Tracking a convoy of multiple targets using acoustic sensor data

Science.gov (United States)

Damarla, T. R.

2003-08-01

In this paper we present an algorithm to track a convoy of several targets in a scene using acoustic sensor array data. The tracking algorithm is based on template of the direction of arrival (DOA) angles for the leading target. Often the first target is the closest target to the sensor array and hence the loudest with good signal to noise ratio. Several steps were used to generate a template of the DOA angle for the leading target, namely, (a) the angle at the present instant should be close to the angle at the previous instant and (b) the angle at the present instant should be within error bounds of the predicted value based on the previous values. Once the template of the DOA angles of the leading target is developed, it is used to predict the DOA angle tracks of the remaining targets. In order to generate the tracks for the remaining targets, a track is established if the angles correspond to the initial track values of the first target. Second the time delay between the first track and the remaining tracks are estimated at the highest correlation points between the first track and the remaining tracks. As the vehicles move at different speeds the tracks either compress or expand depending on whether a target is moving fast or slow compared to the first target. The expansion and compression ratios are estimated and used to estimate the predicted DOA angle values of the remaining targets. Based on these predicted DOA angles of the remaining targets the DOA angles obtained from the MVDR or Incoherent MUSIC will be appropriately assigned to proper tracks. Several other rules were developed to avoid mixing the tracks. The algorithm is tested on data collected at Aberdeen Proving Ground with a convoy of 3, 4 and 5 vehicles. Some of the vehicles are tracked and some are wheeled vehicles. The tracking algorithm results are found to be good. The results will be presented at the conference and in the paper.

Research on infrared small-target tracking technology under complex background

Science.gov (United States)

Liu, Lei; Wang, Xin; Chen, Jilu; Pan, Tao

2012-10-01

In this paper, some basic principles and the implementing flow charts of a series of algorithms for target tracking are described. On the foundation of above works, a moving target tracking software base on the OpenCV is developed by the software developing platform MFC. Three kinds of tracking algorithms are integrated in this software. These two tracking algorithms are Kalman Filter tracking method and Camshift tracking method. In order to explain the software clearly, the framework and the function are described in this paper. At last, the implementing processes and results are analyzed, and those algorithms for tracking targets are evaluated from the two aspects of subjective and objective. This paper is very significant in the application of the infrared target tracking technology.

Node Depth Adjustment Based Target Tracking in UWSNs Using Improved Harmony Search

Directory of Open Access Journals (Sweden)

Meiqin Liu

2017-12-01

Full Text Available Underwater wireless sensor networks (UWSNs can provide a promising solution to underwater target tracking. Due to the limited computation and bandwidth resources, only a small part of nodes are selected to track the target at each interval. How to improve tracking accuracy with a small number of nodes is a key problem. In recent years, a node depth adjustment system has been developed and applied to issues of network deployment and routing protocol. As far as we know, all existing tracking schemes keep underwater nodes static or moving with water flow, and node depth adjustment has not been utilized for underwater target tracking yet. This paper studies node depth adjustment method for target tracking in UWSNs. Firstly, since a Fisher Information Matrix (FIM can quantify the estimation accuracy, its relation to node depth is derived as a metric. Secondly, we formulate the node depth adjustment as an optimization problem to determine moving depth of activated node, under the constraint of moving range, the value of FIM is used as objective function, which is aimed to be minimized over moving distance of nodes. Thirdly, to efficiently solve the optimization problem, an improved Harmony Search (HS algorithm is proposed, in which the generating probability is modified to improve searching speed and accuracy. Finally, simulation results are presented to verify performance of our scheme.

Straight-Line Target Tracking for Unmanned Surface Vehicles

Directory of Open Access Journals (Sweden)

Morten Breivik

2008-10-01

Full Text Available This paper considers the subject of straight-line target tracking for unmanned surface vehicles (USVs. Target-tracking represents motion control scenarios where no information about the target behavior is known in advance, i.e., the path that the target traverses is not defined apriori. Specifically, this work presents the design of a motion control system which enables an underactuated USV to track a target that moves in a straight line at high speed. The motion control system employs a guidance principle originally developed for interceptor missiles, as well as a novel velocity controller inspired by maneuverability and agility concepts found in fighter aircraft literature. The performance of the suggested design is illustrated through full-scale USV experiments in the Trondheimsfjord.

A game theory approach to target tracking in sensor networks.

Science.gov (United States)

Gu, Dongbing

2011-02-01

In this paper, we investigate a moving-target tracking problem with sensor networks. Each sensor node has a sensor to observe the target and a processor to estimate the target position. It also has wireless communication capability but with limited range and can only communicate with neighbors. The moving target is assumed to be an intelligent agent, which is "smart" enough to escape from the detection by maximizing the estimation error. This adversary behavior makes the target tracking problem more difficult. We formulate this target estimation problem as a zero-sum game in this paper and use a minimax filter to estimate the target position. The minimax filter is a robust filter that minimizes the estimation error by considering the worst case noise. Furthermore, we develop a distributed version of the minimax filter for multiple sensor nodes. The distributed computation is implemented via modeling the information received from neighbors as measurements in the minimax filter. The simulation results show that the target tracking algorithm proposed in this paper provides a satisfactory result.

Adaptive Moving Object Tracking Integrating Neural Networks And Intelligent Processing

Science.gov (United States)

Lee, James S. J.; Nguyen, Dziem D.; Lin, C.

1989-03-01

A real-time adaptive scheme is introduced to detect and track moving objects under noisy, dynamic conditions including moving sensors. This approach integrates the adaptiveness and incremental learning characteristics of neural networks with intelligent reasoning and process control. Spatiotemporal filtering is used to detect and analyze motion, exploiting the speed and accuracy of multiresolution processing. A neural network algorithm constitutes the basic computational structure for classification. A recognition and learning controller guides the on-line training of the network, and invokes pattern recognition to determine processing parameters dynamically and to verify detection results. A tracking controller acts as the central control unit, so that tracking goals direct the over-all system. Performance is benchmarked against the Widrow-Hoff algorithm, for target detection scenarios presented in diverse FLIR image sequences. Efficient algorithm design ensures that this recognition and control scheme, implemented in software and commercially available image processing hardware, meets the real-time requirements of tracking applications.

Super-resolution imaging applied to moving object tracking

Science.gov (United States)

Swalaganata, Galandaru; Ratna Sulistyaningrum, Dwi; Setiyono, Budi

2017-10-01

Moving object tracking in a video is a method used to detect and analyze changes that occur in an object that being observed. Visual quality and the precision of the tracked target are highly wished in modern tracking system. The fact that the tracked object does not always seem clear causes the tracking result less precise. The reasons are low quality video, system noise, small object, and other factors. In order to improve the precision of the tracked object especially for small object, we propose a two step solution that integrates a super-resolution technique into tracking approach. First step is super-resolution imaging applied into frame sequences. This step was done by cropping the frame in several frame or all of frame. Second step is tracking the result of super-resolution images. Super-resolution image is a technique to obtain high-resolution images from low-resolution images. In this research single frame super-resolution technique is proposed for tracking approach. Single frame super-resolution was a kind of super-resolution that it has the advantage of fast computation time. The method used for tracking is Camshift. The advantages of Camshift was simple calculation based on HSV color that use its histogram for some condition and color of the object varies. The computational complexity and large memory requirements required for the implementation of super-resolution and tracking were reduced and the precision of the tracked target was good. Experiment showed that integrate a super-resolution imaging into tracking technique can track the object precisely with various background, shape changes of the object, and in a good light conditions.

A lightweight target-tracking scheme using wireless sensor network

International Nuclear Information System (INIS)

Kuang, Xing-hong; Shao, Hui-he; Feng, Rui

2008-01-01

This paper describes a lightweight target-tracking scheme using wireless sensor network, where randomly distributed sensor nodes take responsibility for tracking the moving target based on the acoustic sensing signal. At every localization interval, a backoff timer algorithm is performed to elect the leader node and determine the transmission order of the localization nodes. An adaptive active region size algorithm based on the node density is proposed to select the optimal nodes taking part in localization. An improved particle filter algorithm performed by the leader node estimates the target state based on the selected nodes' acoustic energy measurements. Some refinements such as optimal linear combination algorithm, residual resampling algorithm, Markov chain Monte Carlo method are introduced in the scheme to improve the tracking performance. Simulation results validate the efficiency of the proposed tracking scheme

Deployment Design of Wireless Sensor Network for Simple Multi-Point Surveillance of a Moving Target

Science.gov (United States)

Tsukamoto, Kazuya; Ueda, Hirofumi; Tamura, Hitomi; Kawahara, Kenji; Oie, Yuji

2009-01-01

In this paper, we focus on the problem of tracking a moving target in a wireless sensor network (WSN), in which the capability of each sensor is relatively limited, to construct large-scale WSNs at a reasonable cost. We first propose two simple multi-point surveillance schemes for a moving target in a WSN and demonstrate that one of the schemes can achieve high tracking probability with low power consumption. In addition, we examine the relationship between tracking probability and sensor density through simulations, and then derive an approximate expression representing the relationship. As the results, we present guidelines for sensor density, tracking probability, and the number of monitoring sensors that satisfy a variety of application demands. PMID:22412326

Efficient characterization of labeling uncertainty in closely-spaced targets tracking

NARCIS (Netherlands)

Moreno Leon, Carlos; Moreno Leon, Carlos; Driessen, Hans; Mandal, Pranab K.

2016-01-01

In this paper we propose a novel solution to the labeled multi-target tracking problem. The method presented is specially effective in scenarios where the targets have once moved in close proximity. When this is the case, disregarding the labeling uncertainty present in a solution (after the targets

TRAX - Real-World Tracking of Moving Objects

DEFF Research Database (Denmark)

Jensen, Christian Søndergaard; Pakalnis, Stardas

2007-01-01

accuracy. This paper presents the TRAX tracking system that supports several techniques capable of tracking the current positions of moving objects with guaranteed accuracies at low update and communication costs in real-world settings. The techniques are readily relevant for practical applications......, but they also have implications for continued research. The tracking techniques offer a realistic setting for existing query processing techniques that assume that it is possible to always know the exact positions of moving objects. The techniques enable studies of trade-offs between querying and update...

Learning the trajectory of a moving visual target and evolution of its tracking in the monkey

Science.gov (United States)

Bourrelly, Clara; Quinet, Julie; Cavanagh, Patrick

2016-01-01

An object moving in the visual field triggers a saccade that brings its image onto the fovea. It is followed by a combination of slow eye movements and catch-up saccades that try to keep the target image on the fovea as long as possible. The accuracy of this ability to track the “here-and-now” location of a visual target contrasts with the spatiotemporally distributed nature of its encoding in the brain. We show in six experimentally naive monkeys how this performance is acquired and gradually evolves during successive daily sessions. During the early exposure, the tracking is mostly saltatory, made of relatively large saccades separated by low eye velocity episodes, demonstrating that accurate (here and now) pursuit is not spontaneous and that gaze direction lags behind its location most of the time. Over the sessions, while the pursuit velocity is enhanced, the gaze is more frequently directed toward the current target location as a consequence of a 25% reduction in the number of catch-up saccades and a 37% reduction in size (for the first saccade). This smoothing is observed at several scales: during the course of single trials, across the set of trials within a session, and over successive sessions. We explain the neurophysiological processes responsible for this combined evolution of saccades and pursuit in the absence of stringent training constraints. More generally, our study shows that the oculomotor system can be used to discover the neural mechanisms underlying the ability to synchronize a motor effector with a dynamic external event. PMID:27683886

Fusion-based multi-target tracking and localization for intelligent surveillance systems

Science.gov (United States)

Rababaah, Haroun; Shirkhodaie, Amir

2008-04-01

In this paper, we have presented two approaches addressing visual target tracking and localization in complex urban environment. The two techniques presented in this paper are: fusion-based multi-target visual tracking, and multi-target localization via camera calibration. For multi-target tracking, the data fusion concepts of hypothesis generation/evaluation/selection, target-to-target registration, and association are employed. An association matrix is implemented using RGB histograms for associated tracking of multi-targets of interests. Motion segmentation of targets of interest (TOI) from the background was achieved by a Gaussian Mixture Model. Foreground segmentation, on other hand, was achieved by the Connected Components Analysis (CCA) technique. The tracking of individual targets was estimated by fusing two sources of information, the centroid with the spatial gating, and the RGB histogram association matrix. The localization problem is addressed through an effective camera calibration technique using edge modeling for grid mapping (EMGM). A two-stage image pixel to world coordinates mapping technique is introduced that performs coarse and fine location estimation of moving TOIs. In coarse estimation, an approximate neighborhood of the target position is estimated based on nearest 4-neighbor method, and in fine estimation, we use Euclidean interpolation to localize the position within the estimated four neighbors. Both techniques were tested and shown reliable results for tracking and localization of Targets of interests in complex urban environment.

A parallel spatiotemporal saliency and discriminative online learning method for visual target tracking in aerial videos.

Science.gov (United States)

Aghamohammadi, Amirhossein; Ang, Mei Choo; A Sundararajan, Elankovan; Weng, Ng Kok; Mogharrebi, Marzieh; Banihashem, Seyed Yashar

2018-01-01

Visual tracking in aerial videos is a challenging task in computer vision and remote sensing technologies due to appearance variation difficulties. Appearance variations are caused by camera and target motion, low resolution noisy images, scale changes, and pose variations. Various approaches have been proposed to deal with appearance variation difficulties in aerial videos, and amongst these methods, the spatiotemporal saliency detection approach reported promising results in the context of moving target detection. However, it is not accurate for moving target detection when visual tracking is performed under appearance variations. In this study, a visual tracking method is proposed based on spatiotemporal saliency and discriminative online learning methods to deal with appearance variations difficulties. Temporal saliency is used to represent moving target regions, and it was extracted based on the frame difference with Sauvola local adaptive thresholding algorithms. The spatial saliency is used to represent the target appearance details in candidate moving regions. SLIC superpixel segmentation, color, and moment features can be used to compute feature uniqueness and spatial compactness of saliency measurements to detect spatial saliency. It is a time consuming process, which prompted the development of a parallel algorithm to optimize and distribute the saliency detection processes that are loaded into the multi-processors. Spatiotemporal saliency is then obtained by combining the temporal and spatial saliencies to represent moving targets. Finally, a discriminative online learning algorithm was applied to generate a sample model based on spatiotemporal saliency. This sample model is then incrementally updated to detect the target in appearance variation conditions. Experiments conducted on the VIVID dataset demonstrated that the proposed visual tracking method is effective and is computationally efficient compared to state-of-the-art methods.

Pilots' Attention Distributions Between Chasing a Moving Target and a Stationary Target.

Science.gov (United States)

Li, Wen-Chin; Yu, Chung-San; Braithwaite, Graham; Greaves, Matthew

2016-12-01

Attention plays a central role in cognitive processing; ineffective attention may induce accidents in flight operations. The objective of the current research was to examine military pilots' attention distributions between chasing a moving target and a stationary target. In the current research, 37 mission-ready F-16 pilots participated. Subjects' eye movements were collected by a portable head-mounted eye-tracker during tactical training in a flight simulator. The scenarios of chasing a moving target (air-to-air) and a stationary target (air-to-surface) consist of three operational phases: searching, aiming, and lock-on to the targets. The findings demonstrated significant differences in pilots' percentage of fixation during the searching phase between air-to-air (M = 37.57, SD = 5.72) and air-to-surface (M = 33.54, SD = 4.68). Fixation duration can indicate pilots' sustained attention to the trajectory of a dynamic target during air combat maneuvers. Aiming at the stationary target resulted in larger pupil size (M = 27,105, SD = 6565), reflecting higher cognitive loading than aiming at the dynamic target (M = 23,864, SD = 8762). Pilots' visual behavior is not only closely related to attention distribution, but also significantly associated with task characteristics. Military pilots demonstrated various visual scan patterns for searching and aiming at different types of targets based on the research settings of a flight simulator. The findings will facilitate system designers' understanding of military pilots' cognitive processes during tactical operations. They will assist human-centered interface design to improve pilots' situational awareness. The application of an eye-tracking device integrated with a flight simulator is a feasible and cost-effective intervention to improve the efficiency and safety of tactical training.Li W-C, Yu C-S, Braithwaite G, Greaves M. Pilots' attention distributions between chasing a moving target and a stationary target. Aerosp Med

Dazzle camouflage, target tracking, and the confusion effect.

Science.gov (United States)

Hogan, Benedict G; Cuthill, Innes C; Scott-Samuel, Nicholas E

2016-01-01

The influence of coloration on the ecology and evolution of moving animals in groups is poorly understood. Animals in groups benefit from the "confusion effect," where predator attack success is reduced with increasing group size or density. This is thought to be due to a sensory bottleneck: an increase in the difficulty of tracking one object among many. Motion dazzle camouflage has been hypothesized to disrupt accurate perception of the trajectory or speed of an object or animal. The current study investigates the suggestion that dazzle camouflage may enhance the confusion effect. Utilizing a computer game style experiment with human predators, we found that when moving in groups, targets with stripes parallel to the targets' direction of motion interact with the confusion effect to a greater degree, and are harder to track, than those with more conventional background matching patterns. The findings represent empirical evidence that some high-contrast patterns may benefit animals in groups. The results also highlight the possibility that orientation and turning may be more relevant in the mechanisms of dazzle camouflage than previously recognized.

Real-time non-rigid target tracking for ultrasound-guided clinical interventions

NARCIS (Netherlands)

Zachiu, Cornel; Ries, Mario G; Ramaekers, Pascal; Guey, Jean-Luc; Moonen, Chrit T W; de Senneville, Baudouin Denis

2017-01-01

Biological motion is a problem for non- or mini-invasive interventions when conducted in mobile/deformable organs due to the targeted pathology moving/deforming with the organ. This may lead to high miss rates and/or incomplete treatment of the pathology. Therefore, real-time tracking of the target

Interacting with target tracking algorithms in a gaze-enhanced motion video analysis system

Science.gov (United States)

Hild, Jutta; Krüger, Wolfgang; Heinze, Norbert; Peinsipp-Byma, Elisabeth; Beyerer, Jürgen

2016-05-01

Motion video analysis is a challenging task, particularly if real-time analysis is required. It is therefore an important issue how to provide suitable assistance for the human operator. Given that the use of customized video analysis systems is more and more established, one supporting measure is to provide system functions which perform subtasks of the analysis. Recent progress in the development of automated image exploitation algorithms allow, e.g., real-time moving target tracking. Another supporting measure is to provide a user interface which strives to reduce the perceptual, cognitive and motor load of the human operator for example by incorporating the operator's visual focus of attention. A gaze-enhanced user interface is able to help here. This work extends prior work on automated target recognition, segmentation, and tracking algorithms as well as about the benefits of a gaze-enhanced user interface for interaction with moving targets. We also propose a prototypical system design aiming to combine both the qualities of the human observer's perception and the automated algorithms in order to improve the overall performance of a real-time video analysis system. In this contribution, we address two novel issues analyzing gaze-based interaction with target tracking algorithms. The first issue extends the gaze-based triggering of a target tracking process, e.g., investigating how to best relaunch in the case of track loss. The second issue addresses the initialization of tracking algorithms without motion segmentation where the operator has to provide the system with the object's image region in order to start the tracking algorithm.

A parallel spatiotemporal saliency and discriminative online learning method for visual target tracking in aerial videos

Science.gov (United States)

2018-01-01

Visual tracking in aerial videos is a challenging task in computer vision and remote sensing technologies due to appearance variation difficulties. Appearance variations are caused by camera and target motion, low resolution noisy images, scale changes, and pose variations. Various approaches have been proposed to deal with appearance variation difficulties in aerial videos, and amongst these methods, the spatiotemporal saliency detection approach reported promising results in the context of moving target detection. However, it is not accurate for moving target detection when visual tracking is performed under appearance variations. In this study, a visual tracking method is proposed based on spatiotemporal saliency and discriminative online learning methods to deal with appearance variations difficulties. Temporal saliency is used to represent moving target regions, and it was extracted based on the frame difference with Sauvola local adaptive thresholding algorithms. The spatial saliency is used to represent the target appearance details in candidate moving regions. SLIC superpixel segmentation, color, and moment features can be used to compute feature uniqueness and spatial compactness of saliency measurements to detect spatial saliency. It is a time consuming process, which prompted the development of a parallel algorithm to optimize and distribute the saliency detection processes that are loaded into the multi-processors. Spatiotemporal saliency is then obtained by combining the temporal and spatial saliencies to represent moving targets. Finally, a discriminative online learning algorithm was applied to generate a sample model based on spatiotemporal saliency. This sample model is then incrementally updated to detect the target in appearance variation conditions. Experiments conducted on the VIVID dataset demonstrated that the proposed visual tracking method is effective and is computationally efficient compared to state-of-the-art methods. PMID:29438421

Spot Weight Adaptation for Moving Target in Spot Scanning Proton Therapy.

Science.gov (United States)

Morel, Paul; Wu, Xiaodong; Blin, Guillaume; Vialette, Stéphane; Flynn, Ryan; Hyer, Daniel; Wang, Dongxu

2015-01-01

This study describes a real-time spot weight adaptation method in spot-scanning proton therapy for moving target or moving patient, so that the resultant dose distribution closely matches the planned dose distribution. The method proposed in this study adapts the weight (MU) of the delivering pencil beam to that of the target spot; it will actually hit during patient/target motion. The target spot that a certain delivering pencil beam may hit relies on patient monitoring and/or motion modeling using four-dimensional (4D) CT. After the adapted delivery, the required total weight [Monitor Unit (MU)] for this target spot is then subtracted from the planned value. With continuous patient motion and continuous spot scanning, the planned doses to all target spots will eventually be all fulfilled. In a proof-of-principle test, a lung case was presented with realistic temporal and motion parameters; the resultant dose distribution using spot weight adaptation was compared to that without using this method. The impact of the real-time patient/target position tracking or prediction was also investigated. For moderate motion (i.e., mean amplitude 0.5 cm), D95% to the planning target volume (PTV) was only 81.5% of the prescription (RX) dose; with spot weight adaptation PTV D95% achieves 97.7% RX. For large motion amplitude (i.e., 1.5 cm), without spot weight adaptation PTV D95% is only 42.9% of RX; with spot weight adaptation, PTV D95% achieves 97.7% RX. Larger errors in patient/target position tracking or prediction led to worse final target coverage; an error of 3 mm or smaller in patient/target position tracking is preferred. The proposed spot weight adaptation method was able to deliver the planned dose distribution and maintain target coverage when patient motion was involved. The successful implementation of this method would rely on accurate monitoring or prediction of patient/target motion.

Spot Weight Adaptation for Moving Target in Spot Scanning Proton Therapy

Directory of Open Access Journals (Sweden)

Paul eMorel

2015-05-01

Full Text Available Purpose: This study describes a real-time spot weight adaptation method in spot-scanning proton therapy for moving target or moving patient, so that the resultant dose distribution closely matches the planned dose distribution. Materials and Methods: The method proposed in this study adapts the weight (MU of the delivering pencil beam to that of the target spot it will actually hit during patient/target motion. The target spot a certain delivering pencil beam may hit relies on patient monitoring and/or motion modeling using four-dimensional (4D CT. After the adapted delivery, the required total weight (MU for this target spot is then subtracted from the planned value. With continuous patient motion and continuous spot scanning, the planned doses to all target spots will eventually be all fulfilled. In a proof-of-principle test, a lung case was presented with realistic temporal and motion parameters; the resultant dose distribution using spot weight adaptation was compared to that without using this method. The impact of the real-time patient/target position tracking or prediction was also investigated.Results: For moderate motion (i.e., mean amplitude 0.5 cm, D95% to the planning target volume (PTV was only 81.5% of the prescription (RX dose; with spot weight adaptation PTV D95% achieves 97.7%RX. For large motion amplitude (i.e., 1.5 cm, without spot weight adaptation PTV D95% is only 42.9% of RX; with spot weight adaptation, PTV D95% achieves 97.7%RX. Larger errors in patient/target position tracking or prediction led to worse final target coverage; an error of 3mm or smaller in patient/target position tracking is preferred. Conclusion: The proposed spot weight adaptation method was able to deliver the planned dose distribution and maintain target coverage when patient motion was involved. The successful implementation of this method would rely on accurate monitoring or prediction of patient/target motion.

A-Track: Detecting Moving Objects in FITS images

Science.gov (United States)

Atay, T.; Kaplan, M.; Kilic, Y.; Karapinar, N.

2017-04-01

A-Track is a fast, open-source, cross-platform pipeline for detecting moving objects (asteroids and comets) in sequential telescope images in FITS format. The moving objects are detected using a modified line detection algorithm.

Loss of positional information when tracking multiple moving dots: the role of visual memory.

Science.gov (United States)

Narasimhan, Sathyasri; Tripathy, Srimant P; Barrett, Brendan T

2009-01-01

Pylyshyn, Z.W. and Storm, R.W. (1988) (Tracking multiple independent targets: Evidence for a parallel tracking mechanism. Spatial Vision, 3(3), 179-197) proposed that human observers could simultaneously track up to five dots when presented with an array of dots moving in a random manner. In contrast, Tripathy, S.P., and Barrett, B.T. (2004) (Severe loss of positional information when detecting deviations in multiple trajectories. Journal of Vision, 4(12):4, 1020-1043, http://journalofvision.org/4/14/4/, doi: 10.1167/4.12.4) showed that when a threshold paradigm was employed, observers' ability to track deviations in straight-line trajectories is severely compromised when attending to two or more dots. In this study we present a series of four experiments that investigates the role of attention and visual memory while tracking deviations in multiple trajectories using a threshold paradigm. Our stimuli consisted of several linear, non-parallel, left-to-right trajectories, each moving at the same speed. At the trajectory mid-point (reached simultaneously by all dots), one of the dots (target) deviated clockwise or counter-clockwise. The observers' task was to identify the direction of deviation. The target trajectory was cued in the second half of the trial either by disappearance of distractors at the monitor's mid-line (Experiment 1) or by means of a change in colour of the target (Experiment 2); in both cases deviation thresholds rose steeply when the number of distractor trajectories was increased from 0 (typical threshold approximately 2 degrees) to 3 (typical threshold>20 degrees). When all the trajectories were presented statically in a single frame (Experiment 3), thresholds for identifying the orientation change of the target trajectory remained relatively unchanged as the number of distractor trajectories was increased. When a temporal delay of a few hundred milliseconds was introduced between the first and second halves of trajectories (Experiment 4

Low-resolution Airborne Radar Air/ground Moving Target Classification and Recognition

Directory of Open Access Journals (Sweden)

Wang Fu-you

2014-10-01

Full Text Available Radar Target Recognition (RTR is one of the most important needs of modern and future airborne surveillance radars, and it is still one of the key technologies of radar. The majority of present algorithms are based on wide-band radar signal, which not only needs high performance radar system and high target Signal-to-Noise Ratio (SNR, but also is sensitive to angle between radar and target. Low-Resolution Airborne Surveillance Radar (LRASR in downward-looking mode, slow flying aircraft and ground moving truck have similar Doppler velocity and Radar Cross Section (RCS, leading to the problem that LRASR air/ground moving targets can not be distinguished, which also disturbs detection, tracking, and classification of low altitude slow flying aircraft to solve these issues, an algorithm based on narrowband fractal feature and phase modulation feature is presented for LRASR air/ground moving targets classification. Real measured data is applied to verify the algorithm, the classification results validate the proposed method, helicopters and truck can be well classified, the average discrimination rate is more than 89% when SNR ≥ 15 dB.

