion Using Adaboost-Based Feature Selection

    Directory of Open Access Journals (Sweden)

    Sungho Kim

    2016-07-01

    Full Text Available Long-range ground targets are difficult to detect in a noisy cluttered environment using either synthetic aperture radar (SAR images or infrared (IR images. SAR-based detectors can provide a high detection rate with a high false alarm rate to background scatter noise. IR-based approaches can detect hot targets but are affected strongly by the weather conditions. This paper proposes a novel target detection method by decision-level SAR and IR fusion using an Adaboost-based machine learning scheme to achieve a high detection rate and low false alarm rate. The proposed method consists of individual detection, registration, and fusion architecture. This paper presents a single framework of a SAR and IR target detection method using modified Boolean map visual theory (modBMVT and feature-selection based fusion. Previous methods applied different algorithms to detect SAR and IR targets because of the different physical image characteristics. One method that is optimized for IR target detection produces unsuccessful results in SAR target detection. This study examined the image characteristics and proposed a unified SAR and IR target detection method by inserting a median local average filter (MLAF, pre-filter and an asymmetric morphological closing filter (AMCF, post-filter into the BMVT. The original BMVT was optimized to detect small infrared targets. The proposed modBMVT can remove the thermal and scatter noise by the MLAF and detect extended targets by attaching the AMCF after the BMVT. Heterogeneous SAR and IR images were registered automatically using the proposed RANdom SAmple Region Consensus (RANSARC-based homography optimization after a brute-force correspondence search using the detected target centers and regions. The final targets were detected by feature-selection based sensor fusion using Adaboost. The proposed method showed good SAR and IR target detection performance through feature selection-based decision fusion on a synthetic

  2. Robust Ground Target Detection by SAR and IR Sensor Fusion Using Adaboost-Based Feature Selection

    Science.gov (United States)

    Kim, Sungho; Song, Woo-Jin; Kim, So-Hyun

    2016-01-01

    Long-range ground targets are difficult to detect in a noisy cluttered environment using either synthetic aperture radar (SAR) images or infrared (IR) images. SAR-based detectors can provide a high detection rate with a high false alarm rate to background scatter noise. IR-based approaches can detect hot targets but are affected strongly by the weather conditions. This paper proposes a novel target detection method by decision-level SAR and IR fusion using an Adaboost-based machine learning scheme to achieve a high detection rate and low false alarm rate. The proposed method consists of individual detection, registration, and fusion architecture. This paper presents a single framework of a SAR and IR target detection method using modified Boolean map visual theory (modBMVT) and feature-selection based fusion. Previous methods applied different algorithms to detect SAR and IR targets because of the different physical image characteristics. One method that is optimized for IR target detection produces unsuccessful results in SAR target detection. This study examined the image characteristics and proposed a unified SAR and IR target detection method by inserting a median local average filter (MLAF, pre-filter) and an asymmetric morphological closing filter (AMCF, post-filter) into the BMVT. The original BMVT was optimized to detect small infrared targets. The proposed modBMVT can remove the thermal and scatter noise by the MLAF and detect extended targets by attaching the AMCF after the BMVT. Heterogeneous SAR and IR images were registered automatically using the proposed RANdom SAmple Region Consensus (RANSARC)-based homography optimization after a brute-force correspondence search using the detected target centers and regions. The final targets were detected by feature-selection based sensor fusion using Adaboost. The proposed method showed good SAR and IR target detection performance through feature selection-based decision fusion on a synthetic database generated

  3. Sensor Data Fusion

    DEFF Research Database (Denmark)

    Plascencia, Alfredo; Stepán, Petr

    2006-01-01

    The main contribution of this paper is to present a sensor fusion approach to scene environment mapping as part of a Sensor Data Fusion (SDF) architecture. This approach involves combined sonar array with stereo vision readings.  Sonar readings are interpreted using probability density functions...

  4. Enhanced chemical weapon warning via sensor fusion

    Science.gov (United States)

    Flaherty, Michael; Pritchett, Daniel; Cothren, Brian; Schwaiger, James

    2011-05-01

    Torch Technologies Inc., is actively involved in chemical sensor networking and data fusion via multi-year efforts with Dugway Proving Ground (DPG) and the Defense Threat Reduction Agency (DTRA). The objective of these efforts is to develop innovative concepts and advanced algorithms that enhance our national Chemical Warfare (CW) test and warning capabilities via the fusion of traditional and non-traditional CW sensor data. Under Phase I, II, and III Small Business Innovative Research (SBIR) contracts with DPG, Torch developed the Advanced Chemical Release Evaluation System (ACRES) software to support non real-time CW sensor data fusion. Under Phase I and II SBIRs with DTRA in conjunction with the Edgewood Chemical Biological Center (ECBC), Torch is using the DPG ACRES CW sensor data fuser as a framework from which to develop the Cloud state Estimation in a Networked Sensor Environment (CENSE) data fusion system. Torch is currently developing CENSE to implement and test innovative real-time sensor network based data fusion concepts using CW and non-CW ancillary sensor data to improve CW warning and detection in tactical scenarios.

  5. Fusion of Images from Dissimilar Sensor Systems

    National Research Council Canada - National Science Library

    Chow, Khin

    2004-01-01

    Different sensors exploit different regions of the electromagnetic spectrum; therefore a multi-sensor image fusion system can take full advantage of the complementary capabilities of individual sensors in the suit...

  6. Adaptive sensor fusion using genetic algorithms

    International Nuclear Information System (INIS)

    Fitzgerald, D.S.; Adams, D.G.

    1994-01-01

    Past attempts at sensor fusion have used some form of Boolean logic to combine the sensor information. As an alteniative, an adaptive ''fuzzy'' sensor fusion technique is described in this paper. This technique exploits the robust capabilities of fuzzy logic in the decision process as well as the optimization features of the genetic algorithm. This paper presents a brief background on fuzzy logic and genetic algorithms and how they are used in an online implementation of adaptive sensor fusion

  7. Enhanced technologies for unattended ground sensor systems

    Science.gov (United States)

    Hartup, David C.

    2010-04-01

    Progress in several technical areas is being leveraged to advantage in Unattended Ground Sensor (UGS) systems. This paper discusses advanced technologies that are appropriate for use in UGS systems. While some technologies provide evolutionary improvements, other technologies result in revolutionary performance advancements for UGS systems. Some specific technologies discussed include wireless cameras and viewers, commercial PDA-based system programmers and monitors, new materials and techniques for packaging improvements, low power cueing sensor radios, advanced long-haul terrestrial and SATCOM radios, and networked communications. Other technologies covered include advanced target detection algorithms, high pixel count cameras for license plate and facial recognition, small cameras that provide large stand-off distances, video transmissions of target activity instead of still images, sensor fusion algorithms, and control center hardware. The impact of each technology on the overall UGS system architecture is discussed, along with the advantages provided to UGS system users. Areas of analysis include required camera parameters as a function of stand-off distance for license plate and facial recognition applications, power consumption for wireless cameras and viewers, sensor fusion communication requirements, and requirements to practically implement video transmission through UGS systems. Examples of devices that have already been fielded using technology from several of these areas are given.

  8. Sensor fusion for intelligent alarm analysis

    International Nuclear Information System (INIS)

    Nelson, C.L.; Fitzgerald, D.S.

    1996-01-01

    The purpose of an intelligent alarm analysis system is to provide complete and manageable information to a central alarm station operator by applying alarm processing and fusion techniques to sensor information. This paper discusses the sensor fusion approach taken to perform intelligent alarm analysis for the Advanced Exterior Sensor (AES). The AES is an intrusion detection and assessment system designed for wide-area coverage, quick deployment, low false/nuisance alarm operation, and immediate visual assessment. It combines three sensor technologies (visible, infrared, and millimeter wave radar) collocated on a compact and portable remote sensor module. The remote sensor module rotates at a rate of 1 revolution per second to detect and track motion and provide assessment in a continuous 360 degree field-of-regard. Sensor fusion techniques are used to correlate and integrate the track data from these three sensors into a single track for operator observation. Additional inputs to the fusion process include environmental data, knowledge of sensor performance under certain weather conditions, sensor priority, and recent operator feedback. A confidence value is assigned to the track as a result of the fusion process. This helps to reduce nuisance alarms and to increase operator confidence in the system while reducing the workload of the operator

  9. Efficient sensor selection for active information fusion.

    Science.gov (United States)

    Zhang, Yongmian; Ji, Qiang

    2010-06-01

    In our previous paper, we formalized an active information fusion framework based on dynamic Bayesian networks to provide active information fusion. This paper focuses on a central issue of active information fusion, i.e., the efficient identification of a subset of sensors that are most decision relevant and cost effective. Determining the most informative and cost-effective sensors requires an evaluation of all the possible subsets of sensors, which is computationally intractable, particularly when information-theoretic criterion such as mutual information is used. To overcome this challenge, we propose a new quantitative measure for sensor synergy based on which a sensor synergy graph is constructed. Using the sensor synergy graph, we first introduce an alternative measure to multisensor mutual information for characterizing the sensor information gain. We then propose an approximated nonmyopic sensor selection method that can efficiently and near-optimally select a subset of sensors for active fusion. The simulation study demonstrates both the performance and the efficiency of the proposed sensor selection method.

  10. Sensor Fusion Based Model for Collision Free Mobile Robot Navigation

    Science.gov (United States)

    Almasri, Marwah; Elleithy, Khaled; Alajlan, Abrar

    2015-01-01

    Autonomous mobile robots have become a very popular and interesting topic in the last decade. Each of them are equipped with various types of sensors such as GPS, camera, infrared and ultrasonic sensors. These sensors are used to observe the surrounding environment. However, these sensors sometimes fail and have inaccurate readings. Therefore, the integration of sensor fusion will help to solve this dilemma and enhance the overall performance. This paper presents a collision free mobile robot navigation based on the fuzzy logic fusion model. Eight distance sensors and a range finder camera are used for the collision avoidance approach where three ground sensors are used for the line or path following approach. The fuzzy system is composed of nine inputs which are the eight distance sensors and the camera, two outputs which are the left and right velocities of the mobile robot’s wheels, and 24 fuzzy rules for the robot’s movement. Webots Pro simulator is used for modeling the environment and the robot. The proposed methodology, which includes the collision avoidance based on fuzzy logic fusion model and line following robot, has been implemented and tested through simulation and real time experiments. Various scenarios have been presented with static and dynamic obstacles using one robot and two robots while avoiding obstacles in different shapes and sizes. PMID:26712766

  11. Sensor Fusion Based Model for Collision Free Mobile Robot Navigation

    Directory of Open Access Journals (Sweden)

    Marwah Almasri

    2015-12-01

    Full Text Available Autonomous mobile robots have become a very popular and interesting topic in the last decade. Each of them are equipped with various types of sensors such as GPS, camera, infrared and ultrasonic sensors. These sensors are used to observe the surrounding environment. However, these sensors sometimes fail and have inaccurate readings. Therefore, the integration of sensor fusion will help to solve this dilemma and enhance the overall performance. This paper presents a collision free mobile robot navigation based on the fuzzy logic fusion model. Eight distance sensors and a range finder camera are used for the collision avoidance approach where three ground sensors are used for the line or path following approach. The fuzzy system is composed of nine inputs which are the eight distance sensors and the camera, two outputs which are the left and right velocities of the mobile robot’s wheels, and 24 fuzzy rules for the robot’s movement. Webots Pro simulator is used for modeling the environment and the robot. The proposed methodology, which includes the collision avoidance based on fuzzy logic fusion model and line following robot, has been implemented and tested through simulation and real time experiments. Various scenarios have been presented with static and dynamic obstacles using one robot and two robots while avoiding obstacles in different shapes and sizes.

  12. Sensor fusion for mobile robot navigation

    International Nuclear Information System (INIS)

    Kam, M.; Zhu, X.; Kalata, P.

    1997-01-01

    The authors review techniques for sensor fusion in robot navigation, emphasizing algorithms for self-location. These find use when the sensor suite of a mobile robot comprises several different sensors, some complementary and some redundant. Integrating the sensor readings, the robot seeks to accomplish tasks such as constructing a map of its environment, locating itself in that map, and recognizing objects that should be avoided or sought. The review describes integration techniques in two categories: low-level fusion is used for direct integration of sensory data, resulting in parameter and state estimates; high-level fusion is used for indirect integration of sensory data in hierarchical architectures, through command arbitration and integration of control signals suggested by different modules. The review provides an arsenal of tools for addressing this (rather ill-posed) problem in machine intelligence, including Kalman filtering, rule-based techniques, behavior based algorithms and approaches that borrow from information theory, Dempster-Shafer reasoning, fuzzy logic and neural networks. It points to several further-research needs, including: robustness of decision rules; simultaneous consideration of self-location, motion planning, motion control and vehicle dynamics; the effect of sensor placement and attention focusing on sensor fusion; and adaptation of techniques from biological sensor fusion

  13. Sensor Fusion for Autonomous Mobile Robot Navigation

    DEFF Research Database (Denmark)

    Plascencia, Alfredo

    Multi-sensor data fusion is a broad area of constant research which is applied to a wide variety of fields such as the field of mobile robots. Mobile robots are complex systems where the design and implementation of sensor fusion is a complex task. But research applications are explored constantl....... The scope of the thesis is limited to building a map for a laboratory robot by fusing range readings from a sonar array with landmarks extracted from stereo vision images using the (Scale Invariant Feature Transform) SIFT algorithm....

  14. Performance evaluation of multi-sensor data fusion technique for ...

    Indian Academy of Sciences (India)

    R. Narasimhan (Krishtel eMaging) 1461 1996 Oct 15 13:05:22

    Multi-sensor data fusion; Test Range application; trajectory .... Kalman filtering technique utilizes the noise statistics of the underlying system under con- ..... Hall D L 1992 Mathematical techniques in multi-sensor data fusion (Boston, MA: ...

  15. Data fusion and sensor management for nuclear power plant safety

    Energy Technology Data Exchange (ETDEWEB)

    Ciftcioglu, O [Istanbul Technical Univ., Istanbul (Turkey). Nuclear Power Dept.; Turkcan, E [Netherlands Energy Research Foundation (ECN), Petten (Netherlands)

    1997-12-31

    The paper describes the implementation of the data-sensor fusion and sensor management technology for accident management through simulated severe accident (SA) scenarios subjected to study. The organization of the present paper is as follows. As the data-sensor fusion and sensor management is an emerging technology which is not widely known, in Sec. 2, the definition and goals of data-sensor fusion and sensor management technology is described. In Sec. 3 fits, with reference to Kalman filtering as an information filter, statistical data-sensor fusion technology is described. This is followed by deterministic data-sensor fusion technology using gross plant state variables and neural networks (NN) and the implementation for severe accident management in NPPs. In Sec. 4, the sensor management technology is described. Finally, the performance of the data-sensor fusion technology for NPP safety is discussed. 12 refs, 6 figs.

  16. Data fusion and sensor management for nuclear power plant safety

    International Nuclear Information System (INIS)

    Ciftcioglu, O.

    1996-01-01

    The paper describes the implementation of the data-sensor fusion and sensor management technology for accident management through simulated severe accident (SA) scenarios subjected to study. The organization of the present paper is as follows. As the data-sensor fusion and sensor management is an emerging technology which is not widely known, in Sec. 2, the definition and goals of data-sensor fusion and sensor management technology is described. In Sec. 3 fits, with reference to Kalman filtering as an information filter, statistical data-sensor fusion technology is described. This is followed by deterministic data-sensor fusion technology using gross plant state variables and neural networks (NN) and the implementation for severe accident management in NPPs. In Sec. 4, the sensor management technology is described. Finally, the performance of the data-sensor fusion technology for NPP safety is discussed. 12 refs, 6 figs

  17. A comparison of decision-level sensor-fusion methods for anti-personnel landmine detection.

    NARCIS (Netherlands)

    Schutte, K.; Schavemaker, J.G.M.; Cremer, F.; Breejen, E. den

    2001-01-01

    We present the sensor-fusion results obtained from measurements within the European research project ground explosive ordinance detection (GEODE) system that strives for the realisation of a vehicle-mounted, multi-sensor, anti-personnel landmine-detection system for humanitarian de-mining. The

  18. Infrared processing and sensor fusion for anti-personnel land-mine detection

    NARCIS (Netherlands)

    Schavemaker, J.G.M.; Cremer, F.; Schutte, K.; Breejen, E. den

    2000-01-01

    In this paper we present the results of infrared processing and sensor fusion obtained within the European research project GEODE (Ground Explosive Ordnance DEtection) that strives for the realization of a vehicle-mounted, multi-sensor anti-personnel land-mine detection system for humanitarian

  19. Non-verbal communication through sensor fusion

    Science.gov (United States)

    Tairych, Andreas; Xu, Daniel; O'Brien, Benjamin M.; Anderson, Iain A.

    2016-04-01

    When we communicate face to face, we subconsciously engage our whole body to convey our message. In telecommunication, e.g. during phone calls, this powerful information channel cannot be used. Capturing nonverbal information from body motion and transmitting it to the receiver parallel to speech would make these conversations feel much more natural. This requires a sensing device that is capable of capturing different types of movements, such as the flexion and extension of joints, and the rotation of limbs. In a first embodiment, we developed a sensing glove that is used to control a computer game. Capacitive dielectric elastomer (DE) sensors measure finger positions, and an inertial measurement unit (IMU) detects hand roll. These two sensor technologies complement each other, with the IMU allowing the player to move an avatar through a three-dimensional maze, and the DE sensors detecting finger flexion to fire weapons or open doors. After demonstrating the potential of sensor fusion in human-computer interaction, we take this concept to the next level and apply it in nonverbal communication between humans. The current fingerspelling glove prototype uses capacitive DE sensors to detect finger gestures performed by the sending person. These gestures are mapped to corresponding messages and transmitted wirelessly to another person. A concept for integrating an IMU into this system is presented. The fusion of the DE sensor and the IMU combines the strengths of both sensor types, and therefore enables very comprehensive body motion sensing, which makes a large repertoire of gestures available to nonverbal communication over distances.

  20. Sensor data fusion to predict multiple soil properties

    NARCIS (Netherlands)

    Mahmood, H.S.; Hoogmoed, W.B.; Henten, van E.J.

    2012-01-01

    The accuracy of a single sensor is often low because all proximal soil sensors respond to more than one soil property of interest. Sensor data fusion can potentially overcome this inability of a single sensor and can best extract useful and complementary information from multiple sensors or sources.

  1. Sensor Fusion and Smart Sensor in Sports and Biomedical Applications

    Directory of Open Access Journals (Sweden)

    José Jair Alves Mendes Jr.

    2016-09-01

    Full Text Available The following work presents an overview of smart sensors and sensor fusion targeted at biomedical applications and sports areas. In this work, the integration of these areas is demonstrated, promoting a reflection about techniques and applications to collect, quantify and qualify some physical variables associated with the human body. These techniques are presented in various biomedical and sports applications, which cover areas related to diagnostics, rehabilitation, physical monitoring, and the development of performance in athletes, among others. Although some applications are described in only one of two fields of study (biomedicine and sports, it is very likely that the same application fits in both, with small peculiarities or adaptations. To illustrate the contemporaneity of applications, an analysis of specialized papers published in the last six years has been made. In this context, the main characteristic of this review is to present the largest quantity of relevant examples of sensor fusion and smart sensors focusing on their utilization and proposals, without deeply addressing one specific system or technique, to the detriment of the others.

  2. Feasibility study on sensor data fusion for the CP-140 aircraft: fusion architecture analyses

    Science.gov (United States)

    Shahbazian, Elisa

    1995-09-01

    Loral Canada completed (May 1995) a Department of National Defense (DND) Chief of Research and Development (CRAD) contract, to study the feasibility of implementing a multi- sensor data fusion (MSDF) system onboard the CP-140 Aurora aircraft. This system is expected to fuse data from: (a) attributed measurement oriented sensors (ESM, IFF, etc.); (b) imaging sensors (FLIR, SAR, etc.); (c) tracking sensors (radar, acoustics, etc.); (d) data from remote platforms (data links); and (e) non-sensor data (intelligence reports, environmental data, visual sightings, encyclopedic data, etc.). Based on purely theoretical considerations a central-level fusion architecture will lead to a higher performance fusion system. However, there are a number of systems and fusion architecture issues involving fusion of such dissimilar data: (1) the currently existing sensors are not designed to provide the type of data required by a fusion system; (2) the different types (attribute, imaging, tracking, etc.) of data may require different degree of processing, before they can be used within a fusion system efficiently; (3) the data quality from different sensors, and more importantly from remote platforms via the data links must be taken into account before fusing; and (4) the non-sensor data may impose specific requirements on the fusion architecture (e.g. variable weight/priority for the data from different sensors). This paper presents the analyses performed for the selection of the fusion architecture for the enhanced sensor suite planned for the CP-140 aircraft in the context of the mission requirements and environmental conditions.

  3. Phase 1 report on sensor technology, data fusion and data interpretation for site characterization

    International Nuclear Information System (INIS)

    Beckerman, M.

    1991-10-01

    In this report we discuss sensor technology, data fusion and data interpretation approaches of possible maximal usefulness for subsurface imaging and characterization of land-fill waste sites. Two sensor technologies, terrain conductivity using electromagnetic induction and ground penetrating radar, are described and the literature on the subject is reviewed. We identify the maximum entropy stochastic method as one providing a rigorously justifiable framework for fusing the sensor data, briefly summarize work done by us in this area, and examine some of the outstanding issues with regard to data fusion and interpretation. 25 refs., 17 figs

  4. Fluorescent sensors based on bacterial fusion proteins

    International Nuclear Information System (INIS)

    Mateu, Batirtze Prats; Pum, Dietmar; Sleytr, Uwe B; Toca-Herrera, José L; Kainz, Birgit

    2014-01-01

    Fluorescence proteins are widely used as markers for biomedical and technological purposes. Therefore, the aim of this project was to create a fluorescent sensor, based in the green and cyan fluorescent protein, using bacterial S-layers proteins as scaffold for the fluorescent tag. We report the cloning, expression and purification of three S-layer fluorescent proteins: SgsE-EGFP, SgsE-ECFP and SgsE-13aa-ECFP, this last containing a 13-amino acid rigid linker. The pH dependence of the fluorescence intensity of the S-layer fusion proteins, monitored by fluorescence spectroscopy, showed that the ECFP tag was more stable than EGFP. Furthermore, the fluorescent fusion proteins were reassembled on silica particles modified with cationic and anionic polyelectrolytes. Zeta potential measurements confirmed the particle coatings and indicated their colloidal stability. Flow cytometry and fluorescence microscopy showed that the fluorescence of the fusion proteins was pH dependent and sensitive to the underlying polyelectrolyte coating. This might suggest that the fluorescent tag is not completely exposed to the bulk media as an independent moiety. Finally, it was found out that viscosity enhanced the fluorescence intensity of the three fluorescent S-layer proteins. (paper)

  5. Sensor fusion in smart camera networks for ambient Intelligence

    NARCIS (Netherlands)

    Maatta, T.T.

    2013-01-01

    This short report introduces the topics of PhD research that was conducted on 2008-2013 and was defended on July 2013. The PhD thesis covers sensor fusion theory, gathers it into a framework with design rules for fusion-friendly design of vision networks, and elaborates on the rules through fusion

  6. Advances in multi-sensor data fusion: algorithms and applications.

    Science.gov (United States)

    Dong, Jiang; Zhuang, Dafang; Huang, Yaohuan; Fu, Jingying

    2009-01-01

    With the development of satellite and remote sensing techniques, more and more image data from airborne/satellite sensors have become available. Multi-sensor image fusion seeks to combine information from different images to obtain more inferences than can be derived from a single sensor. In image-based application fields, image fusion has emerged as a promising research area since the end of the last century. The paper presents an overview of recent advances in multi-sensor satellite image fusion. Firstly, the most popular existing fusion algorithms are introduced, with emphasis on their recent improvements. Advances in main applications fields in remote sensing, including object identification, classification, change detection and maneuvering targets tracking, are described. Both advantages and limitations of those applications are then discussed. Recommendations are addressed, including: (1) Improvements of fusion algorithms; (2) Development of "algorithm fusion" methods; (3) Establishment of an automatic quality assessment scheme.

  7. Tracking and sensor data fusion methodological framework and selected applications

    CERN Document Server

    Koch, Wolfgang

    2013-01-01

    Sensor Data Fusion is the process of combining incomplete and imperfect pieces of mutually complementary sensor information in such a way that a better understanding of an underlying real-world phenomenon is achieved. Typically, this insight is either unobtainable otherwise or a fusion result exceeds what can be produced from a single sensor output in accuracy, reliability, or cost. This book provides an introduction Sensor Data Fusion, as an information technology as well as a branch of engineering science and informatics. Part I presents a coherent methodological framework, thus providing th

  8. Distributed data fusion across multiple hard and soft mobile sensor platforms

    Science.gov (United States)

    Sinsley, Gregory

    One of the biggest challenges currently facing the robotics field is sensor data fusion. Unmanned robots carry many sophisticated sensors including visual and infrared cameras, radar, laser range finders, chemical sensors, accelerometers, gyros, and global positioning systems. By effectively fusing the data from these sensors, a robot would be able to form a coherent view of its world that could then be used to facilitate both autonomous and intelligent operation. Another distinct fusion problem is that of fusing data from teammates with data from onboard sensors. If an entire team of vehicles has the same worldview they will be able to cooperate much more effectively. Sharing worldviews is made even more difficult if the teammates have different sensor types. The final fusion challenge the robotics field faces is that of fusing data gathered by robots with data gathered by human teammates (soft sensors). Humans sense the world completely differently from robots, which makes this problem particularly difficult. The advantage of fusing data from humans is that it makes more information available to the entire team, thus helping each agent to make the best possible decisions. This thesis presents a system for fusing data from multiple unmanned aerial vehicles, unmanned ground vehicles, and human observers. The first issue this thesis addresses is that of centralized data fusion. This is a foundational data fusion issue, which has been very well studied. Important issues in centralized fusion include data association, classification, tracking, and robotics problems. Because these problems are so well studied, this thesis does not make any major contributions in this area, but does review it for completeness. The chapter on centralized fusion concludes with an example unmanned aerial vehicle surveillance problem that demonstrates many of the traditional fusion methods. The second problem this thesis addresses is that of distributed data fusion. Distributed data fusion

  9. Data fusion and sensor management for nuclear power plant safety

    International Nuclear Information System (INIS)

    Ciftcioglu, Oe.

    1996-05-01

    The paper describes the implementation of the data-sensor fusion and sensor management technology for accident management through simulated severe accident (SA) scenarios subjected to study. By means of accident management the appropriate prompt actions to be taken to avoid nuclear accident (SA) scenarios subjected to study. By means of accident management the appropriate prompt actions to be taken to avoid nuclear accidents are meant, while such accidents are deemed to somehow be imminent during plant operation. The organisation of the present paper is as follows. As the data-sensor fusion and sensor management is an emerging technology which is not widely known, in Sec. 2, the definition and goals of data-sensor fusion and sensor management technology is described. In Sec. 3 first, with reference to Kalman filtering as an information filter, statistical data-sensor fusion technology is described. This is followed by the examples of deterministic data-sensor fusion technology using gross plant state variables and neural networks (NN) and the implementation for severe accident management in NPPs. In Sec. 4, the sensor management technology is described. Finally, the performance of the data-sensor fusion technology for NPP safety is discussed. (orig./WL)

  10. PERSON AUTHENTICATION USING MULTIPLE SENSOR DATA FUSION

    Directory of Open Access Journals (Sweden)

    S. Vasuhi

    2011-04-01

    Full Text Available This paper proposes a real-time system for face authentication, obtained through fusion of Infra Red (IR and visible images. In order to identify the unknown person authentication in highly secured areas, multiple algorithms are needed. The four well known algorithms for face recognition, Block Independent Component Analysis(BICA, Kalman Filtering(KF method, Discrete Cosine Transform(DCT and Orthogonal Locality Preserving Projections (OLPP are used to extract the features. If the data base size is very large and the features are not distinct then ambiguity will exists in face recognition. Hence more than one sensor is needed for critical and/or highly secured areas. This paper deals with multiple fusion methodology using weighted average and Fuzzy Logic. The visible sensor output depends on the environmental condition namely lighting conditions, illumination etc., to overcome this problem use histogram technique to choose appropriate algorithm. DCT and Kalman filtering are holistic approaches, BICA follows feature based approach and OLPP preserves the Euclidean structure of face space. These recognizers are capable of considering the problem of dimensionality reduction by eliminating redundant features and reducing the feature space. The system can handle variations like illumination, pose, orientation, occlusion, etc. up to a significant level. The integrated system overcomes the drawbacks of individual recognizers. The proposed system is aimed at increasing the accuracy of the person authentication system and at the same time reducing the limitations of individual algorithms. It is tested on real time database and the results are found to be 96% accurate.

  11. Artillery localization using networked wireless ground sensors

    Science.gov (United States)

    Swanson, David C.

    2002-08-01

    This paper presents the results of an installation of four acoustic/seismic ground sensors built using COTS computers and networking gear and operating on a continuous basis at Yuma Proving Grounds, Arizona. A description of the design can be found as well, which is essentially a Windows 2000 PC with 24-bit data acquisition, GPS timing, and environmental sensors for wind and temperature. A 4-element square acoustic array 1.8m on a side can be used to detect the time and angle of arrival of the muzzle blast and the impact explosion. A 3-component geophone allows the seismic wave direction to be estimated. The 8th channel of the 24-bit data acquisition system has a 1-pulse-per-second time signal from the GPS. This allows acoustic/seismic 'snapshots' to be coherently related from multiple disconnected ground sensor nodes. COTS 2.4 GHz frequency hopping radios (802.11 standard) are used with either omni or yagi antennas depending on the location on the range. Localization of the artillery or impact can be done by using the time and angle of arrival of the waves at 2 or more ground sensor locations. However, this straightforward analysis can be significantly complicated by weather and wind noise and is also the subject of another research contract. This work will present a general description of the COTS ground sensor installation, show example data autonomously collected including agent-based atmospheric data, and share some of the lessons learned from operating a Windows 2000 based system continuously outdoors.

  12. Fusion of Radar and EO-sensors for Surveillance

    NARCIS (Netherlands)

    Kester, L.J.H.M.; Theil, A.

    2001-01-01

    Fusion of radar and EO-sensors is investigated for the purpose of surveillance in littoral waters is. All sensors are considered to be co-located with respect to the distance, typically 1 to 10 km, of the area under surveillance. The sensor suite is a coherent polarimetric radar in combination with

  13. Multivariate Sensitivity Analysis of Time-of-Flight Sensor Fusion

    Science.gov (United States)

    Schwarz, Sebastian; Sjöström, Mårten; Olsson, Roger

    2014-09-01

    Obtaining three-dimensional scenery data is an essential task in computer vision, with diverse applications in various areas such as manufacturing and quality control, security and surveillance, or user interaction and entertainment. Dedicated Time-of-Flight sensors can provide detailed scenery depth in real-time and overcome short-comings of traditional stereo analysis. Nonetheless, they do not provide texture information and have limited spatial resolution. Therefore such sensors are typically combined with high resolution video sensors. Time-of-Flight Sensor Fusion is a highly active field of research. Over the recent years, there have been multiple proposals addressing important topics such as texture-guided depth upsampling and depth data denoising. In this article we take a step back and look at the underlying principles of ToF sensor fusion. We derive the ToF sensor fusion error model and evaluate its sensitivity to inaccuracies in camera calibration and depth measurements. In accordance with our findings, we propose certain courses of action to ensure high quality fusion results. With this multivariate sensitivity analysis of the ToF sensor fusion model, we provide an important guideline for designing, calibrating and running a sophisticated Time-of-Flight sensor fusion capture systems.

  14. Assessing the Performance of Sensor Fusion Methods: Application to Magnetic-Inertial-Based Human Body Tracking.

    Science.gov (United States)

    Ligorio, Gabriele; Bergamini, Elena; Pasciuto, Ilaria; Vannozzi, Giuseppe; Cappozzo, Aurelio; Sabatini, Angelo Maria

    2016-01-26

    Information from complementary and redundant sensors are often combined within sensor fusion algorithms to obtain a single accurate observation of the system at hand. However, measurements from each sensor are characterized by uncertainties. When multiple data are fused, it is often unclear how all these uncertainties interact and influence the overall performance of the sensor fusion algorithm. To address this issue, a benchmarking procedure is presented, where simulated and real data are combined in different scenarios in order to quantify how each sensor's uncertainties influence the accuracy of the final result. The proposed procedure was applied to the estimation of the pelvis orientation using a waist-worn magnetic-inertial measurement unit. Ground-truth data were obtained from a stereophotogrammetric system and used to obtain simulated data. Two Kalman-based sensor fusion algorithms were submitted to the proposed benchmarking procedure. For the considered application, gyroscope uncertainties proved to be the main error source in orientation estimation accuracy for both tested algorithms. Moreover, although different performances were obtained using simulated data, these differences became negligible when real data were considered. The outcome of this evaluation may be useful both to improve the design of new sensor fusion methods and to drive the algorithm tuning process.

  15. Application of a sensor fusion algorithm for improving grasping stability

    Energy Technology Data Exchange (ETDEWEB)

    Kim, Jae Hyeon; Yoon, Hyun Suck; Moon, Hyung Pil; Choi, Hyouk Ryeol; Koo Ja Choon [Sungkyunkwan University, Suwon (Korea, Republic of)

    2015-07-15

    A robot hand normally employees various sensors that are packaged in small form factor, perform with delicately accurate, and cost mostly very expensive. Grasping operation of the hand relies especially on accuracy of those sensors. Even with a set of advanced sensory systems embedded in a robot hand, securing a stable grasping is still challenging task. The present work makes an attempt to improve force sensor accuracy by applying sensor fusion method. An optimal weight value sensor fusion method formulated with Kalman filters is presented and tested in the work. Using a set of inexpensive sensors, the work achieves a reliable force sensing and applies the enhanced sensor stability to an object pinch grasping.

  16. Application of a sensor fusion algorithm for improving grasping stability

    International Nuclear Information System (INIS)

    Kim, Jae Hyeon; Yoon, Hyun Suck; Moon, Hyung Pil; Choi, Hyouk Ryeol; Koo Ja Choon

    2015-01-01

    A robot hand normally employees various sensors that are packaged in small form factor, perform with delicately accurate, and cost mostly very expensive. Grasping operation of the hand relies especially on accuracy of those sensors. Even with a set of advanced sensory systems embedded in a robot hand, securing a stable grasping is still challenging task. The present work makes an attempt to improve force sensor accuracy by applying sensor fusion method. An optimal weight value sensor fusion method formulated with Kalman filters is presented and tested in the work. Using a set of inexpensive sensors, the work achieves a reliable force sensing and applies the enhanced sensor stability to an object pinch grasping.

  17. Multi-sensor image fusion and its applications

    CERN Document Server

    Blum, Rick S

    2005-01-01

    Taking another lesson from nature, the latest advances in image processing technology seek to combine image data from several diverse types of sensors in order to obtain a more accurate view of the scene: very much the same as we rely on our five senses. Multi-Sensor Image Fusion and Its Applications is the first text dedicated to the theory and practice of the registration and fusion of image data, covering such approaches as statistical methods, color-related techniques, model-based methods, and visual information display strategies.After a review of state-of-the-art image fusion techniques,

  18. Performance evaluation of multi-sensor data-fusion systems

    Indian Academy of Sciences (India)

    In this paper, the utilization of multi-sensors of different types, their characteristics, and their data-fusion in launch vehicles to achieve the goal of injecting the satellite into a precise orbit is explained. Performance requirements of sensors and their redundancy management in a typical launch vehicle are also included.

  19. Motion Artifact Quantification and Sensor Fusion for Unobtrusive Health Monitoring

    Directory of Open Access Journals (Sweden)

    Christoph Hoog Antink

    2017-12-01

    Full Text Available Sensors integrated into objects of everyday life potentially allow unobtrusive health monitoring at home. However, since the coupling of sensors and subject is not as well-defined as compared to a clinical setting, the signal quality is much more variable and can be disturbed significantly by motion artifacts. One way of tackling this challenge is the combined evaluation of multiple channels via sensor fusion. For robust and accurate sensor fusion, analyzing the influence of motion on different modalities is crucial. In this work, a multimodal sensor setup integrated into an armchair is presented that combines capacitively coupled electrocardiography, reflective photoplethysmography, two high-frequency impedance sensors and two types of ballistocardiography sensors. To quantify motion artifacts, a motion protocol performed by healthy volunteers is recorded with a motion capture system, and reference sensors perform cardiorespiratory monitoring. The shape-based signal-to-noise ratio SNR S is introduced and used to quantify the effect on motion on different sensing modalities. Based on this analysis, an optimal combination of sensors and fusion methodology is developed and evaluated. Using the proposed approach, beat-to-beat heart-rate is estimated with a coverage of 99.5% and a mean absolute error of 7.9 ms on 425 min of data from seven volunteers in a proof-of-concept measurement scenario.

  20. Motion Artifact Quantification and Sensor Fusion for Unobtrusive Health Monitoring

    Science.gov (United States)

    Hoog Antink, Christoph; Schulz, Florian; Walter, Marian

    2017-01-01

    Sensors integrated into objects of everyday life potentially allow unobtrusive health monitoring at home. However, since the coupling of sensors and subject is not as well-defined as compared to a clinical setting, the signal quality is much more variable and can be disturbed significantly by motion artifacts. One way of tackling this challenge is the combined evaluation of multiple channels via sensor fusion. For robust and accurate sensor fusion, analyzing the influence of motion on different modalities is crucial. In this work, a multimodal sensor setup integrated into an armchair is presented that combines capacitively coupled electrocardiography, reflective photoplethysmography, two high-frequency impedance sensors and two types of ballistocardiography sensors. To quantify motion artifacts, a motion protocol performed by healthy volunteers is recorded with a motion capture system, and reference sensors perform cardiorespiratory monitoring. The shape-based signal-to-noise ratio SNRS is introduced and used to quantify the effect on motion on different sensing modalities. Based on this analysis, an optimal combination of sensors and fusion methodology is developed and evaluated. Using the proposed approach, beat-to-beat heart-rate is estimated with a coverage of 99.5% and a mean absolute error of 7.9 ms on 425 min of data from seven volunteers in a proof-of-concept measurement scenario. PMID:29295594

  1. Motion Artifact Quantification and Sensor Fusion for Unobtrusive Health Monitoring.

    Science.gov (United States)

    Hoog Antink, Christoph; Schulz, Florian; Leonhardt, Steffen; Walter, Marian

    2017-12-25

    Sensors integrated into objects of everyday life potentially allow unobtrusive health monitoring at home. However, since the coupling of sensors and subject is not as well-defined as compared to a clinical setting, the signal quality is much more variable and can be disturbed significantly by motion artifacts. One way of tackling this challenge is the combined evaluation of multiple channels via sensor fusion. For robust and accurate sensor fusion, analyzing the influence of motion on different modalities is crucial. In this work, a multimodal sensor setup integrated into an armchair is presented that combines capacitively coupled electrocardiography, reflective photoplethysmography, two high-frequency impedance sensors and two types of ballistocardiography sensors. To quantify motion artifacts, a motion protocol performed by healthy volunteers is recorded with a motion capture system, and reference sensors perform cardiorespiratory monitoring. The shape-based signal-to-noise ratio SNR S is introduced and used to quantify the effect on motion on different sensing modalities. Based on this analysis, an optimal combination of sensors and fusion methodology is developed and evaluated. Using the proposed approach, beat-to-beat heart-rate is estimated with a coverage of 99.5% and a mean absolute error of 7.9 ms on 425 min of data from seven volunteers in a proof-of-concept measurement scenario.

  2. Projective Method for Generic Sensor Fusion Problem

    International Nuclear Information System (INIS)

    Rao, N.S.V.

    1999-01-01

    In a multiple sensor system, each sensor produces an output which is related to the desired feature according to a certain probability distribution. We propose a fuser that combines the sensor outputs to more accurately predict the desired feature. The fuser utilizes the lower envelope of regression curves of sensors to project the sensor with the least error at each point of the feature space. This fuser is optimal among all projective fusers and also satisfies the isolation property that ensures a performance at least as good as the best sensor. In the case the sensor distributions are not known, we show that a consistent estimator of this fuser can be computed entirely based on a training sample. Compared to linear fusers, the projective fusers provide a complementary performance. We propose two classes of metafusers that utilize both linear and projectives fusers to perform at least as good as the best sensor as well as the best fuser

  3. Proposed design criteria for a fusion facility electrical ground system

    International Nuclear Information System (INIS)

    Armellino, C.A.

    1983-01-01

    Ground grid design considerations for a nuclear fusion reactor facility are no different than any other facility in that the basis for design must be safety first and foremost. Unlike a conventional industrial facility the available fault energy comes not only from the utility source and in-house rotating machinery, but also from energy storage capacitor banks, collapsing magnetic fields and D.C. transmission lines. It is not inconceivable for a fault condition occurrence where all available energy can be discharged. The ground grid must adequately shunt this sudden energy discharge in a way that personnel will not be exposed by step and/or touch to hazardous energy levels that are in excess of maximum tolerable levels for humans. Fault energy discharge rate is a function of the ground grid surge impedance characteristic. Closed loop paths must be avoided in the ground grid design so that during energy discharge no stray magnetic fields or large voltage potentials between remote points can be created by circulating currents. Single point connection of equipment to the ground grid will afford protection to personnel and sensitive equipment by reducing the probability of circulating currents. The overall ground grid system design is best illustrated as a wagon wheel concept with the fusion machine at the center. Radial branches or spokes reach out to the perimeter limits designated by step-and-touch high risk areas based on soil resistivity criteria considerations. Conventional methods for the design of a ground grid with all of its radial branches are still pertinent. The center of the grid could include a deep well single ground rod element the length of which is at least equivalent to the radius of an imaginary sphere that enshrouds the immediate machine area. Special facilities such as screen rooms or other shielded areas are part of the ground grid system by way of connection to radial branches

  4. Multi-sensor fusion with interacting multiple model filter for improved aircraft position accuracy.

    Science.gov (United States)

    Cho, Taehwan; Lee, Changho; Choi, Sangbang

    2013-03-27

    The International Civil Aviation Organization (ICAO) has decided to adopt Communications, Navigation, and Surveillance/Air Traffic Management (CNS/ATM) as the 21st century standard for navigation. Accordingly, ICAO members have provided an impetus to develop related technology and build sufficient infrastructure. For aviation surveillance with CNS/ATM, Ground-Based Augmentation System (GBAS), Automatic Dependent Surveillance-Broadcast (ADS-B), multilateration (MLAT) and wide-area multilateration (WAM) systems are being established. These sensors can track aircraft positions more accurately than existing radar and can compensate for the blind spots in aircraft surveillance. In this paper, we applied a novel sensor fusion method with Interacting Multiple Model (IMM) filter to GBAS, ADS-B, MLAT, and WAM data in order to improve the reliability of the aircraft position. Results of performance analysis show that the position accuracy is improved by the proposed sensor fusion method with the IMM filter.

  5. Decentralized Sensor Fusion for Ubiquitous Networking Robotics in Urban Areas

    Science.gov (United States)

    Sanfeliu, Alberto; Andrade-Cetto, Juan; Barbosa, Marco; Bowden, Richard; Capitán, Jesús; Corominas, Andreu; Gilbert, Andrew; Illingworth, John; Merino, Luis; Mirats, Josep M.; Moreno, Plínio; Ollero, Aníbal; Sequeira, João; Spaan, Matthijs T.J.

    2010-01-01

    In this article we explain the architecture for the environment and sensors that has been built for the European project URUS (Ubiquitous Networking Robotics in Urban Sites), a project whose objective is to develop an adaptable network robot architecture for cooperation between network robots and human beings and/or the environment in urban areas. The project goal is to deploy a team of robots in an urban area to give a set of services to a user community. This paper addresses the sensor architecture devised for URUS and the type of robots and sensors used, including environment sensors and sensors onboard the robots. Furthermore, we also explain how sensor fusion takes place to achieve urban outdoor execution of robotic services. Finally some results of the project related to the sensor network are highlighted. PMID:22294927

  6. Decentralized Sensor Fusion for Ubiquitous Networking Robotics in Urban Areas

    Directory of Open Access Journals (Sweden)

    Aníbal Ollero

    2010-03-01

    Full Text Available In this article we explain the architecture for the environment and sensors that has been built for the European project URUS (Ubiquitous Networking Robotics in Urban Sites, a project whose objective is to develop an adaptable network robot architecture for cooperation between network robots and human beings and/or the environment in urban areas. The project goal is to deploy a team of robots in an urban area to give a set of services to a user community. This paper addresses the sensor architecture devised for URUS and the type of robots and sensors used, including environment sensors and sensors onboard the robots. Furthermore, we also explain how sensor fusion takes place to achieve urban outdoor execution of robotic services. Finally some results of the project related to the sensor network are highlighted.

  7. A hierarchical structure approach to MultiSensor Information Fusion

    Energy Technology Data Exchange (ETDEWEB)

    Maren, A.J. (Tennessee Univ., Tullahoma, TN (United States). Space Inst.); Pap, R.M.; Harston, C.T. (Accurate Automation Corp., Chattanooga, TN (United States))

    1989-01-01

    A major problem with image-based MultiSensor Information Fusion (MSIF) is establishing the level of processing at which information should be fused. Current methodologies, whether based on fusion at the pixel, segment/feature, or symbolic levels, are each inadequate for robust MSIF. Pixel-level fusion has problems with coregistration of the images or data. Attempts to fuse information using the features of segmented images or data relies an a presumed similarity between the segmentation characteristics of each image or data stream. Symbolic-level fusion requires too much advance processing to be useful, as we have seen in automatic target recognition tasks. Image-based MSIF systems need to operate in real-time, must perform fusion using a variety of sensor types, and should be effective across a wide range of operating conditions or deployment environments. We address this problem through developing a new representation level which facilitates matching and information fusion. The Hierarchical Scene Structure (HSS) representation, created using a multilayer, cooperative/competitive neural network, meets this need. The MSS is intermediate between a pixel-based representation and a scene interpretation representation, and represents the perceptual organization of an image. Fused HSSs will incorporate information from multiple sensors. Their knowledge-rich structure aids top-down scene interpretation via both model matching and knowledge-based,region interpretation.

  8. A hierarchical structure approach to MultiSensor Information Fusion

    Energy Technology Data Exchange (ETDEWEB)

    Maren, A.J. [Tennessee Univ., Tullahoma, TN (United States). Space Inst.; Pap, R.M.; Harston, C.T. [Accurate Automation Corp., Chattanooga, TN (United States)

    1989-12-31

    A major problem with image-based MultiSensor Information Fusion (MSIF) is establishing the level of processing at which information should be fused. Current methodologies, whether based on fusion at the pixel, segment/feature, or symbolic levels, are each inadequate for robust MSIF. Pixel-level fusion has problems with coregistration of the images or data. Attempts to fuse information using the features of segmented images or data relies an a presumed similarity between the segmentation characteristics of each image or data stream. Symbolic-level fusion requires too much advance processing to be useful, as we have seen in automatic target recognition tasks. Image-based MSIF systems need to operate in real-time, must perform fusion using a variety of sensor types, and should be effective across a wide range of operating conditions or deployment environments. We address this problem through developing a new representation level which facilitates matching and information fusion. The Hierarchical Scene Structure (HSS) representation, created using a multilayer, cooperative/competitive neural network, meets this need. The MSS is intermediate between a pixel-based representation and a scene interpretation representation, and represents the perceptual organization of an image. Fused HSSs will incorporate information from multiple sensors. Their knowledge-rich structure aids top-down scene interpretation via both model matching and knowledge-based,region interpretation.

  9. Multi-Level Sensor Fusion Algorithm Approach for BMD Interceptor Applications

    National Research Council Canada - National Science Library

    Allen, Doug

    1998-01-01

    ... through fabrication and testing of advanced sensor hardware concepts and advanced sensor fusion algorithms. Advanced sensor concepts include onboard LADAR in conjunction with a multi-color passive IR sensor...

  10. Sensor Fusion-based Event Detection in Wireless Sensor Networks

    NARCIS (Netherlands)

    Bahrepour, M.; Meratnia, Nirvana; Havinga, Paul J.M.

    2009-01-01

    Recently, Wireless Sensor Networks (WSN) community has witnessed an application focus shift. Although, monitoring was the initial application of wireless sensor networks, in-network data processing and (near) real-time actuation capability have made wireless sensor networks suitable candidate for

  11. Fuzzy-Based Sensor Fusion for Cognitive Radio-Based Vehicular Ad Hoc and Sensor Networks

    Directory of Open Access Journals (Sweden)

    Mohammad Jalil Piran

    2015-01-01

    Full Text Available In wireless sensor networks, sensor fusion is employed to integrate the acquired data from diverse sensors to provide a unified interpretation. The best and most salient advantage of sensor fusion is to obtain high-level information in both statistical and definitive aspects, which cannot be attained by a single sensor. In this paper, we propose a novel sensor fusion technique based on fuzzy theory for our earlier proposed Cognitive Radio-based Vehicular Ad Hoc and Sensor Networks (CR-VASNET. In the proposed technique, we considered four input sensor readings (antecedents and one output (consequent. The employed mobile nodes in CR-VASNET are supposed to be equipped with diverse sensors, which cater to our antecedent variables, for example, The Jerk, Collision Intensity, and Temperature and Inclination Degree. Crash_Severity is considered as the consequent variable. The processing and fusion of the diverse sensory signals are carried out by fuzzy logic scenario. Accuracy and reliability of the proposed protocol, demonstrated by the simulation results, introduce it as an applicable system to be employed to reduce the causalities rate of the vehicles’ crashes.

  12. Conflict management based on belief function entropy in sensor fusion.

    Science.gov (United States)

    Yuan, Kaijuan; Xiao, Fuyuan; Fei, Liguo; Kang, Bingyi; Deng, Yong

    2016-01-01

    Wireless sensor network plays an important role in intelligent navigation. It incorporates a group of sensors to overcome the limitation of single detection system. Dempster-Shafer evidence theory can combine the sensor data of the wireless sensor network by data fusion, which contributes to the improvement of accuracy and reliability of the detection system. However, due to different sources of sensors, there may be conflict among the sensor data under uncertain environment. Thus, this paper proposes a new method combining Deng entropy and evidence distance to address the issue. First, Deng entropy is adopted to measure the uncertain information. Then, evidence distance is applied to measure the conflict degree. The new method can cope with conflict effectually and improve the accuracy and reliability of the detection system. An example is illustrated to show the efficiency of the new method and the result is compared with that of the existing methods.

  13. Kalman Filter Sensor Fusion for Mecanum Wheeled Automated Guided Vehicle Localization

    Directory of Open Access Journals (Sweden)

    Sang Won Yoon

    2015-01-01

    Full Text Available The Mecanum automated guided vehicle (AGV, which can move in any direction by using a special wheel structure with a LIM-wheel and a diagonally positioned roller, holds considerable promise for the field of industrial electronics. A conventional method for Mecanum AGV localization has certain limitations, such as slip phenomena, because there are variations in the surface of the road and ground friction. Therefore, precise localization is a very important issue for the inevitable slip phenomenon situation. So a sensor fusion technique is developed to cope with this drawback by using the Kalman filter. ENCODER and StarGazer were used for sensor fusion. StarGazer is a position sensor for an image recognition device and always generates some errors due to the limitations of the image recognition device. ENCODER has also errors accumulating over time. On the other hand, there are no moving errors. In this study, we developed a Mecanum AGV prototype system and showed by simulation that we can eliminate the disadvantages of each sensor. We obtained the precise localization of the Mecanum AGV in a slip phenomenon situation via sensor fusion using a Kalman filter.

  14. Sensor fusion for active vibration isolation in precision equipment

    NARCIS (Netherlands)

    Tjepkema, D.; van Dijk, Johannes; Soemers, Herman

    2012-01-01

    Sensor fusion is a promising control strategy to improve the performance of active vibration isolation systems that are used in precision equipment. Normally, those vibration isolation systems are only capable of realizing a low transmissibility. Additional objectives are to increase the damping

  15. Sensor Fusion and Model Verification for a Mobile Robot

    DEFF Research Database (Denmark)

    Bisgaard, Morten; Vinther, Dennis; Østergaard, Kasper Zinck

    2005-01-01

    This paper presents the results of modeling, sensor fusion and model verification for a four-wheel driven, four-wheel steered mobile robot moving in outdoor terrain. The model derived for the robot describes the actuator and wheel dynamics and the vehicle kinematics, and includes friction terms...

  16. Sensor fusion-based map building for mobile robot exploration

    International Nuclear Information System (INIS)

    Ribo, M.

    2000-01-01

    To carry out exploration tasks in unknown or partially unknown environments, a mobile robot needs to acquire and maintain models of its environment. In doing so, several sensors of same nature and/or heterogeneous sensor configurations may be used by the robot to achieve reliable performances. However, this in turn poses the problem of sensor fusion-based map building: How to interpret, combine and integrate sensory information in order to build a proper representation of the environment. Specifically, the goal of this thesis is to probe integration algorithms for Occupancy Grid (OG) based map building using odometry, ultrasonic rangefinders, and stereo vision. Three different uncertainty calculi are presented here which are used for sensor fusion-based map building purposes. They are based on probability theory, Dempster-Shafer theory of evidence, and fuzzy set theory. Besides, two different sensor models are depicted which are used to translate sensing data into range information. Experimental examples of OGs built from real data recorded by two robots in office-like environment are presented. They show the feasibility of the proposed approach for building both sonar and visual based OGs. A comparison among the presented uncertainty calculi is performed in a sonar-based framework. Finally, the fusion of both sonar and visual information based of the fuzzy set theory is depicted. (author)

  17. Fusion of intraoperative force sensoring, surface reconstruction and biomechanical modeling

    Science.gov (United States)

    Röhl, S.; Bodenstedt, S.; Küderle, C.; Suwelack, S.; Kenngott, H.; Müller-Stich, B. P.; Dillmann, R.; Speidel, S.

    2012-02-01

    Minimally invasive surgery is medically complex and can heavily benefit from computer assistance. One way to help the surgeon is to integrate preoperative planning data into the surgical workflow. This information can be represented as a customized preoperative model of the surgical site. To use it intraoperatively, it has to be updated during the intervention due to the constantly changing environment. Hence, intraoperative sensor data has to be acquired and registered with the preoperative model. Haptic information which could complement the visual sensor data is still not established. In addition, biomechanical modeling of the surgical site can help in reflecting the changes which cannot be captured by intraoperative sensors. We present a setting where a force sensor is integrated into a laparoscopic instrument. In a test scenario using a silicone liver phantom, we register the measured forces with a reconstructed surface model from stereo endoscopic images and a finite element model. The endoscope, the instrument and the liver phantom are tracked with a Polaris optical tracking system. By fusing this information, we can transfer the deformation onto the finite element model. The purpose of this setting is to demonstrate the principles needed and the methods developed for intraoperative sensor data fusion. One emphasis lies on the calibration of the force sensor with the instrument and first experiments with soft tissue. We also present our solution and first results concerning the integration of the force sensor as well as accuracy to the fusion of force measurements, surface reconstruction and biomechanical modeling.

  18. Resource-Aware Data Fusion Algorithms for Wireless Sensor Networks

    CERN Document Server

    Abdelgawad, Ahmed

    2012-01-01

    This book introduces resource-aware data fusion algorithms to gather and combine data from multiple sources (e.g., sensors) in order to achieve inferences.  These techniques can be used in centralized and distributed systems to overcome sensor failure, technological limitation, and spatial and temporal coverage problems. The algorithms described in this book are evaluated with simulation and experimental results to show they will maintain data integrity and make data useful and informative.   Describes techniques to overcome real problems posed by wireless sensor networks deployed in circumstances that might interfere with measurements provided, such as strong variations of pressure, temperature, radiation, and electromagnetic noise; Uses simulation and experimental results to evaluate algorithms presented and includes real test-bed; Includes case study implementing data fusion algorithms on a remote monitoring framework for sand production in oil pipelines.

  19. Sensor Fusion for Nuclear Proliferation Activity Monitoring

    Energy Technology Data Exchange (ETDEWEB)

    Adel Ghanem, Ph D

    2007-03-30

    The objective of Phase 1 of this STTR project is to demonstrate a Proof-of-Concept (PoC) of the Geo-Rad system that integrates a location-aware SmartTag (made by ZonTrak) and a radiation detector (developed by LLNL). It also includes the ability to transmit the collected radiation data and location information to the ZonTrak server (ZonService). The collected data is further transmitted to a central server at LLNL (the Fusion Server) to be processed in conjunction with overhead imagery to generate location estimates of nuclear proliferation and radiation sources.

  20. APPLICATION OF SENSOR FUSION TO IMPROVE UAV IMAGE CLASSIFICATION

    Directory of Open Access Journals (Sweden)

    S. Jabari

    2017-08-01

    Full Text Available Image classification is one of the most important tasks of remote sensing projects including the ones that are based on using UAV images. Improving the quality of UAV images directly affects the classification results and can save a huge amount of time and effort in this area. In this study, we show that sensor fusion can improve image quality which results in increasing the accuracy of image classification. Here, we tested two sensor fusion configurations by using a Panchromatic (Pan camera along with either a colour camera or a four-band multi-spectral (MS camera. We use the Pan camera to benefit from its higher sensitivity and the colour or MS camera to benefit from its spectral properties. The resulting images are then compared to the ones acquired by a high resolution single Bayer-pattern colour camera (here referred to as HRC. We assessed the quality of the output images by performing image classification tests. The outputs prove that the proposed sensor fusion configurations can achieve higher accuracies compared to the images of the single Bayer-pattern colour camera. Therefore, incorporating a Pan camera on-board in the UAV missions and performing image fusion can help achieving higher quality images and accordingly higher accuracy classification results.

  1. Application of Sensor Fusion to Improve Uav Image Classification

    Science.gov (United States)

    Jabari, S.; Fathollahi, F.; Zhang, Y.

    2017-08-01

    Image classification is one of the most important tasks of remote sensing projects including the ones that are based on using UAV images. Improving the quality of UAV images directly affects the classification results and can save a huge amount of time and effort in this area. In this study, we show that sensor fusion can improve image quality which results in increasing the accuracy of image classification. Here, we tested two sensor fusion configurations by using a Panchromatic (Pan) camera along with either a colour camera or a four-band multi-spectral (MS) camera. We use the Pan camera to benefit from its higher sensitivity and the colour or MS camera to benefit from its spectral properties. The resulting images are then compared to the ones acquired by a high resolution single Bayer-pattern colour camera (here referred to as HRC). We assessed the quality of the output images by performing image classification tests. The outputs prove that the proposed sensor fusion configurations can achieve higher accuracies compared to the images of the single Bayer-pattern colour camera. Therefore, incorporating a Pan camera on-board in the UAV missions and performing image fusion can help achieving higher quality images and accordingly higher accuracy classification results.

  2. Data fusion for target tracking and classification with wireless sensor network

    Science.gov (United States)

    Pannetier, Benjamin; Doumerc, Robin; Moras, Julien; Dezert, Jean; Canevet, Loic

    2016-10-01

    In this paper, we address the problem of multiple ground target tracking and classification with information obtained from a unattended wireless sensor network. A multiple target tracking (MTT) algorithm, taking into account road and vegetation information, is proposed based on a centralized architecture. One of the key issue is how to adapt classical MTT approach to satisfy embedded processing. Based on track statistics, the classification algorithm uses estimated location, velocity and acceleration to help to classify targets. The algorithms enables tracking human and vehicles driving both on and off road. We integrate road or trail width and vegetation cover, as constraints in target motion models to improve performance of tracking under constraint with classification fusion. Our algorithm also presents different dynamic models, to palliate the maneuvers of targets. The tracking and classification algorithms are integrated into an operational platform (the fusion node). In order to handle realistic ground target tracking scenarios, we use an autonomous smart computer deposited in the surveillance area. After the calibration step of the heterogeneous sensor network, our system is able to handle real data from a wireless ground sensor network. The performance of system is evaluated in a real exercise for intelligence operation ("hunter hunt" scenario).

  3. Sensor-fusion-based biometric identity verification

    International Nuclear Information System (INIS)

    Carlson, J.J.; Bouchard, A.M.; Osbourn, G.C.; Martinez, R.F.; Bartholomew, J.W.; Jordan, J.B.; Flachs, G.M.; Bao, Z.; Zhu, L.

    1998-02-01

    Future generation automated human biometric identification and verification will require multiple features/sensors together with internal and external information sources to achieve high performance, accuracy, and reliability in uncontrolled environments. The primary objective of the proposed research is to develop a theoretical and practical basis for identifying and verifying people using standoff biometric features that can be obtained with minimal inconvenience during the verification process. The basic problem involves selecting sensors and discovering features that provide sufficient information to reliably verify a person's identity under the uncertainties caused by measurement errors and tactics of uncooperative subjects. A system was developed for discovering hand, face, ear, and voice features and fusing them to verify the identity of people. The system obtains its robustness and reliability by fusing many coarse and easily measured features into a near minimal probability of error decision algorithm

  4. A fiber Bragg grating acceleration sensor for ground surveillance

    Science.gov (United States)

    Jiang, Shaodong; Zhang, Faxiang; Lv, Jingsheng; Ni, Jiasheng; Wang, Chang

    2017-10-01

    Ground surveillance system is a kind of intelligent monitoring equipment for detecting and tracking the ground target. This paper presents a fiber Bragg grating (FBG) acceleration sensor for ground surveillance, which has the characteristics of no power supply, anti-electromagnetic interference, easy large-scale networking, and small size. Which make it able to achieve the advantage of the ground surveillance system while avoiding the shortcoming of the electric sensing. The sensor has a double cantilever beam structure with a sensitivity of 1000 pm/g. Field experiment has been carried out on a flood beach to examine the sensor performance. The result shows that the detection distance on the walking of personnel reaches 70m, and the detection distance on the ordinary motor vehicle reaches 200m. The performance of the FBG sensor can satisfy the actual needs of the ground surveillance system.

  5. Distributed Sensor Fusion for Scalar Field Mapping Using Mobile Sensor Networks.

    Science.gov (United States)

    La, Hung Manh; Sheng, Weihua

    2013-04-01

    In this paper, autonomous mobile sensor networks are deployed to measure a scalar field and build its map. We develop a novel method for multiple mobile sensor nodes to build this map using noisy sensor measurements. Our method consists of two parts. First, we develop a distributed sensor fusion algorithm by integrating two different distributed consensus filters to achieve cooperative sensing among sensor nodes. This fusion algorithm has two phases. In the first phase, the weighted average consensus filter is developed, which allows each sensor node to find an estimate of the value of the scalar field at each time step. In the second phase, the average consensus filter is used to allow each sensor node to find a confidence of the estimate at each time step. The final estimate of the value of the scalar field is iteratively updated during the movement of the mobile sensors via weighted average. Second, we develop the distributed flocking-control algorithm to drive the mobile sensors to form a network and track the virtual leader moving along the field when only a small subset of the mobile sensors know the information of the leader. Experimental results are provided to demonstrate our proposed algorithms.

  6. Noncontact Sleep Study by Multi-Modal Sensor Fusion

    Directory of Open Access Journals (Sweden)

    Ku-young Chung

    2017-07-01

    Full Text Available Polysomnography (PSG is considered as the gold standard for determining sleep stages, but due to the obtrusiveness of its sensor attachments, sleep stage classification algorithms using noninvasive sensors have been developed throughout the years. However, the previous studies have not yet been proven reliable. In addition, most of the products are designed for healthy customers rather than for patients with sleep disorder. We present a novel approach to classify sleep stages via low cost and noncontact multi-modal sensor fusion, which extracts sleep-related vital signals from radar signals and a sound-based context-awareness technique. This work is uniquely designed based on the PSG data of sleep disorder patients, which were received and certified by professionals at Hanyang University Hospital. The proposed algorithm further incorporates medical/statistical knowledge to determine personal-adjusted thresholds and devise post-processing. The efficiency of the proposed algorithm is highlighted by contrasting sleep stage classification performance between single sensor and sensor-fusion algorithms. To validate the possibility of commercializing this work, the classification results of this algorithm were compared with the commercialized sleep monitoring device, ResMed S+. The proposed algorithm was investigated with random patients following PSG examination, and results show a promising novel approach for determining sleep stages in a low cost and unobtrusive manner.

  7. Coresident sensor fusion and compression using the wavelet transform

    Energy Technology Data Exchange (ETDEWEB)

    Yocky, D.A.

    1996-03-11

    Imagery from coresident sensor platforms, such as unmanned aerial vehicles, can be combined using, multiresolution decomposition of the sensor images by means of the two-dimensional wavelet transform. The wavelet approach uses the combination of spatial/spectral information at multiple scales to create a fused image. This can be done in both an ad hoc or model-based approach. We compare results from commercial ``fusion`` software and the ad hoc, wavelet approach. Results show the wavelet approach outperforms the commercial algorithms and also supports efficient compression of the fused image.

  8. An evidential sensor fusion method in fault diagnosis

    Directory of Open Access Journals (Sweden)

    Wen Jiang

    2016-03-01

    Full Text Available Dempster–Shafer evidence theory is widely used in information fusion. However, it may lead to an unreasonable result when dealing with high conflict evidence. In order to solve this problem, we put forward a new method based on the credibility of evidence. First, a novel belief entropy, Deng entropy, is applied to measure the information volume of the evidence and then the discounting coefficients of each evidence are obtained. Finally, weighted averaging the evidence in the system, the Dempster combination rule was used to realize information fusion. A weighted averaging combination role is presented for multi-sensor data fusion in fault diagnosis. It seems more reasonable than before using the new belief function to determine the weight. A numerical example is given to illustrate that the proposed rule is more effective to perform fault diagnosis than classical evidence theory in fusing multi-symptom domains.

  9. Distributed cluster management techniques for unattended ground sensor networks

    Science.gov (United States)

    Essawy, Magdi A.; Stelzig, Chad A.; Bevington, James E.; Minor, Sharon

    2005-05-01

    Smart Sensor Networks are becoming important target detection and tracking tools. The challenging problems in such networks include the sensor fusion, data management and communication schemes. This work discusses techniques used to distribute sensor management and multi-target tracking responsibilities across an ad hoc, self-healing cluster of sensor nodes. Although miniaturized computing resources possess the ability to host complex tracking and data fusion algorithms, there still exist inherent bandwidth constraints on the RF channel. Therefore, special attention is placed on the reduction of node-to-node communications within the cluster by minimizing unsolicited messaging, and distributing the sensor fusion and tracking tasks onto local portions of the network. Several challenging problems are addressed in this work including track initialization and conflict resolution, track ownership handling, and communication control optimization. Emphasis is also placed on increasing the overall robustness of the sensor cluster through independent decision capabilities on all sensor nodes. Track initiation is performed using collaborative sensing within a neighborhood of sensor nodes, allowing each node to independently determine if initial track ownership should be assumed. This autonomous track initiation prevents the formation of duplicate tracks while eliminating the need for a central "management" node to assign tracking responsibilities. Track update is performed as an ownership node requests sensor reports from neighboring nodes based on track error covariance and the neighboring nodes geo-positional location. Track ownership is periodically recomputed using propagated track states to determine which sensing node provides the desired coverage characteristics. High fidelity multi-target simulation results are presented, indicating the distribution of sensor management and tracking capabilities to not only reduce communication bandwidth consumption, but to also

  10. Security of nuclear materials using fusion multi sensor wavelett

    International Nuclear Information System (INIS)

    Djoko Hari Nugroho

    2010-01-01

    Security of a nuclear material in an installation is determined by how far the installation is to assure that nuclear material remains at a predetermined location. This paper observed a preliminary design on nuclear material tracking system in the installation for decision making support based on multi sensor fusion that is reliable and accurate to ensure that the nuclear material remains inside the control area. Capability on decision making in the Management Information System is represented by an understanding of perception in the third level of abstraction. The second level will be achieved with the support of image analysis and organizing data. The first level of abstraction is constructed by merger between several CCD camera sensors distributed in a building in a data fusion representation. Data fusion is processed based on Wavelett approach. Simulation utilizing Matlab programming shows that Wavelett fuses multi information from sensors as well. Hope that when the nuclear material out of control regions which have been predetermined before, there will arise a warning alarm and a message in the Management Information System display. Thus the nuclear material movement time event can be obtained and tracked as well. (author)

  11. Unmanned Aerial System (UAS)-based phenotyping of soybean using multi-sensor data fusion and extreme learning machine

    Science.gov (United States)

    Maimaitijiang, Maitiniyazi; Ghulam, Abduwasit; Sidike, Paheding; Hartling, Sean; Maimaitiyiming, Matthew; Peterson, Kyle; Shavers, Ethan; Fishman, Jack; Peterson, Jim; Kadam, Suhas; Burken, Joel; Fritschi, Felix

    2017-12-01

    Estimating crop biophysical and biochemical parameters with high accuracy at low-cost is imperative for high-throughput phenotyping in precision agriculture. Although fusion of data from multiple sensors is a common application in remote sensing, less is known on the contribution of low-cost RGB, multispectral and thermal sensors to rapid crop phenotyping. This is due to the fact that (1) simultaneous collection of multi-sensor data using satellites are rare and (2) multi-sensor data collected during a single flight have not been accessible until recent developments in Unmanned Aerial Systems (UASs) and UAS-friendly sensors that allow efficient information fusion. The objective of this study was to evaluate the power of high spatial resolution RGB, multispectral and thermal data fusion to estimate soybean (Glycine max) biochemical parameters including chlorophyll content and nitrogen concentration, and biophysical parameters including Leaf Area Index (LAI), above ground fresh and dry biomass. Multiple low-cost sensors integrated on UASs were used to collect RGB, multispectral, and thermal images throughout the growing season at a site established near Columbia, Missouri, USA. From these images, vegetation indices were extracted, a Crop Surface Model (CSM) was advanced, and a model to extract the vegetation fraction was developed. Then, spectral indices/features were combined to model and predict crop biophysical and biochemical parameters using Partial Least Squares Regression (PLSR), Support Vector Regression (SVR), and Extreme Learning Machine based Regression (ELR) techniques. Results showed that: (1) For biochemical variable estimation, multispectral and thermal data fusion provided the best estimate for nitrogen concentration and chlorophyll (Chl) a content (RMSE of 9.9% and 17.1%, respectively) and RGB color information based indices and multispectral data fusion exhibited the largest RMSE 22.6%; the highest accuracy for Chl a + b content estimation was

  12. Inertial Sensor Error Reduction through Calibration and Sensor Fusion

    Directory of Open Access Journals (Sweden)

    Stefan Lambrecht

    2016-02-01

    Full Text Available This paper presents the comparison between cooperative and local Kalman Filters (KF for estimating the absolute segment angle, under two calibration conditions. A simplified calibration, that can be replicated in most laboratories; and a complex calibration, similar to that applied by commercial vendors. The cooperative filters use information from either all inertial sensors attached to the body, Matricial KF; or use information from the inertial sensors and the potentiometers of an exoskeleton, Markovian KF. A one minute walking trial of a subject walking with a 6-DoF exoskeleton was used to assess the absolute segment angle of the trunk, thigh, shank, and foot. The results indicate that regardless of the segment and filter applied, the more complex calibration always results in a significantly better performance compared to the simplified calibration. The interaction between filter and calibration suggests that when the quality of the calibration is unknown the Markovian KF is recommended. Applying the complex calibration, the Matricial and Markovian KF perform similarly, with average RMSE below 1.22 degrees. Cooperative KFs perform better or at least equally good as Local KF, we therefore recommend to use cooperative KFs instead of local KFs for control or analysis of walking.

  13. Towards an operational sensor-fusion system for anti-personnel landmine detection

    NARCIS (Netherlands)

    Cremer, F.; Schutte, K.; Schavemaker, J.G.M.; Breejen, E. den

    2000-01-01

    To acquire detection performance required for an operational system for the detection of anti-personnel landmines, it is necessary to use multiple sensors and sensor-fusion techniques. This paper describes five decision-level sensor-fusion techniques and their common optimisation method. The

  14. Dempster Shafer Sensor Fusion for Autonomously Driving Vehicles : Association Free Tracking of Dynamic Objects

    OpenAIRE

    Högger, Andreas

    2016-01-01

    Autonomous driving vehicles introduce challenging research areas combining differ-ent disciplines. One challenge is the detection of obstacles with different sensors and the combination of information to generate a comprehensive representation of the environment, which can be used for path planning and decision making.The sensor fusion is demonstrated using two Velodyne multi beam laser scanners, but it is possible to extend the proposed sensor fusion framework for different sensor types. Sensor...

  15. CONTEXT-CAPTURE MULTI-VALUED DECISION FUSION WITH FAULT TOLERANT CAPABILITY FOR WIRELESS SENSOR NETWORKS

    OpenAIRE

    Jun Wu; Shigeru Shimamoto

    2011-01-01

    Wireless sensor networks (WSNs) are usually utilized to perform decision fusion of event detection. Current decision fusion schemes are based on binary valued decision and do not consider bursty contextcapture. However, bursty context and multi-valued data are important characteristics of WSNs. One on hand, the local decisions from sensors usually have bursty and contextual characteristics. Fusion center must capture the bursty context information from the sensors. On the other hand, in pract...

  16. Infrared sensors and sensor fusion; Proceedings of the Meeting, Orlando, FL, May 19-21, 1987

    International Nuclear Information System (INIS)

    Buser, R.G.; Warren, F.B.

    1987-01-01

    The present conference discusses topics in the fields of IR sensor multifunctional design; image modeling, simulation, and detection; IR sensor configurations and components; thermal sensor arrays; silicide-based IR sensors; and IR focal plane array utilization. Attention is given to the fusion of lidar and FLIR for target segmentation and enhancement, the synergetic integration of thermal and visual images for computer vision, the 'Falcon Eye' FLIR system, multifunctional electrooptics and multiaperture sensors for precision-guided munitions, and AI approaches to data integration. Also discussed are the comparative performance of Ir silicide and Pt silicide photodiodes, high fill-factor silicide monolithic arrays, and the characterization of noise in staring IR focal plane arrays

  17. Discrete Kalman Filter based Sensor Fusion for Robust Accessibility Interfaces

    International Nuclear Information System (INIS)

    Ghersi, I; Miralles, M T; Mariño, M

    2016-01-01

    Human-machine interfaces have evolved, benefiting from the growing access to devices with superior, embedded signal-processing capabilities, as well as through new sensors that allow the estimation of movements and gestures, resulting in increasingly intuitive interfaces. In this context, sensor fusion for the estimation of the spatial orientation of body segments allows to achieve more robust solutions, overcoming specific disadvantages derived from the use of isolated sensors, such as the sensitivity of magnetic-field sensors to external influences, when used in uncontrolled environments. In this work, a method for the combination of image-processing data and angular-velocity registers from a 3D MEMS gyroscope, through a Discrete-time Kalman Filter, is proposed and deployed as an alternate user interface for mobile devices, in which an on-screen pointer is controlled with head movements. Results concerning general performance of the method are presented, as well as a comparative analysis, under a dedicated test application, with results from a previous version of this system, in which the relative-orientation information was acquired directly from MEMS sensors (3D magnetometer-accelerometer). These results show an improved response for this new version of the pointer, both in terms of precision and response time, while keeping many of the benefits that were highlighted for its predecessor, giving place to a complementary method for signal acquisition that can be used as an alternative-input device, as well as for accessibility solutions. (paper)

  18. An alternative sensor fusion method for object orientation using low-cost MEMS inertial sensors

    Science.gov (United States)

    Bouffard, Joshua L.

    This thesis develops an alternative sensor fusion approach for object orientation using low-cost MEMS inertial sensors. The alternative approach focuses on the unique challenges of small UAVs. Such challenges include the vibrational induced noise onto the accelerometer and bias offset errors of the rate gyroscope. To overcome these challenges, a sensor fusion algorithm combines the measured data from the accelerometer and rate gyroscope to achieve a single output free from vibrational noise and bias offset errors. One of the most prevalent sensor fusion algorithms used for orientation estimation is the Extended Kalman filter (EKF). The EKF filter performs the fusion process by first creating the process model using the nonlinear equations of motion and then establishing a measurement model. With the process and measurement models established, the filter operates by propagating the mean and covariance of the states through time. The success of EKF relies on the ability to establish a representative process and measurement model of the system. In most applications, the EKF measurement model utilizes the accelerometer and GPS-derived accelerations to determine an estimate of the orientation. However, if the GPS-derived accelerations are not available then the measurement model becomes less reliable when subjected to harsh vibrational environments. This situation led to the alternative approach, which focuses on the correlation between the rate gyroscope and accelerometer-derived angle. The correlation between the two sensors then determines how much the algorithm will use one sensor over the other. The result is a measurement that does not suffer from the vibrational noise or from bias offset errors.

  19. The pH sensor for flavivirus membrane fusion

    OpenAIRE

    Harrison, Stephen C.

    2008-01-01

    Viruses that infect cells by uptake through endosomes have generally evolved to ?sense? the local pH as part of the mechanism by which they penetrate into the cytosol. Even for the very well studied fusion proteins of enveloped viruses, identification of the specific pH sensor has been a challenge, one that has now been met successfully, for flaviviruses, by Fritz et al. (Fritz, R., K. Stiasny, and F.X. Heinz. 2008. J. Cell Biol. 183:353?361) in this issue. Thorough mutational analysis of con...

  20. Fault-tolerant Sensor Fusion for Marine Navigation

    DEFF Research Database (Denmark)

    Blanke, Mogens

    2006-01-01

    Reliability of navigation data are critical for steering and manoeuvring control, and in particular so at high speed or in critical phases of a mission. Should faults occur, faulty instruments need be autonomously isolated and faulty information discarded. This paper designs a navigation solution...... where essential navigation information is provided even with multiple faults in instrumentation. The paper proposes a provable correct implementation through auto-generated state-event logics in a supervisory part of the algorithms. Test results from naval vessels document the performance and shows...... events where the fault-tolerant sensor fusion provided uninterrupted navigation data despite temporal instrument defects...

  1. Relative Vessel Motion Tracking using Sensor Fusion, Aruco Markers, and MRU Sensors

    Directory of Open Access Journals (Sweden)

    Sondre Sanden Tordal

    2017-04-01

    Full Text Available This paper presents a novel approach for estimating the relative motion between two moving offshore vessels. The method is based on a sensor fusion algorithm including a vision system and two motion reference units (MRUs. The vision system makes use of the open-source computer vision library OpenCV and a cube with Aruco markers placed onto each of the cube sides. The Extended Quaternion Kalman Filter (EQKF is used for bad pose rejection for the vision system. The presented sensor fusion algorithm is based on the Indirect Feedforward Kalman Filter for error estimation. The system is self-calibrating in the sense that the Aruco cube can be placed in an arbitrary location on the secondary vessel. Experimental 6-DOF results demonstrate the accuracy and efficiency of the proposed sensor fusion method compared with the internal joint sensors of two Stewart platforms and the industrial robot. The standard deviation error was found to be 31mm or better when the Arcuo cube was placed at three different locations.

  2. Context-Aided Sensor Fusion for Enhanced Urban Navigation

    Directory of Open Access Journals (Sweden)

    Enrique David Martí

    2012-12-01

    Full Text Available  The deployment of Intelligent Vehicles in urban environments requires reliable estimation of positioning for urban navigation. The inherent complexity of this kind of environments fosters the development of novel systems which should provide reliable and precise solutions to the vehicle. This article details an advanced GNSS/IMU fusion system based on a context-aided Unscented Kalman filter for navigation in urban conditions. The constrained non-linear filter is here conditioned by a contextual knowledge module which reasons about sensor quality and driving context in order to adapt it to the situation, while at the same time it carries out a continuous estimation and correction of INS drift errors. An exhaustive analysis has been carried out with available data in order to characterize the behavior of available sensors and take it into account in the developed solution. The performance is then analyzed with an extensive dataset containing representative situations. The proposed solution suits the use of fusion algorithms for deploying Intelligent Transport Systems in urban environments.

  3. Context-Aided Sensor Fusion for Enhanced Urban Navigation

    Science.gov (United States)

    Martí, Enrique David; Martín, David; García, Jesús; de la Escalera, Arturo; Molina, José Manuel; Armingol, José María

    2012-01-01

    The deployment of Intelligent Vehicles in urban environments requires reliable estimation of positioning for urban navigation. The inherent complexity of this kind of environments fosters the development of novel systems which should provide reliable and precise solutions to the vehicle. This article details an advanced GNSS/IMU fusion system based on a context-aided Unscented Kalman filter for navigation in urban conditions. The constrained non-linear filter is here conditioned by a contextual knowledge module which reasons about sensor quality and driving context in order to adapt it to the situation, while at the same time it carries out a continuous estimation and correction of INS drift errors. An exhaustive analysis has been carried out with available data in order to characterize the behavior of available sensors and take it into account in the developed solution. The performance is then analyzed with an extensive dataset containing representative situations. The proposed solution suits the use of fusion algorithms for deploying Intelligent Transport Systems in urban environments. PMID:23223080

  4. Dynamic tire pressure sensor for measuring ground vibration.

    Science.gov (United States)

    Wang, Qi; McDaniel, James Gregory; Wang, Ming L

    2012-11-07

    This work presents a convenient and non-contact acoustic sensing approach for measuring ground vibration. This approach, which uses an instantaneous dynamic tire pressure sensor (DTPS), possesses the capability to replace the accelerometer or directional microphone currently being used for inspecting pavement conditions. By measuring dynamic pressure changes inside the tire, ground vibration can be amplified and isolated from environmental noise. In this work, verifications of the DTPS concept of sensing inside the tire have been carried out. In addition, comparisons between a DTPS, ground-mounted accelerometer, and directional microphone are made. A data analysis algorithm has been developed and optimized to reconstruct ground acceleration from DTPS data. Numerical and experimental studies of this DTPS reveal a strong potential for measuring ground vibration caused by a moving vehicle. A calibration of transfer function between dynamic tire pressure change and ground acceleration may be needed for different tire system or for more accurate application.

  5. A New Multi-Sensor Track Fusion Architecture for Multi-Sensor Information Integration

    Science.gov (United States)

    2004-09-01

    NUMBER 5b. GRANT NUMBER 5c. PROGRAM ELEMENT NUMBER 6. AUTHOR(S) 5d. PROJECT NUMBER 5e. TASK NUMBER 5f. WORK UNIT NUMBER 7. PERFORMING ORGANIZATION ...NAME(S) AND ADDRESS(ES) Lockheed Martin Aeronautical Systems Company,Marietta,GA,3063 8. PERFORMING ORGANIZATION REPORT NUMBER 9. SPONSORING...tracking process and degrades the track accuracy. ARCHITECHTURE OF MULTI-SENSOR TRACK FUSION MODEL The Alpha

  6. Sensor fusion III: 3-D perception and recognition; Proceedings of the Meeting, Boston, MA, Nov. 5-8, 1990

    Science.gov (United States)

    Schenker, Paul S. (Editor)

    1991-01-01

    The volume on data fusion from multiple sources discusses fusing multiple views, temporal analysis and 3D motion interpretation, sensor fusion and eye-to-hand coordination, and integration in human shape perception. Attention is given to surface reconstruction, statistical methods in sensor fusion, fusing sensor data with environmental knowledge, computational models for sensor fusion, and evaluation and selection of sensor fusion techniques. Topics addressed include the structure of a scene from two and three projections, optical flow techniques for moving target detection, tactical sensor-based exploration in a robotic environment, and the fusion of human and machine skills for remote robotic operations. Also discussed are K-nearest-neighbor concepts for sensor fusion, surface reconstruction with discontinuities, a sensor-knowledge-command fusion paradigm for man-machine systems, coordinating sensing and local navigation, and terrain map matching using multisensing techniques for applications to autonomous vehicle navigation.

  7. Sensor management in RADAR/IRST track fusion

    Science.gov (United States)

    Hu, Shi-qiang; Jing, Zhong-liang

    2004-07-01

    In this paper, a novel radar management strategy technique suitable for RADAR/IRST track fusion, which is based on Fisher Information Matrix (FIM) and fuzzy stochastic decision approach, is put forward. Firstly, optimal radar measurements' scheduling is obtained by the method of maximizing determinant of the Fisher information matrix of radar and IRST measurements, which is managed by the expert system. Then, suggested a "pseudo sensor" to predict the possible target position using the polynomial method based on the radar and IRST measurements, using "pseudo sensor" model to estimate the target position even if the radar is turned off. At last, based on the tracking performance and the state of target maneuver, fuzzy stochastic decision is used to adjust the optimal radar scheduling and retrieve the module parameter of "pseudo sensor". The experiment result indicates that the algorithm can not only limit Radar activity effectively but also keep the tracking accuracy of active/passive system well. And this algorithm eliminates the drawback of traditional Radar management methods that the Radar activity is fixed and not easy to control and protect.

  8. Report on the Audit of Unattended Ground Sensor Systems

    Science.gov (United States)

    1991-02-26

    This final report on the Audit of Unattended Ground Sensor Systems is for your information and use. Comments on the draft were considered in...preparing the final report and changes have been made where appropriate. We performed the audit from February through August 1990. The objective was to

  9. The application of unattended ground sensors to stationary targets

    International Nuclear Information System (INIS)

    Sleefe, G.E.; Peglow, S.; Hamrick, R.

    1997-01-01

    The unattended sensing of stationary (i.e. non-mobile) targets is important in applications ranging from counter-proliferation to law enforcement. With stationary targets, sources of seismic, acoustic, and electro-magnetic emissions can potentially be used to detect, identify, and locate the target. Stationary targets have considerably different sensing requirements than the traditional mobile-target unattended ground sensor applications. This paper presents the novel features and requirements of a system for sensing stationary targets. In particular, issues associated with long-listen time signal processing for signal detection, and array processing techniques for signal localization are presented. Example data and signal processing outputs from a stationary target will be used to illustrate these issues. The impact on sensor, electronic signal processing, battery subsystem, and communication requirements will also be discussed. The paper will conclude with a detailed comparison between mobile-target and stationary-target unattended ground sensor architectures

  10. Advances in Multi-Sensor Information Fusion: Theory and Applications 2017.

    Science.gov (United States)

    Jin, Xue-Bo; Sun, Shuli; Wei, Hong; Yang, Feng-Bao

    2018-04-11

    The information fusion technique can integrate a large amount of data and knowledge representing the same real-world object and obtain a consistent, accurate, and useful representation of that object. The data may be independent or redundant, and can be obtained by different sensors at the same time or at different times. A suitable combination of investigative methods can substantially increase the profit of information in comparison with that from a single sensor. Multi-sensor information fusion has been a key issue in sensor research since the 1970s, and it has been applied in many fields. For example, manufacturing and process control industries can generate a lot of data, which have real, actionable business value. The fusion of these data can greatly improve productivity through digitization. The goal of this special issue is to report innovative ideas and solutions for multi-sensor information fusion in the emerging applications era, focusing on development, adoption, and applications.

  11. Advances in Multi-Sensor Information Fusion: Theory and Applications 2017

    Directory of Open Access Journals (Sweden)

    Xue-Bo Jin

    2018-04-01

    Full Text Available The information fusion technique can integrate a large amount of data and knowledge representing the same real-world object and obtain a consistent, accurate, and useful representation of that object. The data may be independent or redundant, and can be obtained by different sensors at the same time or at different times. A suitable combination of investigative methods can substantially increase the profit of information in comparison with that from a single sensor. Multi-sensor information fusion has been a key issue in sensor research since the 1970s, and it has been applied in many fields. For example, manufacturing and process control industries can generate a lot of data, which have real, actionable business value. The fusion of these data can greatly improve productivity through digitization. The goal of this special issue is to report innovative ideas and solutions for multi-sensor information fusion in the emerging applications era, focusing on development, adoption, and applications.

  12. Grounding Lines Detecting Using LANDSAT8 Oli and CRYOSAT-2 Data Fusion

    Science.gov (United States)

    Li, F.; Guo, Y.; Zhang, Y.; Zhang, S.

    2018-04-01

    The grounding zone is the region where ice transitions from grounded ice sheet to freely floating ice shelf, grounding lines are actually more of a zone, typically over several kilometers. The mass loss from Antarctica is strongly linked to changes in the ice shelves and their grounding lines, since the variation in the grounding line can result in very rapid changes in glacier and ice-shelf behavior. Based on remote sensing observations, five global Antarctic grounding line products have been released internationally, including MOA, ASAID, ICESat, MEaSUREs, and Synthesized grounding lines. However, the five products could not provide the annual grounding line products of the whole Antarctic, even some products have stopped updating, which limits the time series analysis of Antarctic material balance to a certain extent. Besides, the accurate of single remote-sensing data based grounding line products is far from satisficed. Therefore, we use algorithms to extract grounding lines with SAR and Cryosat-2 data respectively, and combine the results of two kinds of grounding lines to obtain new products, we obtain a mature grounding line extraction algorithm process, so that we can realize the extraction of grounding line of the Antarctic each year in the future. The comparison between fusion results and the MOA product results indicate that there is a maximum deviation of 188.67 meters between the MOA product and the fusion result.

  13. Estimating Orientation Using Magnetic and Inertial Sensors and Different Sensor Fusion Approaches: Accuracy Assessment in Manual and Locomotion Tasks

    Directory of Open Access Journals (Sweden)

    Elena Bergamini

    2014-10-01

    Full Text Available Magnetic and inertial measurement units are an emerging technology to obtain 3D orientation of body segments in human movement analysis. In this respect, sensor fusion is used to limit the drift errors resulting from the gyroscope data integration by exploiting accelerometer and magnetic aiding sensors. The present study aims at investigating the effectiveness of sensor fusion methods under different experimental conditions. Manual and locomotion tasks, differing in time duration, measurement volume, presence/absence of static phases, and out-of-plane movements, were performed by six subjects, and recorded by one unit located on the forearm or the lower trunk, respectively. Two sensor fusion methods, representative of the stochastic (Extended Kalman Filter and complementary (Non-linear observer filtering, were selected, and their accuracy was assessed in terms of attitude (pitch and roll angles and heading (yaw angle errors using stereophotogrammetric data as a reference. The sensor fusion approaches provided significantly more accurate results than gyroscope data integration. Accuracy improved mostly for heading and when the movement exhibited stationary phases, evenly distributed 3D rotations, it occurred in a small volume, and its duration was greater than approximately 20 s. These results were independent from the specific sensor fusion method used. Practice guidelines for improving the outcome accuracy are provided.

  14. Obstacle negotiation control for a mobile robot suspended on overhead ground wires by optoelectronic sensors

    Science.gov (United States)

    Zheng, Li; Yi, Ruan

    2009-11-01

    Power line inspection and maintenance already benefit from developments in mobile robotics. This paper presents mobile robots capable of crossing obstacles on overhead ground wires. A teleoperated robot realizes inspection and maintenance tasks on power transmission line equipment. The inspection robot is driven by 11 motor with two arms, two wheels and two claws. The inspection robot is designed to realize the function of observation, grasp, walk, rolling, turn, rise, and decline. This paper is oriented toward 100% reliable obstacle detection and identification, and sensor fusion to increase the autonomy level. An embedded computer based on PC/104 bus is chosen as the core of control system. Visible light camera and thermal infrared Camera are both installed in a programmable pan-and-tilt camera (PPTC) unit. High-quality visual feedback rapidly becomes crucial for human-in-the-loop control and effective teleoperation. The communication system between the robot and the ground station is based on Mesh wireless networks by 700 MHz bands. An expert system programmed with Visual C++ is developed to implement the automatic control. Optoelectronic laser sensors and laser range scanner were installed in robot for obstacle-navigation control to grasp the overhead ground wires. A novel prototype with careful considerations on mobility was designed to inspect the 500KV power transmission lines. Results of experiments demonstrate that the robot can be applied to execute the navigation and inspection tasks.

  15. Asynchronous Sensor fuSion for Improved Safety of air Traffic (ASSIST), Phase I

    Data.gov (United States)

    National Aeronautics and Space Administration — SSCI proposes to develop, implement and test a collision detection system for unmanned aerial vehicles (UAV), referred to as the Asynchronous Sensor fuSion for...

  16. A Radiosonde Using a Humidity Sensor Array with a Platinum Resistance Heater and Multi-Sensor Data Fusion

    Science.gov (United States)

    Shi, Yunbo; Luo, Yi; Zhao, Wenjie; Shang, Chunxue; Wang, Yadong; Chen, Yinsheng

    2013-01-01

    This paper describes the design and implementation of a radiosonde which can measure the meteorological temperature, humidity, pressure, and other atmospheric data. The system is composed of a CPU, microwave module, temperature sensor, pressure sensor and humidity sensor array. In order to effectively solve the humidity sensor condensation problem due to the low temperatures in the high altitude environment, a capacitive humidity sensor including four humidity sensors to collect meteorological humidity and a platinum resistance heater was developed using micro-electro-mechanical-system (MEMS) technology. A platinum resistance wire with 99.999% purity and 0.023 mm in diameter was used to obtain the meteorological temperature. A multi-sensor data fusion technique was applied to process the atmospheric data. Static and dynamic experimental results show that the designed humidity sensor with platinum resistance heater can effectively tackle the sensor condensation problem, shorten response times and enhance sensitivity. The humidity sensor array can improve measurement accuracy and obtain a reliable initial meteorological humidity data, while the multi-sensor data fusion technique eliminates the uncertainty in the measurement. The radiosonde can accurately reflect the meteorological changes. PMID:23857263

  17. Application of D-S Evidence Fusion Method in the Fault Detection of Temperature Sensor

    Directory of Open Access Journals (Sweden)

    Zheng Dou

    2014-01-01

    Full Text Available Due to the complexity and dangerousness of drying process, the fault detection of temperature sensor is very difficult and dangerous in actual working practice and the detection effectiveness is not satisfying. For this problem, in this paper, based on the idea of information fusion and the requirements of D-S evidence method, a D-S evidence fusion structure with two layers was introduced to detect the temperature sensor fault in drying process. The first layer was data layer to establish the basic belief assignment function of evidence which could be realized by BP Neural Network. The second layer was decision layer to detect and locate the sensor fault which could be realized by D-S evidence fusion method. According to the numerical simulation results, the working conditions of sensors could be described effectively and accurately by this method, so that it could be used to detect and locate the sensor fault.

  18. Development of mine explosion ground truth smart sensors

    Energy Technology Data Exchange (ETDEWEB)

    Taylor, Steven R. [Rocky Mountain Geophysics, Inc., Los Alamos, NM (United States); Harben, Phillip E. [Rocky Mountain Geophysics, Inc., Los Alamos, NM (United States); Jarpe, Steve [Jarpe Data Solutions, Prescott, AZ (United States); Harris, David B. [Deschutes Signal Processing, Maupin, OR (United States)

    2015-09-14

    Accurate seismo-acoustic source location is one of the fundamental aspects of nuclear explosion monitoring. Critical to improved location is the compilation of ground truth data sets for which origin time and location are accurately known. Substantial effort by the National Laboratories and other seismic monitoring groups have been undertaken to acquire and develop ground truth catalogs that form the basis of location efforts (e.g. Sweeney, 1998; Bergmann et al., 2009; Waldhauser and Richards, 2004). In particular, more GT1 (Ground Truth 1 km) events are required to improve three-dimensional velocity models that are currently under development. Mine seismicity can form the basis of accurate ground truth datasets. Although the location of mining explosions can often be accurately determined using array methods (e.g. Harris, 1991) and from overhead observations (e.g. MacCarthy et al., 2008), accurate origin time estimation can be difficult. Occasionally, mine operators will share shot time, location, explosion size and even shot configuration, but this is rarely done, especially in foreign countries. Additionally, shot times provided by mine operators are often inaccurate. An inexpensive, ground truth event detector that could be mailed to a contact, placed in close proximity (< 5 km) to mining regions or earthquake aftershock regions that automatically transmits back ground-truth parameters, would greatly aid in development of ground truth datasets that could be used to improve nuclear explosion monitoring capabilities. We are developing an inexpensive, compact, lightweight smart sensor unit (or units) that could be used in the development of ground truth datasets for the purpose of improving nuclear explosion monitoring capabilities. The units must be easy to deploy, be able to operate autonomously for a significant period of time (> 6 months) and inexpensive enough to be discarded after useful operations have expired (although this may not be part of our business

  19. The Rover Environmental Monitoring Station Ground Temperature Sensor: A Pyrometer for Measuring Ground Temperature on Mars

    Directory of Open Access Journals (Sweden)

    Miguel Ramos

    2010-10-01

    Full Text Available We describe the parameters that drive the design and modeling of the Rover Environmental Monitoring Station (REMS Ground Temperature Sensor (GTS, an instrument aboard NASA’s Mars Science Laboratory, and report preliminary test results. REMS GTS is a lightweight, low-power, and low cost pyrometer for measuring the Martian surface kinematic temperature. The sensor’s main feature is its innovative design, based on a simple mechanical structure with no moving parts. It includes an in-flight calibration system that permits sensor recalibration when sensor sensitivity has been degraded by deposition of dust over the optics. This paper provides the first results of a GTS engineering model working in a Martian-like, extreme environment.

  20. Freeway Multisensor Data Fusion Approach Integrating Data from Cellphone Probes and Fixed Sensors

    Directory of Open Access Journals (Sweden)

    Shanglu He

    2016-01-01

    Full Text Available Freeway traffic state information from multiple sources provides sufficient support to the traffic surveillance but also brings challenges. This paper made an investigation into the fusion of a new data combination from cellular handoff probe system and microwave sensors. And a fusion method based on the neural network technique was proposed. To identify the factors influencing the accuracy of fusion results, we analyzed the sensitivity of those factors by changing the inputs of neural-network-based fusion model. The results showed that handoff link length and sample size were identified as the most influential parameters to the precision of fusion. Then, the effectiveness and capability of proposed fusion method under various traffic conditions were evaluated. And a comparative analysis between the proposed method and other fusion approaches was conducted. The results of simulation test and evaluation showed that the fusion method could complement the drawback of each collection method, improve the overall estimation accuracy, adapt to the variable traffic condition (free flow or incident state, suit the fusion of data from cellphone probes and fixed sensors, and outperform other fusion methods.

  1. Ground-based transmission line conductor motion sensor

    International Nuclear Information System (INIS)

    Jacobs, M.L.; Milano, U.

    1988-01-01

    A ground-based-conductor motion-sensing apparatus is provided for remotely sensing movement of electric-power transmission lines, particularly as would occur during the wind-induced condition known as galloping. The apparatus is comprised of a motion sensor and signal-generating means which are placed underneath a transmission line and will sense changes in the electric field around the line due to excessive line motion. The detector then signals a remote station when a conditioning of galloping is sensed. The apparatus of the present invention is advantageous over the line-mounted sensors of the prior art in that it is easier and less hazardous to install. The system can also be modified so that a signal will only be given when particular conditions, such as specific temperature range, large-amplitude line motion, or excessive duration of the line motion, are occurring

  2. Multi-Source Multi-Sensor Information Fusion

    Indian Academy of Sciences (India)

    M. Senthilkumar (Newgen Imaging) 1461 1996 Oct 15 13:05:22

    applications in biomedical, industrial automation, aerospace systems and environmental ... performance evaluation and achievable accuracy, mainly for aerospace ... system and sensors, sensor data processing and performance requirement, ...

  3. Sensor Interoperability and Fusion in Fingerprint Verification: A Case Study using Minutiae-and Ridge-Based Matchers

    NARCIS (Netherlands)

    Alonso-Fernandez, F.; Veldhuis, Raymond N.J.; Bazen, A.M.; Fierrez-Aguilar, J.; Ortega-Garcia, J.

    2006-01-01

    Information fusion in fingerprint recognition has been studied in several papers. However, only a few papers have been focused on sensor interoperability and sensor fusion. In this paper, these two topics are studied using a multisensor database acquired with three different fingerprint sensors.

  4. Integrative Multi-Spectral Sensor Device for Far-Infrared and Visible Light Fusion

    Science.gov (United States)

    Qiao, Tiezhu; Chen, Lulu; Pang, Yusong; Yan, Gaowei

    2018-06-01

    Infrared and visible light image fusion technology is a hot spot in the research of multi-sensor fusion technology in recent years. Existing infrared and visible light fusion technologies need to register before fusion because of using two cameras. However, the application effect of the registration technology has yet to be improved. Hence, a novel integrative multi-spectral sensor device is proposed for infrared and visible light fusion, and by using the beam splitter prism, the coaxial light incident from the same lens is projected to the infrared charge coupled device (CCD) and visible light CCD, respectively. In this paper, the imaging mechanism of the proposed sensor device is studied with the process of the signals acquisition and fusion. The simulation experiment, which involves the entire process of the optic system, signal acquisition, and signal fusion, is constructed based on imaging effect model. Additionally, the quality evaluation index is adopted to analyze the simulation result. The experimental results demonstrate that the proposed sensor device is effective and feasible.

  5. Detecting Pedestrian Flocks by Fusion of Multi-Modal Sensors in Mobile Phones

    DEFF Research Database (Denmark)

    Kjærgaard, Mikkel Baun; Wirz, Martin; Roggen, Daniel

    2012-01-01

    derived from multiple sensor modalities of modern smartphones. Automatic detection of flocks has several important applications, including evacuation management and socially aware computing. The novelty of this paper is, firstly, to use data fusion techniques to combine several sensor modalities (WiFi...

  6. Sensor Fusion Techniques for Phased-Array Eddy Current and Phased-Array Ultrasound Data

    Energy Technology Data Exchange (ETDEWEB)

    Arrowood, Lloyd F. [Y-12 National Security Complex, Oak Ridge, TN (United States)

    2018-03-15

    Sensor (or Data) fusion is the process of integrating multiple data sources to produce more consistent, accurate and comprehensive information than is provided by a single data source. Sensor fusion may also be used to combine multiple signals from a single modality to improve the performance of a particular inspection technique. Industrial nondestructive testing may utilize multiple sensors to acquire inspection data depending upon the object under inspection and the anticipated types of defects that can be identified. Sensor fusion can be performed at various levels of signal abstraction with each having its strengths and weaknesses. A multimodal data fusion strategy first proposed by Heideklang and Shokouhi that combines spatially scattered detection locations to improve detection performance of surface-breaking and near-surface cracks in ferromagnetic metals is shown using a surface inspection example and is then extended for volumetric inspections. Utilizing data acquired from an Olympus Omniscan MX2 from both phased array eddy current and ultrasound probes on test phantoms, single and multilevel fusion techniques are employed to integrate signals from the two modalities. Preliminary results demonstrate how confidence in defect identification and interpretation benefit from sensor fusion techniques. Lastly, techniques for integrating data into radiographic and volumetric imagery from computed tomography are described and results are presented.

  7. Sensor Fusion of Cameras and a Laser for City-Scale 3D Reconstruction

    Directory of Open Access Journals (Sweden)

    Yunsu Bok

    2014-11-01

    Full Text Available This paper presents a sensor fusion system of cameras and a 2D laser sensorfor large-scale 3D reconstruction. The proposed system is designed to capture data on afast-moving ground vehicle. The system consists of six cameras and one 2D laser sensor,and they are synchronized by a hardware trigger. Reconstruction of 3D structures is doneby estimating frame-by-frame motion and accumulating vertical laser scans, as in previousworks. However, our approach does not assume near 2D motion, but estimates free motion(including absolute scale in 3D space using both laser data and image features. In orderto avoid the degeneration associated with typical three-point algorithms, we present a newalgorithm that selects 3D points from two frames captured by multiple cameras. The problemof error accumulation is solved by loop closing, not by GPS. The experimental resultsshow that the estimated path is successfully overlaid on the satellite images, such that thereconstruction result is very accurate.

  8. Distributed fusion estimation for sensor networks with communication constraints

    CERN Document Server

    Zhang, Wen-An; Song, Haiyu; Yu, Li

    2016-01-01

    This book systematically presents energy-efficient robust fusion estimation methods to achieve thorough and comprehensive results in the context of network-based fusion estimation. It summarizes recent findings on fusion estimation with communication constraints; several novel energy-efficient and robust design methods for dealing with energy constraints and network-induced uncertainties are presented, such as delays, packet losses, and asynchronous information... All the results are presented as algorithms, which are convenient for practical applications.

  9. Airfield Ground Safety

    National Research Council Canada - National Science Library

    Petrescu, Jon

    2000-01-01

    .... The system developed under AGS, called the Ground Safety Tracking and Reporting System, uses multisensor data fusion from in-pavement inductive loop sensors to address a critical problem affecting out nation's airports: runway incursions...

  10. The use of proximal soil sensor data fusion and digital soil mapping for precision agriculture

    OpenAIRE

    Ji, Wenjun; Adamchuk, Viacheslav; Chen, Songchao; Biswas, Asim; Leclerc, Maxime; Viscarra Rossel, Raphael

    2017-01-01

    Proximal soil sensing (PSS) is a promising approach when it comes to detailed characterization of spatial soil heterogeneity. Since none of existing PSS systems can measure all soil information needed for implementation precision agriculture, sensor data fusion can provide a reasonable al- ternative to characterize the complexity of soils. In this study, we fused the data measured using a gamma-ray sensor, an apparent electrical conductivity (ECa) sensor, and a commercial Veris MS...

  11. Optical Communication System for Remote Monitoring and Adaptive Control of Distributed Ground Sensors Exhibiting Collective Intelligence

    Energy Technology Data Exchange (ETDEWEB)

    Cameron, S.M.; Stantz, K.M.; Trahan, M.W.; Wagner, J.S.

    1998-11-01

    Comprehensive management of the battle-space has created new requirements in information management, communication, and interoperability as they effect surveillance and situational awareness. The objective of this proposal is to expand intelligent controls theory to produce a uniquely powerful implementation of distributed ground-based measurement incorporating both local collective behavior, and interoperative global optimization for sensor fusion and mission oversight. By using a layered hierarchal control architecture to orchestrate adaptive reconfiguration of autonomous robotic agents, we can improve overall robustness and functionality in dynamic tactical environments without information bottlenecks. In this concept, each sensor is equipped with a miniaturized optical reflectance modulator which is interactively monitored as a remote transponder using a covert laser communication protocol from a remote mothership or operative. Robot data-sharing at the ground level can be leveraged with global evaluation criteria, including terrain overlays and remote imaging data. Information sharing and distributed intelli- gence opens up a new class of remote-sensing applications in which small single-function autono- mous observers at the local level can collectively optimize and measure large scale ground-level signals. AS the need for coverage and the number of agents grows to improve spatial resolution, cooperative behavior orchestrated by a global situational awareness umbrella will be an essential ingredient to offset increasing bandwidth requirements within the net. A system of the type described in this proposal will be capable of sensitively detecting, tracking, and mapping spatial distributions of measurement signatures which are non-stationary or obscured by clutter and inter- fering obstacles by virtue of adaptive reconfiguration. This methodology could be used, for example, to field an adaptive ground-penetrating radar for detection of underground structures in

  12. Sensor management for identity fusion on a mobile robot

    DEFF Research Database (Denmark)

    Larsen, Thomas Dall; Andersen, Nils Axel; Ravn, Ole

    1998-01-01

    This paper addresses the problem of identity fusion, i.e. the problem of selecting one of several identity hypotheses concerning an observed object. Two problems are considered. Firstly the problem of preserving the information in the representation and fusion of measurements relating to identity...

  13. Multi-Sensor Optimal Data Fusion Based on the Adaptive Fading Unscented Kalman Filter.

    Science.gov (United States)

    Gao, Bingbing; Hu, Gaoge; Gao, Shesheng; Zhong, Yongmin; Gu, Chengfan

    2018-02-06

    This paper presents a new optimal data fusion methodology based on the adaptive fading unscented Kalman filter for multi-sensor nonlinear stochastic systems. This methodology has a two-level fusion structure: at the bottom level, an adaptive fading unscented Kalman filter based on the Mahalanobis distance is developed and serves as local filters to improve the adaptability and robustness of local state estimations against process-modeling error; at the top level, an unscented transformation-based multi-sensor optimal data fusion for the case of N local filters is established according to the principle of linear minimum variance to calculate globally optimal state estimation by fusion of local estimations. The proposed methodology effectively refrains from the influence of process-modeling error on the fusion solution, leading to improved adaptability and robustness of data fusion for multi-sensor nonlinear stochastic systems. It also achieves globally optimal fusion results based on the principle of linear minimum variance. Simulation and experimental results demonstrate the efficacy of the proposed methodology for INS/GNSS/CNS (inertial navigation system/global navigation satellite system/celestial navigation system) integrated navigation.

  14. An epidemic model for biological data fusion in ad hoc sensor networks

    Science.gov (United States)

    Chang, K. C.; Kotari, Vikas

    2009-05-01

    Bio terrorism can be a very refined and a catastrophic approach of attacking a nation. This requires the development of a complete architecture dedicatedly designed for this purpose which includes but is not limited to Sensing/Detection, Tracking and Fusion, Communication, and others. In this paper we focus on one such architecture and evaluate its performance. Various sensors for this specific purpose have been studied. The accent has been on use of Distributed systems such as ad-hoc networks and on application of epidemic data fusion algorithms to better manage the bio threat data. The emphasis has been on understanding the performance characteristics of these algorithms under diversified real time scenarios which are implemented through extensive JAVA based simulations. Through comparative studies on communication and fusion the performance of channel filter algorithm for the purpose of biological sensor data fusion are validated.

  15. Data Fusion Based on Node Trust Evaluation in Wireless Sensor Networks

    Directory of Open Access Journals (Sweden)

    Zhou Jianming

    2014-01-01

    Full Text Available Abnormal behavior detection and trust evaluation mode of traditional sensor node have a single function without considering all the factors, and the trust value algorithm is relatively complicated. To avoid these above disadvantages, a trust evaluation model based on the autonomous behavior of sensor node is proposed in this paper. Each sensor node has the monitoring privilege and obligation. Neighboring sensor nodes can monitor each other. Their direct and indirect trust values can be achieved by using a relatively simple calculation method, the synthesis trust value of which could be got according to the composition rule of D-S evidence theory. Firstly, the cluster head assigns different weighted value for the data from each sensor node, then the weight vector is set according to the synthesis trust value, the data fusion processing is executed, and finally the cluster head sensor node transmits the fused result to the base station. Simulation experiment results demonstrate that the trust evaluation model can rapidly, exactly, and effectively recognize malicious sensor node and avoid malicious sensor node becoming cluster head sensor node. The proposed algorithm can greatly increase the safety and accuracy of data fusion, improve communication efficiency, save energy of sensor node, suit different application fields, and deploy environments.

  16. Bi-channel Sensor Fusion for Automatic Sign Language Recognition

    DEFF Research Database (Denmark)

    Kim, Jonghwa; Wagner, Johannes; Rehm, Matthias

    2008-01-01

    In this paper, we investigate the mutual-complementary functionality of accelerometer (ACC) and electromyogram (EMG) for recognizing seven word-level sign vocabularies in German sign language (GSL). Results are discussed for the single channels and for feature-level fusion for the bichannel senso......-independent condition, where subjective differences do not allow for high recognition rates. Finally we discuss a problem of feature-level fusion caused by high disparity between accuracies of each single channel classification....

  17. A flexible data fusion architecture for persistent surveillance using ultra-low-power wireless sensor networks

    Science.gov (United States)

    Hanson, Jeffrey A.; McLaughlin, Keith L.; Sereno, Thomas J.

    2011-06-01

    We have developed a flexible, target-driven, multi-modal, physics-based fusion architecture that efficiently searches sensor detections for targets and rejects clutter while controlling the combinatoric problems that commonly arise in datadriven fusion systems. The informational constraints imposed by long lifetime requirements make systems vulnerable to false alarms. We demonstrate that our data fusion system significantly reduces false alarms while maintaining high sensitivity to threats. In addition, mission goals can vary substantially in terms of targets-of-interest, required characterization, acceptable latency, and false alarm rates. Our fusion architecture provides the flexibility to match these trade-offs with mission requirements unlike many conventional systems that require significant modifications for each new mission. We illustrate our data fusion performance with case studies that span many of the potential mission scenarios including border surveillance, base security, and infrastructure protection. In these studies, we deployed multi-modal sensor nodes - including geophones, magnetometers, accelerometers and PIR sensors - with low-power processing algorithms and low-bandwidth wireless mesh networking to create networks capable of multi-year operation. The results show our data fusion architecture maintains high sensitivities while suppressing most false alarms for a variety of environments and targets.

  18. Reliability estimates for selected sensors in fusion applications

    International Nuclear Information System (INIS)

    Cadwallader, L.C.

    1996-09-01

    This report presents the results of a study to define several types of sensors in use, the qualitative reliability (failure modes) and quantitative reliability (average failure rates) for these types of process sensors. Temperature, pressure, flow, and level sensors are discussed for water coolant and for cryogenic coolants. The failure rates that have been found are useful for risk assessment and safety analysis. Repair times and calibration intervals are also given when found in the literature. All of these values can also be useful to plant operators and maintenance personnel. Designers may be able to make use of these data when planning systems. The final chapter in this report discusses failure rates for several types of personnel safety sensors, including ionizing radiation monitors, toxic and combustible gas detectors, humidity sensors, and magnetic field sensors. These data could be useful to industrial hygienists and other safety professionals when designing or auditing for personnel safety

  19. Sensor fusion to enable next generation low cost Night Vision systems

    Science.gov (United States)

    Schweiger, R.; Franz, S.; Löhlein, O.; Ritter, W.; Källhammer, J.-E.; Franks, J.; Krekels, T.

    2010-04-01

    The next generation of automotive Night Vision Enhancement systems offers automatic pedestrian recognition with a performance beyond current Night Vision systems at a lower cost. This will allow high market penetration, covering the luxury as well as compact car segments. Improved performance can be achieved by fusing a Far Infrared (FIR) sensor with a Near Infrared (NIR) sensor. However, fusing with today's FIR systems will be too costly to get a high market penetration. The main cost drivers of the FIR system are its resolution and its sensitivity. Sensor cost is largely determined by sensor die size. Fewer and smaller pixels will reduce die size but also resolution and sensitivity. Sensitivity limits are mainly determined by inclement weather performance. Sensitivity requirements should be matched to the possibilities of low cost FIR optics, especially implications of molding of highly complex optical surfaces. As a FIR sensor specified for fusion can have lower resolution as well as lower sensitivity, fusing FIR and NIR can solve performance and cost problems. To allow compensation of FIR-sensor degradation on the pedestrian detection capabilities, a fusion approach called MultiSensorBoosting is presented that produces a classifier holding highly discriminative sub-pixel features from both sensors at once. The algorithm is applied on data with different resolution and on data obtained from cameras with varying optics to incorporate various sensor sensitivities. As it is not feasible to record representative data with all different sensor configurations, transformation routines on existing high resolution data recorded with high sensitivity cameras are investigated in order to determine the effects of lower resolution and lower sensitivity to the overall detection performance. This paper also gives an overview of the first results showing that a reduction of FIR sensor resolution can be compensated using fusion techniques and a reduction of sensitivity can be

  20. Kalman filter-based EM-optical sensor fusion for needle deflection estimation.

    Science.gov (United States)

    Jiang, Baichuan; Gao, Wenpeng; Kacher, Daniel; Nevo, Erez; Fetics, Barry; Lee, Thomas C; Jayender, Jagadeesan

    2018-04-01

    In many clinical procedures such as cryoablation that involves needle insertion, accurate placement of the needle's tip at the desired target is the major issue for optimizing the treatment and minimizing damage to the neighboring anatomy. However, due to the interaction force between the needle and tissue, considerable error in intraoperative tracking of the needle tip can be observed as needle deflects. In this paper, measurements data from an optical sensor at the needle base and a magnetic resonance (MR) gradient field-driven electromagnetic (EM) sensor placed 10 cm from the needle tip are used within a model-integrated Kalman filter-based sensor fusion scheme. Bending model-based estimations and EM-based direct estimation are used as the measurement vectors in the Kalman filter, thus establishing an online estimation approach. Static tip bending experiments show that the fusion method can reduce the mean error of the tip position estimation from 29.23 mm of the optical sensor-based approach to 3.15 mm of the fusion-based approach and from 39.96 to 6.90 mm, at the MRI isocenter and the MRI entrance, respectively. This work established a novel sensor fusion scheme that incorporates model information, which enables real-time tracking of needle deflection with MRI compatibility, in a free-hand operating setup.

  1. Comparison of pH Data Measured with a pH Sensor Array Using Different Data Fusion Methods

    Directory of Open Access Journals (Sweden)

    Yi-Hung Liao

    2012-09-01

    Full Text Available This paper introduces different data fusion methods which are used for an electrochemical measurement using a sensor array. In this study, we used ruthenium dioxide sensing membrane pH electrodes to form a sensor array. The sensor array was used for detecting the pH values of grape wine, generic cola drink and bottled base water. The measured pH data were used for data fusion methods to increase the reliability of the measured results, and we also compared the fusion results with other different data fusion methods.

  2. Advanced data visualization and sensor fusion: Conversion of techniques from medical imaging to Earth science

    Science.gov (United States)

    Savage, Richard C.; Chen, Chin-Tu; Pelizzari, Charles; Ramanathan, Veerabhadran

    1993-01-01

    Hughes Aircraft Company and the University of Chicago propose to transfer existing medical imaging registration algorithms to the area of multi-sensor data fusion. The University of Chicago's algorithms have been successfully demonstrated to provide pixel by pixel comparison capability for medical sensors with different characteristics. The research will attempt to fuse GOES (Geostationary Operational Environmental Satellite), AVHRR (Advanced Very High Resolution Radiometer), and SSM/I (Special Sensor Microwave Imager) sensor data which will benefit a wide range of researchers. The algorithms will utilize data visualization and algorithm development tools created by Hughes in its EOSDIS (Earth Observation SystemData/Information System) prototyping. This will maximize the work on the fusion algorithms since support software (e.g. input/output routines) will already exist. The research will produce a portable software library with documentation for use by other researchers.

  3. Proximal soil sensors and data fusion for precision agriculture

    NARCIS (Netherlands)

    Mahmood, H.S.

    2013-01-01

    different remote and proximal soil sensors are available today that can scan entire fields and give detailed information on various physical, chemical, mechanical and biological soil properties. The first objective of this thesis was to evaluate different proximal soil sensors available today and to

  4. Scalable sensor management for automated fusion and tactical reconnaissance

    Science.gov (United States)

    Walls, Thomas J.; Wilson, Michael L.; Partridge, Darin C.; Haws, Jonathan R.; Jensen, Mark D.; Johnson, Troy R.; Petersen, Brad D.; Sullivan, Stephanie W.

    2013-05-01

    The capabilities of tactical intelligence, surveillance, and reconnaissance (ISR) payloads are expanding from single sensor imagers to integrated systems-of-systems architectures. Increasingly, these systems-of-systems include multiple sensing modalities that can act as force multipliers for the intelligence analyst. Currently, the separate sensing modalities operate largely independent of one another, providing a selection of operating modes but not an integrated intelligence product. We describe here a Sensor Management System (SMS) designed to provide a small, compact processing unit capable of managing multiple collaborative sensor systems on-board an aircraft. Its purpose is to increase sensor cooperation and collaboration to achieve intelligent data collection and exploitation. The SMS architecture is designed to be largely sensor and data agnostic and provide flexible networked access for both data providers and data consumers. It supports pre-planned and ad-hoc missions, with provisions for on-demand tasking and updates from users connected via data links. Management of sensors and user agents takes place over standard network protocols such that any number and combination of sensors and user agents, either on the local network or connected via data link, can register with the SMS at any time during the mission. The SMS provides control over sensor data collection to handle logging and routing of data products to subscribing user agents. It also supports the addition of algorithmic data processing agents for feature/target extraction and provides for subsequent cueing from one sensor to another. The SMS architecture was designed to scale from a small UAV carrying a limited number of payloads to an aircraft carrying a large number of payloads. The SMS system is STANAG 4575 compliant as a removable memory module (RMM) and can act as a vehicle specific module (VSM) to provide STANAG 4586 compliance (level-3 interoperability) to a non-compliant sensor system

  5. Sensor Fusion - Sonar and Stereo Vision, Using Occupancy Grids and SIFT

    DEFF Research Database (Denmark)

    Plascencia, Alfredo; Bendtsen, Jan Dimon

    2006-01-01

    to the occupied and empty regions. SIFT (Scale Invariant Feature Transform) feature descriptors are  interpreted using gaussian probabilistic error models. The use of occupancy grids is proposed for representing the sonar  as well as the features descriptors readings. The Bayesian estimation approach is applied...... to update the sonar and the SIFT descriptors' uncertainty grids. The sensor fusion yields a significant reduction in the uncertainty of the occupancy grid compared to the individual sensor readings....

  6. Probabilistic Multi-Sensor Fusion Based Indoor Positioning System on a Mobile Device

    Directory of Open Access Journals (Sweden)

    Xiang He

    2015-12-01

    Full Text Available Nowadays, smart mobile devices include more and more sensors on board, such as motion sensors (accelerometer, gyroscope, magnetometer, wireless signal strength indicators (WiFi, Bluetooth, Zigbee, and visual sensors (LiDAR, camera. People have developed various indoor positioning techniques based on these sensors. In this paper, the probabilistic fusion of multiple sensors is investigated in a hidden Markov model (HMM framework for mobile-device user-positioning. We propose a graph structure to store the model constructed by multiple sensors during the offline training phase, and a multimodal particle filter to seamlessly fuse the information during the online tracking phase. Based on our algorithm, we develop an indoor positioning system on the iOS platform. The experiments carried out in a typical indoor environment have shown promising results for our proposed algorithm and system design.

  7. Heterogeneous Multi-Metric Learning for Multi-Sensor Fusion

    Science.gov (United States)

    2011-07-01

    Neural Information Processing Systems, 2010. [18] C.-C. Shen and W.-H. Tsai. Multisensor fusion in smartphones for lifestyle monitoring. In Int. Conf. on...Ministry of Education (708085) of China. REFERENCES [1] C. M. Bishop. Pattern Recognition and Machine Learning. Springer, 2006. [2] S. Boughhorbel, J

  8. Sensor fusion control system for computer integrated manufacturing

    CSIR Research Space (South Africa)

    Kumile, CM

    2007-08-01

    Full Text Available -floor control using sensors previously missing in manufacturing research. The contribution is in the ease and the elegance that the concept provides finite state/ automata activities as well as the production engineering elements such as planning...

  9. Health-Enabled Smart Sensor Fusion Technology, Phase I

    Data.gov (United States)

    National Aeronautics and Space Administration — It has been proven that the combination of smart sensors with embedded metadata and wireless technologies present real opportunities for significant improvements in...

  10. The assessment of multi-sensor image fusion using wavelet transforms for mapping the Brazilian Savanna

    NARCIS (Netherlands)

    Weimar Acerbi, F.; Clevers, J.G.P.W.; Schaepman, M.E.

    2006-01-01

    Multi-sensor image fusion using the wavelet approach provides a conceptual framework for the improvement of the spatial resolution with minimal distortion of the spectral content of the source image. This paper assesses whether images with a large ratio of spatial resolution can be fused, and

  11. Localization in orchards using Extended Kalman Filter for sensor-fusion - A FroboMind component

    DEFF Research Database (Denmark)

    Christiansen, Martin Peter; Jensen, Kjeld; Ellekilde, Lars-Peter

    Using the detected trees seen in gure 4(b) a localised SLAM map of the surroundings area, can be created an used to determine the localisation of the tractor. This kind of sensor-fusion is used, to keep the amount of prior information about outlay of the orchard to a minimum, so it can be used...

  12. Performance of Hall sensor-based devices for magnetic field diagnosis at fusion reactors

    Czech Academy of Sciences Publication Activity Database

    Bolshakova, I.; Ďuran, Ivan; Holyaka, R.; Hristoforou, E.; Marusenkov, A.

    2007-01-01

    Roč. 5, č. 1 (2007), s. 283-288 ISSN 1546-198X R&D Projects: GA AV ČR KJB100430504 Institutional research plan: CEZ:AV0Z20430508 Keywords : Galvanomagnetic * Sensor * Fusion Reactor * Magnetic Diagnostics * Radiation Hardness Subject RIV: BG - Nuclear, Atomic and Molecular Physics, Colliders Impact factor: 1.587, year: 2007

  13. Sensor Data Fusion for Accurate Cloud Presence Prediction Using Dempster-Shafer Evidence Theory

    Directory of Open Access Journals (Sweden)

    Jesse S. Jin

    2010-10-01

    Full Text Available Sensor data fusion technology can be used to best extract useful information from multiple sensor observations. It has been widely applied in various applications such as target tracking, surveillance, robot navigation, signal and image processing. This paper introduces a novel data fusion approach in a multiple radiation sensor environment using Dempster-Shafer evidence theory. The methodology is used to predict cloud presence based on the inputs of radiation sensors. Different radiation data have been used for the cloud prediction. The potential application areas of the algorithm include renewable power for virtual power station where the prediction of cloud presence is the most challenging issue for its photovoltaic output. The algorithm is validated by comparing the predicted cloud presence with the corresponding sunshine occurrence data that were recorded as the benchmark. Our experiments have indicated that comparing to the approaches using individual sensors, the proposed data fusion approach can increase correct rate of cloud prediction by ten percent, and decrease unknown rate of cloud prediction by twenty three percent.

  14. Summary of sensor evaluation for the Fusion ELectromagnetic Induction eXperiment (FELIX)

    International Nuclear Information System (INIS)

    Knott, M.J.

    1982-08-01

    As part of the First Wall/Blanket/Shield Engineering Test Program, a test bed called FELIX (Fusion ELectromagnetic Induction eXperiment) is now under construction at ANL. Its purpose will be to test, evaluate, and develop computer codes for the prediction of electromagnetically induced phenomenon in a magnetic environment modeling that of a fusion reaction. Crucial to this process is the sensing and recording of the various induced effects. Sensor evaluation for FELIX has reached the point where most sensor types have been evaluated and preliminary decisions are being made as to type and quantity for the initial FELIX experiments. These early experiments, the first, flat plate experiment in particular, will be aimed at testing the sensors as well as the pertinent theories involved. The reason for these evaluations, decisions, and proof tests is the harsh electrical and magnetic environment that FELIX presents

  15. All-IP-Ethernet architecture for real-time sensor-fusion processing

    Science.gov (United States)

    Hiraki, Kei; Inaba, Mary; Tezuka, Hiroshi; Tomari, Hisanobu; Koizumi, Kenichi; Kondo, Shuya

    2016-03-01

    Serendipter is a device that distinguishes and selects very rare particles and cells from huge amount of population. We are currently designing and constructing information processing system for a Serendipter. The information processing system for Serendipter is a kind of sensor-fusion system but with much more difficulties: To fulfill these requirements, we adopt All IP based architecture: All IP-Ethernet based data processing system consists of (1) sensor/detector directly output data as IP-Ethernet packet stream, (2) single Ethernet/TCP/IP streams by a L2 100Gbps Ethernet switch, (3) An FPGA board with 100Gbps Ethernet I/F connected to the switch and a Xeon based server. Circuits in the FPGA include 100Gbps Ethernet MAC, buffers and preprocessing, and real-time Deep learning circuits using multi-layer neural networks. Proposed All-IP architecture solves existing problem to construct large-scale sensor-fusion systems.

  16. Development of Mine Explosion Ground Truth Smart Sensors

    Science.gov (United States)

    2011-09-01

    interest. The two candidates are the GS11-D by Oyo Geospace that is used extensively in seismic monitoring of geothermal fields and the Sensor Nederland SM...Technologies 853 Figure 4. Our preferred sensors and processor for the GTMS. (a) Sensor Nederland SM-6 geophone with emplacement spike. (b

  17. Statistical methods of combining information: Applications to sensor data fusion

    Energy Technology Data Exchange (ETDEWEB)

    Burr, T.

    1996-12-31

    This paper reviews some statistical approaches to combining information from multiple sources. Promising new approaches will be described, and potential applications to combining not-so-different data sources such as sensor data will be discussed. Experiences with one real data set are described.

  18. Sensor fusion in head pose tracking for augmented reality

    NARCIS (Netherlands)

    Persa, S.F.

    2006-01-01

    The focus of this thesis is on studying diverse techniques, methods and sensors for position and orientation determination with application to augmented reality applications. In Chapter 2 we reviewed a variety of existing techniques and systems for position determination. From a practical point of

  19. A novel method of range measuring for a mobile robot based on multi-sensor information fusion

    International Nuclear Information System (INIS)

    Zhang Yi; Luo Yuan; Wang Jifeng

    2005-01-01

    The traditional measuring range for a mobile robot is based on a sonar sensor. Because of different working environments, it is very difficult to obtain high precision by using just one single method of range measurement. So, a hybrid sonar sensor and laser scanner method is put forward to overcome these shortcomings. A novel fusion model is proposed based on basic theory and a method of information fusion. An optimal measurement result has been obtained with information fusion from different sensors. After large numbers of experiments and performance analysis, a conclusion can be drawn that the laser scanner and sonar sensor method with multi-sensor information fusion have a higher precision than the single method of sonar. It can also be the same with different environments

  20. A Cluster-Based Fuzzy Fusion Algorithm for Event Detection in Heterogeneous Wireless Sensor Networks

    Directory of Open Access Journals (Sweden)

    ZiQi Hao

    2015-01-01

    Full Text Available As limited energy is one of the tough challenges in wireless sensor networks (WSN, energy saving becomes important in increasing the lifecycle of the network. Data fusion enables combining information from several sources thus to provide a unified scenario, which can significantly save sensor energy and enhance sensing data accuracy. In this paper, we propose a cluster-based data fusion algorithm for event detection. We use k-means algorithm to form the nodes into clusters, which can significantly reduce the energy consumption of intracluster communication. Distances between cluster heads and event and energy of clusters are fuzzified, thus to use a fuzzy logic to select the clusters that will participate in data uploading and fusion. Fuzzy logic method is also used by cluster heads for local decision, and then the local decision results are sent to the base station. Decision-level fusion for final decision of event is performed by base station according to the uploaded local decisions and fusion support degree of clusters calculated by fuzzy logic method. The effectiveness of this algorithm is demonstrated by simulation results.

  1. Keystrokes Inference Attack on Android: A Comparative Evaluation of Sensors and Their Fusion

    Directory of Open Access Journals (Sweden)

    Ahmed Al-Haiqi

    2014-11-01

    Full Text Available Introducing motion sensors into smartphones contributed to a wide range of applications in human-phone interaction, gaming, and many others. However, built-in sensors that detect subtle motion changes (e.g. accelerometers, might also reveal information about taps on touch screens: the main user input mode. Few researchers have already demonstrated the idea of exploiting motion sensors as side-channels into inferring keystrokes. Taken at most as initial explorations, much research is still needed to analyze the practicality of the new threat and examine various aspects of its implementation. One important aspect affecting directly the attack effectiveness is the selection of the right combination of sensors, to supply inference data. Although other aspects also play crucial role (e.g. the features set, we start in this paper by focusing on the comparison of different available sensors, in terms of the inference accuracy. We consider individual sensors shipped on Android phones, and study few options of preprocessing their raw datasets as well as fusing several sensors' readings. Our results indicate an outstanding performance of the gyroscope, and the potential of sensors data fusion. However, it seems that sensors with magnetometer component or the accelerometer alone have less benefit in the context of the adverted attack.

  2. An integrated multi-sensor fusion-based deep feature learning approach for rotating machinery diagnosis

    Science.gov (United States)

    Liu, Jie; Hu, Youmin; Wang, Yan; Wu, Bo; Fan, Jikai; Hu, Zhongxu

    2018-05-01

    The diagnosis of complicated fault severity problems in rotating machinery systems is an important issue that affects the productivity and quality of manufacturing processes and industrial applications. However, it usually suffers from several deficiencies. (1) A considerable degree of prior knowledge and expertise is required to not only extract and select specific features from raw sensor signals, and but also choose a suitable fusion for sensor information. (2) Traditional artificial neural networks with shallow architectures are usually adopted and they have a limited ability to learn the complex and variable operating conditions. In multi-sensor-based diagnosis applications in particular, massive high-dimensional and high-volume raw sensor signals need to be processed. In this paper, an integrated multi-sensor fusion-based deep feature learning (IMSFDFL) approach is developed to identify the fault severity in rotating machinery processes. First, traditional statistics and energy spectrum features are extracted from multiple sensors with multiple channels and combined. Then, a fused feature vector is constructed from all of the acquisition channels. Further, deep feature learning with stacked auto-encoders is used to obtain the deep features. Finally, the traditional softmax model is applied to identify the fault severity. The effectiveness of the proposed IMSFDFL approach is primarily verified by a one-stage gearbox experimental platform that uses several accelerometers under different operating conditions. This approach can identify fault severity more effectively than the traditional approaches.

  3. Comparison of pH Data Measured with a pH Sensor Array Using Different Data Fusion Methods

    OpenAIRE

    Yi-Hung Liao; Jung-Chuan Chou

    2012-01-01

    This paper introduces different data fusion methods which are used for an electrochemical measurement using a sensor array. In this study, we used ruthenium dioxide sensing membrane pH electrodes to form a sensor array. The sensor array was used for detecting the pH values of grape wine, generic cola drink and bottled base water. The measured pH data were used for data fusion methods to increase the reliability of the measured results, and we also compared the fusion results with other differ...