Error Analysis of Fast Moving Target Geo-location in Wide Area Surveillance Ground Moving Target Indication Mode

Directory of Open Access Journals (Sweden)

Zheng Shi-chao

2013-12-01

Full Text Available As an important mode in airborne radar systems, Wide Area Surveillance Ground Moving Target Indication (WAS-GMTI mode has the ability of monitoring a large area in a short time, and then the detected moving targets can be located quickly. However, in real environment, many factors introduce considerable errors into the location of moving targets. In this paper, a fast location method based on the characteristics of the moving targets in WAS-GMTI mode is utilized. And in order to improve the location performance, those factors that introduce location errors are analyzed and moving targets are relocated. Finally, the analysis of those factors is proved to be reasonable by simulation and real data experiments.

Kinect-Based Moving Human Tracking System with Obstacle Avoidance

Directory of Open Access Journals (Sweden)

Abdel Mehsen Ahmad

2017-04-01

Full Text Available This paper is an extension of work originally presented and published in IEEE International Multidisciplinary Conference on Engineering Technology (IMCET. This work presents a design and implementation of a moving human tracking system with obstacle avoidance. The system scans the environment by using Kinect, a 3D sensor, and tracks the center of mass of a specific user by using Processing, an open source computer programming language. An Arduino microcontroller is used to drive motors enabling it to move towards the tracked user and avoid obstacles hampering the trajectory. The implemented system is tested under different lighting conditions and the performance is analyzed using several generated depth images.

FDTD Seismic Simulation of Moving Tracked Vehicle

National Research Council Canada - National Science Library

Ketcham, Stephen

2000-01-01

This paper describes the utility of a large finite-difference time domain (FDTD) simulation of seismic wave propagation from a spatially and time varying source that generically represents a moving tracked vehicle...

Tracking moving identities: after attending the right location, the identity does not come for free.

Directory of Open Access Journals (Sweden)

Yaïr Pinto

Full Text Available Although tracking identical moving objects has been studied since the 1980's, only recently the study into tracking moving objects with distinct identities has started (referred to as Multiple Identity Tracking, MIT. So far, only behavioral studies into MIT have been undertaken. These studies have left a fundamental question regarding MIT unanswered, is MIT a one-stage or a two-stage process? According to the one-stage model, after a location has been attended, the identity is released without effort. However, according to the two-stage model, there are two effortful stages in MIT, attending to a location, and attending to the identity of the object at that location. In the current study we investigated this question by measuring brain activity in response to tracking familiar and unfamiliar targets. Familiarity is known to automate effortful processes, so if attention to identify the object is needed, this should become easier. However, if no such attention is needed, familiarity can only affect other processes (such as memory for the target set. Our results revealed that on unfamiliar trials neural activity was higher in both attentional networks, and visual identification networks. These results suggest that familiarity in MIT automates attentional identification processes, thus suggesting that attentional identification is needed in MIT. This then would imply that MIT is essentially a two-stage process, since after attending the location, the identity does not seem to come for free.

An indirect adaptive neural control of a visual-based quadrotor robot for pursuing a moving target.

Science.gov (United States)

Shirzadeh, Masoud; Amirkhani, Abdollah; Jalali, Aliakbar; Mosavi, Mohammad R

2015-11-01

This paper aims to use a visual-based control mechanism to control a quadrotor type aerial robot which is in pursuit of a moving target. The nonlinear nature of a quadrotor, on the one hand, and the difficulty of obtaining an exact model for it, on the other hand, constitute two serious challenges in designing a controller for this UAV. A potential solution for such problems is the use of intelligent control methods such as those that rely on artificial neural networks and other similar approaches. In addition to the two mentioned problems, another problem that emerges due to the moving nature of a target is the uncertainty that exists in the target image. By employing an artificial neural network with a Radial Basis Function (RBF) an indirect adaptive neural controller has been designed for a quadrotor robot in search of a moving target. The results of the simulation for different paths show that the quadrotor has efficiently tracked the moving target. Copyright © 2015 ISA. Published by Elsevier Ltd. All rights reserved.

Target Tracking in 3-D Using Estimation Based Nonlinear Control Laws for UAVs

Directory of Open Access Journals (Sweden)

Mousumi Ahmed

2016-02-01

Full Text Available This paper presents an estimation based backstepping like control law design for an Unmanned Aerial Vehicle (UAV to track a moving target in 3-D space. A ground-based sensor or an onboard seeker antenna provides range, azimuth angle, and elevation angle measurements to a chaser UAV that implements an extended Kalman filter (EKF to estimate the full state of the target. A nonlinear controller then utilizes this estimated target state and the chaser’s state to provide speed, flight path, and course/heading angle commands to the chaser UAV. Tracking performance with respect to measurement uncertainty is evaluated for three cases: (1 stationary white noise; (2 stationary colored noise and (3 non-stationary (range correlated white noise. Furthermore, in an effort to improve tracking performance, the measurement model is made more realistic by taking into consideration range-dependent uncertainties in the measurements, i.e., as the chaser closes in on the target, measurement uncertainties are reduced in the EKF, thus providing the UAV with more accurate control commands. Simulation results for these cases are shown to illustrate target state estimation and trajectory tracking performance.

Study on the Detection of Moving Target in the Mining Method Based on Hybrid Algorithm for Sports Video Analysis

Directory of Open Access Journals (Sweden)

Huang Tian

2014-10-01

Full Text Available Moving object detection and tracking is the computer vision and image processing is a hot research direction, based on the analysis of the moving target detection and tracking algorithm in common use, focus on the sports video target tracking non rigid body. In sports video, non rigid athletes often have physical deformation in the process of movement, and may be associated with the occurrence of moving target under cover. Media data is surging to fast search and query causes more difficulties in data. However, the majority of users want to be able to quickly from the multimedia data to extract the interested content and implicit knowledge (concepts, rules, rules, models and correlation, retrieval and query quickly to take advantage of them, but also can provide the decision support problem solving hierarchy. Based on the motion in sport video object as the object of study, conducts the system research from the theoretical level and technical framework and so on, from the layer by layer mining between low level motion features to high-level semantic motion video, not only provides support for users to find information quickly, but also can provide decision support for the user to solve the problem.

Performance evaluation software moving object detection and tracking in videos

CERN Document Server

Karasulu, Bahadir

2013-01-01

Performance Evaluation Software: Moving Object Detection and Tracking in Videos introduces a software approach for the real-time evaluation and performance comparison of the methods specializing in moving object detection and/or tracking (D&T) in video processing. Digital video content analysis is an important item for multimedia content-based indexing (MCBI), content-based video retrieval (CBVR) and visual surveillance systems. There are some frequently-used generic algorithms for video object D&T in the literature, such as Background Subtraction (BS), Continuously Adaptive Mean-shift (CMS),

Detection of Moving Targets Using Soliton Resonance Effect

Science.gov (United States)

Kulikov, Igor K.; Zak, Michail

2013-01-01

The objective of this research was to develop a fundamentally new method for detecting hidden moving targets within noisy and cluttered data-streams using a novel "soliton resonance" effect in nonlinear dynamical systems. The technique uses an inhomogeneous Korteweg de Vries (KdV) equation containing moving-target information. Solution of the KdV equation will describe a soliton propagating with the same kinematic characteristics as the target. The approach uses the time-dependent data stream obtained with a sensor in form of the "forcing function," which is incorporated in an inhomogeneous KdV equation. When a hidden moving target (which in many ways resembles a soliton) encounters the natural "probe" soliton solution of the KdV equation, a strong resonance phenomenon results that makes the location and motion of the target apparent. Soliton resonance method will amplify the moving target signal, suppressing the noise. The method will be a very effective tool for locating and identifying diverse, highly dynamic targets with ill-defined characteristics in a noisy environment. The soliton resonance method for the detection of moving targets was developed in one and two dimensions. Computer simulations proved that the method could be used for detection of singe point-like targets moving with constant velocities and accelerations in 1D and along straight lines or curved trajectories in 2D. The method also allows estimation of the kinematic characteristics of moving targets, and reconstruction of target trajectories in 2D. The method could be very effective for target detection in the presence of clutter and for the case of target obscurations.

Slower resting alpha frequency is associated with superior localisation of moving targets.

Science.gov (United States)

Howard, Christina J; Arnold, Craig P A; Belmonte, Matthew K

2017-10-01

We examined the neurophysiological underpinnings of individual differences in the ability to maintain up-to-date representations of the positions of moving objects. In two experiments similar to the multiple object tracking (MOT) task, we asked observers to monitor continuously one or several targets as they moved unpredictably for a semi-random period. After all objects disappeared, observers were immediately prompted to report the perceived final position of one queried target. Precision of these position reports declined with attentional load, and reports tended to best resemble positions occupied by the queried target between 0 and 30ms in the past. Measurement of event-related potentials showed a contralateral delay activity over occipital scalp, maximal in the right hemisphere. The peak power-spectral frequency of observers' eyes-closed resting occipital alpha oscillations reliably predicted performance, such that lower-frequency alpha was associated with superior spatial localisation. Slower resting alpha might be associated with a cognitive style that depends less on memory-related processing and instead emphasises attention to changing stimuli. Crown Copyright © 2017. Published by Elsevier Inc. All rights reserved.

Moving Target Detection With Compact Laser Doppler Radar

Science.gov (United States)

Sepp, G.; Breining, A.; Eisfeld, W.; Knopp, R.; Lill, E.; Wagner, D.

1989-12-01

This paper describes an experimental integrated optronic system for detection and tracking of moving objects. The system is based on a CO2 waveguide laser Doppler ra-dar with homodyne receiver and galvanometer mirror beam scanner. A "hot spot" seeker consisting of a thermal imager with image processor transmits the coordinates of IR-emitting, i.e. potentially powered, objects to the laser radar scanner. The scanner addresses these "hot" locations operating in a large field-of-view (FOV) random ac-cess mode. Hot spots exhibiting a Doppler shifted laser signal are indicated in the thermal image by velocity-to-colour encoded markers. After switching to a small FOV scanning mode, the laser Doppler radar is used to track fast moving objects. Labora-tory and field experiments with moving objects including rotating discs, automobiles and missiles are described.

Techniques for Efficient Tracking of Road-Network-Based Moving Objects

DEFF Research Database (Denmark)

Civilis, Alminas; Jensen, Christian Søndergaard; Saltenis, Simonas

With the continued advances in wireless communications, geo-positioning, and consumer electronics, an infrastructure is emerging that enables location-based services that rely on the tracking of the continuously changing positions of entire populations of service users, termed moving objects....... The main issue considered is how to represent the location of a moving object in a database so that tracking can be done with as few updates as possible. The paper proposes to use the road network within which the objects are assumed to move for predicting their future positions. The paper presents...... algorithms that modify an initial road-network representation, so that it works better as a basis for predicting an object's position; it proposes to use known movement patterns of the object, in the form of routes; and it proposes to use acceleration profiles together with the routes. Using real GPS...

Techniques for efficient road-network-based tracking of moving objects

DEFF Research Database (Denmark)

Civilis, A.; Jensen, Christian Søndergaard; Pakalnis, Stardas

2005-01-01

With the continued advances in wireless communications, geo-positioning, and consumer electronics, an infrastructure is emerging that enables location-based services that rely on the tracking of the continuously changing positions of entire populations of service users, termed moving objects....... The main issue considered is how to represent the location of a moving object in a database so that tracking can be done with as few updates as possible. The paper proposes to use the road network within which the objects are assumed to move for predicting their future positions. The paper presents...... algorithms that modify an initial road-network representation, so that it works better as a basis for predicting an object's position; it proposes to use known movement patterns of the object, in the form of routes; and it proposes to use acceleration profiles together with the routes. Using real GPS...

Hypersonic sliding target tracking in near space

Directory of Open Access Journals (Sweden)

Xiang-yu Zhang

2015-12-01

Full Text Available To improve the tracking accuracy of hypersonic sliding target in near space, the influence of target hypersonic movement on radar detection and tracking is analyzed, and an IMM tracking algorithm is proposed based on radial velocity compensating and cancellation processing of high dynamic biases under the earth centered earth fixed (ECEF coordinate. Based on the analysis of effect of target hypersonic movement, a measurement model is constructed to reduce the filter divergence which is caused by the model mismatch. The high dynamic biases due to the target hypersonic movement are approximately compensated through radial velocity estimation to achieve the hypersonic target tracking at low systematic biases in near space. The high dynamic biases are further eliminated by the cancellation processing of different radars, in which the track association problem can be solved when the dynamic biases are low. An IMM algorithm based on constant acceleration (CA, constant turning (CT and Singer models is used to achieve the hypersonic sliding target tracking in near space. Simulation results show that the target tracking in near space can be achieved more effectively by using the proposed algorithm.

Exploiting target amplitude information to improve multi-target tracking

Science.gov (United States)

Ehrman, Lisa M.; Blair, W. Dale

2006-05-01

Closely-spaced (but resolved) targets pose a challenge for measurement-to-track data association algorithms. Since the Mahalanobis distances between measurements collected on closely-spaced targets and tracks are similar, several elements of the corresponding kinematic measurement-to-track cost matrix are also similar. Lacking any other information on which to base assignments, it is not surprising that data association algorithms make mistakes. One ad hoc approach for mitigating this problem is to multiply the kinematic measurement-to-track likelihoods by amplitude likelihoods. However, this can actually be detrimental to the measurement-to-track association process. With that in mind, this paper pursues a rigorous treatment of the hypothesis probabilities for kinematic measurements and features. Three simple scenarios are used to demonstrate the impact of basing data association decisions on these hypothesis probabilities for Rayleigh, fixed-amplitude, and Rician targets. The first scenario assumes that the tracker carries two tracks but only one measurement is collected. This provides insight into more complex scenarios in which there are fewer measurements than tracks. The second scenario includes two measurements and one track. This extends naturally to the case with more measurements than tracks. Two measurements and two tracks are present in the third scenario, which provides insight into the performance of this method when the number of measurements equals the number of tracks. In all cases, basing data association decisions on the hypothesis probabilities leads to good results.

Postural sway and gaze can track the complex motion of a visual target.

Directory of Open Access Journals (Sweden)

Vassilia Hatzitaki

Full Text Available Variability is an inherent and important feature of human movement. This variability has form exhibiting a chaotic structure. Visual feedback training using regular predictive visual target motions does not take into account this essential characteristic of the human movement, and may result in task specific learning and loss of visuo-motor adaptability. In this study, we asked how well healthy young adults can track visual target cues of varying degree of complexity during whole-body swaying in the Anterior-Posterior (AP and Medio-Lateral (ML direction. Participants were asked to track three visual target motions: a complex (Lorenz attractor, a noise (brown and a periodic (sine moving target while receiving online visual feedback about their performance. Postural sway, gaze and target motion were synchronously recorded and the degree of force-target and gaze-target coupling was quantified using spectral coherence and Cross-Approximate entropy. Analysis revealed that both force-target and gaze-target coupling was sensitive to the complexity of the visual stimuli motions. Postural sway showed a higher degree of coherence with the Lorenz attractor than the brown noise or sinusoidal stimulus motion. Similarly, gaze was more synchronous with the Lorenz attractor than the brown noise and sinusoidal stimulus motion. These results were similar regardless of whether tracking was performed in the AP or ML direction. Based on the theoretical model of optimal movement variability tracking of a complex signal may provide a better stimulus to improve visuo-motor adaptation and learning in postural control.

Underwater Acoustic Target Tracking: A Review

Science.gov (United States)

Han, Ying; Fan, Liying

2018-01-01

Advances in acoustic technology and instrumentation now make it possible to explore marine resources. As a significant component of ocean exploration, underwater acoustic target tracking has aroused wide attention both in military and civil fields. Due to the complexity of the marine environment, numerous techniques have been proposed to obtain better tracking performance. In this paper, we survey over 100 papers ranging from innovative papers to the state-of-the-art in this field to present underwater tracking technologies. Not only the related knowledge of acoustic tracking instrument and tracking progress is clarified in detail, but also a novel taxonomy method is proposed. In this paper, algorithms for underwater acoustic target tracking are classified based on the methods used as: (1) instrument-assisted methods; (2) mode-based methods; (3) tracking optimization methods. These algorithms are compared and analyzed in the aspect of dimensions, numbers, and maneuvering of the tracking target, which is different from other survey papers. Meanwhile, challenges, countermeasures, and lessons learned are illustrated in this paper. PMID:29301318

Heterogeneous CPU-GPU moving targets detection for UAV video

Science.gov (United States)

Li, Maowen; Tang, Linbo; Han, Yuqi; Yu, Chunlei; Zhang, Chao; Fu, Huiquan

2017-07-01

Moving targets detection is gaining popularity in civilian and military applications. On some monitoring platform of motion detection, some low-resolution stationary cameras are replaced by moving HD camera based on UAVs. The pixels of moving targets in the HD Video taken by UAV are always in a minority, and the background of the frame is usually moving because of the motion of UAVs. The high computational cost of the algorithm prevents running it at higher resolutions the pixels of frame. Hence, to solve the problem of moving targets detection based UAVs video, we propose a heterogeneous CPU-GPU moving target detection algorithm for UAV video. More specifically, we use background registration to eliminate the impact of the moving background and frame difference to detect small moving targets. In order to achieve the effect of real-time processing, we design the solution of heterogeneous CPU-GPU framework for our method. The experimental results show that our method can detect the main moving targets from the HD video taken by UAV, and the average process time is 52.16ms per frame which is fast enough to solve the problem.

Ultrasound image based visual servoing for moving target ablation by high intensity focused ultrasound.

Science.gov (United States)

Seo, Joonho; Koizumi, Norihiro; Mitsuishi, Mamoru; Sugita, Naohiko

2017-12-01

Although high intensity focused ultrasound (HIFU) is a promising technology for tumor treatment, a moving abdominal target is still a challenge in current HIFU systems. In particular, respiratory-induced organ motion can reduce the treatment efficiency and negatively influence the treatment result. In this research, we present: (1) a methodology for integration of ultrasound (US) image based visual servoing in a HIFU system; and (2) the experimental results obtained using the developed system. In the visual servoing system, target motion is monitored by biplane US imaging and tracked in real time (40 Hz) by registration with a preoperative 3D model. The distance between the target and the current HIFU focal position is calculated in every US frame and a three-axis robot physically compensates for differences. Because simultaneous HIFU irradiation disturbs US target imaging, a sophisticated interlacing strategy was constructed. In the experiments, respiratory-induced organ motion was simulated in a water tank with a linear actuator and kidney-shaped phantom model. Motion compensation with HIFU irradiation was applied to the moving phantom model. Based on the experimental results, visual servoing exhibited a motion compensation accuracy of 1.7 mm (RMS) on average. Moreover, the integrated system could make a spherical HIFU-ablated lesion in the desired position of the respiratory-moving phantom model. We have demonstrated the feasibility of our US image based visual servoing technique in a HIFU system for moving target treatment. © 2016 The Authors The International Journal of Medical Robotics and Computer Assisted Surgery Published by John Wiley & Sons Ltd.

An Energy-Efficient Target-Tracking Strategy for Mobile Sensor Networks.

Science.gov (United States)

Mahboubi, Hamid; Masoudimansour, Walid; Aghdam, Amir G; Sayrafian-Pour, Kamran

2017-02-01

In this paper, an energy-efficient strategy is proposed for tracking a moving target in an environment with obstacles, using a network of mobile sensors. Typically, the most dominant sources of energy consumption in a mobile sensor network are sensing, communication, and movement. The proposed algorithm first divides the field into a grid of sufficiently small cells. The grid is then represented by a graph whose edges are properly weighted to reflect the energy consumption of sensors. The proposed technique searches for near-optimal locations for the sensors in different time instants to route information from the target to destination, using a shortest path algorithm. Simulations confirm the efficacy of the proposed algorithm.

Impedance modulation and feedback corrections in tracking targets of variable size and frequency.

Science.gov (United States)

Selen, Luc P J; van Dieën, Jaap H; Beek, Peter J

2006-11-01

Humans are able to adjust the accuracy of their movements to the demands posed by the task at hand. The variability in task execution caused by the inherent noisiness of the neuromuscular system can be tuned to task demands by both feedforward (e.g., impedance modulation) and feedback mechanisms. In this experiment, we studied both mechanisms, using mechanical perturbations to estimate stiffness and damping as indices of impedance modulation and submovement scaling as an index of feedback driven corrections. Eight subjects tracked three differently sized targets (0.0135, 0.0270, and 0.0405 rad) moving at three different frequencies (0.20, 0.25, and 0.33 Hz). Movement variability decreased with both decreasing target size and movement frequency, whereas stiffness and damping increased with decreasing target size, independent of movement frequency. These results are consistent with the theory that mechanical impedance acts as a filter of noisy neuromuscular signals but challenge stochastic theories of motor control that do not account for impedance modulation and only partially for feedback control. Submovements during unperturbed cycles were quantified in terms of their gain, i.e., the slope between their duration and amplitude in the speed profile. Submovement gain decreased with decreasing movement frequency and increasing target size. The results were interpreted to imply that submovement gain is related to observed tracking errors and that those tracking errors are expressed in units of target size. We conclude that impedance and submovement gain modulation contribute additively to tracking accuracy.

IFE Target Injection Tracking and Position Prediction Update

International Nuclear Information System (INIS)

Petzoldt, Ronald W.; Jonestrask, Kevin

2005-01-01

To achieve high gain in an inertial fusion energy power plant, driver beams must hit direct drive targets with ±20 μm accuracy (±100 μm for indirect drive). Targets will have to be tracked with even greater accuracy. The conceptual design for our tracking system, which predicts target arrival position and timing based on position measurements outside of the reaction chamber was previously described. The system has been built and has begun tracking targets at the first detector station. Additional detector stations are being modified for increased field of view. After three tracking stations are operational, position predictions at the final station will be compared to position measurements at that station as a measure of target position prediction accuracy.The as-installed design will be described together with initial target tracking and position prediction accuracy results. Design modifications that allow for improved accuracy and/or in-chamber target tracking will also be presented

Mapping and tracking of moving objects in dynamic environments

CSIR Research Space (South Africa)

Pancham, A

2012-10-01

Full Text Available In order for mobile robots to operate in dynamic or real world environments they must be able to localise themselves while building a map of the environment, and detect and track moving objects. This work involves the research and implementation...

Investigation on effect of image lag in fluoroscopic images obtained with a dynamic flat-panel detector (FPD) on accuracy of target tracking in radiotherapy

International Nuclear Information System (INIS)

Tanaka, Rie; Ichikawa, Katsuhiro; Sanada, Sigeru; Mori, Shinichiro; Dobashi, Suguru; Kumagai, Motoki; Minohara, Shinichi; Kawashima, Hiroki

2010-01-01

Real-time tumor tracking in external radiotherapy can be achieved by diagnostic (kV) X-ray imaging with a dynamic flat-panel detector (FPD). The purpose of this study was to address image lag in target tracking and its influence on the accuracy of tumor tracking. Fluoroscopic images were obtained using a direct type of dynamic FPD. Image lag properties were measured without test devices according to IEC 62220-1. Modulation transfer function (MTF) and profile curves were measured on the edges of a moving tungsten plate at movement rate of 10 and 20 mm/s, covering lung tumor movement of normal breathing. A lung tumor and metal sphere with blurred edge due to image lag was simulated using the results and then superimposed on breathing chest radiographs of a patient. The moving target with and without image lag was traced using a template-matching technique. In the results, the image lag for the first frame after X-ray cutoff was 2.0% and decreased to less than 0.1% in the fifth frame. In the measurement of profile curves on the edges of static and moving tungsten material plates, the effect of image lag was seen as blurred edges of the plate. The blurred edges of a moving target were indicated as reduction of MTF. However, the target could be traced within an error of ±5 mm. The results indicated that there was no effect of image lag on target tracking in usual breathing speed in a radiotherapy situation. (author)

Space moving target detection using time domain feature

Science.gov (United States)

Wang, Min; Chen, Jin-yong; Gao, Feng; Zhao, Jin-yu

2018-01-01

The traditional space target detection methods mainly use the spatial characteristics of the star map to detect the targets, which can not make full use of the time domain information. This paper presents a new space moving target detection method based on time domain features. We firstly construct the time spectral data of star map, then analyze the time domain features of the main objects (target, stars and the background) in star maps, finally detect the moving targets using single pulse feature of the time domain signal. The real star map target detection experimental results show that the proposed method can effectively detect the trajectory of moving targets in the star map sequence, and the detection probability achieves 99% when the false alarm rate is about 8×10-5, which outperforms those of compared algorithms.

Real-time non-rigid target tracking for ultrasound-guided clinical interventions

Science.gov (United States)

Zachiu, C.; Ries, M.; Ramaekers, P.; Guey, J.-L.; Moonen, C. T. W.; de Senneville, B. Denis

2017-10-01

Biological motion is a problem for non- or mini-invasive interventions when conducted in mobile/deformable organs due to the targeted pathology moving/deforming with the organ. This may lead to high miss rates and/or incomplete treatment of the pathology. Therefore, real-time tracking of the target anatomy during the intervention would be beneficial for such applications. Since the aforementioned interventions are often conducted under B-mode ultrasound (US) guidance, target tracking can be achieved via image registration, by comparing the acquired US images to a separate image established as positional reference. However, such US images are intrinsically altered by speckle noise, introducing incoherent gray-level intensity variations. This may prove problematic for existing intensity-based registration methods. In the current study we address US-based target tracking by employing the recently proposed EVolution registration algorithm. The method is, by construction, robust to transient gray-level intensities. Instead of directly matching image intensities, EVolution aligns similar contrast patterns in the images. Moreover, the displacement is computed by evaluating a matching criterion for image sub-regions rather than on a point-by-point basis, which typically provides more robust motion estimates. However, unlike similar previously published approaches, which assume rigid displacements in the image sub-regions, the EVolution algorithm integrates the matching criterion in a global functional, allowing the estimation of an elastic dense deformation. The approach was validated for soft tissue tracking under free-breathing conditions on the abdomen of seven healthy volunteers. Contact echography was performed on all volunteers, while three of the volunteers also underwent standoff echography. Each of the two modalities is predominantly specific to a particular type of non- or mini-invasive clinical intervention. The method demonstrated on average an accuracy of�

Computer-aided target tracking in motion analysis studies

Science.gov (United States)

Burdick, Dominic C.; Marcuse, M. L.; Mislan, J. D.