  4. Robust site security using smart seismic array technology and multi-sensor data fusion

    Science.gov (United States)

    Hellickson, Dean; Richards, Paul; Reynolds, Zane; Keener, Joshua

    2010-04-01

    Traditional site security systems are susceptible to high individual sensor nuisance alarm rates that reduce the overall system effectiveness. Visual assessment of intrusions can be intensive and manually difficult as cameras are slewed by the system to non intrusion areas or as operators respond to nuisance alarms. Very little system intrusion performance data are available other than discrete sensor alarm indications that provide no real value. This paper discusses the system architecture, integration and display of a multi-sensor data fused system for wide area surveillance, local site intrusion detection and intrusion classification. The incorporation of a novel seismic array of smart sensors using FK Beamforming processing that greatly enhances the overall system detection and classification performance of the system is discussed. Recent test data demonstrates the performance of the seismic array within several different installations and its ability to classify and track moving targets at significant standoff distances with exceptional immunity to background clutter and noise. Multi-sensor data fusion is applied across a suite of complimentary sensors eliminating almost all nuisance alarms while integrating within a geographical information system to feed a visual-fusion display of the area being secured. Real-time sensor detection and intrusion classification data is presented within a visual-fusion display providing greatly enhanced situational awareness, system performance information and real-time assessment of intrusions and situations of interest with limited security operator involvement. This approach scales from a small local perimeter to very large geographical area and can be used across multiple sites controlled at a single command and control station.

  5. Bio-inspired approach for intelligent unattended ground sensors

    Science.gov (United States)

    Hueber, Nicolas; Raymond, Pierre; Hennequin, Christophe; Pichler, Alexander; Perrot, Maxime; Voisin, Philippe; Moeglin, Jean-Pierre

    2015-05-01

    Improving the surveillance capacity over wide zones requires a set of smart battery-powered Unattended Ground Sensors capable of issuing an alarm to a decision-making center. Only high-level information has to be sent when a relevant suspicious situation occurs. In this paper we propose an innovative bio-inspired approach that mimics the human bi-modal vision mechanism and the parallel processing ability of the human brain. The designed prototype exploits two levels of analysis: a low-level panoramic motion analysis, the peripheral vision, and a high-level event-focused analysis, the foveal vision. By tracking moving objects and fusing multiple criteria (size, speed, trajectory, etc.), the peripheral vision module acts as a fast relevant event detector. The foveal vision module focuses on the detected events to extract more detailed features (texture, color, shape, etc.) in order to improve the recognition efficiency. The implemented recognition core is able to acquire human knowledge and to classify in real-time a huge amount of heterogeneous data thanks to its natively parallel hardware structure. This UGS prototype validates our system approach under laboratory tests. The peripheral analysis module demonstrates a low false alarm rate whereas the foveal vision correctly focuses on the detected events. A parallel FPGA implementation of the recognition core succeeds in fulfilling the embedded application requirements. These results are paving the way of future reconfigurable virtual field agents. By locally processing the data and sending only high-level information, their energy requirements and electromagnetic signature are optimized. Moreover, the embedded Artificial Intelligence core enables these bio-inspired systems to recognize and learn new significant events. By duplicating human expertise in potentially hazardous places, our miniature visual event detector will allow early warning and contribute to better human decision making.

  6. A New Multi-Sensor Track Fusion Architecture for Multi-Sensor Information Integration

    National Research Council Canada - National Science Library

    Jean, Buddy H; Younker, John; Hung, Chih-Cheng

    2004-01-01

    .... This new technology will integrate multi-sensor information and extract integrated multi-sensor information to detect, track and identify multiple targets at any time, in any place under all weather conditions...

  7. Scalable Sensor Management for Automated Fusion and Tactical Reconnaissance

    OpenAIRE

    Walls, Thomas J.; Wilson, Michael L.; Partridge, Darin C.; Haws, Jonathan R.; Jensen, Mark D.; Johnson, Troy R.; Petersen, Brad D.; Sullivan, Stephanie W.

    2013-01-01

    The capabilities of tactical intelligence, surveillance, and reconnaissance (ISR) payloads are expanding from single sensor imagers to integrated systems-of-systems architectures. Increasingly, these systems-of-systems include multiple sensing modalities that can act as force multipliers for the intelligence analyst. Currently, the separate sensing modalities operate largely independent of one another, providing a selection of operating modes but not an integrated intelligence product. We des...

  8. Demonstration of MPV Sensor at Yuma Proving Ground, AZ

    Science.gov (United States)

    2011-06-01

    test plot in Ashland, OR, where magnetic soils have shown to have a significant effect on EMI sensors ( Pasion et al., 2008). The recorded signal...sensors was also investigated during that survey as part of SERDP MM-1573 (PI: Len Pasion , Sky Research). The MPV offers possibilities to defeat...of magnetic soils (Lhomme et al., 2008; Pasion et al., 2008). The MPV response due to sensor motion and topography over magnetic soil is predicable

  9. Sensor-Data Fusion for Multi-Person Indoor Location Estimation.

    Science.gov (United States)

    Mohebbi, Parisa; Stroulia, Eleni; Nikolaidis, Ioanis

    2017-10-18

    We consider the problem of estimating the location of people as they move and work in indoor environments. More specifically, we focus on the scenario where one of the persons of interest is unable or unwilling to carry a smartphone, or any other "wearable" device, which frequently arises in caregiver/cared-for situations. We consider the case of indoor spaces populated with anonymous binary sensors (Passive Infrared motion sensors) and eponymous wearable sensors (smartphones interacting with Estimote beacons), and we propose a solution to the resulting sensor-fusion problem. Using a data set with sensor readings collected from one-person and two-person sessions engaged in a variety of activities of daily living, we investigate the relative merits of relying solely on anonymous sensors, solely on eponymous sensors, or on their combination. We examine how the lack of synchronization across different sensing sources impacts the quality of location estimates, and discuss how it could be mitigated without resorting to device-level mechanisms. Finally, we examine the trade-off between the sensors' coverage of the monitored space and the quality of the location estimates.

  10. Soft sensor design by multivariate fusion of image features and process measurements

    DEFF Research Database (Denmark)

    Lin, Bao; Jørgensen, Sten Bay

    2011-01-01

    This paper presents a multivariate data fusion procedure for design of dynamic soft sensors where suitably selected image features are combined with traditional process measurements to enhance the performance of data-driven soft sensors. A key issue of fusing multiple sensor data, i.e. to determine...... with a multivariate analysis technique from RGB pictures. The color information is also transformed to hue, saturation and intensity components. Both sets of image features are combined with traditional process measurements to obtain an inferential model by partial least squares (PLS) regression. A dynamic PLS model...... oxides (NOx) emission of cement kilns. On-site tests demonstrate improved performance over soft sensors based on conventional process measurements only....

  11. Automatic tracking of wake vortices using ground-wind sensor data

    Science.gov (United States)

    1977-01-03

    Algorithms for automatic tracking of wake vortices using ground-wind anemometer : data are developed. Methods of bad-data suppression, track initiation, and : track termination are included. An effective sensor-failure detection-and identification : ...

  12. The development of fusion sensor techniques for condition monitoring of a check valve

    International Nuclear Information System (INIS)

    Seong, S.H.; Kim, J.S.; Hur, S.; Kim, J.T.; Park, W.M.; Cha, D.B.

    2004-01-01

    The failures of check valves are one of the most important problems in nuclear power plants because the reverse flows through the failed check valve impact on the healthy hydraulic loop. The present test method of finding out the mechanical failure of a check valve is very risky in the radiated environments during normal operation. In addition, the detection of failures in the overhaul period is very costly and tedious because many check valves are used in the plants and manual disassembly work is required. We have suggested the fusion sensor technology for detecting the failures of check valves through measuring and analyzing the backward leakage flow and mechanical vibration without disassembling the check valve. The fusion sensor means that more than two sensors are used in order to identify and analyze the changes of the frequency response between the failed check valve and healthy check valve. We use the accelerometer and acoustic emission sensor as an alternative to the fusion sensor methodology. We have found that the acoustic emission sensor would be capable of directly detecting a high frequency acoustic wave generated from backward leakage flow itself at a low pressure and temperature. The accelerometer for detecting the mechanical vibration induced from leakage flows would, also, be useful at a high pressure and temperature from the previous studies. The effectiveness of this system is that it is possible for predictive maintenance and information of the problem valve will be captured and it reduces the radiation exposure for the maintenance personnel during power operation as well as the maintenance period. (orig.)

  13. Unique sensor fusion system for coordinate-measuring machine tasks

    Science.gov (United States)

    Nashman, Marilyn; Yoshimi, Billibon; Hong, Tsai Hong; Rippey, William G.; Herman, Martin

    1997-09-01

    This paper describes a real-time hierarchical system that fuses data from vision and touch sensors to improve the performance of a coordinate measuring machine (CMM) used for dimensional inspection tasks. The system consists of sensory processing, world modeling, and task decomposition modules. It uses the strengths of each sensor -- the precision of the CMM scales and the analog touch probe and the global information provided by the low resolution camera -- to improve the speed and flexibility of the inspection task. In the experiment described, the vision module performs all computations in image coordinate space. The part's boundaries are extracted during an initialization process and then the probe's position is continuously updated as it scans and measures the part surface. The system fuses the estimated probe velocity and distance to the part boundary in image coordinates with the estimated velocity and probe position provided by the CMM controller. The fused information provides feedback to the monitor controller as it guides the touch probe to scan the part. We also discuss integrating information from the vision system and the probe to autonomously collect data for 2-D to 3-D calibration, and work to register computer aided design (CAD) models with images of parts in the workplace.

  14. A Bayes-Maximum Entropy method for multi-sensor data fusion

    Energy Technology Data Exchange (ETDEWEB)

    Beckerman, M.

    1991-01-01

    In this paper we introduce a Bayes-Maximum Entropy formalism for multi-sensor data fusion, and present an application of this methodology to the fusion of ultrasound and visual sensor data as acquired by a mobile robot. In our approach the principle of maximum entropy is applied to the construction of priors and likelihoods from the data. Distances between ultrasound and visual points of interest in a dual representation are used to define Gibbs likelihood distributions. Both one- and two-dimensional likelihoods are presented, and cast into a form which makes explicit their dependence upon the mean. The Bayesian posterior distributions are used to test a null hypothesis, and Maximum Entropy Maps used for navigation are updated using the resulting information from the dual representation. 14 refs., 9 figs.

  15. Sensor fusion IV: Control paradigms and data structures; Proceedings of the Meeting, Boston, MA, Nov. 12-15, 1991

    Science.gov (United States)

    Schenker, Paul S. (Editor)

    1992-01-01

    Various papers on control paradigms and data structures in sensor fusion are presented. The general topics addressed include: decision models and computational methods, sensor modeling and data representation, active sensing strategies, geometric planning and visualization, task-driven sensing, motion analysis, models motivated biology and psychology, decentralized detection and distributed decision, data fusion architectures, robust estimation of shapes and features, application and implementation. Some of the individual subjects considered are: the Firefly experiment on neural networks for distributed sensor data fusion, manifold traversing as a model for learning control of autonomous robots, choice of coordinate systems for multiple sensor fusion, continuous motion using task-directed stereo vision, interactive and cooperative sensing and control for advanced teleoperation, knowledge-based imaging for terrain analysis, physical and digital simulations for IVA robotics.

  16. A Dempster-Shafer Method for Multi-Sensor Fusion

    Science.gov (United States)

    2012-03-01

    Sacroiliac Somatic Dysfunction .” The Journal of the American Osteopathic Association, 110(2): 81-86 (1 February 2010). http://www.jaoa.org/content/110/2/81/F3...cadence, stride length, step length, joint angles (hip, knee, ankle), speed, and ground contact time [11; 27]. These measurements are easy to obtain because...Conference of Radar. 393-396. Beijing: October 1996. 27. “ Joint Function & GAIT Analysis.” http://wings.buffalo.edu/eng/mae/courses/417- 517/Orthopaedic

  17. Vehicle recognition and tracking using a generic multi-sensor and multi-algorithm fusion approach

    OpenAIRE

    Nashashibi , Fawzi; Khammari , Ayoub; Laurgeau , Claude

    2008-01-01

    International audience; This paper tackles the problem of improving the robustness of vehicle detection for Adaptive Cruise Control (ACC) applications. Our approach is based on a multisensor and a multialgorithms data fusion for vehicle detection and recognition. Our architecture combines two sensors: a frontal camera and a laser scanner. The improvement of the robustness stems from two aspects. First, we addressed the vision-based detection by developing an original approach based on fine gr...

  18. Sensor data fusion for textured reconstruction and virtual representation of alpine scenes

    Science.gov (United States)

    Häufel, Gisela; Bulatov, Dimitri; Solbrig, Peter

    2017-10-01

    The concept of remote sensing is to provide information about a wide-range area without making physical contact with this area. If, additionally to satellite imagery, images and videos taken by drones provide a more up-to-date data at a higher resolution, or accurate vector data is downloadable from the Internet, one speaks of sensor data fusion. The concept of sensor data fusion is relevant for many applications, such as virtual tourism, automatic navigation, hazard assessment, etc. In this work, we describe sensor data fusion aiming to create a semantic 3D model of an extremely interesting yet challenging dataset: An alpine region in Southern Germany. A particular challenge of this work is that rock faces including overhangs are present in the input airborne laser point cloud. The proposed procedure for identification and reconstruction of overhangs from point clouds comprises four steps: Point cloud preparation, filtering out vegetation, mesh generation and texturing. Further object types are extracted in several interesting subsections of the dataset: Building models with textures from UAV (Unmanned Aerial Vehicle) videos, hills reconstructed as generic surfaces and textured by the orthophoto, individual trees detected by the watershed algorithm, as well as the vector data for roads retrieved from openly available shapefiles and GPS-device tracks. We pursue geo-specific reconstruction by assigning texture and width to roads of several pre-determined types and modeling isolated trees and rocks using commercial software. For visualization and simulation of the area, we have chosen the simulation system Virtual Battlespace 3 (VBS3). It becomes clear that the proposed concept of sensor data fusion allows a coarse reconstruction of a large scene and, at the same time, an accurate and up-to-date representation of its relevant subsections, in which simulation can take place.

  19. Multi-sensor radiation detection, imaging, and fusion

    Energy Technology Data Exchange (ETDEWEB)

    Vetter, Kai [Department of Nuclear Engineering, University of California, Berkeley, CA 94720 (United States); Nuclear Science Division, Lawrence Berkeley National Laboratory, Berkeley, CA 94720 (United States)

    2016-01-01

    Glenn Knoll was one of the leaders in the field of radiation detection and measurements and shaped this field through his outstanding scientific and technical contributions, as a teacher, his personality, and his textbook. His Radiation Detection and Measurement book guided me in my studies and is now the textbook in my classes in the Department of Nuclear Engineering at UC Berkeley. In the spirit of Glenn, I will provide an overview of our activities at the Berkeley Applied Nuclear Physics program reflecting some of the breadth of radiation detection technologies and their applications ranging from fundamental studies in physics to biomedical imaging and to nuclear security. I will conclude with a discussion of our Berkeley Radwatch and Resilient Communities activities as a result of the events at the Dai-ichi nuclear power plant in Fukushima, Japan more than 4 years ago. - Highlights: • .Electron-tracking based gamma-ray momentum reconstruction. • .3D volumetric and 3D scene fusion gamma-ray imaging. • .Nuclear Street View integrates and associates nuclear radiation features with specific objects in the environment. • Institute for Resilient Communities combines science, education, and communities to minimize impact of disastrous events.

  20. Unmanned Ground Vehicle Navigation and Coverage Hole Patching in Wireless Sensor Networks

    Science.gov (United States)

    Zhang, Guyu

    2013-01-01

    This dissertation presents a study of an Unmanned Ground Vehicle (UGV) navigation and coverage hole patching in coordinate-free and localization-free Wireless Sensor Networks (WSNs). Navigation and coverage maintenance are related problems since coverage hole patching requires effective navigation in the sensor network environment. A…

  1. Exploiting Social Media Sensor Networks through Novel Data Fusion Techniques

    Energy Technology Data Exchange (ETDEWEB)

    Kouri, Tina [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States)

    2017-11-01

    Unprecedented amounts of data are continuously being generated by sensors (“hard” data) and by humans (“soft” data), and this data needs to be exploited to its full potential. The first step in exploiting this data is determine how the hard and soft data are related to each other. In this project we fuse hard and soft data, using the attributes of each (e.g., time and space), to gain more information about interesting events. Next, we attempt to use social networking textual data to predict the present (i.e., predict that an interesting event is occurring and details about the event) using data mining, machine learning, natural language processing, and text analysis techniques.

  2. Sensor Fusion of Position- and Micro-Sensors (MEMS) integrated in a Wireless Sensor Network for movement detection in landslide areas

    Science.gov (United States)

    Arnhardt, Christian; Fernández-Steeger, Tomas; Azzam, Rafig

    2010-05-01

    Monitoring systems in landslide areas are important elements of effective Early Warning structures. Data acquisition and retrieval allows the detection of movement processes and thus is essential to generate warnings in time. Apart from the precise measurement, the reliability of data is fundamental, because outliers can trigger false alarms and leads to the loss of acceptance of such systems. For the monitoring of mass movements and their risk it is important to know, if there is movement, how fast it is and how trustworthy is the information. The joint project "Sensorbased landslide early warning system" (SLEWS) deals with these questions, and tries to improve data quality and to reduce false alarm rates, due to the combination of sensor date (sensor fusion). The project concentrates on the development of a prototypic Alarm- and Early Warning system (EWS) for different types of landslides by using various low-cost sensors, integrated in a wireless sensor network (WSN). The network consists of numerous connection points (nodes) that transfer data directly or over other nodes (Multi-Hop) in real-time to a data collection point (gateway). From there all the data packages are transmitted to a spatial data infrastructure (SDI) for further processing, analyzing and visualizing with respect to end-user specifications. The ad-hoc characteristic of the network allows the autonomous crosslinking of the nodes according to existing connections and communication strength. Due to the independent finding of new or more stable connections (self healing) a breakdown of the whole system is avoided. The bidirectional data stream enables the receiving of data from the network but also allows the transfer of commands and pointed requests into the WSN. For the detection of surface deformations in landslide areas small low-cost Micro-Electro-Mechanical-Systems (MEMS) and positionsensors from the automobile industries, different industrial applications and from other measurement

  3. Sensor-Data Fusion for Multi-Person Indoor Location Estimation

    Directory of Open Access Journals (Sweden)

    Parisa Mohebbi

    2017-10-01

    Full Text Available We consider the problem of estimating the location of people as they move and work in indoor environments. More specifically, we focus on the scenario where one of the persons of interest is unable or unwilling to carry a smartphone, or any other “wearable” device, which frequently arises in caregiver/cared-for situations. We consider the case of indoor spaces populated with anonymous binary sensors (Passive Infrared motion sensors and eponymous wearable sensors (smartphones interacting with Estimote beacons, and we propose a solution to the resulting sensor-fusion problem. Using a data set with sensor readings collected from one-person and two-person sessions engaged in a variety of activities of daily living, we investigate the relative merits of relying solely on anonymous sensors, solely on eponymous sensors, or on their combination. We examine how the lack of synchronization across different sensing sources impacts the quality of location estimates, and discuss how it could be mitigated without resorting to device-level mechanisms. Finally, we examine the trade-off between the sensors’ coverage of the monitored space and the quality of the location estimates.

  4. Unattended Ground Sensors for Expeditionary Force 21 Intelligence Collections

    Science.gov (United States)

    2015-06-01

    little impact on modern intelligence collections. This thesis analyzes and compares the units and individual Marine skillsets that employ UGS, and the...the sensor employment planning cycle, and the socialization of this plan through the proper chain-of-command [4]. Figure 8 depicts the Sensor...the use of newly developed cellphone based technologies and emerging UGS capabilities to assist in Listening Post/ Observation Post (LP/OP

  5. Camera-laser fusion sensor system and environmental recognition for humanoids in disaster scenarios

    International Nuclear Information System (INIS)

    Lee, Inho; Oh, Jaesung; Oh, Jun-Ho; Kim, Inhyeok

    2017-01-01

    This research aims to develop a vision sensor system and a recognition algorithm to enable a humanoid to operate autonomously in a disaster environment. In disaster response scenarios, humanoid robots that perform manipulation and locomotion tasks must identify the objects in the environment from those challenged by the call by the United States’ Defense Advanced Research Projects Agency, e.g., doors, valves, drills, debris, uneven terrains, and stairs, among others. In order for a humanoid to undertake a number of tasks, we con- struct a camera–laser fusion system and develop an environmental recognition algorithm. Laser distance sensor and motor are used to obtain 3D cloud data. We project the 3D cloud data onto a 2D image according to the intrinsic parameters of the camera and the distortion model of the lens. In this manner, our fusion sensor system performs functions such as those performed by the RGB-D sensor gener- ally used in segmentation research. Our recognition algorithm is based on super-pixel segmentation and random sampling. The proposed approach clusters the unorganized cloud data according to geometric characteristics, namely, proximity and co-planarity. To assess the feasibility of our system and algorithm, we utilize the humanoid robot, DRC-HUBO, and the results are demonstrated in the accompanying video.

  6. Marker-Based Multi-Sensor Fusion Indoor Localization System for Micro Air Vehicles.

    Science.gov (United States)

    Xing, Boyang; Zhu, Quanmin; Pan, Feng; Feng, Xiaoxue

    2018-05-25

    A novel multi-sensor fusion indoor localization algorithm based on ArUco marker is designed in this paper. The proposed ArUco mapping algorithm can build and correct the map of markers online with Grubbs criterion and K-mean clustering, which avoids the map distortion due to lack of correction. Based on the conception of multi-sensor information fusion, the federated Kalman filter is utilized to synthesize the multi-source information from markers, optical flow, ultrasonic and the inertial sensor, which can obtain a continuous localization result and effectively reduce the position drift due to the long-term loss of markers in pure marker localization. The proposed algorithm can be easily implemented in a hardware of one Raspberry Pi Zero and two STM32 micro controllers produced by STMicroelectronics (Geneva, Switzerland). Thus, a small-size and low-cost marker-based localization system is presented. The experimental results show that the speed estimation result of the proposed system is better than Px4flow, and it has the centimeter accuracy of mapping and positioning. The presented system not only gives satisfying localization precision, but also has the potential to expand other sensors (such as visual odometry, ultra wideband (UWB) beacon and lidar) to further improve the localization performance. The proposed system can be reliably employed in Micro Aerial Vehicle (MAV) visual localization and robotics control.

  7. Camera-laser fusion sensor system and environmental recognition for humanoids in disaster scenarios

    Energy Technology Data Exchange (ETDEWEB)

    Lee, Inho [Institute for Human and Machine Cognition (IHMC), Florida (United States); Oh, Jaesung; Oh, Jun-Ho [Korea Advanced Institute of Science and Technology (KAIST), Daejeon (Korea, Republic of); Kim, Inhyeok [NAVER Green Factory, Seongnam (Korea, Republic of)

    2017-06-15

    This research aims to develop a vision sensor system and a recognition algorithm to enable a humanoid to operate autonomously in a disaster environment. In disaster response scenarios, humanoid robots that perform manipulation and locomotion tasks must identify the objects in the environment from those challenged by the call by the United States’ Defense Advanced Research Projects Agency, e.g., doors, valves, drills, debris, uneven terrains, and stairs, among others. In order for a humanoid to undertake a number of tasks, we con- struct a camera–laser fusion system and develop an environmental recognition algorithm. Laser distance sensor and motor are used to obtain 3D cloud data. We project the 3D cloud data onto a 2D image according to the intrinsic parameters of the camera and the distortion model of the lens. In this manner, our fusion sensor system performs functions such as those performed by the RGB-D sensor gener- ally used in segmentation research. Our recognition algorithm is based on super-pixel segmentation and random sampling. The proposed approach clusters the unorganized cloud data according to geometric characteristics, namely, proximity and co-planarity. To assess the feasibility of our system and algorithm, we utilize the humanoid robot, DRC-HUBO, and the results are demonstrated in the accompanying video.

  8. Two-level Robust Measurement Fusion Kalman Filter for Clustering Sensor Networks

    Institute of Scientific and Technical Information of China (English)

    ZHANG Peng; QI Wen-Juan; DENG Zi-Li

    2014-01-01

    This paper investigates the distributed fusion Kalman filtering over clustering sensor networks. The sensor network is partitioned as clusters by the nearest neighbor rule and each cluster consists of sensing nodes and cluster-head. Using the minimax robust estimation principle, based on the worst-case conservative system with the conservative upper bounds of noise variances, two-level robust measurement fusion Kalman filter is presented for the clustering sensor network systems with uncertain noise variances. It can significantly reduce the communication load and save energy when the number of sensors is very large. A Lyapunov equation approach for the robustness analysis is presented, by which the robustness of the local and fused Kalman filters is proved. The concept of the robust accuracy is presented, and the robust accuracy relations among the local and fused robust Kalman filters are proved. It is proved that the robust accuracy of the two-level weighted measurement fuser is equal to that of the global centralized robust fuser and is higher than those of each local robust filter and each local weighted measurement fuser. A simulation example shows the correctness and effectiveness of the proposed results.

  9. Marker-Based Multi-Sensor Fusion Indoor Localization System for Micro Air Vehicles

    Directory of Open Access Journals (Sweden)

    Boyang Xing

    2018-05-01

    Full Text Available A novel multi-sensor fusion indoor localization algorithm based on ArUco marker is designed in this paper. The proposed ArUco mapping algorithm can build and correct the map of markers online with Grubbs criterion and K-mean clustering, which avoids the map distortion due to lack of correction. Based on the conception of multi-sensor information fusion, the federated Kalman filter is utilized to synthesize the multi-source information from markers, optical flow, ultrasonic and the inertial sensor, which can obtain a continuous localization result and effectively reduce the position drift due to the long-term loss of markers in pure marker localization. The proposed algorithm can be easily implemented in a hardware of one Raspberry Pi Zero and two STM32 micro controllers produced by STMicroelectronics (Geneva, Switzerland. Thus, a small-size and low-cost marker-based localization system is presented. The experimental results show that the speed estimation result of the proposed system is better than Px4flow, and it has the centimeter accuracy of mapping and positioning. The presented system not only gives satisfying localization precision, but also has the potential to expand other sensors (such as visual odometry, ultra wideband (UWB beacon and lidar to further improve the localization performance. The proposed system can be reliably employed in Micro Aerial Vehicle (MAV visual localization and robotics control.

  10. IMU-Based Gait Recognition Using Convolutional Neural Networks and Multi-Sensor Fusion

    Directory of Open Access Journals (Sweden)

    Omid Dehzangi

    2017-11-01

    Full Text Available The wide spread usage of wearable sensors such as in smart watches has provided continuous access to valuable user generated data such as human motion that could be used to identify an individual based on his/her motion patterns such as, gait. Several methods have been suggested to extract various heuristic and high-level features from gait motion data to identify discriminative gait signatures and distinguish the target individual from others. However, the manual and hand crafted feature extraction is error prone and subjective. Furthermore, the motion data collected from inertial sensors have complex structure and the detachment between manual feature extraction module and the predictive learning models might limit the generalization capabilities. In this paper, we propose a novel approach for human gait identification using time-frequency (TF expansion of human gait cycles in order to capture joint 2 dimensional (2D spectral and temporal patterns of gait cycles. Then, we design a deep convolutional neural network (DCNN learning to extract discriminative features from the 2D expanded gait cycles and jointly optimize the identification model and the spectro-temporal features in a discriminative fashion. We collect raw motion data from five inertial sensors placed at the chest, lower-back, right hand wrist, right knee, and right ankle of each human subject synchronously in order to investigate the impact of sensor location on the gait identification performance. We then present two methods for early (input level and late (decision score level multi-sensor fusion to improve the gait identification generalization performance. We specifically propose the minimum error score fusion (MESF method that discriminatively learns the linear fusion weights of individual DCNN scores at the decision level by minimizing the error rate on the training data in an iterative manner. 10 subjects participated in this study and hence, the problem is a 10-class

  11. RGB-D, Laser and Thermal Sensor Fusion for People following in a Mobile Robot

    Directory of Open Access Journals (Sweden)

    Loreto Susperregi

    2013-06-01

    Full Text Available Detecting and tracking people is a key capability for robots that operate in populated environments. In this paper, we used a multiple sensor fusion approach that combines three kinds of sensors in order to detect people using RGB-D vision, lasers and a thermal sensor mounted on a mobile platform. The Kinect sensor offers a rich data set at a significantly low cost, however, there are some limitations to its use in a mobile platform, mainly that the Kinect algorithms for people detection rely on images captured by a static camera. To cope with these limitations, this work is based on the combination of the Kinect and a Hokuyo laser and a thermopile array sensor. A real-time particle filter system merges the information provided by the sensors and calculates the position of the target, using probabilistic leg and thermal patterns, image features and optical flow to this end. Experimental results carried out with a mobile platform in a Science museum have shown that the combination of different sensory cues increases the reliability of the people following system.

  12. A Neural Network Approach for Building An Obstacle Detection Model by Fusion of Proximity Sensors Data

    Science.gov (United States)

    Peralta, Emmanuel; Vargas, Héctor; Hermosilla, Gabriel

    2018-01-01

    Proximity sensors are broadly used in mobile robots for obstacle detection. The traditional calibration process of this kind of sensor could be a time-consuming task because it is usually done by identification in a manual and repetitive way. The resulting obstacles detection models are usually nonlinear functions that can be different for each proximity sensor attached to the robot. In addition, the model is highly dependent on the type of sensor (e.g., ultrasonic or infrared), on changes in light intensity, and on the properties of the obstacle such as shape, colour, and surface texture, among others. That is why in some situations it could be useful to gather all the measurements provided by different kinds of sensor in order to build a unique model that estimates the distances to the obstacles around the robot. This paper presents a novel approach to get an obstacles detection model based on the fusion of sensors data and automatic calibration by using artificial neural networks. PMID:29495338

  13. Large-Scale, Parallel, Multi-Sensor Atmospheric Data Fusion Using Cloud Computing

    Science.gov (United States)

    Wilson, B. D.; Manipon, G.; Hua, H.; Fetzer, E. J.

    2013-12-01

    NASA's Earth Observing System (EOS) is an ambitious facility for studying global climate change. The mandate now is to combine measurements from the instruments on the 'A-Train' platforms (AIRS, AMSR-E, MODIS, MISR, MLS, and CloudSat) and other Earth probes to enable large-scale studies of climate change over decades. Moving to multi-sensor, long-duration analyses of important climate variables presents serious challenges for large-scale data mining and fusion. For example, one might want to compare temperature and water vapor retrievals from one instrument (AIRS) to another (MODIS), and to a model (MERRA), stratify the comparisons using a classification of the 'cloud scenes' from CloudSat, and repeat the entire analysis over 10 years of data. To efficiently assemble such datasets, we are utilizing Elastic Computing in the Cloud and parallel map/reduce-based algorithms. However, these problems are Data Intensive computing so the data transfer times and storage costs (for caching) are key issues. SciReduce is a Hadoop-like parallel analysis system, programmed in parallel python, that is designed from the ground up for Earth science. SciReduce executes inside VMWare images and scales to any number of nodes in the Cloud. Unlike Hadoop, SciReduce operates on bundles of named numeric arrays, which can be passed in memory or serialized to disk in netCDF4 or HDF5. Figure 1 shows the architecture of the full computational system, with SciReduce at the core. Multi-year datasets are automatically 'sharded' by time and space across a cluster of nodes so that years of data (millions of files) can be processed in a massively parallel way. Input variables (arrays) are pulled on-demand into the Cloud using OPeNDAP URLs or other subsetting services, thereby minimizing the size of the cached input and intermediate datasets. We are using SciReduce to automate the production of multiple versions of a ten-year A-Train water vapor climatology under a NASA MEASURES grant. We will

  14. Design and Analysis of a Data Fusion Scheme in Mobile Wireless Sensor Networks Based on Multi-Protocol Mobile Agents

    Directory of Open Access Journals (Sweden)

    Chunxue Wu

    2017-11-01

    Full Text Available Sensors are increasingly used in mobile environments with wireless network connections. Multiple sensor types measure distinct aspects of the same event. Their measurements are then combined to produce integrated, reliable results. As the number of sensors in networks increases, low energy requirements and changing network connections complicate event detection and measurement. We present a data fusion scheme for use in mobile wireless sensor networks with high energy efficiency and low network delays, that still produces reliable results. In the first phase, we used a network simulation where mobile agents dynamically select the next hop migration node based on the stability parameter of the link, and perform the data fusion at the migration node. Agents use the fusion results to decide if it should return the fusion results to the processing center or continue to collect more data. In the second phase. The feasibility of data fusion at the node level is confirmed by an experimental design where fused data from color sensors show near-identical results to actual physical temperatures. These results are potentially important for new large-scale sensor network applications.

  15. Design and Analysis of a Data Fusion Scheme in Mobile Wireless Sensor Networks Based on Multi-Protocol Mobile Agents.

    Science.gov (United States)

    Wu, Chunxue; Wu, Wenliang; Wan, Caihua; Bekkering, Ernst; Xiong, Naixue

    2017-11-03

    Sensors are increasingly used in mobile environments with wireless network connections. Multiple sensor types measure distinct aspects of the same event. Their measurements are then combined to produce integrated, reliable results. As the number of sensors in networks increases, low energy requirements and changing network connections complicate event detection and measurement. We present a data fusion scheme for use in mobile wireless sensor networks with high energy efficiency and low network delays, that still produces reliable results. In the first phase, we used a network simulation where mobile agents dynamically select the next hop migration node based on the stability parameter of the link, and perform the data fusion at the migration node. Agents use the fusion results to decide if it should return the fusion results to the processing center or continue to collect more data. In the second phase. The feasibility of data fusion at the node level is confirmed by an experimental design where fused data from color sensors show near-identical results to actual physical temperatures. These results are potentially important for new large-scale sensor network applications.

  16. Solid state magnetic field sensors for micro unattended ground networks using spin dependent tunneling

    Science.gov (United States)

    Tondra, Mark; Nordman, Catherine A.; Lange, Erik H.; Reed, Daniel; Jander, Albrect; Akou, Seraphin; Daughton, James

    2001-09-01

    Micro Unattended Ground Sensor Networks will likely employ magnetic sensors, primarily for discrimination of objects as opposed to initial detection. These magnetic sensors, then, must fit within very small cost, size, and power budgets to be compatible with the envisioned sensor suites. Also, a high degree of sensitivity is required to minimize the number of sensor cells required to survey a given area in the field. Solid state magnetoresistive sensors, with their low cost, small size, and ease of integration, are excellent candidates for these applications assuming that their power and sensitivity performance are acceptable. SDT devices have been fabricated into prototype magnetic field sensors suitable for use in micro unattended ground sensor networks. They are housed in tiny SOIC 8-pin packages and mounted on a circuit board with required voltage regulation, signal amplification and conditioning, and sensor control and communications functions. The best sensitivity results to date are 289 pT/rt. Hz at 1 Hz, and and 7 pT/rt. Hz at f > 10 kHz. Expected near term improvements in performance would bring these levels to approximately 10 pT/rt Hz at 1 Hz and approximately 1 pT/rt. Hz at > 1 kHz.

  17. Fusion

    CERN Document Server

    Mahaffey, James A

    2012-01-01

    As energy problems of the world grow, work toward fusion power continues at a greater pace than ever before. The topic of fusion is one that is often met with the most recognition and interest in the nuclear power arena. Written in clear and jargon-free prose, Fusion explores the big bang of creation to the blackout death of worn-out stars. A brief history of fusion research, beginning with the first tentative theories in the early 20th century, is also discussed, as well as the race for fusion power. This brand-new, full-color resource examines the various programs currently being funded or p

  18. Low-Cost Ground Sensor Network for Intrusion Detection

    Science.gov (United States)

    2017-09-01

    their suitability to our research. 1. Wireless Sensor Networks The backend network infrastructure forms the communication links for the network...were not ideal as they were perpetually turned on. Our research considered the backend communication infrastructure and its power requirements when...7 3. Border Patrol— Mobile Situation Awareness Tool (MSAT

  19. Multi-sensor information fusion method for vibration fault diagnosis of rolling bearing

    Science.gov (United States)

    Jiao, Jing; Yue, Jianhai; Pei, Di

    2017-10-01

    Bearing is a key element in high-speed electric multiple unit (EMU) and any defect of it can cause huge malfunctioning of EMU under high operation speed. This paper presents a new method for bearing fault diagnosis based on least square support vector machine (LS-SVM) in feature-level fusion and Dempster-Shafer (D-S) evidence theory in decision-level fusion which were used to solve the problems about low detection accuracy, difficulty in extracting sensitive characteristics and unstable diagnosis system of single-sensor in rolling bearing fault diagnosis. Wavelet de-nosing technique was used for removing the signal noises. LS-SVM was used to make pattern recognition of the bearing vibration signal, and then fusion process was made according to the D-S evidence theory, so as to realize recognition of bearing fault. The results indicated that the data fusion method improved the performance of the intelligent approach in rolling bearing fault detection significantly. Moreover, the results showed that this method can efficiently improve the accuracy of fault diagnosis.

  20. A near-optimal low complexity sensor fusion technique for accurate indoor localization based on ultrasound time of arrival measurements from low-quality sensors

    Science.gov (United States)

    Mitilineos, Stelios A.; Argyreas, Nick D.; Thomopoulos, Stelios C. A.

    2009-05-01

    A fusion-based localization technique for location-based services in indoor environments is introduced herein, based on ultrasound time-of-arrival measurements from multiple off-the-shelf range estimating sensors which are used in a market-available localization system. In-situ field measurements results indicated that the respective off-the-shelf system was unable to estimate position in most of the cases, while the underlying sensors are of low-quality and yield highly inaccurate range and position estimates. An extensive analysis is performed and a model of the sensor-performance characteristics is established. A low-complexity but accurate sensor fusion and localization technique is then developed, which consists inof evaluating multiple sensor measurements and selecting the one that is considered most-accurate based on the underlying sensor model. Optimality, in the sense of a genie selecting the optimum sensor, is subsequently evaluated and compared to the proposed technique. The experimental results indicate that the proposed fusion method exhibits near-optimal performance and, albeit being theoretically suboptimal, it largely overcomes most flaws of the underlying single-sensor system resulting in a localization system of increased accuracy, robustness and availability.

  1. On the Use of Sensor Fusion to Reduce the Impact of Rotational and Additive Noise in Human Activity Recognition

    Directory of Open Access Journals (Sweden)

    Ignacio Rojas

    2012-06-01

    Full Text Available The main objective of fusion mechanisms is to increase the individual reliability of the systems through the use of the collectivity knowledge. Moreover, fusion models are also intended to guarantee a certain level of robustness. This is particularly required for problems such as human activity recognition where runtime changes in the sensor setup seriously disturb the reliability of the initial deployed systems. For commonly used recognition systems based on inertial sensors, these changes are primarily characterized as sensor rotations, displacements or faults related to the batteries or calibration. In this work we show the robustness capabilities of a sensor-weighted fusion model when dealing with such disturbances under different circumstances. Using the proposed method, up to 60% outperformance is obtained when a minority of the sensors are artificially rotated or degraded, independent of the level of disturbance (noise imposed. These robustness capabilities also apply for any number of sensors affected by a low to moderate noise level. The presented fusion mechanism compensates the poor performance that otherwise would be obtained when just a single sensor is considered.

  2. Identifying and tracking pedestrians based on sensor fusion and motion stability predictions.

    Science.gov (United States)

    Musleh, Basam; García, Fernando; Otamendi, Javier; Armingol, José Maria; de la Escalera, Arturo

    2010-01-01

    The lack of trustworthy sensors makes development of Advanced Driver Assistance System (ADAS) applications a tough task. It is necessary to develop intelligent systems by combining reliable sensors and real-time algorithms to send the proper, accurate messages to the drivers. In this article, an application to detect and predict the movement of pedestrians in order to prevent an imminent collision has been developed and tested under real conditions. The proposed application, first, accurately measures the position of obstacles using a two-sensor hybrid fusion approach: a stereo camera vision system and a laser scanner. Second, it correctly identifies pedestrians using intelligent algorithms based on polylines and pattern recognition related to leg positions (laser subsystem) and dense disparity maps and u-v disparity (vision subsystem). Third, it uses statistical validation gates and confidence regions to track the pedestrian within the detection zones of the sensors and predict their position in the upcoming frames. The intelligent sensor application has been experimentally tested with success while tracking pedestrians that cross and move in zigzag fashion in front of a vehicle.

  3. Identifying and Tracking Pedestrians Based on Sensor Fusion and Motion Stability Predictions

    Directory of Open Access Journals (Sweden)

    Arturo de la Escalera

    2010-08-01

    Full Text Available The lack of trustworthy sensors makes development of Advanced Driver Assistance System (ADAS applications a tough task. It is necessary to develop intelligent systems by combining reliable sensors and real-time algorithms to send the proper, accurate messages to the drivers. In this article, an application to detect and predict the movement of pedestrians in order to prevent an imminent collision has been developed and tested under real conditions. The proposed application, first, accurately measures the position of obstacles using a two-sensor hybrid fusion approach: a stereo camera vision system and a laser scanner. Second, it correctly identifies pedestrians using intelligent algorithms based on polylines and pattern recognition related to leg positions (laser subsystem and dense disparity maps and u-v disparity (vision subsystem. Third, it uses statistical validation gates and confidence regions to track the pedestrian within the detection zones of the sensors and predict their position in the upcoming frames. The intelligent sensor application has been experimentally tested with success while tracking pedestrians that cross and move in zigzag fashion in front of a vehicle.

  4. Design and performance of an integrated ground and space sensor web for monitoring active volcanoes.

    Science.gov (United States)

    Lahusen, Richard; Song, Wenzhan; Kedar, Sharon; Shirazi, Behrooz; Chien, Steve; Doubleday, Joshua; Davies, Ashley; Webb, Frank; Dzurisin, Dan; Pallister, John

    2010-05-01

    An interdisciplinary team of computer, earth and space scientists collaborated to develop a sensor web system for rapid deployment at active volcanoes. The primary goals of this Optimized Autonomous Space In situ Sensorweb (OASIS) are to: 1) integrate complementary space and in situ (ground-based) elements into an interactive, autonomous sensor web; 2) advance sensor web power and communication resource management technology; and 3) enable scalability for seamless addition sensors and other satellites into the sensor web. This three-year project began with a rigorous multidisciplinary interchange that resulted in definition of system requirements to guide the design of the OASIS network and to achieve the stated project goals. Based on those guidelines, we have developed fully self-contained in situ nodes that integrate GPS, seismic, infrasonic and lightning (ash) detection sensors. The nodes in the wireless sensor network are linked to the ground control center through a mesh network that is highly optimized for remote geophysical monitoring. OASIS also features an autonomous bidirectional interaction between ground nodes and instruments on the EO-1 space platform through continuous analysis and messaging capabilities at the command and control center. Data from both the in situ sensors and satellite-borne hyperspectral imaging sensors stream into a common database for real-time visualization and analysis by earth scientists. We have successfully completed a field deployment of 15 nodes within the crater and on the flanks of Mount St. Helens, Washington. The demonstration that sensor web technology facilitates rapid network deployments and that we can achieve real-time continuous data acquisition. We are now optimizing component performance and improving user interaction for additional deployments at erupting volcanoes in 2010.

  5. Large-Scale, Parallel, Multi-Sensor Data Fusion in the Cloud

    Science.gov (United States)

    Wilson, B. D.; Manipon, G.; Hua, H.

    2012-12-01

    NASA's Earth Observing System (EOS) is an ambitious facility for studying global climate change. The mandate now is to combine measurements from the instruments on the "A-Train" platforms (AIRS, AMSR-E, MODIS, MISR, MLS, and CloudSat) and other Earth probes to enable large-scale studies of climate change over periods of years to decades. However, moving from predominantly single-instrument studies to a multi-sensor, measurement-based model for long-duration analysis of important climate variables presents serious challenges for large-scale data mining and data fusion. For example, one might want to compare temperature and water vapor retrievals from one instrument (AIRS) to another instrument (MODIS), and to a model (ECMWF), stratify the comparisons using a classification of the "cloud scenes" from CloudSat, and repeat the entire analysis over years of AIRS data. To perform such an analysis, one must discover & access multiple datasets from remote sites, find the space/time "matchups" between instruments swaths and model grids, understand the quality flags and uncertainties for retrieved physical variables, assemble merged datasets, and compute fused products for further scientific and statistical analysis. To efficiently assemble such decade-scale datasets in a timely manner, we are utilizing Elastic Computing in the Cloud and parallel map/reduce-based algorithms. "SciReduce" is a Hadoop-like parallel analysis system, programmed in parallel python, that is designed from the ground up for Earth science. SciReduce executes inside VMWare images and scales to any number of nodes in the Cloud. Unlike Hadoop, in which simple tuples (keys & values) are passed between the map and reduce functions, SciReduce operates on bundles of named numeric arrays, which can be passed in memory or serialized to disk in netCDF4 or HDF5. Thus, SciReduce uses the native datatypes (geolocated grids, swaths, and points) that geo-scientists are familiar with. We are deploying within Sci

  6. Integrated multi-sensor fusion for mapping and localization in outdoor environments for mobile robots

    Science.gov (United States)

    Emter, Thomas; Petereit, Janko

    2014-05-01

    An integrated multi-sensor fusion framework for localization and mapping for autonomous navigation in unstructured outdoor environments based on extended Kalman filters (EKF) is presented. The sensors for localization include an inertial measurement unit, a GPS, a fiber optic gyroscope, and wheel odometry. Additionally a 3D LIDAR is used for simultaneous localization and mapping (SLAM). A 3D map is built while concurrently a localization in a so far established 2D map is estimated with the current scan of the LIDAR. Despite of longer run-time of the SLAM algorithm compared to the EKF update, a high update rate is still guaranteed by sophisticatedly joining and synchronizing two parallel localization estimators.

  7. Reconnaissance blind multi-chess: an experimentation platform for ISR sensor fusion and resource management

    Science.gov (United States)

    Newman, Andrew J.; Richardson, Casey L.; Kain, Sean M.; Stankiewicz, Paul G.; Guseman, Paul R.; Schreurs, Blake A.; Dunne, Jeffrey A.

    2016-05-01

    This paper introduces the game of reconnaissance blind multi-chess (RBMC) as a paradigm and test bed for understanding and experimenting with autonomous decision making under uncertainty and in particular managing a network of heterogeneous Intelligence, Surveillance and Reconnaissance (ISR) sensors to maintain situational awareness informing tactical and strategic decision making. The intent is for RBMC to serve as a common reference or challenge problem in fusion and resource management of heterogeneous sensor ensembles across diverse mission areas. We have defined a basic rule set and a framework for creating more complex versions, developed a web-based software realization to serve as an experimentation platform, and developed some initial machine intelligence approaches to playing it.

  8. Neuromorphic Audio-Visual Sensor Fusion on a Sound-Localising Robot

    Directory of Open Access Journals (Sweden)

    Vincent Yue-Sek Chan

    2012-02-01

    Full Text Available This paper presents the first robotic system featuring audio-visual sensor fusion with neuromorphic sensors. We combine a pair of silicon cochleae and a silicon retina on a robotic platform to allow the robot to learn sound localisation through self-motion and visual feedback, using an adaptive ITD-based sound localisation algorithm. After training, the robot can localise sound sources (white or pink noise in a reverberant environment with an RMS error of 4 to 5 degrees in azimuth. In the second part of the paper, we investigate the source binding problem. An experiment is conducted to test the effectiveness of matching an audio event with a corresponding visual event based on their onset time. The results show that this technique can be quite effective, despite its simplicity.

  9. Estimation of tool wear during CNC milling using neural network-based sensor fusion

    Science.gov (United States)

    Ghosh, N.; Ravi, Y. B.; Patra, A.; Mukhopadhyay, S.; Paul, S.; Mohanty, A. R.; Chattopadhyay, A. B.

    2007-01-01

    Cutting tool wear degrades the product quality in manufacturing processes. Monitoring tool wear value online is therefore needed to prevent degradation in machining quality. Unfortunately there is no direct way of measuring the tool wear online. Therefore one has to adopt an indirect method wherein the tool wear is estimated from several sensors measuring related process variables. In this work, a neural network-based sensor fusion model has been developed for tool condition monitoring (TCM). Features extracted from a number of machining zone signals, namely cutting forces, spindle vibration, spindle current, and sound pressure level have been fused to estimate the average flank wear of the main cutting edge. Novel strategies such as, signal level segmentation for temporal registration, feature space filtering, outlier removal, and estimation space filtering have been proposed. The proposed approach has been validated by both laboratory and industrial implementations.

  10. An Inertial and Optical Sensor Fusion Approach for Six Degree-of-Freedom Pose Estimation

    Science.gov (United States)

    He, Changyu; Kazanzides, Peter; Sen, Hasan Tutkun; Kim, Sungmin; Liu, Yue

    2015-01-01

    Optical tracking provides relatively high accuracy over a large workspace but requires line-of-sight between the camera and the markers, which may be difficult to maintain in actual applications. In contrast, inertial sensing does not require line-of-sight but is subject to drift, which may cause large cumulative errors, especially during the measurement of position. To handle cases where some or all of the markers are occluded, this paper proposes an inertial and optical sensor fusion approach in which the bias of the inertial sensors is estimated when the optical tracker provides full six degree-of-freedom (6-DOF) pose information. As long as the position of at least one marker can be tracked by the optical system, the 3-DOF position can be combined with the orientation estimated from the inertial measurements to recover the full 6-DOF pose information. When all the markers are occluded, the position tracking relies on the inertial sensors that are bias-corrected by the optical tracking system. Experiments are performed with an augmented reality head-mounted display (ARHMD) that integrates an optical tracking system (OTS) and inertial measurement unit (IMU). Experimental results show that under partial occlusion conditions, the root mean square errors (RMSE) of orientation and position are 0.04° and 0.134 mm, and under total occlusion conditions for 1 s, the orientation and position RMSE are 0.022° and 0.22 mm, respectively. Thus, the proposed sensor fusion approach can provide reliable 6-DOF pose under long-term partial occlusion and short-term total occlusion conditions. PMID:26184191

  11. Potential use of ground-based sensor technologies for weed detection.

    Science.gov (United States)

    Peteinatos, Gerassimos G; Weis, Martin; Andújar, Dionisio; Rueda Ayala, Victor; Gerhards, Roland

    2014-02-01

    Site-specific weed management is the part of precision agriculture (PA) that tries to effectively control weed infestations with the least economical and environmental burdens. This can be achieved with the aid of ground-based or near-range sensors in combination with decision rules and precise application technologies. Near-range sensor technologies, developed for mounting on a vehicle, have been emerging for PA applications during the last three decades. These technologies focus on identifying plants and measuring their physiological status with the aid of their spectral and morphological characteristics. Cameras, spectrometers, fluorometers and distance sensors are the most prominent sensors for PA applications. The objective of this article is to describe-ground based sensors that have the potential to be used for weed detection and measurement of weed infestation level. An overview of current sensor systems is presented, describing their concepts, results that have been achieved, already utilized commercial systems and problems that persist. A perspective for the development of these sensors is given. © 2013 Society of Chemical Industry.

  12. Multi-Sensor Information Fusion for Optimizing Electric Bicycle Routes Using a Swarm Intelligence Algorithm

    Science.gov (United States)

    Villarubia, Gabriel; De Paz, Juan F.; Bajo, Javier

    2017-01-01

    The use of electric bikes (e-bikes) has grown in popularity, especially in large cities where overcrowding and traffic congestion are common. This paper proposes an intelligent engine management system for e-bikes which uses the information collected from sensors to optimize battery energy and time. The intelligent engine management system consists of a built-in network of sensors in the e-bike, which is used for multi-sensor data fusion; the collected data is analysed and fused and on the basis of this information the system can provide the user with optimal and personalized assistance. The user is given recommendations related to battery consumption, sensors, and other parameters associated with the route travelled, such as duration, speed, or variation in altitude. To provide a user with these recommendations, artificial neural networks are used to estimate speed and consumption for each of the segments of a route. These estimates are incorporated into evolutionary algorithms in order to make the optimizations. A comparative analysis of the results obtained has been conducted for when routes were travelled with and without the optimization system. From the experiments, it is evident that the use of an engine management system results in significant energy and time savings. Moreover, user satisfaction increases as the level of assistance adapts to user behavior and the characteristics of the route. PMID:29088087

  13. Sensor fusion: lane marking detection and autonomous intelligent cruise control system

    Science.gov (United States)

    Baret, Marc; Baillarin, S.; Calesse, C.; Martin, Lionel

    1995-12-01

    In the past few years MATRA and RENAULT have developed an Autonomous Intelligent Cruise Control (AICC) system based on a LIDAR sensor. This sensor incorporating a charge coupled device was designed to acquire pulsed laser diode emission reflected by standard car reflectors. The absence of moving mechanical parts, the large field of view, the high measurement rate and the very good accuracy for distance range and angular position of targets make this sensor very interesting. It provides the equipped car with the distance and the relative speed of other vehicles enabling the safety distance to be controlled by acting on the throttle and the automatic gear box. Experiments in various real traffic situations have shown the limitations of this kind of system especially on bends. All AICC sensors are unable to distinguish between a bend and a change of lane. This is easily understood if we consider a road without lane markings. This fact has led MATRA to improve its AICC system by providing the lane marking information. Also in the scope of the EUREKA PROMETHEUS project, MATRA and RENAULT have developed a lane keeping system in order to warn of the drivers lack of vigilance. Thus, MATRA have spread this system to far field lane marking detection and have coupled it with the AICC system. Experiments will be carried out on roads to estimate the gain in performance and comfort due to this fusion.

  14. Multi-Sensor Information Fusion for Optimizing Electric Bicycle Routes Using a Swarm Intelligence Algorithm

    Directory of Open Access Journals (Sweden)

    Daniel H. De La Iglesia

    2017-10-01

    Full Text Available The use of electric bikes (e-bikes has grown in popularity, especially in large cities where overcrowding and traffic congestion are common. This paper proposes an intelligent engine management system for e-bikes which uses the information collected from sensors to optimize battery energy and time. The intelligent engine management system consists of a built-in network of sensors in the e-bike, which is used for multi-sensor data fusion; the collected data is analysed and fused and on the basis of this information the system can provide the user with optimal and personalized assistance. The user is given recommendations related to battery consumption, sensors, and other parameters associated with the route travelled, such as duration, speed, or variation in altitude. To provide a user with these recommendations, artificial neural networks are used to estimate speed and consumption for each of the segments of a route. These estimates are incorporated into evolutionary algorithms in order to make the optimizations. A comparative analysis of the results obtained has been conducted for when routes were travelled with and without the optimization system. From the experiments, it is evident that the use of an engine management system results in significant energy and time savings. Moreover, user satisfaction increases as the level of assistance adapts to user behavior and the characteristics of the route.

  15. Multi-Sensor Information Fusion for Optimizing Electric Bicycle Routes Using a Swarm Intelligence Algorithm.

    Science.gov (United States)

    De La Iglesia, Daniel H; Villarrubia, Gabriel; De Paz, Juan F; Bajo, Javier

    2017-10-31

    The use of electric bikes (e-bikes) has grown in popularity, especially in large cities where overcrowding and traffic congestion are common. This paper proposes an intelligent engine management system for e-bikes which uses the information collected from sensors to optimize battery energy and time. The intelligent engine management system consists of a built-in network of sensors in the e-bike, which is used for multi-sensor data fusion; the collected data is analysed and fused and on the basis of this information the system can provide the user with optimal and personalized assistance. The user is given recommendations related to battery consumption, sensors, and other parameters associated with the route travelled, such as duration, speed, or variation in altitude. To provide a user with these recommendations, artificial neural networks are used to estimate speed and consumption for each of the segments of a route. These estimates are incorporated into evolutionary algorithms in order to make the optimizations. A comparative analysis of the results obtained has been conducted for when routes were travelled with and without the optimization system. From the experiments, it is evident that the use of an engine management system results in significant energy and time savings. Moreover, user satisfaction increases as the level of assistance adapts to user behavior and the characteristics of the route.

  16. A Method Based on Multi-Sensor Data Fusion for Fault Detection of Planetary Gearboxes

    Directory of Open Access Journals (Sweden)

    Detong Kong

    2012-02-01

    Full Text Available Studies on fault detection and diagnosis of planetary gearboxes are quite limited compared with those of fixed-axis gearboxes. Different from fixed-axis gearboxes, planetary gearboxes exhibit unique behaviors, which invalidate fault diagnosis methods that work well for fixed-axis gearboxes. It is a fact that for systems as complex as planetary gearboxes, multiple sensors mounted on different locations provide complementary information on the health condition of the systems. On this basis, a fault detection method based on multi-sensor data fusion is introduced in this paper. In this method, two features developed for planetary gearboxes are used to characterize the gear health conditions, and an adaptive neuro-fuzzy inference system (ANFIS is utilized to fuse all features from different sensors. In order to demonstrate the effectiveness of the proposed method, experiments are carried out on a planetary gearbox test rig, on which multiple accelerometers are mounted for data collection. The comparisons between the proposed method and the methods based on individual sensors show that the former achieves much higher accuracies in detecting planetary gearbox faults.

  17. Metal Hall sensors for the new generation fusion reactors of DEMO scale

    Science.gov (United States)

    Bolshakova, I.; Bulavin, M.; Kargin, N.; Kost, Ya.; Kuech, T.; Kulikov, S.; Radishevskiy, M.; Shurygin, F.; Strikhanov, M.; Vasil'evskii, I.; Vasyliev, A.

    2017-11-01

    For the first time, the results of on-line testing of metal Hall sensors based on nano-thickness (50-70) nm gold films, which was conducted under irradiation by high-energy neutrons up to the high fluences of 1 · 1024 n · m-2, are presented. The testing has been carried out in the IBR-2 fast pulsed reactor in the neutron flux with the intensity of 1.5 · 1017 n · m-2 · s-1 at the Joint Institute for Nuclear Research. The energy spectrum of neutron flux was very close to that expected for the ex-vessel sensors locations in the ITER experimental reactor. The magnetic field sensitivity of the gold sensors was stable within the whole fluence range under research. Also, sensitivity values at the start and at the end of irradiation session were equal within the measurement error (<1%). The results obtained make it possible to recommend gold sensors for magnetic diagnostics in the new generation fusion reactors of DEMO scale.

  18. Signal processing, sensor fusion, and target recognition; Proceedings of the Meeting, Orlando, FL, Apr. 20-22, 1992

    Science.gov (United States)

    Libby, Vibeke; Kadar, Ivan

    Consideration is given to a multiordered mapping technique for target prioritization, a neural network approach to multiple-target-tracking problems, a multisensor fusion algorithm for multitarget multibackground classification, deconvolutiom of multiple images of the same object, neural networks and genetic algorithms for combinatorial optimization of sensor data fusion, classification of atmospheric acoustic signals from fixed-wing aircraft, and an optics approach to sensor fusion for target recognition. Also treated are a zoom lens for automatic target recognition, a hybrid model for the analysis of radar sensors, an innovative test bed for developing and assessing air-to-air noncooperative target identification algorithms, SAR imagery scene segmentation using fractal processing, sonar feature-based bandwidth compression, laboratory experiments for a new sonar system, computational algorithms for discrete transform using fixed-size filter matrices, and pattern recognition for power systems.

  19. Sensor data fusion for automated threat recognition in manned-unmanned infantry platoons

    Science.gov (United States)

    Wildt, J.; Varela, M.; Ulmke, M.; Brüggermann, B.

    2017-05-01

    To support a dismounted infantry platoon during deployment we team it with several unmanned aerial and ground vehicles (UAV and UGV, respectively). The unmanned systems integrate seamlessly into the infantry platoon, providing automated reconnaissance during movement while keeping formation as well as conducting close range reconnaissance during halt. The sensor data each unmanned system provides is continuously analyzed in real time by specialized algorithms, detecting humans in live videos of UAV mounted infrared cameras as well as gunshot detection and bearing by acoustic sensors. All recognized threats are fused into a consistent situational picture in real time, available to platoon and squad leaders as well as higher level command and control (C2) systems. This gives friendly forces local information superiority and increased situational awareness without the need to constantly monitor the unmanned systems and sensor data.

  20. New distributed fusion filtering algorithm based on covariances over sensor networks with random packet dropouts

    Science.gov (United States)

    Caballero-Águila, R.; Hermoso-Carazo, A.; Linares-Pérez, J.

    2017-07-01

    This paper studies the distributed fusion estimation problem from multisensor measured outputs perturbed by correlated noises and uncertainties modelled by random parameter matrices. Each sensor transmits its outputs to a local processor over a packet-erasure channel and, consequently, random losses may occur during transmission. Different white sequences of Bernoulli variables are introduced to model the transmission losses. For the estimation, each lost output is replaced by its estimator based on the information received previously, and only the covariances of the processes involved are used, without requiring the signal evolution model. First, a recursive algorithm for the local least-squares filters is derived by using an innovation approach. Then, the cross-correlation matrices between any two local filters is obtained. Finally, the distributed fusion filter weighted by matrices is obtained from the local filters by applying the least-squares criterion. The performance of the estimators and the influence of both sensor uncertainties and transmission losses on the estimation accuracy are analysed in a numerical example.

  1. An Improved Evidential-IOWA Sensor Data Fusion Approach in Fault Diagnosis.

    Science.gov (United States)

    Tang, Yongchuan; Zhou, Deyun; Zhuang, Miaoyan; Fang, Xueyi; Xie, Chunhe

    2017-09-18

    As an important tool of information fusion, Dempster-Shafer evidence theory is widely applied in handling the uncertain information in fault diagnosis. However, an incorrect result may be obtained if the combined evidence is highly conflicting, which may leads to failure in locating the fault. To deal with the problem, an improved evidential-Induced Ordered Weighted Averaging (IOWA) sensor data fusion approach is proposed in the frame of Dempster-Shafer evidence theory. In the new method, the IOWA operator is used to determine the weight of different sensor data source, while determining the parameter of the IOWA, both the distance of evidence and the belief entropy are taken into consideration. First, based on the global distance of evidence and the global belief entropy, the α value of IOWA is obtained. Simultaneously, a weight vector is given based on the maximum entropy method model. Then, according to IOWA operator, the evidence are modified before applying the Dempster's combination rule. The proposed method has a better performance in conflict management and fault diagnosis due to the fact that the information volume of each evidence is taken into consideration. A numerical example and a case study in fault diagnosis are presented to show the rationality and efficiency of the proposed method.

  2. Gyro Drift Correction for An Indirect Kalman Filter Based Sensor Fusion Driver

    Directory of Open Access Journals (Sweden)

    Chan-Gun Lee

    2016-06-01

    Full Text Available Sensor fusion techniques have made a significant contribution to the success of the recently emerging mobile applications era because a variety of mobile applications operate based on multi-sensing information from the surrounding environment, such as navigation systems, fitness trackers, interactive virtual reality games, etc. For these applications, the accuracy of sensing information plays an important role to improve the user experience (UX quality, especially with gyroscopes and accelerometers. Therefore, in this paper, we proposed a novel mechanism to resolve the gyro drift problem, which negatively affects the accuracy of orientation computations in the indirect Kalman filter based sensor fusion. Our mechanism focuses on addressing the issues of external feedback loops and non-gyro error elements contained in the state vectors of an indirect Kalman filter. Moreover, the mechanism is implemented in the device-driver layer, providing lower process latency and transparency capabilities for the upper applications. These advances are relevant to millions of legacy applications since utilizing our mechanism does not require the existing applications to be re-programmed. The experimental results show that the root mean square errors (RMSE before and after applying our mechanism are significantly reduced from 6.3 × 10−1 to 5.3 × 10−7, respectively.

  3. Evaluation of chemical sensors for in situ ground-water monitoring at the Hanford Site

    Energy Technology Data Exchange (ETDEWEB)

    Murphy, E.M.; Hostetler, D.D.

    1989-03-01

    This report documents a preliminary review and evaluation of instrument systems and sensors that may be used to detect ground-water contaminants in situ at the Hanford Site. Three topics are covered in this report: (1) identification of a group of priority contaminants at Hanford that could be monitored in situ, (2) a review of current instrument systems and sensors for environmental monitoring, and (3) an evaluation of instrument systems that could be used to monitor Hanford contaminants. Thirteen priority contaminants were identified in Hanford ground water, including carbon tetrachloride and six related chlorinated hydrocarbons, cyanide, methyl ethyl ketone, chromium (VI), fluoride, nitrate, and uranium. Based on transduction principles, chemical sensors were divided into four classes, ten specific types of instrument systems were considered: fluorescence spectroscopy, surface-enhanced Raman spectroscopy (SERS), spark excitation-fiber optic spectrochemical emission sensor (FOSES), chemical optrodes, stripping voltammetry, catalytic surface-modified ion electrode immunoassay sensors, resistance/capacitance, quartz piezobalance and surface acoustic wave devices. Because the flow of heat is difficult to control, there are currently no environmental chemical sensors based on thermal transduction. The ability of these ten instrument systems to detect the thirteen priority contaminants at the Hanford Site at the required sensitivity was evaluated. In addition, all ten instrument systems were qualitatively evaluated for general selectivity, response time, reliability, and field operability. 45 refs., 23 figs., 7 tabs.

  4. Evaluation of chemical sensors for in situ ground-water monitoring at the Hanford Site

    International Nuclear Information System (INIS)

    Murphy, E.M.; Hostetler, D.D.

    1989-03-01

    This report documents a preliminary review and evaluation of instrument systems and sensors that may be used to detect ground-water contaminants in situ at the Hanford Site. Three topics are covered in this report: (1) identification of a group of priority contaminants at Hanford that could be monitored in situ, (2) a review of current instrument systems and sensors for environmental monitoring, and (3) an evaluation of instrument systems that could be used to monitor Hanford contaminants. Thirteen priority contaminants were identified in Hanford ground water, including carbon tetrachloride and six related chlorinated hydrocarbons, cyanide, methyl ethyl ketone, chromium (VI), fluoride, nitrate, and uranium. Based on transduction principles, chemical sensors were divided into four classes, ten specific types of instrument systems were considered: fluorescence spectroscopy, surface-enhanced Raman spectroscopy (SERS), spark excitation-fiber optic spectrochemical emission sensor (FOSES), chemical optrodes, stripping voltammetry, catalytic surface-modified ion electrode immunoassay sensors, resistance/capacitance, quartz piezobalance and surface acoustic wave devices. Because the flow of heat is difficult to control, there are currently no environmental chemical sensors based on thermal transduction. The ability of these ten instrument systems to detect the thirteen priority contaminants at the Hanford Site at the required sensitivity was evaluated. In addition, all ten instrument systems were qualitatively evaluated for general selectivity, response time, reliability, and field operability. 45 refs., 23 figs., 7 tabs

  5. Pose estimation of surgical instrument using sensor data fusion with optical tracker and IMU based on Kalman filter

    Directory of Open Access Journals (Sweden)

    Oh Hyunmin

    2015-01-01

    Full Text Available Tracking system is essential for Image Guided Surgery(IGS. The Optical Tracking Sensor(OTS has been widely used as tracking system for IGS due to its high accuracy and easy usage. However, OTS has a limit that tracking fails when occlusion of marker occurs. In this paper, sensor fusion with OTS and Inertial Measurement Unit(IMU is proposed to solve this problem. The proposed algorithm improves the accuracy of tracking system by eliminating scattering error of the sensor and supplements the disadvantages of OTS and IMU through sensor fusion based on Kalman filter. Also, coordinate axis calibration method that improves the accuracy is introduced. The performed experiment verifies the effectualness of the proposed algorithm.