1990-08-01

Motion analysis studies require the precise tracking of reference objects in sequential scenes. In a typical situation, events of interest are captured at high frame rates using special cameras, and selected objects or targets are tracked on a frame by frame basis to provide necessary data for motion reconstruction. Tracking is usually done using manual methods which are slow and prone to error. A computer based image analysis system has been developed that performs tracking automatically. The objective of this work was to eliminate the bottleneck due to manual methods in high volume tracking applications such as the analysis of crash test films for the automotive industry. The system has proven to be successful in tracking standard fiducial targets and other objects in crash test scenes. Over 95 percent of target positions which could be located using manual methods can be tracked by the system, with a significant improvement in throughput over manual methods. Future work will focus on the tracking of clusters of targets and on tracking deformable objects such as airbags.

Camouflage, detection and identification of moving targets.

Science.gov (United States)

Hall, Joanna R; Cuthill, Innes C; Baddeley, Roland; Shohet, Adam J; Scott-Samuel, Nicholas E

2013-05-07

Nearly all research on camouflage has investigated its effectiveness for concealing stationary objects. However, animals have to move, and patterns that only work when the subject is static will heavily constrain behaviour. We investigated the effects of different camouflages on the three stages of predation-detection, identification and capture-in a computer-based task with humans. An initial experiment tested seven camouflage strategies on static stimuli. In line with previous literature, background-matching and disruptive patterns were found to be most successful. Experiment 2 showed that if stimuli move, an isolated moving object on a stationary background cannot avoid detection or capture regardless of the type of camouflage. Experiment 3 used an identification task and showed that while camouflage is unable to slow detection or capture, camouflaged targets are harder to identify than uncamouflaged targets when similar background objects are present. The specific details of the camouflage patterns have little impact on this effect. If one has to move, camouflage cannot impede detection; but if one is surrounded by similar targets (e.g. other animals in a herd, or moving background distractors), then camouflage can slow identification. Despite previous assumptions, motion does not entirely 'break' camouflage.

Measurement of vertical track deflection from a moving rail car.

Science.gov (United States)

2013-02-01

The University of Nebraska has been conducting research sponsored by the Federal Railroad Administrations Office of Research and Development to develop a system that measures vertical track deflection/modulus from a moving rail car. Previous work ...

Satisfaction in motion: Subsequent search misses are more likely in moving search displays.

Science.gov (United States)

Stothart, Cary; Clement, Andrew; Brockmole, James R

2018-02-01

People often conduct visual searches in which multiple targets are possible (e.g., medical X-rays can contain multiple abnormalities). In this type of search, observers are more likely to miss a second target after having found a first one (a subsequent search miss). Recent evidence has suggested that this effect may be due to a depletion of cognitive resources from tracking the identities and locations of found targets. Given that tracking moving objects is resource-demanding, would finding a moving target further increase the chances of missing a subsequent one? To address this question, we had participants search for one or more targets hidden among distractors. Subsequent search misses were more likely when the targets and distractors moved throughout the display than when they remained stationary. However, when the found targets were highlighted in a unique color, subsequent search misses were no more likely in moving displays. Together, these results suggest that the effect of movement is likely due to the increased cognitive demands of tracking moving targets. Overall, our findings reveal that activities that involve searching for moving targets (e.g., driving) are more susceptible to subsequent search misses than are those that involve searching for stationary targets (e.g., baggage screening).

Efficient Tracking of Moving Objects with Precision Guarantees

DEFF Research Database (Denmark)

Civilis, Alminas; Jensen, Christian Søndergaard; Nenortaite, Jovita

2004-01-01

Sustained advances in wireless communications, geo-positioning, and consumer electronics pave the way to a kind of location-based service that relies on the tracking of the continuously changing positions of an entire population of service users. This type of service is characterized by large...... an object is moving. Empirical performance studies based on a real road network and GPS logs from cars are reported....

Tracking integration in concentrating photovoltaics using laterally moving optics.

Science.gov (United States)

Duerr, Fabian; Meuret, Youri; Thienpont, Hugo

2011-05-09

In this work the concept of tracking-integrated concentrating photovoltaics is studied and its capabilities are quantitatively analyzed. The design strategy desists from ideal concentration performance to reduce the external mechanical solar tracking effort in favor of a compact installation, possibly resulting in lower overall cost. The proposed optical design is based on an extended Simultaneous Multiple Surface (SMS) algorithm and uses two laterally moving plano-convex lenses to achieve high concentration over a wide angular range of ±24°. It achieves 500× concentration, outperforming its conventional concentrating photovoltaic counterparts on a polar aligned single axis tracker.

Nonmyopic Sensor Scheduling and its Efficient Implementation for Target Tracking Applications

Directory of Open Access Journals (Sweden)

Morrell Darryl

2006-01-01

Full Text Available We propose two nonmyopic sensor scheduling algorithms for target tracking applications. We consider a scenario where a bearing-only sensor is constrained to move in a finite number of directions to track a target in a two-dimensional plane. Both algorithms provide the best sensor sequence by minimizing a predicted expected scheduler cost over a finite time-horizon. The first algorithm approximately computes the scheduler costs based on the predicted covariance matrix of the tracker error. The second algorithm uses the unscented transform in conjunction with a particle filter to approximate covariance-based costs or information-theoretic costs. We also propose the use of two branch-and-bound-based optimal pruning algorithms for efficient implementation of the scheduling algorithms. We design the first pruning algorithm by combining branch-and-bound with a breadth-first search and a greedy-search; the second pruning algorithm combines branch-and-bound with a uniform-cost search. Simulation results demonstrate the advantage of nonmyopic scheduling over myopic scheduling and the significant savings in computational and memory resources when using the pruning algorithms.

Autonomous Vehicles Navigation with Visual Target Tracking: Technical Approaches

Directory of Open Access Journals (Sweden)

Zhen Jia

2008-12-01

Full Text Available This paper surveys the developments of last 10 years in the area of vision based target tracking for autonomous vehicles navigation. First, the motivations and applications of using vision based target tracking for autonomous vehicles navigation are presented in the introduction section. It can be concluded that it is very necessary to develop robust visual target tracking based navigation algorithms for the broad applications of autonomous vehicles. Then this paper reviews the recent techniques in three different categories: vision based target tracking for the applications of land, underwater and aerial vehicles navigation. Next, the increasing trends of using data fusion for visual target tracking based autonomous vehicles navigation are discussed. Through data fusion the tracking performance is improved and becomes more robust. Based on the review, the remaining research challenges are summarized and future research directions are investigated.

Spatial Release from Masking with a Moving Target

Directory of Open Access Journals (Sweden)

M. Torben Pastore

2017-12-01

Full Text Available In the visual domain, a stationary object that is difficult to detect usually becomes far more salient if it moves while the objects around it do not. This “pop out” effect is important for parsing the visual world into figure/ground relationships that allow creatures to detect food, threats, etc. We tested for an auditory correlate to this visual effect by asking listeners to identify a single word, spoken by a female, embedded with two or four masking words spoken by males. Percentage correct scores were analyzed and compared between conditions where target and maskers were presented from the same position vs. when the target was presented from one position while maskers were presented from different positions. In some trials, the target word was moved across the speaker array using amplitude panning, while in other trials that target was played from a single, static position. Results showed a spatial release from masking for all conditions where the target and maskers were not located at the same position, but there was no statistically significant difference between identification performance when the target was moving vs. when it was stationary. These results suggest that, at least for short stimulus durations (0.75 s for the stimuli in this experiment, there is unlikely to be a “pop out” effect for moving target stimuli in the auditory domain as there is in the visual domain.

Virtual target tracking (VTT) as applied to mobile satellite communication networks

Science.gov (United States)

Amoozegar, Farid

1999-08-01

Traditionally, target tracking has been used for aerospace applications, such as, tracking highly maneuvering targets in a cluttered environment for missile-to-target intercept scenarios. Although the speed and maneuvering capability of current aerospace targets demand more efficient algorithms, many complex techniques have already been proposed in the literature, which primarily cover the defense applications of tracking methods. On the other hand, the rapid growth of Global Communication Systems, Global Information Systems (GIS), and Global Positioning Systems (GPS) is creating new and more diverse challenges for multi-target tracking applications. Mobile communication and computing can very well appreciate a huge market for Cellular Communication and Tracking Devices (CCTD), which will be tracking networked devices at the cellular level. The objective of this paper is to introduce a new concept, i.e., Virtual Target Tracking (VTT) for commercial applications of multi-target tracking algorithms and techniques as applied to mobile satellite communication networks. It would be discussed how Virtual Target Tracking would bring more diversity to target tracking research.

Experimental research on laser tracking system with galvanometer scanner for measuring spatial coordinates of moving target

Science.gov (United States)

Wang, Jia; Hu, Zhaohui; Liu, Yongdong; Liang, Jinwen

2000-10-01

The spatial position of industrial object, such as robot end- effector, is an important geometric parameter whose accuracy determines whether robot can perform accurately. Therefore, we have established a laser tracking and coordinate measuring system with galvanometer scanner for high accuracy, large range, non- contact, and spatial dynamic measurement. In this paper, the laser tracking system and its setup are illuminated at first. Then, the formulae for calculating coordinates are deduced, and the calibration method of the initial distance from tracking mirror to target is presented. After that, two preliminary experiments in different distances are described. One is on CMM; the other is with grating ruler as reference. In the former, the maximum measurement error of coordinates is 70micrometers and the maximum error of length is 35micrometers in the 85x100x100mm3 measurement volume, and in the 1m initial distance. In the later, the maximum error of length is 140micrometers in the range of 480mm, and in the 5m initial distance. At the end of the paper, the error sources are analyzed and simulated.

Tracking 3D Moving Objects Based on GPS/IMU Navigation Solution, Laser Scanner Point Cloud and GIS Data

Directory of Open Access Journals (Sweden)

Siavash Hosseinyalamdary

2015-07-01

Full Text Available Monitoring vehicular road traffic is a key component of any autonomous driving platform. Detecting moving objects, and tracking them, is crucial to navigating around objects and predicting their locations and trajectories. Laser sensors provide an excellent observation of the area around vehicles, but the point cloud of objects may be noisy, occluded, and prone to different errors. Consequently, object tracking is an open problem, especially for low-quality point clouds. This paper describes a pipeline to integrate various sensor data and prior information, such as a Geospatial Information System (GIS map, to segment and track moving objects in a scene. We show that even a low-quality GIS map, such as OpenStreetMap (OSM, can improve the tracking accuracy, as well as decrease processing time. A bank of Kalman filters is used to track moving objects in a scene. In addition, we apply non-holonomic constraint to provide a better orientation estimation of moving objects. The results show that moving objects can be correctly detected, and accurately tracked, over time, based on modest quality Light Detection And Ranging (LiDAR data, a coarse GIS map, and a fairly accurate Global Positioning System (GPS and Inertial Measurement Unit (IMU navigation solution.

A Synthetic Algorithm for Tracking a Moving Object in a Multiple-Dynamic Obstacles Environment Based on Kinematically Planar Redundant Manipulators

Directory of Open Access Journals (Sweden)

Hongzhe Jin

2017-01-01

Full Text Available This paper presents a synthetic algorithm for tracking a moving object in a multiple-dynamic obstacles environment based on kinematically planar manipulators. By observing the motions of the object and obstacles, Spline filter associated with polynomial fitting is utilized to predict their moving paths for a period of time in the future. Several feasible paths for the manipulator in Cartesian space can be planned according to the predicted moving paths and the defined feasibility criterion. The shortest one among these feasible paths is selected as the optimized path. Then the real-time path along the optimized path is planned for the manipulator to track the moving object in real-time. To improve the convergence rate of tracking, a virtual controller based on PD controller is designed to adaptively adjust the real-time path. In the process of tracking, the null space of inverse kinematic and the local rotation coordinate method (LRCM are utilized for the arms and the end-effector to avoid obstacles, respectively. Finally, the moving object in a multiple-dynamic obstacles environment is thus tracked via real-time updating the joint angles of manipulator according to the iterative method. Simulation results show that the proposed algorithm is feasible to track a moving object in a multiple-dynamic obstacles environment.

Tracking of Range and Azimuth for Continuous Imaging of Marine Target in Monopulse ISAR with Wideband Echoes

Directory of Open Access Journals (Sweden)

Junhao Xie

2016-01-01

Full Text Available Real-time tracking of maneuvering targets is the prerequisite for continuous imaging of moving targets in inverse synthetic aperture radar (ISAR. In this paper, the range and azimuth tracking (RAT method with wideband radar echoes is first presented for a mechanical scanning monopulse ISAR, which is regarded as the simplest phased array unit due to the two antenna feeds. To relieve the estimation fluctuation and poor robustness of the RAT method with a single snapshot, a modified range and azimuth tracking approach based on centroid algorithm (RATCA with forgotten factor and multiple echoes is then proposed. The performances of different forgotten factors are investigated. Both theoretical analysis and experimental results demonstrate that RATCA is superior to RAT method. Particularly, when target echo is missing occasionally, RAT method fails while RATCA still keeps good performance. The potential of continuous imaging with shipborne ISAR is verified by experimental results. With minor modification, the method proposed in this paper can be potentially applied in the phased array radar.

An autonomous robot inspired by insect neurophysiology pursues moving features in natural environments

Science.gov (United States)

Bagheri, Zahra M.; Cazzolato, Benjamin S.; Grainger, Steven; O'Carroll, David C.; Wiederman, Steven D.

2017-08-01

Objective. Many computer vision and robotic applications require the implementation of robust and efficient target-tracking algorithms on a moving platform. However, deployment of a real-time system is challenging, even with the computational power of modern hardware. Lightweight and low-powered flying insects, such as dragonflies, track prey or conspecifics within cluttered natural environments, illustrating an efficient biological solution to the target-tracking problem. Approach. We used our recent recordings from ‘small target motion detector’ neurons in the dragonfly brain to inspire the development of a closed-loop target detection and tracking algorithm. This model exploits facilitation, a slow build-up of response to targets which move along long, continuous trajectories, as seen in our electrophysiological data. To test performance in real-world conditions, we implemented this model on a robotic platform that uses active pursuit strategies based on insect behaviour. Main results. Our robot performs robustly in closed-loop pursuit of targets, despite a range of challenging conditions used in our experiments; low contrast targets, heavily cluttered environments and the presence of distracters. We show that the facilitation stage boosts responses to targets moving along continuous trajectories, improving contrast sensitivity and detection of small moving targets against textured backgrounds. Moreover, the temporal properties of facilitation play a useful role in handling vibration of the robotic platform. We also show that the adoption of feed-forward models which predict the sensory consequences of self-movement can significantly improve target detection during saccadic movements. Significance. Our results provide insight into the neuronal mechanisms that underlie biological target detection and selection (from a moving platform), as well as highlight the effectiveness of our bio-inspired algorithm in an artificial visual system.

Active Multimodal Sensor System for Target Recognition and Tracking.

Science.gov (United States)

Qu, Yufu; Zhang, Guirong; Zou, Zhaofan; Liu, Ziyue; Mao, Jiansen

2017-06-28

High accuracy target recognition and tracking systems using a single sensor or a passive multisensor set are susceptible to external interferences and exhibit environmental dependencies. These difficulties stem mainly from limitations to the available imaging frequency bands, and a general lack of coherent diversity of the available target-related data. This paper proposes an active multimodal sensor system for target recognition and tracking, consisting of a visible, an infrared, and a hyperspectral sensor. The system makes full use of its multisensor information collection abilities; furthermore, it can actively control different sensors to collect additional data, according to the needs of the real-time target recognition and tracking processes. This level of integration between hardware collection control and data processing is experimentally shown to effectively improve the accuracy and robustness of the target recognition and tracking system.

Designs and Algorithms to Map Eye Tracking Data with Dynamic Multielement Moving Objects

Directory of Open Access Journals (Sweden)

Ziho Kang

2016-01-01

Full Text Available Design concepts and algorithms were developed to address the eye tracking analysis issues that arise when (1 participants interrogate dynamic multielement objects that can overlap on the display and (2 visual angle error of the eye trackers is incapable of providing exact eye fixation coordinates. These issues were addressed by (1 developing dynamic areas of interests (AOIs in the form of either convex or rectangular shapes to represent the moving and shape-changing multielement objects, (2 introducing the concept of AOI gap tolerance (AGT that controls the size of the AOIs to address the overlapping and visual angle error issues, and (3 finding a near optimal AGT value. The approach was tested in the context of air traffic control (ATC operations where air traffic controller specialists (ATCSs interrogated multiple moving aircraft on a radar display to detect and control the aircraft for the purpose of maintaining safe and expeditious air transportation. In addition, we show how eye tracking analysis results can differ based on how we define dynamic AOIs to determine eye fixations on moving objects. The results serve as a framework to more accurately analyze eye tracking data and to better support the analysis of human performance.

Target tracking system based on preliminary and precise two-stage compound cameras

Science.gov (United States)

Shen, Yiyan; Hu, Ruolan; She, Jun; Luo, Yiming; Zhou, Jie

2018-02-01

Early detection of goals and high-precision of target tracking is two important performance indicators which need to be balanced in actual target search tracking system. This paper proposed a target tracking system with preliminary and precise two - stage compound. This system using a large field of view to achieve the target search. After the target was searched and confirmed, switch into a small field of view for two field of view target tracking. In this system, an appropriate filed switching strategy is the key to achieve tracking. At the same time, two groups PID parameters are add into the system to reduce tracking error. This combination way with preliminary and precise two-stage compound can extend the scope of the target and improve the target tracking accuracy and this method has practical value.

Bayesian target tracking based on particle filter

Institute of Scientific and Technical Information of China (English)

无

2005-01-01

For being able to deal with the nonlinear or non-Gaussian problems, particle filters have been studied by many researchers. Based on particle filter, the extended Kalman filter (EKF) proposal function is applied to Bayesian target tracking. Markov chain Monte Carlo (MCMC) method, the resampling step, etc novel techniques are also introduced into Bayesian target tracking. And the simulation results confirm the improved particle filter with these techniques outperforms the basic one.

Target-type probability combining algorithms for multisensor tracking

Science.gov (United States)

Wigren, Torbjorn

2001-08-01

Algorithms for the handing of target type information in an operational multi-sensor tracking system are presented. The paper discusses recursive target type estimation, computation of crosses from passive data (strobe track triangulation), as well as the computation of the quality of the crosses for deghosting purposes. The focus is on Bayesian algorithms that operate in the discrete target type probability space, and on the approximations introduced for computational complexity reduction. The centralized algorithms are able to fuse discrete data from a variety of sensors and information sources, including IFF equipment, ESM's, IRST's as well as flight envelopes estimated from track data. All algorithms are asynchronous and can be tuned to handle clutter, erroneous associations as well as missed and erroneous detections. A key to obtain this ability is the inclusion of data forgetting by a procedure for propagation of target type probability states between measurement time instances. Other important properties of the algorithms are their abilities to handle ambiguous data and scenarios. The above aspects are illustrated in a simulations study. The simulation setup includes 46 air targets of 6 different types that are tracked by 5 airborne sensor platforms using ESM's and IRST's as data sources.

Schema generation in recurrent neural nets for intercepting a moving target.

Science.gov (United States)

Fleischer, Andreas G

2010-06-01

The grasping of a moving object requires the development of a motor strategy to anticipate the trajectory of the target and to compute an optimal course of interception. During the performance of perception-action cycles, a preprogrammed prototypical movement trajectory, a motor schema, may highly reduce the control load. Subjects were asked to hit a target that was moving along a circular path by means of a cursor. Randomized initial target positions and velocities were detected in the periphery of the eyes, resulting in a saccade toward the target. Even when the target disappeared, the eyes followed the target's anticipated course. The Gestalt of the trajectories was dependent on target velocity. The prediction capability of the motor schema was investigated by varying the visibility range of cursor and target. Motor schemata were determined to be of limited precision, and therefore visual feedback was continuously required to intercept the moving target. To intercept a target, the motor schema caused the hand to aim ahead and to adapt to the target trajectory. The control of cursor velocity determined the point of interception. From a modeling point of view, a neural network was developed that allowed the implementation of a motor schema interacting with feedback control in an iterative manner. The neural net of the Wilson type consists of an excitation-diffusion layer allowing the generation of a moving bubble. This activation bubble runs down an eye-centered motor schema and causes a planar arm model to move toward the target. A bubble provides local integration and straightening of the trajectory during repetitive moves. The schema adapts to task demands by learning and serves as forward controller. On the basis of these model considerations the principal problem of embedding motor schemata in generalized control strategies is discussed.

Management of three-dimensional intrafraction motion through real-time DMLC tracking

International Nuclear Information System (INIS)

Sawant, Amit; Venkat, Raghu; Srivastava, Vikram; Carlson, David; Povzner, Sergey; Cattell, Herb; Keall, Paul

2008-01-01

Tumor tracking using a dynamic multileaf collimator (DMLC) represents a promising approach for intrafraction motion management in thoracic and abdominal cancer radiotherapy. In this work, we develop, empirically demonstrate, and characterize a novel 3D tracking algorithm for real-time, conformal, intensity modulated radiotherapy (IMRT) and volumetric modulated arc therapy (VMAT)-based radiation delivery to targets moving in three dimensions. The algorithm obtains real-time information of target location from an independent position monitoring system and dynamically calculates MLC leaf positions to account for changes in target position. Initial studies were performed to evaluate the geometric accuracy of DMLC tracking of 3D target motion. In addition, dosimetric studies were performed on a clinical linac to evaluate the impact of real-time DMLC tracking for conformal, step-and-shoot (S-IMRT), dynamic (D-IMRT), and VMAT deliveries to a moving target. The efficiency of conformal and IMRT delivery in the presence of tracking was determined. Results show that submillimeter geometric accuracy in all three dimensions is achievable with DMLC tracking. Significant dosimetric improvements were observed in the presence of tracking for conformal and IMRT deliveries to moving targets. A gamma index evaluation with a 3%-3 mm criterion showed that deliveries without DMLC tracking exhibit between 1.7 (S-IMRT) and 4.8 (D-IMRT) times more dose points that fail the evaluation compared to corresponding deliveries with tracking. The efficiency of IMRT delivery, as measured in the lab, was observed to be significantly lower in case of tracking target motion perpendicular to MLC leaf travel compared to motion parallel to leaf travel. Nevertheless, these early results indicate that accurate, real-time DMLC tracking of 3D tumor motion is feasible and can potentially result in significant geometric and dosimetric advantages leading to more effective management of intrafraction motion

Tracking sentence planning and production.

Science.gov (United States)

Kemper, Susan; Bontempo, Daniel; McKedy, Whitney; Schmalzried, RaLynn; Tagliaferri, Bruno; Kieweg, Doug

2011-03-01

To assess age differences in the costs of language planning and production. A controlled sentence production task was combined with digital pursuit rotor tracking. Participants were asked to track a moving target while formulating a sentence using specified nouns and verbs and to continue to track the moving target while producing their response. The length of the critical noun phrase (NP) as well as the type of verb provided were manipulated. The analysis indicated that sentence planning was more costly than sentence production, and sentence planning costs increased when participants had to incorporate a long NP into their sentence. The long NPs also tended to be shifted to the end of the sentence, whereas short NPs tended to be positioned after the verb. Planning or producing responses with long NPs was especially difficult for older adults, although verb type and NP shift had similar costs for young and older adults. Pursuit rotor tracking during controlled sentence production reveals the effects of aging on sentence planning and production.

Adaptive block online learning target tracking based on super pixel segmentation

Science.gov (United States)

Cheng, Yue; Li, Jianzeng

2018-04-01

Video target tracking technology under the unremitting exploration of predecessors has made big progress, but there are still lots of problems not solved. This paper proposed a new algorithm of target tracking based on image segmentation technology. Firstly we divide the selected region using simple linear iterative clustering (SLIC) algorithm, after that, we block the area with the improved density-based spatial clustering of applications with noise (DBSCAN) clustering algorithm. Each sub-block independently trained classifier and tracked, then the algorithm ignore the failed tracking sub-block while reintegrate the rest of the sub-blocks into tracking box to complete the target tracking. The experimental results show that our algorithm can work effectively under occlusion interference, rotation change, scale change and many other problems in target tracking compared with the current mainstream algorithms.

Automatically tracking neurons in a moving and deforming brain.

Directory of Open Access Journals (Sweden)

Jeffrey P Nguyen

2017-05-01

Full Text Available Advances in optical neuroimaging techniques now allow neural activity to be recorded with cellular resolution in awake and behaving animals. Brain motion in these recordings pose a unique challenge. The location of individual neurons must be tracked in 3D over time to accurately extract single neuron activity traces. Recordings from small invertebrates like C. elegans are especially challenging because they undergo very large brain motion and deformation during animal movement. Here we present an automated computer vision pipeline to reliably track populations of neurons with single neuron resolution in the brain of a freely moving C. elegans undergoing large motion and deformation. 3D volumetric fluorescent images of the animal's brain are straightened, aligned and registered, and the locations of neurons in the images are found via segmentation. Each neuron is then assigned an identity using a new time-independent machine-learning approach we call Neuron Registration Vector Encoding. In this approach, non-rigid point-set registration is used to match each segmented neuron in each volume with a set of reference volumes taken from throughout the recording. The way each neuron matches with the references defines a feature vector which is clustered to assign an identity to each neuron in each volume. Finally, thin-plate spline interpolation is used to correct errors in segmentation and check consistency of assigned identities. The Neuron Registration Vector Encoding approach proposed here is uniquely well suited for tracking neurons in brains undergoing large deformations. When applied to whole-brain calcium imaging recordings in freely moving C. elegans, this analysis pipeline located 156 neurons for the duration of an 8 minute recording and consistently found more neurons more quickly than manual or semi-automated approaches.

Tumor trailing strategy for intensity-modulated radiation therapy of moving targets

International Nuclear Information System (INIS)

Trofimov, Alexei; Vrancic, Christian; Chan, Timothy C. Y.; Sharp, Gregory C.; Bortfeld, Thomas

2008-01-01

Internal organ motion during the course of radiation therapy of cancer affects the distribution of the delivered dose and, generally, reduces its conformality to the targeted volume. Previously proposed approaches aimed at mitigating the effect of internal motion in intensity-modulated radiation therapy (IMRT) included expansion of the target margins, motion-correlated delivery (e.g., respiratory gating, tumor tracking), and adaptive treatment plan optimization employing a probabilistic description of motion. We describe and test the tumor trailing strategy, which utilizes the synergy of motion-adaptive treatment planning and delivery methods. We regard the (rigid) target motion as a superposition of a relatively fast cyclic component (e.g., respiratory) and slow aperiodic trends (e.g., the drift of exhalation baseline). In the trailing approach, these two components of motion are decoupled and dealt with separately. Real-time motion monitoring is employed to identify the 'slow' shifts, which are then corrected by applying setup adjustments. The delivery does not track the target position exactly, but trails the systematic trend due to the delay between the time a shift occurs, is reliably detected, and, subsequently, corrected. The ''fast'' cyclic motion is accounted for with a robust motion-adaptive treatment planning, which allows for variability in motion parameters (e.g., mean and extrema of the tidal volume, variable period of respiration, and expiratory duration). Motion-surrogate data from gated IMRT treatments were used to provide probability distribution data for motion-adaptive planning and to test algorithms that identified systematic trends in the character of motion. Sample IMRT fields were delivered on a clinical linear accelerator to a programmable moving phantom. Dose measurements were performed with a commercial two-dimensional ion-chamber array. The results indicate that by reducing intrafractional motion variability, the trailing strategy

Collaborative In-Network Processing for Target Tracking

Directory of Open Access Journals (Sweden)

Juan Liu

2003-03-01

Full Text Available This paper presents a class of signal processing techniques for collaborative signal processing in ad hoc sensor networks, focusing on a vehicle tracking application. In particular, we study two types of commonly used sensors—acoustic-amplitude sensors for target distance estimation and direction-of-arrival sensors for bearing estimation—and investigate how networks of such sensors can collaborate to extract useful information with minimal resource usage. The information-driven sensor collaboration has several advantages: tracking is distributed, and the network is energy-efficient, activated only on a when-needed basis. We demonstrate the effectiveness of the approach to target tracking using both simulation and field data.

Robust Target Tracking with Multi-Static Sensors under Insufficient TDOA Information.

Science.gov (United States)

Shin, Hyunhak; Ku, Bonhwa; Nelson, Jill K; Ko, Hanseok

2018-05-08

This paper focuses on underwater target tracking based on a multi-static sonar network composed of passive sonobuoys and an active ping. In the multi-static sonar network, the location of the target can be estimated using TDOA (Time Difference of Arrival) measurements. However, since the sensor network may obtain insufficient and inaccurate TDOA measurements due to ambient noise and other harsh underwater conditions, target tracking performance can be significantly degraded. We propose a robust target tracking algorithm designed to operate in such a scenario. First, track management with track splitting is applied to reduce performance degradation caused by insufficient measurements. Second, a target location is estimated by a fusion of multiple TDOA measurements using a Gaussian Mixture Model (GMM). In addition, the target trajectory is refined by conducting a stack-based data association method based on multiple-frames measurements in order to more accurately estimate target trajectory. The effectiveness of the proposed method is verified through simulations.

Comparisons of Online Reading Paradigms: Eye Tracking, Moving-Window, and Maze

Science.gov (United States)

Witzel, Naoko; Witzel, Jeffrey; Forster, Kenneth

2012-01-01

This study compares four methodologies used to examine online sentence processing during reading. Specifically, self-paced, non-cumulative, moving-window reading (Just et al. in "J Exp Psychol Gen" 111:228-238, 1982), eye tracking (see e.g., Rayner in "Q J Exp Psychol" 62:1457-1506, 2009), and two versions of the maze task (Forster et al. in…

Symmetric Kullback-Leibler Metric Based Tracking Behaviors for Bioinspired Robotic Eyes.

Science.gov (United States)

Liu, Hengli; Luo, Jun; Wu, Peng; Xie, Shaorong; Li, Hengyu

2015-01-01

A symmetric Kullback-Leibler metric based tracking system, capable of tracking moving targets, is presented for a bionic spherical parallel mechanism to minimize a tracking error function to simulate smooth pursuit of human eyes. More specifically, we propose a real-time moving target tracking algorithm which utilizes spatial histograms taking into account symmetric Kullback-Leibler metric. In the proposed algorithm, the key spatial histograms are extracted and taken into particle filtering framework. Once the target is identified, an image-based control scheme is implemented to drive bionic spherical parallel mechanism such that the identified target is to be tracked at the center of the captured images. Meanwhile, the robot motion information is fed forward to develop an adaptive smooth tracking controller inspired by the Vestibuloocular Reflex mechanism. The proposed tracking system is designed to make the robot track dynamic objects when the robot travels through transmittable terrains, especially bumpy environment. To perform bumpy-resist capability under the condition of violent attitude variation when the robot works in the bumpy environment mentioned, experimental results demonstrate the effectiveness and robustness of our bioinspired tracking system using bionic spherical parallel mechanism inspired by head-eye coordination.

Symmetric Kullback-Leibler Metric Based Tracking Behaviors for Bioinspired Robotic Eyes

Directory of Open Access Journals (Sweden)

Hengli Liu

2015-01-01

Full Text Available A symmetric Kullback-Leibler metric based tracking system, capable of tracking moving targets, is presented for a bionic spherical parallel mechanism to minimize a tracking error function to simulate smooth pursuit of human eyes. More specifically, we propose a real-time moving target tracking algorithm which utilizes spatial histograms taking into account symmetric Kullback-Leibler metric. In the proposed algorithm, the key spatial histograms are extracted and taken into particle filtering framework. Once the target is identified, an image-based control scheme is implemented to drive bionic spherical parallel mechanism such that the identified target is to be tracked at the center of the captured images. Meanwhile, the robot motion information is fed forward to develop an adaptive smooth tracking controller inspired by the Vestibuloocular Reflex mechanism. The proposed tracking system is designed to make the robot track dynamic objects when the robot travels through transmittable terrains, especially bumpy environment. To perform bumpy-resist capability under the condition of violent attitude variation when the robot works in the bumpy environment mentioned, experimental results demonstrate the effectiveness and robustness of our bioinspired tracking system using bionic spherical parallel mechanism inspired by head-eye coordination.

Adaptive Colour Feature Identification in Image for Object Tracking

Directory of Open Access Journals (Sweden)

Feng Su

2012-01-01

Full Text Available Identification and tracking of a moving object using computer vision techniques is important in robotic surveillance. In this paper, an adaptive colour filtering method is introduced for identifying and tracking a moving object appearing in image sequences. This filter is capable of automatically identifying the most salient colour feature of the moving object in the image and using this for a robot to track the object. The method enables the selected colour feature to adapt to surrounding condition when it is changed. A method of determining the region of interest of the moving target is also developed for the adaptive colour filter to extract colour information. Experimental results show that by using a camera mounted on a robot, the proposed methods can perform robustly in tracking a randomly moving object using adaptively selected colour features in a crowded environment.

Low cost, robust and real time system for detecting and tracking moving objects to automate cargo handling in port terminals

NARCIS (Netherlands)

Vaquero, V.; Repiso, E.; Sanfeliu, A.; Vissers, J.; Kwakkernaat, M.

2016-01-01

The presented paper addresses the problem of detecting and tracking moving objects for autonomous cargo handling in port terminals using a perception system which input data is a single layer laser scanner. A computationally low cost and robust Detection and Tracking Moving Objects (DATMO) algorithm

INSPTRAX - The Inspection Targeting, Planning and Tracking Database

Data.gov (United States)

U.S. Environmental Protection Agency — The INSPTRAX System tracks Air, RCRA, and Water inspection targeting, planning and tracking information. It is used by the the Air, RCRA, and Water programs to input...

Moving target detection based on temporal-spatial information fusion for infrared image sequences

Science.gov (United States)

Toing, Wu-qin; Xiong, Jin-yu; Zeng, An-jun; Wu, Xiao-ping; Xu, Hao-peng

2009-07-01

Moving target detection and localization is one of the most fundamental tasks in visual surveillance. In this paper, through analyzing the advantages and disadvantages of the traditional approaches about moving target detection, a novel approach based on temporal-spatial information fusion is proposed for moving target detection. The proposed method combines the spatial feature in single frame and the temporal properties within multiple frames of an image sequence of moving target. First, the method uses the spatial image segmentation for target separation from background and uses the local temporal variance for extracting targets and wiping off the trail artifact. Second, the logical "and" operator is used to fuse the temporal and spatial information. In the end, to the fusion image sequence, the morphological filtering and blob analysis are used to acquire exact moving target. The algorithm not only requires minimal computation and memory but also quickly adapts to the change of background and environment. Comparing with other methods, such as the KDE, the Mixture of K Gaussians, etc., the simulation results show the proposed method has better validity and higher adaptive for moving target detection, especially in infrared image sequences with complex illumination change, noise change, and so on.

Algorithm of search and track of static and moving large-scale objects

Directory of Open Access Journals (Sweden)

Kalyaev Anatoly

2017-01-01

Full Text Available We suggest an algorithm for processing of a sequence, which contains images of search and track of static and moving large-scale objects. The possible software implementation of the algorithm, based on multithread CUDA processing, is suggested. Experimental analysis of the suggested algorithm implementation is performed.

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).

Distributed Cooperative Search Control Method of Multiple UAVs for Moving Target

Directory of Open Access Journals (Sweden)

Chang-jian Ru

2015-01-01

Full Text Available To reduce the impact of uncertainties caused by unknown motion parameters on searching plan of moving targets and improve the efficiency of UAV’s searching, a novel distributed Multi-UAVs cooperative search control method for moving target is proposed in this paper. Based on detection results of onboard sensors, target probability map is updated using Bayesian theory. A Gaussian distribution of target transition probability density function is introduced to calculate prediction probability of moving target existence, and then target probability map can be further updated in real-time. A performance index function combining with target cost, environment cost, and cooperative cost is constructed, and the cooperative searching problem can be transformed into a central optimization problem. To improve computational efficiency, the distributed model predictive control method is presented, and thus the control command of each UAV can be obtained. The simulation results have verified that the proposed method can avoid the blindness of UAV searching better and improve overall efficiency of the team effectively.

Beyond Group: Multiple Person Tracking via Minimal Topology-Energy-Variation.

Science.gov (United States)

Gao, Shan; Ye, Qixiang; Xing, Junliang; Kuijper, Arjan; Han, Zhenjun; Jiao, Jianbin; Ji, Xiangyang

2017-12-01

Tracking multiple persons is a challenging task when persons move in groups and occlude each other. Existing group-based methods have extensively investigated how to make group division more accurately in a tracking-by-detection framework; however, few of them quantify the group dynamics from the perspective of targets' spatial topology or consider the group in a dynamic view. Inspired by the sociological properties of pedestrians, we propose a novel socio-topology model with a topology-energy function to factor the group dynamics of moving persons and groups. In this model, minimizing the topology-energy-variance in a two-level energy form is expected to produce smooth topology transitions, stable group tracking, and accurate target association. To search for the strong minimum in energy variation, we design the discrete group-tracklet jump moves embedded in the gradient descent method, which ensures that the moves reduce the energy variation of group and trajectory alternately in the varying topology dimension. Experimental results on both RGB and RGB-D data sets show the superiority of our proposed model for multiple person tracking in crowd scenes.

Nonlinear Autoregressive Network with the Use of a Moving Average Method for Forecasting Typhoon Tracks

OpenAIRE

Tienfuan Kerh; Shin-Hung Wu

2017-01-01

Forecasting of a typhoon moving path may help to evaluate the potential negative impacts in the neighbourhood areas along the moving path. This study proposed a work of using both static and dynamic neural network models to link a time series of typhoon track parameters including longitude and latitude of the typhoon central location, cyclonic radius, central wind speed, and typhoon moving speed. Based on the historical records of 100 typhoons, the performances of neural network models are ev...

Computing proton dose to irregularly moving targets

International Nuclear Information System (INIS)

Phillips, Justin; Gueorguiev, Gueorgui; Grassberger, Clemens; Dowdell, Stephen; Paganetti, Harald; Sharp, Gregory C; Shackleford, James A

2014-01-01

Purpose: While four-dimensional computed tomography (4DCT) and deformable registration can be used to assess the dose delivered to regularly moving targets, there are few methods available for irregularly moving targets. 4DCT captures an idealized waveform, but human respiration during treatment is characterized by gradual baseline shifts and other deviations from a periodic signal. This paper describes a method for computing the dose delivered to irregularly moving targets based on 1D or 3D waveforms captured at the time of delivery. Methods: The procedure uses CT or 4DCT images for dose calculation, and 1D or 3D respiratory waveforms of the target position at time of delivery. Dose volumes are converted from their Cartesian geometry into a beam-specific radiological depth space, parameterized in 2D by the beam aperture, and longitudinally by the radiological depth. In this new frame of reference, the proton doses are translated according to the motion found in the 1D or 3D trajectory. These translated dose volumes are weighted and summed, then transformed back into Cartesian space, yielding an estimate of the dose that includes the effect of the measured breathing motion. The method was validated using a synthetic lung phantom and a single representative patient CT. Simulated 4DCT was generated for the phantom with 2 cm peak-to-peak motion. Results: A passively-scattered proton treatment plan was generated using 6 mm and 5 mm smearing for the phantom and patient plans, respectively. The method was tested without motion, and with two simulated breathing signals: a 2 cm amplitude sinusoid, and a 2 cm amplitude sinusoid with 3 cm linear drift in the phantom. The tumor positions were equally weighted for the patient calculation. Motion-corrected dose was computed based on the mid-ventilation CT image in the phantom and the peak exhale position in the patient. Gamma evaluation was 97.8% without motion, 95.7% for 2 cm sinusoidal motion, 95.7% with 3 cm drift in

SmoothMoves : Smooth pursuits head movements for augmented reality

NARCIS (Netherlands)

Esteves, Augusto; Verweij, David; Suraiya, Liza; Islam, Rasel; Lee, Youryang; Oakley, Ian

2017-01-01

SmoothMoves is an interaction technique for augmented reality (AR) based on smooth pursuits head movements. It works by computing correlations between the movements of on-screen targets and the user's head while tracking those targets. The paper presents three studies. The first suggests that head

Group Targets Tracking Using Multiple Models GGIW-CPHD Based on Best-Fitting Gaussian Approximation and Strong Tracking Filter

Directory of Open Access Journals (Sweden)

Yun Wang

2016-01-01

Full Text Available Gamma Gaussian inverse Wishart cardinalized probability hypothesis density (GGIW-CPHD algorithm was always used to track group targets in the presence of cluttered measurements and missing detections. A multiple models GGIW-CPHD algorithm based on best-fitting Gaussian approximation method (BFG and strong tracking filter (STF is proposed aiming at the defect that the tracking error of GGIW-CPHD algorithm will increase when the group targets are maneuvering. The best-fitting Gaussian approximation method is proposed to implement the fusion of multiple models using the strong tracking filter to correct the predicted covariance matrix of the GGIW component. The corresponding likelihood functions are deduced to update the probability of multiple tracking models. From the simulation results we can see that the proposed tracking algorithm MM-GGIW-CPHD can effectively deal with the combination/spawning of groups and the tracking error of group targets in the maneuvering stage is decreased.

Research on moving target defense based on SDN

Science.gov (United States)

Chen, Mingyong; Wu, Weimin

2017-08-01

An address mutation strategy was proposed. This strategy provided an unpredictable change in address, replacing the real address of the packet forwarding process and path mutation, thus hiding the real address of the host and path. a mobile object defense technology based on Spatio-temporal Mutation on this basis is proposed, Using the software Defined Network centralized control architecture advantage combines sFlow traffic monitoring technology and Moving Target Defense. A mutated time period which can be changed in real time according to the network traffic is changed, and the destination address is changed while the controller abruptly changes the address while the data packet is transferred between the switches to construct a moving target, confusing the host within the network, thereby protecting the host and network.

Saccadic interception of a moving visual target after a spatiotemporal perturbation.

Science.gov (United States)

Fleuriet, Jérome; Goffart, Laurent

2012-01-11

Animals can make saccadic eye movements to intercept a moving object at the right place and time. Such interceptive saccades indicate that, despite variable sensorimotor delays, the brain is able to estimate the current spatiotemporal (hic et nunc) coordinates of a target at saccade end. The present work further tests the robustness of this estimate in the monkey when a change in eye position and a delay are experimentally added before the onset of the saccade and in the absence of visual feedback. These perturbations are induced by brief microstimulation in the deep superior colliculus (dSC). When the microstimulation moves the eyes in the direction opposite to the target motion, a correction saccade brings gaze back on the target path or very near. When it moves the eye in the same direction, the performance is more variable and depends on the stimulated sites. Saccades fall ahead of the target with an error that increases when the stimulation is applied more caudally in the dSC. The numerous cases of compensation indicate that the brain is able to maintain an accurate and robust estimate of the location of the moving target. The inaccuracies observed when stimulating the dSC that encodes the visual field traversed by the target indicate that dSC microstimulation can interfere with signals encoding the target motion path. The results are discussed within the framework of the dual-drive and the remapping hypotheses.

Through-Wall Multiple Targets Vital Signs Tracking Based on VMD Algorithm

Directory of Open Access Journals (Sweden)

Jiaming Yan

2016-08-01

Full Text Available Targets located at the same distance are easily neglected in most through-wall multiple targets detecting applications which use the single-input single-output (SISO ultra-wideband (UWB radar system. In this paper, a novel multiple targets vital signs tracking algorithm for through-wall detection using SISO UWB radar has been proposed. Taking advantage of the high-resolution decomposition of the Variational Mode Decomposition (VMD based algorithm, the respiration signals of different targets can be decomposed into different sub-signals, and then, we can track the time-varying respiration signals accurately when human targets located in the same distance. Intensive evaluation has been conducted to show the effectiveness of our scheme with a 0.15 m thick concrete brick wall. Constant, piecewise-constant and time-varying vital signs could be separated and tracked successfully with the proposed VMD based algorithm for two targets, even up to three targets. For the multiple targets’ vital signs tracking issues like urban search and rescue missions, our algorithm has superior capability in most detection applications.

The Bering Target Tracking Instrumentation

DEFF Research Database (Denmark)

Denver, Troelz; Jørgensen, John Leif; Betto, Maurizio

2003-01-01

The key science instrument on the Bering satellite mission is a relative small telescope with an entrance aperture of 300 mm and a focal length between 500 and 1000 mm. The detection of potential targets is performed by one of the target scanning advanced stellar compasses (ASCs). This procedure...... results in a simple prioritized list of right ascension, declination, proper motion and intensity of each prospective target. The telescope itself has a dedicated ASC Camera Head Unit (CHU) mounted on the secondary mirror, largely co-aligned with the telescope. This CHU accurately determines the telescope......'s pointing direction. To achieve fast tracking over a large solid angle, the telescope pointing is achieved by means of a folding mirror in the optical pathway. When a prospective target approaches the telescope FOV, the ASC on the secondary will guide the folding mirror into position such that the target...

A Novel Loss Recovery and Tracking Scheme for Maneuvering Target in Hybrid WSNs.

Science.gov (United States)

Qian, Hanwang; Fu, Pengcheng; Li, Baoqing; Liu, Jianpo; Yuan, Xiaobing

2018-01-25

Tracking a mobile target, which aims to timely monitor the invasion of specific target, is one of the most prominent applications in wireless sensor networks (WSNs). Traditional tracking methods in WSNs only based on static sensor nodes (SNs) have several critical problems. For example, to void the loss of mobile target, many SNs must be active to track the target in all possible directions, resulting in excessive energy consumption. Additionally, when entering coverage holes in the monitoring area, the mobile target may be missing and then its state is unknown during this period. To tackle these problems, in this paper, a few mobile sensor nodes (MNs) are introduced to cooperate with SNs to form a hybrid WSN due to their stronger abilities and less constrained energy. Then, we propose a valid target tracking scheme for hybrid WSNs to dynamically schedule the MNs and SNs. Moreover, a novel loss recovery mechanism is proposed to find the lost target and recover the tracking with fewer SNs awakened. Furthermore, to improve the robustness and accuracy of the recovery mechanism, an adaptive unscented Kalman filter (AUKF) algorithm is raised to dynamically adjust the process noise covariance. Simulation results demonstrate that our tracking scheme for maneuvering target in hybrid WSNs can not only track the target effectively even if the target is lost but also maintain an excellent accuracy and robustness with fewer activated nodes.

Improving Global Multi-target Tracking with Local Updates

DEFF Research Database (Denmark)

Milan, Anton; Gade, Rikke; Dick, Anthony

2014-01-01

-target tracker, if they result in a reduction in the global cost function. Since tracking failures typically arise when targets become occluded, we propose a local data association scheme to maintain the target identities in these situations. We demonstrate a reduction of up to 50% in the global cost function...

Moving-Target Position Estimation Using GPU-Based Particle Filter for IoT Sensing Applications

Directory of Open Access Journals (Sweden)

Seongseop Kim

2017-11-01

Full Text Available A particle filter (PF has been introduced for effective position estimation of moving targets for non-Gaussian and nonlinear systems. The time difference of arrival (TDOA method using acoustic sensor array has normally been used to for estimation by concealing the location of a moving target, especially underwater. In this paper, we propose a GPU -based acceleration of target position estimation using a PF and propose an efficient system and software architecture. The proposed graphic processing unit (GPU-based algorithm has more advantages in applying PF signal processing to a target system, which consists of large-scale Internet of Things (IoT-driven sensors because of the parallelization which is scalable. For the TDOA measurement from the acoustic sensor array, we use the generalized cross correlation phase transform (GCC-PHAT method to obtain the correlation coefficient of the signal using Fast Fourier Transform (FFT, and we try to accelerate the calculations of GCC-PHAT based TDOA measurements using FFT with GPU compute unified device architecture (CUDA. The proposed approach utilizes a parallelization method in the target position estimation algorithm using GPU-based PF processing. In addition, it could efficiently estimate sudden movement change of the target using GPU-based parallel computing which also can be used for multiple target tracking. It also provides scalability in extending the detection algorithm according to the increase of the number of sensors. Therefore, the proposed architecture can be applied in IoT sensing applications with a large number of sensors. The target estimation algorithm was verified using MATLAB and implemented using GPU CUDA. We implemented the proposed signal processing acceleration system using target GPU to analyze in terms of execution time. The execution time of the algorithm is reduced by 55% from to the CPU standalone operation in target embedded board, NVIDIA Jetson TX1. Also, to apply large

Real-time Non-linear Target Tracking Control of Wheeled Mobile Robots

Institute of Scientific and Technical Information of China (English)

YU Wenyong

2006-01-01

A control strategy for real-time target tracking for wheeled mobile robots is presented. Using a modified Kalman filter for environment perception, a novel tracking control law derived from Lyapunov stability theory is introduced. Tuning of linear velocity and angular velocity with mechanical constraints is applied. The proposed control system can simultaneously solve the target trajectory prediction, real-time tracking, and posture regulation problems of a wheeled mobile robot. Experimental results illustrate the effectiveness of the proposed tracking control laws.

PMHT Approach for Multi-Target Multi-Sensor Sonar Tracking in Clutter.

Science.gov (United States)

Li, Xiaohua; Li, Yaan; Yu, Jing; Chen, Xiao; Dai, Miao

2015-11-06

Multi-sensor sonar tracking has many advantages, such as the potential to reduce the overall measurement uncertainty and the possibility to hide the receiver. However, the use of multi-target multi-sensor sonar tracking is challenging because of the complexity of the underwater environment, especially the low target detection probability and extremely large number of false alarms caused by reverberation. In this work, to solve the problem of multi-target multi-sensor sonar tracking in the presence of clutter, a novel probabilistic multi-hypothesis tracker (PMHT) approach based on the extended Kalman filter (EKF) and unscented Kalman filter (UKF) is proposed. The PMHT can efficiently handle the unknown measurements-to-targets and measurements-to-transmitters data association ambiguity. The EKF and UKF are used to deal with the high degree of nonlinearity in the measurement model. The simulation results show that the proposed algorithm can improve the target tracking performance in a cluttered environment greatly, and its computational load is low.

Random Scenario Generation for a Multiple Target Tracking Environment Evaluation

DEFF Research Database (Denmark)

Hussain, Dil Muhammad Akbar

2006-01-01

, which were normally crossing targets, was to test the efficiency of the track splitting algorithm for different situations. However this approach only gives a measure of performance for a specific, possibly unrealistic, scenario and it was felt appropriate to develop procedures that would enable a more...... general performance assessment. Therefore, a random target motion scenario is adopted. Its implementation in particular for testing the track splitting algorithm using Kalman filters is used and a couple of tracking performance parameters are computed to investigate such random scenarios....

Dynamic-MLC leaf control utilizing on-flight intensity calculations: A robust method for real-time IMRT delivery over moving rigid targets

International Nuclear Information System (INIS)

McMahon, Ryan; Papiez, Lech; Rangaraj, Dharanipathy

2007-01-01

An algorithm is presented that allows for the control of multileaf collimation (MLC) leaves based entirely on real-time calculations of the intensity delivered over the target. The algorithm is capable of efficiently correcting generalized delivery errors without requiring the interruption of delivery (self-correcting trajectories), where a generalized delivery error represents anything that causes a discrepancy between the delivered and intended intensity profiles. The intensity actually delivered over the target is continually compared to its intended value. For each pair of leaves, these comparisons are used to guide the control of the following leaf and keep this discrepancy below a user-specified value. To demonstrate the basic principles of the algorithm, results of corrected delivery are shown for a leading leaf positional error during dynamic-MLC (DMLC) IMRT delivery over a rigid moving target. It is then shown that, with slight modifications, the algorithm can be used to track moving targets in real time. The primary results of this article indicate that the algorithm is capable of accurately delivering DMLC IMRT over a rigid moving target whose motion is (1) completely unknown prior to delivery and (2) not faster than the maximum MLC leaf velocity over extended periods of time. These capabilities are demonstrated for clinically derived intensity profiles and actual tumor motion data, including situations when the target moves in some instances faster than the maximum admissible MLC leaf velocity. The results show that using the algorithm while calculating the delivered intensity every 50 ms will provide a good level of accuracy when delivering IMRT over a rigid moving target translating along the direction of MLC leaf travel. When the maximum velocities of the MLC leaves and target were 4 and 4.2 cm/s, respectively, the resulting error in the two intensity profiles used was 0.1±3.1% and -0.5±2.8% relative to the maximum of the intensity profiles. For

Minefield overwatch using moving target indicator radar

Science.gov (United States)

Donadio, Anthony; Ewing, Robert; Kenneally, William J.; Santapietro, John J.