  6. Fusion of Haptic and Gesture Sensors for Rehabilitation of Bimanual Coordination and Dexterous Manipulation

    Directory of Open Access Journals (Sweden)

    Ningbo Yu

    2016-03-01

    Full Text Available Disabilities after neural injury, such as stroke, bring tremendous burden to patients, families and society. Besides the conventional constrained-induced training with a paretic arm, bilateral rehabilitation training involves both the ipsilateral and contralateral sides of the neural injury, fitting well with the fact that both arms are needed in common activities of daily living (ADLs, and can promote good functional recovery. In this work, the fusion of a gesture sensor and a haptic sensor with force feedback capabilities has enabled a bilateral rehabilitation training therapy. The Leap Motion gesture sensor detects the motion of the healthy hand, and the omega.7 device can detect and assist the paretic hand, according to the designed cooperative task paradigm, as much as needed, with active force feedback to accomplish the manipulation task. A virtual scenario has been built up, and the motion and force data facilitate instantaneous visual and audio feedback, as well as further analysis of the functional capabilities of the patient. This task-oriented bimanual training paradigm recruits the sensory, motor and cognitive aspects of the patient into one loop, encourages the active involvement of the patients into rehabilitation training, strengthens the cooperation of both the healthy and impaired hands, challenges the dexterous manipulation capability of the paretic hand, suits easy of use at home or centralized institutions and, thus, promises effective potentials for rehabilitation training.

  7. Motion-sensor fusion-based gesture recognition and its VLSI architecture design for mobile devices

    Science.gov (United States)

    Zhu, Wenping; Liu, Leibo; Yin, Shouyi; Hu, Siqi; Tang, Eugene Y.; Wei, Shaojun

    2014-05-01

    With the rapid proliferation of smartphones and tablets, various embedded sensors are incorporated into these platforms to enable multimodal human-computer interfaces. Gesture recognition, as an intuitive interaction approach, has been extensively explored in the mobile computing community. However, most gesture recognition implementations by now are all user-dependent and only rely on accelerometer. In order to achieve competitive accuracy, users are required to hold the devices in predefined manner during the operation. In this paper, a high-accuracy human gesture recognition system is proposed based on multiple motion sensor fusion. Furthermore, to reduce the energy overhead resulted from frequent sensor sampling and data processing, a high energy-efficient VLSI architecture implemented on a Xilinx Virtex-5 FPGA board is also proposed. Compared with the pure software implementation, approximately 45 times speed-up is achieved while operating at 20 MHz. The experiments show that the average accuracy for 10 gestures achieves 93.98% for user-independent case and 96.14% for user-dependent case when subjects hold the device randomly during completing the specified gestures. Although a few percent lower than the conventional best result, it still provides competitive accuracy acceptable for practical usage. Most importantly, the proposed system allows users to hold the device randomly during operating the predefined gestures, which substantially enhances the user experience.

  8. Fusion of Haptic and Gesture Sensors for Rehabilitation of Bimanual Coordination and Dexterous Manipulation.

    Science.gov (United States)

    Yu, Ningbo; Xu, Chang; Li, Huanshuai; Wang, Kui; Wang, Liancheng; Liu, Jingtai

    2016-03-18

    Disabilities after neural injury, such as stroke, bring tremendous burden to patients, families and society. Besides the conventional constrained-induced training with a paretic arm, bilateral rehabilitation training involves both the ipsilateral and contralateral sides of the neural injury, fitting well with the fact that both arms are needed in common activities of daily living (ADLs), and can promote good functional recovery. In this work, the fusion of a gesture sensor and a haptic sensor with force feedback capabilities has enabled a bilateral rehabilitation training therapy. The Leap Motion gesture sensor detects the motion of the healthy hand, and the omega.7 device can detect and assist the paretic hand, according to the designed cooperative task paradigm, as much as needed, with active force feedback to accomplish the manipulation task. A virtual scenario has been built up, and the motion and force data facilitate instantaneous visual and audio feedback, as well as further analysis of the functional capabilities of the patient. This task-oriented bimanual training paradigm recruits the sensory, motor and cognitive aspects of the patient into one loop, encourages the active involvement of the patients into rehabilitation training, strengthens the cooperation of both the healthy and impaired hands, challenges the dexterous manipulation capability of the paretic hand, suits easy of use at home or centralized institutions and, thus, promises effective potentials for rehabilitation training.

  9. An Embodied Multi-Sensor Fusion Approach to Visual Motion Estimation Using Unsupervised Deep Networks.

    Science.gov (United States)

    Shamwell, E Jared; Nothwang, William D; Perlis, Donald

    2018-05-04

    Aimed at improving size, weight, and power (SWaP)-constrained robotic vision-aided state estimation, we describe our unsupervised, deep convolutional-deconvolutional sensor fusion network, Multi-Hypothesis DeepEfference (MHDE). MHDE learns to intelligently combine noisy heterogeneous sensor data to predict several probable hypotheses for the dense, pixel-level correspondence between a source image and an unseen target image. We show how our multi-hypothesis formulation provides increased robustness against dynamic, heteroscedastic sensor and motion noise by computing hypothesis image mappings and predictions at 76⁻357 Hz depending on the number of hypotheses being generated. MHDE fuses noisy, heterogeneous sensory inputs using two parallel, inter-connected architectural pathways and n (1⁻20 in this work) multi-hypothesis generating sub-pathways to produce n global correspondence estimates between a source and a target image. We evaluated MHDE on the KITTI Odometry dataset and benchmarked it against the vision-only DeepMatching and Deformable Spatial Pyramids algorithms and were able to demonstrate a significant runtime decrease and a performance increase compared to the next-best performing method.

  10. Accurate human limb angle measurement: sensor fusion through Kalman, least mean squares and recursive least-squares adaptive filtering

    Science.gov (United States)

    Olivares, A.; Górriz, J. M.; Ramírez, J.; Olivares, G.

    2011-02-01

    Inertial sensors are widely used in human body motion monitoring systems since they permit us to determine the position of the subject's limbs. Limb angle measurement is carried out through the integration of the angular velocity measured by a rate sensor and the decomposition of the components of static gravity acceleration measured by an accelerometer. Different factors derived from the sensors' nature, such as the angle random walk and dynamic bias, lead to erroneous measurements. Dynamic bias effects can be reduced through the use of adaptive filtering based on sensor fusion concepts. Most existing published works use a Kalman filtering sensor fusion approach. Our aim is to perform a comparative study among different adaptive filters. Several least mean squares (LMS), recursive least squares (RLS) and Kalman filtering variations are tested for the purpose of finding the best method leading to a more accurate and robust limb angle measurement. A new angle wander compensation sensor fusion approach based on LMS and RLS filters has been developed.

  11. Accurate human limb angle measurement: sensor fusion through Kalman, least mean squares and recursive least-squares adaptive filtering

    International Nuclear Information System (INIS)

    Olivares, A; Olivares, G; Górriz, J M; Ramírez, J

    2011-01-01

    Inertial sensors are widely used in human body motion monitoring systems since they permit us to determine the position of the subject's limbs. Limb angle measurement is carried out through the integration of the angular velocity measured by a rate sensor and the decomposition of the components of static gravity acceleration measured by an accelerometer. Different factors derived from the sensors' nature, such as the angle random walk and dynamic bias, lead to erroneous measurements. Dynamic bias effects can be reduced through the use of adaptive filtering based on sensor fusion concepts. Most existing published works use a Kalman filtering sensor fusion approach. Our aim is to perform a comparative study among different adaptive filters. Several least mean squares (LMS), recursive least squares (RLS) and Kalman filtering variations are tested for the purpose of finding the best method leading to a more accurate and robust limb angle measurement. A new angle wander compensation sensor fusion approach based on LMS and RLS filters has been developed

  12. An Extension to Deng's Entropy in the Open World Assumption with an Application in Sensor Data Fusion.

    Science.gov (United States)

    Tang, Yongchuan; Zhou, Deyun; Chan, Felix T S

    2018-06-11

    Quantification of uncertain degree in the Dempster-Shafer evidence theory (DST) framework with belief entropy is still an open issue, even a blank field for the open world assumption. Currently, the existed uncertainty measures in the DST framework are limited to the closed world where the frame of discernment (FOD) is assumed to be complete. To address this issue, this paper focuses on extending a belief entropy to the open world by considering the uncertain information represented as the FOD and the nonzero mass function of the empty set simultaneously. An extension to Deng’s entropy in the open world assumption (EDEOW) is proposed as a generalization of the Deng’s entropy and it can be degenerated to the Deng entropy in the closed world wherever necessary. In order to test the reasonability and effectiveness of the extended belief entropy, an EDEOW-based information fusion approach is proposed and applied to sensor data fusion under uncertainty circumstance. The experimental results verify the usefulness and applicability of the extended measure as well as the modified sensor data fusion method. In addition, a few open issues still exist in the current work: the necessary properties for a belief entropy in the open world assumption, whether there exists a belief entropy that satisfies all the existed properties, and what is the most proper fusion frame for sensor data fusion under uncertainty.

  13. An Extension to Deng’s Entropy in the Open World Assumption with an Application in Sensor Data Fusion

    Directory of Open Access Journals (Sweden)

    Yongchuan Tang

    2018-06-01

    Full Text Available Quantification of uncertain degree in the Dempster-Shafer evidence theory (DST framework with belief entropy is still an open issue, even a blank field for the open world assumption. Currently, the existed uncertainty measures in the DST framework are limited to the closed world where the frame of discernment (FOD is assumed to be complete. To address this issue, this paper focuses on extending a belief entropy to the open world by considering the uncertain information represented as the FOD and the nonzero mass function of the empty set simultaneously. An extension to Deng’s entropy in the open world assumption (EDEOW is proposed as a generalization of the Deng’s entropy and it can be degenerated to the Deng entropy in the closed world wherever necessary. In order to test the reasonability and effectiveness of the extended belief entropy, an EDEOW-based information fusion approach is proposed and applied to sensor data fusion under uncertainty circumstance. The experimental results verify the usefulness and applicability of the extended measure as well as the modified sensor data fusion method. In addition, a few open issues still exist in the current work: the necessary properties for a belief entropy in the open world assumption, whether there exists a belief entropy that satisfies all the existed properties, and what is the most proper fusion frame for sensor data fusion under uncertainty.

  14. Kalman Filters in Geotechnical Monitoring of Ground Subsidence Using Data from MEMS Sensors

    Science.gov (United States)

    Li, Cheng; Azzam, Rafig; Fernández-Steeger, Tomás M.

    2016-01-01

    The fast development of wireless sensor networks and MEMS make it possible to set up today real-time wireless geotechnical monitoring. To handle interferences and noises from the output data, Kalman filter can be selected as a method to achieve a more realistic estimate of the observations. In this paper, a one-day wireless measurement using accelerometers and inclinometers was deployed on top of a tunnel section under construction in order to monitor ground subsidence. The normal vectors of the sensors were firstly obtained with the help of rotation matrices, and then be projected to the plane of longitudinal section, by which the dip angles over time would be obtained via a trigonometric function. Finally, a centralized Kalman filter was applied to estimate the tilt angles of the sensor nodes based on the data from the embedded accelerometer and the inclinometer. Comparing the results from two sensor nodes deployed away and on the track respectively, the passing of the tunnel boring machine can be identified from unusual performances. Using this method, the ground settlement due to excavation can be measured and a real-time monitoring of ground subsidence can be realized. PMID:27447630

  15. Kalman Filters in Geotechnical Monitoring of Ground Subsidence Using Data from MEMS Sensors

    Directory of Open Access Journals (Sweden)

    Cheng Li

    2016-07-01

    Full Text Available The fast development of wireless sensor networks and MEMS make it possible to set up today real-time wireless geotechnical monitoring. To handle interferences and noises from the output data, Kalman filter can be selected as a method to achieve a more realistic estimate of the observations. In this paper, a one-day wireless measurement using accelerometers and inclinometers was deployed on top of a tunnel section under construction in order to monitor ground subsidence. The normal vectors of the sensors were firstly obtained with the help of rotation matrices, and then be projected to the plane of longitudinal section, by which the dip angles over time would be obtained via a trigonometric function. Finally, a centralized Kalman filter was applied to estimate the tilt angles of the sensor nodes based on the data from the embedded accelerometer and the inclinometer. Comparing the results from two sensor nodes deployed away and on the track respectively, the passing of the tunnel boring machine can be identified from unusual performances. Using this method, the ground settlement due to excavation can be measured and a real-time monitoring of ground subsidence can be realized.

  16. Kalman Filters in Geotechnical Monitoring of Ground Subsidence Using Data from MEMS Sensors.

    Science.gov (United States)

    Li, Cheng; Azzam, Rafig; Fernández-Steeger, Tomás M

    2016-07-19

    The fast development of wireless sensor networks and MEMS make it possible to set up today real-time wireless geotechnical monitoring. To handle interferences and noises from the output data, Kalman filter can be selected as a method to achieve a more realistic estimate of the observations. In this paper, a one-day wireless measurement using accelerometers and inclinometers was deployed on top of a tunnel section under construction in order to monitor ground subsidence. The normal vectors of the sensors were firstly obtained with the help of rotation matrices, and then be projected to the plane of longitudinal section, by which the dip angles over time would be obtained via a trigonometric function. Finally, a centralized Kalman filter was applied to estimate the tilt angles of the sensor nodes based on the data from the embedded accelerometer and the inclinometer. Comparing the results from two sensor nodes deployed away and on the track respectively, the passing of the tunnel boring machine can be identified from unusual performances. Using this method, the ground settlement due to excavation can be measured and a real-time monitoring of ground subsidence can be realized.

  17. An Adaptive Multi-Sensor Data Fusion Method Based on Deep Convolutional Neural Networks for Fault Diagnosis of Planetary Gearbox

    Science.gov (United States)

    Jing, Luyang; Wang, Taiyong; Zhao, Ming; Wang, Peng

    2017-01-01

    A fault diagnosis approach based on multi-sensor data fusion is a promising tool to deal with complicated damage detection problems of mechanical systems. Nevertheless, this approach suffers from two challenges, which are (1) the feature extraction from various types of sensory data and (2) the selection of a suitable fusion level. It is usually difficult to choose an optimal feature or fusion level for a specific fault diagnosis task, and extensive domain expertise and human labor are also highly required during these selections. To address these two challenges, we propose an adaptive multi-sensor data fusion method based on deep convolutional neural networks (DCNN) for fault diagnosis. The proposed method can learn features from raw data and optimize a combination of different fusion levels adaptively to satisfy the requirements of any fault diagnosis task. The proposed method is tested through a planetary gearbox test rig. Handcraft features, manual-selected fusion levels, single sensory data, and two traditional intelligent models, back-propagation neural networks (BPNN) and a support vector machine (SVM), are used as comparisons in the experiment. The results demonstrate that the proposed method is able to detect the conditions of the planetary gearbox effectively with the best diagnosis accuracy among all comparative methods in the experiment. PMID:28230767

  18. Ground and river water quality monitoring using a smartphone-based pH sensor

    Directory of Open Access Journals (Sweden)

    Sibasish Dutta

    2015-05-01

    Full Text Available We report here the working of a compact and handheld smartphone-based pH sensor for monitoring of ground and river water quality. Using simple laboratory optical components and the camera of the smartphone, we develop a compact spectrophotometer which is operational in the wavelength range of 400-700 nm and having spectral resolution of 0.305 nm/pixel for our equipment. The sensor measures variations in optical absorption band of pH sensitive dye sample in different pH solutions. The transmission image spectra through a transmission grating gets captured by the smartphone, and subsequently converted into intensity vs. wavelengths. Using the designed sensor, we measure water quality of ground water and river water from different locations in Assam and the results are found to be reliable when compared with the standard spectrophotometer tool. The overall cost involved for development of the sensor is relatively low. We envision that the designed sensing technique could emerge as an inexpensive, compact and portable pH sensor that would be useful for in-field applications.

  19. Improvement of force-sensor-based heart rate estimation using multichannel data fusion.

    Science.gov (United States)

    Bruser, Christoph; Kortelainen, Juha M; Winter, Stefan; Tenhunen, Mirja; Parkka, Juha; Leonhardt, Steffen

    2015-01-01

    The aim of this paper is to present and evaluate algorithms for heartbeat interval estimation from multiple spatially distributed force sensors integrated into a bed. Moreover, the benefit of using multichannel systems as opposed to a single sensor is investigated. While it might seem intuitive that multiple channels are superior to a single channel, the main challenge lies in finding suitable methods to actually leverage this potential. To this end, two algorithms for heart rate estimation from multichannel vibration signals are presented and compared against a single-channel sensing solution. The first method operates by analyzing the cepstrum computed from the average spectra of the individual channels, while the second method applies Bayesian fusion to three interval estimators, such as the autocorrelation, which are applied to each channel. This evaluation is based on 28 night-long sleep lab recordings during which an eight-channel polyvinylidene fluoride-based sensor array was used to acquire cardiac vibration signals. The recruited patients suffered from different sleep disorders of varying severity. From the sensor array data, a virtual single-channel signal was also derived for comparison by averaging the channels. The single-channel results achieved a beat-to-beat interval error of 2.2% with a coverage (i.e., percentage of the recording which could be analyzed) of 68.7%. In comparison, the best multichannel results attained a mean error and coverage of 1.0% and 81.0%, respectively. These results present statistically significant improvements of both metrics over the single-channel results (p < 0.05).

  20. Geographic information system for fusion and analysis of high-resolution remote sensing and ground data

    Science.gov (United States)

    Freeman, Anthony; Way, Jo Bea; Dubois, Pascale; Leberl, Franz

    1993-01-01

    We seek to combine high-resolution remotely sensed data with models and ground truth measurements, in the context of a Geographical Information System (GIS), integrated with specialized image processing software. We will use this integrated system to analyze the data from two Case Studies, one at a boreal forest site, the other a tropical forest site. We will assess the information content of the different components of the data, determine the optimum data combinations to study biogeophysical changes in the forest, assess the best way to visualize the results, and validate the models for the forest response to different radar wavelengths/polarizations. During the 1990's, unprecedented amounts of high-resolution images from space of the Earth's surface will become available to the applications scientist from the LANDSAT/TM series, European and Japanese ERS-1 satellites, RADARSAT and SIR-C missions. When the Earth Observation Systems (EOS) program is operational, the amount of data available for a particular site can only increase. The interdisciplinary scientist, seeking to use data from various sensors to study his site of interest, may be faced with massive difficulties in manipulating such large data sets, assessing their information content, determining the optimum combinations of data to study a particular parameter, visualizing his results and validating his model of the surface. The techniques to deal with these problems are also needed to support the analysis of data from NASA's current program of Multi-sensor Airborne Campaigns, which will also generate large volumes of data. In the Case Studies outlined in this proposal, we will have somewhat unique data sets. For the Bonanza Creek Experimental Forest (Case 1) calibrated DC-8 SAR (Synthetic Aperture Radar) data and extensive ground truth measurement are already at our disposal. The data set shows documented evidence to temporal change. The Belize Forest Experiment (Case 2) will produce calibrated DC-8 SAR

  1. Real-time classification and sensor fusion with a spiking deep belief network.

    Science.gov (United States)

    O'Connor, Peter; Neil, Daniel; Liu, Shih-Chii; Delbruck, Tobi; Pfeiffer, Michael

    2013-01-01

    Deep Belief Networks (DBNs) have recently shown impressive performance on a broad range of classification problems. Their generative properties allow better understanding of the performance, and provide a simpler solution for sensor fusion tasks. However, because of their inherent need for feedback and parallel update of large numbers of units, DBNs are expensive to implement on serial computers. This paper proposes a method based on the Siegert approximation for Integrate-and-Fire neurons to map an offline-trained DBN onto an efficient event-driven spiking neural network suitable for hardware implementation. The method is demonstrated in simulation and by a real-time implementation of a 3-layer network with 2694 neurons used for visual classification of MNIST handwritten digits with input from a 128 × 128 Dynamic Vision Sensor (DVS) silicon retina, and sensory-fusion using additional input from a 64-channel AER-EAR silicon cochlea. The system is implemented through the open-source software in the jAER project and runs in real-time on a laptop computer. It is demonstrated that the system can recognize digits in the presence of distractions, noise, scaling, translation and rotation, and that the degradation of recognition performance by using an event-based approach is less than 1%. Recognition is achieved in an average of 5.8 ms after the onset of the presentation of a digit. By cue integration from both silicon retina and cochlea outputs we show that the system can be biased to select the correct digit from otherwise ambiguous input.

  2. A Weighted Combination Method for Conflicting Evidence in Multi-Sensor Data Fusion

    Directory of Open Access Journals (Sweden)

    Fuyuan Xiao

    2018-05-01

    Full Text Available Dempster–Shafer evidence theory is widely applied in various fields related to information fusion. However, how to avoid the counter-intuitive results is an open issue when combining highly conflicting pieces of evidence. In order to handle such a problem, a weighted combination method for conflicting pieces of evidence in multi-sensor data fusion is proposed by considering both the interplay between the pieces of evidence and the impacts of the pieces of evidence themselves. First, the degree of credibility of the evidence is determined on the basis of the modified cosine similarity measure of basic probability assignment. Then, the degree of credibility of the evidence is adjusted by leveraging the belief entropy function to measure the information volume of the evidence. Finally, the final weight of each piece of evidence generated from the above steps is obtained and adopted to modify the bodies of evidence before using Dempster’s combination rule. A numerical example is provided to illustrate that the proposed method is reasonable and efficient in handling the conflicting pieces of evidence. In addition, applications in data classification and motor rotor fault diagnosis validate the practicability of the proposed method with better accuracy.

  3. Spatial Aspects of Multi-Sensor Data Fusion: Aerosol Optical Thickness

    Science.gov (United States)

    Leptoukh, Gregory; Zubko, V.; Gopalan, A.

    2007-01-01

    The Goddard Earth Sciences Data and Information Services Center (GES DISC) investigated the applicability and limitations of combining multi-sensor data through data fusion, to increase the usefulness of the multitude of NASA remote sensing data sets, and as part of a larger effort to integrate this capability in the GES-DISC Interactive Online Visualization and Analysis Infrastructure (Giovanni). This initial study focused on merging daily mean Aerosol Optical Thickness (AOT), as measured by the Moderate Resolution Imaging Spectroradiometer (MODIS) onboard the Terra and Aqua satellites, to increase spatial coverage and produce complete fields to facilitate comparison with models and station data. The fusion algorithm used the maximum likelihood technique to merge the pixel values where available. The algorithm was applied to two regional AOT subsets (with mostly regular and irregular gaps, respectively) and a set of AOT fields that differed only in the size and location of artificially created gaps. The Cumulative Semivariogram (CSV) was found to be sensitive to the spatial distribution of gap areas and, thus, useful for assessing the sensitivity of the fused data to spatial gaps.

  4. Passive in-vehicle driver breath alcohol detection using advanced sensor signal acquisition and fusion.

    Science.gov (United States)

    Ljungblad, Jonas; Hök, Bertil; Allalou, Amin; Pettersson, Håkan

    2017-05-29

    The research objective of the present investigation is to demonstrate the present status of passive in-vehicle driver breath alcohol detection and highlight the necessary conditions for large-scale implementation of such a system. Completely passive detection has remained a challenge mainly because of the requirements on signal resolution combined with the constraints of vehicle integration. The work is part of the Driver Alcohol Detection System for Safety (DADSS) program aiming at massive deployment of alcohol sensing systems that could potentially save thousands of American lives annually. The work reported here builds on earlier investigations, in which it has been shown that detection of alcohol vapor in the proximity of a human subject may be traced to that subject by means of simultaneous recording of carbon dioxide (CO 2 ) at the same location. Sensors based on infrared spectroscopy were developed to detect and quantify low concentrations of alcohol and CO 2 . In the present investigation, alcohol and CO 2 were recorded at various locations in a vehicle cabin while human subjects were performing normal in-step procedures and driving preparations. A video camera directed to the driver position was recording images of the driver's upper body parts, including the face, and the images were analyzed with respect to features of significance to the breathing behavior and breath detection, such as mouth opening and head direction. Improvement of the sensor system with respect to signal resolution including algorithm and software development, and fusion of the sensor and camera signals was successfully implemented and tested before starting the human study. In addition, experimental tests and simulations were performed with the purpose of connecting human subject data with repeatable experimental conditions. The results include occurrence statistics of detected breaths by signal peaks of CO 2 and alcohol. From the statistical data, the accuracy of breath alcohol

  5. Multi-rate sensor fusion-based adaptive discrete finite-time synergetic control for flexible-joint mechanical systems

    International Nuclear Information System (INIS)

    Xue Guang-Yue; Ren Xue-Mei; Xia Yuan-Qing

    2013-01-01

    This paper proposes an adaptive discrete finite-time synergetic control (ADFTSC) scheme based on a multi-rate sensor fusion estimator for flexible-joint mechanical systems in the presence of unmeasured states and dynamic uncertainties. Multi-rate sensors are employed to observe the system states which cannot be directly obtained by encoders due to the existence of joint flexibilities. By using an extended Kalman filter (EKF), the finite-time synergetic controller is designed based on a sensor fusion estimator which estimates states and parameters of the mechanical system with multi-rate measurements. The proposed controller can guarantee the finite-time convergence of tracking errors by the theoretical derivation. Simulation and experimental studies are included to validate the effectiveness of the proposed approach. (general)

  6. Multi-Sensor Building Fire Alarm System with Information Fusion Technology Based on D-S Evidence Theory

    Directory of Open Access Journals (Sweden)

    Qian Ding

    2014-10-01

    Full Text Available Multi-sensor and information fusion technology based on Dempster-Shafer evidence theory is applied in the system of a building fire alarm to realize early detecting and alarming. By using a multi-sensor to monitor the parameters of the fire process, such as light, smoke, temperature, gas and moisture, the range of fire monitoring in space and time is expanded compared with a single-sensor system. Then, the D-S evidence theory is applied to fuse the information from the multi-sensor with the specific fire model, and the fire alarm is more accurate and timely. The proposed method can avoid the failure of the monitoring data effectively, deal with the conflicting evidence from the multi-sensor robustly and improve the reliability of fire warning significantly.

  7. Para-quinodimethane-bridged perylene dimers and pericondensed quaterrylenes: The effect of the fusion mode on the ground states and physical properties

    KAUST Repository

    Das, Soumyajit; Lee, Sangsu; Son, Minjung; Zhu, Xiaojian; Zhang, Wenhua; Zheng, Bin; Hu, Pan; Zeng, Zebing; Sun, Zhe; Zeng, Wangdong; Li, Runwei; Huang, Kuo-Wei; Ding, Jun; Kim, Dongho; Wu, Jishan

    2014-01-01

    relationships. In this study, para-quinodimethane (p-QDM)-bridged quinoidal perylene dimers 4 and 5 with different fusion modes and their corresponding aromatic counterparts, the pericondensed quaterrylenes 6 and 7, were synthesized. Their ground

  8. Clay content prediction using on-the-go proximal soil sensor fusion

    DEFF Research Database (Denmark)

    Tabatabai, Salman; Knadel, Maria; Greve, Mogens Humlekrog

    on soil usability, very few studies so far have provided robust and accurate predictions for fields with high clay content variability. An on-the-go multi-sensor platform was used to measure topsoil (25cm) VNIR spectra and temperature as well as electrical conductivity of top 30cm and top 90cm in 5 fields...... least squares regression (PLSR) and support vector machines regression (SVMR) were performed using VNIR spectra, EC and soil temperature as predictors and clay content as the response variable. PLSR and SVMR models were validated using full and 20-segment cross-validation respectively. The results were...... highly accurate with R2 of 0.91 and 0.93, root mean square error (RMSE) of 1.19 and 1.08, and ratio of performance to interquartile range (RPIQ) of 4.6 and 5.1 for PLSR and SVMR respectively. This shows the high potential of on-the-go soil sensor fusion to predict soil clay content and automate...

  9. Robust and reliable banknote authentification and print flaw detection with opto-acoustical sensor fusion methods

    Science.gov (United States)

    Lohweg, Volker; Schaede, Johannes; Türke, Thomas

    2006-02-01

    The authenticity checking and inspection of bank notes is a high labour intensive process where traditionally every note on every sheet is inspected manually. However with the advent of more and more sophisticated security features, both visible and invisible, and the requirement of cost reduction in the printing process, it is clear that automation is required. As more and more print techniques and new security features will be established, total quality security, authenticity and bank note printing must be assured. Therefore, this factor necessitates amplification of a sensorial concept in general. We propose a concept for both authenticity checking and inspection methods for pattern recognition and classification for securities and banknotes, which is based on the concept of sensor fusion and fuzzy interpretation of data measures. In the approach different methods of authenticity analysis and print flaw detection are combined, which can be used for vending or sorting machines, as well as for printing machines. Usually only the existence or appearance of colours and their textures are checked by cameras. Our method combines the visible camera images with IR-spectral sensitive sensors, acoustical and other measurements like temperature and pressure of printing machines.

  10. Wi-GIM system: a new wireless sensor network (WSN) for accurate ground instability monitoring

    Science.gov (United States)

    Mucchi, Lorenzo; Trippi, Federico; Schina, Rosa; Fornaciai, Alessandro; Gigli, Giovanni; Nannipieri, Luca; Favalli, Massimiliano; Marturia Alavedra, Jordi; Intrieri, Emanuele; Agostini, Andrea; Carnevale, Ennio; Bertolini, Giovanni; Pizziolo, Marco; Casagli, Nicola

    2016-04-01

    Landslides are among the most serious and common geologic hazards around the world. Their impact on human life is expected to increase in the next future as a consequence of human-induced climate change as well as the population growth in proximity of unstable slopes. Therefore, developing better performing technologies for monitoring landslides and providing local authorities with new instruments able to help them in the decision making process, is becoming more and more important. The recent progresses in Information and Communication Technologies (ICT) allow us to extend the use of wireless technologies in landslide monitoring. In particular, the developments in electronics components have permitted to lower the price of the sensors and, at the same time, to actuate more efficient wireless communications. In this work we present a new wireless sensor network (WSN) system, designed and developed for landslide monitoring in the framework of EU Wireless Sensor Network for Ground Instability Monitoring - Wi-GIM project (LIFE12 ENV/IT/001033). We show the preliminary performance of the Wi-GIM system after the first period of monitoring on the active Roncovetro Landslide and on a large subsiding area in the neighbourhood of Sallent village. The Roncovetro landslide is located in the province of Reggio Emilia (Italy) and moved an inferred volume of about 3 million cubic meters. Sallent village is located at the centre of the Catalan evaporitic basin in Spain. The Wi-GIM WSN monitoring system consists of three levels: 1) Master/Gateway level coordinates the WSN and performs data aggregation and local storage; 2) Master/Server level takes care of acquiring and storing data on a remote server; 3) Nodes level that is based on a mesh of peripheral nodes, each consisting in a sensor board equipped with sensors and wireless module. The nodes are located in the landslide ground perimeter and are able to create an ad-hoc WSN. The location of each sensor on the ground is

  11. Sensor data fusion of radar, ESM, IFF, and data LINK of the Canadian Patrol Frigate and the data alignment issues

    Science.gov (United States)

    Couture, Jean; Boily, Edouard; Simard, Marc-Alain

    1996-05-01

    The research and development group at Loral Canada is now at the second phase of the development of a data fusion demonstration model (DFDM) for a naval anti-air warfare to be used as a workbench tool to perform exploratory research. This project has emphatically addressed how the concepts related to fusion could be implemented within the Canadian Patrol Frigate (CPF) software environment. The project has been designed to read data passively on the CPF bus without any modification to the CPF software. This has brought to light important time alignment issues since the CPF sensors and the CPF command and control system were not important time alignment issues since the CPF sensors and the CPF command and control system were not originally designed to support a track management function which fuses information. The fusion of data from non-organic sensors with the tactical Link-11 data has produced stimulating spatial alignment problems which have been overcome by the use of a geodetic referencing coordinate system. Some benchmark scenarios have been selected to quantitatively demonstrate the capabilities of this fusion implementation. This paper describes the implementation design of DFDM (version 2), and summarizes the results obtained so far when fusing the scenarios simulated data.

  12. Embry-Riddle Aeronautical University multispectral sensor and data fusion laboratory: a model for distributed research and education

    Science.gov (United States)

    McMullen, Sonya A. H.; Henderson, Troy; Ison, David

    2017-05-01

    The miniaturization of unmanned systems and spacecraft, as well as computing and sensor technologies, has opened new opportunities in the areas of remote sensing and multi-sensor data fusion for a variety of applications. Remote sensing and data fusion historically have been the purview of large government organizations, such as the Department of Defense (DoD), National Aeronautics and Space Administration (NASA), and National Geospatial-Intelligence Agency (NGA) due to the high cost and complexity of developing, fielding, and operating such systems. However, miniaturized computers with high capacity processing capabilities, small and affordable sensors, and emerging, commercially available platforms such as UAS and CubeSats to carry such sensors, have allowed for a vast range of novel applications. In order to leverage these developments, Embry-Riddle Aeronautical University (ERAU) has developed an advanced sensor and data fusion laboratory to research component capabilities and their employment on a wide-range of autonomous, robotic, and transportation systems. This lab is unique in several ways, for example, it provides a traditional campus laboratory for students and faculty to model and test sensors in a range of scenarios, process multi-sensor data sets (both simulated and experimental), and analyze results. Moreover, such allows for "virtual" modeling, testing, and teaching capability reaching beyond the physical confines of the facility for use among ERAU Worldwide students and faculty located around the globe. Although other institutions such as Georgia Institute of Technology, Lockheed Martin, University of Dayton, and University of Central Florida have optical sensor laboratories, the ERAU virtual concept is the first such lab to expand to multispectral sensors and data fusion, while focusing on the data collection and data products and not on the manufacturing aspect. Further, the initiative is a unique effort among Embry-Riddle faculty to develop multi

  13. A Real-Time Smooth Weighted Data Fusion Algorithm for Greenhouse Sensing Based on Wireless Sensor Networks

    Directory of Open Access Journals (Sweden)

    Tengyue Zou

    2017-11-01

    Full Text Available Wireless sensor networks are widely used to acquire environmental parameters to support agricultural production. However, data variation and noise caused by actuators often produce complex measurement conditions. These factors can lead to nonconformity in reporting samples from different nodes and cause errors when making a final decision. Data fusion is well suited to reduce the influence of actuator-based noise and improve automation accuracy. A key step is to identify the sensor nodes disturbed by actuator noise and reduce their degree of participation in the data fusion results. A smoothing value is introduced and a searching method based on Prim’s algorithm is designed to help obtain stable sensing data. A voting mechanism with dynamic weights is then proposed to obtain the data fusion result. The dynamic weighting process can sharply reduce the influence of actuator noise in data fusion and gradually condition the data to normal levels over time. To shorten the data fusion time in large networks, an acceleration method with prediction is also presented to reduce the data collection time. A real-time system is implemented on STMicroelectronics STM32F103 and NORDIC nRF24L01 platforms and the experimental results verify the improvement provided by these new algorithms.

  14. Reliability of Measured Data for pH Sensor Arrays with Fault Diagnosis and Data Fusion Based on LabVIEW

    OpenAIRE

    Liao, Yi-Hung; Chou, Jung-Chuan; Lin, Chin-Yi

    2013-01-01

    Fault diagnosis (FD) and data fusion (DF) technologies implemented in the LabVIEW program were used for a ruthenium dioxide pH sensor array. The purpose of the fault diagnosis and data fusion technologies is to increase the reliability of measured data. Data fusion is a very useful statistical method used for sensor arrays in many fields. Fault diagnosis is used to avoid sensor faults and to measure errors in the electrochemical measurement system, therefore, in this study, we use fault diagn...

  15. Mixed H2/H∞-Based Fusion Estimation for Energy-Limited Multi-Sensors in Wearable Body Networks

    Directory of Open Access Journals (Sweden)

    Chao Li

    2017-12-01

    Full Text Available In wireless sensor networks, sensor nodes collect plenty of data for each time period. If all of data are transmitted to a Fusion Center (FC, the power of sensor node would run out rapidly. On the other hand, the data also needs a filter to remove the noise. Therefore, an efficient fusion estimation model, which can save the energy of the sensor nodes while maintaining higher accuracy, is needed. This paper proposes a novel mixed H2/H∞-based energy-efficient fusion estimation model (MHEEFE for energy-limited Wearable Body Networks. In the proposed model, the communication cost is firstly reduced efficiently while keeping the estimation accuracy. Then, the parameters in quantization method are discussed, and we confirm them by an optimization method with some prior knowledge. Besides, some calculation methods of important parameters are researched which make the final estimates more stable. Finally, an iteration-based weight calculation algorithm is presented, which can improve the fault tolerance of the final estimate. In the simulation, the impacts of some pivotal parameters are discussed. Meanwhile, compared with the other related models, the MHEEFE shows a better performance in accuracy, energy-efficiency and fault tolerance.

  16. Mobile Ground-Based Radar Sensor for Localization and Mapping: An Evaluation of two Approaches

    Directory of Open Access Journals (Sweden)

    Damien Vivet

    2013-08-01

    Full Text Available This paper is concerned with robotic applications using a ground-based radar sensor for simultaneous localization and mapping problems. In mobile robotics, radar technology is interesting because of its long range and the robustness of radar waves to atmospheric conditions, making these sensors well-suited for extended outdoor robotic applications. Two localization and mapping approaches using data obtained from a 360° field of view microwave radar sensor are presented and compared. The first method is a trajectory-oriented simultaneous localization and mapping technique, which makes no landmark assumptions and avoids the data association problem. The estimation of the ego-motion makes use of the Fourier-Mellin transform for registering radar images in a sequence, from which the rotation and translation of the sensor motion can be estimated. The second approach uses the consequence of using a rotating range sensor in high speed robotics. In such a situation, movement combinations create distortions in the collected data. Velocimetry is achieved here by explicitly analysing these measurement distortions. As a result, the trajectory of the vehicle and then the radar map of outdoor environments can be obtained. The evaluation of experimental results obtained by the two methods is presented on real-world data from a vehicle moving at 30 km/h over a 2.5 km course.

  17. Experimental measurement of oil–water two-phase flow by data fusion of electrical tomography sensors and venturi tube

    International Nuclear Information System (INIS)

    Liu, Yinyan; Deng, Yuchi; Zhang, Maomao; Yu, Peining; Li, Yi

    2017-01-01

    Oil–water two-phase flows are commonly found in the production processes of the petroleum industry. Accurate online measurement of flow rates is crucial to ensure the safety and efficiency of oil exploration and production. A research team from Tsinghua University has developed an experimental apparatus for multiphase flow measurement based on an electrical capacitance tomography (ECT) sensor, an electrical resistance tomography (ERT) sensor, and a venturi tube. This work presents the phase fraction and flow rate measurements of oil–water two-phase flows based on the developed apparatus. Full-range phase fraction can be obtained by the combination of the ECT sensor and the ERT sensor. By data fusion of differential pressures measured by venturi tube and the phase fraction, the total flow rate and single-phase flow rate can be calculated. Dynamic experiments were conducted on the multiphase flow loop in horizontal and vertical pipelines and at various flow rates. (paper)

  18. Development of an optochemical sensor for continuous reversible determination of nitrate in drinking water and ground water

    International Nuclear Information System (INIS)

    Lumpp, R.

    1993-09-01

    An optochemical sensor has been developed for continuous reversible determination of nitrate in drinking water and ground water. The sensor is based on the combination of the anion selective liquid ion exchanger Ni(II[bathophenanthroline] 3 2+ with phenolsulfonephtalein dyes in a polyvinylchloride membrane. (orig.) [de

  19. Sensors Fusion based Online Mapping and Features Extraction of Mobile Robot in the Road Following and Roundabout

    International Nuclear Information System (INIS)

    Ali, Mohammed A H; Yussof, Wan Azhar B.; Hamedon, Zamzuri B; Yussof, Zulkifli B.; Majeed, Anwar P P; Mailah, Musa

    2016-01-01

    A road feature extraction based mapping system using a sensor fusion technique for mobile robot navigation in road environments is presented in this paper. The online mapping of mobile robot is performed continuously in the road environments to find the road properties that enable the robot to move from a certain start position to pre-determined goal while discovering and detecting the roundabout. The sensors fusion involving laser range finder, camera and odometry which are installed in a new platform, are used to find the path of the robot and localize it within its environments. The local maps are developed using camera and laser range finder to recognize the roads borders parameters such as road width, curbs and roundabout. Results show the capability of the robot with the proposed algorithms to effectively identify the road environments and build a local mapping for road following and roundabout. (paper)

  20. Accurate positioning of pedestrains in mixed indoor/outdoor settings : A particle filter approach to sensor and map fusion

    DEFF Research Database (Denmark)

    Toftkjær, Thomas

    , through an extensive GNSS measurement campaign. The results of this campaign provides researchers a foundation for choosing and designing complementary technologies and systems. The contributions in this thesis are novel sensor fusion methods based on particle lters for improved positioning, hence......Pedestrian positioning with full coverage in urban environments is a long sought after research goal. This thesis proposes new techniques for handling the challenging task of truly pervasive pedestrian positioning. It shows that through sensor fusion one can both improve accuracy and extend...... the following four aspects all advance this research direction. Firstly, this thesis proposes ProPosition, a system that utilizes GNSS-complementary technologies such as WiFi and Dead Reckoning by Inertial Measurements Units. We show, that through ProPosition's use of the probabilistic Bayes lter technique...

  1. A multi-sensor fusion framework for improving situational awareness in demanding maritime training

    International Nuclear Information System (INIS)

    Sanfilippo, Filippo

    2017-01-01

    Real offshore operational scenarios can involve a considerable amount of risk. Sophisticated training programmes involving specially designed simulator environments constitute a promising approach for improving an individual's perception and assessment of dangerous situations in real applications. One of the world's most advanced providers of simulators for such demanding offshore operations is the Offshore Simulator Centre AS (OSC). However, even though the OSC provides powerful simulation tools, techniques for visualising operational procedures that can be used to further improve Situational awareness (SA), are still lacking. Providing the OSC with an integrated multi-sensor fusion framework is the goal of this work. The proposed framework is designed to improve planning, execution and assessment of demanding maritime operations by adopting newly-designed risk-evaluation tools. Different information from the simulator scene and from the real world can be collected, such as audio, video, bio-metric data from eye-trackers, other sensor data and annotations. This integration is the base for research on novel SA assessment methodologies. This will serve the industry for the purpose of improving operational effectiveness and safety through the use of simulators. In this work, a training methodology based on the concept of briefing/debriefing is adopted based on previous literature. By using this methodology borrowed from similarly demanding applications, the efficiency of the proposed framework is validated in a conceptual case study. In particular, the training procedure, which was previously performed by Statoil and partners, for the world's first sub-sea gas compression plant, in Aasgard, Norway, is considered and reviewed highlighting the potentials of the proposed framework. - Highlights: • A framework for improving SA in demanding maritime training is proposed. • The proposed framework is integrated with the Offshore Simulator Centre AS (OSC). • This

  2. A new approach to self-localization for mobile robots using sensor data fusion

    International Nuclear Information System (INIS)

    Moshiri, B.; Asharif, M.; Hoseim Nezhad, R.

    2002-01-01

    This paper proposes a new approach for calibration of dead reckoning process. Using the well-known UMB mark (University of Michigan Benchmark) is not sufficient for a desirable calibration of dead reckoning. Besides, existing calibration methods usually require explicit measurement of actual motion of the robot. Some recent methods use the smart encoder trailer or long range finder sensors such as ultrasonic or laser range finders for automatic calibration. Manual measurement is necessary in the case of the robots that are not equipped with long-range detectors or such smart encoder trailer. Our proposed approach uses an environment map that is created by fusion of proximity data, in order to calibrate the odometry error automatically. In the new approach, the systematic part of the error is adaptively estimated and compensated by an efficient and incremental maximum likelihood algorithm. Actually, environment map data are fused with the odometry and current sensory data in order to acquire the maximum likelihood estimation. The advantages of the proposed approach are demonstrated in some experiments with Khepera robot. It is shown that the amount of pose estimation error is reduced by a percentage of more than 80%

  3. A Combined Approach of Sensor Data Fusion and Multivariate Geostatistics for Delineation of Homogeneous Zones in an Agricultural Field

    Directory of Open Access Journals (Sweden)

    Annamaria Castrignanò

    2017-12-01

    Full Text Available To assess spatial variability at the very fine scale required by Precision Agriculture, different proximal and remote sensors have been used. They provide large amounts and different types of data which need to be combined. An integrated approach, using multivariate geostatistical data-fusion techniques and multi-source geophysical sensor data to determine simple summary scale-dependent indices, is described here. These indices can be used to delineate management zones to be submitted to differential management. Such a data fusion approach with geophysical sensors was applied in a soil of an agronomic field cropped with tomato. The synthetic regionalized factors determined, contributed to split the 3D edaphic environment into two main horizontal structures with different hydraulic properties and to disclose two main horizons in the 0–1.0-m depth with a discontinuity probably occurring between 0.40 m and 0.70 m. Comparing this partition with the soil properties measured with a shallow sampling, it was possible to verify the coherence in the topsoil between the dielectric properties and other properties more directly related to agronomic management. These results confirm the advantages of using proximal sensing as a preliminary step in the application of site-specific management. Combining disparate spatial data (data fusion is not at all a naive problem and novel and powerful methods need to be developed.

  4. A Combined Approach of Sensor Data Fusion and Multivariate Geostatistics for Delineation of Homogeneous Zones in an Agricultural Field.

    Science.gov (United States)

    Castrignanò, Annamaria; Buttafuoco, Gabriele; Quarto, Ruggiero; Vitti, Carolina; Langella, Giuliano; Terribile, Fabio; Venezia, Accursio

    2017-12-03

    To assess spatial variability at the very fine scale required by Precision Agriculture, different proximal and remote sensors have been used. They provide large amounts and different types of data which need to be combined. An integrated approach, using multivariate geostatistical data-fusion techniques and multi-source geophysical sensor data to determine simple summary scale-dependent indices, is described here. These indices can be used to delineate management zones to be submitted to differential management. Such a data fusion approach with geophysical sensors was applied in a soil of an agronomic field cropped with tomato. The synthetic regionalized factors determined, contributed to split the 3D edaphic environment into two main horizontal structures with different hydraulic properties and to disclose two main horizons in the 0-1.0-m depth with a discontinuity probably occurring between 0.40 m and 0.70 m. Comparing this partition with the soil properties measured with a shallow sampling, it was possible to verify the coherence in the topsoil between the dielectric properties and other properties more directly related to agronomic management. These results confirm the advantages of using proximal sensing as a preliminary step in the application of site-specific management. Combining disparate spatial data (data fusion) is not at all a naive problem and novel and powerful methods need to be developed.

  5. Scene Recognition for Indoor Localization Using a Multi-Sensor Fusion Approach

    Directory of Open Access Journals (Sweden)

    Mengyun Liu

    2017-12-01

    Full Text Available After decades of research, there is still no solution for indoor localization like the GNSS (Global Navigation Satellite System solution for outdoor environments. The major reasons for this phenomenon are the complex spatial topology and RF transmission environment. To deal with these problems, an indoor scene constrained method for localization is proposed in this paper, which is inspired by the visual cognition ability of the human brain and the progress in the computer vision field regarding high-level image understanding. Furthermore, a multi-sensor fusion method is implemented on a commercial smartphone including cameras, WiFi and inertial sensors. Compared to former research, the camera on a smartphone is used to “see” which scene the user is in. With this information, a particle filter algorithm constrained by scene information is adopted to determine the final location. For indoor scene recognition, we take advantage of deep learning that has been proven to be highly effective in the computer vision community. For particle filter, both WiFi and magnetic field signals are used to update the weights of particles. Similar to other fingerprinting localization methods, there are two stages in the proposed system, offline training and online localization. In the offline stage, an indoor scene model is trained by Caffe (one of the most popular open source frameworks for deep learning and a fingerprint database is constructed by user trajectories in different scenes. To reduce the volume requirement of training data for deep learning, a fine-tuned method is adopted for model training. In the online stage, a camera in a smartphone is used to recognize the initial scene. Then a particle filter algorithm is used to fuse the sensor data and determine the final location. To prove the effectiveness of the proposed method, an Android client and a web server are implemented. The Android client is used to collect data and locate a user. The web

  6. Large-Scale, Multi-Sensor Atmospheric Data Fusion Using Hybrid Cloud Computing

    Science.gov (United States)

    Wilson, B. D.; Manipon, G.; Hua, H.; Fetzer, E. J.

    2015-12-01

    NASA's Earth Observing System (EOS) is an ambitious facility for studying global climate change. The mandate now is to combine measurements from the instruments on the "A-Train" platforms (AIRS, MODIS, MLS, and CloudSat) and other Earth probes to enable large-scale studies of climate change over decades. Moving to multi-sensor, long-duration presents serious challenges for large-scale data mining and fusion. For example, one might want to compare temperature and water vapor retrievals from one instrument (AIRS) to another (MODIS), and to a model (ECMWF), stratify the comparisons using a classification of the "cloud scenes" from CloudSat, and repeat the entire analysis over 10 years of data. HySDS is a Hybrid-Cloud Science Data System that has been developed and applied under NASA AIST, MEaSUREs, and ACCESS grants. HySDS uses the SciFlow workflow engine to partition analysis workflows into parallel tasks (e.g. segmenting by time or space) that are pushed into a durable job queue. The tasks are "pulled" from the queue by worker Virtual Machines (VM's) and executed in an on-premise Cloud (Eucalyptus or OpenStack) or at Amazon in the public Cloud or govCloud. In this way, years of data (millions of files) can be processed in a massively parallel way. Input variables (arrays) are pulled on-demand into the Cloud using OPeNDAP URLs or other subsetting services, thereby minimizing the size of the transferred data. We are using HySDS to automate the production of multiple versions of a ten-year A-Train water vapor climatology under a MEASURES grant. We will present the architecture of HySDS, describe the achieved "clock time" speedups in fusing datasets on our own nodes and in the Amazon Cloud, and discuss the Cloud cost tradeoffs for storage, compute, and data transfer. Our system demonstrates how one can pull A-Train variables (Levels 2 & 3) on-demand into the Amazon Cloud, and cache only those variables that are heavily used, so that any number of compute jobs can be

  7. DEVELOPMENT OF A PEDESTRIAN INDOOR NAVIGATION SYSTEM BASED ON MULTI-SENSOR FUSION AND FUZZY LOGIC ESTIMATION ALGORITHMS

    Directory of Open Access Journals (Sweden)

    Y. C. Lai

    2015-05-01

    Full Text Available This paper presents a pedestrian indoor navigation system based on the multi-sensor fusion and fuzzy logic estimation algorithms. The proposed navigation system is a self-contained dead reckoning navigation that means no other outside signal is demanded. In order to achieve the self-contained capability, a portable and wearable inertial measure unit (IMU has been developed. Its adopted sensors are the low-cost inertial sensors, accelerometer and gyroscope, based on the micro electro-mechanical system (MEMS. There are two types of the IMU modules, handheld and waist-mounted. The low-cost MEMS sensors suffer from various errors due to the results of manufacturing imperfections and other effects. Therefore, a sensor calibration procedure based on the scalar calibration and the least squares methods has been induced in this study to improve the accuracy of the inertial sensors. With the calibrated data acquired from the inertial sensors, the step length and strength of the pedestrian are estimated by multi-sensor fusion and fuzzy logic estimation algorithms. The developed multi-sensor fusion algorithm provides the amount of the walking steps and the strength of each steps in real-time. Consequently, the estimated walking amount and strength per step are taken into the proposed fuzzy logic estimation algorithm to estimates the step lengths of the user. Since the walking length and direction are both the required information of the dead reckoning navigation, the walking direction is calculated by integrating the angular rate acquired by the gyroscope of the developed IMU module. Both the walking length and direction are calculated on the IMU module and transmit to a smartphone with Bluetooth to perform the dead reckoning navigation which is run on a self-developed APP. Due to the error accumulating of dead reckoning navigation, a particle filter and a pre-loaded map of indoor environment have been applied to the APP of the proposed navigation system

  8. Development of a Pedestrian Indoor Navigation System Based on Multi-Sensor Fusion and Fuzzy Logic Estimation Algorithms

    Science.gov (United States)

    Lai, Y. C.; Chang, C. C.; Tsai, C. M.; Lin, S. Y.; Huang, S. C.

    2015-05-01

    This paper presents a pedestrian indoor navigation system based on the multi-sensor fusion and fuzzy logic estimation algorithms. The proposed navigation system is a self-contained dead reckoning navigation that means no other outside signal is demanded. In order to achieve the self-contained capability, a portable and wearable inertial measure unit (IMU) has been developed. Its adopted sensors are the low-cost inertial sensors, accelerometer and gyroscope, based on the micro electro-mechanical system (MEMS). There are two types of the IMU modules, handheld and waist-mounted. The low-cost MEMS sensors suffer from various errors due to the results of manufacturing imperfections and other effects. Therefore, a sensor calibration procedure based on the scalar calibration and the least squares methods has been induced in this study to improve the accuracy of the inertial sensors. With the calibrated data acquired from the inertial sensors, the step length and strength of the pedestrian are estimated by multi-sensor fusion and fuzzy logic estimation algorithms. The developed multi-sensor fusion algorithm provides the amount of the walking steps and the strength of each steps in real-time. Consequently, the estimated walking amount and strength per step are taken into the proposed fuzzy logic estimation algorithm to estimates the step lengths of the user. Since the walking length and direction are both the required information of the dead reckoning navigation, the walking direction is calculated by integrating the angular rate acquired by the gyroscope of the developed IMU module. Both the walking length and direction are calculated on the IMU module and transmit to a smartphone with Bluetooth to perform the dead reckoning navigation which is run on a self-developed APP. Due to the error accumulating of dead reckoning navigation, a particle filter and a pre-loaded map of indoor environment have been applied to the APP of the proposed navigation system to extend its

  9. Toward High Altitude Airship Ground-Based Boresight Calibration of Hyperspectral Pushbroom Imaging Sensors

    Directory of Open Access Journals (Sweden)

    Aiwu Zhang

    2015-12-01

    Full Text Available The complexity of the single linear hyperspectral pushbroom imaging based on a high altitude airship (HAA without a three-axis stabilized platform is much more than that based on the spaceborne and airborne. Due to the effects of air pressure, temperature and airflow, the large pitch and roll angles tend to appear frequently that create pushbroom images highly characterized with severe geometric distortions. Thus, the in-flight calibration procedure is not appropriate to apply to the single linear pushbroom sensors on HAA having no three-axis stabilized platform. In order to address this problem, a new ground-based boresight calibration method is proposed. Firstly, a coordinate’s transformation model is developed for direct georeferencing (DG of the linear imaging sensor, and then the linear error equation is derived from it by using the Taylor expansion formula. Secondly, the boresight misalignments are worked out by using iterative least squares method with few ground control points (GCPs and ground-based side-scanning experiments. The proposed method is demonstrated by three sets of experiments: (i the stability and reliability of the method is verified through simulation-based experiments; (ii the boresight calibration is performed using ground-based experiments; and (iii the validation is done by applying on the orthorectification of the real hyperspectral pushbroom images from a HAA Earth observation payload system developed by our research team—“LanTianHao”. The test results show that the proposed boresight calibration approach significantly improves the quality of georeferencing by reducing the geometric distortions caused by boresight misalignments to the minimum level.

  10. Estimation of Vertical Ground Reaction Forces and Sagittal Knee Kinematics During Running Using Three Inertial Sensors

    Directory of Open Access Journals (Sweden)

    Frank J. Wouda

    2018-03-01

    Full Text Available Analysis of running mechanics has traditionally been limited to a gait laboratory using either force plates or an instrumented treadmill in combination with a full-body optical motion capture system. With the introduction of inertial motion capture systems, it becomes possible to measure kinematics in any environment. However, kinetic information could not be provided with such technology. Furthermore, numerous body-worn sensors are required for a full-body motion analysis. The aim of this study is to examine the validity of a method to estimate sagittal knee joint angles and vertical ground reaction forces during running using an ambulatory minimal body-worn sensor setup. Two concatenated artificial neural networks were trained (using data from eight healthy subjects to estimate the kinematics and kinetics of the runners. The first artificial neural network maps the information (orientation and acceleration of three inertial sensors (placed at the lower legs and pelvis to lower-body joint angles. The estimated joint angles in combination with measured vertical accelerations are input to a second artificial neural network that estimates vertical ground reaction forces. To validate our approach, estimated joint angles were compared to both inertial and optical references, while kinetic output was compared to measured vertical ground reaction forces from an instrumented treadmill. Performance was evaluated using two scenarios: training and evaluating on a single subject and training on multiple subjects and evaluating on a different subject. The estimated kinematics and kinetics of most subjects show excellent agreement (ρ>0.99 with the reference, for single subject training. Knee flexion/extension angles are estimated with a mean RMSE <5°. Ground reaction forces are estimated with a mean RMSE < 0.27 BW. Additionaly, peak vertical ground reaction force, loading rate and maximal knee flexion during stance were compared, however, no significant

  11. Three-dimensional fusion of spaceborne and ground radar reflectivity data using a neural network-based approach

    Science.gov (United States)

    Kou, Leilei; Wang, Zhuihui; Xu, Fen

    2018-03-01

    The spaceborne precipitation radar onboard the Tropical Rainfall Measuring Mission satellite (TRMM PR) can provide good measurement of the vertical structure of reflectivity, while ground radar (GR) has a relatively high horizontal resolution and greater sensitivity. Fusion of TRMM PR and GR reflectivity data may maximize the advantages from both instruments. In this paper, TRMM PR and GR reflectivity data are fused using a neural network (NN)-based approach. The main steps included are: quality control of TRMM PR and GR reflectivity data; spatiotemporal matchup; GR calibration bias correction; conversion of TRMM PR data from Ku to S band; fusion of TRMM PR and GR reflectivity data with an NN method; interpolation of reflectivity data that are below PR's sensitivity; blind areas compensation with a distance weighting-based merging approach; combination of three types of data: data with the NN method, data below PR's sensitivity and data within compensated blind areas. During the NN fusion step, the TRMM PR data are taken as targets of the training NNs, and gridded GR data after horizontal downsampling at different heights are used as the input. The trained NNs are then used to obtain 3D high-resolution reflectivity from the original GR gridded data. After 3D fusion of the TRMM PR and GR reflectivity data, a more complete and finer-scale 3D radar reflectivity dataset incorporating characteristics from both the TRMM PR and GR observations can be obtained. The fused reflectivity data are evaluated based on a convective precipitation event through comparison with the high resolution TRMM PR and GR data with an interpolation algorithm.

  12. Detection capability of a pulsed Ground Penetrating Radar utilizing an oscilloscope and Radargram Fusion Approach for optimal signal quality

    Science.gov (United States)

    Seyfried, Daniel; Schoebel, Joerg

    2015-07-01

    In scientific research pulsed radars often employ a digital oscilloscope as sampling unit. The sensitivity of an oscilloscope is determined in general by means of the number of digits of its analog-to-digital converter and the selected full scale vertical setting, i.e., the maximal voltage range displayed. Furthermore oversampling or averaging of the input signal may increase the effective number of digits, hence the sensitivity. Especially for Ground Penetrating Radar applications high sensitivity of the radar system is demanded since reflection amplitudes of buried objects are strongly attenuated in ground. Hence, in order to achieve high detection capability this parameter is one of the most crucial ones. In this paper we analyze the detection capability of our pulsed radar system utilizing a Rohde & Schwarz RTO 1024 oscilloscope as sampling unit for Ground Penetrating Radar applications, such as detection of pipes and cables in the ground. Also effects of averaging and low-noise amplification of the received signal prior to sampling are investigated by means of an appropriate laboratory setup. To underline our findings we then present real-world radar measurements performed on our GPR test site, where we have buried pipes and cables of different types and materials in different depths. The results illustrate the requirement for proper choice of the settings of the oscilloscope for optimal data recording. However, as we show, displaying both strong signal contributions due to e.g., antenna cross-talk and direct ground bounce reflection as well as weak reflections from objects buried deeper in ground requires opposing trends for the oscilloscope's settings. We therefore present our Radargram Fusion Approach. By means of this approach multiple radargrams recorded in parallel, each with an individual optimized setting for a certain type of contribution, can be fused in an appropriate way in order to finally achieve a single radargram which displays all

  13. Nighttime Infrared radiative cooling and opacity inferred by REMS Ground Temperature Sensor Measurements

    Science.gov (United States)

    Martín-Torres, Javier; Paz Zorzano, María; Pla-García, Jorge; Rafkin, Scot; Lepinette, Alain; Sebastián, Eduardo; Gómez-Elvira, Javier; REMS Team

    2013-04-01

    Due to the low density of the Martian atmosphere, the temperature of the surface is controlled primarily by solar heating, and infrared cooling to the atmosphere and space, rather than heat exchange with the atmosphere. In the absence of solar radiation the infrared (IR) cooling, and then the nighttime surface temperatures, are directly controlled by soil termal inertia and atmospheric optical thickness (τ) at infrared wavelengths. Under non-wind conditions, and assuming no processes involving latent heat changes in the surface, for a particular site where the rover stands the main parameter controlling the IR cooling will be τ. The minimal ground temperature values at a fixed position may thus be used to detect local variations in the total dust/aerosols/cloud tickness. The Ground Temperature Sensor (GTS) and Air Temperature Sensor (ATS) in the Rover Environmental Monitoring Station (REMS) on board the Mars Science Laboratory (MSL) Curiosity rover provides hourly ground and air temperature measurements respectively. During the first 100 sols of operation of the rover, within the area of low thermal inertia, the minimal nightime ground temperatures reached values between 180 K and 190 K. For this season the expected frost point temperature is 200 K. Variations of up to 10 K have been observed associated with dust loading at Gale at the onset of the dust season. We will use these measurements together with line-by-line radiative transfer simulations using the Full Transfer By Optimized LINe-by-line (FUTBOLIN) code [Martín-Torres and Mlynczak, 2005] to estimate the IR atmospheric opacity and then dust/cloud coverage over the rover during the course of the MSL mission. Monitoring the dust loading and IR nightime cooling evolution during the dust season will allow for a better understanding of the influence of the atmosphere on the ground temperature and provide ground truth to models and orbiter measurements. References Martín-Torres, F. J. and M. G. Mlynczak

  14. Disposable Multi-Sensor Unattended Ground Sensor Systems for Detecting Personnel (Systemes de detection multi-capteurs terrestres autonome destines a detecter du personnel)

    Science.gov (United States)

    2015-02-01

    the set of DCT coefficients for all the training data corresponding to the people. Then, the matrix ][ pX can be written as: ][][][ −+ −= ppp XXX ...deployed on two types of ground conditions. This included ARL multi-modal sensors, video and acoustic sensors from the Universities of Memphis and...Mississippi, SASNet from Canada, video from Night Vision Laboratory and Pearls of Wisdom system from Israel operated in conjunction with ARL personnel. This

  15. Reliability of measured data for pH sensor arrays with fault diagnosis and data fusion based on LabVIEW.

    Science.gov (United States)

    Liao, Yi-Hung; Chou, Jung-Chuan; Lin, Chin-Yi

    2013-12-13

    Fault diagnosis (FD) and data fusion (DF) technologies implemented in the LabVIEW program were used for a ruthenium dioxide pH sensor array. The purpose of the fault diagnosis and data fusion technologies is to increase the reliability of measured data. Data fusion is a very useful statistical method used for sensor arrays in many fields. Fault diagnosis is used to avoid sensor faults and to measure errors in the electrochemical measurement system, therefore, in this study, we use fault diagnosis to remove any faulty sensors in advance, and then proceed with data fusion in the sensor array. The average, self-adaptive and coefficient of variance data fusion methods are used in this study. The pH electrode is fabricated with ruthenium dioxide (RuO2) sensing membrane using a sputtering system to deposit it onto a silicon substrate, and eight RuO2 pH electrodes are fabricated to form a sensor array for this study.

  16. Reliability of Measured Data for pH Sensor Arrays with Fault Diagnosis and Data Fusion Based on LabVIEW

    Directory of Open Access Journals (Sweden)

    Yi-Hung Liao

    2013-12-01

    Full Text Available Fault diagnosis (FD and data fusion (DF technologies implemented in the LabVIEW program were used for a ruthenium dioxide pH sensor array. The purpose of the fault diagnosis and data fusion technologies is to increase the reliability of measured data. Data fusion is a very useful statistical method used for sensor arrays in many fields. Fault diagnosis is used to avoid sensor faults and to measure errors in the electrochemical measurement system, therefore, in this study, we use fault diagnosis to remove any faulty sensors in advance, and then proceed with data fusion in the sensor array. The average, self-adaptive and coefficient of variance data fusion methods are used in this study. The pH electrode is fabricated with ruthenium dioxide (RuO2 sensing membrane using a sputtering system to deposit it onto a silicon substrate, and eight RuO2 pH electrodes are fabricated to form a sensor array for this study.

  17. Decentralized vs. centralized scheduling in wireless sensor networks for data fusion

    OpenAIRE

    Mitici, M.A.; Goseling, Jasper; de Graaf, Maurits; Boucherie, Richardus J.

    2014-01-01

    We consider the problem of data estimation in a sensor wireless network where sensors transmit their observations according to decentralized and centralized transmission schedules. A data collector is interested in achieving a data estimation using several sensor observations such that the variance of the estimation is below a targeted threshold. We analyze the waiting time for a collector to receive sufficient sensor observations. We show that, for sufficiently large sensor sets, the decentr...