1999-07-01

Traditional antipersonnel land mines are an effective military tool, but they are unable to distinguish friend from foe, or civilian from military personnel. The concept described here uses an advanced moving target indicator (MTI) radar to scan the minefield in order to detect movement towards or within the minefield, coupled with visual identification by a human operator and a communication link for command and control. Selected mines in the minefield can then be activated by means of the command link. In order to demonstrate this concept, a 3D, interactive simulation has been developed. This simulation builds on previous work by integrating a detailed analytical model of an MTI radar. This model has been tailored to the specific application of detection of slowly moving dismounted entities immersed in ground clutter. The model incorporates the effects of internal scatterer motion and antenna scanning modulation in order to provide a realistic representation of the detection problem in this environment. The angle information on the MTI target detection is then passed to a virtual 3D sight which cues a human operator to the target location. In addition, radar propagation effects and an experimental design in which the radar itself is used as a command link are explored.

Tracking target objects orbiting earth using satellite-based telescopes

Science.gov (United States)

De Vries, Willem H; Olivier, Scot S; Pertica, Alexander J

2014-10-14

A system for tracking objects that are in earth orbit via a constellation or network of satellites having imaging devices is provided. An object tracking system includes a ground controller and, for each satellite in the constellation, an onboard controller. The ground controller receives ephemeris information for a target object and directs that ephemeris information be transmitted to the satellites. Each onboard controller receives ephemeris information for a target object, collects images of the target object based on the expected location of the target object at an expected time, identifies actual locations of the target object from the collected images, and identifies a next expected location at a next expected time based on the identified actual locations of the target object. The onboard controller processes the collected image to identify the actual location of the target object and transmits the actual location information to the ground controller.

Computationally Efficient Automatic Coast Mode Target Tracking Based on Occlusion Awareness in Infrared Images.

Science.gov (United States)

Kim, Sohyun; Jang, Gwang-Il; Kim, Sungho; Kim, Junmo

2018-03-27

This paper proposes the automatic coast mode tracking of centroid trackers for infrared images to overcome the target occlusion status. The centroid tracking method, using only the brightness information of an image, is still widely used in infrared imaging tracking systems because it is difficult to extract meaningful features from infrared images. However, centroid trackers are likely to lose the track because they are highly vulnerable to screened status by the clutter or background. Coast mode, one of the tracking modes, maintains the servo slew rate with the tracking rate right before the loss of track. The proposed automatic coast mode tracking method makes decisions regarding entering coast mode by the prediction of target occlusion and tries to re-lock the target and resume the tracking after blind time. This algorithm comprises three steps. The first step is the prediction process of the occlusion by checking both matters which have target-likelihood brightness and which may screen the target despite different brightness. The second step is the process making inertial tracking commands to the servo. The last step is the process of re-locking a target based on the target modeling of histogram ratio. The effectiveness of the proposed algorithm is addressed by presenting experimental results based on computer simulation with various test imagery sequences compared to published tracking algorithms. The proposed algorithm is tested under a real environment with a naval electro-optical tracking system (EOTS) and airborne EO/IR system.

Computationally Efficient Automatic Coast Mode Target Tracking Based on Occlusion Awareness in Infrared Images

Directory of Open Access Journals (Sweden)

Sohyun Kim

2018-03-01

Full Text Available This paper proposes the automatic coast mode tracking of centroid trackers for infrared images to overcome the target occlusion status. The centroid tracking method, using only the brightness information of an image, is still widely used in infrared imaging tracking systems because it is difficult to extract meaningful features from infrared images. However, centroid trackers are likely to lose the track because they are highly vulnerable to screened status by the clutter or background. Coast mode, one of the tracking modes, maintains the servo slew rate with the tracking rate right before the loss of track. The proposed automatic coast mode tracking method makes decisions regarding entering coast mode by the prediction of target occlusion and tries to re-lock the target and resume the tracking after blind time. This algorithm comprises three steps. The first step is the prediction process of the occlusion by checking both matters which have target-likelihood brightness and which may screen the target despite different brightness. The second step is the process making inertial tracking commands to the servo. The last step is the process of re-locking a target based on the target modeling of histogram ratio. The effectiveness of the proposed algorithm is addressed by presenting experimental results based on computer simulation with various test imagery sequences compared to published tracking algorithms. The proposed algorithm is tested under a real environment with a naval electro-optical tracking system (EOTS and airborne EO/IR system.

SAR Ground Moving Target Indication Based on Relative Residue of DPCA Processing

Directory of Open Access Journals (Sweden)

Jia Xu

2016-10-01

Full Text Available For modern synthetic aperture radar (SAR, it has much more urgent demands on ground moving target indication (GMTI, which includes not only the point moving targets like cars, truck or tanks but also the distributed moving targets like river or ocean surfaces. Among the existing GMTI methods, displaced phase center antenna (DPCA can effectively cancel the strong ground clutter and has been widely used. However, its detection performance is closely related to the target’s signal-to-clutter ratio (SCR as well as radial velocity, and it cannot effectively detect the weak large-sized river surfaces in strong ground clutter due to their low SCR caused by specular scattering. This paper proposes a novel method called relative residue of DPCA (RR-DPCA, which jointly utilizes the DPCA cancellation outputs and the multi-look images to improve the detection performance of weak river surfaces. Furthermore, based on the statistics analysis of the RR-DPCA outputs on the homogenous background, the cell average (CA method can be well applied for subsequent constant false alarm rate (CFAR detection. The proposed RR-DPCA method can well detect the point moving targets and distributed moving targets simultaneously. Finally, the results of both simulated and real data are provided to demonstrate the effectiveness of the proposed SAR/GMTI method.

TRUSTWORTHY OPTIMIZED CLUSTERING BASED TARGET DETECTION AND TRACKING FOR WIRELESS SENSOR NETWORK

Directory of Open Access Journals (Sweden)

C. Jehan

2016-06-01

Full Text Available In this paper, an efficient approach is proposed to address the problem of target tracking in wireless sensor network (WSN. The problem being tackled here uses adaptive dynamic clustering scheme for tracking the target. It is a specific problem in object tracking. The proposed adaptive dynamic clustering target tracking scheme uses three steps for target tracking. The first step deals with the identification of clusters and cluster heads using OGSAFCM. Here, kernel fuzzy c-means (KFCM and gravitational search algorithm (GSA are combined to create clusters. At first, oppositional gravitational search algorithm (OGSA is used to optimize the initial clustering center and then the KFCM algorithm is availed to guide the classification and the cluster formation process. In the OGSA, the concept of the opposition based population initialization in the basic GSA to improve the convergence profile. The identified clusters are changed dynamically. The second step deals with the data transmission to the cluster heads. The third step deals with the transmission of aggregated data to the base station as well as the detection of target. From the experimental results, the proposed scheme efficiently and efficiently identifies the target. As a result the tracking error is minimized.

An Integral Model for Target Tracking Based on the Use of a WSN

Directory of Open Access Journals (Sweden)

Pietro Manzoni

2013-06-01

Full Text Available The use of wireless sensor networks (WSN in tracking applications is growing at a fast pace. In these applications, the sensor nodes discover, monitor and track an event or target object. A significant number of proposals relating the use of WSNs for target tracking have been published to date. However, they either focus on the tracking algorithm or on the communication protocol, and none of them address the problem integrally. In this paper, a comprehensive proposal for target detection and tracking is discussed. We introduce a tracking algorithm to detect and estimate a target location. Moreover, we introduce a low-overhead routing protocol to be used along with our tracking algorithm. The proposed algorithm has low computational complexity and has been designed considering the use of a mobile sink while generating minimal delay and packet loss. We also discuss the results of the evaluation of the proposed algorithms.

Reallocating attention during multiple object tracking.

Science.gov (United States)

Ericson, Justin M; Christensen, James C

2012-07-01

Wolfe, Place, and Horowitz (Psychonomic Bulletin & Review 14:344-349, 2007) found that participants were relatively unaffected by selecting and deselecting targets while performing a multiple object tracking task, such that maintaining tracking was possible for longer durations than the few seconds typically studied. Though this result was generally consistent with other findings on tracking duration (Franconeri, Jonathon, & Scimeca Psychological Science 21:920-925, 2010), it was inconsistent with research involving cuing paradigms, specifically precues (Pylyshyn & Annan Spatial Vision 19:485-504, 2006). In the present research, we broke down the addition and removal of targets into separate conditions and incorporated a simple performance model to evaluate the costs associated with the selection and deselection of moving targets. Across three experiments, we demonstrated evidence against a cost being associated with any shift in attention, but rather that varying the type of cue used for target deselection produces no additional cost to performance and that hysteresis effects are not induced by a reduction in tracking load.

Multi-target camera tracking, hand-off and display LDRD 158819 final report

International Nuclear Information System (INIS)

Anderson, Robert J.

2014-01-01

Modern security control rooms gather video and sensor feeds from tens to hundreds of cameras. Advanced camera analytics can detect motion from individual video streams and convert unexpected motion into alarms, but the interpretation of these alarms depends heavily upon human operators. Unfortunately, these operators can be overwhelmed when a large number of events happen simultaneously, or lulled into complacency due to frequent false alarms. This LDRD project has focused on improving video surveillance-based security systems by changing the fundamental focus from the cameras to the targets being tracked. If properly integrated, more cameras shouldn't lead to more alarms, more monitors, more operators, and increased response latency but instead should lead to better information and more rapid response times. For the course of the LDRD we have been developing algorithms that take live video imagery from multiple video cameras, identifies individual moving targets from the background imagery, and then displays the results in a single 3D interactive video. In this document we summarize the work in developing this multi-camera, multi-target system, including lessons learned, tools developed, technologies explored, and a description of current capability.

Multi-target camera tracking, hand-off and display LDRD 158819 final report

Energy Technology Data Exchange (ETDEWEB)

Anderson, Robert J. [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States)

2014-10-01

Modern security control rooms gather video and sensor feeds from tens to hundreds of cameras. Advanced camera analytics can detect motion from individual video streams and convert unexpected motion into alarms, but the interpretation of these alarms depends heavily upon human operators. Unfortunately, these operators can be overwhelmed when a large number of events happen simultaneously, or lulled into complacency due to frequent false alarms. This LDRD project has focused on improving video surveillance-based security systems by changing the fundamental focus from the cameras to the targets being tracked. If properly integrated, more cameras shouldn't lead to more alarms, more monitors, more operators, and increased response latency but instead should lead to better information and more rapid response times. For the course of the LDRD we have been developing algorithms that take live video imagery from multiple video cameras, identifies individual moving targets from the background imagery, and then displays the results in a single 3D interactive video. In this document we summarize the work in developing this multi-camera, multi-target system, including lessons learned, tools developed, technologies explored, and a description of current capability.

Multi-Target Camera Tracking, Hand-off and Display LDRD 158819 Final Report

Energy Technology Data Exchange (ETDEWEB)

Anderson, Robert J. [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States). Robotic and Security Systems Dept.

2014-10-01

Modern security control rooms gather video and sensor feeds from tens to hundreds of cameras. Advanced camera analytics can detect motion from individual video streams and convert unexpected motion into alarms, but the interpretation of these alarms depends heavily upon human operators. Unfortunately, these operators can be overwhelmed when a large number of events happen simultaneously, or lulled into complacency due to frequent false alarms. This LDRD project has focused on improving video surveillance-based security systems by changing the fundamental focus from the cameras to the targets being tracked. If properly integrated, more cameras shouldn’t lead to more alarms, more monitors, more operators, and increased response latency but instead should lead to better information and more rapid response times. For the course of the LDRD we have been developing algorithms that take live video imagery from multiple video cameras, identify individual moving targets from the background imagery, and then display the results in a single 3D interactive video. In this document we summarize the work in developing this multi-camera, multi-target system, including lessons learned, tools developed, technologies explored, and a description of current capability.

EXPERIMENTAL TARGET INJECTION AND TRACKING SYSTEM CONSTRUCTION AND SINGLE SHOT TESTING

International Nuclear Information System (INIS)

PETZOLDT, R.W.; ALEXANDER, N.B.; DRAKE, T.J.; GOODIN, D.T; JONESTRACK, K; VERMILLION, B.A

2003-01-01

Targets must be injected into an IFE power plant at a rate of approximately 5 to 10 Hz. Targets must be tracked very accurately to allow driver beams to be aligned with defined points on the targets with accuracy ± 150 (micro)m for indirect drive and ± 20 (micro)m for direct drive. An experimental target injection and tracking system has been constructed at General Atomics. The injector system will be used as a tool for testing the survivability of various target designs and provide feedback to the target designers. Helium gas propels the targets down an 8 m gun barrel up to 400 m/s. Direct-drive targets are protected in the barrel by sabots that are spring loaded to separate into two halves after acceleration. A sabot deflector directs the sabot halves away from the target injection path. Targets will be optically tracked with laser beams and line-scan cameras. Target position and arrival time will be predicted in real time based on early target position measurements. The system installation will be described. System testing to overcome excessive projectile wear and debris in the gun barrel is presented

Constraints on Multiple Object Tracking in Williams Syndrome: How Atypical Development Can Inform Theories of Visual Processing

Science.gov (United States)

Ferrara, Katrina; Hoffman, James E.; O'Hearn, Kirsten; Landau, Barbara

2016-01-01

The ability to track moving objects is a crucial skill for performance in everyday spatial tasks. The tracking mechanism depends on representation of moving items as coherent entities, which follow the spatiotemporal constraints of objects in the world. In the present experiment, participants tracked 1 to 4 targets in a display of 8 identical…

Tracking Target and Spiral Waves

DEFF Research Database (Denmark)

Jensen, Flemming G.; Sporring, Jon; Nielsen, Mads

2002-01-01

A new algorithm for analyzing the evolution of patterns of spiral and target waves in large aspect ratio chemical systems is introduced. The algorithm does not depend on finding the spiral tip but locates the center of the pattern by a new concept, called the spiral focus, which is defined...... by the evolutes of the actual spiral or target wave. With the use of Gaussian smoothing, a robust method is developed that permits the identification of targets and spirals foci independently of the wave profile. Examples of an analysis of long image sequences from experiments with the Belousov......–Zhabotinsky reaction catalyzed by ruthenium-tris-bipyridyl are presented. Moving target and spiral foci are found, and the speed and direction of movement of single as well as double spiral foci are investigated. For the experiments analyzed in this paper it is found that the movement of a focus correlates with foci...

The Quadrotor Dynamic Modeling and Indoor Target Tracking Control Method

Directory of Open Access Journals (Sweden)

Dewei Zhang

2014-01-01

Full Text Available A reliable nonlinear dynamic model of the quadrotor is presented. The nonlinear dynamic model includes actuator dynamic and aerodynamic effect. Since the rotors run near a constant hovering speed, the dynamic model is simplified at hovering operating point. Based on the simplified nonlinear dynamic model, the PID controllers with feedback linearization and feedforward control are proposed using the backstepping method. These controllers are used to control both the attitude and position of the quadrotor. A fully custom quadrotor is developed to verify the correctness of the dynamic model and control algorithms. The attitude of the quadrotor is measured by inertia measurement unit (IMU. The position of the quadrotor in a GPS-denied environment, especially indoor environment, is estimated from the downward camera and ultrasonic sensor measurements. The validity and effectiveness of the proposed dynamic model and control algorithms are demonstrated by experimental results. It is shown that the vehicle achieves robust vision-based hovering and moving target tracking control.

CHAOS: An SDN-Based Moving Target Defense System

Directory of Open Access Journals (Sweden)

Yuan Shi

2017-01-01

Full Text Available Moving target defense (MTD has provided a dynamic and proactive network defense to reduce or move the attack surface that is available for exploitation. However, traditional network is difficult to realize dynamic and active security defense effectively and comprehensively. Software-defined networking (SDN points out a brand-new path for building dynamic and proactive defense system. In this paper, we propose CHAOS, an SDN-based MTD system. Utilizing the programmability and flexibility of SDN, CHAOS obfuscates the attack surface including host mutation obfuscation, ports obfuscation, and obfuscation based on decoy servers, thereby enhancing the unpredictability of the networking environment. We propose the Chaos Tower Obfuscation (CTO method, which uses the Chaos Tower Structure (CTS to depict the hierarchy of all the hosts in an intranet and define expected connection and unexpected connection. Moreover, we develop fast CTO algorithms to achieve a different degree of obfuscation for the hosts in each layer. We design and implement CHAOS as an application of SDN controller. Our approach makes it very easy to realize moving target defense in networks. Our experimental results show that a network protected by CHAOS is capable of decreasing the percentage of information disclosure effectively to guarantee the normal flow of traffic.

Ballistic target tracking algorithm based on improved particle filtering

Science.gov (United States)

Ning, Xiao-lei; Chen, Zhan-qi; Li, Xiao-yang

2015-10-01

Tracking ballistic re-entry target is a typical nonlinear filtering problem. In order to track the ballistic re-entry target in the nonlinear and non-Gaussian complex environment, a novel chaos map particle filter (CMPF) is used to estimate the target state. CMPF has better performance in application to estimate the state and parameter of nonlinear and non-Gassuian system. The Monte Carlo simulation results show that, this method can effectively solve particle degeneracy and particle impoverishment problem by improving the efficiency of particle sampling to obtain the better particles to part in estimation. Meanwhile CMPF can improve the state estimation precision and convergence velocity compared with EKF, UKF and the ordinary particle filter.

Synchronizing the tracking eye movements with the motion of a visual target: Basic neural processes.

Science.gov (United States)

Goffart, Laurent; Bourrelly, Clara; Quinet, Julie

2017-01-01

In primates, the appearance of an object moving in the peripheral visual field elicits an interceptive saccade that brings the target image onto the foveae. This foveation is then maintained more or less efficiently by slow pursuit eye movements and subsequent catch-up saccades. Sometimes, the tracking is such that the gaze direction looks spatiotemporally locked onto the moving object. Such a spatial synchronism is quite spectacular when one considers that the target-related signals are transmitted to the motor neurons through multiple parallel channels connecting separate neural populations with different conduction speeds and delays. Because of the delays between the changes of retinal activity and the changes of extraocular muscle tension, the maintenance of the target image onto the fovea cannot be driven by the current retinal signals as they correspond to past positions of the target. Yet, the spatiotemporal coincidence observed during pursuit suggests that the oculomotor system is driven by a command estimating continuously the current location of the target, i.e., where it is here and now. This inference is also supported by experimental perturbation studies: when the trajectory of an interceptive saccade is experimentally perturbed, a correction saccade is produced in flight or after a short delay, and brings the gaze next to the location where unperturbed saccades would have landed at about the same time, in the absence of visual feedback. In this chapter, we explain how such correction can be supported by previous visual signals without assuming "predictive" signals encoding future target locations. We also describe the basic neural processes which gradually yield the synchronization of eye movements with the target motion. When the process fails, the gaze is driven by signals related to past locations of the target, not by estimates to its upcoming locations, and a catch-up is made to reinitiate the synchronization. © 2017 Elsevier B.V. All rights

COLOR INFLUENCES IDENTIFICATION OF THE MOVING OBJECTS MORE THAN SHAPE

Directory of Open Access Journals (Sweden)

Suncica Zdravkovic

2009-02-01

Full Text Available When people track moving objects, they concentrate on different characteristics.Recent results show that people more often concentrate on spatiotemporalthan featural properties of the objects. In other words, location and directionof motion seem to be more informative properties than the stable featuralcharacteristics. This finding contradicts some of our knowledge about cognitivesystem. Current research was done in attempt to specify the effect of featuralcharacteristics, especially color and shape. In Experiment 1, subjects were askedto track four mobile targets presented with another four moving objects. Afterthe motion has stopped, they had to mark the initial four targets. Our resultshave shown that participants pay more attention to the featural properties thanto spatiotemporal characteristics. Since our task was more difficult than thetasks typically reported in the literature, the results might be interpreted as if thesubjects relied mostly on attentional processes. The task in Experiment 2 wasmade even more difficult: the subjects were asked to direct attention on identityof every target. Consequently, the task demanded more complex cognitiveprocesses and emphasizing effects of featural properties. Results suggest thatcolor and shape does not have the same influences on multiple object tracking,but that color has more significant effect.

Moving finite element method for ICF target implosion

Science.gov (United States)

Furuta, J.; Kawata, S.; Niu, K.

1985-03-01

One dimensional hydrodynamic codes for the analysis of internal confinement fusion (ICF) target implosion which include various effects were developed, but most of them utilize the artificial viscosity (e.g., Von Neumann's viscosity) which cannot reveal accurately the shock waves. A gain of ICF target implosion is much due to the dissipation at the shock fronts, so it is necessary to express correctly the shock waves which are affected by the viscosity. The width of the shock waves is usually a few times as large as the length of mean free path, therefore the meshes for the shock waves must be set to about 10 to the 4th to 10 to the 5th power. It is a serious problem because of the computational memories or CPU time. In the moving finite element (MPE) method, both nodal amplitudes and nodal positions move continuously with time in such a way as to satisfy simultaneous ordinary differential equations (OPDs) which minimize partial differential equation (PDE) residuals.

Feature Extraction in Radar Target Classification

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Z. Kus

1999-09-01

Full Text Available This paper presents experimental results of extracting features in the Radar Target Classification process using the J frequency band pulse radar. The feature extraction is based on frequency analysis methods, the discrete-time Fourier Transform (DFT and Multiple Signal Characterisation (MUSIC, based on the detection of Doppler effect. The analysis has turned to the preference of DFT with implemented Hanning windowing function. We assumed to classify targets-vehicles into two classes, the wheeled vehicle and tracked vehicle. The results show that it is possible to classify them only while moving. The feature of the class results from a movement of moving parts of the vehicle. However, we have not found any feature to classify the wheeled and tracked vehicles while non-moving, although their engines are on.

Analysis of LFM-waveform Libraries for Cognitive Tracking Maneuvering Targets

Directory of Open Access Journals (Sweden)

Wang Hongyan

2016-01-01

Full Text Available Based on the idea of the waveform agility in cognitive radars，the waveform libraries for maneuvering target tracking are discussed. LFM-waveform libraries are designed according to different combinations of chirp parameters and FrFT rotation angles. By applying the interact multiple model (IMM algorithm in tracking maneuvering targets, transmitted waveform is called real time from the LFM-waveform libraries. The waveforms are selected from the library according to the criterion of maximum mutual information between the current state of knowledge of the model and the measurement. Simulation results show that waveform library containing certain amount LFM-waveforms can improve the performance of cognitive tracking radar.

Potential dosimetric benefits of adaptive tumor tracking over the internal target volume concept for stereotactic body radiation therapy of pancreatic cancer.

Science.gov (United States)

Karava, Konstantina; Ehrbar, Stefanie; Riesterer, Oliver; Roesch, Johannes; Glatz, Stefan; Klöck, Stephan; Guckenberger, Matthias; Tanadini-Lang, Stephanie

2017-11-09

Radiotherapy for pancreatic cancer has two major challenges: (I) the tumor is adjacent to several critical organs and, (II) the mobility of both, the tumor and its surrounding organs at risk (OARs). A treatment planning study simulating stereotactic body radiation therapy (SBRT) for pancreatic tumors with both the internal target volume (ITV) concept and the tumor tracking approach was performed. The two respiratory motion-management techniques were compared in terms of doses to the target volume and organs at risk. Two volumetric-modulated arc therapy (VMAT) treatment plans (5 × 5 Gy) were created for each of the 12 previously treated pancreatic cancer patients, one using the ITV concept and one the tumor tracking approach. To better evaluate the overall dose delivered to the moving tumor volume, 4D dose calculations were performed on four-dimensional computed tomography (4DCT) scans. The resulting planning target volume (PTV) size for each technique was analyzed. Target and OAR dose parameters were reported and analyzed for both 3D and 4D dose calculation. Tumor motion ranged from 1.3 to 11.2 mm. Tracking led to a reduction of PTV size (max. 39.2%) accompanied with significant better tumor coverage (p<0.05, paired Wilcoxon signed rank test) both in 3D and 4D dose calculations and improved organ at risk sparing. Especially for duodenum, stomach and liver, the mean dose was significantly reduced (p<0.05) with tracking for 3D and 4D dose calculations. By using an adaptive tumor tracking approach for respiratory-induced pancreatic motion management, a significant reduction in PTV size can be achieved, which subsequently facilitates treatment planning, and improves organ dose sparing. The dosimetric benefit of tumor tracking is organ and patient-specific.

Enhancement of tracking performance in electro-optical system based on servo control algorithm

Science.gov (United States)

Choi, WooJin; Kim, SungSu; Jung, DaeYoon; Seo, HyoungKyu

2017-10-01

Modern electro-optical surveillance and reconnaissance systems require tracking capability to get exact images of target or to accurately direct the line of sight to target which is moving or still. This leads to the tracking system composed of image based tracking algorithm and servo control algorithm. In this study, we focus on the servo control function to minimize the overshoot in the tracking motion and do not miss the target. The scheme is to limit acceleration and velocity parameters in the tracking controller, depending on the target state information in the image. We implement the proposed techniques by creating a system model of DIRCM and simulate the same environment, validate the performance on the actual equipment.

A Bayesian solution to multi-target tracking problems with mixed labelling

NARCIS (Netherlands)

Aoki, E.H.; Boers, Y.; Svensson, Lennart; Mandal, Pranab K.; Bagchi, Arunabha

In Multi-Target Tracking (MTT), the problem of assigning labels to tracks (track labelling) is vastly covered in literature and has been previously formulated using Bayesian recursion. However, the existing literature lacks an appropriate measure of uncertainty related to the assigned labels which

A Single Unexpected Change in Target- but Not Distractor Motion Impairs Multiple Object Tracking

Directory of Open Access Journals (Sweden)

Hauke S. Meyerhoff

2013-02-01

Full Text Available Recent research addresses the question whether motion information of multiple objects contributes to maintaining a selection of objects across a period of motion. Here, we investigate whether target and/or distractor motion information is used during attentive tracking. We asked participants to track four objects and changed either the motion direction of targets, the motion direction of distractors, neither, or both during a brief flash in the middle of a tracking interval. We observed that a single direction change of targets is sufficient to impair tracking performance. In contrast, changing the motion direction of distractors had no effect on performance. This indicates that target- but not distractor motion information is evaluated during tracking.