  18. Robust Sequential Covariance Intersection Fusion Kalman Filtering over Multi-agent Sensor Networks with Measurement Delays and Uncertain Noise Variances

    Institute of Scientific and Technical Information of China (English)

    QI Wen-Juan; ZHANG Peng; DENG Zi-Li

    2014-01-01

    This paper deals with the problem of designing robust sequential covariance intersection (SCI) fusion Kalman filter for the clustering multi-agent sensor network system with measurement delays and uncertain noise variances. The sensor network is partitioned into clusters by the nearest neighbor rule. Using the minimax robust estimation principle, based on the worst-case conservative sensor network system with conservative upper bounds of noise variances, and applying the unbiased linear minimum variance (ULMV) optimal estimation rule, we present the two-layer SCI fusion robust steady-state Kalman filter which can reduce communication and computation burdens and save energy sources, and guarantee that the actual filtering error variances have a less-conservative upper-bound. A Lyapunov equation method for robustness analysis is proposed, by which the robustness of the local and fused Kalman filters is proved. The concept of the robust accuracy is presented and the robust accuracy relations of the local and fused robust Kalman filters are proved. It is proved that the robust accuracy of the global SCI fuser is higher than those of the local SCI fusers and the robust accuracies of all SCI fusers are higher than that of each local robust Kalman filter. A simulation example for a tracking system verifies the robustness and robust accuracy relations.

  19. Detection scheme for a partially occluded pedestrian based on occluded depth in lidar-radar sensor fusion

    Science.gov (United States)

    Kwon, Seong Kyung; Hyun, Eugin; Lee, Jin-Hee; Lee, Jonghun; Son, Sang Hyuk

    2017-11-01

    Object detections are critical technologies for the safety of pedestrians and drivers in autonomous vehicles. Above all, occluded pedestrian detection is still a challenging topic. We propose a new detection scheme for occluded pedestrian detection by means of lidar-radar sensor fusion. In the proposed method, the lidar and radar regions of interest (RoIs) have been selected based on the respective sensor measurement. Occluded depth is a new means to determine whether an occluded target exists or not. The occluded depth is a region projected out by expanding the longitudinal distance with maintaining the angle formed by the outermost two end points of the lidar RoI. The occlusion RoI is the overlapped region made by superimposing the radar RoI and the occluded depth. The object within the occlusion RoI is detected by the radar measurement information and the occluded object is estimated as a pedestrian based on human Doppler distribution. Additionally, various experiments are performed in detecting a partially occluded pedestrian in outdoor as well as indoor environments. According to experimental results, the proposed sensor fusion scheme has much better detection performance compared to the case without our proposed method.

  20. A Method for Improving the Pose Accuracy of a Robot Manipulator Based on Multi-Sensor Combined Measurement and Data Fusion

    Science.gov (United States)

    Liu, Bailing; Zhang, Fumin; Qu, Xinghua

    2015-01-01

    An improvement method for the pose accuracy of a robot manipulator by using a multiple-sensor combination measuring system (MCMS) is presented. It is composed of a visual sensor, an angle sensor and a series robot. The visual sensor is utilized to measure the position of the manipulator in real time, and the angle sensor is rigidly attached to the manipulator to obtain its orientation. Due to the higher accuracy of the multi-sensor, two efficient data fusion approaches, the Kalman filter (KF) and multi-sensor optimal information fusion algorithm (MOIFA), are used to fuse the position and orientation of the manipulator. The simulation and experimental results show that the pose accuracy of the robot manipulator is improved dramatically by 38%∼78% with the multi-sensor data fusion. Comparing with reported pose accuracy improvement methods, the primary advantage of this method is that it does not require the complex solution of the kinematics parameter equations, increase of the motion constraints and the complicated procedures of the traditional vision-based methods. It makes the robot processing more autonomous and accurate. To improve the reliability and accuracy of the pose measurements of MCMS, the visual sensor repeatability is experimentally studied. An optimal range of 1 × 0.8 × 1 ∼ 2 × 0.8 × 1 m in the field of view (FOV) is indicated by the experimental results. PMID:25850067

  1. Geospace Science from Ground-based Magnetometer Arrays: Advances in Sensors, Data Collection, and Data Integration

    Science.gov (United States)

    Mann, Ian; Chi, Peter

    2016-07-01

    Networks of ground-based magnetometers now provide the basis for the diagnosis of magnetic disturbances associated with solar wind-magnetosphere-ionosphere coupling on a truly global scale. Advances in sensor and digitisation technologies offer increases in sensitivity in fluxgate, induction coil, and new micro-sensor technologies - including the promise of hybrid sensors. Similarly, advances in remote connectivity provide the capacity for truly real-time monitoring of global dynamics at cadences sufficient for monitoring and in many cases resolving system level spatio-temporal ambiguities especially in combination with conjugate satellite measurements. A wide variety of the plasmaphysical processes active in driving geospace dynamics can be monitored based on the response of the electrical current system, including those associated with changes in global convection, magnetospheric substorms and nightside tail flows, as well as due to solar wind changes in both dynamic pressure and in response to rotations of the direction of the IMF. Significantly, any changes to the dynamical system must be communicated by the propagation of long-period Alfven and/or compressional waves. These wave populations hence provide diagnostics for not only the energy transport by the wave fields themselves, but also provide a mechanism for diagnosing the structure of the background plasma medium through which the waves propagate. Ultra-low frequency (ULF) waves are especially significant in offering a monitor for mass density profiles, often invisible to particle detectors because of their very low energy, through the application of a variety of magneto-seismology and cross-phase techniques. Renewed scientific interest in the plasma waves associated with near-Earth substorm dynamics, including magnetosphere-ionosphere coupling at substorm onset and their relation to magnetotail flows, as well the importance of global scale ultra-low frequency waves for the energisation, transport

  2. Detection of water-quality contamination events based on multi-sensor fusion using an extented Dempster–Shafer method

    International Nuclear Information System (INIS)

    Hou, Dibo; He, Huimei; Huang, Pingjie; Zhang, Guangxin; Loaiciga, Hugo

    2013-01-01

    This study presents a method for detecting contamination events of sources of drinking water based on the Dempster–Shafer (D-S) evidence theory. The detection method has the purpose of protecting water supply systems against accidental and intentional contamination events. This purpose is achieved by first predicting future water-quality parameters using an autoregressive (AR) model. The AR model predicts future water-quality parameters using recent measurements of these parameters made with automated (on-line) water-quality sensors. Next, a probabilistic method assigns probabilities to the time series of residuals formed by comparing predicted water-quality parameters with threshold values. Finally, the D-S fusion method searches for anomalous probabilities of the residuals and uses the result of that search to determine whether the current water quality is normal (that is, free of pollution) or contaminated. The D-S fusion method is extended and improved in this paper by weighted averaging of water-contamination evidence and by the analysis of the persistence of anomalous probabilities of water-quality parameters. The extended D-S fusion method makes determinations that have a high probability of being correct concerning whether or not a source of drinking water has been contaminated. This paper's method for detecting water-contamination events was tested with water-quality time series from automated (on-line) water quality sensors. In addition, a small-scale, experimental, water-pipe network was tested to detect water-contamination events. The two tests demonstrated that the extended D-S fusion method achieves a low false alarm rate and high probabilities of detecting water contamination events. (paper)

  3. Improving mine recognition through processing and Dempster-Shafer fusion of ground-penetrating radar data

    NARCIS (Netherlands)

    Milisavljević, N.; Bloch, I.; Broek, S.P. van den; Acheroy, M.

    2003-01-01

    A methodfor modeling andcombination of measures extractedfrom a ground-penetrating radar (GPR) in terms of belief functions within the Dempster-Shafer framework is presentedandillustratedon a real GPR data set. A starting point in the analysis is a preprocessed C-scan of a sand-lane containing some

  4. Overview of Sensor Fusion Research at RDECOM NVESD & Recent Results on Vehicle Detection Using Multiple Sensor Nodes

    National Research Council Canada - National Science Library

    Perconti, Philip; Hilger, James; Loew, Murry

    2003-01-01

    .... This paper provides an overview of the on going research at NVESD related to fusing a mixture of active and passive sensors for countermine, dismounted AND mounted soldiers, aviation and unattended...

  5. Decentralized vs. centralized scheduling in wireless sensor networks for data fusion

    NARCIS (Netherlands)

    Mitici, M.A.; Goseling, Jasper; de Graaf, Maurits; Boucherie, Richardus J.

    2014-01-01

    We consider the problem of data estimation in a sensor wireless network where sensors transmit their observations according to decentralized and centralized transmission schedules. A data collector is interested in achieving a data estimation using several sensor observations such that the variance

  6. Decentralized vs. centralized scheduling in wireless sensor networks for data fusion

    NARCIS (Netherlands)

    Mitici, Mihaela; Goseling, Jasper; de Graaf, Maurits; Boucherie, Richardus J.

    2013-01-01

    We consider the problem of data estimation in a sensor wireless network where sensors transmit their observations according to decentralized and centralized transmission schedules. A data collector is interested in achieving a data estimation using several sensor observations such that the variance

  7. A low-noise MEMS accelerometer for unattended ground sensor applications

    Science.gov (United States)

    Speller, Kevin E.; Yu, Duli

    2004-09-01

    A low-noise micro-machined servo accelerometer has been developed for use in Unattended Ground Sensors (UGS). Compared to conventional coil-and-magnet based velocity transducers, this Micro-Electro-Mechanical System (MEMS) accelerometer offers several key benefits for battlefield monitoring. Many UGS require a compass to determine deployment orientation with respect to magnetic North. This orientation information is critical for determining the bearing of incoming signals. Conventional sensors with sensing technology based on a permanent magnet can cause interference with a compass when used in close proximity. This problem is solved with a MEMS accelerometer which does not require any magnetic materials. Frequency information below 10 Hz is valuable for identification of signal sources. Conventional seismometers used in UGS are typically limited in frequency response from 20 to 200 Hz. The MEMS accelerometer has a flat frequency response from DC to 5 kHz. The wider spectrum of signals received improves detection, classification and monitoring on the battlefield. The DC-coupled output of the MEMS accelerometer also has the added benefit of providing tilt orientation data for the deployed UGS. Other performance parameters of the MEMS accelerometer that are important to UGS such as size, weight, shock survivability, phase response, distortion, and cross-axis rejection will be discussed. Additionally, field test data from human footsteps recorded with the MEMS accelerometer will be presented.

  8. Instrumental intelligent test of food sensory quality as mimic of human panel test combining multiple cross-perception sensors and data fusion.

    Science.gov (United States)

    Ouyang, Qin; Zhao, Jiewen; Chen, Quansheng

    2014-09-02

    Instrumental test of food quality using perception sensors instead of human panel test is attracting massive attention recently. A novel cross-perception multi-sensors data fusion imitating multiple mammal perception was proposed for the instrumental test in this work. First, three mimic sensors of electronic eye, electronic nose and electronic tongue were used in sequence for data acquisition of rice wine samples. Then all data from the three different sensors were preprocessed and merged. Next, three cross-perception variables i.e., color, aroma and taste, were constructed using principal components analysis (PCA) and multiple linear regression (MLR) which were used as the input of models. MLR, back-propagation artificial neural network (BPANN) and support vector machine (SVM) were comparatively used for modeling, and the instrumental test was achieved for the comprehensive quality of samples. Results showed the proposed cross-perception multi-sensors data fusion presented obvious superiority to the traditional data fusion methodologies, also achieved a high correlation coefficient (>90%) with the human panel test results. This work demonstrated that the instrumental test based on the cross-perception multi-sensors data fusion can actually mimic the human test behavior, therefore is of great significance to ensure the quality of products and decrease the loss of the manufacturers. Copyright © 2014 Elsevier B.V. All rights reserved.

  9. Aircraft monitoring by the fusion of satellite and ground ADS-B data

    Science.gov (United States)

    Zhang, Xuan; Zhang, Jingjing; Wu, Shufan; Cheng, Qian; Zhu, Rui

    2018-02-01

    The Automatic Dependent Surveillance- Broadcast (ADS-B) system is today a standard equipment on civil aircraft, transmitting periodically data packages containing information of key data such as aircraft ID, position, altitude and intention. It is designed for terrestrial based ground station to monitor air traffic flow in certain regions. Space based ADS-B is the idea to place sensitive receivers on board satellites in orbit, which can receive ADS-B packages and relay them the relevant ground stations. The terrestrial ADS-B receiver has been widely applied for airport information system, help monitor and control traffic flow, etc. However, its coverage is strongly limited by sea or mountain conditions. This paper first introduces the CubeSat mission, then discusses the integrated application of ADS-B data received from ground stations and from satellites, analyze their characteristics with statistical results of comparison, and explore the technologies to fuse these two different data resources for an integrated application. The satellite data is based on a Chinese CubeSat, STU-2C, being launched into space on Sept 25th 2015. The ADS-B data received from two different resources have shown a good complementary each other, such as to increase the coverage of space for air traffic, and to monitor the whole space in a better and complete way.

  10. Thermophysical Properties Along Curiosity's Traverse in Gale Crater, Mars, Derived from the REMS Ground Temperature Sensor

    Science.gov (United States)

    Vasavada, Ashwin R.; Piqueux, Sylvain; Lewis, Kevin W.; Lemmon, Mark T.; Smith, Michael Doyle

    2016-01-01

    The REMS instrument onboard the Mars Science Laboratory rover, Curiosity, has measured ground temperature nearly continuously at hourly intervals for two Mars years. Coverage of the entire diurnal cycle at 1 Hz is available every few martian days. We compare these measurements with predictions of surface atmosphere thermal models to derive the apparent thermal inertia and thermally derived albedo along the rovers traverse after accounting for the radiative effects of atmospheric water ice during fall and winter, as is necessary to match the measured seasonal trend. The REMS measurements can distinguish between active sand, other loose materials, mudstone, and sandstone based on their thermophysical properties. However, the apparent thermal inertias of bedrock dominated surfaces [approx. 350-550 J m(exp. -2) K(exp. -1 s(exp. -1/2 )] are lower than expected. We use rover imagery and the detailed shape of the diurnal ground temperature curve to explore whether lateral or vertical heterogeneity in the surface materials within the sensor footprint might explain the low inertias. We find that the bedrock component of the surface can have a thermal inertia as high as 650-1700 J m(exp. -2) K(exp. -1) s(exp. -1/2) for mudstone sites and approx. 700 J m(exp. -2) K(exp. -1) s(exp. - 1/2) for sandstone sites in models runs that include lateral and vertical mixing. Although the results of our forward modeling approach may be non-unique, they demonstrate the potential to extract information about lateral and vertical variations in thermophysical properties from temporally resolved measurements of ground temperature.

  11. Integrated active fire retrievals and biomass burning emissions using complementary near-coincident ground, airborne and spaceborne sensor data

    Science.gov (United States)

    Wilfrid Schroeder; Evan Ellicott; Charles Ichoku; Luke Ellison; Matthew B. Dickinson; Roger D. Ottmar; Craig Clements; Dianne Hall; Vincent Ambrosia; Robert. Kremens

    2013-01-01

    Ground, airborne and spaceborne data were collected for a 450 ha prescribed fire implemented on 18 October 2011 at the Henry W. Coe State Park in California. The integration of various data elements allowed near-coincident active fire retrievals to be estimated. The Autonomous Modular Sensor-Wildfire (AMS) airborne multispectral imaging system was used as a bridge...

  12. Fuzzy Risk Evaluation in Failure Mode and Effects Analysis Using a D Numbers Based Multi-Sensor Information Fusion Method.

    Science.gov (United States)

    Deng, Xinyang; Jiang, Wen

    2017-09-12

    Failure mode and effect analysis (FMEA) is a useful tool to define, identify, and eliminate potential failures or errors so as to improve the reliability of systems, designs, and products. Risk evaluation is an important issue in FMEA to determine the risk priorities of failure modes. There are some shortcomings in the traditional risk priority number (RPN) approach for risk evaluation in FMEA, and fuzzy risk evaluation has become an important research direction that attracts increasing attention. In this paper, the fuzzy risk evaluation in FMEA is studied from a perspective of multi-sensor information fusion. By considering the non-exclusiveness between the evaluations of fuzzy linguistic variables to failure modes, a novel model called D numbers is used to model the non-exclusive fuzzy evaluations. A D numbers based multi-sensor information fusion method is proposed to establish a new model for fuzzy risk evaluation in FMEA. An illustrative example is provided and examined using the proposed model and other existing method to show the effectiveness of the proposed model.

  13. A Novel Evidence Theory and Fuzzy Preference Approach-Based Multi-Sensor Data Fusion Technique for Fault Diagnosis

    Directory of Open Access Journals (Sweden)

    Fuyuan Xiao

    2017-10-01

    Full Text Available The multi-sensor data fusion technique plays a significant role in fault diagnosis and in a variety of such applications, and the Dempster–Shafer evidence theory is employed to improve the system performance; whereas, it may generate a counter-intuitive result when the pieces of evidence highly conflict with each other. To handle this problem, a novel multi-sensor data fusion approach on the basis of the distance of evidence, belief entropy and fuzzy preference relation analysis is proposed. A function of evidence distance is first leveraged to measure the conflict degree among the pieces of evidence; thus, the support degree can be obtained to represent the reliability of the evidence. Next, the uncertainty of each piece of evidence is measured by means of the belief entropy. Based on the quantitative uncertainty measured above, the fuzzy preference relations are applied to represent the relative credibility preference of the evidence. Afterwards, the support degree of each piece of evidence is adjusted by taking advantage of the relative credibility preference of the evidence that can be utilized to generate an appropriate weight with respect to each piece of evidence. Finally, the modified weights of the evidence are adopted to adjust the bodies of the evidence in the advance of utilizing Dempster’s combination rule. A numerical example and a practical application in fault diagnosis are used as illustrations to demonstrate that the proposal is reasonable and efficient in the management of conflict and fault diagnosis.

  14. Recognition of Wheat Spike from Field Based Phenotype Platform Using Multi-Sensor Fusion and Improved Maximum Entropy Segmentation Algorithms

    Directory of Open Access Journals (Sweden)

    Chengquan Zhou

    2018-02-01

    Full Text Available To obtain an accurate count of wheat spikes, which is crucial for estimating yield, this paper proposes a new algorithm that uses computer vision to achieve this goal from an image. First, a home-built semi-autonomous multi-sensor field-based phenotype platform (FPP is used to obtain orthographic images of wheat plots at the filling stage. The data acquisition system of the FPP provides high-definition RGB images and multispectral images of the corresponding quadrats. Then, the high-definition panchromatic images are obtained by fusion of three channels of RGB. The Gram–Schmidt fusion algorithm is then used to fuse these multispectral and panchromatic images, thereby improving the color identification degree of the targets. Next, the maximum entropy segmentation method is used to do the coarse-segmentation. The threshold of this method is determined by a firefly algorithm based on chaos theory (FACT, and then a morphological filter is used to de-noise the coarse-segmentation results. Finally, morphological reconstruction theory is applied to segment the adhesive part of the de-noised image and realize the fine-segmentation of the image. The computer-generated counting results for the wheat plots, using independent regional statistical function in Matlab R2017b software, are then compared with field measurements which indicate that the proposed method provides a more accurate count of wheat spikes when compared with other traditional fusion and segmentation methods mentioned in this paper.

  15. Satellite and ground-based sensors for the Urban Heat Island analysis in the city of Rome

    DEFF Research Database (Denmark)

    Fabrizi, Roberto; Bonafoni, Stefania; Biondi, Riccardo

    2010-01-01

    In this work, the trend of the Urban Heat Island (UHI) of Rome is analyzed by both ground-based weather stations and a satellite-based infrared sensor. First, we have developed a suitable algorithm employing satellite brightness temperatures for the estimation of the air temperature belonging...... and nighttime scenes taken between 2003 and 2006 have been processed. Analysis of the Canopy Layer Heat Island (CLHI) during summer months reveals a mean growth in magnitude of 3-4 K during nighttime and a negative or almost zero CLHI intensity during daytime, confirmed by the weather stations. © 2010...... by the authors; licensee MDPI, Basel, Switzerland. Keyword: Thermal pollution,Summer months,Advanced-along track scanning radiometers,Urban heat island,Remote sensing,Canopy layer,Atmospheric temperature,Ground based sensors,Weather information services,Satellite remote sensing,Infra-red sensor,Weather stations...

  16. On-the-go throughput prediction in a combine harvester using sensor fusion

    DEFF Research Database (Denmark)

    Hermann, Dan; Bilde, Morten L.; Andersen, Nils Axel

    2017-01-01

    of the current grain throughput is obtained, hence the effect from the lag in the momentary yield sensor reading due to material transport delays can be reduced. Statistical change detection is used to detect feederhouse load condition as well as sensor discrepancies using the observer innovation signal...

  17. Multi-sensor fusion using an adaptive multi-hypothesis tracking algorithm

    NARCIS (Netherlands)

    Kester, L.J.H.M.

    2003-01-01

    The purpose of a tracking algorithm is to associate data measured by one or more (moving) sensors to moving objects in the environment. The state of these objects that can be estimated with the tracking process depends on the type of data that is provided by these sensors. It is discussed how the

  18. Distributed service-based approach for sensor data fusion in IoT environments.

    Science.gov (United States)

    Rodríguez-Valenzuela, Sandra; Holgado-Terriza, Juan A; Gutiérrez-Guerrero, José M; Muros-Cobos, Jesús L

    2014-10-15

    The Internet of Things (IoT) enables the communication among smart objects promoting the pervasive presence around us of a variety of things or objects that are able to interact and cooperate jointly to reach common goals. IoT objects can obtain data from their context, such as the home, office, industry or body. These data can be combined to obtain new and more complex information applying data fusion processes. However, to apply data fusion algorithms in IoT environments, the full system must deal with distributed nodes, decentralized communication and support scalability and nodes dynamicity, among others restrictions. In this paper, a novel method to manage data acquisition and fusion based on a distributed service composition model is presented, improving the data treatment in IoT pervasive environments.

  19. Thin film metal sensors in fusion bonded glass chips for high-pressure microfluidics

    International Nuclear Information System (INIS)

    Andersson, Martin; Ek, Johan; Hedman, Ludvig; Johansson, Fredrik; Sehlstedt, Viktor; Stocklassa, Jesper; Snögren, Pär; Pettersson, Victor; Larsson, Jonas; Vizuete, Olivier; Hjort, Klas; Klintberg, Lena

    2017-01-01

    High-pressure microfluidics offers fast analyses of thermodynamic parameters for compressed process solvents. However, microfluidic platforms handling highly compressible supercritical CO 2 are difficult to control, and on-chip sensing would offer added control of the devices. Therefore, there is a need to integrate sensors into highly pressure tolerant glass chips. In this paper, thin film Pt sensors were embedded in shallow etched trenches in a glass wafer that was bonded with another glass wafer having microfluidic channels. The devices having sensors integrated into the flow channels sustained pressures up to 220 bar, typical for the operation of supercritical CO 2 . No leakage from the devices could be found. Integrated temperature sensors were capable of measuring local decompression cooling effects and integrated calorimetric sensors measured flow velocities over the range 0.5–13.8 mm s −1 . By this, a better control of high-pressure microfluidic platforms has been achieved. (paper)

  20. Coincident Observation of Lightning using Spaceborne Spectrophotometer and Ground-Level Electromagnetic Sensors

    Science.gov (United States)

    Adachi, Toru; Cohen, Morris; Li, Jingbo; Cummer, Steve; Blakeslee, Richard; Marshall, THomas; Stolzenberg, Maribeth; Karunarathne, Sumedhe; Hsu, Rue-Ron; Su, Han-Tzong; hide

    2012-01-01

    The present study aims at assessing a possible new way to reveal the properties of lightning flash, using spectrophotometric data obtained by FORMOSAT-2/ISUAL which is the first spaceborne multicolor lightning detector. The ISUAL data was analyzed in conjunction with ground ]based electromagnetic data obtained by Duke magnetic field sensors, NLDN, North Alabama Lightning Mapping Array (LMA), and Kennedy Space Center (KSC) electric field antennas. We first classified the observed events into cloud ]to ]ground (CG) and intra ]cloud (IC) lightning based on the Duke and NLDN measurements and analyzed ISUAL data to clarify their optical characteristics. It was found that the ISUAL optical waveform of CG lightning was strongly correlated with the current moment waveform, suggesting that it is possible to evaluate the electrical properties of lightning from satellite optical measurement to some extent. The ISUAL data also indicated that the color of CG lightning turned to red at the time of return stroke while the color of IC pulses remained unchanged. Furthermore, in one CG event which was simultaneously detected by ISUAL and LMA, the observed optical emissions slowly turned red as the altitude of optical source gradually decreased. All of these results indicate that the color of lightning flash depends on the source altitude and suggest that spaceborne optical measurement could be a new tool to discriminate CG and IC lightning. In the presentation, we will also show results on the comparison between the ISUAL and KSC electric field data to clarify characteristics of each lightning process such as preliminary breakdown, return stroke, and subsequent upward illumination.

  1. Perception-oriented fusion of multi-sensor imagery: visible, IR, and SAR

    Science.gov (United States)

    Sidorchuk, D.; Volkov, V.; Gladilin, S.

    2018-04-01

    This paper addresses the problem of image fusion of optical (visible and thermal domain) data and radar data for the purpose of visualization. These types of images typically contain a lot of complimentary information, and their joint visualization can be useful and more convenient for human user than a set of individual images. To solve the image fusion problem we propose a novel algorithm that utilizes some peculiarities of human color perception and based on the grey-scale structural visualization. Benefits of presented algorithm are exemplified by satellite imagery.

  2. A Multi-Sensor Acquisition Architecture and Real-Time Reference for Sensor and Fusion Methods Benchmarking

    OpenAIRE

    KAIS, Mikaël; MILLESCAMPS, Damien; BETAILLE, David; LUSETTI, Benoît; CHAPELON, Antoine

    2006-01-01

    Localization is a key functionality for Advance Driving Assistance Systems (ADAS) as well as for Vehicle-Vehicle or Vehicle-Infrastructure cooperation. Indeed, depending on the accuracy and integrity of the localization process, applications such as driver information, driver assistance or even fully autonomous driving can be performed. This paper presents a multi-sensor acquisition architecture for localization. Special attention has been given to main parameters that can affect the accuracy...

  3. Neuromorphic infrared focal plane performs sensor fusion on-plane local-contrast-enhancement spatial and temporal filtering

    Science.gov (United States)

    Massie, Mark A.; Woolaway, James T., II; Curzan, Jon P.; McCarley, Paul L.

    1993-08-01

    An infrared focal plane has been simulated, designed and fabricated which mimics the form and function of the vertebrate retina. The `Neuromorphic' focal plane has the capability of performing pixel-based sensor fusion and real-time local contrast enhancement, much like the response of the human eye. The device makes use of an indium antimonide detector array with a 3 - 5 micrometers spectral response, and a switched capacitor resistive network to compute a real-time 2D spatial average. This device permits the summation of other sensor outputs to be combined on-chip with the infrared detections of the focal plane itself. The resulting real-time analog processed information thus represents the combined information of many sensors with the advantage that analog spatial and temporal signal processing is performed at the focal plane. A Gaussian subtraction method is used to produce the pixel output which when displayed produces an image with enhanced edges, representing spatial and temporal derivatives in the scene. The spatial and temporal responses of the device are tunable during operation, permitting the operator to `peak up' the response of the array to spatial and temporally varying signals. Such an array adapts to ambient illumination conditions without loss of detection performance. This paper reviews the Neuromorphic infrared focal plane from initial operational simulations to detailed design characteristics, and concludes with a presentation of preliminary operational data for the device as well as videotaped imagery.

  4. Finite Element Modelling of a Field-Sensed Magnetic Suspended System for Accurate Proximity Measurement Based on a Sensor Fusion Algorithm with Unscented Kalman Filter.

    Science.gov (United States)

    Chowdhury, Amor; Sarjaš, Andrej

    2016-09-15

    The presented paper describes accurate distance measurement for a field-sensed magnetic suspension system. The proximity measurement is based on a Hall effect sensor. The proximity sensor is installed directly on the lower surface of the electro-magnet, which means that it is very sensitive to external magnetic influences and disturbances. External disturbances interfere with the information signal and reduce the usability and reliability of the proximity measurements and, consequently, the whole application operation. A sensor fusion algorithm is deployed for the aforementioned reasons. The sensor fusion algorithm is based on the Unscented Kalman Filter, where a nonlinear dynamic model was derived with the Finite Element Modelling approach. The advantage of such modelling is a more accurate dynamic model parameter estimation, especially in the case when the real structure, materials and dimensions of the real-time application are known. The novelty of the paper is the design of a compact electro-magnetic actuator with a built-in low cost proximity sensor for accurate proximity measurement of the magnetic object. The paper successively presents a modelling procedure with the finite element method, design and parameter settings of a sensor fusion algorithm with Unscented Kalman Filter and, finally, the implementation procedure and results of real-time operation.

  5. Instrumental intelligent test of food sensory quality as mimic of human panel test combining multiple cross-perception sensors and data fusion

    International Nuclear Information System (INIS)

    Ouyang, Qin; Zhao, Jiewen; Chen, Quansheng

    2014-01-01

    Highlights: • To develop a novel instrumental intelligent test methodology for food sensory analysis. • A novel data fusion was used in instrumental intelligent test methodology. • Linear and nonlinear tools were comparatively used for modeling. • The instrumental test methodology can be imitative of human test behavior. - Abstract: Instrumental test of food quality using perception sensors instead of human panel test is attracting massive attention recently. A novel cross-perception multi-sensors data fusion imitating multiple mammal perception was proposed for the instrumental test in this work. First, three mimic sensors of electronic eye, electronic nose and electronic tongue were used in sequence for data acquisition of rice wine samples. Then all data from the three different sensors were preprocessed and merged. Next, three cross-perception variables i.e., color, aroma and taste, were constructed using principal components analysis (PCA) and multiple linear regression (MLR) which were used as the input of models. MLR, back-propagation artificial neural network (BPANN) and support vector machine (SVM) were comparatively used for modeling, and the instrumental test was achieved for the comprehensive quality of samples. Results showed the proposed cross-perception multi-sensors data fusion presented obvious superiority to the traditional data fusion methodologies, also achieved a high correlation coefficient (>90%) with the human panel test results. This work demonstrated that the instrumental test based on the cross-perception multi-sensors data fusion can actually mimic the human test behavior, therefore is of great significance to ensure the quality of products and decrease the loss of the manufacturers

  6. Instrumental intelligent test of food sensory quality as mimic of human panel test combining multiple cross-perception sensors and data fusion

    Energy Technology Data Exchange (ETDEWEB)

    Ouyang, Qin; Zhao, Jiewen; Chen, Quansheng, E-mail: qschen@ujs.edu.cn

    2014-09-02

    Highlights: • To develop a novel instrumental intelligent test methodology for food sensory analysis. • A novel data fusion was used in instrumental intelligent test methodology. • Linear and nonlinear tools were comparatively used for modeling. • The instrumental test methodology can be imitative of human test behavior. - Abstract: Instrumental test of food quality using perception sensors instead of human panel test is attracting massive attention recently. A novel cross-perception multi-sensors data fusion imitating multiple mammal perception was proposed for the instrumental test in this work. First, three mimic sensors of electronic eye, electronic nose and electronic tongue were used in sequence for data acquisition of rice wine samples. Then all data from the three different sensors were preprocessed and merged. Next, three cross-perception variables i.e., color, aroma and taste, were constructed using principal components analysis (PCA) and multiple linear regression (MLR) which were used as the input of models. MLR, back-propagation artificial neural network (BPANN) and support vector machine (SVM) were comparatively used for modeling, and the instrumental test was achieved for the comprehensive quality of samples. Results showed the proposed cross-perception multi-sensors data fusion presented obvious superiority to the traditional data fusion methodologies, also achieved a high correlation coefficient (>90%) with the human panel test results. This work demonstrated that the instrumental test based on the cross-perception multi-sensors data fusion can actually mimic the human test behavior, therefore is of great significance to ensure the quality of products and decrease the loss of the manufacturers.

  7. The role of unattended ground sensors (UGS) in regional confidence building and arms control

    Energy Technology Data Exchange (ETDEWEB)

    Vannoni, M.; Duggan, R.

    1997-03-01

    Although the Cold War has ended, the world has not become more peaceful. Without the stability provided by an international system dominated by two super-powers, local conflicts are more likely to escalate. Agreements to counter destabilizing pressures in regional conflicts can benefit from the use of cooperative monitoring. Cooperative monitoring is the collecting, analyzing, and sharing of information among parties to an agreement. Ground sensor technologies can contribute to the collection of relevant information. If implemented with consideration for local conditions, cooperative monitoring can build confidence, strengthen existing agreements, and set the stage for continued progress. This presentation describes two examples: the Israeli-Egyptian Sinai agreements of the 1970s and a conceptual example for the contemporary Korean Peninsula. The Sinai was a precedent for the successful use of UGS within the context of cooperative monitoring. The Korean Peninsula is the world`s largest military confrontation. Future confidence building measures that address the security needs of both countries could decrease the danger of conflict and help create an environment for a peace agreement.

  8. Ground Motion Analysis of Co-Located DAS and Seismometer Sensors

    Science.gov (United States)

    Wang, H. F.; Fratta, D.; Lord, N. E.; Lancelle, C.; Thurber, C. H.; Zeng, X.; Parker, L.; Chalari, A.; Miller, D.; Feigl, K. L.; Team, P.

    2016-12-01

    The PoroTomo research team deployed 8700-meters of Distributed Acoustic Sensing (DAS) cable in a shallow trench and 400-meters in a borehole at Brady Hot Springs, Nevada in March 2016 together with an array of 246, three-component geophones. The seismic sensors occupied a natural laboratory 1500 x 500 x 400 meters overlying the Brady geothermal field. The DAS cable was laid out in three parallel zig-zag lines with line segments approximately 100-meters in length and geophones were spaced at approximately 50-m intervals. In several line segments, geophones were co-located within one meter of the DAS cable. Both DAS and the conventional geophones recorded continuously over 15 days. A large Vibroseis truck (T-Rex) provided the seismic source at approximately 250 locations outside and within the array. The Vibroseis protocol called for excitation in one vertical and two orthogonal horizontal directions at each location. For each mode, three, 5-to-80-Hz upsweeps were made over 20 seconds. In addition, a moderate-sized earthquake with a local magnitude of 4.3 was recorded on March 21, 2016. Its epicenter was approximately 150-km away. Several DAS line segments with co-located geophone stations were used to test relationships between the strain rate recorded by DAS and ground velocity recorded by the geophones.

  9. Seismic Target Classification Using a Wavelet Packet Manifold in Unattended Ground Sensors Systems

    Directory of Open Access Journals (Sweden)

    Enliang Song

    2013-07-01

    Full Text Available One of the most challenging problems in target classification is the extraction of a robust feature, which can effectively represent a specific type of targets. The use of seismic signals in unattended ground sensor (UGS systems makes this problem more complicated, because the seismic target signal is non-stationary, geology-dependent and with high-dimensional feature space. This paper proposes a new feature extraction algorithm, called wavelet packet manifold (WPM, by addressing the neighborhood preserving embedding (NPE algorithm of manifold learning on the wavelet packet node energy (WPNE of seismic signals. By combining non-stationary information and low-dimensional manifold information, WPM provides a more robust representation for seismic target classification. By using a K nearest neighbors classifier on the WPM signature, the algorithm of wavelet packet manifold classification (WPMC is proposed. Experimental results show that the proposed WPMC can not only reduce feature dimensionality, but also improve the classification accuracy up to 95.03%. Moreover, compared with state-of-the-art methods, WPMC is more suitable for UGS in terms of recognition ratio and computational complexity.

  10. Para-quinodimethane-bridged perylene dimers and pericondensed quaterrylenes: The effect of the fusion mode on the ground states and physical properties

    KAUST Repository

    Das, Soumyajit

    2014-07-23

    Polycyclic hydrocarbon compounds with a singlet biradical ground state show unique physical properties and promising material applications; therefore, it is important to understand the fundamental structure/biradical character/physical properties relationships. In this study, para-quinodimethane (p-QDM)-bridged quinoidal perylene dimers 4 and 5 with different fusion modes and their corresponding aromatic counterparts, the pericondensed quaterrylenes 6 and 7, were synthesized. Their ground-state electronic structures and physical properties were studied by using various experiments assisted with DFT calculations. The proaromatic p-QDM-bridged perylene monoimide dimer 4 has a singlet biradical ground state with a small singlet/triplet energy gap (-2.97 kcalmol-1), whereas the antiaromatic s-indacene-bridged N-annulated perylene dimer 5 exists as a closed-shell quinoid with an obvious intramolecular charge-transfer character. Both of these dimers showed shorter singlet excited-state lifetimes, larger two-photon-absorption cross sections, and smaller energy gaps than the corresponding aromatic quaterrylene derivatives 6 and 7, respectively. Our studies revealed how the fusion mode and aromaticity affect the ground state and, consequently, the photophysical properties and electronic properties of a series of extended polycyclic hydrocarbon compounds. A matter of fusion mode! Fusion of a para-quinodimethane (p-QDM) subunit at the peri and β positions of perylene dimers leads to systems with different ground states, that is, open and closed shell (see picture). These systems showed large two-photon absorption cross sections and ultrafast excited-state dynamics relative to their corresponding pericondensed aromatic quaterrylene counterparts. © 2014 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

  11. Camera-marker and inertial sensor fusion for improved motion tracking

    NARCIS (Netherlands)

    Roetenberg, D.; Veltink, P.H.

    2005-01-01

    A method for combining a camera-marker based motion analysis system with miniature inertial sensors is proposed. It is used to fill gaps of optical data and can increase the data rate of the optical system.

  12. Opponent-Color Fusion of Multi-Sensor Imagery: Visible, IR and SAR

    National Research Council Canada - National Science Library

    Waxman, A

    1998-01-01

    .... Building on the work reported in two of our earlier papers from IRIS Passive Sensors 1996, we show how opponent-color processing and center-surround shunting neural networks can be used to develop...

  13. 3D Buried Utility Location Using A Marching-Cross-Section Algorithm for Multi-Sensor Data Fusion.

    Science.gov (United States)

    Dou, Qingxu; Wei, Lijun; Magee, Derek R; Atkins, Phil R; Chapman, David N; Curioni, Giulio; Goddard, Kevin F; Hayati, Farzad; Jenks, Hugo; Metje, Nicole; Muggleton, Jennifer; Pennock, Steve R; Rustighi, Emiliano; Swingler, Steven G; Rogers, Christopher D F; Cohn, Anthony G

    2016-11-02

    We address the problem of accurately locating buried utility segments by fusing data from multiple sensors using a novel Marching-Cross-Section (MCS) algorithm. Five types of sensors are used in this work: Ground Penetrating Radar (GPR), Passive Magnetic Fields (PMF), Magnetic Gradiometer (MG), Low Frequency Electromagnetic Fields (LFEM) and Vibro-Acoustics (VA). As part of the MCS algorithm, a novel formulation of the extended Kalman Filter (EKF) is proposed for marching existing utility tracks from a scan cross-section (scs) to the next one; novel rules for initializing utilities based on hypothesized detections on the first scs and for associating predicted utility tracks with hypothesized detections in the following scss are introduced. Algorithms are proposed for generating virtual scan lines based on given hypothesized detections when different sensors do not share common scan lines, or when only the coordinates of the hypothesized detections are provided without any information of the actual survey scan lines. The performance of the proposed system is evaluated with both synthetic data and real data. The experimental results in this work demonstrate that the proposed MCS algorithm can locate multiple buried utility segments simultaneously, including both straight and curved utilities, and can separate intersecting segments. By using the probabilities of a hypothesized detection being a pipe or a cable together with its 3D coordinates, the MCS algorithm is able to discriminate a pipe and a cable close to each other. The MCS algorithm can be used for both post- and on-site processing. When it is used on site, the detected tracks on the current scs can help to determine the location and direction of the next scan line. The proposed "multi-utility multi-sensor" system has no limit to the number of buried utilities or the number of sensors, and the more sensor data used, the more buried utility segments can be detected with more accurate location and orientation.

  14. Multistream sensor fusion-based prognostics model for systems with single failure modes

    International Nuclear Information System (INIS)

    Fang, Xiaolei; Paynabar, Kamran; Gebraeel, Nagi

    2017-01-01

    Advances in sensor technology have facilitated the capability of monitoring the degradation of complex engineering systems through the analysis of multistream degradation signals. However, the varying levels of correlation with physical degradation process for different sensors, high-dimensionality of the degradation signals and cross-correlation among different signal streams pose significant challenges in monitoring and prognostics of such systems. To address the foregoing challenges, we develop a three-step multi-sensor prognostic methodology that utilizes multistream signals to predict residual useful lifetimes of partially degraded systems. We first identify the informative sensors via the penalized (log)-location-scale regression. Then, we fuse the degradation signals of the informative sensors using multivariate functional principal component analysis, which is capable of modeling the cross-correlation of signal streams. Finally, the third step focuses on utilizing the fused signal features for prognostics via adaptive penalized (log)-location-scale regression. We validate our multi-sensor prognostic methodology using simulation study as well as a case study of aircraft turbofan engines available from NASA repository.

  15. A New Localization System for Indoor Service Robots in Low Luminance and Slippery Indoor Environment Using Afocal Optical Flow Sensor Based Sensor Fusion

    Directory of Open Access Journals (Sweden)

    Dong-Hoon Yi

    2018-01-01

    Full Text Available In this paper, a new localization system utilizing afocal optical flow sensor (AOFS based sensor fusion for indoor service robots in low luminance and slippery environment is proposed, where conventional localization systems do not perform well. To accurately estimate the moving distance of a robot in a slippery environment, the robot was equipped with an AOFS along with two conventional wheel encoders. To estimate the orientation of the robot, we adopted a forward-viewing mono-camera and a gyroscope. In a very low luminance environment, it is hard to conduct conventional feature extraction and matching for localization. Instead, the interior space structure from an image and robot orientation was assessed. To enhance the appearance of image boundary, rolling guidance filter was applied after the histogram equalization. The proposed system was developed to be operable on a low-cost processor and implemented on a consumer robot. Experiments were conducted in low illumination condition of 0.1 lx and carpeted environment. The robot moved for 20 times in a 1.5 × 2.0 m square trajectory. When only wheel encoders and a gyroscope were used for robot localization, the maximum position error was 10.3 m and the maximum orientation error was 15.4°. Using the proposed system, the maximum position error and orientation error were found as 0.8 m and within 1.0°, respectively.

  16. A New Localization System for Indoor Service Robots in Low Luminance and Slippery Indoor Environment Using Afocal Optical Flow Sensor Based Sensor Fusion.

    Science.gov (United States)

    Yi, Dong-Hoon; Lee, Tae-Jae; Cho, Dong-Il Dan

    2018-01-10

    In this paper, a new localization system utilizing afocal optical flow sensor (AOFS) based sensor fusion for indoor service robots in low luminance and slippery environment is proposed, where conventional localization systems do not perform well. To accurately estimate the moving distance of a robot in a slippery environment, the robot was equipped with an AOFS along with two conventional wheel encoders. To estimate the orientation of the robot, we adopted a forward-viewing mono-camera and a gyroscope. In a very low luminance environment, it is hard to conduct conventional feature extraction and matching for localization. Instead, the interior space structure from an image and robot orientation was assessed. To enhance the appearance of image boundary, rolling guidance filter was applied after the histogram equalization. The proposed system was developed to be operable on a low-cost processor and implemented on a consumer robot. Experiments were conducted in low illumination condition of 0.1 lx and carpeted environment. The robot moved for 20 times in a 1.5 × 2.0 m square trajectory. When only wheel encoders and a gyroscope were used for robot localization, the maximum position error was 10.3 m and the maximum orientation error was 15.4°. Using the proposed system, the maximum position error and orientation error were found as 0.8 m and within 1.0°, respectively.

  17. Development of Deep Learning Based Data Fusion Approach for Accurate Rainfall Estimation Using Ground Radar and Satellite Precipitation Products

    Science.gov (United States)

    Chen, H.; Chandra, C. V.; Tan, H.; Cifelli, R.; Xie, P.

    2016-12-01

    Rainfall estimation based on onboard satellite measurements has been an important topic in satellite meteorology for decades. A number of precipitation products at multiple time and space scales have been developed based upon satellite observations. For example, NOAA Climate Prediction Center has developed a morphing technique (i.e., CMORPH) to produce global precipitation products by combining existing space based rainfall estimates. The CMORPH products are essentially derived based on geostationary satellite IR brightness temperature information and retrievals from passive microwave measurements (Joyce et al. 2004). Although the space-based precipitation products provide an excellent tool for regional and global hydrologic and climate studies as well as improved situational awareness for operational forecasts, its accuracy is limited due to the sampling limitations, particularly for extreme events such as very light and/or heavy rain. On the other hand, ground-based radar is more mature science for quantitative precipitation estimation (QPE), especially after the implementation of dual-polarization technique and further enhanced by urban scale radar networks. Therefore, ground radars are often critical for providing local scale rainfall estimation and a "heads-up" for operational forecasters to issue watches and warnings as well as validation of various space measurements and products. The CASA DFW QPE system, which is based on dual-polarization X-band CASA radars and a local S-band WSR-88DP radar, has demonstrated its excellent performance during several years of operation in a variety of precipitation regimes. The real-time CASA DFW QPE products are used extensively for localized hydrometeorological applications such as urban flash flood forecasting. In this paper, a neural network based data fusion mechanism is introduced to improve the satellite-based CMORPH precipitation product by taking into account the ground radar measurements. A deep learning system is

  18. An optical liquid level sensor based on core-offset fusion splicing method using polarization-maintaining fiber

    Science.gov (United States)

    Lou, Weimin; Chen, Debao; Shen, Changyu; Lu, Yanfang; Liu, Huanan; Wei, Jian

    2016-01-01

    A simple liquid level sensor using a small piece of hydrofluoric acid (HF) etched polarization maintaining fiber (PMF), with SMF-PMF-SMF fiber structure based on Mach- Zehnder interference (MZI) mechanism is proposed. The core-offset fusion splicing method induced cladding modes interfere with the core mode. Moreover, the changing liquid level would influence the optical path difference of the MZI since the effective refractive indices of the air and the liquid is different. Both the variations of the wavelength shifts and power intensity attenuation corresponding to the liquid level can be obtained with a sensitivity of 0.4956nm/mm and 0.2204dB/mm, respectively.

  19. Fusion and Sense Making of Heterogeneous Sensor Network and Other Sources

    Science.gov (United States)

    2017-03-16

    two benchmark datasets: UIUC- Sport dataset, LabelMe8 dataset. Comparisons of our method with other state-of-the- art methods are conducted. (1...of-the- art feature descriptors upon the UIUC- Sport dataset when they are used alone or combined with web resources under the multimodal fusion...web textual resources aided image classification framework can improve classification accuracy of some classes by 13% and 12% in the UIUC- Sports and

  20. An adaptive Kalman filter approach for cardiorespiratory signal extraction and fusion of non-contacting sensors.

    Science.gov (United States)

    Foussier, Jerome; Teichmann, Daniel; Jia, Jing; Misgeld, Berno; Leonhardt, Steffen

    2014-05-09

    Extracting cardiorespiratory signals from non-invasive and non-contacting sensor arrangements, i.e. magnetic induction sensors, is a challenging task. The respiratory and cardiac signals are mixed on top of a large and time-varying offset and are likely to be disturbed by measurement noise. Basic filtering techniques fail to extract relevant information for monitoring purposes. We present a real-time filtering system based on an adaptive Kalman filter approach that separates signal offsets, respiratory and heart signals from three different sensor channels. It continuously estimates respiration and heart rates, which are fed back into the system model to enhance performance. Sensor and system noise covariance matrices are automatically adapted to the aimed application, thus improving the signal separation capabilities. We apply the filtering to two different subjects with different heart rates and sensor properties and compare the results to the non-adaptive version of the same Kalman filter. Also, the performance, depending on the initialization of the filters, is analyzed using three different configurations ranging from best to worst case. Extracted data are compared with reference heart rates derived from a standard pulse-photoplethysmographic sensor and respiration rates from a flowmeter. In the worst case for one of the subjects the adaptive filter obtains mean errors (standard deviations) of -0.2 min(-1) (0.3 min(-1)) and -0.7 bpm (1.7 bpm) (compared to -0.2 min(-1) (0.4 min(-1)) and 42.0 bpm (6.1 bpm) for the non-adaptive filter) for respiration and heart rate, respectively. In bad conditions the heart rate is only correctly measurable when the Kalman matrices are adapted to the target sensor signals. Also, the reduced mean error between the extracted offset and the raw sensor signal shows that adapting the Kalman filter continuously improves the ability to separate the desired signals from the raw sensor data. The average total computational time needed

  1. A Fusion Approach to Feature Extraction by Wavelet Decomposition and Principal Component Analysis in Transient Signal Processing of SAW Odor Sensor Array

    Directory of Open Access Journals (Sweden)

    Prashant SINGH

    2011-03-01

    Full Text Available This paper presents theoretical analysis of a new approach for development of surface acoustic wave (SAW sensor array based odor recognition system. The construction of sensor array employs a single polymer interface for selective sorption of odorant chemicals in vapor phase. The individual sensors are however coated with different thicknesses. The idea of sensor coating thickness variation is for terminating solvation and diffusion kinetics of vapors into polymer up to different stages of equilibration on different sensors. This is expected to generate diversity in information content of the sensors transient. The analysis is based on wavelet decomposition of transient signals. The single sensor transients have been used earlier for generating odor identity signatures based on wavelet approximation coefficients. In the present work, however, we exploit variability in diffusion kinetics due to polymer thicknesses for making odor signatures. This is done by fusion of the wavelet coefficients from different sensors in the array, and then applying the principal component analysis. We find that the present approach substantially enhances the vapor class separability in feature space. The validation is done by generating synthetic sensor array data based on well-established SAW sensor theory.

  2. Forecasting Global Horizontal Irradiance Using the LETKF and a Combination of Advected Satellite Images and Sparse Ground Sensors

    Science.gov (United States)

    Harty, T. M.; Lorenzo, A.; Holmgren, W.; Morzfeld, M.

    2017-12-01

    The irradiance incident on a solar panel is the main factor in determining the power output of that panel. For this reason, accurate global horizontal irradiance (GHI) estimates and forecasts are critical when determining the optimal location for a solar power plant, forecasting utility scale solar power production, or forecasting distributed, behind the meter rooftop solar power production. Satellite images provide a basis for producing the GHI estimates needed to undertake these objectives. The focus of this work is to combine satellite derived GHI estimates with ground sensor measurements and an advection model. The idea is to use accurate but sparsely distributed ground sensors to improve satellite derived GHI estimates which can cover large areas (the size of a city or a region of the United States). We use a Bayesian framework to perform the data assimilation, which enables us to produce irradiance forecasts and associated uncertainties which incorporate both satellite and ground sensor data. Within this framework, we utilize satellite images taken from the GOES-15 geostationary satellite (available every 15-30 minutes) as well as ground data taken from irradiance sensors and rooftop solar arrays (available every 5 minutes). The advection model, driven by wind forecasts from a numerical weather model, simulates cloud motion between measurements. We use the Local Ensemble Transform Kalman Filter (LETKF) to perform the data assimilation. We present preliminary results towards making such a system useful in an operational context. We explain how localization and inflation in the LETKF, perturbations of wind-fields, and random perturbations of the advection model, affect the accuracy of our estimates and forecasts. We present experiments showing the accuracy of our forecasted GHI over forecast-horizons of 15 mins to 1 hr. The limitations of our approach and future improvements are also discussed.

  3. Geographic information system for fusion and analysis of high-resolution remote sensing and ground truth data

    Science.gov (United States)

    Freeman, Anthony; Way, Jo Bea; Dubois, Pascale; Leberl, Franz

    1992-01-01

    We seek to combine high-resolution remotely sensed data with models and ground truth measurements, in the context of a Geographical Information System, integrated with specialized image processing software. We will use this integrated system to analyze the data from two Case Studies, one at a bore Al forest site, the other a tropical forest site. We will assess the information content of the different components of the data, determine the optimum data combinations to study biogeophysical changes in the forest, assess the best way to visualize the results, and validate the models for the forest response to different radar wavelengths/polarizations. During the 1990's, unprecedented amounts of high-resolution images from space of the Earth's surface will become available to the applications scientist from the LANDSAT/TM series, European and Japanese ERS-1 satellites, RADARSAT and SIR-C missions. When the Earth Observation Systems (EOS) program is operational, the amount of data available for a particular site can only increase. The interdisciplinary scientist, seeking to use data from various sensors to study his site of interest, may be faced with massive difficulties in manipulating such large data sets, assessing their information content, determining the optimum combinations of data to study a particular parameter, visualizing his results and validating his model of the surface. The techniques to deal with these problems are also needed to support the analysis of data from NASA's current program of Multi-sensor Airborne Campaigns, which will also generate large volumes of data. In the Case Studies outlined in this proposal, we will have somewhat unique data sets. For the Bonanza Creek Experimental Forest (Case I) calibrated DC-8 SAR data and extensive ground truth measurement are already at our disposal. The data set shows documented evidence to temporal change. The Belize Forest Experiment (Case II) will produce calibrated DC-8 SAR and AVIRIS data, together with

  4. Observability considerations for multi-sensor and product fusion: Bias, information content, and validation (Invited)

    Science.gov (United States)

    Reid, J. S.; Zhang, J.; Hyer, E. J.; Campbell, J. R.; Christopher, S. A.; Ferrare, R. A.; Leptoukh, G. G.; Stackhouse, P. W.

    2009-12-01

    With the successful development of many aerosol products from the NASA A-train as well as new operational geostationary and polar orbiting sensors, the scientific community now has a host of new parameters to use in their analyses. The variety and quality of products has reached a point where the community has moved from basic observation-based science to sophisticated multi-component research that addresses the complex atmospheric environment. In order for these satellite data contribute to the science their uncertainty levels must move from semi-quantitative to quantitative. Initial attempts to quantify uncertainties have led to some recent debate in the community as to the efficacy of aerosol products from current and future NASA satellite sensors. In an effort to understand the state of satellite product fidelity, the Naval Research Laboratory and a newly reformed Global Energy and Water Cycle Experiment (GEWEX) aerosol panel have both initiated assessments of the nature of aerosol remote sensing uncertainty and bias. In this talk we go over areas of specific concern based on the authors’ experiences with the data, emphasizing the multi-sensor problem. We first enumerate potential biases, including retrieval, sampling/contextual, and cognitive bias. We show examples of how these biases can subsequently lead to the pitfalls of correlated/compensating errors, tautology, and confounding. The nature of bias is closely related to the information content of the sensor signal and its subsequent application to the derived aerosol quantity of interest (e.g., optical depth, flux, index of refraction, etc.). Consequently, purpose-specific validation methods must be employed, especially when generating multi-sensor products. Indeed, cloud and lower boundary condition biases in particular complicate the more typical methods of regressional bias elimination and histogram matching. We close with a discussion of sequestration of uncertainty in multi-sensor applications of

  5. Autonomous underwater vehicle motion tracking using a Kalman filter for sensor fusion

    CSIR Research Space (South Africa)

    Holtzhausen, S

    2008-11-01

    Full Text Available it will be shown how a Kalman Filter is used to estimate the position of an autonomous vehicle in a three dimensional space. The Kalman filter is used to estimate movement and position using measurements from multiple sensors...

  6. A Navigation System for the Visually Impaired: A Fusion of Vision and Depth Sensor

    Science.gov (United States)

    Kanwal, Nadia; Bostanci, Erkan; Currie, Keith; Clark, Adrian F.

    2015-01-01

    For a number of years, scientists have been trying to develop aids that can make visually impaired people more independent and aware of their surroundings. Computer-based automatic navigation tools are one example of this, motivated by the increasing miniaturization of electronics and the improvement in processing power and sensing capabilities. This paper presents a complete navigation system based on low cost and physically unobtrusive sensors such as a camera and an infrared sensor. The system is based around corners and depth values from Kinect's infrared sensor. Obstacles are found in images from a camera using corner detection, while input from the depth sensor provides the corresponding distance. The combination is both efficient and robust. The system not only identifies hurdles but also suggests a safe path (if available) to the left or right side and tells the user to stop, move left, or move right. The system has been tested in real time by both blindfolded and blind people at different indoor and outdoor locations, demonstrating that it operates adequately. PMID:27057135

  7. Environment model creation and ADAS architecture for trucks : design and implementation of a sensor fusion algorithm

    NARCIS (Netherlands)

    Stamatopoulos, E.

    2016-01-01

    This report presents a structural approach for environment model creation and ADAS architecture for trucks. In particular, an appropriate sensor suite that is suitable for a set of ADAS functions is defined. On this basis, the development of a proof of concept for an Environment Model system, by

  8. Tracking and Interception of Ground-Based RF Sources Using Autonomous Guided Munitions with Passive Bearings-Only Sensors and Tracking Algorithms

    National Research Council Canada - National Science Library

    Ezal, Kenan; Agate, Craig

    2006-01-01

    This paper considers the problem of tracking and intercepting a potentially moving ground-based RF source with an autonomous guided munition that has a passive bearings-only sensor located on its nose...

  9. Data-Fusion for a Vision-Aided Radiological Detection System: Sensor dependence and Source Tracking

    Science.gov (United States)

    Stadnikia, Kelsey; Martin, Allan; Henderson, Kristofer; Koppal, Sanjeev; Enqvist, Andreas

    2018-01-01

    The University of Florida is taking a multidisciplinary approach to fuse the data between 3D vision sensors and radiological sensors in hopes of creating a system capable of not only detecting the presence of a radiological threat, but also tracking it. The key to developing such a vision-aided radiological detection system, lies in the count rate being inversely dependent on the square of the distance. Presented in this paper are the results of the calibration algorithm used to predict the location of the radiological detectors based on 3D distance from the source to the detector (vision data) and the detectors count rate (radiological data). Also presented are the results of two correlation methods used to explore source tracking.

  10. Activity Recognition Using Fusion of Low-Cost Sensors on a Smartphone for Mobile Navigation Application

    Directory of Open Access Journals (Sweden)

    Sara Saeedi

    2015-08-01

    Full Text Available Low-cost inertial and motion sensors embedded on smartphones have provided a new platform for dynamic activity pattern inference. In this research, a comparison has been conducted on different sensor data, feature spaces and feature selection methods to increase the efficiency and reduce the computation cost of activity recognition on the smartphones. We evaluated a variety of feature spaces and a number of classification algorithms from the area of Machine Learning, including Naive Bayes, Decision Trees, Artificial Neural Networks and Support Vector Machine classifiers. A smartphone app that performs activity recognition is being developed to collect data and send them to a server for activity recognition. Using extensive experiments, the performance of various feature spaces has been evaluated. The results showed that the Bayesian Network classifier yields recognition accuracy of 96.21% using four features while requiring fewer computations.

  11. Low Complexity Track Initialization and Fusion for Multi-Modal Sensor Networks

    Science.gov (United States)

    2012-11-08

    that is, freely available to any visitor to IEEE Xplore . Authors who choose open access must do so by electing this option by notifying the Editor-In...Publications 1. Q. Le and L.M. Kaplan, “Target localization using proximity binary sensors,” Proceedings of IEEE Aerospace conference, Big Sky, MT... IEEE Aerospace Conference, Big Sky, MT, Mar. 2011. 5. Q. Le, and L. M. Kaplan, “Effects of Operation Parameters on Multitarget Tracking in Proximity

  12. Multi-sensor fusion method for crop row tracking and traversability operations

    OpenAIRE

    Benet, B.; Lenain, R.

    2017-01-01

    Precision agriculture vehicles need autonomous navigation in cultures to carry out their tasks, such as planting, maintenance and harvesting in cultures such as vegetable, vineyard, or horticulture. The detection of natural objects like trunks, grass, leaf, or obstacles in front of vehicle in crop row is crucial for safe navigation. Sensors such as LiDAR devices or Time Of Flight cameras (TOF), allow to obtain geometric data in natural environment, using information of an Inertial Measurement...

  13. Absolute Position Sensing Based on a Robust Differential Capacitive Sensor with a Grounded Shield Window

    Directory of Open Access Journals (Sweden)

    Yang Bai

    2016-05-01

    Full Text Available A simple differential capacitive sensor is provided in this paper to measure the absolute positions of length measuring systems. By utilizing a shield window inside the differential capacitor, the measurement range and linearity range of the sensor can reach several millimeters. What is more interesting is that this differential capacitive sensor is only sensitive to one translational degree of freedom (DOF movement, and immune to the vibration along the other two translational DOFs. In the experiment, we used a novel circuit based on an AC capacitance bridge to directly measure the differential capacitance value. The experimental result shows that this differential capacitive sensor has a sensitivity of 2 × 10−4 pF/μm with 0.08 μm resolution. The measurement range of this differential capacitive sensor is 6 mm, and the linearity error are less than 0.01% over the whole absolute position measurement range.

  14. Extended Kalman filtering for model-based sensor fusion in robotics

    International Nuclear Information System (INIS)

    Fujii, Yuji; Wehe, D.K.; Lee, J.C.

    1990-01-01

    Remote surveillance and maintenance in advanced nuclear power plants will benefit from the increased utilization of mobile robotic systems. For these robotic systems to function most effectively in hazardous environments, they should be able to make decisions and take necessary actions with minimal human supervision. To accomplish this, the robot must be able to construct an accurate model of the power plant environment from diverse sensory data and a priori maps. In this paper, the authors demonstrate how a recursive parameter estimation technique known as Kalman filtering can integrate noisy data from various sensors to construct a consistent representation of the sensed environment

  15. Multi-Sensor Fusion for Enhanced Contextual Awareness of Everyday Activities with Ubiquitous Devices

    Directory of Open Access Journals (Sweden)

    John J. Guiry

    2014-03-01

    Full Text Available In this paper, the authors investigate the role that smart devices, including smartphones and smartwatches, can play in identifying activities of daily living. A feasibility study involving N = 10 participants was carried out to evaluate the devices’ ability to differentiate between nine everyday activities. The activities examined include walking, running, cycling, standing, sitting, elevator ascents, elevator descents, stair ascents and stair descents. The authors also evaluated the ability of these devices to differentiate indoors from outdoors, with the aim of enhancing contextual awareness. Data from this study was used to train and test five well known machine learning algorithms: C4.5, CART, Naïve Bayes, Multi-Layer Perceptrons and finally Support Vector Machines. Both single and multi-sensor approaches were examined to better understand the role each sensor in the device can play in unobtrusive activity recognition. The authors found overall results to be promising, with some models correctly classifying up to 100% of all instances.

  16. Measuring indoor occupancy in intelligent buildings using the fusion of vision sensors

    International Nuclear Information System (INIS)

    Liu, Dixin; Guan, Xiaohong; Du, Youtian; Zhao, Qianchuan

    2013-01-01

    In intelligent buildings, practical sensing systems designed to gather indoor occupancy information play an indispensable role in improving occupant comfort and energy efficiency. In this paper, we propose a novel method for occupancy measurement based on the video surveillance now widely used in buildings. In our method, we analyze occupant detection both at the entrance and inside the room. A two-stage static detector is presented based on both appearances and shapes to find the human heads in rooms, and motion-based technology is used for occupant detection at the entrance. To model the change of occupancy and combine the detection results from multiple vision sensors located at entrances and inside rooms for more accurate occupancy estimation, we propose a dynamic Bayesian network-based method. The detection results of each vision sensor play the role of evidence nodes of this network, and thus, we can estimate the true occupancy at time t using the evidence prior to (and including) time t. Experimental results demonstrate the effectiveness and efficiency of the proposed method. (paper)

  17. Multi-Sensor Fusion of Infrared and Electro-Optic Signals for High Resolution Night Images

    Directory of Open Access Journals (Sweden)

    Victor Lawrence

    2012-07-01

    Full Text Available Electro-optic (EO image sensors exhibit the properties of high resolution and low noise level at daytime, but they do not work in dark environments. Infrared (IR image sensors exhibit poor resolution and cannot separate objects with similar temperature. Therefore, we propose a novel framework of IR image enhancement based on the information (e.g., edge from EO images, which improves the resolution of IR images and helps us distinguish objects at night. Our framework superimposing/blending the edges of the EO image onto the corresponding transformed IR image improves their resolution. In this framework, we adopt the theoretical point spread function (PSF proposed by Hardie et al. for the IR image, which has the modulation transfer function (MTF of a uniform detector array and the incoherent optical transfer function (OTF of diffraction-limited optics. In addition, we design an inverse filter for the proposed PSF and use it for the IR image transformation. The framework requires four main steps: (1 inverse filter-based IR image transformation; (2 EO image edge detection; (3 registration; and (4 blending/superimposing of the obtained image pair. Simulation results show both blended and superimposed IR images, and demonstrate that blended IR images have better quality over the superimposed images. Additionally, based on the same steps, simulation result shows a blended IR image of better quality when only the original IR image is available.

  18. Sensor Fusion and Autonomy as a Powerful Combination for Biological Assessment in the Marine Environment

    Directory of Open Access Journals (Sweden)

    Mark A. Moline

    2016-02-01

    Full Text Available The ocean environment and the physical and biological processes that govern dynamics are complex. Sampling the ocean to better understand these processes is difficult given the temporal and spatial domains and sampling tools available. Biological systems are especially difficult as organisms possess behavior, operate at horizontal scales smaller than traditional shipboard sampling allows, and are often disturbed by the sampling platforms themselves. Sensors that measure biological processes have also generally not kept pace with the development of physical counterparts as their requirements are as complex as the target organisms. Here, we attempt to address this challenge by advocating the need for sensor-platform combinations to integrate and process data in real-time and develop data products that are useful in increasing sampling efficiencies. Too often, the data of interest is only garnered after post-processing after a sampling effort and the opportunity to use that information to guide sampling is lost. Here we demonstrate a new autonomous platform, where data are collected, analyzed, and data products are output in real-time to inform autonomous decision-making. This integrated capability allows for enhanced and informed sampling towards improving our understanding of the marine environment.

  19. Detection and Tracking of Road Barrier Based on Radar and Vision Sensor Fusion

    Directory of Open Access Journals (Sweden)

    Taeryun Kim

    2016-01-01

    Full Text Available The detection and tracking algorithms of road barrier including tunnel and guardrail are proposed to enhance performance and reliability for driver assistance systems. Although the road barrier is one of the key features to determine a safe drivable area, it may be recognized incorrectly due to performance degradation of commercial sensors such as radar and monocular camera. Two frequent cases among many challenging problems are considered with the commercial sensors. The first case is that few tracks of radar to road barrier are detected due to material type of road barrier. The second one is inaccuracy of relative lateral position by radar, thus resulting in large variance of distance between a vehicle and road barrier. To overcome the problems, the detection and estimation algorithms of tracks corresponding to road barrier are proposed. Then, the tracking algorithm based on a probabilistic data association filter (PDAF is used to reduce variation of lateral distance between vehicle and road barrier. Finally, the proposed algorithms are validated via field test data and their performance is compared with that of road barrier measured by lidar.

  20. The Distribution of Titanium in Lunar Soils on the Basis of Sensor and In Situ Data Fusion

    Science.gov (United States)

    Clark, P. E.; Evans, L.

    1999-01-01

    A variety of remote-sensing measurements have been used to map the distribution of elements on the Moon as a means of providing constraints on the processes from which its crust and major terranes originated. Discussed here is Ti, which is incorporated into refractory minerals such as ilmenite during the latter stages of differentiation, and is thus a most useful element for understanding mare basalt petrogenesis. One of the earliest Ti maps showed Ti variations in nearside maria on the basis of groundbased spectral reflectance measurements. A map of Ti derived from gamma-ray measurements on Apollo 15 and 16 was produced at about the same time, and was improved upon considerably by Davis and coworkers, who effectively removed sources of spurious variation from Fe and Al or REE (e.g., Th) interference, and calibrated Ti on the bases of landing-site soil averages. In recent years, spectral reflectance measurements from Clementine have been used by Lucey and coworkers to produce global Ti distribution maps as well. As we indicated previously, the Lucey and Davis maps agree to first order. Meanwhile, we are using the concept of sensor data fusion to combine measurements from the AGR (Apollo gamma-ray) and CSR (Clementine Spectral Reflectance) techniques with ground truth from lunar soils to utilize the differences between the two maps to understand the distribution of Ti within lunar soil components, as we have done with Fe. This technique should be verified and applied on Lunar Prospector gamma-ray measurements of Ti, as the calibrated data become available within the next couple of years. Lunar Ti is found principally in the mineral ilmenite, and is associated with certain components of lunar soil: crystalline Ilmenite mineral fragments and high Ti-bearing glass. All data indicate that Ti is associated with maria and mafic minerals. In AGR and CSR datasets, Ti is highest on the nearside and in the maria, particularly in southern Serenitatis/northern Tranquillitatis

  1. Motor Function Evaluation of Hemiplegic Upper-Extremities Using Data Fusion from Wearable Inertial and Surface EMG Sensors

    Directory of Open Access Journals (Sweden)

    Yanran Li

    2017-03-01

    Full Text Available Quantitative evaluation of motor function is of great demand for monitoring clinical outcome of applied interventions and further guiding the establishment of therapeutic protocol. This study proposes a novel framework for evaluating upper limb motor function based on data fusion from inertial measurement units (IMUs and surface electromyography (EMG sensors. With wearable sensors worn on the tested upper limbs, subjects were asked to perform eleven straightforward, specifically designed canonical upper-limb functional tasks. A series of machine learning algorithms were applied to the recorded motion data to produce evaluation indicators, which is able to reflect the level of upper-limb motor function abnormality. Sixteen healthy subjects and eighteen stroke subjects with substantial hemiparesis were recruited in the experiment. The combined IMU and EMG data yielded superior performance over the IMU data alone and the EMG data alone, in terms of decreased normal data variation rate (NDVR and improved determination coefficient (DC from a regression analysis between the derived indicator and routine clinical assessment score. Three common unsupervised learning algorithms achieved comparable performance with NDVR around 10% and strong DC around 0.85. By contrast, the use of a supervised algorithm was able to dramatically decrease the NDVR to 6.55%. With the proposed framework, all the produced indicators demonstrated high agreement with the routine clinical assessment scale, indicating their capability of assessing upper-limb motor functions. This study offers a feasible solution to motor function assessment in an objective and quantitative manner, especially suitable for home and community use.

  2. Measuring Radiant Emissions from Entire Prescribed Fires with Ground, Airborne and Satellite Sensors RxCADRE 2012

    Science.gov (United States)

    Dickinson, Matthew B.; Hudak, Andrew T.; Zajkowski, Thomas; Loudermilk, E. Louise; Schroeder, Wilfrid; Ellison, Luke; Kremens, Robert L.; Holley, William; Martinez, Otto; Paxton, Alexander; hide

    2015-01-01

    Characterising radiation from wildland fires is an important focus of fire science because radiation relates directly to the combustion process and can be measured across a wide range of spatial extents and resolutions. As part of a more comprehensive set of measurements collected during the 2012 Prescribed Fire Combustion and Atmospheric Dynamics Research (RxCADRE) field campaign, we used ground, airborne and spaceborne sensors to measure fire radiative power (FRP) from whole fires, applying different methods to small (2 ha) and large (.100 ha) burn blocks. For small blocks (n1/46), FRP estimated from an obliquely oriented long-wave infrared (LWIR) camera mounted on a boom lift were compared with FRP derived from combined data from tower-mounted radiometers and remotely piloted aircraft systems (RPAS). For large burn blocks (n1/43), satellite FRP measurements from the Moderate-resolution Imaging Spectroradiometer (MODIS) and Visible Infrared Imaging Radiometer Suite (VIIRS) sensors were compared with near-coincident FRP measurements derived from a LWIR imaging system aboard a piloted aircraft. We describe measurements and consider their strengths and weaknesses. Until quantitative sensors exist for small RPAS, their use in fire research will remain limited. For oblique, airborne and satellite sensors, further FRP measurement development is needed along with greater replication of coincident measurements, which we show to be feasible.

  3. Uncertainty estimation and multi sensor fusion for kinematic laser tracker measurements

    Science.gov (United States)

    Ulrich, Thomas

    2013-08-01

    Laser trackers are widely used to measure kinematic tasks such as tracking robot movements. Common methods to evaluate the uncertainty in the kinematic measurement include approximations specified by the manufacturers, various analytical adjustment methods and the Kalman filter. In this paper a new, real-time technique is proposed, which estimates the 4D-path (3D-position + time) uncertainty of an arbitrary path in space. Here a hybrid system estimator is applied in conjunction with the kinematic measurement model. This method can be applied to processes, which include various types of kinematic behaviour, constant velocity, variable acceleration or variable turn rates. The new approach is compared with the Kalman filter and a manufacturer's approximations. The comparison was made using data obtained by tracking an industrial robot's tool centre point with a Leica laser tracker AT901 and a Leica laser tracker LTD500. It shows that the new approach is more appropriate to analysing kinematic processes than the Kalman filter, as it reduces overshoots and decreases the estimated variance. In comparison with the manufacturer's approximations, the new approach takes account of kinematic behaviour with an improved description of the real measurement process and a reduction in estimated variance. This approach is therefore well suited to the analysis of kinematic processes with unknown changes in kinematic behaviour as well as the fusion among laser trackers.

  4. Reovirus FAST Proteins Drive Pore Formation and Syncytiogenesis Using a Novel Helix-Loop-Helix Fusion-Inducing Lipid Packing Sensor.

    Directory of Open Access Journals (Sweden)

    Jolene Read

    2015-06-01

    Full Text Available Pore formation is the most energy-demanding step during virus-induced membrane fusion, where high curvature of the fusion pore rim increases the spacing between lipid headgroups, exposing the hydrophobic interior of the membrane to water. How protein fusogens breach this thermodynamic barrier to pore formation is unclear. We identified a novel fusion-inducing lipid packing sensor (FLiPS in the cytosolic endodomain of the baboon reovirus p15 fusion-associated small transmembrane (FAST protein that is essential for pore formation during cell-cell fusion and syncytiogenesis. NMR spectroscopy and mutational studies indicate the dependence of this FLiPS on a hydrophobic helix-loop-helix structure. Biochemical and biophysical assays reveal the p15 FLiPS preferentially partitions into membranes with high positive curvature, and this partitioning is impeded by bis-ANS, a small molecule that inserts into hydrophobic defects in membranes. Most notably, the p15 FLiPS can be functionally replaced by heterologous amphipathic lipid packing sensors (ALPS but not by other membrane-interactive amphipathic helices. Furthermore, a previously unrecognized amphipathic helix in the cytosolic domain of the reptilian reovirus p14 FAST protein can functionally replace the p15 FLiPS, and is itself replaceable by a heterologous ALPS motif. Anchored near the cytoplasmic leaflet by the FAST protein transmembrane domain, the FLiPS is perfectly positioned to insert into hydrophobic defects that begin to appear in the highly curved rim of nascent fusion pores, thereby lowering the energy barrier to stable pore formation.

  5. A Ubiquitous and Low-Cost Solution for Movement Monitoring and Accident Detection Based on Sensor Fusion

    Directory of Open Access Journals (Sweden)

    Filipe Felisberto

    2014-05-01

    Full Text Available The low average birth rate in developed countries and the increase in life expectancy have lead society to face for the first time an ageing situation. This situation associated with the World’s economic crisis (which started in 2008 forces the need of equating better and more efficient ways of providing more quality of life for the elderly. In this context, the solution presented in this work proposes to tackle the problem of monitoring the elderly in a way that is not restrictive for the life of the monitored, avoiding the need for premature nursing home admissions. To this end, the system uses the fusion of sensory data provided by a network of wireless sensors placed on the periphery of the user. Our approach was also designed with a low-cost deployment in mind, so that the target group may be as wide as possible. Regarding the detection of long-term problems, the tests conducted showed that the precision of the system in identifying and discerning body postures and body movements allows for a valid monitorization and rehabilitation of the user. Moreover, concerning the detection of accidents, while the proposed solution presented a near 100% precision at detecting normal falls, the detection of more complex falls (i.e., hampered falls will require further study.

  6. Assessment of Closed-Loop Control Using Multi-Mode Sensor Fusion For a High Reynolds Number Transonic Jet

    Science.gov (United States)

    Low, Kerwin; Elhadidi, Basman; Glauser, Mark

    2009-11-01

    Understanding the different noise production mechanisms caused by the free shear flows in a turbulent jet flow provides insight to improve ``intelligent'' feedback mechanisms to control the noise. Towards this effort, a control scheme is based on feedback of azimuthal pressure measurements in the near field of the jet at two streamwise locations. Previous studies suggested that noise reduction can be achieved by azimuthal actuators perturbing the shear layer at the jet lip. The closed-loop actuation will be based on a low-dimensional Fourier representation of the hydrodynamic pressure measurements. Preliminary results show that control authority and reduction in the overall sound pressure level was possible. These results provide motivation to move forward with the overall vision of developing innovative multi-mode sensing methods to improve state estimation and derive dynamical systems. It is envisioned that estimating velocity-field and dynamic pressure information from various locations both local and in the far-field regions, sensor fusion techniques can be utilized to ascertain greater overall control authority.

  7. Adaptation of Dubins Paths for UAV Ground Obstacle Avoidance When Using a Low Cost On-Board GNSS Sensor.

    Science.gov (United States)

    Kikutis, Ramūnas; Stankūnas, Jonas; Rudinskas, Darius; Masiulionis, Tadas

    2017-09-28

    Current research on Unmanned Aerial Vehicles (UAVs) shows a lot of interest in autonomous UAV navigation. This interest is mainly driven by the necessity to meet the rules and restrictions for small UAV flights that are issued by various international and national legal organizations. In order to lower these restrictions, new levels of automation and flight safety must be reached. In this paper, a new method for ground obstacle avoidance derived by using UAV navigation based on the Dubins paths algorithm is presented. The accuracy of the proposed method has been tested, and research results have been obtained by using Software-in-the-Loop (SITL) simulation and real UAV flights, with the measurements done with a low cost Global Navigation Satellite System (GNSS) sensor. All tests were carried out in a three-dimensional space, but the height accuracy was not assessed. The GNSS navigation data for the ground obstacle avoidance algorithm is evaluated statistically.

  8. Adaptation of Dubins Paths for UAV Ground Obstacle Avoidance When Using a Low Cost On-Board GNSS Sensor

    Directory of Open Access Journals (Sweden)

    Ramūnas Kikutis

    2017-09-01

    Full Text Available Current research on Unmanned Aerial Vehicles (UAVs shows a lot of interest in autonomous UAV navigation. This interest is mainly driven by the necessity to meet the rules and restrictions for small UAV flights that are issued by various international and national legal organizations. In order to lower these restrictions, new levels of automation and flight safety must be reached. In this paper, a new method for ground obstacle avoidance derived by using UAV navigation based on the Dubins paths algorithm is presented. The accuracy of the proposed method has been tested, and research results have been obtained by using Software-in-the-Loop (SITL simulation and real UAV flights, with the measurements done with a low cost Global Navigation Satellite System (GNSS sensor. All tests were carried out in a three-dimensional space, but the height accuracy was not assessed. The GNSS navigation data for the ground obstacle avoidance algorithm is evaluated statistically.

  9. Enhanced research in ground-penetrating radar and multisensor fusion with application to the detection and visualization of buried waste. Final report

    Energy Technology Data Exchange (ETDEWEB)

    Devney, A.J.; DiMarzio, C.; Kokar, M.; Miller, E.L.; Rappaport, C.M.; Weedon, W.H.

    1996-05-14

    Recognizing the difficulty and importance of the landfill remediation problems faced by DOE, and the fact that no one sensor alone can provide complete environmental site characterization, a multidisciplinary team approach was chosen for this project. The authors have developed a multisensor fusion approach that is suitable for the wide variety of sensors available to DOE, that allows separate detection algorithms to be developed and custom-tailored to each sensor. This approach is currently being applied to the Geonics EM-61 and Coleman step-frequency radar data. High-resolution array processing techniques were developed for detecting and localizing buried waste containers. A soil characterization laboratory facility was developed using a HP-8510 network analyzer and near-field coaxial probe. Both internal and external calibration procedures were developed for de-embedding the frequency-dependent soil electrical parameters from the measurements. Dispersive soil propagation modeling algorithms were also developed for simulating wave propagation in dispersive soil media. A study was performed on the application of infrared sensors to the landfill remediation problem, particularly for providing information on volatile organic compounds (VOC`s) in the atmosphere. A dust-emission lidar system is proposed for landfill remediation monitoring. Design specifications are outlined for a system which could be used to monitor dust emissions in a landfill remediation effort. The detailed results of the investigations are contained herein.

  10. Enhanced research in ground-penetrating radar and multisensor fusion with application to the detection and visualization of buried waste. Final report

    International Nuclear Information System (INIS)

    Devney, A.J.; DiMarzio, C.; Kokar, M.; Miller, E.L.; Rappaport, C.M.; Weedon, W.H.

    1996-01-01

    Recognizing the difficulty and importance of the landfill remediation problems faced by DOE, and the fact that no one sensor alone can provide complete environmental site characterization, a multidisciplinary team approach was chosen for this project. The authors have developed a multisensor fusion approach that is suitable for the wide variety of sensors available to DOE, that allows separate detection algorithms to be developed and custom-tailored to each sensor. This approach is currently being applied to the Geonics EM-61 and Coleman step-frequency radar data. High-resolution array processing techniques were developed for detecting and localizing buried waste containers. A soil characterization laboratory facility was developed using a HP-8510 network analyzer and near-field coaxial probe. Both internal and external calibration procedures were developed for de-embedding the frequency-dependent soil electrical parameters from the measurements. Dispersive soil propagation modeling algorithms were also developed for simulating wave propagation in dispersive soil media. A study was performed on the application of infrared sensors to the landfill remediation problem, particularly for providing information on volatile organic compounds (VOC's) in the atmosphere. A dust-emission lidar system is proposed for landfill remediation monitoring. Design specifications are outlined for a system which could be used to monitor dust emissions in a landfill remediation effort. The detailed results of the investigations are contained herein

  11. Spatio-temporal monitoring of cotton cultivation using ground-based and airborne multispectral sensors in GIS environment.

    Science.gov (United States)

    Papadopoulos, Antonis; Kalivas, Dionissios; Theocharopoulos, Sid

    2017-07-01

    Multispectral sensor capability of capturing reflectance data at several spectral channels, together with the inherent reflectance responses of various soils and especially plant surfaces, has gained major interest in crop production. In present study, two multispectral sensing systems, a ground-based and an aerial-based, were applied for the multispatial and temporal monitoring of two cotton fields in central Greece. The ground-based system was Crop Circle ACS-430, while the aerial consisted of a consumer-level quadcopter (Phantom 2) and a modified Hero3+ Black digital camera. The purpose of the research was to monitor crop growth with the two systems and investigate possible interrelations between the derived well-known normalized difference vegetation index (NDVI). Five data collection campaigns were conducted during the cultivation period and concerned scanning soil and plants with the ground-based sensor and taking aerial photographs of the fields with the unmanned aerial system. According to the results, both systems successfully monitored cotton growth stages in terms of space and time. The mean values of NDVI changes through time as retrieved by the ground-based system were satisfactorily modelled by a second-order polynomial equation (R 2 0.96 in Field 1 and 0.99 in Field 2). Further, they were highly correlated (r 0.90 in Field 1 and 0.74 in Field 2) with the according values calculated via the aerial-based system. The unmanned aerial system (UAS) can potentially substitute crop scouting as it concerns a time-effective, non-destructive and reliable way of soil and plant monitoring.

  12. Preparatory research to develop an operational method to calibrate airborne sensor data using a network of ground calibration sites

    International Nuclear Information System (INIS)

    Milton, E.J.; Smith, G.M.; Lawless, K.P.

    1996-01-01

    The objective of the research is to develop an operational method to convert airborne spectral radiance data to reflectance using a number of well-characterized ground calibration sites located around the UK. The study is in three phases. First, a pilot study has been conducted at a disused airfield in southern England to test the feasibility of the open-quote empirical line close-quote method of sensor calibration. The second phase is developing methods to predict temporal changes in the bidirectional reflectance of ground calibration sites. The final phase of the project will look at methods to extend such calibrations spatially. This paper presents some results from the first phase of this study. The viability of the empirical line method of correction is shown to depend upon the use of ground targets whose in-band reflectance encompasses that of the targets of interest in the spectral band(s) concerned. The experimental design for the second phase of the study, in which methods to predict temporal trends in the bidirectional reflectance of these sites will be developed, is discussed. Finally, it is planned to develop an automated method of searching through Landsat TM data for the UK to identify a number of candidate ground calibration sites for which the model can be tested. 11 refs., 5 figs., 5 tabs

  13. Monitoring soil moisture patterns in alpine meadows using ground sensor networks and remote sensing techniques

    Science.gov (United States)

    Bertoldi, Giacomo; Brenner, Johannes; Notarnicola, Claudia; Greifeneder, Felix; Nicolini, Irene; Della Chiesa, Stefano; Niedrist, Georg; Tappeiner, Ulrike

    2015-04-01

    Soil moisture content (SMC) is a key factor for numerous processes, including runoff generation, groundwater recharge, evapotranspiration, soil respiration, and biological productivity. Understanding the controls on the spatial and temporal variability of SMC in mountain catchments is an essential step towards improving quantitative predictions of catchment hydrological processes and related ecosystem services. The interacting influences of precipitation, soil properties, vegetation, and topography on SMC and the influence of SMC patterns on runoff generation processes have been extensively investigated (Vereecken et al., 2014). However, in mountain areas, obtaining reliable SMC estimations is still challenging, because of the high variability in topography, soil and vegetation properties. In the last few years, there has been an increasing interest in the estimation of surface SMC at local scales. On the one hand, low cost wireless sensor networks provide high-resolution SMC time series. On the other hand, active remote sensing microwave techniques, such as Synthetic Aperture Radars (SARs), show promising results (Bertoldi et al. 2014). As these data provide continuous coverage of large spatial extents with high spatial resolution (10-20 m), they are particularly in demand for mountain areas. However, there are still limitations related to the fact that the SAR signal can penetrate only a few centimeters in the soil. Moreover, the signal is strongly influenced by vegetation, surface roughness and topography. In this contribution, we analyse the spatial and temporal dynamics of surface and root-zone SMC (2.5 - 5 - 25 cm depth) of alpine meadows and pastures in the Long Term Ecological Research (LTER) Area Mazia Valley (South Tyrol - Italy) with different techniques: (I) a network of 18 stations; (II) field campaigns with mobile ground sensors; (III) 20-m resolution RADARSAT2 SAR images; (IV) numerical simulations using the GEOtop hydrological model (Rigon et al

  14. Implications of sensor design for coral reef detection: Upscaling ground hyperspectral imagery in spatial and spectral scales

    Science.gov (United States)

    Caras, Tamir; Hedley, John; Karnieli, Arnon

    2017-12-01

    Remote sensing offers a potential tool for large scale environmental surveying and monitoring. However, remote observations of coral reefs are difficult especially due to the spatial and spectral complexity of the target compared to sensor specifications as well as the environmental implications of the water medium above. The development of sensors is driven by technological advances and the desired products. Currently, spaceborne systems are technologically limited to a choice between high spectral resolution and high spatial resolution, but not both. The current study explores the dilemma of whether future sensor design for marine monitoring should prioritise on improving their spatial or spectral resolution. To address this question, a spatially and spectrally resampled ground-level hyperspectral image was used to test two classification elements: (1) how the tradeoff between spatial and spectral resolutions affects classification; and (2) how a noise reduction by majority filter might improve classification accuracy. The studied reef, in the Gulf of Aqaba (Eilat), Israel, is heterogeneous and complex so the local substrate patches are generally finer than currently available imagery. Therefore, the tested spatial resolution was broadly divided into four scale categories from five millimeters to one meter. Spectral resolution resampling aimed to mimic currently available and forthcoming spaceborne sensors such as (1) Environmental Mapping and Analysis Program (EnMAP) that is characterized by 25 bands of 6.5 nm width; (2) VENμS with 12 narrow bands; and (3) the WorldView series with broadband multispectral resolution. Results suggest that spatial resolution should generally be prioritized for coral reef classification because the finer spatial scale tested (pixel size mind, while the focus in this study was on the technologically limited spaceborne design, aerial sensors may presently provide an opportunity to implement the suggested setup.

  15. Magnetic Sensor for Detection of Ground Vehicles Based on Microwave Spin Wave Generation in Ferrite Films

    National Research Council Canada - National Science Library

    Slavin, A; Tiberkevich, V; Bankowski, E

    2006-01-01

    We propose to use the magnetic signatures, formed either by the residual magnetization or by deformation of the local Earth's magnetic field by large metal masses, for distant detection of ground vehicles...

  16. Fiber-optic sensors for rapid, inexpensive characterization of soil and ground water contamination

    International Nuclear Information System (INIS)

    Milanovich, F.P.; Yow, J.L. Jr.

    1994-08-01

    The extent and complexity of worldwide environmental contamination are great enough that characterization, remediation, and performance monitoring will be extremely costly and lengthy. Characterization techniques that are rapid, inexpensive, and simple and that do not generate waste are urgently needed. Towards this end LLNL is developing a fiber-optic chemical sensor technology for use in groundwater and vadose-zone monitoring. We use a colorimetric detection technique, based on an irreversible chemical reaction between a specific reagent and the target compound. The accuracy and sensitivity of the sensor (<5 ppb by weight in water, determined by comparison with gas chromatographic standard measurements) are sufficient for environmental monitoring of trichloroethylene (TCE) and chloroform

  17. A New Proxy Measurement Algorithm with Application to the Estimation of Vertical Ground Reaction Forces Using Wearable Sensors.

    Science.gov (United States)

    Guo, Yuzhu; Storm, Fabio; Zhao, Yifan; Billings, Stephen A; Pavic, Aleksandar; Mazzà, Claudia; Guo, Ling-Zhong

    2017-09-22

    Measurement of the ground reaction forces (GRF) during walking is typically limited to laboratory settings, and only short observations using wearable pressure insoles have been reported so far. In this study, a new proxy measurement method is proposed to estimate the vertical component of the GRF (vGRF) from wearable accelerometer signals. The accelerations are used as the proxy variable. An orthogonal forward regression algorithm (OFR) is employed to identify the dynamic relationships between the proxy variables and the measured vGRF using pressure-sensing insoles. The obtained model, which represents the connection between the proxy variable and the vGRF, is then used to predict the latter. The results have been validated using pressure insoles data collected from nine healthy individuals under two outdoor walking tasks in non-laboratory settings. The results show that the vGRFs can be reconstructed with high accuracy (with an average prediction error of less than 5.0%) using only one wearable sensor mounted at the waist (L5, fifth lumbar vertebra). Proxy measures with different sensor positions are also discussed. Results show that the waist acceleration-based proxy measurement is more stable with less inter-task and inter-subject variability than the proxy measures based on forehead level accelerations. The proposed proxy measure provides a promising low-cost method for monitoring ground reaction forces in real-life settings and introduces a novel generic approach for replacing the direct determination of difficult to measure variables in many applications.

  18. Evaluating MODIS Collection 6 Dark Target Over Water Aerosol Products for Multi-sensor Data Fusion

    Science.gov (United States)

    Shi, Y.; Zhang, J.; Reid, J. S.; Hyer, E. J.; McHardy, T. M.; Lee, L.

    2014-12-01

    The Moderate Resolution Imaging Spectroradiometer (MODIS) aerosol products have been widely used in aerosol related climate, visibility, and air quality studies for more than a decade. Recently, the MODIS collection 6 (c6) aerosol products from MODIS-Aqua have been released. The reported changes between Collection 5 and Collection 6 include updates in the retrieving algorithms and a new cloud filtering process for the over-ocean products. Thus it is necessary to fully evaluate the collection 6 products for applications that require high quality MODIS aerosol optical depth data, such as operational aerosol data assimilation. The uncertainties in the MODIS c6 DT over ocean products are studied through both inter-comparing with the Multi-angle Imaging Spectroradiometer (MISR) aerosol products and by evaluation against ground truth. Special attention is given to the low bias in MODIS DT products due to the misclassifications of heavy aerosol plumes as clouds. Finally, a quality assured data assimilation grade aerosol optical product is constructed for aerosol data assimilation related applications.

  19. Generation of Ground Truth Datasets for the Analysis of 3d Point Clouds in Urban Scenes Acquired via Different Sensors

    Science.gov (United States)

    Xu, Y.; Sun, Z.; Boerner, R.; Koch, T.; Hoegner, L.; Stilla, U.

    2018-04-01

    In this work, we report a novel way of generating ground truth dataset for analyzing point cloud from different sensors and the validation of algorithms. Instead of directly labeling large amount of 3D points requiring time consuming manual work, a multi-resolution 3D voxel grid for the testing site is generated. Then, with the help of a set of basic labeled points from the reference dataset, we can generate a 3D labeled space of the entire testing site with different resolutions. Specifically, an octree-based voxel structure is applied to voxelize the annotated reference point cloud, by which all the points are organized by 3D grids of multi-resolutions. When automatically annotating the new testing point clouds, a voting based approach is adopted to the labeled points within multiple resolution voxels, in order to assign a semantic label to the 3D space represented by the voxel. Lastly, robust line- and plane-based fast registration methods are developed for aligning point clouds obtained via various sensors. Benefiting from the labeled 3D spatial information, we can easily create new annotated 3D point clouds of different sensors of the same scene directly by considering the corresponding labels of 3D space the points located, which would be convenient for the validation and evaluation of algorithms related to point cloud interpretation and semantic segmentation.

  20. Flight Test Result for the Ground-Based Radio Navigation System Sensor with an Unmanned Air Vehicle.

    Science.gov (United States)

    Jang, Jaegyu; Ahn, Woo-Guen; Seo, Seungwoo; Lee, Jang Yong; Park, Jun-Pyo

    2015-11-11

    The Ground-based Radio Navigation System (GRNS) is an alternative/backup navigation system based on time synchronized pseudolites. It has been studied for some years due to the potential vulnerability issue of satellite navigation systems (e.g., GPS or Galileo). In the framework of our study, a periodic pulsed sequence was used instead of the randomized pulse sequence recommended as the RTCM (radio technical commission for maritime services) SC (special committee)-104 pseudolite signal, as a randomized pulse sequence with a long dwell time is not suitable for applications requiring high dynamics. This paper introduces a mathematical model of the post-correlation output in a navigation sensor, showing that the aliasing caused by the additional frequency term of a periodic pulsed signal leads to a false lock (i.e., Doppler frequency bias) during the signal acquisition process or in the carrier tracking loop of the navigation sensor. We suggest algorithms to resolve the frequency false lock issue in this paper, relying on the use of a multi-correlator. A flight test with an unmanned helicopter was conducted to verify the implemented navigation sensor. The results of this analysis show that there were no false locks during the flight test and that outliers stem from bad dilution of precision (DOP) or fluctuations in the received signal quality.

  1. Evaluation of event-based algorithms for optical flow with ground-truth from inertial measurement sensor

    Directory of Open Access Journals (Sweden)

    Bodo eRückauer

    2016-04-01

    Full Text Available In this study we compare nine optical flow algorithms that locally measure the flow normal to edges according to accuracy and computation cost. In contrast to conventional, frame-based motion flow algorithms, our open-source implementations compute optical flow based on address-events from a neuromorphic Dynamic Vision Sensor (DVS. For this benchmarking we created a dataset of two synthesized and three real samples recorded from a 240x180 pixel Dynamic and Active-pixel Vision Sensor (DAVIS. This dataset contains events from the DVS as well as conventional frames to support testing state-of-the-art frame-based methods. We introduce a new source for the ground truth: In the special case that the perceived motion stems solely from a rotation of the vision sensor around its three camera axes, the true optical flow can be estimated using gyro data from the inertial measurement unit integrated with the DAVIS camera. This provides a ground-truth to which we can compare algorithms that measure optical flow by means of motion cues. An analysis of error sources led to the use of a refractory period, more accurate numerical derivatives and a Savitzky-Golay filter to achieve significant improvements in accuracy. Our pure Java implementations of two recently published algorithms reduce computational cost by up to 29% compared to the original implementations. Two of the algorithms introduced in this paper further speed up processing by a factor of 10 compared with the original implementations, at equal or better accuracy. On a desktop PC, they run in real-time on dense natural input recorded by a DAVIS camera.

  2. Assessment of Above-Ground Biomass of Borneo Forests through a New Data-Fusion Approach Combining Two Pan-Tropical Biomass Maps

    Directory of Open Access Journals (Sweden)

    Andreas Langner

    2015-08-01

    Full Text Available This study investigates how two existing pan-tropical above-ground biomass (AGB maps (Saatchi 2011, Baccini 2012 can be combined to derive forest ecosystem specific carbon estimates. Several data-fusion models which combine these AGB maps according to their local correlations with independent datasets such as the spectral bands of SPOT VEGETATION imagery are analyzed. Indeed these spectral bands convey information about vegetation type and structure which can be related to biomass values. Our study area is the island of Borneo. The data-fusion models are evaluated against a reference AGB map available for two forest concessions in Sabah. The highest accuracy was achieved by a model which combines the AGB maps according to the mean of the local correlation coefficients calculated over different kernel sizes. Combining the resulting AGB map with a new Borneo land cover map (whose overall accuracy has been estimated at 86.5% leads to average AGB estimates of 279.8 t/ha and 233.1 t/ha for forests and degraded forests respectively. Lowland dipterocarp and mangrove forests have the highest and lowest AGB values (305.8 t/ha and 136.5 t/ha respectively. The AGB of all natural forests amounts to 10.8 Gt mainly stemming from lowland dipterocarp (66.4%, upper dipterocarp (10.9% and peat swamp forests (10.2%. Degraded forests account for another 2.1 Gt of AGB. One main advantage of our approach is that, once the best fitting data-fusion model is selected, no further AGB reference dataset is required for implementing the data-fusion process. Furthermore, the local harmonization of AGB datasets leads to more spatially precise maps. This approach can easily be extended to other areas in Southeast Asia which are dominated by lowland dipterocarp forest, and can be repeated when newer or more accurate AGB maps become available.

  3. Simulation of olive grove gross primary production by the combination of ground and multi-sensor satellite data

    Science.gov (United States)

    Brilli, L.; Chiesi, M.; Maselli, F.; Moriondo, M.; Gioli, B.; Toscano, P.; Zaldei, A.; Bindi, M.

    2013-08-01

    We developed and tested a methodology to estimate olive (Olea europaea L.) gross primary production (GPP) combining ground and multi-sensor satellite data. An eddy-covariance station placed in an olive grove in central Italy provided carbon and water fluxes over two years (2010-2011), which were used as reference to evaluate the performance of a GPP estimation methodology based on a Monteith type model (modified C-Fix) and driven by meteorological and satellite (NDVI) data. A major issue was related to the consideration of the two main olive grove components, i.e. olive trees and inter-tree ground vegetation: this issue was addressed by the separate simulation of carbon fluxes within the two ecosystem layers, followed by their recombination. In this way the eddy covariance GPP measurements were successfully reproduced, with the exception of two periods that followed tillage operations. For these periods measured GPP could be approximated by considering synthetic NDVI values which simulated the expected response of inter-tree ground vegetation to tillages.

  4. Sensor fusion and computer vision for context-aware control of a multi degree-of-freedom prosthesis.

    Science.gov (United States)

    Markovic, Marko; Dosen, Strahinja; Popovic, Dejan; Graimann, Bernhard; Farina, Dario

    2015-12-01

    Myoelectric activity volitionally generated by the user is often used for controlling hand prostheses in order to replicate the synergistic actions of muscles in healthy humans during grasping. Muscle synergies in healthy humans are based on the integration of visual perception, heuristics and proprioception. Here, we demonstrate how sensor fusion that combines artificial vision and proprioceptive information with the high-level processing characteristics of biological systems can be effectively used in transradial prosthesis control. We developed a novel context- and user-aware prosthesis (CASP) controller integrating computer vision and inertial sensing with myoelectric activity in order to achieve semi-autonomous and reactive control of a prosthetic hand. The presented method semi-automatically provides simultaneous and proportional control of multiple degrees-of-freedom (DOFs), thus decreasing overall physical effort while retaining full user control. The system was compared against the major commercial state-of-the art myoelectric control system in ten able-bodied and one amputee subject. All subjects used transradial prosthesis with an active wrist to grasp objects typically associated with activities of daily living. The CASP significantly outperformed the myoelectric interface when controlling all of the prosthesis DOF. However, when tested with less complex prosthetic system (smaller number of DOF), the CASP was slower but resulted with reaching motions that contained less compensatory movements. Another important finding is that the CASP system required minimal user adaptation and training. The CASP constitutes a substantial improvement for the control of multi-DOF prostheses. The application of the CASP will have a significant impact when translated to real-life scenarious, particularly with respect to improving the usability and acceptance of highly complex systems (e.g., full prosthetic arms) by amputees.

  5. Sensor fusion and computer vision for context-aware control of a multi degree-of-freedom prosthesis

    Science.gov (United States)

    Markovic, Marko; Dosen, Strahinja; Popovic, Dejan; Graimann, Bernhard; Farina, Dario

    2015-12-01

    Objective. Myoelectric activity volitionally generated by the user is often used for controlling hand prostheses in order to replicate the synergistic actions of muscles in healthy humans during grasping. Muscle synergies in healthy humans are based on the integration of visual perception, heuristics and proprioception. Here, we demonstrate how sensor fusion that combines artificial vision and proprioceptive information with the high-level processing characteristics of biological systems can be effectively used in transradial prosthesis control. Approach. We developed a novel context- and user-aware prosthesis (CASP) controller integrating computer vision and inertial sensing with myoelectric activity in order to achieve semi-autonomous and reactive control of a prosthetic hand. The presented method semi-automatically provides simultaneous and proportional control of multiple degrees-of-freedom (DOFs), thus decreasing overall physical effort while retaining full user control. The system was compared against the major commercial state-of-the art myoelectric control system in ten able-bodied and one amputee subject. All subjects used transradial prosthesis with an active wrist to grasp objects typically associated with activities of daily living. Main results. The CASP significantly outperformed the myoelectric interface when controlling all of the prosthesis DOF. However, when tested with less complex prosthetic system (smaller number of DOF), the CASP was slower but resulted with reaching motions that contained less compensatory movements. Another important finding is that the CASP system required minimal user adaptation and training. Significance. The CASP constitutes a substantial improvement for the control of multi-DOF prostheses. The application of the CASP will have a significant impact when translated to real-life scenarious, particularly with respect to improving the usability and acceptance of highly complex systems (e.g., full prosthetic arms) by amputees.

  6. 800 C Silicon Carbide (SiC) Pressure Sensors for Engine Ground Testing

    Science.gov (United States)

    Okojie, Robert S.

    2016-01-01

    MEMS-based 4H-SiC piezoresistive pressure sensors have been demonstrated at 800 C, leading to the discovery of strain sensitivity recovery with increasing temperatures above 400 C, eventually achieving up to, or near, 100 recovery of the room temperature values at 800 C. This result will allow the insertion of highly sensitive pressure sensors closer to jet, rocket, and hypersonic engine combustion chambers to improve the quantification accuracy of combustor dynamics, performance, and increase safety margin. Also, by operating at higher temperature and locating closer to the combustion chamber, reduction of the length (weight) of pressure tubes that are currently used will be achieved. This will result in reduced costlb to access space.

  7. Production Rule Systems as an Approach to Interpretation of Ground Sensor Information.

    Science.gov (United States)

    1980-06-01

    Z_4 1. Overview . . .......... . .. 4 2. tesin of the Prototype Knowledee -based "?roluc tior System ..................... 4 I V ’?>NA...operated by the sensor control and management platoon (SCAMP). One SCAMP is allocated per division; each SCAMP functions under the coRnizance of the 414...apprnach. Sienal understandin- tasks, of which the problem under consideration in this thesis is a member, seem well suited to the application of knowlede

  8. A promising trend for field information collection: An air-ground multi-sensor monitoring system

    OpenAIRE

    Yawei Zhang; Du Chen; Shumao Wang; Lei Tian

    2018-01-01

    Timely identifying and quantifying significant spatial and temporal variability in agricultural field has been a crucial factor for improving agricultural production and management. This paper focuses on the mainstream techniques and applications can be adopted to improve the field information collection method. In this paper, the development of wireless sensor networks (WSNs) and remote sensing (RS) technology were reviewed, especially the micro unmanned aerial vehicle (mUAV)-based WSNs and ...

  9. The Effect of Three Different Data Fusion Approaches on the Quality of Soil Moisture Retrievals from Multiple Passive Microwave Sensors

    Directory of Open Access Journals (Sweden)

    Robin van der Schalie

    2018-01-01

    Full Text Available Long-term climate records of soil moisture are of increased importance to climate researchers. In this study, we aim to evaluate the quality of three different fusion approaches that combine soil moisture retrieval from multiple satellite sensors. The arrival of L-band missions has led to an increased focus on the integration of L-band-based soil moisture retrievals in climate records, emphasizing the need to improve our understanding based on its added value within a multi-sensor framework. The three evaluated approaches were developed on 10-year passive microwave data (2003–2013 from two different satellite sensors, i.e., SMOS (2010–2013 and AMSR-E (2003–2011, and are based on a neural network (NN, regressions (REG, and the Land Parameter Retrieval Model (LPRM. The ability of the different approaches to best match AMSR-E and SMOS in their overlapping period was tested using an inter-comparison exercise between the SMOS and AMSR-E datasets, while the skill of the individual soil moisture products, based on anomalies, was evaluated using two verification techniques; first, a data assimilation technique that links precipitation information to the quality of soil moisture (expressed as the Rvalue, and secondly the triple collocation analysis (TCA. ASCAT soil moisture was included in the skill evaluation, representing the active microwave-based counterpart of soil moisture retrievals. Besides a semi-global analysis, explicit focus was placed on two regions that have strong land–atmosphere coupling, the Sahel (SA and the central Great Plains (CGP of North America. The NN approach gives the highest correlation coefficient between SMOS and AMSR-E, closely followed by LPRM and REG, while the absolute error is approximately the same for all three approaches. The Rvalue and TCA show the strength of using different satellite sources and the impact of different merging approaches on the skill to correctly capture soil moisture anomalies. The

  10. Quantitative characterization of pulverized coal and biomass–coal blends in pneumatic conveying pipelines using electrostatic sensor arrays and data fusion techniques

    International Nuclear Information System (INIS)

    Qian, Xiangchen; Wang, Chao; Yan, Yong; Shao, Jiaqing; Wang, Lijuan; Zhou, Hao

    2012-01-01

    Quantitative data about the dynamic behaviour of pulverized coal and biomass–coal blends in fuel injection pipelines allow power plant operators to detect variations in fuel supply and oscillations in the flow at an early stage, enable them to balance fuel distribution between fuel feeding pipes and ultimately to achieve higher combustion efficiency and lower greenhouse gas emissions. Electrostatic sensor arrays and data fusion algorithms are combined to provide a non-intrusive solution to the measurement of fuel particle velocity, relative solid concentration and flow stability under pneumatic conveying conditions. Electrostatic sensor arrays with circular and arc-shaped electrodes are integrated in the same sensing head to measure ‘averaged’ and ‘localized’ characteristics of pulverized fuel flow. Data fusion techniques are applied to optimize and integrate the results from the sensor arrays. Experimental tests were conducted on the horizontal section of a 150 mm bore pneumatic conveyor circulating pulverized coal and sawdust under various flow conditions. Test results suggest that pure coal particles travel faster and carry more electrostatic charge than biomass–coal blends. As more biomass particles are added to the flow, the overall velocity of the flow reduces, the electrostatic charge level on particles decreases and the flow becomes less stable compared to the pure coal flow. (paper)

  11. Quantitative characterization of pulverized coal and biomass-coal blends in pneumatic conveying pipelines using electrostatic sensor arrays and data fusion techniques

    Science.gov (United States)

    Qian, Xiangchen; Yan, Yong; Shao, Jiaqing; Wang, Lijuan; Zhou, Hao; Wang, Chao

    2012-08-01

    Quantitative data about the dynamic behaviour of pulverized coal and biomass-coal blends in fuel injection pipelines allow power plant operators to detect variations in fuel supply and oscillations in the flow at an early stage, enable them to balance fuel distribution between fuel feeding pipes and ultimately to achieve higher combustion efficiency and lower greenhouse gas emissions. Electrostatic sensor arrays and data fusion algorithms are combined to provide a non-intrusive solution to the measurement of fuel particle velocity, relative solid concentration and flow stability under pneumatic conveying conditions. Electrostatic sensor arrays with circular and arc-shaped electrodes are integrated in the same sensing head to measure ‘averaged’ and ‘localized’ characteristics of pulverized fuel flow. Data fusion techniques are applied to optimize and integrate the results from the sensor arrays. Experimental tests were conducted on the horizontal section of a 150 mm bore pneumatic conveyor circulating pulverized coal and sawdust under various flow conditions. Test results suggest that pure coal particles travel faster and carry more electrostatic charge than biomass-coal blends. As more biomass particles are added to the flow, the overall velocity of the flow reduces, the electrostatic charge level on particles decreases and the flow becomes less stable compared to the pure coal flow.

  12. Sensors

    CERN Document Server

    Pigorsch, Enrico

    1997-01-01

    This is the 5th edition of the Metra Martech Directory "EUROPEAN CENTRES OF EXPERTISE - SENSORS." The entries represent a survey of European sensors development. The new edition contains 425 detailed profiles of companies and research institutions in 22 countries. This is reflected in the diversity of sensors development programmes described, from sensors for physical parameters to biosensors and intelligent sensor systems. We do not claim that all European organisations developing sensors are included, but this is a good cross section from an invited list of participants. If you see gaps or omissions, or would like your organisation to be included, please send details. The data base invites the formation of effective joint ventures by identifying and providing access to specific areas in which organisations offer collaboration. This issue is recognised to be of great importance and most entrants include details of collaboration offered and sought. We hope the directory on Sensors will help you to find the ri...

  13. Sensors

    Energy Technology Data Exchange (ETDEWEB)

    Jensen, H. [PBI-Dansensor A/S (Denmark); Toft Soerensen, O. [Risoe National Lab., Materials Research Dept. (Denmark)

    1999-10-01

    A new type of ceramic oxygen sensors based on semiconducting oxides was developed in this project. The advantage of these sensors compared to standard ZrO{sub 2} sensors is that they do not require a reference gas and that they can be produced in small sizes. The sensor design and the techniques developed for production of these sensors are judged suitable by the participating industry for a niche production of a new generation of oxygen sensors. Materials research on new oxygen ion conducting conductors both for applications in oxygen sensors and in fuel was also performed in this project and finally a new process was developed for fabrication of ceramic tubes by dip-coating. (EHS)

  14. (DCT-FY08) Target Detection Using Multiple Modality Airborne and Ground Based Sensors

    Science.gov (United States)

    2013-03-01

    resolution SIFT grids in metric-topological SLAM ,” in Proc. of the IEEE Conference on Computer Vision and Pattern Recognition, 2009. [4] M. Bosse and R...single camera SLAM ,” IEEE Trans. Pattern Anal. Mach. Intell., vol. 29, no. 6, pp. 1052–1067, 2007. [7] D. Nister, O. Naroditsky, and J. Bergen...segmentation with ground-based and airborne LIDAR range data,” in Proceedings of the Fourth International Symposium on 3D Data Processing

  15. Sensoring fusion data from the optic and acoustic emissions of electric arcs in the GMAW-S process for welding quality assessment.

    Science.gov (United States)

    Alfaro, Sadek Crisóstomo Absi; Cayo, Eber Huanca

    2012-01-01

    The present study shows the relationship between welding quality and optical-acoustic emissions from electric arcs, during welding runs, in the GMAW-S process. Bead on plate welding tests was carried out with pre-set parameters chosen from manufacturing standards. During the welding runs interferences were induced on the welding path using paint, grease or gas faults. In each welding run arc voltage, welding current, infrared and acoustic emission values were acquired and parameters such as arc power, acoustic peaks rate and infrared radiation rate computed. Data fusion algorithms were developed by assessing known welding quality parameters from arc emissions. These algorithms have showed better responses when they are based on more than just one sensor. Finally, it was concluded that there is a close relation between arc emissions and quality in welding and it can be measured from arc emissions sensing and data fusion algorithms.

  16. Sensoring Fusion Data from the Optic and Acoustic Emissions of Electric Arcs in the GMAW-S Process for Welding Quality Assessment

    Directory of Open Access Journals (Sweden)

    Eber Huanca Cayo

    2012-05-01

    Full Text Available The present study shows the relationship between welding quality and optical-acoustic emissions from electric arcs, during welding runs, in the GMAW-S process. Bead on plate welding tests was carried out with pre-set parameters chosen from manufacturing standards. During the welding runs interferences were induced on the welding path using paint, grease or gas faults. In each welding run arc voltage, welding current, infrared and acoustic emission values were acquired and parameters such as arc power, acoustic peaks rate and infrared radiation rate computed. Data fusion algorithms were developed by assessing known welding quality parameters from arc emissions. These algorithms have showed better responses when they are based on more than just one sensor. Finally, it was concluded that there is a close relation between arc emissions and quality in welding and it can be measured from arc emissions sensing and data fusion algorithms.

  17. Satellite and Ground-Based Sensors for the Urban Heat Island Analysis in the City of Rome

    Directory of Open Access Journals (Sweden)

    Roberto Fabrizi

    2010-05-01

    Full Text Available In this work, the trend of the Urban Heat Island (UHI of Rome is analyzed by both ground-based weather stations and a satellite-based infrared sensor. First, we have developed a suitable algorithm employing satellite brightness temperatures for the estimation of the air temperature belonging to the layer of air closest to the surface. UHI spatial characteristics have been assessed using air temperatures measured by both weather stations and brightness temperature maps from the Advanced Along Track Scanning Radiometer (AATSR on board ENVISAT polar-orbiting satellite. In total, 634 daytime and nighttime scenes taken between 2003 and 2006 have been processed. Analysis of the Canopy Layer Heat Island (CLHI during summer months reveals a mean growth in magnitude of 3–4 K during nighttime and a negative or almost zero CLHI intensity during daytime, confirmed by the weather stations.

  18. Fusion of Satellite Multispectral Images Based on Ground-Penetrating Radar (GPR Data for the Investigation of Buried Concealed Archaeological Remains

    Directory of Open Access Journals (Sweden)

    Athos Agapiou

    2017-06-01

    Full Text Available The paper investigates the superficial layers of an archaeological landscape based on the integration of various remote sensing techniques. It is well known in the literature that shallow depths may be rich in archeological remains, which generate different signal responses depending on the applied technique. In this study three main technologies are examined, namely ground-penetrating radar (GPR, ground spectroscopy, and multispectral satellite imagery. The study aims to propose a methodology to enhance optical remote sensing satellite images, intended for archaeological research, based on the integration of ground based and satellite datasets. For this task, a regression model between the ground spectroradiometer and GPR is established which is then projected to a high resolution sub-meter optical image. The overall methodology consists of nine steps. Beyond the acquirement of the in-situ measurements and their calibration (Steps 1–3, various regression models are examined for more than 70 different vegetation indices (Steps 4–5. The specific data analysis indicated that the red-edge position (REP hyperspectral index was the most appropriate for developing a local fusion model between ground spectroscopy data and GPR datasets (Step 6, providing comparable results with the in situ GPR measurements (Step 7. Other vegetation indices, such as the normalized difference vegetation index (NDVI, have also been examined, providing significant correlation between the two datasets (R = 0.50. The model is then projected to a high-resolution image over the area of interest (Step 8. The proposed methodology was evaluated with a series of field data collected from the Vésztő-Mágor Tell in the eastern part of Hungary. The results were compared with in situ magnetic gradiometry measurements, indicating common interpretation results. The results were also compatible with the preliminary archaeological investigations of the area (Step 9. The overall

  19. A New Proxy Measurement Algorithm with Application to the Estimation of Vertical Ground Reaction Forces Using Wearable Sensors

    Directory of Open Access Journals (Sweden)

    Yuzhu Guo

    2017-09-01

    Full Text Available Measurement of the ground reaction forces (GRF during walking is typically limited to laboratory settings, and only short observations using wearable pressure insoles have been reported so far. In this study, a new proxy measurement method is proposed to estimate the vertical component of the GRF (vGRF from wearable accelerometer signals. The accelerations are used as the proxy variable. An orthogonal forward regression algorithm (OFR is employed to identify the dynamic relationships between the proxy variables and the measured vGRF using pressure-sensing insoles. The obtained model, which represents the connection between the proxy variable and the vGRF, is then used to predict the latter. The results have been validated using pressure insoles data collected from nine healthy individuals under two outdoor walking tasks in non-laboratory settings. The results show that the vGRFs can be reconstructed with high accuracy (with an average prediction error of less than 5.0% using only one wearable sensor mounted at the waist (L5, fifth lumbar vertebra. Proxy measures with different sensor positions are also discussed. Results show that the waist acceleration-based proxy measurement is more stable with less inter-task and inter-subject variability than the proxy measures based on forehead level accelerations. The proposed proxy measure provides a promising low-cost method for monitoring ground reaction forces in real-life settings and introduces a novel generic approach for replacing the direct determination of difficult to measure variables in many applications.

  20. Validating MODIS and Sentinel-2 NDVI Products at a Temperate Deciduous Forest Site Using Two Independent Ground-Based Sensors.

    Science.gov (United States)

    Lange, Maximilian; Dechant, Benjamin; Rebmann, Corinna; Vohland, Michael; Cuntz, Matthias; Doktor, Daniel

    2017-08-11

    Quantifying the accuracy of remote sensing products is a timely endeavor given the rapid increase in Earth observation missions. A validation site for Sentinel-2 products was hence established in central Germany. Automatic multispectral and hyperspectral sensor systems were installed in parallel with an existing eddy covariance flux tower, providing spectral information of the vegetation present at high temporal resolution. Normalized Difference Vegetation Index (NDVI) values from ground-based hyperspectral and multispectral sensors were compared with NDVI products derived from Sentinel-2A and Moderate-resolution Imaging Spectroradiometer (MODIS). The influence of different spatial and temporal resolutions was assessed. High correlations and similar phenological patterns between in situ and satellite-based NDVI time series demonstrated the reliability of satellite-based phenological metrics. Sentinel-2-derived metrics showed better agreement with in situ measurements than MODIS-derived metrics. Dynamic filtering with the best index slope extraction algorithm was nevertheless beneficial for Sentinel-2 NDVI time series despite the availability of quality information from the atmospheric correction procedure.

  1. Validation of OMI erythemal doses with multi-sensor ground-based measurements in Thessaloniki, Greece

    Science.gov (United States)

    Zempila, Melina Maria; Fountoulakis, Ilias; Taylor, Michael; Kazadzis, Stelios; Arola, Antti; Koukouli, Maria Elissavet; Bais, Alkiviadis; Meleti, Chariklia; Balis, Dimitrios

    2018-06-01

    The aim of this study is to validate the Ozone Monitoring Instrument (OMI) erythemal dose rates using ground-based measurements in Thessaloniki, Greece. In the Laboratory of Atmospheric Physics of the Aristotle University of Thessaloniki, a Yankee Environmental System UVB-1 radiometer measures the erythemal dose rates every minute, and a Norsk Institutt for Luftforskning (NILU) multi-filter radiometer provides multi-filter based irradiances that were used to derive erythemal dose rates for the period 2005-2014. Both these datasets were independently validated against collocated UV irradiance spectra from a Brewer MkIII spectrophotometer. Cloud detection was performed based on measurements of the global horizontal radiation from a Kipp & Zonen pyranometer and from NILU measurements in the visible range. The satellite versus ground observation validation was performed taking into account the effect of temporal averaging, limitations related to OMI quality control criteria, cloud conditions, the solar zenith angle and atmospheric aerosol loading. Aerosol optical depth was also retrieved using a collocated CIMEL sunphotometer in order to assess its impact on the comparisons. The effect of total ozone columns satellite versus ground-based differences on the erythemal dose comparisons was also investigated. Since most of the public awareness alerts are based on UV Index (UVI) classifications, an analysis and assessment of OMI capability for retrieving UVIs was also performed. An overestimation of the OMI erythemal product by 3-6% and 4-8% with respect to ground measurements is observed when examining overpass and noontime estimates respectively. The comparisons revealed a relatively small solar zenith angle dependence, with the OMI data showing a slight dependence on aerosol load, especially at high aerosol optical depth values. A mean underestimation of 2% in OMI total ozone columns under cloud-free conditions was found to lead to an overestimation in OMI erythemal

  2. Autonomous Aerial Refueling Ground Test Demonstration—A Sensor-in-the-Loop, Non-Tracking Method

    Directory of Open Access Journals (Sweden)

    Chao-I Chen

    2015-05-01

    Full Text Available An essential capability for an unmanned aerial vehicle (UAV to extend its airborne duration without increasing the size of the aircraft is called the autonomous aerial refueling (AAR. This paper proposes a sensor-in-the-loop, non-tracking method for probe-and-drogue style autonomous aerial refueling tasks by combining sensitivity adjustments of a 3D Flash LIDAR camera with computer vision based image-processing techniques. The method overcomes the inherit ambiguity issues when reconstructing 3D information from traditional 2D images by taking advantage of ready to use 3D point cloud data from the camera, followed by well-established computer vision techniques. These techniques include curve fitting algorithms and outlier removal with the random sample consensus (RANSAC algorithm to reliably estimate the drogue center in 3D space, as well as to establish the relative position between the probe and the drogue. To demonstrate the feasibility of the proposed method on a real system, a ground navigation robot was designed and fabricated. Results presented in the paper show that using images acquired from a 3D Flash LIDAR camera as real time visual feedback, the ground robot is able to track a moving simulated drogue and continuously narrow the gap between the robot and the target autonomously.

  3. An interprojection sensor fusion approach to estimate blocked projection signal in synchronized moving grid-based CBCT system

    Energy Technology Data Exchange (ETDEWEB)

    Zhang, Hong; Kong, Vic [Department of Radiation Oncology, Georgia Regents University, Augusta, Georgia 30912 (United States); Ren, Lei; Giles, William; Zhang, You [Department of Radiation Oncology, Duke University, Durham, North Carolina 27710 (United States); Jin, Jian-Yue, E-mail: jjin@gru.edu [Department of Radiation Oncology, Georgia Regents University, Augusta, Georgia 30912 and Department of Radiology, Georgia Regents University, Augusta, Georgia 30912 (United States)

    2016-01-15

    Purpose: A preobject grid can reduce and correct scatter in cone beam computed tomography (CBCT). However, half of the signal in each projection is blocked by the grid. A synchronized moving grid (SMOG) has been proposed to acquire two complimentary projections at each gantry position and merge them into one complete projection. That approach, however, suffers from increased scanning time and the technical difficulty of accurately merging the two projections per gantry angle. Herein, the authors present a new SMOG approach which acquires a single projection per gantry angle, with complimentary grid patterns for any two adjacent projections, and use an interprojection sensor fusion (IPSF) technique to estimate the blocked signal in each projection. The method may have the additional benefit of reduced imaging dose due to the grid blocking half of the incident radiation. Methods: The IPSF considers multiple paired observations from two adjacent gantry angles as approximations of the blocked signal and uses a weighted least square regression of these observations to finally determine the blocked signal. The method was first tested with a simulated SMOG on a head phantom. The signal to noise ratio (SNR), which represents the difference of the recovered CBCT image to the original image without the SMOG, was used to evaluate the ability of the IPSF in recovering the missing signal. The IPSF approach was then tested using a Catphan phantom on a prototype SMOG assembly installed in a bench top CBCT system. Results: In the simulated SMOG experiment, the SNRs were increased from 15.1 and 12.7 dB to 35.6 and 28.9 dB comparing with a conventional interpolation method (inpainting method) for a projection and the reconstructed 3D image, respectively, suggesting that IPSF successfully recovered most of blocked signal. In the prototype SMOG experiment, the authors have successfully reconstructed a CBCT image using the IPSF-SMOG approach. The detailed geometric features in the

  4. An interprojection sensor fusion approach to estimate blocked projection signal in synchronized moving grid-based CBCT system

    International Nuclear Information System (INIS)

    Zhang, Hong; Kong, Vic; Ren, Lei; Giles, William; Zhang, You; Jin, Jian-Yue

    2016-01-01

    Purpose: A preobject grid can reduce and correct scatter in cone beam computed tomography (CBCT). However, half of the signal in each projection is blocked by the grid. A synchronized moving grid (SMOG) has been proposed to acquire two complimentary projections at each gantry position and merge them into one complete projection. That approach, however, suffers from increased scanning time and the technical difficulty of accurately merging the two projections per gantry angle. Herein, the authors present a new SMOG approach which acquires a single projection per gantry angle, with complimentary grid patterns for any two adjacent projections, and use an interprojection sensor fusion (IPSF) technique to estimate the blocked signal in each projection. The method may have the additional benefit of reduced imaging dose due to the grid blocking half of the incident radiation. Methods: The IPSF considers multiple paired observations from two adjacent gantry angles as approximations of the blocked signal and uses a weighted least square regression of these observations to finally determine the blocked signal. The method was first tested with a simulated SMOG on a head phantom. The signal to noise ratio (SNR), which represents the difference of the recovered CBCT image to the original image without the SMOG, was used to evaluate the ability of the IPSF in recovering the missing signal. The IPSF approach was then tested using a Catphan phantom on a prototype SMOG assembly installed in a bench top CBCT system. Results: In the simulated SMOG experiment, the SNRs were increased from 15.1 and 12.7 dB to 35.6 and 28.9 dB comparing with a conventional interpolation method (inpainting method) for a projection and the reconstructed 3D image, respectively, suggesting that IPSF successfully recovered most of blocked signal. In the prototype SMOG experiment, the authors have successfully reconstructed a CBCT image using the IPSF-SMOG approach. The detailed geometric features in the

  5. Weaving Hilbert space fusion frames

    OpenAIRE

    Neyshaburi, Fahimeh Arabyani; Arefijamaal, Ali Akbar

    2018-01-01

    A new notion in frame theory, so called weaving frames has been recently introduced to deal with some problems in signal processing and wireless sensor networks. Also, fusion frames are an important extension of frames, used in many areas especially for wireless sensor networks. In this paper, we survey the notion of weaving Hilbert space fusion frames. This concept can be had potential applications in wireless sensor networks which require distributed processing using different fusion frames...

  6. Communications for unattended sensor networks

    Science.gov (United States)

    Nemeroff, Jay L.; Angelini, Paul; Orpilla, Mont; Garcia, Luis; DiPierro, Stefano

    2004-07-01

    The future model of the US Army's Future Combat Systems (FCS) and the Future Force reflects a combat force that utilizes lighter armor protection than the current standard. Survival on the future battlefield will be increased by the use of advanced situational awareness provided by unattended tactical and urban sensors that detect, identify, and track enemy targets and threats. Successful implementation of these critical sensor fields requires the development of advanced sensors, sensor and data-fusion processors, and a specialized communications network. To ensure warfighter and asset survivability, the communications must be capable of near real-time dissemination of the sensor data using robust, secure, stealthy, and jam resistant links so that the proper and decisive action can be taken. Communications will be provided to a wide-array of mission-specific sensors that are capable of processing data from acoustic, magnetic, seismic, and/or Chemical, Biological, Radiological, and Nuclear (CBRN) sensors. Other, more powerful, sensor node configurations will be capable of fusing sensor data and intelligently collect and process data images from infrared or visual imaging cameras. The radio waveform and networking protocols being developed under the Soldier Level Integrated Communications Environment (SLICE) Soldier Radio Waveform (SRW) and the Networked Sensors for the Future Force Advanced Technology Demonstration are part of an effort to develop a common waveform family which will operate across multiple tactical domains including dismounted soldiers, ground sensor, munitions, missiles and robotics. These waveform technologies will ultimately be transitioned to the JTRS library, specifically the Cluster 5 requirement.

  7. Integrated Active Fire Retrievals and Biomass Burning Emissions Using Complementary Near-Coincident Ground, Airborne and Spaceborne Sensor Data

    Science.gov (United States)

    Schroeder, Wilfrid; Ellicott, Evan; Ichoku, Charles; Ellison, Luke; Dickinson, Matthew B.; Ottmar, Roger D.; Clements, Craig; Hall, Dianne; Ambrosia, Vincent; Kremens, Robert

    2013-01-01

    Ground, airborne and spaceborne data were collected for a 450 ha prescribed fire implemented on 18 October 2011 at the Henry W. Coe State Park in California. The integration of various data elements allowed near coincident active fire retrievals to be estimated. The Autonomous Modular Sensor-Wildfire (AMS) airborne multispectral imaging system was used as a bridge between ground and spaceborne data sets providing high quality reference information to support satellite fire retrieval error analyses and fire emissions estimates. We found excellent agreement between peak fire radiant heat flux data (less than 1% error) derived from near-coincident ground radiometers and AMS. Both MODIS and GOES imager active fire products were negatively influenced by the presence of thick smoke, which was misclassified as cloud by their algorithms, leading to the omission of fire pixels beneath the smoke, and resulting in the underestimation of their retrieved fire radiative power (FRP) values for the burn plot, compared to the reference airborne data. Agreement between airborne and spaceborne FRP data improved significantly after correction for omission errors and atmospheric attenuation, resulting in as low as 5 difference between AquaMODIS and AMS. Use of in situ fuel and fire energy estimates in combination with a collection of AMS, MODIS, and GOES FRP retrievals provided a fuel consumption factor of 0.261 kg per MJ, total energy release of 14.5 x 10(exp 6) MJ, and total fuel consumption of 3.8 x 10(exp 6) kg. Fire emissions were calculated using two separate techniques, resulting in as low as 15 difference for various species

  8. Estimation of ground reaction forces and joint moments on the basis on plantar pressure insoles and wearable sensors for joint angle measurement.

    Science.gov (United States)

    Ostaszewski, Michal; Pauk, Jolanta

    2018-05-16

    Gait analysis is a useful tool medical staff use to support clinical decision making. There is still an urgent need to develop low-cost and unobtrusive mobile health monitoring systems. The goal of this study was twofold. Firstly, a wearable sensor system composed of plantar pressure insoles and wearable sensors for joint angle measurement was developed. Secondly, the accuracy of the system in the measurement of ground reaction forces and joint moments was examined. The measurements included joint angles and plantar pressure distribution. To validate the wearable sensor system and examine the effectiveness of the proposed method for gait analysis, an experimental study on ten volunteer subjects was conducted. The accuracy of measurement of ground reaction forces and joint moments was validated against the results obtained from a reference motion capture system. Ground reaction forces and joint moments measured by the wearable sensor system showed a root mean square error of 1% for min. GRF and 27.3% for knee extension moment. The correlation coefficient was over 0.9, in comparison with the stationary motion capture system. The study suggests that the wearable sensor system could be recommended both for research and clinical applications outside a typical gait laboratory.

  9. Continuous Water Vapor Profiles from Operational Ground-Based Active and Passive Remote Sensors

    Science.gov (United States)

    Turner, D. D.; Feltz, W. F.; Ferrare, R. A.

    2000-01-01

    The Atmospheric Radiation Measurement program's Southern Great Plains Cloud and Radiation Testbed site central facility near Lamont, Oklahoma, offers unique operational water vapor profiling capabilities, including active and passive remote sensors as well as traditional in situ radiosonde measurements. Remote sensing technologies include an automated Raman lidar and an automated Atmospheric Emitted Radiance Interferometer (AERI), which are able to retrieve water vapor profiles operationally through the lower troposphere throughout the diurnal cycle. Comparisons of these two water vapor remote sensing methods to each other and to radiosondes over an 8-month period are presented and discussed, highlighting the accuracy and limitations of each method. Additionally, the AERI is able to retrieve profiles of temperature while the Raman lidar is able to retrieve aerosol extinction profiles operationally. These data, coupled with hourly wind profiles from a 915-MHz wind profiler, provide complete specification of the state of the atmosphere in noncloudy skies. Several case studies illustrate the utility of these high temporal resolution measurements in the characterization of mesoscale features within a 3-day time period in which passage of a dryline, warm air advection, and cold front occurred.

  10. Multiscale Trend Analysis for Pampa Grasslands Using Ground Data and Vegetation Sensor Imagery

    Directory of Open Access Journals (Sweden)

    Fernando C. Scottá

    2015-07-01

    Full Text Available This study aimed to evaluate changes in the aboveground net primary productivity (ANPP of grasslands in the Pampa biome by using experimental plots and changes in the spectral responses of similar vegetation communities obtained by remote sensing and to compare both datasets with meteorological variations to validate the transition scales of the datasets. Two different geographic scales were considered in this study. At the local scale, an analysis of the climate and its direct influences on grassland ANPP was performed using data from a long-term experiment. At the regional scale, the influences of climate on the grassland reflectance patterns were determined using vegetation sensor imagery data. Overall, the monthly variations of vegetation canopy growth analysed using environmental changes (air temperature, total rainfall and total evapotranspiration were similar. The results from the ANPP data and the NDVI data showed the that variations in grassland growth were similar and independent of the analysis scale, which indicated that local data and the relationships of local data with climate can be considered at the regional scale in the Pampa biome by using remote sensing.

  11. Extractive scintillating polymer sensors for trace-level detection of uranium in contaminated ground water

    International Nuclear Information System (INIS)

    Duval, Christine E.; DeVol, Timothy A.; Husson, Scott M.