Numerical simulation on range of high-energy electron moving in accelerator target

International Nuclear Information System (INIS)

Shao Wencheng; Sun Punan; Dai Wenjiang

2008-01-01

In order to determine the range of high-energy electron moving in accelerator target, the range of electron with the energy range of 1 to 100 MeV moving in common target material of accelerator was calculated by Monte-Carlo method. Comparison between the calculated result and the published data were performed. The results of Monte-Carlo calculation are in good agreement with the published data. Empirical formulas were obtained for the range of high-energy electron with the energy range of 1 to 100 MeV in common target material by curve fitting, offering a series of referenced data for the design of targets in electron accelerator. (authors)

SAR Imaging of Ground Moving Targets with Non-ideal Motion Error Compensation(in English

Directory of Open Access Journals (Sweden)

Zhou Hui

2015-06-01

Full Text Available Conventional ground moving target imaging algorithms mainly focus on the range cell migration correction and the motion parameter estimation of the moving target. However, in real Synthetic Aperture Radar (SAR data processing, non-ideal motion error compensation is also a critical process, which focuses and has serious impacts on the imaging quality of moving targets. Non-ideal motion error can not be compensated by either the stationary SAR motion error compensation algorithms or the autofocus techniques. In this paper, two sorts of non-ideal motion errors that affect the Doppler centroid of the moving target is analyzed, and a novel non-ideal motion error compensation algorithm is proposed based on the Inertial Navigation System (INS data and the range walk trajectory. Simulated and real data processing results are provided to demonstrate the effectiveness of the proposed algorithm.

Models and Algorithms for Tracking Target with Coordinated Turn Motion

Directory of Open Access Journals (Sweden)

Xianghui Yuan

2014-01-01

Full Text Available Tracking target with coordinated turn (CT motion is highly dependent on the models and algorithms. First, the widely used models are compared in this paper—coordinated turn (CT model with known turn rate, augmented coordinated turn (ACT model with Cartesian velocity, ACT model with polar velocity, CT model using a kinematic constraint, and maneuver centered circular motion model. Then, in the single model tracking framework, the tracking algorithms for the last four models are compared and the suggestions on the choice of models for different practical target tracking problems are given. Finally, in the multiple models (MM framework, the algorithm based on expectation maximization (EM algorithm is derived, including both the batch form and the recursive form. Compared with the widely used interacting multiple model (IMM algorithm, the EM algorithm shows its effectiveness.

Detection of a faint fast-moving near-Earth asteroid using the synthetic tracking technique

Energy Technology Data Exchange (ETDEWEB)

Zhai, Chengxing; Shao, Michael; Nemati, Bijan; Werne, Thomas; Zhou, Hanying; Turyshev, Slava G.; Sandhu, Jagmit [Jet Propulsion Laboratory, California Institute of Technology, 4800 Oak Grove Drive, Pasadena, CA 91109 (United States); Hallinan, Gregg; Harding, Leon K., E-mail: chengxing.zhai@jpl.nasa.gov [Department of Astronomy, California Institute of Technology, 1200 East California Boulevard, Pasadena, CA 91125 (United States)

2014-09-01

We report a detection of a faint near-Earth asteroid (NEA) using our synthetic tracking technique and the CHIMERA instrument on the Palomar 200 inch telescope. With an apparent magnitude of 23 (H = 29, assuming detection at 20 lunar distances), the asteroid was moving at 6.°32 day{sup –1} and was detected at a signal-to-noise ratio (S/N) of 15 using 30 s of data taken at a 16.7 Hz frame rate. The detection was confirmed by a second observation 77 minutes later at the same S/N. Because of its high proper motion, the NEA moved 7 arcsec over the 30 s of observation. Synthetic tracking avoided image degradation due to trailing loss that affects conventional techniques relying on 30 s exposures; the trailing loss would have degraded the surface brightness of the NEA image on the CCD down to an approximate magnitude of 25 making the object undetectable. This detection was a result of our 12 hr blind search conducted on the Palomar 200 inch telescope over two nights, scanning twice over six (5.°3 × 0.°046) fields. Detecting only one asteroid is consistent with Harris's estimates for the distribution of the asteroid population, which was used to predict a detection of 1.2 NEAs in the H-magnitude range 28-31 for the two nights. The experimental design, data analysis methods, and algorithms are presented. We also demonstrate milliarcsecond-level astrometry using observations of two known bright asteroids on the same system with synthetic tracking. We conclude by discussing strategies for scheduling observations to detect and characterize small and fast-moving NEAs using the new technique.

Online Tracking of Outdoor Lighting Variations for Augmented Reality with Moving Cameras

OpenAIRE

Liu , Yanli; Granier , Xavier

2012-01-01

International audience; In augmented reality, one of key tasks to achieve a convincing visual appearance consistency between virtual objects and video scenes is to have a coherent illumination along the whole sequence. As outdoor illumination is largely dependent on the weather, the lighting condition may change from frame to frame. In this paper, we propose a full image-based approach for online tracking of outdoor illumination variations from videos captured with moving cameras. Our key ide...

Enhanced compressed sensing for visual target tracking in wireless visual sensor networks

Science.gov (United States)

Qiang, Guo

2017-11-01

Moving object tracking in wireless sensor networks (WSNs) has been widely applied in various fields. Designing low-power WSNs for the limited resources of the sensor, such as energy limitation, energy restriction, and bandwidth constraints, is of high priority. However, most existing works focus on only single conflicting optimization criteria. An efficient compressive sensing technique based on a customized memory gradient pursuit algorithm with early termination in WSNs is presented, which strikes compelling trade-offs among energy dissipation for wireless transmission, certain types of bandwidth, and minimum storage. Then, the proposed approach adopts an unscented particle filter to predict the location of the target. The experimental results with a theoretical analysis demonstrate the substantially superior effectiveness of the proposed model and framework in regard to the energy and speed under the resource limitation of a visual sensor node.

Tracking moving objects with megavoltage portal imaging: A feasibility study

International Nuclear Information System (INIS)

Meyer, Juergen; Richter, Anne; Baier, Kurt; Wilbert, Juergen; Guckenberger, Matthias; Flentje, Michael

2006-01-01

Four different algorithms were investigated with the aim to determine their suitability to track an object in conventional megavoltage portal images. The algorithms considered were the mean of the sum of squared differences (MSSD), mutual information (MI), the correlation ratio (CR), and the correlation coefficient (CC). Simulation studies were carried out with various image series containing a rigid object of interest that was moved along a predefined trajectory. For each of the series the signal-to-noise ratio (SNR) was varied to compare the performance of the algorithms under noisy conditions. For a poor SNR of -6 dB the mean tracking error was 2.4, 6.5, 39.0, and 17.2 pixels for MSSD, CC, CR and MI, respectively, with a standard deviation of 1.9, 12.9, 19.5, and 7.5 pixels, respectively. The size of a pixel was 0.5 mm. These results improved to 1.1, 1.3, 1.3, and 2.0 pixels, respectively, with a standard deviation of 0.6, 0.8, 0.8, and 2.1 pixels, respectively, when a mean filter was applied to the images prior to tracking. The implementation of MSSD into existing in-house software demonstrated that, depending on the search range, it was possible to process between 2 and 15 images/s, making this approach capable of real-time applications. In conclusion, the best geometric tracking accuracy overall was obtained with MSSD, followed by CC, CR, and MI. The simplest and best algorithm, both in terms of geometric accuracy as well as computational cost, was the MSSD algorithm and was therefore the method of choice

Dazzle camouflage and the confusion effect: the influence of varying speed on target tracking.

Science.gov (United States)

Hogan, Benedict G; Cuthill, Innes C; Scott-Samuel, Nicholas E

2017-01-01

The formation of groups is a common strategy to avoid predation in animals, and recent research has indicated that there may be interactions between some forms of defensive coloration, notably high-contrast 'dazzle camouflage', and one of the proposed benefits of grouping: the confusion effect. However, research into the benefits of dazzle camouflage has largely used targets moving with constant speed. This simplification may not generalize well to real animal systems, where a number of factors influence both within- and between-individual variation in speed. Departure from the speed of your neighbours in a group may be predicted to undermine the confusion effect. This is because individual speed may become a parameter through which the observer can individuate otherwise similar targets: an 'oddity effect'. However, dazzle camouflage patterns are thought to interfere with predator perception of speed and trajectory. The current experiment investigated the possibility that such patterns could ameliorate the oddity effect caused by within-group differences in prey speed. We found that variation in speed increased the ease with which participants could track targets in all conditions. However, we found no evidence that motion dazzle camouflage patterns reduced oddity effects based on this variation in speed, a result that may be informative about the mechanisms behind this form of defensive coloration. In addition, results from those conditions most similar to those of published studies replicated previous results, indicating that targets with stripes parallel to the direction of motion are harder to track, and that this pattern interacts with the confusion effect to a greater degree than background matching or orthogonal-to-motion striped patterns.

Cooperative multi-robot observation of multiple moving targets

International Nuclear Information System (INIS)

Parker, L.E.; Emmons, B.A.

1997-01-01

An important issue that arises in the automation of many security, surveillance, and reconnaissance tasks is that of monitoring, or observing, the movements of targets navigating in a bounded area of interest. A key research issue in these problems is that of sensor placement--determining where sensors should be located to maintain the targets in view. In complex applications of this type, the use of multiple sensors dynamically moving over time is required. In this paper, the authors investigate the sue of a cooperative team of autonomous sensor-based robots for multi-robot observation of multiple moving targets. They focus primarily on developing the distributed control strategies that allow the robot team to attempt to maximize the collective tie during which each object is being observed by at least one robot in the area of interest. The initial efforts in this problem address the aspects of distributed control in homogeneous robot teams with equivalent sensing and movement capabilities working in an uncluttered, bounded area. This paper first formalizes the problem, discusses related work, and then shows that this problem is NP-hard. They then present a distributed approximate approach to solving this problem that combines low-level multi-robot control with higher-level control

Multiple Maneuvering Target Tracking by Improved Particle Filter Based on Multiscan JPDA

Directory of Open Access Journals (Sweden)

Jing Liu

2012-01-01

Full Text Available The multiple maneuvering target tracking algorithm based on a particle filter is addressed. The equivalent-noise approach is adopted, which uses a simple dynamic model consisting of target state and equivalent noise which accounts for the combined effects of the process noise and maneuvers. The equivalent-noise approach converts the problem of maneuvering target tracking to that of state estimation in the presence of nonstationary process noise with unknown statistics. A novel method for identifying the nonstationary process noise is proposed in the particle filter framework. Furthermore, a particle filter based multiscan Joint Probability Data Association (JPDA filter is proposed to deal with the data association problem in a multiple maneuvering target tracking. In the proposed multiscan JPDA algorithm, the distributions of interest are the marginal filtering distributions for each of the targets, and these distributions are approximated with particles. The multiscan JPDA algorithm examines the joint association events in a multiscan sliding window and calculates the marginal posterior probability based on the multiscan joint association events. The proposed algorithm is illustrated via an example involving the tracking of two highly maneuvering, at times closely spaced and crossed, targets, based on resolved measurements.

Efficient and Adaptive Node Selection for Target Tracking in Wireless Sensor Network

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Juan Feng

2016-01-01

Full Text Available In target tracking wireless sensor network, choosing the proper working nodes can not only minimize the number of active nodes, but also satisfy the tracking reliability requirement. However, most existing works focus on selecting sensor nodes which are the nearest to the target for tracking missions and they did not consider the correlation of the location of the sensor nodes so that these approaches can not meet all the goals of the network. This work proposes an efficient and adaptive node selection approach for tracking a target in a distributed wireless sensor network. The proposed approach combines the distance-based node selection strategy and particle filter prediction considering the spatial correlation of the different sensing nodes. Moreover, a joint distance weighted measurement is proposed to estimate the information utility of sensing nodes. Experimental results show that EANS outperformed the state-of-the-art approaches by reducing the energy cost and computational complexity as well as guaranteeing the tracking accuracy.

Method for Multiple Targets Tracking in Cognitive Radar Based on Compressed Sensing

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Yang Jun

2016-02-01

Full Text Available A multiple targets cognitive radar tracking method based on Compressed Sensing (CS is proposed. In this method, the theory of CS is introduced to the case of cognitive radar tracking process in multiple targets scenario. The echo signal is sparsely expressed. The designs of sparse matrix and measurement matrix are accomplished by expressing the echo signal sparsely, and subsequently, the restruction of measurement signal under the down-sampling condition is realized. On the receiving end, after considering that the problems that traditional particle filter suffers from degeneracy, and require a large number of particles, the particle swarm optimization particle filter is used to track the targets. On the transmitting end, the Posterior Cramér-Rao Bounds (PCRB of the tracking accuracy is deduced, and the radar waveform parameters are further cognitively designed using PCRB. Simulation results show that the proposed method can not only reduce the data quantity, but also provide a better tracking performance compared with traditional method.

Target injection and tracking for inertial fusion energy

Energy Technology Data Exchange (ETDEWEB)

Petzoldt, R.W. [Lawrence Livermore National Lab., CA (United States); Moir, R.W. [Lawrence Livermore National Lab., CA (United States)

1996-11-01

In an inertial fusion power plant, several cryogenic targets must be injected each second into a reaction chamber with speeds of about 100 m s{sup -1}. This speed can be achieved with an acceleration in the range from 1000 to 10 000 m s{sup -2}. The total accuracy of driver beam pointing and target position prediction must be less than {+-}0.6 mm for a 3 mm beam spot radius. A 0.1 {mu}m thick dual membrane supporting the capsule in the hohlraum will allow nearly 2000 m s{sup -2} acceleration. The strength of frozen DT in the capsule is calculated to allow acceleration in excess of 10 000 m s{sup -2} if the DT temperature is less than 17 K. A gas gun is the preferred device for injecting indirect drive targets owing to its simplicity and proven reliability. The amount of gas required for each target (about 10-100 mg) is acceptable. A revolver loading mechanism is recommendced with a cam-operated poppet valve to control the gas flow. Slots near the muzzle of the gun barrel are recommended to vent gas and thereby to improve accuracy and to aid gas pumping. Optical target tracking and electronic timing devices can predict target arrival time with sufficient accuracy. Target steering by electrostatic deflection of the in-flight target is shown to be feasible and would avoid the need to point the beams actively. Calculations show that induced tumble from electrostatically steering the target is not excessive. An experiment has been designed to develop target injection and to verify the predicted accuracy of sequential injection and tracking of multiple targets. (orig.)

A moving target for accelerated charged particle induced X-ray measurement

International Nuclear Information System (INIS)

Chuang, L.S.; Shima, K.; Ebihara, H.; Seki, R.; Mikumo, T.

1980-01-01

To attain good reproducibility as well as to enable an absolute determination in the measurement of X-ray fluorescences, resulting from bombardment of a heterogeneous sample by accelerated charged particles, a moving-target mechanism incorporating an electronic remote control system has been devised. The system is designed to scan the whole sample area with a chosen constant linear speed, by a fixed particle beam with a cross-sectional area a small fraction of that of the sample. Using 16 MeV protons and 40 MeV oxygen-ion beams, test runs of this system showed that the attempted objectives are attainable with good accuracies: reproducibility of the data for a given target is better than 3%, the linearity of the calibration curve is in good agreement, within the weighing errors of the standard elements and the uncertainty due to beam current fluctuation, with the expected values, and the results of absolute determinations using both metal foils and heterogeneous powder samples are in good agreement with accepted results using different methods. Detailed accounts of the moving-target system, and the test for reproducibility and linearity are presented. An absolute determination of the quantities related to accelerated charged-particle induced X-ray fluorescence (PIXE) using the moving target is presented for samples in different forms. (orig./HP)

Robotics Vision-based Heuristic Reasoning for Underwater Target Tracking and Navigation

OpenAIRE

Kia, Chua; Arshad, Mohd Rizal

2006-01-01

This paper presents a robotics vision-based heuristic reasoning system for underwater target tracking and navigation. This system is introduced to improve the level of automation of underwater Remote Operated Vehicles (ROVs) operations. A prototype which combines computer vision with an underwater robotics system is successfully designed and developed to perform target tracking and intelligent navigation. This study focuses on developing image processing algorithms and fuzzy inference system ...

Estimation of Radar Cross Section of a Target under Track

Directory of Open Access Journals (Sweden)

Hong Sun-Mog

2010-01-01

Full Text Available In allocating radar beam for tracking a target, it is attempted to maintain the signal-to-noise ratio (SNR of signal returning from the illuminated target close to an optimum value for efficient track updates. An estimate of the average radar cross section (RCS of the target is required in order to adjust transmitted power based on the estimate such that a desired SNR can be realized. In this paper, a maximum-likelihood (ML approach is presented for estimating the average RCS, and a numerical solution to the approach is proposed based on a generalized expectation maximization (GEM algorithm. Estimation accuracy of the approach is compared to that of a previously reported procedure.

Event-triggered cooperative target tracking in wireless sensor networks

Directory of Open Access Journals (Sweden)

Lu Kelin

2016-10-01

Full Text Available Since the issues of low communication bandwidth supply and limited battery capacity are very crucial for wireless sensor networks, this paper focuses on the problem of event-triggered cooperative target tracking based on set-membership information filtering. We study some fundamental properties of the set-membership information filter with multiple sensor measurements. First, a sufficient condition is derived for the set-membership information filter, under which the boundedness of the outer ellipsoidal approximation set of the estimation means is guaranteed. Second, the equivalence property between the parallel and sequential versions of the set-membership information filter is presented. Finally, the results are applied to a 1D event-triggered target tracking scenario in which the negative information is exploited in the sense that the measurements that do not satisfy the triggering conditions are modelled as set-membership measurements. The tracking performance of the proposed method is validated with extensive Monte Carlo simulations.

Does the Brain Extrapolate the Position of a Transient Moving Target?

Science.gov (United States)

Quinet, Julie; Goffart, Laurent

2015-08-26

When an object moves in the visual field, its motion evokes a streak of activity on the retina and the incoming retinal signals lead to robust oculomotor commands because corrections are observed if the trajectory of the interceptive saccade is perturbed by a microstimulation in the superior colliculus. The present study complements a previous perturbation study by investigating, in the head-restrained monkey, the generation of saccades toward a transient moving target (100-200 ms). We tested whether the saccades land on the average of antecedent target positions or beyond the location where the target disappeared. Using target motions with different speed profiles, we also examined the sensitivity of the process that converts time-varying retinal signals into saccadic oculomotor commands. The results show that, for identical overall target displacements on the visual display, saccades toward a faster target land beyond the endpoint of saccades toward a target moving slower. The rate of change in speed matters in the visuomotor transformation. Indeed, in response to identical overall target displacements and durations, the saccades have smaller amplitude when they are made in response to an accelerating target than to a decelerating one. Moreover, the motion-related signals have different weights depending upon their timing relative to the target onset: early signals are more influential in the specification of saccade amplitude than later signals. We discuss the "predictive" properties of the visuo-saccadic system and the nature of this location where the saccades land, after providing some critical comments to the "hic-et-nunc" hypothesis (Fleuriet and Goffart, 2012). Complementing the work of Fleuriet and Goffart (2012), this study is a contribution to the more general scientific research aimed at understanding how ongoing action is dynamically and adaptively adjusted to the current spatiotemporal aspects of its goal. Using the saccadic eye movement as a probe

Development of target-tracking algorithms using neural network

Energy Technology Data Exchange (ETDEWEB)

Park, Dong Sun; Lee, Joon Whaoan; Yoon, Sook; Baek, Seong Hyun; Lee, Myung Jae [Chonbuk National University, Chonjoo (Korea)

1998-04-01

The utilization of remote-control robot system in atomic power plants or nuclear-related facilities grows rapidly, to protect workers form high radiation environments. Such applications require complete stability of the robot system, so that precisely tracking the robot is essential for the whole system. This research is to accomplish the goal by developing appropriate algorithms for remote-control robot systems. A neural network tracking system is designed and experimented to trace a robot Endpoint. This model is aimed to utilized the excellent capabilities of neural networks; nonlinear mapping between inputs and outputs, learning capability, and generalization capability. The neural tracker consists of two networks for position detection and prediction. Tracking algorithms are developed and experimented for the two models. Results of the experiments show that both models are promising as real-time target-tracking systems for remote-control robot systems. (author). 10 refs., 47 figs.

The search for an alerted moving target; 2005BU2-OA

NARCIS (Netherlands)

Vermeulen, J.F.J.; Brink, M. van den

2005-01-01

We investigate a two-sided, multi-stage search problem where a continuous search effort is made by one or more search units to detect a moving target in a continuous target space, under noisy detection conditions. A specific example of this problem is hunting for an enemy submarine by naval forces.

Multi-agent target tracking using particle filters enhanced with context data

CSIR Research Space (South Africa)

Claessens, R

2015-05-01

Full Text Available The proposed framework for Multi-Agent Target Tracking supports i) tracking of objects and ii) search and rescue based on the fusion of very heterogeneous data. The system is based on a novel approach to fusing sensory observations, intelligence...

Passive target tracking using marginalized particle filter

Institute of Scientific and Technical Information of China (English)

无

2007-01-01

A marginalized particle filtering(MPF)approach is proposed for target tracking under the background of passive measurement.Essentially,the MPF is a combination of particle filtering technique and Kalman filter.By making full use of marginalization,the distributions of the tractable linear part of the total state variables are updated analytically using Kalman filter,and only the lower-dimensional nonlinear state variable needs to be dealt with using particle filter.Simulation studies are performed on an illustrative example,and the results show that the MPF method leads to a significant reduction of the tracking errors when compared with the direct particle implementation.Real data test results also validate the effectiveness of the presented method.

Online variational Bayesian filtering-based mobile target tracking in wireless sensor networks.

Science.gov (United States)

Zhou, Bingpeng; Chen, Qingchun; Li, Tiffany Jing; Xiao, Pei

2014-11-11

The received signal strength (RSS)-based online tracking for a mobile node in wireless sensor networks (WSNs) is investigated in this paper. Firstly, a multi-layer dynamic Bayesian network (MDBN) is introduced to characterize the target mobility with either directional or undirected movement. In particular, it is proposed to employ the Wishart distribution to approximate the time-varying RSS measurement precision's randomness due to the target movement. It is shown that the proposed MDBN offers a more general analysis model via incorporating the underlying statistical information of both the target movement and observations, which can be utilized to improve the online tracking capability by exploiting the Bayesian statistics. Secondly, based on the MDBN model, a mean-field variational Bayesian filtering (VBF) algorithm is developed to realize the online tracking of a mobile target in the presence of nonlinear observations and time-varying RSS precision, wherein the traditional Bayesian filtering scheme cannot be directly employed. Thirdly, a joint optimization between the real-time velocity and its prior expectation is proposed to enable online velocity tracking in the proposed online tacking scheme. Finally, the associated Bayesian Cramer-Rao Lower Bound (BCRLB) analysis and numerical simulations are conducted. Our analysis unveils that, by exploiting the potential state information via the general MDBN model, the proposed VBF algorithm provides a promising solution to the online tracking of a mobile node in WSNs. In addition, it is shown that the final tracking accuracy linearly scales with its expectation when the RSS measurement precision is time-varying.

Moving Shadow Detection in Video Using Cepstrum

Directory of Open Access Journals (Sweden)

Fuat Cogun

2013-01-01

Full Text Available Moving shadows constitute problems in various applications such as image segmentation and object tracking. The main cause of these problems is the misclassification of the shadow pixels as target pixels. Therefore, the use of an accurate and reliable shadow detection method is essential to realize intelligent video processing applications. In this paper, a cepstrum-based method for moving shadow detection is presented. The proposed method is tested on outdoor and indoor video sequences using well-known benchmark test sets. To show the improvements over previous approaches, quantitative metrics are introduced and comparisons based on these metrics are made.

3D Visual Tracking of an Articulated Robot in Precision Automated Tasks.

Science.gov (United States)

Alzarok, Hamza; Fletcher, Simon; Longstaff, Andrew P

2017-01-07

The most compelling requirements for visual tracking systems are a high detection accuracy and an adequate processing speed. However, the combination between the two requirements in real world applications is very challenging due to the fact that more accurate tracking tasks often require longer processing times, while quicker responses for the tracking system are more prone to errors, therefore a trade-off between accuracy and speed, and vice versa is required. This paper aims to achieve the two requirements together by implementing an accurate and time efficient tracking system. In this paper, an eye-to-hand visual system that has the ability to automatically track a moving target is introduced. An enhanced Circular Hough Transform (CHT) is employed for estimating the trajectory of a spherical target in three dimensions, the colour feature of the target was carefully selected by using a new colour selection process, the process relies on the use of a colour segmentation method (Delta E) with the CHT algorithm for finding the proper colour of the tracked target, the target was attached to the six degree of freedom (DOF) robot end-effector that performs a pick-and-place task. A cooperation of two Eye-to Hand cameras with their image Averaging filters are used for obtaining clear and steady images. This paper also examines a new technique for generating and controlling the observation search window in order to increase the computational speed of the tracking system, the techniques is named Controllable Region of interest based on Circular Hough Transform (CRCHT). Moreover, a new mathematical formula is introduced for updating the depth information of the vision system during the object tracking process. For more reliable and accurate tracking, a simplex optimization technique was employed for the calculation of the parameters for camera to robotic transformation matrix. The results obtained show the applicability of the proposed approach to track the moving robot

A System based on Adaptive Background Subtraction Approach for Moving Object Detection and Tracking in Videos

Directory of Open Access Journals (Sweden)

Bahadır KARASULU

2013-04-01

Full Text Available Video surveillance systems are based on video and image processing research areas in the scope of computer science. Video processing covers various methods which are used to browse the changes in existing scene for specific video. Nowadays, video processing is one of the important areas of computer science. Two-dimensional videos are used to apply various segmentation and object detection and tracking processes which exists in multimedia content-based indexing, information retrieval, visual and distributed cross-camera surveillance systems, people tracking, traffic tracking and similar applications. Background subtraction (BS approach is a frequently used method for moving object detection and tracking. In the literature, there exist similar methods for this issue. In this research study, it is proposed to provide a more efficient method which is an addition to existing methods. According to model which is produced by using adaptive background subtraction (ABS, an object detection and tracking system’s software is implemented in computer environment. The performance of developed system is tested via experimental works with related video datasets. The experimental results and discussion are given in the study

Detecting and Georegistering Moving Ground Targets in Airborne QuickSAR via Keystoning and Multiple-Phase Center Interferometry

Directory of Open Access Journals (Sweden)

R. P. Perry

2008-03-01

Full Text Available SAR images experience significant range walk and, without some form of motion compensation, can be quite blurred. The MITRE-developed Keystone formatting simultaneously and automatically compensates for range walk due to the radial velocity component of each moving target, independent of the number of targets or the value of each target's radial velocity with respect to the ground. Target radial motion also causes moving targets in synthetic aperture radar images to appear at locations offset from their true instantaneous locations on the ground. In a multichannel radar, the interferometric phase values associated with all nonmoving points on the ground appear as a continuum of phase differences while the moving targets appear as interferometric phase discontinuities. By multiple threshold comparisons and grouping of pixels within the intensity and the phase images, we show that it is possible to reliably detect and accurately georegister moving targets within short-duration SAR (QuickSAR images.