    2016-01-01

    This contribution describes the synthesis of robust extractive scintillating resin and its use in a flow-cell detector for the direct detection of uranium in environmental waters. The base poly[(4-methyl styrene)-co-(4-vinylbenzyl chloride)-co-(divinylbenzene)-co-(2-(1-napthyl)-4-vinyl-5-phenyloxazole)] resin contains covalently bound fluorophores. Uranium-binding functionality was added to the resin by an Arbuzov reaction followed by hydrolysis via strong acid or trimethylsilyl bromide (TMSBr)-mediated methanolysis. The resin was characterized by Fourier-transform infrared spectroscopy and spectrofluorometry. Fluorophore degradation was observed in the resin hydrolyzed by strong acid, while the resin hydrolyzed by TMSBr-mediated methanolysis maintained luminosity and showed hydrogen bonding-induced Stokes' shift of ∼100 nm. The flow cell detection efficiency for uranium of the TMSBr-mediated methanolysis resin was evaluated at pH 4, 5 and 6 in DI water containing 500 Bq L"−"1 uranium-233 and demonstrated flow cell detection efficiencies of 23%, 16% and 7%. Experiments with pH 4, synthetic groundwater with 50 Bq L"−"1 uranium-233 exhibited a flow cell detection efficiency of 17%. The groundwater measurements show that the resins can concentrate the uranyl cation from waters with high concentrations of competitor ions at near-neutral pH. Findings from this research will lay the groundwork for development of materials for real-time environmental sensing of alpha- and beta-emitting radionuclides. - Highlights: • Extractive scintillating resins synthesized with covalently bound fluor and ligand. • Methylphosphonic acid-derivitized resins characterized for optical properties. • Online detection of uranium in ground water demonstrated at near-neutral pH.

  12. Extractive scintillating polymer sensors for trace-level detection of uranium in contaminated ground water

    Energy Technology Data Exchange (ETDEWEB)

    Duval, Christine E. [Department of Chemical and Biomolecular Engineering, Clemson University, 127 Earle Hall, Clemson, SC 29634 (United States); DeVol, Timothy A. [Department of Environmental Engineering and Earth Sciences, Clemson University, 342 Computer Court, Anderson, SC 29625 (United States); Husson, Scott M., E-mail: shusson@clemson.edu [Department of Chemical and Biomolecular Engineering, Clemson University, 127 Earle Hall, Clemson, SC 29634 (United States)

    2016-12-01

    This contribution describes the synthesis of robust extractive scintillating resin and its use in a flow-cell detector for the direct detection of uranium in environmental waters. The base poly[(4-methyl styrene)-co-(4-vinylbenzyl chloride)-co-(divinylbenzene)-co-(2-(1-napthyl)-4-vinyl-5-phenyloxazole)] resin contains covalently bound fluorophores. Uranium-binding functionality was added to the resin by an Arbuzov reaction followed by hydrolysis via strong acid or trimethylsilyl bromide (TMSBr)-mediated methanolysis. The resin was characterized by Fourier-transform infrared spectroscopy and spectrofluorometry. Fluorophore degradation was observed in the resin hydrolyzed by strong acid, while the resin hydrolyzed by TMSBr-mediated methanolysis maintained luminosity and showed hydrogen bonding-induced Stokes' shift of ∼100 nm. The flow cell detection efficiency for uranium of the TMSBr-mediated methanolysis resin was evaluated at pH 4, 5 and 6 in DI water containing 500 Bq L{sup −1} uranium-233 and demonstrated flow cell detection efficiencies of 23%, 16% and 7%. Experiments with pH 4, synthetic groundwater with 50 Bq L{sup −1} uranium-233 exhibited a flow cell detection efficiency of 17%. The groundwater measurements show that the resins can concentrate the uranyl cation from waters with high concentrations of competitor ions at near-neutral pH. Findings from this research will lay the groundwork for development of materials for real-time environmental sensing of alpha- and beta-emitting radionuclides. - Highlights: • Extractive scintillating resins synthesized with covalently bound fluor and ligand. • Methylphosphonic acid-derivitized resins characterized for optical properties. • Online detection of uranium in ground water demonstrated at near-neutral pH.

  13. Optimal Atmospheric Correction for Above-Ground Forest Biomass Estimation with the ETM+ Remote Sensor.

    Science.gov (United States)

    Nguyen, Hieu Cong; Jung, Jaehoon; Lee, Jungbin; Choi, Sung-Uk; Hong, Suk-Young; Heo, Joon

    2015-07-31

    The reflectance of the Earth's surface is significantly influenced by atmospheric conditions such as water vapor content and aerosols. Particularly, the absorption and scattering effects become stronger when the target features are non-bright objects, such as in aqueous or vegetated areas. For any remote-sensing approach, atmospheric correction is thus required to minimize those effects and to convert digital number (DN) values to surface reflectance. The main aim of this study was to test the three most popular atmospheric correction models, namely (1) Dark Object Subtraction (DOS); (2) Fast Line-of-sight Atmospheric Analysis of Spectral Hypercubes (FLAASH) and (3) the Second Simulation of Satellite Signal in the Solar Spectrum (6S) and compare them with Top of Atmospheric (TOA) reflectance. By using the k-Nearest Neighbor (kNN) algorithm, a series of experiments were conducted for above-ground forest biomass (AGB) estimations of the Gongju and Sejong region of South Korea, in order to check the effectiveness of atmospheric correction methods for Landsat ETM+. Overall, in the forest biomass estimation, the 6S model showed the bestRMSE's, followed by FLAASH, DOS and TOA. In addition, a significant improvement of RMSE by 6S was found with images when the study site had higher total water vapor and temperature levels. Moreover, we also tested the sensitivity of the atmospheric correction methods to each of the Landsat ETM+ bands. The results confirmed that 6S dominates the other methods, especially in the infrared wavelengths covering the pivotal bands for forest applications. Finally, we suggest that the 6S model, integrating water vapor and aerosol optical depth derived from MODIS products, is better suited for AGB estimation based on optical remote-sensing data, especially when using satellite images acquired in the summer during full canopy development.

  14. Complimentary Advanced Fusion Exploration

    National Research Council Canada - National Science Library

    Alford, Mark G; Jones, Eric C; Bubalo, Adnan; Neumann, Melissa; Greer, Michael J

    2005-01-01

    .... The focus areas were in the following regimes: multi-tensor homographic computer vision image fusion, out-of-sequence measurement and track data handling, Nash bargaining approaches to sensor management, pursuit-evasion game theoretic modeling...

  15. Track classification within wireless sensor network

    Science.gov (United States)

    Doumerc, Robin; Pannetier, Benjamin; Moras, Julien; Dezert, Jean; Canevet, Loic

    2017-05-01

    In this paper, we present our study on track classification by taking into account environmental information and target estimated states. The tracker uses several motion model adapted to different target dynamics (pedestrian, ground vehicle and SUAV, i.e. small unmanned aerial vehicle) and works in centralized architecture. The main idea is to explore both: classification given by heterogeneous sensors and classification obtained with our fusion module. The fusion module, presented in his paper, provides a class on each track according to track location, velocity and associated uncertainty. To model the likelihood on each class, a fuzzy approach is used considering constraints on target capability to move in the environment. Then the evidential reasoning approach based on Dempster-Shafer Theory (DST) is used to perform a time integration of this classifier output. The fusion rules are tested and compared on real data obtained with our wireless sensor network.In order to handle realistic ground target tracking scenarios, we use an autonomous smart computer deposited in the surveillance area. After the calibration step of the heterogeneous sensor network, our system is able to handle real data from a wireless ground sensor network. The performance of this system is evaluated in a real exercise for intelligence operation ("hunter hunt" scenario).

  16. A Novel Energy-Efficient Multi-Sensor Fusion Wake-Up Control Strategy Based on a Biomimetic Infectious-Immune Mechanism for Target Tracking.

    Science.gov (United States)

    Zhou, Jie; Liang, Yan; Shen, Qiang; Feng, Xiaoxue; Pan, Quan

    2018-04-18

    A biomimetic distributed infection-immunity model (BDIIM), inspired by the immune mechanism of an infected organism, is proposed in order to achieve a high-efficiency wake-up control strategy based on multi-sensor fusion for target tracking. The resultant BDIIM consists of six sub-processes reflecting the infection-immunity mechanism: occurrence probabilities of direct-infection (DI) and cross-infection (CI), immunity/immune-deficiency of DI and CI, pathogen amount of DI and CI, immune cell production, immune memory, and pathogen accumulation under immunity state. Furthermore, a corresponding relationship between the BDIIM and sensor wake-up control is established to form the collaborative wake-up method. Finally, joint surveillance and target tracking are formulated in the simulation, in which we show that the energy cost and position tracking error are reduced to 50.8% and 78.9%, respectively. Effectiveness of the proposed BDIIM algorithm is shown, and this model is expected to have a significant role in guiding the performance improvement of multi-sensor networks.

  17. Spatial resolution enhancement of satellite image data using fusion approach

    Science.gov (United States)

    Lestiana, H.; Sukristiyanti

    2018-02-01

    Object identification using remote sensing data has a problem when the spatial resolution is not in accordance with the object. The fusion approach is one of methods to solve the problem, to improve the object recognition and to increase the objects information by combining data from multiple sensors. The application of fusion image can be used to estimate the environmental component that is needed to monitor in multiple views, such as evapotranspiration estimation, 3D ground-based characterisation, smart city application, urban environments, terrestrial mapping, and water vegetation. Based on fusion application method, the visible object in land area has been easily recognized using the method. The variety of object information in land area has increased the variation of environmental component estimation. The difficulties in recognizing the invisible object like Submarine Groundwater Discharge (SGD), especially in tropical area, might be decreased by the fusion method. The less variation of the object in the sea surface temperature is a challenge to be solved.

  18. A Geostatistical Data Fusion Technique for Merging Remote Sensing and Ground-Based Observations of Aerosol Optical Thickness

    Science.gov (United States)

    Chatterjee, Abhishek; Michalak, Anna M.; Kahn, Ralph A.; Paradise, Susan R.; Braverman, Amy J.; Miller, Charles E.

    2010-01-01

    Particles in the atmosphere reflect incoming sunlight, tending to cool the Earth below. Some particles, such as soot, also absorb sunlight, which tens to warm the ambient atmosphere. Aerosol optical depth (AOD) is a measure of the amount of particulate matter in the atmosphere, and is a key input to computer models that simulate and predict Earth's changing climate. The global AOD products from the Multi-angle Imaging SpectroRadiometer (MISR) and the MODerate resolution Imaging Spectroradiometer (MODIS), both of which fly on the NASA Earth Observing System's Terra satellite, provide complementary views of the particles in the atmosphere. Whereas MODIS offers global coverage about four times as frequent as MISR, the multi-angle data makes it possible to separate the surface and atmospheric contributions to the observed top-of-atmosphere radiances, and also to more effectively discriminate particle type. Surface-based AERONET sun photometers retrieve AOD with smaller uncertainties than the satellite instruments, but only at a few fixed locations. So there are clear reasons to combine these data sets in a way that takes advantage of their respective strengths. This paper represents an effort at combining MISR, MODIS and AERONET AOD products over the continental US, using a common spatial statistical technique called kriging. The technique uses the correlation between the satellite data and the "ground-truth" sun photometer observations to assign uncertainty to the satellite data on a region-by-region basis. The larger fraction of the sun photometer variance that is duplicated by the satellite data, the higher the confidence assigned to the satellite data in that region. In the Western and Central US, MISR AOD correlation with AERONET are significantly higher than those with MODIS, likely due to bright surfaces in these regions, which pose greater challenges for the single-view MODIS retrievals. In the east, MODIS correlations are higher, due to more frequent sampling

  19. SAR and LIDAR fusion: experiments and applications

    Science.gov (United States)

    Edwards, Matthew C.; Zaugg, Evan C.; Bradley, Joshua P.; Bowden, Ryan D.

    2013-05-01

    In recent years ARTEMIS, Inc. has developed a series of compact, versatile Synthetic Aperture Radar (SAR) systems which have been operated on a variety of small manned and unmanned aircraft. The multi-frequency-band SlimSAR has demonstrated a variety of capabilities including maritime and littoral target detection, ground moving target indication, polarimetry, interferometry, change detection, and foliage penetration. ARTEMIS also continues to build upon the radar's capabilities through fusion with other sensors, such as electro-optical and infrared camera gimbals and light detection and ranging (LIDAR) devices. In this paper we focus on experiments and applications employing SAR and LIDAR fusion. LIDAR is similar to radar in that it transmits a signal which, after being reflected or scattered by a target area, is recorded by the sensor. The differences are that a LIDAR uses a laser as a transmitter and optical sensors as a receiver, and the wavelengths used exhibit a very different scattering phenomenology than the microwaves used in radar, making SAR and LIDAR good complementary technologies. LIDAR is used in many applications including agriculture, archeology, geo-science, and surveying. Some typical data products include digital elevation maps of a target area and features and shapes extracted from the data. A set of experiments conducted to demonstrate the fusion of SAR and LIDAR data include a LIDAR DEM used in accurately processing the SAR data of a high relief area (mountainous, urban). Also, feature extraction is used in improving geolocation accuracy of the SAR and LIDAR data.

  20. Sensor

    OpenAIRE

    Gleeson, Helen; Dierking, Ingo; Grieve, Bruce; Woodyatt, Christopher; Brimicombe, Paul

    2015-01-01

    An electrical temperature sensor (10) comprises a liquid crystalline material (12). First and second electrically conductive contacts (14), (16), having a spaced relationship there between, contact the liquid crystalline material (12). An electric property measuring device is electrically connected to the first and second contacts (14), (16) and is arranged to measure an electric property of the liquid crystalline material (12). The liquid crystalline material (12) has a transition temperatur...

  1. Accurate 3D Positioning for a Mobile Platform in Non-Line-of-Sight Scenarios Based on IMU/Magnetometer Sensor Fusion.

    Science.gov (United States)

    Hellmers, Hendrik; Kasmi, Zakaria; Norrdine, Abdelmoumen; Eichhorn, Andreas

    2018-01-04

    In recent years, a variety of real-time applications benefit from services provided by localization systems due to the advent of sensing and communication technologies. Since the Global Navigation Satellite System (GNSS) enables localization only outside buildings, applications for indoor positioning and navigation use alternative technologies. Ultra Wide Band Signals (UWB), Wireless Local Area Network (WLAN), ultrasonic or infrared are common examples. However, these technologies suffer from fading and multipath effects caused by objects and materials in the building. In contrast, magnetic fields are able to pass through obstacles without significant propagation errors, i.e. in Non-Line of Sight Scenarios (NLoS). The aim of this work is to propose a novel indoor positioning system based on artificially generated magnetic fields in combination with Inertial Measurement Units (IMUs). In order to reach a better coverage, multiple coils are used as reference points. A basic algorithm for three-dimensional applications is demonstrated as well as evaluated in this article. The established system is then realized by a sensor fusion principle as well as a kinematic motion model on the basis of a Kalman filter. Furthermore, a pressure sensor is used in combination with an adaptive filtering method to reliably estimate the platform's altitude.

  2. Pragmatic data fusion uncertainty concerns: Tribute to Dave L. Hall

    CSIR Research Space (South Africa)

    Blasch, E

    2016-07-01

    Full Text Available Over the course of Dave Hall's career, he highlighted various concerns associated with the implementation of data fusion methods. Many of the issues included the role of uncertainty in data fusion, practical implementation of sensor fusion systems...

  3. A Robust Vehicle Localization Approach Based on GNSS/IMU/DMI/LiDAR Sensor Fusion for Autonomous Vehicles.

    Science.gov (United States)

    Meng, Xiaoli; Wang, Heng; Liu, Bingbing

    2017-09-18

    Precise and robust localization in a large-scale outdoor environment is essential for an autonomous vehicle. In order to improve the performance of the fusion of GNSS (Global Navigation Satellite System)/IMU (Inertial Measurement Unit)/DMI (Distance-Measuring Instruments), a multi-constraint fault detection approach is proposed to smooth the vehicle locations in spite of GNSS jumps. Furthermore, the lateral localization error is compensated by the point cloud-based lateral localization method proposed in this paper. Experiment results have verified the algorithms proposed in this paper, which shows that the algorithms proposed in this paper are capable of providing precise and robust vehicle localization.

  4. A Robust Vehicle Localization Approach Based on GNSS/IMU/DMI/LiDAR Sensor Fusion for Autonomous Vehicles

    Directory of Open Access Journals (Sweden)

    Xiaoli Meng

    2017-09-01

    Full Text Available Precise and robust localization in a large-scale outdoor environment is essential for an autonomous vehicle. In order to improve the performance of the fusion of GNSS (Global Navigation Satellite System/IMU (Inertial Measurement Unit/DMI (Distance-Measuring Instruments, a multi-constraint fault detection approach is proposed to smooth the vehicle locations in spite of GNSS jumps. Furthermore, the lateral localization error is compensated by the point cloud-based lateral localization method proposed in this paper. Experiment results have verified the algorithms proposed in this paper, which shows that the algorithms proposed in this paper are capable of providing precise and robust vehicle localization.

  5. Technical Description of Radar and Optical Sensors Contributing to Joint UK-Australian Satellite Tracking, Data-fusion and Cueing Experiment

    Science.gov (United States)

    Eastment, J.; Ladd, D.; Donnelly, P.; Ash, A.; Harwood, N.; Ritchie, I.; Smith, C.; Bennett, J.; Rutten, M.; Gordon, N.

    2014-09-01

    DSTL, DSTO, EOS and STFC have recently participated in a campaign of co-ordinated observations with both radar and optical sensors in order to demonstrate and to refine methodologies for orbit determination, data fusion and cross-sensor cueing. The experimental programme is described in detail in the companion paper by Harwood et al. At the STFC Chilbolton Observatory in Southern England, an S-band radar on a 25 m diameter fully-steerable dish antenna was used to measure object range and radar cross-section. At the EOS Space Systems facility on Mount Stromlo, near Canberra, Australia, an optical system comprising a 2 m alt / az observatory, with Coude path laser tracking at 400W power, was used to acquire, lock and laser track the cued objects, providing accurate orbit determinations for each. DSTO, located at Edinburgh, Australia, operated an optical system consisting of a small commercial telescope and mount, measuring the direction to the objects. Observation times were limited to the evening solar terminator period. Data from these systems was processed independently, using DSTL-developed and DSTO / EOS-developed algorithms, to perform orbit determination and to cross-cue: (i) the radar, based on the optical measurements; (ii) the optical system, based on the radar measurements; and (iii) the radar, using its own prior observations (self-cueing). In some cases, TLEs were used to initialise the orbit determination process; in other cases, the cues were derived entirely from sensor data. In all 3 scenarios, positive results were obtained for a variety of satellites in low earth orbits, demonstrating the feasibility of the different cue generation techniques. The purpose of this paper is to describe the technical characteristics of the radar and optical systems used, the modes of operation employed to acquire the observations, and details of the parameters measured and the data formats.

  6. Optimizing placements of ground-based snow sensors for areal snow cover estimation using a machine-learning algorithm and melt-season snow-LiDAR data

    Science.gov (United States)

    Oroza, C.; Zheng, Z.; Glaser, S. D.; Bales, R. C.; Conklin, M. H.

    2016-12-01

    We present a structured, analytical approach to optimize ground-sensor placements based on time-series remotely sensed (LiDAR) data and machine-learning algorithms. We focused on catchments within the Merced and Tuolumne river basins, covered by the JPL Airborne Snow Observatory LiDAR program. First, we used a Gaussian mixture model to identify representative sensor locations in the space of independent variables for each catchment. Multiple independent variables that govern the distribution of snow depth were used, including elevation, slope, and aspect. Second, we used a Gaussian process to estimate the areal distribution of snow depth from the initial set of measurements. This is a covariance-based model that also estimates the areal distribution of model uncertainty based on the independent variable weights and autocorrelation. The uncertainty raster was used to strategically add sensors to minimize model uncertainty. We assessed the temporal accuracy of the method using LiDAR-derived snow-depth rasters collected in water-year 2014. In each area, optimal sensor placements were determined using the first available snow raster for the year. The accuracy in the remaining LiDAR surveys was compared to 100 configurations of sensors selected at random. We found the accuracy of the model from the proposed placements to be higher and more consistent in each remaining survey than the average random configuration. We found that a relatively small number of sensors can be used to accurately reproduce the spatial patterns of snow depth across the basins, when placed using spatial snow data. Our approach also simplifies sensor placement. At present, field surveys are required to identify representative locations for such networks, a process that is labor intensive and provides limited guarantees on the networks' representation of catchment independent variables.

  7. Sensor Fusion of a Mobile Device to Control and Acquire Videos or Images of Coffee Branches and for Georeferencing Trees

    OpenAIRE

    Ramos Giraldo, Paula Jimena; Guerrero Aguirre, ?lvaro; Mu?oz, Carlos Mario; Prieto, Flavio Augusto; Oliveros, Carlos Eugenio

    2017-01-01

    Smartphones show potential for controlling and monitoring variables in agriculture. Their processing capacity, instrumentation, connectivity, low cost, and accessibility allow farmers (among other users in rural areas) to operate them easily with applications adjusted to their specific needs. In this investigation, the integration of inertial sensors, a GPS, and a camera are presented for the monitoring of a coffee crop. An Android-based application was developed with two operating modes: (i)...

  8. Wild life passer species recognition from a technical passage through data fusion of a wireless sensor network

    Science.gov (United States)

    Gazis, A.; Katsiri, E.

    2017-09-01

    This paper presents a Wireless Sensor Network (WSN) system which was created as a project about protecting wildlife using sensor networks following the assistance of the department of Electrical and Computer Engineering of the Democritus University of Thrace. An automated process was implemented, regarding the recognition of a passenger (ie human, wolf, bear, etc.) traversing a box-shaped underground passage, such as the ones located along main highways fusing Width, Height and Weight values. These were measured using low-cost distance (beam) and weight (S-type load) micro-sensors and stored in a central repository. Moreover, the information provided by the WSN was analyzed, via a variety of methods including a neural pattern recognition network as well as clustering algorithms, which were able to recognize the kind of passenger, with certainty scores over 90%. The main concern, regarding the future, is the evaluation of these passages in respect to their effectiveness, i.e. whether they are frequently utilized by animals. This information was further analysed by appropriate information systems, in order to provide insights about the effectiveness of such mitigation structures.

  9. A multi-resolution approach for an automated fusion of different low-cost 3D sensors.

    Science.gov (United States)

    Dupuis, Jan; Paulus, Stefan; Behmann, Jan; Plümer, Lutz; Kuhlmann, Heiner

    2014-04-24

    The 3D acquisition of object structures has become a common technique in many fields of work, e.g., industrial quality management, cultural heritage or crime scene documentation. The requirements on the measuring devices are versatile, because spacious scenes have to be imaged with a high level of detail for selected objects. Thus, the used measuring systems are expensive and require an experienced operator. With the rise of low-cost 3D imaging systems, their integration into the digital documentation process is possible. However, common low-cost sensors have the limitation of a trade-off between range and accuracy, providing either a low resolution of single objects or a limited imaging field. Therefore, the use of multiple sensors is desirable. We show the combined use of two low-cost sensors, the Microsoft Kinect and the David laserscanning system, to achieve low-resolved scans of the whole scene and a high level of detail for selected objects, respectively. Afterwards, the high-resolved David objects are automatically assigned to their corresponding Kinect object by the use of surface feature histograms and SVM-classification. The corresponding objects are fitted using an ICP-implementation to produce a multi-resolution map. The applicability is shown for a fictional crime scene and the reconstruction of a ballistic trajectory.

  10. A small, lightweight multipollutant sensor system for ground-mobile and aerial emission sampling from open area sources

    Science.gov (United States)

    Characterizing highly dynamic, transient, and vertically lofted emissions from open area sources poses unique measurement challenges. This study developed and applied a multipollutant sensor and integrated sampler system for use on mobile applications including tethered balloons ...

  11. Field Demonstration of the Ground to Space Laser Calibration: Illumination of NASA’s Earth Observing Sensors

    Data.gov (United States)

    National Aeronautics and Space Administration — We will capitalize on a NASA-NIST partnership to conduct a test illumination of an existing radiometric sensor on orbit. This preliminary demonstration would target...

  12. A Sensor Data Fusion System Based on k-Nearest Neighbor Pattern Classification for Structural Health Monitoring Applications

    Directory of Open Access Journals (Sweden)

    Jaime Vitola

    2017-02-01

    Full Text Available Civil and military structures are susceptible and vulnerable to damage due to the environmental and operational conditions. Therefore, the implementation of technology to provide robust solutions in damage identification (by using signals acquired directly from the structure is a requirement to reduce operational and maintenance costs. In this sense, the use of sensors permanently attached to the structures has demonstrated a great versatility and benefit since the inspection system can be automated. This automation is carried out with signal processing tasks with the aim of a pattern recognition analysis. This work presents the detailed description of a structural health monitoring (SHM system based on the use of a piezoelectric (PZT active system. The SHM system includes: (i the use of a piezoelectric sensor network to excite the structure and collect the measured dynamic response, in several actuation phases; (ii data organization; (iii advanced signal processing techniques to define the feature vectors; and finally; (iv the nearest neighbor algorithm as a machine learning approach to classify different kinds of damage. A description of the experimental setup, the experimental validation and a discussion of the results from two different structures are included and analyzed.

  13. Sensor Fusion of a Mobile Device to Control and Acquire Videos or Images of Coffee Branches and for Georeferencing Trees

    Directory of Open Access Journals (Sweden)

    Paula Jimena Ramos Giraldo

    2017-04-01

    Full Text Available Smartphones show potential for controlling and monitoring variables in agriculture. Their processing capacity, instrumentation, connectivity, low cost, and accessibility allow farmers (among other users in rural areas to operate them easily with applications adjusted to their specific needs. In this investigation, the integration of inertial sensors, a GPS, and a camera are presented for the monitoring of a coffee crop. An Android-based application was developed with two operating modes: (i Navigation: for georeferencing trees, which can be as close as 0.5 m from each other; and (ii Acquisition: control of video acquisition, based on the movement of the mobile device over a branch, and measurement of image quality, using clarity indexes to select the most appropriate frames for application in future processes. The integration of inertial sensors in navigation mode, shows a mean relative error of ±0.15 m, and total error ±5.15 m. In acquisition mode, the system correctly identifies the beginning and end of mobile phone movement in 99% of cases, and image quality is determined by means of a sharpness factor which measures blurriness. With the developed system, it will be possible to obtain georeferenced information about coffee trees, such as their production, nutritional state, and presence of plagues or diseases.

  14. Sensor Fusion of a Mobile Device to Control and Acquire Videos or Images of Coffee Branches and for Georeferencing Trees.

    Science.gov (United States)

    Giraldo, Paula Jimena Ramos; Aguirre, Álvaro Guerrero; Muñoz, Carlos Mario; Prieto, Flavio Augusto; Oliveros, Carlos Eugenio

    2017-04-06

    Smartphones show potential for controlling and monitoring variables in agriculture. Their processing capacity, instrumentation, connectivity, low cost, and accessibility allow farmers (among other users in rural areas) to operate them easily with applications adjusted to their specific needs. In this investigation, the integration of inertial sensors, a GPS, and a camera are presented for the monitoring of a coffee crop. An Android-based application was developed with two operating modes: ( i ) Navigation: for georeferencing trees, which can be as close as 0.5 m from each other; and ( ii ) Acquisition: control of video acquisition, based on the movement of the mobile device over a branch, and measurement of image quality, using clarity indexes to select the most appropriate frames for application in future processes. The integration of inertial sensors in navigation mode, shows a mean relative error of ±0.15 m, and total error ±5.15 m. In acquisition mode, the system correctly identifies the beginning and end of mobile phone movement in 99% of cases, and image quality is determined by means of a sharpness factor which measures blurriness. With the developed system, it will be possible to obtain georeferenced information about coffee trees, such as their production, nutritional state, and presence of plagues or diseases.

  15. Terrain Commander: Unattended Ground-Based Surveillance System

    National Research Council Canada - National Science Library

    Steadman, Bob

    2000-01-01

    .... Terrain Commander OASIS provides next generation target detection, classification, and tracking through smart sensor fusion of beamforming acoustic, seismic, passive infrared, and magnetic sensors...

  16. Multi-sensors acquisition, data fusion, knowledge mining and alarm triggering in health smart homes for elderly people.

    Science.gov (United States)

    Demongeot, Jacques; Virone, Gilles; Duchêne, Florence; Benchetrit, Gila; Hervé, Thierry; Noury, Norbert; Rialle, Vincent

    2002-06-01

    We deal in this paper with the concept of health smart home (HSH) designed to follow dependent people at home in order to avoid the hospitalisation, limiting hospital sojourns to short acute care or fast specific diagnostic investigations. For elderly people the project of such a HSH has been called AISLE (Apartment with Intelligent Sensors for Longevity Effectiveness). For this purpose, system having three levels of automatic measuring (1) the circadian activity, (2) the vegetative state, and (3) some state variables specific of certain organs involved in precise diseases, has been developed within the framework of a 'Health Integrated Smart Home Information System' (HIS2). HIS2 is an experimental platform for technologic development and clinical evaluation, in order to ensure the medical security and quality of life for patients who need home based medical monitoring. Location sensors are placed in each room of the HIS2, allowing the monitoring of patient's successive daily activity phases within the patient's home environment. We proceed with a sampling in an hourly schedule to detect weak variations of the nycthemeral rhythms. Based on numerous measurements, we establish a mean value with confidence limits of activity variables in normal behaviour permitting to detect for example a sudden abnormal event (like a fall) as well as a chronic pathologic activity (like a pollakiuria), allowing us to define a canonical domain within which the patient's activity is qualified to be 'predictable'. Alerts are set off if the patient's activity deviates from a predictable canonical domain. Moreover, we can follow the cardio-respiratory state by measuring the intensity of the respiratory sinusal arrhythmia in order to quantify the integrity of the bulbar vegetative system, and we finally propose to carefully watch abnormal symptoms like arterial pressure or presence of plasma proteins in the expired air flow for early detecting respectively hypertension or pulmonary oedema.

  17. Remote sensing image fusion

    CERN Document Server

    Alparone, Luciano; Baronti, Stefano; Garzelli, Andrea

    2015-01-01

    A synthesis of more than ten years of experience, Remote Sensing Image Fusion covers methods specifically designed for remote sensing imagery. The authors supply a comprehensive classification system and rigorous mathematical description of advanced and state-of-the-art methods for pansharpening of multispectral images, fusion of hyperspectral and panchromatic images, and fusion of data from heterogeneous sensors such as optical and synthetic aperture radar (SAR) images and integration of thermal and visible/near-infrared images. They also explore new trends of signal/image processing, such as

  18. A Leader-path-following formation system for AGVs with multi-sensor data fusion based vehicle tracking

    Science.gov (United States)

    Yao, Wen; Zhao, Xijun; Yu, Yufeng; Fang, Yongkun; Wang, Chao; Yang, Tianfu

    2017-09-01

    Caravans composed of vehicles with different functionality or trafficability raise the demand that formation system structure shall allow vehicles to deviate from the path to be followed when necessary. In this paper, a formation system is developed for autonomous ground vehicles (AGVs) who follow the path of a leader vehicle while retaining the ability of deviation from the reference path. In addition, it improves robustness of preceding vehicle localization by fusing Lidar tracking, camera tracking results with predecessor’s global position within an extended Kalman filter (EKF) in case that one or more sources of preceding vehicle localization is not reliable. The system is applied on real AGV platforms and won the 3rd place in an AGV competition in China.

  19. Fusion energy

    International Nuclear Information System (INIS)

    Gross, R.A.

    1984-01-01

    This textbook covers the physics and technology upon which future fusion power reactors will be based. It reviews the history of fusion, reaction physics, plasma physics, heating, and confinement. Descriptions of commercial plants and design concepts are included. Topics covered include: fusion reactions and fuel resources; reaction rates; ignition, and confinement; basic plasma directory; Tokamak confinement physics; fusion technology; STARFIRE: A commercial Tokamak fusion power plant. MARS: A tandem-mirror fusion power plant; and other fusion reactor concepts

  20. Ground Monitoring Neotropical Dry Forests: A Sensor Network for Forest and Microclimate Dynamics in Semi-Arid Environments (Enviro-Net°)

    Science.gov (United States)

    Rankine, C. J.; Sánchez-Azofeifa, G.

    2011-12-01

    In the face of unprecedented global change driven by anthropogenic pressure on natural systems it has become imperative to monitor and better understand potential shifts in ecosystem functioning and services from local to global scales. The utilization of automated sensors technologies offers numerous advantages over traditional on-site ecosystem surveying techniques and, as a result, sensor networks are becoming a powerful tool in environmental monitoring programs. Tropical forests, renowned for their biodiversity, are important regulators of land-atmosphere fluxes yet the seasonally dry tropical forests, which account for 40% of forested ecosystems in the American tropics, have been severely degraded over the past several decades and not much is known of their capacity to recover. With less than 1% of these forests protected, our ability to monitor the dynamics and quantify changes in the remaining primary and recovering secondary tropical dry forests is vital to understanding mechanisms of ecosystem stress responses and climate feedback with respect to annual productivity and desertification processes in the tropics. The remote sensing component of the Tropi-Dry: Human and Biophysical Dimensions of Tropical Dry Forests in the Americas research network supports a network of long-term tropical ecosystem monitoring platforms which focus on the dynamics of seasonally dry tropical forests in the Americas. With over 25 sensor station deployments operating across a latitudinal gradient in Mexico, Costa Rica, Brazil, and Argentina continuously collecting hyper-temporal sensory input based on standardized deployment parameters, this monitoring system is unique among tropical environments. Technologies used in the network include optical canopy phenology towers, understory wireless sensing networks, above and below ground microclimate stations, and digital cameras. Sensory data streams are uploaded to a cyber-infrastructure initiative, denominated Enviro-Net°, for data

  1. Detection of premature browning in ground beef with an integrated optical-fibre based sensor using reflection spectroscopy and fibre Bragg grating technology

    International Nuclear Information System (INIS)

    O'Farrell, M; Sheridan, C; Lewis, E

    2007-01-01

    This paper reports on an optical fibre based sensor system to detect the occurrence of premature browning in ground beef. Premature browning (PMB) occurs when, at a temperature below the pasteurisation temperature of 71 deg. C, there are no traces of pink meat left in the patty. PMB is more frequent if poorer quality beef or beef that has been stored under imperfect conditions. The experimental work pertaining to this paper involved cooking fresh meat and meat that has been stored in a freezer for, 1 week, 1 month and 3 months and recording the reflected spectra and temperature at the core of the product, during the cooking process, in order to develop a classifier based on the spectral response and using a Self-Organising Map (SOM) to classify the patties into one of four categories, based on their colour. Further tests were also carried out on developing an all-optical fibre sensor for measuring both the temperature and colour in a single integrated probe. The integrated probe contains two different sensor concepts, one to monitor temperature, based on Fibre Bragg Grating (FBG) technology and a second for meat quality, based on reflection spectroscopy in the visible wavelength range

  2. Escape and evade control policies for ensuring the physical security of nonholonomic, ground-based, unattended mobile sensor nodes

    Science.gov (United States)

    Mascarenas, David; Stull, Christopher; Farrar, Charles

    2011-06-01

    In order to realize the wide-scale deployment of high-endurance, unattended mobile sensing technologies, it is vital to ensure the self-preservation of the sensing assets. Deployed mobile sensor nodes face a variety of physical security threats including theft, vandalism and physical damage. Unattended mobile sensor nodes must be able to respond to these threats with control policies that facilitate escape and evasion to a low-risk state. In this work the Precision Immobilization Technique (PIT) problem has been considered. The PIT maneuver is a technique that a pursuing, car-like vehicle can use to force a fleeing vehicle to abruptly turn ninety degrees to the direction of travel. The abrupt change in direction generally causes the fleeing driver to lose control and stop. The PIT maneuver was originally developed by law enforcement to end vehicular pursuits in a manner that minimizes damage to the persons and property involved. It is easy to imagine that unattended autonomous convoys could be targets of this type of action by adversarial agents. This effort focused on developing control policies unattended mobile sensor nodes could employ to escape, evade and recover from PIT-maneuver-like attacks. The development of these control policies involved both simulation as well as small-scale experimental testing. The goal of this work is to be a step toward ensuring the physical security of unattended sensor node assets.

  3. TOPOGRAPHIC LOCAL ROUGHNESS EXTRACTION AND CALIBRATION OVER MARTIAN SURFACE BY VERY HIGH RESOLUTION STEREO ANALYSIS AND MULTI SENSOR DATA FUSION

    Directory of Open Access Journals (Sweden)

    J. R. Kim

    2012-08-01

    Full Text Available The planetary topography has been the main focus of the in-orbital remote sensing. In spite of the recent development in active and passive sensing technologies to reconstruct three dimensional planetary topography, the resolution limit of range measurement is theoretically and practically obvious. Therefore, the extraction of inner topographical height variation within a measurement spot is very challengeable and beneficial topic for the many application fields such as the identification of landform, Aeolian process analysis and the risk assessment of planetary lander. In this study we tried to extract the topographic height variation over martian surface so called local roughness with different approaches. One method is the employment of laser beam broadening effect and the other is the multi angle optical imaging. Especially, in both cases, the precise pre processing employing high accuracy DTM (Digital Terrain Model were introduced to minimise the possible errors. Since a processing routine to extract very high resolution DTMs up to 0.5–4m grid-spacing from HiRISE (High Resolution Imaging Science Experiment and 20–10m DTM from CTX (Context Camera stereo pair has been developed, it is now possible to calibrate the local roughness compared with the calculated height variation from very high resolution topographic products. Three testing areas were chosen and processed to extract local roughness with the co-registered multi sensor data sets. Even though, the extracted local roughness products are still showing the strong correlation with the topographic slopes, we demonstrated the potentials of the height variations extraction and calibration methods.

  4. Downscaling soil moisture over East Asia through multi-sensor data fusion and optimization of regression trees

    Science.gov (United States)

    Park, Seonyoung; Im, Jungho; Park, Sumin; Rhee, Jinyoung

    2017-04-01

    optimization based on pruning of rules derived from the modified regression trees was conducted. Root Mean Square Error (RMSE) and Correlation coefficients (r) were used to optimize the rules, and finally 59 rules from modified regression trees were produced. The results show high validation r (0.79) and low validation RMSE (0.0556m3/m3). The 1 km downscaled soil moisture was evaluated using ground soil moisture data at 14 stations, and both soil moisture data showed similar temporal patterns (average r=0.51 and average RMSE=0.041). The spatial distribution of the 1 km downscaled soil moisture well corresponded with GLDAS soil moisture that caught both extremely dry and wet regions. Correlation between GLDAS and the 1 km downscaled soil moisture during growing season was positive (mean r=0.35) in most regions.

  5. WE-EF-207-04: An Inter-Projection Sensor Fusion (IPSF) Approach to Estimate Missing Projection Signal in Synchronized Moving Grid (SMOG) System

    International Nuclear Information System (INIS)

    Zhang, H; Kong, V; Jin, J; Ren, L; Zhang, Y; Giles, W

    2015-01-01

    Purpose: A synchronized moving grid (SMOG) has been proposed to reduce scatter and lag artifacts in cone beam computed tomography (CBCT). However, information is missing in each projection because certain areas are blocked by the grid. A previous solution to this issue is acquiring 2 complimentary projections at each position, which increases scanning time. This study reports our first Result using an inter-projection sensor fusion (IPSF) method to estimate missing projection in our prototype SMOG-based CBCT system. Methods: An in-house SMOG assembling with a 1:1 grid of 3 mm gap has been installed in a CBCT benchtop. The grid moves back and forth in a 3-mm amplitude and up-to 20-Hz frequency. A control program in LabView synchronizes the grid motion with the platform rotation and x-ray firing so that the grid patterns for any two neighboring projections are complimentary. A Catphan was scanned with 360 projections. After scatter correction, the IPSF algorithm was applied to estimate missing signal for each projection using the information from the 2 neighboring projections. Feldkamp-Davis-Kress (FDK) algorithm was applied to reconstruct CBCT images. The CBCTs were compared to those reconstructed using normal projections without applying the SMOG system. Results: The SMOG-IPSF method may reduce image dose by half due to the blocked radiation by the grid. The method almost completely removed scatter related artifacts, such as the cupping artifacts. The evaluation of line pair patterns in the CatPhan suggested that the spatial resolution degradation was minimal. Conclusion: The SMOG-IPSF is promising in reducing scatter artifacts and improving image quality while reducing radiation dose

  6. WE-EF-207-08: Improve Cone Beam CT Using a Synchronized Moving Grid, An Inter-Projection Sensor Fusion and a Probability Total Variation Reconstruction

    Energy Technology Data Exchange (ETDEWEB)

    Zhang, H; Kong, V; Jin, J [Georgia Regents University Cancer Center, Augusta, GA (Georgia); Ren, L; Zhang, Y; Giles, W [Duke University Medical Center, Durham, NC (United States)

    2015-06-15

    Purpose: To present a cone beam computed tomography (CBCT) system, which uses a synchronized moving grid (SMOG) to reduce and correct scatter, an inter-projection sensor fusion (IPSF) algorithm to estimate the missing information blocked by the grid, and a probability total variation (pTV) algorithm to reconstruct the CBCT image. Methods: A prototype SMOG-equipped CBCT system was developed, and was used to acquire gridded projections with complimentary grid patterns in two neighboring projections. Scatter was reduced by the grid, and the remaining scatter was corrected by measuring it under the grid. An IPSF algorithm was used to estimate the missing information in a projection from data in its 2 neighboring projections. Feldkamp-Davis-Kress (FDK) algorithm was used to reconstruct the initial CBCT image using projections after IPSF processing for pTV. A probability map was generated depending on the confidence of estimation in IPSF for the regions of missing data and penumbra. pTV was finally used to reconstruct the CBCT image for a Catphan, and was compared to conventional CBCT image without using SMOG, images without using IPSF (SMOG + FDK and SMOG + mask-TV), and image without using pTV (SMOG + IPSF + FDK). Results: The conventional CBCT without using SMOG shows apparent scatter-induced cup artifacts. The approaches with SMOG but without IPSF show severe (SMOG + FDK) or additional (SMOG + TV) artifacts, possibly due to using projections of missing data. The 2 approaches with SMOG + IPSF removes the cup artifacts, and the pTV approach is superior than the FDK by substantially reducing the noise. Using the SMOG also reduces half of the imaging dose. Conclusion: The proposed technique is promising in improving CBCT image quality while reducing imaging dose.

  7. WE-EF-207-04: An Inter-Projection Sensor Fusion (IPSF) Approach to Estimate Missing Projection Signal in Synchronized Moving Grid (SMOG) System

    Energy Technology Data Exchange (ETDEWEB)

    Zhang, H; Kong, V; Jin, J [Georgia Regents University Cancer Center, Augusta, GA (Georgia); Ren, L; Zhang, Y; Giles, W [Duke University Medical Center, Durham, NC (United States)

    2015-06-15

    Purpose: A synchronized moving grid (SMOG) has been proposed to reduce scatter and lag artifacts in cone beam computed tomography (CBCT). However, information is missing in each projection because certain areas are blocked by the grid. A previous solution to this issue is acquiring 2 complimentary projections at each position, which increases scanning time. This study reports our first Result using an inter-projection sensor fusion (IPSF) method to estimate missing projection in our prototype SMOG-based CBCT system. Methods: An in-house SMOG assembling with a 1:1 grid of 3 mm gap has been installed in a CBCT benchtop. The grid moves back and forth in a 3-mm amplitude and up-to 20-Hz frequency. A control program in LabView synchronizes the grid motion with the platform rotation and x-ray firing so that the grid patterns for any two neighboring projections are complimentary. A Catphan was scanned with 360 projections. After scatter correction, the IPSF algorithm was applied to estimate missing signal for each projection using the information from the 2 neighboring projections. Feldkamp-Davis-Kress (FDK) algorithm was applied to reconstruct CBCT images. The CBCTs were compared to those reconstructed using normal projections without applying the SMOG system. Results: The SMOG-IPSF method may reduce image dose by half due to the blocked radiation by the grid. The method almost completely removed scatter related artifacts, such as the cupping artifacts. The evaluation of line pair patterns in the CatPhan suggested that the spatial resolution degradation was minimal. Conclusion: The SMOG-IPSF is promising in reducing scatter artifacts and improving image quality while reducing radiation dose.

  8. WE-EF-207-08: Improve Cone Beam CT Using a Synchronized Moving Grid, An Inter-Projection Sensor Fusion and a Probability Total Variation Reconstruction

    International Nuclear Information System (INIS)

    Zhang, H; Kong, V; Jin, J; Ren, L; Zhang, Y; Giles, W

    2015-01-01

    Purpose: To present a cone beam computed tomography (CBCT) system, which uses a synchronized moving grid (SMOG) to reduce and correct scatter, an inter-projection sensor fusion (IPSF) algorithm to estimate the missing information blocked by the grid, and a probability total variation (pTV) algorithm to reconstruct the CBCT image. Methods: A prototype SMOG-equipped CBCT system was developed, and was used to acquire gridded projections with complimentary grid patterns in two neighboring projections. Scatter was reduced by the grid, and the remaining scatter was corrected by measuring it under the grid. An IPSF algorithm was used to estimate the missing information in a projection from data in its 2 neighboring projections. Feldkamp-Davis-Kress (FDK) algorithm was used to reconstruct the initial CBCT image using projections after IPSF processing for pTV. A probability map was generated depending on the confidence of estimation in IPSF for the regions of missing data and penumbra. pTV was finally used to reconstruct the CBCT image for a Catphan, and was compared to conventional CBCT image without using SMOG, images without using IPSF (SMOG + FDK and SMOG + mask-TV), and image without using pTV (SMOG + IPSF + FDK). Results: The conventional CBCT without using SMOG shows apparent scatter-induced cup artifacts. The approaches with SMOG but without IPSF show severe (SMOG + FDK) or additional (SMOG + TV) artifacts, possibly due to using projections of missing data. The 2 approaches with SMOG + IPSF removes the cup artifacts, and the pTV approach is superior than the FDK by substantially reducing the noise. Using the SMOG also reduces half of the imaging dose. Conclusion: The proposed technique is promising in improving CBCT image quality while reducing imaging dose

  9. Multi-Sensor Architectures

    DEFF Research Database (Denmark)

    Hussain, Dil Muhammad Akbar; Ahmed, Zaki; Khan, M. Z.

    2012-01-01

    The use of multiple sensors typically requires the fusion of data from different type of sensors. The combined use of such a data has the potential to give an efficient, high quality and reliable estimation. Input data from different sensors allows the introduction of target attributes (target ty...

  10. Electrostatic Architecture of the Infectious Salmon Anemia Virus (ISAV) Core Fusion Protein Illustrates a Carboxyl-Carboxylate pH Sensor.

    Science.gov (United States)

    Cook, Jonathan D; Soto-Montoya, Hazel; Korpela, Markus K; Lee, Jeffrey E

    2015-07-24

    Segment 5, ORF 1 of the infectious salmon anemia virus (ISAV) genome, encodes for the ISAV F protein, which is responsible for viral-host endosomal membrane fusion during a productive ISAV infection. The entry machinery of ISAV is composed of a complex of the ISAV F and ISAV hemagglutinin esterase (HE) proteins in an unknown stoichiometry prior to receptor engagement by ISAV HE. Following binding of the receptor to ISAV HE, dissociation of the ISAV F protein from HE, and subsequent endocytosis, the ISAV F protein resolves into a fusion-competent oligomeric state. Here, we present a 2.1 Å crystal structure of the fusion core of the ISAV F protein determined at low pH. This structure has allowed us to unambiguously demonstrate that the ISAV entry machinery exhibits typical class I viral fusion protein architecture. Furthermore, we have determined stabilizing factors that accommodate the pH-dependent mode of ISAV transmission, and our structure has allowed the identification of a central coil that is conserved across numerous and varied post-fusion viral glycoprotein structures. We then discuss a mechanistic model of ISAV fusion that parallels the paramyxoviral class I fusion strategy wherein attachment and fusion are relegated to separate proteins in a similar fashion to ISAV fusion. © 2015 by The American Society for Biochemistry and Molecular Biology, Inc.

  11. Sensor Validation using Bayesian Networks

    Data.gov (United States)

    National Aeronautics and Space Administration — One of NASA’s key mission requirements is robust state estimation. Sensing, using a wide range of sensors and sensor fusion approaches, plays a central role in...

  12. Challenges in complementing data from ground-based sensors with satellite-derived products to measure ecological changes in relation to climate – lessons from temperate wetland-upland landscapes

    Science.gov (United States)

    Gallant, Alisa L.; Sadinski, Walter J.; Brown, Jesslyn F.; Senay, Gabriel B.; Roth, Mark F.

    2018-01-01

    Assessing climate-related ecological changes across spatiotemporal scales meaningful to resource managers is challenging because no one method reliably produces essential data at both fine and broad scales. We recently confronted such challenges while integrating data from ground- and satellite-based sensors for an assessment of four wetland-rich study areas in the U.S. Midwest. We examined relations between temperature and precipitation and a set of variables measured on the ground at individual wetlands and another set measured via satellite sensors within surrounding 4 km2 landscape blocks. At the block scale, we used evapotranspiration and vegetation greenness as remotely sensed proxies for water availability and to estimate seasonal photosynthetic activity. We used sensors on the ground to coincidentally measure surface-water availability and amphibian calling activity at individual wetlands within blocks. Responses of landscape blocks generally paralleled changes in conditions measured on the ground, but the latter were more dynamic, and changes in ecological conditions on the ground that were critical for biota were not always apparent in measurements of related parameters in blocks. Here, we evaluate the effectiveness of decisions and assumptions we made in applying the remotely sensed data for the assessment and the value of integrating observations across scales, sensors, and disciplines.

  13. Disaster Monitoring using Grid Based Data Fusion Algorithms

    Directory of Open Access Journals (Sweden)

    Cătălin NAE

    2010-12-01

    Full Text Available This is a study of the application of Grid technology and high performance parallelcomputing to a candidate algorithm for jointly accomplishing data fusion from different sensors. Thisincludes applications for both image analysis and/or data processing for simultaneously trackingmultiple targets in real-time. The emphasis is on comparing the architectures of the serial andparallel algorithms, and characterizing the performance benefits achieved by the parallel algorithmwith both on-ground and in-space hardware implementations. The improved performance levelsachieved by the use of Grid technology (middleware for Parallel Data Fusion are presented for themain metrics of interest in near real-time applications, namely latency, total computation load, andtotal sustainable throughput. The objective of this analysis is, therefore, to demonstrate animplementation of multi-sensor data fusion and/or multi-target tracking functions within an integratedmulti-node portable HPC architecture based on emerging Grid technology. The key metrics to bedetermined in support of ongoing system analyses includes: required computational throughput inMFLOPS; latency between receipt of input data and resulting outputs; and scalability, processorutilization and memory requirements. Furthermore, the standard MPI functions are considered to beused for inter-node communications in order to promote code portability across multiple HPCcomputer platforms, both in space and on-ground.

  14. Fluxgate vector magnetometers: Compensated multi-sensor devices for ground, UAV and airborne magnetic survey for various application in near surface geophysics

    Science.gov (United States)

    Gavazzi, Bruno; Le Maire, Pauline; Munschy, Marc; Dechamp, Aline

    2017-04-01

    Fluxgate 3-components magnetometer is the kind of magnetometer which offers the lightest weight and lowest power consumption for the measurement of the intensity of the magnetic field. Moreover, vector measurements make it the only kind of magnetometer allowing compensation of magnetic perturbations due to the equipment carried with it. Unfortunately, Fluxgate magnetometers are quite uncommon in near surface geophysics due to the difficulty to calibrate them precisely. The recent advances in calibration of the sensors and magnetic compensation of the devices from a simple process on the field led Institut de Physique du Globe de Strasbourg to develop instruments for georeferenced magnetic measurements at different scales - from submetric measurements on the ground to aircraft-conducted acquisition through the wide range offered by unmanned aerial vehicles (UAVs) - with a precision in the order of 1 nT. Such equipment is used for different kind of application: structural geology, pipes and UXO detection, archaeology.

  15. Applying Cognitive Fusion to Space Situational Awareness

    Science.gov (United States)

    Ingram, S.; Shaw, M.; Chan, M.

    With recent increases in capability and frequency of rocket launches from countries across the world, maintaining a state-of-the-art Space Situational Awareness model is all the more necessary. We propose a fusion of real-time, natural language processing capability provided by IBM cognitive services with ground-based sensor data of positions and trajectories of satellites in all earth orbits. We believe such insight provided by cognitive services could help determine context to missile launches, help predict when a satellite of interest could be in danger, either by accident or by intent, and could alert interested parties to the perceived threat. We seek to implement an improved Space Situational Awareness model by developing a dynamic factor graph model informed by the fusion of ground-based ”structured” sensor data with ”unstructured” data from the public domain, such as news articles, blogs, and social media, in real time. To this end, we employ IBM’s Cognitive services, specifically, Watson Discovery. Watson Discovery allows real-time natural language processing of text including entity extraction, keyword search, taxonomy classification, concept tagging, relation extraction, sentiment analysis, and emotion analysis. We present various scenarios that demonstrate the utility of this new Space Situational Awareness model, each of which combine past structured information with related open source data. We demonstrate that should the model come to estimate a satellite is ”of interest”, it will indicate it as so, based on the most pertinent data, such as a reading from a sensor or by information available online. We present and discuss the most recent iterations of the model for satellites currently available on Space-Track.org.

  16. A novel chalcone-analogue as an optical sensor based on ground and excited states intramolecular charge transfer: A combined experimental and theoretical study

    International Nuclear Information System (INIS)

    Fayed, Tarek A.

    2006-01-01

    Steady-state absorption and emission spectroscopic techniques as well as semiempirical quantum calculations at the AM1 and ZINDO/S levels have been used to investigate the intramolecular charge transfer (ICT) behaviour of a novel chalcone namely; 1-(2-pyridyl)-5-(4-dimethylaminophenyl)-penta-2,4-diene-1-one, DMAC. The ground state DMAC has a significant ICT character and a great sensitivity to the hydrogen bond donating ability of the medium as reflected from the change of the absorption spectra in pure and mixed organic solvents. On the other hand, its excited singlet state exhibits high ICT characters as manifested by the drastic solvatochromic effects. These results are consistent with the data of charge density calculations in both the ground and excited state, which indicates enhancement of the charge transfer from the dimethyl-amino group to the carbonyl oxygen upon excitation. Also, the dipole moment calculations indicates a highly dipolar excited singlet state (Δμ eg = 15.5 D). The solvent dependence of the fluorescence quantum yield of DMAC was interpreted on the basis of positive and negative solvatokinetic as well as the hydrogen bonding effects. Incorporation of the 2-pyridyl group in the chemical structure of the present DMAC led to design of a potential optical sensor for probing acidity of the medium and metal cations such as Zn 2+ , Cd 2+ and Hg 2+ . This was concluded from the high acidochromic and metallochromic behaviour of DMAC on adding such cations to its acetonitrile solutions

  17. EMP Fusion

    OpenAIRE

    KUNTAY, Isık

    2010-01-01

    This paper introduces a novel fusion scheme, called EMP Fusion, which has the promise of achieving breakeven and realizing commercial fusion power. The method is based on harnessing the power of an electromagnetic pulse generated by the now well-developed flux compression technology. The electromagnetic pulse acts as a means of both heating up the plasma and confining the plasma, eliminating intermediate steps. The EMP Fusion device is simpler compared to other fusion devices and this reduces...

  18. Data fusion mathematics theory and practice

    CERN Document Server

    Raol, Jitendra R

    2015-01-01

    Fills the Existing Gap of Mathematics for Data FusionData fusion (DF) combines large amounts of information from a variety of sources and fuses this data algorithmically, logically and, if required intelligently, using artificial intelligence (AI). Also, known as sensor data fusion (SDF), the DF fusion system is an important component for use in various applications that include the monitoring of vehicles, aerospace systems, large-scale structures, and large industrial automation plants. Data Fusion Mathematics: Theory and Practice offers a comprehensive overview of data fusion, and provides a

  19. A multi-sensor study of the impact of ground-based glaciogenic seeding on orogrpahic clouds and precipitation

    Science.gov (United States)

    Pokharel, Binod

    This dissertation examines reflectivity data from three different radar systems, as well as airborne and ground-based in situ particle imaging data, to study the impact of ground-based glaciogenic seeding on orographic clouds and precipitation formed over the mountains in southern Wyoming. The data for this study come from the AgI Seeding Cloud Impact Investigation (ASCII) field campaign conducted over the Sierra Madre mountains in 2012 (ASCII-12) and over the Medicine Bow mountains in 2013 (ASCII-13) in the context of the Wyoming Weather Modification Pilot Project (WWMPP). The campaigns were supported by a network of ground-based instruments, including a microwave radiometer, two profiling Ka-band Micro Rain Radars (MRRs), a Doppler on Wheels (DOW), rawinsondes, a Cloud Particle Imager, and a Parsivel disdrometer. The University of Wyoming King Air with profiling Wyoming Cloud Radar (WCR) conducted nine successful flights in ASCII-12, and eight flights in ASCII-13. WCR profiles from these flights are combined with those from seven other flights, which followed the same geographically-fixed pattern in 2008-09 (pre-ASCII) over the Medicine Bow range. All sampled storms were relatively shallow, with low-level air forced over the target mountain, and cold enough to support ice initiation by silver iodide (AgI) nuclei in cloud. Three detailed case studies are conducted, each with different atmospheric conditions and different cloud and snow growth properties: one case (21 Feb 2012) is stratiform, with strong winds and cloud droplets too small to enable snow growth by accretion (riming). A second case (13 Feb 2012) contains shallow convective cells. Clouds in the third case study (22 Feb 2012) are stratiform but contain numerous large droplets (mode ~35 microm in diameter), large enough for ice particle growth by riming. These cases and all others, each with a treated period following an untreated period, show that a clear seeding signature is not immediately apparent

  20. GNSS as a sea ice sensor - detecting coastal freeze states with ground-based GNSS-R

    Science.gov (United States)

    Strandberg, Joakim; Hobiger, Thomas; Haas, Rüdiger

    2017-04-01

    Based on the idea of using freely available signals for remote sensing, ground-based GNSS-reflectometry (GNSS-R) has found more and more applications in hydrology, oceanography, agriculture and other Earth sciences. GNSS-R is based on analysing the elevation dependent SNR patterns of GNSS signals, and traditionally only the oscillation frequency and phase have been studied to retrieve parameters from the reflecting surfaces. However, recently Strandberg et al. (2016) developed an inversion algorithm that has changed the paradigms of ground-based GNSS-R as it enables direct access to the radiometric properties of the reflector. Using the signal envelope and the rate at which the magnitude of the SNR oscillations are damped w.r.t. satellite elevation, the algorithm retrieves the roughness of the reflector surface amongst other parameters. Based on this idea, we demonstrate for the first time that a GNSS installation situated close to the coastline can detect the presence of sea-ice unambiguously. Using data from the GTGU antenna at the Onsala Space Observatory, Sweden, the time series of the derived damping parameter clearly matches the occurrence of ice in the bay where the antenna is situated. Our results were validated against visual inspection logs as well as with the help of ice charts from the Swedish Meteorological and Hydrological Institute. Our method is even sensitive to partial and intermediate ice formation stages, with clear difference in response between frazil ice and both open and solidly frozen water surfaces. As the GTGU installation is entirely built with standard geodetic equipment, the method can be applied directly to any coastal GNSS site, allowing analysis of both new and historical data. One can use the method as an automatic way of retrieving independent ground truth data for ice extent measurements for use in hydrology, cryosphere studies, and even societal interest fields such as sea transportation. Finally, the new method opens up for

  1. Artificial Intelligence and Sensor Fusion

    National Research Council Canada - National Science Library

    Capraro, Gerard T; Berdan, Gerald B; Liuzzi, Raymond A; Wicks, Michael C

    2003-01-01

    ...) tools and techniques. This paper investigates leveraging the AI tools being developed by the Semantic Web, DARPA's DAML program and, specifically the building of ontologies and resource description framework (RDF...

  2. observation and analysis of the structure of winter precipitation-generating clouds using ground-based sensor measurements

    Science.gov (United States)

    Menéndez José Luis, Marcos; Gómez José Luis, Sánchez; Campano Laura, López; Ortega Eduardo, García; Suances Andrés, Merino; González Sergio, Fernández; Salvador Estíbaliz, Gascón; González Lucía, Hermida

    2015-04-01

    In this study, we used a 28-day database corresponding to December, January and February of 2011/2012 and 2012/2013 campaigns to analyze cloud structure that produced precipitation in the Sierra Norte near Madrid, Spain. We used remote sensing measurements, both active type like the K-band Micro Rain Radar (MRR) and passive type like the Radiometrics MP-3000A multichannel microwave radiometer. Using reflectivity data from the MRR, we determined the important microphysical parameters of Ice Water Content (IWC) and its integrated value over the atmospheric column, or Ice Water Path (IWP). Among the measurements taken by the MP-3000A were Liquid Water Path (LWP) and Integrated Water Vapor (IWV). By representing these data together, sharp declines in LWP and IWV were evident, coincident with IWP increases. This result indicates the ability of a K-band radar to measure the amount of ice in the atmospheric column, simultaneously revealing the Wegener-Bergeron-Findeisen mechanism. We also used a Present Weather Sensor (VPF-730; Biral Ltd., Bristol, UK) to determine the type and amount of precipitation at the surface. With these data, we used regression equations to establish the relationship between visibility and precipitation intensity. In addition, through theoretical precipitation visibility-intensity relationships, we estimated the type of crystal, degree of accretion (riming), and moisture content of fallen snow crystals.

  3. Osteoclast Fusion

    DEFF Research Database (Denmark)

    Marie Julie Møller, Anaïs; Delaissé, Jean-Marie; Søe, Kent

    2017-01-01

    on the nuclearity of fusion partners. While CD47 promotes cell fusions involving mono-nucleated pre-osteoclasts, syncytin-1 promotes fusion of two multi-nucleated osteoclasts, but also reduces the number of fusions between mono-nucleated pre-osteoclasts. Furthermore, CD47 seems to mediate fusion mostly through...... individual fusion events using time-lapse and antagonists of CD47 and syncytin-1. All time-lapse recordings have been studied by two independent observers. A total of 1808 fusion events were analyzed. The present study shows that CD47 and syncytin-1 have different roles in osteoclast fusion depending...... broad contact surfaces between the partners' cell membrane while syncytin-1 mediate fusion through phagocytic-cup like structure. J. Cell. Physiol. 9999: 1-8, 2016. © 2016 Wiley Periodicals, Inc....

  4. Anti-Personnel Landmine detection using depth fusion

    NARCIS (Netherlands)

    Schutte, K.; Cremer, F.; Breejen, E. den; Schavemaker, J.G.M.; Benoist, K.W.

    2001-01-01

    Detection of Anti-Personnel Landmines is a challenging task for any sensor currently available. Using sensor fusion allows combining individual sensor results such that for each sensor its advantages remain while compensating for its disadvantages by using other sensor types. This paper provides an

  5. Monitoring the Impact of Climate Change on Soil Salinity in Agricultural Areas Using Ground and Satellite Sensors

    Science.gov (United States)

    Corwin, D. L.; Scudiero, E.

    2017-12-01

    Changes in climatic patterns have had dramatic influence on agricultural areas worldwide, particularly in irrigated arid-zone agricultural areas subjected to recurring drought, such as California's San Joaquin Valley (SJV), or areas receiving above average rainfall for a decade or more, such as Minnesota's Red River Valley (RRV). Climate change has impacted water availability with an under or over abundance, which subsequently has impacted soil salinity levels in the root zone primarily from the upward movement of salts from shallow water tables. Inventorying and monitoring the impact of climate change on soil salinity is crucial to evaluate the extent of the problem, to recognize trends, and to formulate state-wide and field-scale irrigation, drainage, and crop management strategies that will sustain the agricultural productivity of the SJV and RRV. Over the past 3 decades, Corwin and colleagues at the U.S. Salinity Laboratory have developed proximal sensor (i.e., electrical resistivity and electromagnetic induction) and remote imagery (i.e., MODIS and Landsat 7) methodologies for assessing soil salinity at multiple scales: field (0.5 ha to 3 km2), landscape (3 to 10 km2), and regional (10 to 105 km2) scales. The purpose of this presentation is to provide an overview of these scale-dependent salinity assessment technologies. Case studies for SJV and RRV are presented to demonstrate at multiple scales the utility of these approaches in assessing soil salinity changes due to management-induced changes and to changes in climate patterns, and in providing site-specific irrigation management information for salinity control. Decision makers in state and federal agencies, irrigation and drainage district managers, soil and water resource managers, producers, agriculture consultants, extension specialists, and Natural Resource Conservation Service field staff are the beneficiaries of this information.

  6. Fusion power

    International Nuclear Information System (INIS)

    Hancox, R.

    1981-01-01

    The principles of fusion power, and its advantages and disadvantages, are outlined. Present research programmes and future plans directed towards the development of a fusion power reactor, are summarized. (U.K.)

  7. Fusion rings and fusion ideals

    DEFF Research Database (Denmark)

    Andersen, Troels Bak

    by the so-called fusion ideals. The fusion rings of Wess-Zumino-Witten models have been widely studied and are well understood in terms of precise combinatorial descriptions and explicit generating sets of the fusion ideals. They also appear in another, more general, setting via tilting modules for quantum......This dissertation investigates fusion rings, which are Grothendieck groups of rigid, monoidal, semisimple, abelian categories. Special interest is in rational fusion rings, i.e., fusion rings which admit a finite basis, for as commutative rings they may be presented as quotients of polynomial rings...

  8. Fusion: introduction

    International Nuclear Information System (INIS)

    Decreton, M.

    2006-01-01

    The article gives an overview and introduction to the activities of SCK-CEN's research programme on fusion. The decision to construct the ITER international nuclear fusion experiment in Cadarache is highlighted. A summary of the Belgian contributions to fusion research is given with particular emphasis on studies of radiation effects on diagnostics systems, radiation effects on remote handling sensing systems, fusion waste management and socio-economic studies

  9. Soil Moisture Estimation Across Scales with Mobile Sensors for Cosmic-Ray Neutrons from the Ground and Air

    Science.gov (United States)

    Schrön, Martin; Köhler, Mandy; Bannehr, Lutz; Köhli, Markus; Fersch, Benjamin; Rebmann, Corinna; Mai, Juliane; Cuntz, Matthias; Kögler, Simon; Schröter, Ingmar; Wollschläger, Ute; Oswald, Sascha; Dietrich, Peter; Zacharias, Steffen

    2016-04-01

    Soil moisture is a key variable for environmental sciences, but its determination at various scales and depths is still an open challenge. Cosmic-ray neutron sensing has become a well accepted and unique method to monitor an effective soil water content, covering tens of hectares in area and tens of centimeters in depth. The technology is famous for its low maintanance, non-invasiveness, continous measurement, and most importantly its large footprint and penetration depth. Beeing more representative than point data, and finer resolved plus deeper penetrating than remote-sensing products, cosmic-ray neutron derived soil moisture products provide unrivaled advantage for agriculture, regional hydrologic and land surface models. The method takes advantage of omnipresent neutrons which are extraordinarily sensitive to hydrogen in soil, plants, snow and air. Unwanted hydrogen sources in the footprint can be excluded by local calibration to extract the pure soil water information. However, this procedure is not feasible for mobile measurements, where neutron detectors are mounted on a car to do catchment-scale surveys. As a solution to that problem, we suggest strategies to correct spatial neutron data with the help of available spatial data of soil type, landuse and vegetation. We further present results of mobile rover campaigns at various scales and conditions, covering small sites from 0.2 km2 to catchments of 100 km2 area, and complex terrain from agricultural fields, urban areas, forests, to snowy alpine sites. As the rover is limited to accessible roads, we further investigated the applicability of airborne measurements. First tests with a gyrocopter at 150 to 200m heights proofed the concept of airborne neutron detection for environmental sciences. Moreover, neutron transport simulations confirm an improved areal coverage during these campaigns. Mobile neutron measurements at the ground or air are a promising tool for the detection of water sources across many

  10. Membrane fusion

    DEFF Research Database (Denmark)

    Bendix, Pól Martin

    2015-01-01

    At Stanford University, Boxer lab, I worked on membrane fusion of small unilamellar lipid vesicles to flat membranes tethered to glass surfaces. This geometry closely resembles biological systems in which liposomes fuse to plasma membranes. The fusion mechanism was studied using DNA zippering...... between complementary strands linked to the two apposing membranes closely mimicking the zippering mechanism of SNARE fusion complexes....

  11. Fusion Canada

    International Nuclear Information System (INIS)

    1987-07-01

    This first issue of a quarterly newsletter announces the startup of the Tokamak de Varennes, describes Canada's national fusion program, and outlines the Canadian Fusion Fuels Technology Program. A map gives the location of the eleven principal fusion centres in Canada. (L.L.)

  12. Fusion neutronics

    CERN Document Server

    Wu, Yican

    2017-01-01

    This book provides a systematic and comprehensive introduction to fusion neutronics, covering all key topics from the fundamental theories and methodologies, as well as a wide range of fusion system designs and experiments. It is the first-ever book focusing on the subject of fusion neutronics research. Compared with other nuclear devices such as fission reactors and accelerators, fusion systems are normally characterized by their complex geometry and nuclear physics, which entail new challenges for neutronics such as complicated modeling, deep penetration, low simulation efficiency, multi-physics coupling, etc. The book focuses on the neutronics characteristics of fusion systems and introduces a series of theories and methodologies that were developed to address the challenges of fusion neutronics, and which have since been widely applied all over the world. Further, it introduces readers to neutronics design’s unique principles and procedures, experimental methodologies and technologies for fusion systems...

  13. Fusion Physics

    Energy Technology Data Exchange (ETDEWEB)

    Kikuchi, Mitsuru; Lackner, Karl; Tran, Minh Quang [eds.

    2012-09-15

    Recreating the energy production process of the Sun - nuclear fusion - on Earth in a controlled fashion is one of the greatest challenges of this century. If achieved at affordable costs, energy supply security would be greatly enhanced and environmental degradation from fossil fuels greatly diminished. Fusion Physics describes the last fifty years or so of physics and research in innovative technologies to achieve controlled thermonuclear fusion for energy production. The International Atomic Energy Agency (IAEA) has been involved since its establishment in 1957 in fusion research. It has been the driving force behind the biennial conferences on Plasma Physics and Controlled Thermonuclear Fusion, today known as the Fusion Energy Conference. Hosted by several Member States, this biennial conference provides a global forum for exchange of the latest achievements in fusion research against the backdrop of the requirements for a net energy producing fusion device and, eventually, a fusion power plant. The scientific and technological knowledge compiled during this series of conferences, as well as by the IAEA Nuclear Fusion journal, is immense and will surely continue to grow in the future. It has led to the establishment of the International Thermonuclear Experimental Reactor (ITER), which represents the biggest experiment in energy production ever envisaged by humankind.

  14. Image fusion for enhanced forest structural assessment

    CSIR Research Space (South Africa)

    Roberts, JW

    2011-01-01

    Full Text Available This research explores the potential benefits of fusing active and passive medium resolution satellite-borne sensor data for forest structural assessment. Image fusion was applied as a means of retaining disparate data features relevant to modeling...

  15. New architecture for the sensor web: the SWAP framework.

    CSIR Research Space (South Africa)

    Moodley, D

    2006-11-01

    Full Text Available Sensor Web is a revolutionary concept towards achieving a collaborative, coherent, consistent, and consolidated sensor data collection, fusion and distribution system. Sensor Webs can perform as an extensive monitoring and sensing system...

  16. Fusion breeder

    International Nuclear Information System (INIS)

    Moir, R.W.

    1982-01-01

    The fusion breeder is a fusion reactor designed with special blankets to maximize the transmutation by 14 MeV neutrons of uranium-238 to plutonium or thorium to uranium-233 for use as a fuel for fission reactors. Breeding fissile fuels has not been a goal of the US fusion energy program. This paper suggests it is time for a policy change to make the fusion breeder a goal of the US fusion program and the US nuclear energy program. The purpose of this paper is to suggest this policy change be made and tell why it should be made, and to outline specific research and development goals so that the fusion breeder will be developed in time to meet fissile fuel needs

  17. Using Co-located Rotational and Translational Ground-Motion Sensors to Characterize Seismic Scattering in the P-Wave Coda

    Science.gov (United States)

    Bartrand, J.; Abbott, R. E.

    2017-12-01

    We present data and analysis of a seismic data collect at the site of a historical underground nuclear explosion at Yucca Flat, a sedimentary basin on the Nevada National Security Site, USA. The data presented here consist of active-source, six degree-of-freedom seismic signals. The translational signals were collected with a Nanometrics Trillium Compact Posthole seismometer and the rotational signals were collected with an ATA Proto-SMHD, a prototype rotational ground motion sensor. The source for the experiment was the Seismic Hammer (a 13,000 kg weight-drop), deployed on two-kilometer, orthogonal arms centered on the site of the nuclear explosion. By leveraging the fact that compressional waves have no rotational component, we generated a map of subsurface scattering and compared the results to known subsurface features. To determine scattering intensity, signals were cut to include only the P-wave and its coda. The ratio of the time-domain signal magnitudes of angular velocity and translational acceleration were sectioned into three time windows within the coda and averaged within each window. Preliminary results indicate an increased rotation/translation ratio in the vicinity of the explosion-generated chimney, suggesting mode conversion of P-wave energy to S-wave energy at that location. Sandia National Laboratories is a multimission laboratory managed and operated by National Technology and Engineering Solutions of Sandia LLC, a wholly owned subsidiary of Honeywell International Inc. for the U.S. Department of Energy's National Nuclear Security Administration under contract DE-NA0003525.

  18. Fusion Implementation

    International Nuclear Information System (INIS)

    Schmidt, J.A.

    2002-01-01

    If a fusion DEMO reactor can be brought into operation during the first half of this century, fusion power production can have a significant impact on carbon dioxide production during the latter half of the century. An assessment of fusion implementation scenarios shows that the resource demands and waste production associated with these scenarios are manageable factors. If fusion is implemented during the latter half of this century it will be one element of a portfolio of (hopefully) carbon dioxide limiting sources of electrical power. It is time to assess the regional implications of fusion power implementation. An important attribute of fusion power is the wide range of possible regions of the country, or countries in the world, where power plants can be located. Unlike most renewable energy options, fusion energy will function within a local distribution system and not require costly, and difficult, long distance transmission systems. For example, the East Coast of the United States is a prime candidate for fusion power deployment by virtue of its distance from renewable energy sources. As fossil fuels become less and less available as an energy option, the transmission of energy across bodies of water will become very expensive. On a global scale, fusion power will be particularly attractive for regions separated from sources of renewable energy by oceans

  19. High Level Information Fusion (HLIF) with nested fusion loops

    Science.gov (United States)

    Woodley, Robert; Gosnell, Michael; Fischer, Amber

    2013-05-01

    Situation modeling and threat prediction require higher levels of data fusion in order to provide actionable information. Beyond the sensor data and sources the analyst has access to, the use of out-sourced and re-sourced data is becoming common. Through the years, some common frameworks have emerged for dealing with information fusion—perhaps the most ubiquitous being the JDL Data Fusion Group and their initial 4-level data fusion model. Since these initial developments, numerous models of information fusion have emerged, hoping to better capture the human-centric process of data analyses within a machine-centric framework. 21st Century Systems, Inc. has developed Fusion with Uncertainty Reasoning using Nested Assessment Characterizer Elements (FURNACE) to address challenges of high level information fusion and handle bias, ambiguity, and uncertainty (BAU) for Situation Modeling, Threat Modeling, and Threat Prediction. It combines JDL fusion levels with nested fusion loops and state-of-the-art data reasoning. Initial research has shown that FURNACE is able to reduce BAU and improve the fusion process by allowing high level information fusion (HLIF) to affect lower levels without the double counting of information or other biasing issues. The initial FURNACE project was focused on the underlying algorithms to produce a fusion system able to handle BAU and repurposed data in a cohesive manner. FURNACE supports analyst's efforts to develop situation models, threat models, and threat predictions to increase situational awareness of the battlespace. FURNACE will not only revolutionize the military intelligence realm, but also benefit the larger homeland defense, law enforcement, and business intelligence markets.

  20. Electric field sensor studies

    International Nuclear Information System (INIS)

    Griffith, R.D.; Parks, S.

    1977-01-01

    Above-ground intrusion sensors are reviewed briefly. Buried wire sensors are next considered; feasibility studies were conducted. A triangular system of an overhead transmitter wire exciting two buried sensor wires was developed and tested. It failed sometimes to detect a man making a broad jump. A differential receiver was developed to solve this problem

  1. Thermonuclear fusion

    International Nuclear Information System (INIS)

    Weisse, J.

    2000-01-01

    This document takes stock of the two ways of thermonuclear fusion research explored today: magnetic confinement fusion and inertial confinement fusion. The basic physical principles are recalled first: fundamental nuclear reactions, high temperatures, elementary properties of plasmas, ignition criterion, magnetic confinement (charged particle in a uniform magnetic field, confinement and Tokamak principle, heating of magnetized plasmas (ohmic, neutral particles, high frequency waves, other heating means), results obtained so far (scale laws and extrapolation of performances, tritium experiments, ITER project), inertial fusion (hot spot ignition, instabilities, results (Centurion-Halite program, laser experiments). The second part presents the fusion reactor and its associated technologies: principle (tritium production, heat source, neutron protection, tritium generation, materials), magnetic fusion (superconducting magnets, divertor (role, principle, realization), inertial fusion (energy vector, laser adaptation, particle beams, reaction chamber, stresses, chamber concepts (dry and wet walls, liquid walls), targets (fabrication, injection and pointing)). The third chapter concerns the socio-economic aspects of thermonuclear fusion: safety (normal operation and accidents, wastes), costs (costs structure and elementary comparison, ecological impact and external costs). (J.S.)

  2. Fusion devices

    International Nuclear Information System (INIS)

    Fowler, T.K.

    1977-01-01

    Three types of thermonuclear fusion devices currently under development are reviewed for an electric utilities management audience. Overall design features of laser fusion, tokamak, and magnetic mirror type reactors are described and illustrated. Thrusts and trends in current research on these devices that promise to improve performance are briefly reviewed. Twenty photographs and drawings are included

  3. FuzzyFusion: an application architecture for multisource information fusion

    Science.gov (United States)

    Fox, Kevin L.; Henning, Ronda R.

    2009-04-01

    The correlation of information from disparate sources has long been an issue in data fusion research. Traditional data fusion addresses the correlation of information from sources as diverse as single-purpose sensors to all-source multi-media information. Information system vulnerability information is similar in its diversity of sources and content, and in the desire to draw a meaningful conclusion, namely, the security posture of the system under inspection. FuzzyFusionTM, A data fusion model that is being applied to the computer network operations domain is presented. This model has been successfully prototyped in an applied research environment and represents a next generation assurance tool for system and network security.

  4. Atomic fusion, Gerrard atomic fusion

    International Nuclear Information System (INIS)

    Gerrard, T.H.

    1980-01-01

    In the approach to atomic fusion described here the heat produced in a fusion reaction, which is induced in a chamber by the interaction of laser beams and U.H.F. electromagnetic beams with atom streams, is transferred to a heat exchanger for electricity generation by a coolant flowing through a jacket surrounding the chamber. (U.K.)

  5. Downscaling Satellite Data for Predicting Catchment-scale Root Zone Soil Moisture with Ground-based Sensors and an Ensemble Kalman Filter

    Science.gov (United States)

    Lin, H.; Baldwin, D. C.; Smithwick, E. A. H.

    2015-12-01

    Predicting root zone (0-100 cm) soil moisture (RZSM) content at a catchment-scale is essential for drought and flood predictions, irrigation planning, weather forecasting, and many other applications. Satellites, such as the NASA Soil Moisture Active Passive (SMAP), can estimate near-surface (0-5 cm) soil moisture content globally at coarse spatial resolutions. We develop a hierarchical Ensemble Kalman Filter (EnKF) data assimilation modeling system to downscale satellite-based near-surface soil moisture and to estimate RZSM content across the Shale Hills Critical Zone Observatory at a 1-m resolution in combination with ground-based soil moisture sensor data. In this example, a simple infiltration model within the EnKF-model has been parameterized for 6 soil-terrain units to forecast daily RZSM content in the catchment from 2009 - 2012 based on AMSRE. LiDAR-derived terrain variables define intra-unit RZSM variability using a novel covariance localization technique. This method also allows the mapping of uncertainty with our RZSM estimates for each time-step. A catchment-wide satellite-to-surface downscaling parameter, which nudges the satellite measurement closer to in situ near-surface data, is also calculated for each time-step. We find significant differences in predicted root zone moisture storage for different terrain units across the experimental time-period. Root mean square error from a cross-validation analysis of RZSM predictions using an independent dataset of catchment-wide in situ Time-Domain Reflectometry (TDR) measurements ranges from 0.060-0.096 cm3 cm-3, and the RZSM predictions are significantly (p < 0.05) correlated with TDR measurements [r = 0.47-0.68]. The predictive skill of this data assimilation system is similar to the Penn State Integrated Hydrologic Modeling (PIHM) system. Uncertainty estimates are significantly (p < 0.05) correlated to cross validation error during wet and dry conditions, but more so in dry summer seasons. Developing an

  6. Peaceful fusion

    Energy Technology Data Exchange (ETDEWEB)

    Englert, Matthias [IANUS, TU Darmstadt (Germany)

    2014-07-01

    Like other intense neutron sources fusion reactors have in principle a potential to be used for military purposes. Although the use of fissile material is usually not considered when thinking of fusion reactors (except in fusion-fission hybrid concepts) quantitative estimates about the possible production potential of future commercial fusion reactor concepts show that significant amounts of weapon grade fissile materials could be produced even with very limited amounts of source materials. In this talk detailed burnup calculations with VESTA and MCMATH using an MCNP model of the PPCS-A will be presented. We compare different irradiation positions and the isotopic vectors of the plutonium bred in different blankets of the reactor wall with the liquid lead-lithium alloy replaced by uranium. The technical, regulatory and policy challenges to manage the proliferation risks of fusion power will be addressed as well. Some of these challenges would benefit if addressed at an early stage of the research and development process. Hence, research on fusion reactor safeguards should start as early as possible and accompany the current research on experimental fusion reactors.

  7. A synthetic dataset for evaluating soft and hard fusion algorithms

    Science.gov (United States)

    Graham, Jacob L.; Hall, David L.; Rimland, Jeffrey

    2011-06-01

    There is an emerging demand for the development of data fusion techniques and algorithms that are capable of combining conventional "hard" sensor inputs such as video, radar, and multispectral sensor data with "soft" data including textual situation reports, open-source web information, and "hard/soft" data such as image or video data that includes human-generated annotations. New techniques that assist in sense-making over a wide range of vastly heterogeneous sources are critical to improving tactical situational awareness in counterinsurgency (COIN) and other asymmetric warfare situations. A major challenge in this area is the lack of realistic datasets available for test and evaluation of such algorithms. While "soft" message sets exist, they tend to be of limited use for data fusion applications due to the lack of critical message pedigree and other metadata. They also lack corresponding hard sensor data that presents reasonable "fusion opportunities" to evaluate the ability to make connections and inferences that span the soft and hard data sets. This paper outlines the design methodologies, content, and some potential use cases of a COIN-based synthetic soft and hard dataset created under a United States Multi-disciplinary University Research Initiative (MURI) program funded by the U.S. Army Research Office (ARO). The dataset includes realistic synthetic reports from a variety of sources, corresponding synthetic hard data, and an extensive supporting database that maintains "ground truth" through logical grouping of related data into "vignettes." The supporting database also maintains the pedigree of messages and other critical metadata.

  8. Visualization of graphical information fusion results

    Science.gov (United States)

    Blasch, Erik; Levchuk, Georgiy; Staskevich, Gennady; Burke, Dustin; Aved, Alex

    2014-06-01

    Graphical fusion methods are popular to describe distributed sensor applications such as target tracking and pattern recognition. Additional graphical methods include network analysis for social, communications, and sensor management. With the growing availability of various data modalities, graphical fusion methods are widely used to combine data from multiple sensors and modalities. To better understand the usefulness of graph fusion approaches, we address visualization to increase user comprehension of multi-modal data. The paper demonstrates a use case that combines graphs from text reports and target tracks to associate events and activities of interest visualization for testing Measures of Performance (MOP) and Measures of Effectiveness (MOE). The analysis includes the presentation of the separate graphs and then graph-fusion visualization for linking network graphs for tracking and classification.

  9. Cold fusion

    International Nuclear Information System (INIS)

    Suh, Suk Yong; Sung, Ki Woong; Kang, Joo Sang; Lee, Jong Jik

    1995-02-01

    So called 'cold fusion phenomena' are not confirmed yet. Excess heat generation is very delicate one. Neutron generation is most reliable results, however, the records are erratic and the same results could not be repeated. So there is no reason to exclude the malfunction of testing instruments. The same arguments arise in recording 4 He, 3 He, 3 H, which are not rich in quantity basically. An experiment where plenty of 4 He were recorded is attached in appendix. The problem is that we are trying to search cold fusion which is permitted by nature or not. The famous tunneling effect in quantum mechanics will answer it, however, the most fusion rate is known to be negligible. The focus of this project is on the theme that how to increase that negligible fusion rate. 6 figs, 4 tabs, 1512 refs. (Author)

  10. Cold fusion

    Energy Technology Data Exchange (ETDEWEB)

    Suh, Suk Yong; Sung, Ki Woong; Kang, Joo Sang; Lee, Jong Jik [Korea Atomic Energy Research Institute, Taejon (Korea, Republic of)

    1995-02-01

    So called `cold fusion phenomena` are not confirmed yet. Excess heat generation is very delicate one. Neutron generation is most reliable results, however, the records are erratic and the same results could not be repeated. So there is no reason to exclude the malfunction of testing instruments. The same arguments arise in recording {sup 4}He, {sup 3}He, {sup 3}H, which are not rich in quantity basically. An experiment where plenty of {sup 4}He were recorded is attached in appendix. The problem is that we are trying to search cold fusion which is permitted by nature or not. The famous tunneling effect in quantum mechanics will answer it, however, the most fusion rate is known to be negligible. The focus of this project is on the theme that how to increase that negligible fusion rate. 6 figs, 4 tabs, 1512 refs. (Author).

  11. Laser fusion

    International Nuclear Information System (INIS)

    Ashby, D.E.T.F.

    1976-01-01

    A short survey is given on laser fusion its basic concepts and problems and the present theoretical and experimental methods. The future research program of the USA in this field is outlined. (WBU) [de

  12. Fusion energy

    International Nuclear Information System (INIS)

    Anon.

    1979-01-01

    The efforts of the Chemical Technology Division in fusion energy include the areas of fuel handling, processing, and containment. Current studies are concerned largely with the development of vacuum pumps for fusion reactors and experiments and with development and evaluation of techniques for recovering tritium from solid or liquid breeding blankets. In addition, a small effort is devoted to support of the ORNL design of a major Tokamak experiment, The Next Step (TNS)

  13. Laser fusion

    International Nuclear Information System (INIS)

    Key, M.H.; Oxford Univ.

    1990-04-01

    The use of lasers to drive implosions for the purpose of inertially confined fusion is an area of intense activity where progress compares favourably with that made in magnetic fusion and there are significant prospects for future development. In this brief review the basic concept is summarised and the current status is outlined both in the area of laser technology and in the most recent results from implosion experiments. Prospects for the future are also considered. (author)

  14. Nuclear fusion

    International Nuclear Information System (INIS)

    Al-zaelic, M.M.

    2013-01-01

    Nuclear fusion can be relied on to solve the global energy crisis if the process of limiting the heat produced by the fusion reaction (Plasma) is successful. Currently scientists are progressively working on this aspect whereas there are two methods to limit the heat produced by fusion reaction, the two methods are auto-restriction using laser beam and magnetic restriction through the use of magnetic fields and research is carried out to improve these two methods. It is expected that at the end of this century the nuclear fusion energy will play a vital role in overcoming the global energy crisis and for these reasons, acquiring energy through the use of nuclear fusion reactors is one of the most urge nt demands of all mankind at this time. The conclusion given is that the source of fuel for energy production is readily available and inexpensive ( hydrogen atoms) and whole process is free of risks and hazards, especially to general health and the environment . Nuclear fusion importance lies in the fact that energy produced by the process is estimated to be about four to five times the energy produced by nuclear fission. (author)

  15. Preliminary study on evaluation of the pancreatic tail observable limit of transabdominal ultrasonography using a position sensor and CT-fusion image

    Energy Technology Data Exchange (ETDEWEB)

    Sumi, Hajime; Itoh, Akihiro; Kawashima, Hiroki [Department of Gastroenterology and Hepatology, Nagoya University Graduate School of Medicine, Nagoya (Japan); Ohno, Eizaburo [Department of Endoscopy, Nagoya University Hospital, Nagoya (Japan); Itoh, Yuya; Nakamura, Yosuke; Hiramatsu, Takeshi; Sugimoto, Hiroyuki; Hayashi, Daijuro; Kuwahara, Takamichi; Morishima, Tomomasa; Kawai, Manabu; Furukawa, Kazuhiro [Department of Gastroenterology and Hepatology, Nagoya University Graduate School of Medicine, Nagoya (Japan); Funasaka, Kohei [Department of Endoscopy, Nagoya University Hospital, Nagoya (Japan); Nakamura, Masanao; Miyahara, Ryoji [Department of Gastroenterology and Hepatology, Nagoya University Graduate School of Medicine, Nagoya (Japan); Katano, Yoshiaki [Department of Gastroenterology, Second Teaching Hospital, Fujita Health University (Japan); Ishigami, Masatoshi [Department of Gastroenterology and Hepatology, Nagoya University Graduate School of Medicine, Nagoya (Japan); Ohmiya, Naoki [Department of Gastroenterology, Second Teaching Hospital, Fujita Health University (Japan); Goto, Hidemi [Department of Gastroenterology and Hepatology, Nagoya University Graduate School of Medicine, Nagoya (Japan); Department of Endoscopy, Nagoya University Hospital, Nagoya (Japan); and others

    2014-08-15

    Background and aim: Transabdominal ultrasonography (US) is commonly used for the initial screening of bilio-pancreatic diseases in Asian countries due to its widespread availability, the non-invasiveness and the cost-effectiveness. However, it is considered that US has limits to observe the area, namely the blind area. The observation of the pancreatic tail is particularly difficult. The goal of this study was to examine the pancreatic tail region that cannot be visualized on transverse scanning of the upper abdomen using US with spatial positional information and factors related to visualization, and observation of the tail from the splenic hilum. Methods: Thirty-nine patients with pancreatic/biliary tract disease underwent CT and US with GPS-like technology and fusion imaging for measurement of the real pancreatic length and the predicted/real unobservable (PU and RU) length of the pancreatic tail. RU from US on transverse scanning and the real pancreatic length were used to determine the unobservable area (UA: RU/the real pancreatic length). Relationships of RU with physical and hematological variables that might influence visualization of the pancreatic tail were investigated. Results: The real pancreatic length was 160.9 ± 16.4 mm, RU was 41.0 ± 17.8 mm, and UA was 25.3 ± 10.4%. RU was correlated with BMI (R = 0.446, P = 0.004) and waist circumferences (R = 0.354, P = 0.027), and strongly correlated with PU (R = 0.788, P < 0.001). The pancreatic tail was visible from the splenic hilum in 22 (56%) subjects and was completely identified in 13 (33%) subjects. Conclusions: Combined GPS-like technology with fusion imaging was useful for the objective estimation of the pancreatic blind area.

  16. Preliminary study on evaluation of the pancreatic tail observable limit of transabdominal ultrasonography using a position sensor and CT-fusion image

    International Nuclear Information System (INIS)

    Sumi, Hajime; Itoh, Akihiro; Kawashima, Hiroki; Ohno, Eizaburo; Itoh, Yuya; Nakamura, Yosuke; Hiramatsu, Takeshi; Sugimoto, Hiroyuki; Hayashi, Daijuro; Kuwahara, Takamichi; Morishima, Tomomasa; Kawai, Manabu; Furukawa, Kazuhiro; Funasaka, Kohei; Nakamura, Masanao; Miyahara, Ryoji; Katano, Yoshiaki; Ishigami, Masatoshi; Ohmiya, Naoki; Goto, Hidemi

    2014-01-01

    Background and aim: Transabdominal ultrasonography (US) is commonly used for the initial screening of bilio-pancreatic diseases in Asian countries due to its widespread availability, the non-invasiveness and the cost-effectiveness. However, it is considered that US has limits to observe the area, namely the blind area. The observation of the pancreatic tail is particularly difficult. The goal of this study was to examine the pancreatic tail region that cannot be visualized on transverse scanning of the upper abdomen using US with spatial positional information and factors related to visualization, and observation of the tail from the splenic hilum. Methods: Thirty-nine patients with pancreatic/biliary tract disease underwent CT and US with GPS-like technology and fusion imaging for measurement of the real pancreatic length and the predicted/real unobservable (PU and RU) length of the pancreatic tail. RU from US on transverse scanning and the real pancreatic length were used to determine the unobservable area (UA: RU/the real pancreatic length). Relationships of RU with physical and hematological variables that might influence visualization of the pancreatic tail were investigated. Results: The real pancreatic length was 160.9 ± 16.4 mm, RU was 41.0 ± 17.8 mm, and UA was 25.3 ± 10.4%. RU was correlated with BMI (R = 0.446, P = 0.004) and waist circumferences (R = 0.354, P = 0.027), and strongly correlated with PU (R = 0.788, P < 0.001). The pancreatic tail was visible from the splenic hilum in 22 (56%) subjects and was completely identified in 13 (33%) subjects. Conclusions: Combined GPS-like technology with fusion imaging was useful for the objective estimation of the pancreatic blind area

  17. Review of 3d GIS Data Fusion Methods and Progress

    Science.gov (United States)

    Hua, Wei; Hou, Miaole; Hu, Yungang

    2018-04-01

    3D data fusion is a research hotspot in the field of computer vision and fine mapping, and plays an important role in fine measurement, risk monitoring, data display and other processes. At present, the research of 3D data fusion in the field of Surveying and mapping focuses on the 3D model fusion of terrain and ground objects. This paper summarizes the basic methods of 3D data fusion of terrain and ground objects in recent years, and classified the data structure and the establishment method of 3D model, and some of the most widely used fusion methods are analysed and commented.

  18. REVIEW OF 3D GIS DATA FUSION METHODS AND PROGRESS

    Directory of Open Access Journals (Sweden)

    W. Hua

    2018-04-01

    Full Text Available 3D data fusion is a research hotspot in the field of computer vision and fine mapping, and plays an important role in fine measurement, risk monitoring, data display and other processes. At present, the research of 3D data fusion in the field of Surveying and mapping focuses on the 3D model fusion of terrain and ground objects. This paper summarizes the basic methods of 3D data fusion of terrain and ground objects in recent years, and classified the data structure and the establishment method of 3D model, and some of the most widely used fusion methods are analysed and commented.

  19. Autonomous sensor manager agents (ASMA)

    Science.gov (United States)

    Osadciw, Lisa A.

    2004-04-01

    Autonomous sensor manager agents are presented as an algorithm to perform sensor management within a multisensor fusion network. The design of the hybrid ant system/particle swarm agents is described in detail with some insight into their performance. Although the algorithm is designed for the general sensor management problem, a simulation example involving 2 radar systems is presented. Algorithmic parameters are determined by the size of the region covered by the sensor network, the number of sensors, and the number of parameters to be selected. With straight forward modifications, this algorithm can be adapted for most sensor management problems.

  20. Multisensor Fusion for Change Detection

    Science.gov (United States)

    Schenk, T.; Csatho, B.

    2005-12-01

    Combining sensors that record different properties of a 3-D scene leads to complementary and redundant information. If fused properly, a more robust and complete scene description becomes available. Moreover, fusion facilitates automatic procedures for object reconstruction and modeling. For example, aerial imaging sensors, hyperspectral scanning systems, and airborne laser scanning systems generate complementary data. We describe how data from these sensors can be fused for such diverse applications as mapping surface erosion and landslides, reconstructing urban scenes, monitoring urban land use and urban sprawl, and deriving velocities and surface changes of glaciers and ice sheets. An absolute prerequisite for successful fusion is a rigorous co-registration of the sensors involved. We establish a common 3-D reference frame by using sensor invariant features. Such features are caused by the same object space phenomena and are extracted in multiple steps from the individual sensors. After extracting, segmenting and grouping the features into more abstract entities, we discuss ways on how to automatically establish correspondences. This is followed by a brief description of rigorous mathematical models suitable to deal with linear and area features. In contrast to traditional, point-based registration methods, lineal and areal features lend themselves to a more robust and more accurate registration. More important, the chances to automate the registration process increases significantly. The result of the co-registration of the sensors is a unique transformation between the individual sensors and the object space. This makes spatial reasoning of extracted information more versatile; reasoning can be performed in sensor space or in 3-D space where domain knowledge about features and objects constrains reasoning processes, reduces the search space, and helps to make the problem well-posed. We demonstrate the feasibility of the proposed multisensor fusion approach

  1. Sensor Fusion Based on an Integrated Neural Network and Probability Density Function (PDF) Dual Kalman Filter for On-Line Estimation of Vehicle Parameters and States.

    Science.gov (United States)

    Vargas-Melendez, Leandro; Boada, Beatriz L; Boada, Maria Jesus L; Gauchia, Antonio; Diaz, Vicente

    2017-04-29

    Vehicles with a high center of gravity (COG), such as light trucks and heavy vehicles, are prone to rollover. This kind of accident causes nearly 33 % of all deaths from passenger vehicle crashes. Nowadays, these vehicles are incorporating roll stability control (RSC) systems to improve their safety. Most of the RSC systems require the vehicle roll angle as a known input variable to predict the lateral load transfer. The vehicle roll angle can be directly measured by a dual antenna global positioning system (GPS), but it is expensive. For this reason, it is important to estimate the vehicle roll angle from sensors installed onboard in current vehicles. On the other hand, the knowledge of the vehicle's parameters values is essential to obtain an accurate vehicle response. Some of vehicle parameters cannot be easily obtained and they can vary over time. In this paper, an algorithm for the simultaneous on-line estimation of vehicle's roll angle and parameters is proposed. This algorithm uses a probability density function (PDF)-based truncation method in combination with a dual Kalman filter (DKF), to guarantee that both vehicle's states and parameters are within bounds that have a physical meaning, using the information obtained from sensors mounted on vehicles. Experimental results show the effectiveness of the proposed algorithm.

  2. Data fusion concept in multispectral system for perimeter protection of stationary and moving objects

    Science.gov (United States)

    Ciurapiński, Wieslaw; Dulski, Rafal; Kastek, Mariusz; Szustakowski, Mieczyslaw; Bieszczad, Grzegorz; Życzkowski, Marek; Trzaskawka, Piotr; Piszczek, Marek

    2009-09-01

    The paper presents the concept of multispectral protection system for perimeter protection for stationary and moving objects. The system consists of active ground radar, thermal and visible cameras. The radar allows the system to locate potential intruders and to control an observation area for system cameras. The multisensor construction of the system ensures significant improvement of detection probability of intruder and reduction of false alarms. A final decision from system is worked out using image data. The method of data fusion used in the system has been presented. The system is working under control of FLIR Nexus system. The Nexus offers complete technology and components to create network-based, high-end integrated systems for security and surveillance applications. Based on unique "plug and play" architecture, system provides unmatched flexibility and simplistic integration of sensors and devices in TCP/IP networks. Using a graphical user interface it is possible to control sensors and monitor streaming video and other data over the network, visualize the results of data fusion process and obtain detailed information about detected intruders over a digital map. System provides high-level applications and operator workload reduction with features such as sensor to sensor cueing from detection devices, automatic e-mail notification and alarm triggering.

  3. An Approach to Automated Fusion System Design and Adaptation

    Directory of Open Access Journals (Sweden)

    Alexander Fritze

    2017-03-01

    Full Text Available Industrial applications are in transition towards modular and flexible architectures that are capable of self-configuration and -optimisation. This is due to the demand of mass customisation and the increasing complexity of industrial systems. The conversion to modular systems is related to challenges in all disciplines. Consequently, diverse tasks such as information processing, extensive networking, or system monitoring using sensor and information fusion systems need to be reconsidered. The focus of this contribution is on distributed sensor and information fusion systems for system monitoring, which must reflect the increasing flexibility of fusion systems. This contribution thus proposes an approach, which relies on a network of self-descriptive intelligent sensor nodes, for the automatic design and update of sensor and information fusion systems. This article encompasses the fusion system configuration and adaptation as well as communication aspects. Manual interaction with the flexibly changing system is reduced to a minimum.

  4. An Approach to Automated Fusion System Design and Adaptation.

    Science.gov (United States)

    Fritze, Alexander; Mönks, Uwe; Holst, Christoph-Alexander; Lohweg, Volker

    2017-03-16

    Industrial applications are in transition towards modular and flexible architectures that are capable of self-configuration and -optimisation. This is due to the demand of mass customisation and the increasing complexity of industrial systems. The conversion to modular systems is related to challenges in all disciplines. Consequently, diverse tasks such as information processing, extensive networking, or system monitoring using sensor and information fusion systems need to be reconsidered. The focus of this contribution is on distributed sensor and information fusion systems for system monitoring, which must reflect the increasing flexibility of fusion systems. This contribution thus proposes an approach, which relies on a network of self-descriptive intelligent sensor nodes, for the automatic design and update of sensor and information fusion systems. This article encompasses the fusion system configuration and adaptation as well as communication aspects. Manual interaction with the flexibly changing system is reduced to a minimum.

  5. Cold fusion

    International Nuclear Information System (INIS)

    Koster, J.

    1989-01-01

    In this contribution the author the phenomenom of so-called cold fusion, inspired by the memorable lecture of Moshe Gai on his own search for this effect. Thus much of what follows was presented by Dr. Gai; the rest is from independent reading. What is referred to as cold fusion is of course the observation of possible products of deuteron-deuteron (d-d) fusion within deuterium-loaded (dentended) electrodes. The debate over the two vanguard cold fusion experiments has raged under far more public attention than usually accorded new scientific phenomena. The clamor commenced with the press conference of M. Fleishmann and S. Pons on March 23, 1989 and the nearly simultaneous wide circulation of a preprint of S. Jones and collaborators. The majority of work attempting to confirm these observations has at the time of this writing yet to appear in published form, but contributions to conferences and electronic mail over computer networks were certainly filled with preliminary results. To keep what follows to a reasonable length the author limit this discussion to the searches for neutron (suggested by ref. 2) or for excessive heat production (suggested by ref. 1), following a synopsis of the hypotheses of cold fusion

  6. Fusion events

    International Nuclear Information System (INIS)

    Aboufirassi, M; Angelique, J.C.; Bizard, G.; Bougault, R.; Brou, R.; Buta, A.; Colin, J.; Cussol, D.; Durand, D.; Genoux-Lubain, A.; Horn, D.; Kerambrun, A.; Laville, J.L.; Le Brun, C.; Lecolley, J.F.; Lefebvres, F.; Lopez, O.; Louvel, M.; Meslin, C.; Metivier, V.; Nakagawa, T.; Peter, J.; Popescu, R.; Regimbart, R.; Steckmeyer, J.C.; Tamain, B.; Vient, E.; Wieloch, A.; Yuasa-Nakagawa, K.

    1998-01-01

    The fusion reactions between low energy heavy ions have a very high cross section. First measurements at energies around 30-40 MeV/nucleon indicated no residue of either complete or incomplete fusion, thus demonstrating the disappearance of this process. This is explained as being due to the high amount o energies transferred to the nucleus, what leads to its total dislocation in light fragments and particles. Exclusive analyses have permitted to mark clearly the presence of fusion processes in heavy systems at energies above 30-40 MeV/nucleon. Among the complete events of the Kr + Au reaction at 60 MeV/nucleon the majority correspond to binary collisions. Nevertheless, for the most considerable energy losses, a class of events do occur for which the detected fragments appears to be emitted from a unique source. These events correspond to an incomplete projectile-target fusion followed by a multifragmentation. Such events were singled out also in the reaction Xe + Sn at 50 MeV/nucleon. For the events in which the energy dissipation was maximal it was possible to isolate an isotropic group of events showing all the characteristics of fusion nuclei. The fusion is said to be incomplete as pre-equilibrium Z = 1 and Z = 2 particles are emitted. The cross section is of the order of 25 mb. Similar conclusions were drown for the systems 36 Ar + 27 Al and 64 Zn + nat Ti. A cross section value of ∼ 20 mb was determined at 55 MeV/nucleon in the first case, while the measurement of evaporation light residues in the last system gave an upper limit of 20-30 mb for the cross section at 50 MeV/nucleon

  7. Extending lifetime of wireless sensor networks using multi-sensor ...

    Indian Academy of Sciences (India)

    SOUMITRA DAS

    In this paper a multi-sensor data fusion approach for wireless sensor network based on bayesian methods and ant colony ... niques for efficiently routing the data from source to the BS ... Literature review ... efficient scheduling and lot more to increase the lifetime of ... Nature-inspired algorithms such as ACO algorithms have.

  8. A Fuzzy-Based Fusion Method of Multimodal Sensor-Based Measurements for the Quantitative Evaluation of Eye Fatigue on 3D Displays

    Directory of Open Access Journals (Sweden)

    Jae Won Bang

    2015-05-01

    Full Text Available With the rapid increase of 3-dimensional (3D content, considerable research related to the 3D human factor has been undertaken for quantitatively evaluating visual discomfort, including eye fatigue and dizziness, caused by viewing 3D content. Various modalities such as electroencephalograms (EEGs, biomedical signals, and eye responses have been investigated. However, the majority of the previous research has analyzed each modality separately to measure user eye fatigue. This cannot guarantee the credibility of the resulting eye fatigue evaluations. Therefore, we propose a new method for quantitatively evaluating eye fatigue related to 3D content by combining multimodal measurements. This research is novel for the following four reasons: first, for the evaluation of eye fatigue with high credibility on 3D displays, a fuzzy-based fusion method (FBFM is proposed based on the multimodalities of EEG signals, eye blinking rate (BR, facial temperature (FT, and subjective evaluation (SE; second, to measure a more accurate variation of eye fatigue (before and after watching a 3D display, we obtain the quality scores of EEG signals, eye BR, FT and SE; third, for combining the values of the four modalities we obtain the optimal weights of the EEG signals BR, FT and SE using a fuzzy system based on quality scores; fourth, the quantitative level of the variation of eye fatigue is finally obtained using the weighted sum of the values measured by the four modalities. Experimental results confirm that the effectiveness of the proposed FBFM is greater than other conventional multimodal measurements. Moreover, the credibility of the variations of the eye fatigue using the FBFM before and after watching the 3D display is proven using a t-test and descriptive statistical analysis using effect size.

  9. Nuclear fusion

    International Nuclear Information System (INIS)

    Huber, H.

    1978-01-01

    A comprehensive survey is presented of the present state of knowledge in nuclear fusion research. In the first part, potential thermonuclear reactions, basic energy balances of the plasma (Lawson criterion), and the main criteria to be observed in the selection of appropriate thermonuclear reactions are dealt with. This is followed by a discussion of the problems encountered in plasma physics (plasma confinement and heating, transport processes, plasma impurities, plasma instabilities and plasma diagnostics) and by a consideration of the materials problems involved, such as material of the first wall, fuel inlet and outlet, magnetic field generation, as well as repair work and in-service inspections. Two main methods have been developed to tackle these problems: reactor concepts using the magnetic pinch (stellarator, Tokamak, High-Beta reactors, mirror machines) on the one hand, and the other concept using the inertial confinement (laser fusion reactor). These two approaches and their specific problems as well as past, present and future fusion experiments are treated in detail. The last part of the work is devoted to safety and environmental aspects of the potential thermonuclear aspects of the potential thermonuclear reactor, discussing such problems as fusion-specific hazards, normal operation and potential hazards, reactor incidents, environmental pollution by thermal effluents, radiological pollution, radioactive wastes and their disposal, and siting problems. (orig./GG) [de

  10. Short fusion

    CERN Multimedia

    2002-01-01

    French and UK researchers are perfecting a particle accelerator technique that could aid the quest for fusion energy or make X-rays that are safer and produce higher-resolution images. Led by Dr Victor Malka from the Ecole Nationale Superieure des Techniques Avancees in Paris, the team has developed a better way of accelerating electrons over short distances (1 page).

  11. Magnetic fusion

    International Nuclear Information System (INIS)

    2002-01-01

    This document is a detailed lecture on thermonuclear fusion. The basic physics principles are recalled and the technological choices that have led to tokamaks or stellarators are exposed. Different aspects concerning thermonuclear reactors such as safety, economy and feasibility are discussed. Tore-supra is described in details as well as the ITER project

  12. Cold fusion

    International Nuclear Information System (INIS)

    Seo, Suk Yong; You, Jae Jun

    1996-01-01

    Nearly every technical information is chased in the world. All of them are reviewed and analyzed. Some of them are chosen to study further more to review every related documents. And a probable suggestion about the excitonic process in deuteron absorbed condensed matter is proposed a way to cold fusion. 8 refs. (Author)

  13. Trust metrics in information fusion

    Science.gov (United States)

    Blasch, Erik

    2014-05-01

    Trust is an important concept for machine intelligence and is not consistent across many applications. In this paper, we seek to understand trust from a variety of factors: humans, sensors, communications, intelligence processing algorithms and human-machine displays of information. In modeling the various aspects of trust, we provide an example from machine intelligence that supports the various attributes of measuring trust such as sensor accuracy, communication timeliness, machine processing confidence, and display throughput to convey the various attributes that support user acceptance of machine intelligence results. The example used is fusing video and text whereby an analyst needs trust information in the identified imagery track. We use the proportional conflict redistribution rule as an information fusion technique that handles conflicting data from trusted and mistrusted sources. The discussion of the many forms of trust explored in the paper seeks to provide a systems-level design perspective for information fusion trust quantification.

  14. The Radio Frequency Health Node Wireless Sensor System

    Science.gov (United States)

    Valencia, J. Emilio; Stanley, Priscilla C.; Mackey, Paul J.

    2009-01-01

    The Radio Frequency Health Node (RFHN) wireless sensor system differs from other wireless sensor systems in ways originally intended to enhance utility as an instrumentation system for a spacecraft. The RFHN can also be adapted to use in terrestrial applications in which there are requirements for operational flexibility and integrability into higher-level instrumentation and data acquisition systems. As shown in the figure, the heart of the system is the RFHN, which is a unit that passes commands and data between (1) one or more commercially available wireless sensor units (optionally, also including wired sensor units) and (2) command and data interfaces with a local control computer that may be part of the spacecraft or other engineering system in which the wireless sensor system is installed. In turn, the local control computer can be in radio or wire communication with a remote control computer that may be part of a higher-level system. The remote control computer, acting via the local control computer and the RFHN, cannot only monitor readout data from the sensor units but can also remotely configure (program or reprogram) the RFHN and the sensor units during operation. In a spacecraft application, the RFHN and the sensor units can also be configured more nearly directly, prior to launch, via a serial interface that includes an umbilical cable between the spacecraft and ground support equipment. In either case, the RFHN wireless sensor system has the flexibility to be configured, as required, with different numbers and types of sensors for different applications. The RFHN can be used to effect realtime transfer of data from, and commands to, the wireless sensor units. It can also store data for later retrieval by an external computer. The RFHN communicates with the wireless sensor units via a radio transceiver module. The modular design of the RFHN makes it possible to add radio transceiver modules as needed to accommodate additional sets of wireless sensor

  15. Cold fusion, Alchemist's dream

    International Nuclear Information System (INIS)

    Clayton, E.D.

    1989-09-01

    In this report the following topics relating to cold fusion are discussed: muon catalysed cold fusion; piezonuclear fusion; sundry explanations pertaining to cold fusion; cosmic ray muon catalysed cold fusion; vibrational mechanisms in excited states of D 2 molecules; barrier penetration probabilities within the hydrogenated metal lattice/piezonuclear fusion; branching ratios of D 2 fusion at low energies; fusion of deuterons into 4 He; secondary D+T fusion within the hydrogenated metal lattice; 3 He to 4 He ratio within the metal lattice; shock induced fusion; and anomalously high isotopic ratios of 3 He/ 4 He

  16. Magnetic fusion; La fusion magnetique

    Energy Technology Data Exchange (ETDEWEB)

    NONE

    2002-07-01

    This document is a detailed lecture on thermonuclear fusion. The basic physics principles are recalled and the technological choices that have led to tokamaks or stellarators are exposed. Different aspects concerning thermonuclear reactors such as safety, economy and feasibility are discussed. Tore-supra is described in details as well as the ITER project.

  17. Mitigation of the ground reflection effect in real-time locating systems based on wireless sensor networks by using artificial neural networks

    OpenAIRE

    de Paz Santana, Juan F.; Tapia Martínez, Dante I.; Alonso Rincón, Ricardo S.; Pinzón, Cristian; Bajo Pérez, Javier; Corchado Rodríguez, Juan M.

    2017-01-01

    Wireless sensor networks (WSNs) have become much more relevant in recent years, mainly because they can be used in a wide diversity of applications. Real-time locating systems (RTLSs) are one of the most promising applications based on WSNs and represent a currently growing market. Specifically, WSNs are an ideal alternative to develop RTLSs aimed at indoor environments where existing global navigation satellite systems, such as the global positioning system, do not work correctly due to the ...

  18. An Assessment of Pseudo-Operational Ground-Based Light Detection and Ranging Sensors to Determine the Boundary-Layer Structure in the Coastal Atmosphere

    Directory of Open Access Journals (Sweden)

    Conor Milroy

    2012-01-01

    Full Text Available Twenty-one cases of boundary-layer structure were retrieved by three co-located remote sensors, One LIDAR and two ceilometers at the coastal site of Mace Head, Ireland. Data were collected during the ICOS field campaign held at the GAW Atmospheric Station of Mace Head, Ireland, from 8th to 28th of June, 2009. The study is a two-step investigation of the BL structure based on (i the intercomparison of the backscatter profiles from the three laser sensors, namely the Leosphere ALS300 LIDAR, the Vaisala CL31 ceilometer and the Jenoptik CHM15K ceilometer; (ii and the comparison of the backscatter profiles with twenty-three radiosoundings performed during the period from the 8th to the 15th of June, 2009. The sensor-independent Temporal Height-Tracking algorithm was applied to the backscatter profiles as retrieved by each instrument to determine the decoupled structure of the BL over Mace Head. The LIDAR and ceilometers-retrieved BL heights were compared to the radiosoundings temperature profiles. The comparison between the remote and the in-situ data proved the existence of the inherent link between temperature and aerosol backscatter profiles and opened at future studies focusing on the further assessment of LIDAR-ceilometer comparison.

  19. Distributed estimation based on observations prediction in wireless sensor networks

    KAUST Repository

    Bouchoucha, Taha; Ahmed, Mohammed F A; Al-Naffouri, Tareq Y.; Alouini, Mohamed-Slim

    2015-01-01

    We consider wireless sensor networks (WSNs) used for distributed estimation of unknown parameters. Due to the limited bandwidth, sensor nodes quantize their noisy observations before transmission to a fusion center (FC) for the estimation process

  20. Cold nuclear fusion

    Energy Technology Data Exchange (ETDEWEB)

    Tsyganov, E.N., E-mail: edward.tsyganov@coldfusion-power.com [Cold Fusion Power, International (United States); Bavizhev, M.D. [LLC “Radium”, Moscow (Russian Federation); Buryakov, M.G. [Joint Institute for Nuclear Research (JINR), Dubna (Russian Federation); Dabagov, S.B. [RAS P.N. Lebedev Physical Institute, Leninsky pr. 53, 119991 Moscow (Russian Federation); National Research Nuclear University MEPhI, Kashirskoe shosse 31, 115409 Moscow (Russian Federation); Golovatyuk, V.M.; Lobastov, S.P. [Joint Institute for Nuclear Research (JINR), Dubna (Russian Federation)

    2015-07-15

    If target deuterium atoms were implanted in a metal crystal in accelerator experiments, a sharp increase in the probability of DD-fusion reaction was clearly observed when compared with the reaction’s theoretical value. The electronic screening potential, which for a collision of free deuterium atoms is about 27 eV, reached 300–700 eV in the case of the DD-fusion in metallic crystals. These data leads to the conclusion that a ban must exist for deuterium atoms to be in the ground state 1s in a niche filled with free conduction electrons. At the same time, the state 2p whose energy level is only 10 eV above that of state 1s is allowed in these conditions. With anisotropy of 2p, 3p or above orbitals, their spatial positions are strictly determined in the lattice coordinate system. When filling out the same potential niches with two deuterium atoms in the states 2p, 3p or higher, the nuclei of these atoms can be permanently positioned without creating much Coulomb repulsion at a very short distance from each other. In this case, the transparency of the potential barrier increases dramatically compared to the ground state 1s for these atoms. The probability of the deuterium nuclei penetrating the Coulomb barrier by zero quantum vibration of the DD-system also increases dramatically. The so-called cold nuclear DD-fusion for a number of years was registered in many experiments, however, was still rejected by mainstream science for allegedly having no consistent scientific explanation. Finally, it received the validation. Below, we outline the concept of this explanation and give the necessary calculations. This paper also considers the further destiny of the formed intermediate state of {sup 4}He{sup ∗}.

  1. Splenogonadal Fusion

    Directory of Open Access Journals (Sweden)

    Sung-Lang Chen

    2008-11-01

    Full Text Available Splenogonadal fusion (SGF is a rare congenital non-malignant anomaly characterized by fusion of splenic tissue to the gonad, and can be continuous or discontinuous. Very few cases have been diagnosed preoperatively, and many patients who present with testicular swelling undergo unnecessary orchiectomy under the suspicion of testicular neoplasm. A 16-year-old boy presented with a left scrotal mass and underwent total excision of a 1.6-cm tumor without damaging the testis, epididymis or its accompanying vessels. Pathologic examination revealed SFG (discontinuous type. If clinically suspected before surgery, the diagnosis may be confirmed by Tc-99m sulfur colloid imaging, which shows uptake in both the spleen and accessory splenic tissue within the scrotum. Frozen section should be considered if there remains any doubt regarding the diagnosis during operation.

  2. Laser fusion

    International Nuclear Information System (INIS)

    Eliezer, S.

    1982-02-01

    In this paper, the physics of laser fusion is described on an elementary level. The irradiated matter consists of a dense inner core surrounded by a less dense plasma corona. The laser radiation is mainly absorbed in the outer periphery of the plasma. The absorbed energy is transported inward to the ablation surface where plasma flow is created. Due to this plasma flow, a sequence of inward going shock waves and heat waves are created, resulting in the compression and heating of the core to high density and temperature. The interaction physics between laser and matter leading to thermonuclear burn is summarized by the following sequence of events: Laser absorption → Energy transport → Compression → Nuclear Fusion. This scenario is shown in particular for a Nd:laser with a wavelength of 1 μm. The wavelength scaling of the physical processes is also discussed. In addition to the laser-plasma physics, the Nd high power pulsed laser is described. We give a very brief description of the oscillator, the amplifiers, the spatial filters, the isolators and the diagnostics involved. Last, but not least, the concept of reactors for laser fusion and the necessary laser system are discussed. (author)

  3. Fusion spectroscopy

    International Nuclear Information System (INIS)

    Peacock, N.J.

    1995-09-01

    This article traces developments in the spectroscopy of high temperature laboratory plasma used in controlled fusion research from the early 1960's until the present. These three and a half decades have witnessed many orders of magnitude increase in accessible plasma parameters such as density and temperature as well as particle and energy confinement timescales. Driven by the need to interpret the radiation in terms of the local plasma parameters, the thrust of fusion spectroscopy has been to develop our understanding of (i) the atomic structure of highly ionised atoms, usually of impurities in the hydrogen isotope fuel; (ii) the atomic collision rates and their incorporation into ionization structure and emissivity models that take into account plasma phenomena like plasma-wall interactions, particle transport and radiation patterns; (iii) the diagnostic applications of spectroscopy aided by increasingly sophisticated characterisation of the electron fluid. These topics are discussed in relation to toroidal magnetically confined plasmas, particularly the Tokamak which appears to be the most promising approach to controlled fusion to date. (author)

  4. Medium resolution image fusion, does it enhance forest structure assessment

    CSIR Research Space (South Africa)

    Roberts, JW

    2008-07-01

    Full Text Available This research explored the potential benefits of fusing optical and Synthetic Aperture Radar (SAR) medium resolution satellite-borne sensor data for forest structural assessment. Image fusion was applied as a means of retaining disparate data...

  5. Ground water and earthquakes

    Energy Technology Data Exchange (ETDEWEB)

    Ts' ai, T H

    1977-11-01

    Chinese folk wisdom has long seen a relationship between ground water and earthquakes. Before an earthquake there is often an unusual change in the ground water level and volume of flow. Changes in the amount of particulate matter in ground water as well as changes in color, bubbling, gas emission, and noises and geysers are also often observed before earthquakes. Analysis of these features can help predict earthquakes. Other factors unrelated to earthquakes can cause some of these changes, too. As a first step it is necessary to find sites which are sensitive to changes in ground stress to be used as sensor points for predicting earthquakes. The necessary features are described. Recording of seismic waves of earthquake aftershocks is also an important part of earthquake predictions.

  6. Fusion Machines

    International Nuclear Information System (INIS)

    Weynants, R.R.

    2004-01-01

    A concise overview is given of the principles of inertial and magnetic fusion, with an emphasis on the latter in view of the aim of this summer school. The basis of magnetic confinement in mirror and toroidal geometry is discussed and applied to the tokamak concept. A brief discussion of the reactor prospects of this configuration identifies which future developments are crucial and where alternative concepts might help in optimising the reactor design. The text also aims at introducing the main concepts encountered in tokamak research that will be studied and used in the subsequent lectures

  7. Performance of UWB Array-Based Radar Sensor in a Multi-Sensor Vehicle-Based Suit for Landmine Detection

    NARCIS (Netherlands)

    Yarovoy, A.; Savelyev, T.; Zhuge, X.; Aubry, P.; Ligthart, L.; Schavemaker, J.G.M.; Tettelaar, P.; Breejen, E. de

    2008-01-01

    In this paper, integration of an UWB array-based timedomain radar sensor in a vehicle-mounted multi-sensor system for landmine detection is described. Dedicated real-time signal processing algorithms are developed to compute the radar sensor confidence map which is used for sensor fusion.

  8. TFTR grounding scheme and ground-monitor system

    International Nuclear Information System (INIS)

    Viola, M.

    1983-01-01

    The Tokamak Fusion Test Reactor (TFTR) grounding system utilizes a single-point ground. It is located directly under the machine, at the basement floor level, and is tied to the building perimeter ground. Wired to this single-point ground, via individual 500 MCM insulated cables, are: the vacuum vessel; four toroidal field coil cases/inner support structure quadrants; umbrella structure halves; the substructure ring girder; radial beams and columns; and the diagnostic systems. Prior to the first machine operation, a ground-loop removal program was initiated. It required insulation of all hangers and supports (within a 35-foot radius of the center of the machine) of the various piping, conduits, cable trays, and ventilation systems. A special ground-monitor system was designed and installed. It actively monitors each of the individual machine grounds to insure that there are no inadvertent ground loops within the machine structure or its ground and that the machine grounds are intact prior to each pulse. The TFTR grounding system has proven to be a very manageable system and one that is easy to maintain

  9. Engineering workstation: Sensor modeling

    Science.gov (United States)

    Pavel, M; Sweet, B.

    1993-01-01

    The purpose of the engineering workstation is to provide an environment for rapid prototyping and evaluation of fusion and image processing algorithms. Ideally, the algorithms are designed to optimize the extraction of information that is useful to a pilot for all phases of flight operations. Successful design of effective fusion algorithms depends on the ability to characterize both the information available from the sensors and the information useful to a pilot. The workstation is comprised of subsystems for simulation of sensor-generated images, image processing, image enhancement, and fusion algorithms. As such, the workstation can be used to implement and evaluate both short-term solutions and long-term solutions. The short-term solutions are being developed to enhance a pilot's situational awareness by providing information in addition to his direct vision. The long term solutions are aimed at the development of complete synthetic vision systems. One of the important functions of the engineering workstation is to simulate the images that would be generated by the sensors. The simulation system is designed to use the graphics modeling and rendering capabilities of various workstations manufactured by Silicon Graphics Inc. The workstation simulates various aspects of the sensor-generated images arising from phenomenology of the sensors. In addition, the workstation can be used to simulate a variety of impairments due to mechanical limitations of the sensor placement and due to the motion of the airplane. Although the simulation is currently not performed in real-time, sequences of individual frames can be processed, stored, and recorded in a video format. In that way, it is possible to examine the appearance of different dynamic sensor-generated and fused images.

  10. Fusion Canada issue 10

    International Nuclear Information System (INIS)

    1990-02-01

    A short bulletin from the National Fusion Program. Included in this issue is a report on Fusion Materials Research, ITER physics research, fusion performance record at JET, and design options for reactor building. 4 figs

  11. Infrared stereo calibration for unmanned ground vehicle navigation

    Science.gov (United States)

    Harguess, Josh; Strange, Shawn

    2014-06-01

    The problem of calibrating two color cameras as a stereo pair has been heavily researched and many off-the-shelf software packages, such as Robot Operating System and OpenCV, include calibration routines that work in most cases. However, the problem of calibrating two infrared (IR) cameras for the purposes of sensor fusion and point could generation is relatively new and many challenges exist. We present a comparison of color camera and IR camera stereo calibration using data from an unmanned ground vehicle. There are two main challenges in IR stereo calibration; the calibration board (material, design, etc.) and the accuracy of calibration pattern detection. We present our analysis of these challenges along with our IR stereo calibration methodology. Finally, we present our results both visually and analytically with computed reprojection errors.

  12. AGSM Intelligent Devices/Smart Sensors Project

    Science.gov (United States)

    Harp, Janicce Leshay

    2014-01-01

    This project provides development and qualification of Smart Sensors capable of self-diagnosis and assessment of their capability/readiness to support operations. These sensors will provide pressure and temperature measurements to use in ground systems.

  13. State fusion with unknown correlation: ellipsoidal intersection

    NARCIS (Netherlands)

    Sijs, J.; Lazar, M.; Bosch, P.P.J. van den

    2010-01-01

    Some crucial challenges of estimation over sensor networks are reaching consensus on the estimates of different systems in the network and separating the mutual information of two estimates from their exclusive information. Current fusion methods of two estimates tend to bypass the mutual

  14. State fusion with unknown correlation : ellipsoidal intersection

    NARCIS (Netherlands)

    Sijs, J.; Lazar, M.; Bosch, van den P.P.J.

    2010-01-01

    Some crucial challenges of estimation over sensor networks are reaching consensus on the estimates of different systems in the network and separating the mutual information of two estimates from their exclusive information. Current fusion methods of two estimates tend to bypass the mutual

  15. A Generic Algorithm to Estimate LAI, FAPAR and FCOVER Variables from SPOT4_HRVIR and Landsat Sensors: Evaluation of the Consistency and Comparison with Ground Measurements

    Directory of Open Access Journals (Sweden)

    Wenjuan Li

    2015-11-01

    Full Text Available The leaf area index (LAI and the fraction of photosynthetically active radiation absorbed by green vegetation (FAPAR are essential climatic variables in surface process models. FCOVER is also important to separate vegetation and soil for energy balance processes. Currently, several LAI, FAPAR and FCOVER satellite products are derived moderate to coarse spatial resolution. The launch of Sentinel-2 in 2015 will provide data at decametric resolution with a high revisit frequency to allow quantifying the canopy functioning at the local to regional scales. The aim of this study is thus to evaluate the performances of a neural network based algorithm to derive LAI, FAPAR and FCOVER products at decametric spatial resolution and high temporal sampling. The algorithm is generic, i.e., it is applied without any knowledge of the landcover. A time series of high spatial resolution SPOT4_HRVIR (16 scenes and Landsat 8 (18 scenes images acquired in 2013 over the France southwestern site were used to generate the LAI, FAPAR and FCOVER products. For each sensor and each biophysical variable, a neural network was first trained over PROSPECT+SAIL radiative transfer model simulations of top of canopy reflectance data for green, red, near-infra red and short wave infra-red bands. Our results show a good spatial and temporal consistency between the variables derived from both sensors: almost half the pixels show an absolute difference between SPOT and LANDSAT estimates of lower that 0.5 unit for LAI, and 0.05 unit for FAPAR and FCOVER. Finally, downward-looking digital hemispherical cameras were completed over the main land cover types to validate the accuracy of the products. Results show that the derived products are strongly correlated with the field measurements (R2 > 0.79, corresponding to a RMSE = 0.49 for LAI, RMSE = 0.10 (RMSE = 0.12 for black-sky (white sky FAPAR and RMSE = 0.15 for FCOVER. It is concluded that the proposed generic algorithm provides a good

  16. Inertial fusion by laser

    International Nuclear Information System (INIS)

    Dautray, R.; Watteau, J.-P.

    1980-01-01

    Following a brief historical survey of research into the effects of interaction of laser with matter, the principles of fusion by inertial confinement are described and the main parameters and possible levels given. The development of power lasers is then discussed with details of performances of the main lasers used in various laboratories, and with an assessment of the respective merits of neodymium glass, carbon dioxide or iodine lasers. The phenomena of laser radiation and its interaction with matter is then described, with emphasis on the results of experiments concerned with target implosion with the object of compressing and heating the mixture of heavy hydrogen and tritium to be ignited. Finally, a review is made of future possibilities opened up by the use of large power lasers which have recently become operational or are being constructed, and the ground still to be covered before a reactor can be produced [fr

  17. Revitalizing Fusion via Fission Fusion

    Science.gov (United States)

    Manheimer, Wallace

    2001-10-01

    Existing tokamaks could generate significant nuclear fuel. TFTR, operating steady state with DT might generate enough fuel for a 300 MW nuclear reactor. The immediate goals of the magnetic fusion program would necessarily shift from a study of advanced plasma regimes in larger sized devices, to mostly known plasmas regimes, but at steady state or high duty cycle operation in DT plasmas. The science and engineering of breeding blankets would be equally important. Follow on projects could possibly produce nuclear fuel in large quantity at low price. Although today there is strong opposition to nuclear power in the United States, in a 21st century world of 10 billion people, all of whom will demand a middle class life style, nuclear energy will be important. Concern over greenhouse gases will also drive the world toward nuclear power. There are studies indicating that the world will need 10 TW of carbon free energy by 2050. It is difficult to see how this can be achieved without the breeding of nuclear fuel. By using the thorium cycle, proliferation risks are minimized. [1], [2]. 1 W. Manheimer, Fusion Technology, 36, 1, 1999, 2.W. Manheimer, Physics and Society, v 29, #3, p5, July, 2000

  18. Catalysed fusion

    CERN Document Server

    Farley, Francis

    2012-01-01

    A sizzling romance and a romp with subatomic particles at CERN. Love, discovery and adventure in the city where nations meet and beams collide. Life in a large laboratory. As always, the challenges are the same. Who leads? Who follows? Who succeeds? Who gets the credit? Who gets the women or the men? Young Jeremy arrives in CERN and joins the quest for green energy. Coping with baffling jargon and manifold dangers, he is distracted by radioactive rats, lovely ladies and an unscrupulous rival. Full of doubts and hesitations, he falls for a dazzling Danish girl, who leads him astray. His brilliant idea leads to a discovery and a new route to cold fusion. But his personal life is scrambled. Does it bring fame or failure? Tragedy or triumph?

  19. Fusion cuisine

    DEFF Research Database (Denmark)

    Peters, Chris; Broersma, Marcel

    2018-01-01

    JJournalism studies as an academic field is characterized by multidisciplinarity. Focusing on one object of study, journalism and the news, it established itself by integrating and synthesizing approaches from established disciplines – a tendency that lives on today. This constant gaze to the out......JJournalism studies as an academic field is characterized by multidisciplinarity. Focusing on one object of study, journalism and the news, it established itself by integrating and synthesizing approaches from established disciplines – a tendency that lives on today. This constant gaze...... to the outside for conceptual inspiration and methodological tools lends itself to a journalism studies that is a fusion cuisine of media, communication, and related scholarship. However, what happens when this object becomes as fragmented and multifaceted as the ways we study it? This essay addresses...

  20. Water-Cut Sensor System

    KAUST Repository

    Karimi, Muhammad Akram

    2018-01-11

    Provided in some embodiments is a method of manufacturing a pipe conformable water-cut sensors system. Provided in some embodiments is method for manufacturing a water-cut sensor system that includes providing a helical T-resonator, a helical ground conductor, and a separator at an exterior of a cylindrical pipe. The helical T-resonator including a feed line, and a helical open shunt stub conductively coupled to the feed line. The helical ground conductor including a helical ground plane opposite the helical open shunt stub and a ground ring conductively coupled to the helical ground plane. The feed line overlapping at least a portion of the ground ring, and the separator disposed between the feed line and the portion of the ground ring overlapped by the feed line to electrically isolate the helical T-resonator from the helical ground conductor.