Saccadic foveation of a moving visual target in the rhesus monkey.

Science.gov (United States)

Fleuriet, Jérome; Hugues, Sandrine; Perrinet, Laurent; Goffart, Laurent

2011-02-01

When generating a saccade toward a moving target, the target displacement that occurs during the period spanning from its detection to the saccade end must be taken into account to accurately foveate the target and to initiate its pursuit. Previous studies have shown that these saccades are characterized by a lower peak velocity and a prolonged deceleration phase. In some cases, a second peak eye velocity appears during the deceleration phase, presumably reflecting the late influence of a mechanism that compensates for the target displacement occurring before saccade end. The goal of this work was to further determine in the head restrained monkey the dynamics of this putative compensatory mechanism. A step-ramp paradigm, where the target motion was orthogonal to a target step occurring along the primary axes, was used to estimate from the generated saccades: a component induced by the target step and another one induced by the target motion. Resulting oblique saccades were compared with saccades to a static target with matched horizontal and vertical amplitudes. This study permitted to estimate the time taken for visual motion-related signals to update the programming and execution of saccades. The amplitude of the motion-related component was slightly hypometric with an undershoot that increased with target speed. Moreover, it matched with the eccentricity that the target had 40-60 ms before saccade end. The lack of significant difference in the delay between the onsets of the horizontal and vertical components between saccades directed toward a static target and those aimed at a moving target questions the late influence of the compensatory mechanism. The results are discussed within the framework of the "dual drive" and "remapping" hypotheses.

Image-Based Multi-Target Tracking through Multi-Bernoulli Filtering with Interactive Likelihoods.

Science.gov (United States)

Hoak, Anthony; Medeiros, Henry; Povinelli, Richard J

2017-03-03

We develop an interactive likelihood (ILH) for sequential Monte Carlo (SMC) methods for image-based multiple target tracking applications. The purpose of the ILH is to improve tracking accuracy by reducing the need for data association. In addition, we integrate a recently developed deep neural network for pedestrian detection along with the ILH with a multi-Bernoulli filter. We evaluate the performance of the multi-Bernoulli filter with the ILH and the pedestrian detector in a number of publicly available datasets (2003 PETS INMOVE, Australian Rules Football League (AFL) and TUD-Stadtmitte) using standard, well-known multi-target tracking metrics (optimal sub-pattern assignment (OSPA) and classification of events, activities and relationships for multi-object trackers (CLEAR MOT)). In all datasets, the ILH term increases the tracking accuracy of the multi-Bernoulli filter.

Square tracking sensor for autonomous helicopter hover stabilization

Science.gov (United States)

Oertel, Carl-Henrik

1995-06-01

Sensors for synthetic vision are needed to extend the mission profiles of helicopters. A special task for various applications is the autonomous position hold of a helicopter above a ground fixed or moving target. As a proof of concept for a general synthetic vision solution a restricted machine vision system, which is capable of locating and tracking a special target, was developed by the Institute of Flight Mechanics of Deutsche Forschungsanstalt fur Luft- und Raumfahrt e.V. (i.e., German Aerospace Research Establishment). This sensor, which is specialized to detect and track a square, was integrated in the fly-by-wire helicopter ATTHeS (i.e., Advanced Technology Testing Helicopter System). An existing model following controller for the forward flight condition was adapted for the hover and low speed requirements of the flight vehicle. The special target, a black square with a length of one meter, was mounted on top of a car. Flight tests demonstrated the automatic stabilization of the helicopter above the moving car by synthetic vision.

Target Tracking of a Linear Time Invariant System under Irregular Sampling

Directory of Open Access Journals (Sweden)

Jin Xue-Bo

2012-11-01

Full Text Available Due to event-triggered sampling in a system, or maybe with the aim of reducing data storage, tracking many applications will encounter irregular sampling time. By calculating the matrix exponential using an inverse Laplace transform, this paper transforms the irregular sampling tracking problem to the problem of tracking with time-varying parameters of a system. Using the common Kalman filter, the developed method is used to track a target for the simulated trajectory and video tracking. The results of simulation experiments have shown that it can obtain good estimation performance even at a very high irregular rate of measurement sampling time.

Bearings-Only Tracking of Manoeuvring Targets Using Particle Filters

Directory of Open Access Journals (Sweden)

M. Sanjeev Arulampalam

2004-11-01

Full Text Available We investigate the problem of bearings-only tracking of manoeuvring targets using particle filters (PFs. Three different (PFs are proposed for this problem which is formulated as a multiple model tracking problem in a jump Markov system (JMS framework. The proposed filters are (i multiple model PF (MMPF, (ii auxiliary MMPF (AUX-MMPF, and (iii jump Markov system PF (JMS-PF. The performance of these filters is compared with that of standard interacting multiple model (IMM-based trackers such as IMM-EKF and IMM-UKF for three separate cases: (i single-sensor case, (ii multisensor case, and (iii tracking with hard constraints. A conservative CRLB applicable for this problem is also derived and compared with the RMS error performance of the filters. The results confirm the superiority of the PFs for this difficult nonlinear tracking problem.

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).

DMPD: Fifty years of interferon research: aiming at a moving target. [Dynamic Macrophage Pathway CSML Database

Lifescience Database Archive (English)

Full Text Available mmunity. 2006 Sep;25(3):343-8. (.png) (.svg) (.html) (.csml) Show Fifty years of interferon research: aiming at a moving target. Pubm...edID 16979566 Title Fifty years of interferon research: aiming at a moving target.

Tracking planets and moons: mechanisms of object tracking revealed with a new paradigm.

Science.gov (United States)

Tombu, Michael; Seiffert, Adriane E

2011-04-01

People can attend to and track multiple moving objects over time. Cognitive theories of this ability emphasize location information and differ on the importance of motion information. Results from several experiments have shown that increasing object speed impairs performance, although speed was confounded with other properties such as proximity of objects to one another. Here, we introduce a new paradigm to study multiple object tracking in which object speed and object proximity were manipulated independently. Like the motion of a planet and moon, each target-distractor pair rotated about both a common local point as well as the center of the screen. Tracking performance was strongly affected by object speed even when proximity was controlled. Additional results suggest that two different mechanisms are used in object tracking--one sensitive to speed and proximity and the other sensitive to the number of distractors. These observations support models of object tracking that include information about object motion and reject models that use location alone.

SU-E-J-199: Evaluation of Motion Tracking Effects On Stereotactic Body Radiotherapy of Abdominal Targets

Energy Technology Data Exchange (ETDEWEB)

Monterroso, M; Dogan, N; Yang, Y [University Miami, Miami, FL (United States)

2014-06-01

Purpose: To evaluate the effects of respiratory motion on the delivered dose distribution of CyberKnife motion tracking-based stereotactic body radiotherapy (SBRT) of abdominal targets. Methods: Four patients (two pancreas and two liver, and all with 4DCT scans) were retrospectively evaluated. A plan (3D plan) using CyberKnife Synchrony was optimized on the end-exhale phase in the CyberKnife's MultiPlan treatment planning system (TPS), with 40Gy prescribed in 5 fractions. A 4D plan was then created following the 4D planning utility in the MultiPlan TPS, by recalculating dose from the 3D plan beams on all 4DCT phases, with the same prescribed isodose line. The other seven phases of the 4DCT were then deformably registered to the end-exhale phase for 4D dose summation. Doses to the target and organs at risk (OAR) were compared between 3D and 4D plans for each patient. The mean and maximum doses to duodenum, liver, spinal cord and kidneys, and doses to 5cc of duodenum, 700cc of liver, 0.25cc of spinal cord and 200cc of kidneys were used. Results: Target coverage in the 4D plans was about 1% higher for two patients and about 9% lower in the other two. OAR dose differences between 3D and 4D varied among structures, with doses as much as 8.26Gy lower or as much as 5.41Gy higher observed in the 4D plans. Conclusion: The delivered dose can be significantly different from the planned dose for both the target and OAR close to the target, which is caused by the relative geometry change while the beams chase the moving target. Studies will be performed on more patients in the future. The differences of motion tracking versus passive motion management with the use of internal target volumes will also be investigated.

Image-Based Multi-Target Tracking through Multi-Bernoulli Filtering with Interactive Likelihoods

Directory of Open Access Journals (Sweden)

Anthony Hoak

2017-03-01

Full Text Available We develop an interactive likelihood (ILH for sequential Monte Carlo (SMC methods for image-based multiple target tracking applications. The purpose of the ILH is to improve tracking accuracy by reducing the need for data association. In addition, we integrate a recently developed deep neural network for pedestrian detection along with the ILH with a multi-Bernoulli filter. We evaluate the performance of the multi-Bernoulli filter with the ILH and the pedestrian detector in a number of publicly available datasets (2003 PETS INMOVE, Australian Rules Football League (AFL and TUD-Stadtmitte using standard, well-known multi-target tracking metrics (optimal sub-pattern assignment (OSPA and classification of events, activities and relationships for multi-object trackers (CLEAR MOT. In all datasets, the ILH term increases the tracking accuracy of the multi-Bernoulli filter.

Kalman filter-based tracking of moving objects using linear ultrasonic sensor array for road vehicles

Science.gov (United States)

Li, Shengbo Eben; Li, Guofa; Yu, Jiaying; Liu, Chang; Cheng, Bo; Wang, Jianqiang; Li, Keqiang

2018-01-01

Detection and tracking of objects in the side-near-field has attracted much attention for the development of advanced driver assistance systems. This paper presents a cost-effective approach to track moving objects around vehicles using linearly arrayed ultrasonic sensors. To understand the detection characteristics of a single sensor, an empirical detection model was developed considering the shapes and surface materials of various detected objects. Eight sensors were arrayed linearly to expand the detection range for further application in traffic environment recognition. Two types of tracking algorithms, including an Extended Kalman filter (EKF) and an Unscented Kalman filter (UKF), for the sensor array were designed for dynamic object tracking. The ultrasonic sensor array was designed to have two types of fire sequences: mutual firing or serial firing. The effectiveness of the designed algorithms were verified in two typical driving scenarios: passing intersections with traffic sign poles or street lights, and overtaking another vehicle. Experimental results showed that both EKF and UKF had more precise tracking position and smaller RMSE (root mean square error) than a traditional triangular positioning method. The effectiveness also encourages the application of cost-effective ultrasonic sensors in the near-field environment perception in autonomous driving systems.

Development of Feedforward Control in a Dynamic Manual Tracking Task

Science.gov (United States)

van Roon, Dominique; Caeyenberghs, Karen; Swinnen, Stephan P.; Smits-Engelsman, Bouwien C. M.

2008-01-01

To examine the development of feedforward control during manual tracking, 117 participants in 5 age groups (6 to 7, 8 to 9, 10 to 11, 12 to 14, and 15 to 17 years) tracked an accelerating dot presented on a monitor by moving an electronic pen on a digitizer. To remain successful at higher target velocities, they had to create a predictive model of…

Moving Target Techniques: Cyber Resilience throught Randomization, Diversity, and Dynamism

Science.gov (United States)

2017-03-03

attacks. Simply put, these techniques turn systems into moving targets that will be hard for cyber attackers to compromise. MT techniques leverage...been diversified, they can attack it as if it was not diversified at all. Dynamic Data: Techniques in the dynamic data domain change the format

Neuromorphic Modeling of Moving Target Detection in Insects

Science.gov (United States)

2007-12-31

Standard Form 298 (Rev. 8/98) Prescribed by ANSI Std. Z39, 18 Grants FA9550-04-1-0283 and FA9550-04-1-0294 Neuromorphic Modeling of Moving Target Detection...natural for neuromorphic sensory processing. We developed visual motion detection circuitry, including photodetectors, early vision, and models for both...Lincoln Labs 3DM2 run, Tanner Research reserved and utilized space corresponding to two MOSIS ’tiny chips ’ (2mm square each), each with three interconnected

Moving Object Tracking and Avoidance Algorithm for Differential Driving AGV Based on Laser Measurement Technology

Directory of Open Access Journals (Sweden)

Pandu Sandi Pratama

2012-12-01

Full Text Available This paper proposed an algorithm to track the obstacle position and avoid the moving objects for differential driving Automatic Guided Vehicles (AGV system in industrial environment. This algorithm has several abilities such as: to detect the moving objects, to predict the velocity and direction of moving objects, to predict the collision possibility and to plan the avoidance maneuver. For sensing the local environment and positioning, the laser measurement system LMS-151 and laser navigation system NAV-200 are applied. Based on the measurement results of the sensors, the stationary and moving obstacles are detected and the collision possibility is calculated. The velocity and direction of the obstacle are predicted using Kalman filter algorithm. Collision possibility, time, and position can be calculated by comparing the AGV movement and obstacle prediction result obtained by Kalman filter. Finally the avoidance maneuver using the well known tangent Bug algorithm is decided based on the calculation data. The effectiveness of proposed algorithm is verified using simulation and experiment. Several examples of experiment conditions are presented using stationary obstacle, and moving obstacles. The simulation and experiment results show that the AGV can detect and avoid the obstacles successfully in all experimental condition. [Keywords— Obstacle avoidance, AGV, differential drive, laser measurement system, laser navigation system].

On the Impact of Localization and Density Control Algorithms in Target Tracking Applications for Wireless Sensor Networks

Science.gov (United States)

Campos, Andre N.; Souza, Efren L.; Nakamura, Fabiola G.; Nakamura, Eduardo F.; Rodrigues, Joel J. P. C.

2012-01-01

Target tracking is an important application of wireless sensor networks. The networks' ability to locate and track an object is directed linked to the nodes' ability to locate themselves. Consequently, localization systems are essential for target tracking applications. In addition, sensor networks are often deployed in remote or hostile environments. Therefore, density control algorithms are used to increase network lifetime while maintaining its sensing capabilities. In this work, we analyze the impact of localization algorithms (RPE and DPE) and density control algorithms (GAF, A3 and OGDC) on target tracking applications. We adapt the density control algorithms to address the k-coverage problem. In addition, we analyze the impact of network density, residual integration with density control, and k-coverage on both target tracking accuracy and network lifetime. Our results show that DPE is a better choice for target tracking applications than RPE. Moreover, among the evaluated density control algorithms, OGDC is the best option among the three. Although the choice of the density control algorithm has little impact on the tracking precision, OGDC outperforms GAF and A3 in terms of tracking time. PMID:22969329

Taking aim at a moving target: designing drugs to inhibit drug-resistant HIV-1 reverse transcriptases.

Science.gov (United States)

Sarafianos, Stefan G; Das, Kalyan; Hughes, Stephen H; Arnold, Eddy

2004-12-01

HIV undergoes rapid genetic variation; this variation is caused primarily by the enormous number of viruses produced daily in an infected individual. Because of this variation, HIV presents a moving target for drug and vaccine development. The variation within individuals has led to the generation of diverse HIV-1 subtypes, which further complicates the development of effective drugs and vaccines. In general, it is more difficult to hit a moving target than a stationary target. Two broad strategies for hitting a moving target (in this case, HIV replication) are to understand the movement and to aim at the portions that move the least. In the case of anti-HIV drug development, the first option can be addressed by understanding the mechanism(s) of drug resistance and developing drugs that effectively inhibit mutant viruses. The second can be addressed by designing drugs that interact with portions of the viral machinery that are evolutionarily conserved, such as enzyme active sites.

Moving target feature phenomenology data collection at China Lake

Science.gov (United States)

Gross, David C.; Hill, Jeff; Schmitz, James L.

2002-08-01

This paper describes the DARPA Moving Target Feature Phenomenology (MTFP) data collection conducted at the China Lake Naval Weapons Center's Junction Ranch in July 2001. The collection featured both X-band and Ku-band radars positioned on top of Junction Ranch's Parrot Peak. The test included seven targets used in eleven configurations with vehicle motion consisting of circular, straight-line, and 90-degree turning motion. Data was collected at 10-degree and 17-degree depression angles. Key parameters in the collection were polarization, vehicle speed, and road roughness. The collection also included a canonical target positioned at Junction Ranch's tilt-deck turntable. The canonical target included rotating wheels (military truck tire and civilian pick-up truck tire) and a flat plate with variable positioned corner reflectors. The canonical target was also used to simulate a rotating antenna and a vibrating plate. The target vehicles were instrumented with ARDS pods for differential GPS and roll, pitch and yaw measurements. Target motion was also documented using a video camera slaved to the X-band radar antenna and by a video camera operated near the target site.

Wake Shield Target Protection

International Nuclear Information System (INIS)

Valmianski, Emanuil I.; Petzoldt, Ronald W.; Alexander, Neil B.

2003-01-01

The heat flux from both gas convection and chamber radiation on a direct drive target must be limited to avoid target damage from excessive D-T temperature increase. One of the possibilities of protecting the target is a wake shield flying in front of the target. A shield will also reduce drag force on the target, thereby facilitating target tracking and position prediction. A Direct Simulation Monte Carlo (DSMC) code was used to calculate convection heat loads as boundary conditions input into ANSYS thermal calculations. These were used for studying the quality of target protection depending on various shapes of shields, target-shield distance, and protective properties of the shield moving relative to the target. The results show that the shield can reduce the convective heat flux by a factor of 2 to 5 depending on pressure, temperature, and velocity. The protective effect of a shield moving relative to the target is greater than the protective properties of a fixed shield. However, the protective effect of a shield moving under the drag force is not sufficient for bringing the heat load on the target down to the necessary limit. Some other ways of diminishing heat flux using a protective shield are discussed

Multi-Target Tracking via Mixed Integer Optimization

Science.gov (United States)

2016-05-13

an easily interpretable global objective function. Furthermore, we propose a greedy heuristic which quickly finds good solutions. We extend both the... heuristic and the MIO model to scenarios with missed detections and false alarms. Index Terms—optimization; multi-target tracking; data asso- ciation...energy in [14] and then again as a minimization of discrete-continuous energy in [15]. These algorithms aim to more accurately represent the nature of the

Optimized swimmer tracking system based on a novel multi-related-targets approach

Science.gov (United States)

Benarab, D.; Napoléon, T.; Alfalou, A.; Verney, A.; Hellard, P.

2017-02-01

Robust tracking is a crucial step in automatic swimmer evaluation from video sequences. We designed a robust swimmer tracking system using a new multi-related-targets approach. The main idea is to consider the swimmer as a bloc of connected subtargets that advance at the same speed. If one of the subtargets is partially or totally occluded, it can be localized by knowing the position of the others. In this paper, we first introduce the two-dimensional direct linear transformation technique that we used to calibrate the videos. Then, we present the classical tracking approach based on dynamic fusion. Next, we highlight the main contribution of our work, which is the multi-related-targets tracking approach. This approach, the classical head-only approach and the ground truth are then compared, through testing on a database of high-level swimmers in training, national and international competitions (French National Championships, Limoges 2015, and World Championships, Kazan 2015). Tracking percentage and the accuracy of the instantaneous speed are evaluated and the findings show that our new appraoach is significantly more accurate than the classical approach.

Measuring coseismic displacements with point-like targets offset tracking

KAUST Repository

Hu, Xie; Wang, Teng; Liao, Mingsheng

2014-01-01

Offset tracking is an important complement to measure large ground displacements in both azimuth and range dimensions where synthetic aperture radar (SAR) interferometry is unfeasible. Subpixel offsets can be obtained by searching for the cross-correlation peak calculated from the match patches uniformly distributed on two SAR images. However, it has its limitations, including redundant computation and incorrect estimations on decorrelated patches. In this letter, we propose a simple strategy that performs offset tracking on detected point-like targets (PT). We first detect image patches within bright PT by using a sinc-like template from a single SAR image and then perform offset tracking on them to obtain the pixel shifts. Compared with the standard method, the application on the 2010 M 7.2 El Mayor-Cucapah earthquake shows that the proposed PT offset tracking can significantly increase the cross-correlation and thus result in both efficiency and reliability improvements. © 2013 IEEE.

Real-time WAMI streaming target tracking in fog

Science.gov (United States)

Chen, Yu; Blasch, Erik; Chen, Ning; Deng, Anna; Ling, Haibin; Chen, Genshe

2016-05-01

Real-time information fusion based on WAMI (Wide-Area Motion Imagery), FMV (Full Motion Video), and Text data is highly desired for many mission critical emergency or security applications. Cloud Computing has been considered promising to achieve big data integration from multi-modal sources. In many mission critical tasks, however, powerful Cloud technology cannot satisfy the tight latency tolerance as the servers are allocated far from the sensing platform, actually there is no guaranteed connection in the emergency situations. Therefore, data processing, information fusion, and decision making are required to be executed on-site (i.e., near the data collection). Fog Computing, a recently proposed extension and complement for Cloud Computing, enables computing on-site without outsourcing jobs to a remote Cloud. In this work, we have investigated the feasibility of processing streaming WAMI in the Fog for real-time, online, uninterrupted target tracking. Using a single target tracking algorithm, we studied the performance of a Fog Computing prototype. The experimental results are very encouraging that validated the effectiveness of our Fog approach to achieve real-time frame rates.

3D Visual Tracking of an Articulated Robot in Precision Automated Tasks

Directory of Open Access Journals (Sweden)

Hamza Alzarok

2017-01-01

Full Text Available The most compelling requirements for visual tracking systems are a high detection accuracy and an adequate processing speed. However, the combination between the two requirements in real world applications is very challenging due to the fact that more accurate tracking tasks often require longer processing times, while quicker responses for the tracking system are more prone to errors, therefore a trade-off between accuracy and speed, and vice versa is required. This paper aims to achieve the two requirements together by implementing an accurate and time efficient tracking system. In this paper, an eye-to-hand visual system that has the ability to automatically track a moving target is introduced. An enhanced Circular Hough Transform (CHT is employed for estimating the trajectory of a spherical target in three dimensions, the colour feature of the target was carefully selected by using a new colour selection process, the process relies on the use of a colour segmentation method (Delta E with the CHT algorithm for finding the proper colour of the tracked target, the target was attached to the six degree of freedom (DOF robot end-effector that performs a pick-and-place task. A cooperation of two Eye-to Hand cameras with their image Averaging filters are used for obtaining clear and steady images. This paper also examines a new technique for generating and controlling the observation search window in order to increase the computational speed of the tracking system, the techniques is named Controllable Region of interest based on Circular Hough Transform (CRCHT. Moreover, a new mathematical formula is introduced for updating the depth information of the vision system during the object tracking process. For more reliable and accurate tracking, a simplex optimization technique was employed for the calculation of the parameters for camera to robotic transformation matrix. The results obtained show the applicability of the proposed approach to track the

Wideband Radar Echo Frequency-domain Simulation and Analysis for High Speed Moving Targets

Directory of Open Access Journals (Sweden)

Ning Chao

2014-04-01

Full Text Available A frequency-domain method is proposed for wideband radar echo simulation of high-speed moving targets. Based on the physical process of electromagnetic waves observing a moving target, a frequency-domain echo model of wideband radar is constructed, and the block diagram of the radar echo simulation in frequency-domain is presented. Then, the impacts of radial velocity and slant range on the matching filtering of LFM radar are analyzed, and some quantitative conclusions on the shift and expansion of the radar profiles are obtained. Simulation results illustrate the correctness and efficiency of the proposed method.

Target tracking control and semi-physical simulation of Qball-X4 quad-rotor unmanned aerial vehicle

Directory of Open Access Journals (Sweden)

Lu Liu

2017-01-01

Full Text Available In this article, a set of integrated ground target tracking flight system has been proposed based on the Qball-X4 quad-rotor unmanned aerial vehicle hardware platform and the QuaRC software platform. Both of the hardware and software platforms are developed by Quanser Company, Canada. The proposed tracking and positioning algorithm could be divided into several stages. First, a tracker is developed based on an optical flow method to track the target; and then, in order to improve the reliability of tracking algorithm and also help in retrieving the lost target, a cascade target detector is developed; meanwhile, a model updated scheme aiming at some possible errors in tracking and detecting process is presented based on Positive-Negative (P-N learning system; at last, a monocular visual positioning system is designed based on the corresponding navigation message. In addition, the effectiveness of the proposed flight control system is verified by both simulation and hardware-in-loop system results in several tracking flight tests.

Joint passive radar tracking and target classification using radar cross section

Science.gov (United States)

Herman, Shawn M.

2004-01-01

We present a recursive Bayesian solution for the problem of joint tracking and classification of airborne targets. In our system, we allow for complications due to multiple targets, false alarms, and missed detections. More importantly, though, we utilize the full benefit of a joint approach by implementing our tracker using an aerodynamically valid flight model that requires aircraft-specific coefficients such as wing area and vehicle mass, which are provided by our classifier. A key feature that bridges the gap between tracking and classification is radar cross section (RCS). By modeling the true deterministic relationship that exists between RCS and target aspect, we are able to gain both valuable class information and an estimate of target orientation. However, the lack of a closed-form relationship between RCS and target aspect prevents us from using the Kalman filter or its variants. Instead, we rely upon a sequential Monte Carlo-based approach known as particle filtering. In addition to allowing us to include RCS as a measurement, the particle filter also simplifies the implementation of our nonlinear non-Gaussian flight model.

Automated target recognition and tracking using an optical pattern recognition neural network

Science.gov (United States)

Chao, Tien-Hsin

1991-01-01

The on-going development of an automatic target recognition and tracking system at the Jet Propulsion Laboratory is presented. This system is an optical pattern recognition neural network (OPRNN) that is an integration of an innovative optical parallel processor and a feature extraction based neural net training algorithm. The parallel optical processor provides high speed and vast parallelism as well as full shift invariance. The neural network algorithm enables simultaneous discrimination of multiple noisy targets in spite of their scales, rotations, perspectives, and various deformations. This fully developed OPRNN system can be effectively utilized for the automated spacecraft recognition and tracking that will lead to success in the Automated Rendezvous and Capture (AR&C) of the unmanned Cargo Transfer Vehicle (CTV). One of the most powerful optical parallel processors for automatic target recognition is the multichannel correlator. With the inherent advantages of parallel processing capability and shift invariance, multiple objects can be simultaneously recognized and tracked using this multichannel correlator. This target tracking capability can be greatly enhanced by utilizing a powerful feature extraction based neural network training algorithm such as the neocognitron. The OPRNN, currently under investigation at JPL, is constructed with an optical multichannel correlator where holographic filters have been prepared using the neocognitron training algorithm. The computation speed of the neocognitron-type OPRNN is up to 10(exp 14) analog connections/sec that enabling the OPRNN to outperform its state-of-the-art electronics counterpart by at least two orders of magnitude.

ESAM: Endocrine inspired Sensor Activation Mechanism for multi-target tracking in WSNs

Science.gov (United States)

Adil Mahdi, Omar; Wahab, Ainuddin Wahid Abdul; Idris, Mohd Yamani Idna; Znaid, Ammar Abu; Khan, Suleman; Al-Mayouf, Yusor Rafid Bahar

2016-10-01

Target tracking is a significant application of wireless sensor networks (WSNs) in which deployment of self-organizing and energy efficient algorithms is required. The tracking accuracy increases as more sensor nodes are activated around the target but more energy is consumed. Thus, in this study, we focus on limiting the number of sensors by forming an ad-hoc network that operates autonomously. This will reduce the energy consumption and prolong the sensor network lifetime. In this paper, we propose a fully distributed algorithm, an Endocrine inspired Sensor Activation Mechanism for multi target-tracking (ESAM) which reflecting the properties of real life sensor activation system based on the information circulating principle in the endocrine system of the human body. Sensor nodes in our network are secreting different hormones according to certain rules. The hormone level enables the nodes to regulate an efficient sleep and wake up cycle of nodes to reduce the energy consumption. It is evident from the simulation results that the proposed ESAM in autonomous sensor network exhibits a stable performance without the need of commands from a central controller. Moreover, the proposed ESAM generates more efficient and persistent results as compared to other algorithms for tracking an invading object.

Accurate location estimation of moving object In Wireless Sensor network

Directory of Open Access Journals (Sweden)

Vinay Bhaskar Semwal

2011-12-01

Full Text Available One of the central issues in wirless sensor networks is track the location, of moving object which have overhead of saving data, an accurate estimation of the target location of object with energy constraint .We do not have any mechanism which control and maintain data .The wireless communication bandwidth is also very limited. Some field which is using this technique are flood and typhoon detection, forest fire detection, temperature and humidity and ones we have these information use these information back to a central air conditioning and ventilation.In this research paper, we propose protocol based on the prediction and adaptive based algorithm which is using less sensor node reduced by an accurate estimation of the target location. We had shown that our tracking method performs well in terms of energy saving regardless of mobility pattern of the mobile target. We extends the life time of network with less sensor node. Once a new object is detected, a mobile agent will be initiated to track the roaming path of the object.

Study on moving target detection to passive radar based on FM broadcast transmitter

Institute of Scientific and Technical Information of China (English)

无

2007-01-01

Target detection by a noncooperative illuminator is a topic of general interest in the electronic warfare field.First of all,direct-path interference(DPI)suppression which is the technique of bottleneck of moving target detection by a noncooperative frequency modulation(FM) broadcast transmitter is analyzed in this article;Secondly,a space-time-frequency domain synthetic solution to this problem is introduced:Adaptive nulling array processing is considered in the space domain,DPI cancellation based on adaptive fractional delay interpolation(AFDI)technique is used in planned time domain,and long-time coherent integration is utilized in the frequency domain;Finally,an experimental system is planned by considering FM broadcast transmitter as a noncooperative illuminator,Simulation results by real collected data show that the proposed method has a better performance of moving target detection.

Visual attention is required for multiple object tracking.

Science.gov (United States)

Tran, Annie; Hoffman, James E

2016-12-01

In the multiple object tracking task, participants attempt to keep track of a moving set of target objects embedded in an identical set of moving distractors. Depending on several display parameters, observers are usually only able to accurately track 3 to 4 objects. Various proposals attribute this limit to a fixed number of discrete indexes (Pylyshyn, 1989), limits in visual attention (Cavanagh & Alvarez, 2005), or "architectural limits" in visual cortical areas (Franconeri, 2013). The present set of experiments examined the specific role of visual attention in tracking using a dual-task methodology in which participants tracked objects while identifying letter probes appearing on the tracked objects and distractors. As predicted by the visual attention model, probe identification was faster and/or more accurate when probes appeared on tracked objects. This was the case even when probes were more than twice as likely to appear on distractors suggesting that some minimum amount of attention is required to maintain accurate tracking performance. When the need to protect tracking accuracy was relaxed, participants were able to allocate more attention to distractors when probes were likely to appear there but only at the expense of large reductions in tracking accuracy. A final experiment showed that people attend to tracked objects even when letters appearing on them are task-irrelevant, suggesting that allocation of attention to tracked objects is an obligatory process. These results support the claim that visual attention is required for tracking objects. (PsycINFO Database Record (c) 2016 APA, all rights reserved).

Homography-based multiple-camera person-tracking

Science.gov (United States)

Turk, Matthew R.

2009-01-01

Multiple video cameras are cheaply installed overlooking an area of interest. While computerized single-camera tracking is well-developed, multiple-camera tracking is a relatively new problem. The main multi-camera problem is to give the same tracking label to all projections of a real-world target. This is called the consistent labelling problem. Khan and Shah (2003) introduced a method to use field of view lines to perform multiple-camera tracking. The method creates inter-camera meta-target associations when objects enter at the scene edges. They also said that a plane-induced homography could be used for tracking, but this method was not well described. Their homography-based system would not work if targets use only one side of a camera to enter the scene. This paper overcomes this limitation and fully describes a practical homography-based tracker. A new method to find the feet feature is introduced. The method works especially well if the camera is tilted, when using the bottom centre of the target's bounding-box would produce inaccurate results. The new method is more accurate than the bounding-box method even when the camera is not tilted. Next, a method is presented that uses a series of corresponding point pairs "dropped" by oblivious, live human targets to find a plane-induced homography. The point pairs are created by tracking the feet locations of moving targets that were associated using the field of view line method. Finally, a homography-based multiple-camera tracking algorithm is introduced. Rules governing when to create the homography are specified. The algorithm ensures that homography-based tracking only starts after a non-degenerate homography is found. The method works when not all four field of view lines are discoverable; only one line needs to be found to use the algorithm. To initialize the system, the operator must specify pairs of overlapping cameras. Aside from that, the algorithm is fully automatic and uses the natural movement of

Applying the decision moving window to risky choice: Comparison of eye-tracking and mousetracing methods

Directory of Open Access Journals (Sweden)

Ana M. Franco-Watkins

2011-12-01

Full Text Available Currently, a disparity exists between the process-level models decision researchers use to describe and predict decision behavior and the methods implemented and metrics collected to test these models. The current work seeks to remedy this disparity by combining the advantages of work in decision research (mouse-tracing paradigms with contingent information display and cognitive psychology (eye-tracking paradigms from reading and scene perception. In particular, we introduce a new decision moving-window paradigm that presents stimulus information contingent on eye fixations. We provide data from the first application of this method to risky decision making, and show how it compares to basic eye-tracking and mouse-tracing methods. We also enumerate the practical, theoretical, and analytic advantages this method offers above and beyond both mouse-tracing with occlusion and basic eye tracking of information without occlusion. We include the use of new metrics that offer more precision than those typically calculated on mouse-tracing data as well as those not possible or feasible within the mouse-tracing paradigm.

What triggers catch-up saccades during visual tracking?

Science.gov (United States)

de Brouwer, Sophie; Yuksel, Demet; Blohm, Gunnar; Missal, Marcus; Lefèvre, Philippe

2002-03-01

When tracking moving visual stimuli, primates orient their visual axis by combining two kinds of eye movements, smooth pursuit and saccades, that have very different dynamics. Yet, the mechanisms that govern the decision to switch from one type of eye movement to the other are still poorly understood, even though they could bring a significant contribution to the understanding of how the CNS combines different kinds of control strategies to achieve a common motor and sensory goal. In this study, we investigated the oculomotor responses to a large range of different combinations of position error and velocity error during visual tracking of moving stimuli in humans. We found that the oculomotor system uses a prediction of the time at which the eye trajectory will cross the target, defined as the "eye crossing time" (T(XE)). The eye crossing time, which depends on both position error and velocity error, is the criterion used to switch between smooth and saccadic pursuit, i.e., to trigger catch-up saccades. On average, for T(XE) between 40 and 180 ms, no saccade is triggered and target tracking remains purely smooth. Conversely, when T(XE) becomes smaller than 40 ms or larger than 180 ms, a saccade is triggered after a short latency (around 125 ms).

Event-triggered Kalman-consensus filter for two-target tracking sensor networks.

Science.gov (United States)

Su, Housheng; Li, Zhenghao; Ye, Yanyan

2017-11-01

This paper is concerned with the problem of event-triggered Kalman-consensus filter for two-target tracking sensor networks. According to the event-triggered protocol and the mean-square analysis, a suboptimal Kalman gain matrix is derived and a suboptimal event-triggered distributed filter is obtained. Based on the Kalman-consensus filter protocol, all sensors which only depend on its neighbors' information can track their corresponding targets. Furthermore, utilizing Lyapunov method and matrix theory, some sufficient conditions are presented for ensuring the stability of the system. Finally, a simulation example is presented to verify the effectiveness of the proposed event-triggered protocol. Copyright © 2017 ISA. Published by Elsevier Ltd. All rights reserved.

Intrafractional tracking accuracy in infrared marker-based hybrid dynamic tumour-tracking irradiation with a gimballed linac

International Nuclear Information System (INIS)

Mukumoto, Nobutaka; Nakamura, Mitsuhiro; Yamada, Masahiro; Takahashi, Kunio; Tanabe, Hiroaki; Yano, Shinsuke; Miyabe, Yuki; Ueki, Nami; Kaneko, Shuji; Matsuo, Yukinori; Mizowaki, Takashi; Sawada, Akira; Kokubo, Masaki; Hiraoka, Masahiro

2014-01-01

Purpose: To verify the intrafractional tracking accuracy in infrared (IR) marker-based hybrid dynamic tumour tracking irradiation (“IR Tracking”) with the Vero4DRT. Materials and methods: The gimballed X-ray head tracks a moving target by predicting its future position from displacements of IR markers in real-time. Ten lung cancer patients who underwent IR Tracking were enrolled. The 95th percentiles of intrafractional mechanical (iE M 95 ), prediction (iE P 95 ), and overall targeting errors (iE T 95 ) were calculated from orthogonal fluoroscopy images acquired during tracking irradiation and from the synchronously acquired log files. Results: Averaged intrafractional errors were (left–right, cranio-caudal [CC], anterior–posterior [AP]) = (0.1 mm, 0.4 mm, 0.1 mm) for iE M 95 , (1.2 mm, 2.7 mm, 2.1 mm) for iE P 95 , and (1.3 mm, 2.4 mm, 1.4 mm) for iE T 95 . By correcting systematic prediction errors in the previous field, the iE P 95 was reduced significantly, by an average of 0.4 mm in the CC (p < 0.05) and by 0.3 mm in the AP (p < 0.01) directions. Conclusions: Prediction errors were the primary cause of overall targeting errors, whereas mechanical errors were negligible. Furthermore, improvement of the prediction accuracy could be achieved by correcting systematic prediction errors in the previous field

First Demonstration of Combined kV/MV Image-Guided Real-Time Dynamic Multileaf-Collimator Target Tracking

International Nuclear Information System (INIS)

Cho, Byungchul; Poulsen, Per R.; Sloutsky, Alex; Sawant, Amit; Keall, Paul J.

2009-01-01

Purpose: For intrafraction motion management, a real-time tracking system was developed by combining fiducial marker-based tracking via simultaneous kilovoltage (kV) and megavoltage (MV) imaging and a dynamic multileaf collimator (DMLC) beam-tracking system. Methods and Materials: The integrated tracking system employed a Varian Trilogy system equipped with kV/MV imaging systems and a Millennium 120-leaf MLC. A gold marker in elliptical motion (2-cm superior-inferior, 1-cm left-right, 10 cycles/min) was simultaneously imaged by the kV and MV imagers at 6.7 Hz and segmented in real time. With these two-dimensional projections, the tracking software triangulated the three-dimensional marker position and repositioned the MLC leaves to follow the motion. Phantom studies were performed to evaluate time delay from image acquisition to MLC adjustment, tracking error, and dosimetric impact of target motion with and without tracking. Results: The time delay of the integrated tracking system was ∼450 ms. The tracking error using a prediction algorithm was 0.9 ± 0.5 mm for the elliptical motion. The dose distribution with tracking showed better target coverage and less dose to surrounding region over no tracking. The failure rate of the gamma test (3%/3-mm criteria) was 22.5% without tracking but was reduced to 0.2% with tracking. Conclusion: For the first time, a complete tracking system combining kV/MV image-guided target tracking and DMLC beam tracking was demonstrated. The average geometric error was less than 1 mm, and the dosimetric error was negligible. This system is a promising method for intrafraction motion management.

Signal and data processing of small targets 1990; Proceedings of the Meeting, Orlando, FL, Apr. 16-18, 1990

Science.gov (United States)

Drummond, Oliver E.

Various papers on signal and data processing of small targets are presented. Individual topics addressed include: clutter rejection using multispectral processing, new sensor for automatic guidance, Doppler domain localized generalized-likelihood-ratio detector, linear filter for resolution of point sources, analysis of order-statistic filters for robust detection, distribution functions for additive Gaussian and gamma noise, temperature discrimination of closely space objects, knowledge-based tracking algorithm, detecting and tracking low-observable targets using IR, weak target detection using the entropy concept, measurement-based neural-net multitarget tracker, object-track closed-form solution in angle space, passive-sensor data association for tracking. Also discussed are: application of MHT to dim moving targets, automatic static covariance analysis with mathematica, neural network implementation of plot/track association, application of Bayesian networks to multitarget tracking, tracking clusters and extended objects with multiple sensors, target tracking by human operator, finite impulse response estimator, multitarget tracking using an extended Kalman filter, maneuvering target tracking using a two-state model algorithm, mixture reduction algorithms for target tracking in clutter, scene interpretation approach to high-level target tracking.

Sensing across large-scale cognitive radio networks: Data processing, algorithms, and testbed for wireless tomography and moving target tracking

Science.gov (United States)

Bonior, Jason David

As the use of wireless devices has become more widespread so has the potential for utilizing wireless networks for remote sensing applications. Regular wireless communication devices are not typically designed for remote sensing. Remote sensing techniques must be carefully tailored to the capabilities of these networks before they can be applied. Experimental verification of these techniques and algorithms requires robust yet flexible testbeds. In this dissertation, two experimental testbeds for the advancement of research into sensing across large-scale cognitive radio networks are presented. System architectures, implementations, capabilities, experimental verification, and performance are discussed. One testbed is designed for the collection of scattering data to be used in RF and wireless tomography research. This system is used to collect full complex scattering data using a vector network analyzer (VNA) and amplitude-only data using non-synchronous software-defined radios (SDRs). Collected data is used to experimentally validate a technique for phase reconstruction using semidefinite relaxation and demonstrate the feasibility of wireless tomography. The second testbed is a SDR network for the collection of experimental data. The development of tools for network maintenance and data collection is presented and discussed. A novel recursive weighted centroid algorithm for device-free target localization using the variance of received signal strength for wireless links is proposed. The signal variance resulting from a moving target is modeled as having contours related to Cassini ovals. This model is used to formulate recursive weights which reduce the influence of wireless links that are farther from the target location estimate. The algorithm and its implementation on this testbed are presented and experimental results discussed.

High-performance object tracking and fixation with an online neural estimator.

Science.gov (United States)

Kumarawadu, Sisil; Watanabe, Keigo; Lee, Tsu-Tian

2007-02-01

Vision-based target tracking and fixation to keep objects that move in three dimensions in view is important for many tasks in several fields including intelligent transportation systems and robotics. Much of the visual control literature has focused on the kinematics of visual control and ignored a number of significant dynamic control issues that limit performance. In line with this, this paper presents a neural network (NN)-based binocular tracking scheme for high-performance target tracking and fixation with minimum sensory information. The procedure allows the designer to take into account the physical (Lagrangian dynamics) properties of the vision system in the control law. The design objective is to synthesize a binocular tracking controller that explicitly takes the systems dynamics into account, yet needs no knowledge of dynamic nonlinearities and joint velocity sensory information. The combined neurocontroller-observer scheme can guarantee the uniform ultimate bounds of the tracking, observer, and NN weight estimation errors under fairly general conditions on the controller-observer gains. The controller is tested and verified via simulation tests in the presence of severe target motion changes.

Detection of moving objects from a moving platform in urban scenes

NARCIS (Netherlands)

Haar, F.B. ter; Hollander, R.J.M. den; Dijk, J.

2010-01-01

Moving object detection in urban scenes is important for the guidance of autonomous vehicles, robot navigation, and monitoring. In this paper moving objects are automatically detected using three sequential frames and tracked over a longer period. To this extend we modify the plane+parallax,

Collaborative 3D Target Tracking in Distributed Smart Camera Networks for Wide-Area Surveillance

Directory of Open Access Journals (Sweden)

Xenofon Koutsoukos

2013-05-01

Full Text Available With the evolution and fusion of wireless sensor network and embedded camera technologies, distributed smart camera networks have emerged as a new class of systems for wide-area surveillance applications. Wireless networks, however, introduce a number of constraints to the system that need to be considered, notably the communication bandwidth constraints. Existing approaches for target tracking using a camera network typically utilize target handover mechanisms between cameras, or combine results from 2D trackers in each camera into 3D target estimation. Such approaches suffer from scale selection, target rotation, and occlusion, drawbacks typically associated with 2D tracking. In this paper, we present an approach for tracking multiple targets directly in 3D space using a network of smart cameras. The approach employs multi-view histograms to characterize targets in 3D space using color and texture as the visual features. The visual features from each camera along with the target models are used in a probabilistic tracker to estimate the target state. We introduce four variations of our base tracker that incur different computational and communication costs on each node and result in different tracking accuracy. We demonstrate the effectiveness of our proposed trackers by comparing their performance to a 3D tracker that fuses the results of independent 2D trackers. We also present performance analysis of the base tracker along Quality-of-Service (QoS and Quality-of-Information (QoI metrics, and study QoS vs. QoI trade-offs between the proposed tracker variations. Finally, we demonstrate our tracker in a real-life scenario using a camera network deployed in a building.

Signal and data processing of small targets 1989; Proceedings of the Meeting, Orlando, FL, Mar. 27-29, 1989

Science.gov (United States)

Drummond, Oliver E. (Editor)

1989-01-01

The present conference on digital signal processing, association and filtering techniques, and multiple-sensor/multiple-tracking techniques, discusses single-frame velocity estimation, efficient target extraction for laser radar imagery, precision target tracking for small extended objects, IR clutter partitioning for matched filter design, the maximum-likelihood approach to gamma circumvention, position estimation for optical point targets using staring detector arrays, and a multiple-scan signal processing technique for area-moving target indication. Also discussed are a proportional integral estimator, the prediction of track purity in tracking performance evaluations, synchronization and fault-tolerance in a distributed tracker, the benefits of soft sensors and probabilistic fusion, and testing track initiation algorithms fusing two-dimensional tracks.

Fish tracking by combining motion based segmentation and particle filtering

Science.gov (United States)

Bichot, E.; Mascarilla, L.; Courtellemont, P.

2006-01-01

In this paper, we suggest a new importance sampling scheme to improve a particle filtering based tracking process. This scheme relies on exploitation of motion segmentation. More precisely, we propagate hypotheses from particle filtering to blobs of similar motion to target. Hence, search is driven toward regions of interest in the state space and prediction is more accurate. We also propose to exploit segmentation to update target model. Once the moving target has been identified, a representative model is learnt from its spatial support. We refer to this model in the correction step of the tracking process. The importance sampling scheme and the strategy to update target model improve the performance of particle filtering in complex situations of occlusions compared to a simple Bootstrap approach as shown by our experiments on real fish tank sequences.

Signal Detection, Target Tracking and Differential Geometry Applications to Statistical Inference

National Research Council Canada - National Science Library

Rao, C

1997-01-01

Signal detection and target tracking. A novel method known as polynomial rooting approach is proposed to obtain estimates of frequencies, amplitudes and noise variance of two-dimensional exponential signals...

Multiple operating system rotation environment moving target defense

Science.gov (United States)

Evans, Nathaniel; Thompson, Michael

2016-03-22

Systems and methods for providing a multiple operating system rotation environment ("MORE") moving target defense ("MTD") computing system are described. The MORE-MTD system provides enhanced computer system security through a rotation of multiple operating systems. The MORE-MTD system increases attacker uncertainty, increases the cost of attacking the system, reduces the likelihood of an attacker locating a vulnerability, and reduces the exposure time of any located vulnerability. The MORE-MTD environment is effectuated by rotation of the operating systems at a given interval. The rotating operating systems create a consistently changing attack surface for remote attackers.

Hierarchically Coordinated Power Management for Target Tracking in Wireless Sensor Networks

Directory of Open Access Journals (Sweden)

Feng Juan

2013-10-01

Full Text Available Energy efficiency is very important for wireless sensor networks (WSNs since sensor nodes have a limited energy supply from a battery. So far, a lot research has focused on this issue, while less emphasis has been placed on the adaptive sleep time for each node with a consideration for the application constraints. In this paper, we propose a hierarchically coordinated power management (HCPM approach, which both addresses the energy conservation problem and reduces the packet forwarding delay for target tracking WSNs based on a virtual-grid-based network structure. We extend the network lifetime by adopting an adaptive sleep scheduling scheme that combines the local power management (PM and the adaptive coordinate PM strategies to schedule the activities of the sensor nodes at the surveillance stage. Furthermore, we propose a hierarchical structure for the tracking stage. Experimental results show that the proposed approach has a greater capability of extending the network lifetime while maintaining a short transmission delay when compared with the protocol which does not consider the application constraints in target tracking sensor networks.

A Bayesian analysis of the mixed labelling phenomenon in two-target tracking

NARCIS (Netherlands)

Aoki, E.H.; Boers, Y.; Svensson, L.; Mandal, Pranab K.; Bagchi, Arunabha

In mulit-target tracking and labelling (MTTL), mixed labelling corresponds to a situation where there is ambiguity in labelling, i.e. in the assignment of labels to locations (where a "location" here means simply an unlabelled single-target state. The phenomenon is well-known in literature, and

Fuzzy logic control for camera tracking system

Science.gov (United States)

Lea, Robert N.; Fritz, R. H.; Giarratano, J.; Jani, Yashvant

1992-01-01

A concept utilizing fuzzy theory has been developed for a camera tracking system to provide support for proximity operations and traffic management around the Space Station Freedom. Fuzzy sets and fuzzy logic based reasoning are used in a control system which utilizes images from a camera and generates required pan and tilt commands to track and maintain a moving target in the camera's field of view. This control system can be implemented on a fuzzy chip to provide an intelligent sensor for autonomous operations. Capabilities of the control system can be expanded to include approach, handover to other sensors, caution and warning messages.

Interaction of 80 MeV PI+ with different targets: Track detector studies

Energy Technology Data Exchange (ETDEWEB)

Tabassum, L; Chohan, A S [Government Coll., Lahore. (Pakistan) Deptt. of Physics Khan, H.A. (Pakistan Inst. of Nuclear Science and Technology, Islamabad (Pakistan). Nuclear Engineering Div.)

1990-04-01

CR-39 and mica track detectors have been used in the study of the interactions of 80 MeV PI+ with thin targets of Bi, Pb, Ho, Sb. The binary fission cross sections, the length and angular distributions of etched tracks have been obtained. The cross-section values obtained by using CR-39 are higher as compared to those obtained with mica. (author).

Interaction of 80 MeV PI+ with different targets: Track detector studies

International Nuclear Information System (INIS)

Tabassum, L.; Chohan, A.S.

1990-01-01

CR-39 and mica track detectors have been used in the study of the interactions of 80 MeV PI+ with thin targets of Bi, Pb, Ho, Sb. The binary fission cross sections, the length and angular distributions of etched tracks have been obtained. The cross-section values obtained by using CR-39 are higher as compared to those obtained with mica. (author)

Tracking Positioning Algorithm for Direction of Arrival Based on Direction Lock Loop

Directory of Open Access Journals (Sweden)

Xiu-Zhi Cheng

2015-06-01

Full Text Available In order to solve the problem of poor real-time performance, low accuracy and high computational complexity in the traditional process of locating and tracking of Direction of Arrival (DOA of moving targets, this paper proposes a DOA algorithm based on the Direction Lock Loop (DILL which adopts Lock Loop structure to realize the estimation and location of DOA and can adjust the direction automatically along with the changes of a signal’s angular variation to track the position of the signal. Meanwhile, to reduce the influence of nonlinearity and noise on its performance, the UKF filter is designed for eliminating interference of the estimated target signal to improve accuracy of the signal tracking and stability of the system. Simulation results prove that the algorithm can not only get a high resolution DOA estimate signal, but can also locate and track multiple mobile targets effectively with enhanced accuracy, efficiency and stability.

Familiar trajectories facilitate the interpretation of physical forces when intercepting a moving target.

Science.gov (United States)

Mijatović, Antonija; La Scaleia, Barbara; Mercuri, Nicola; Lacquaniti, Francesco; Zago, Myrka

2014-12-01

Familiarity with the visual environment affects our expectations about the objects in a scene, aiding in recognition and interaction. Here we tested whether the familiarity with the specific trajectory followed by a moving target facilitates the interpretation of the effects of underlying physical forces. Participants intercepted a target sliding down either an inclined plane or a tautochrone. Gravity accelerated the target by the same amount in both cases, but the inclined plane represented a familiar trajectory whereas the tautochrone was unfamiliar to the participants. In separate sessions, the gravity field was consistent with either natural gravity or artificial reversed gravity. Target motion was occluded from view over the last segment. We found that the responses in the session with unnatural forces were systematically delayed relative to those with natural forces, but only for the inclined plane. The time shift is consistent with a bias for natural gravity, in so far as it reflects an a priori expectation that a target not affected by natural forces will arrive later than one accelerated downwards by gravity. Instead, we did not find any significant time shift with unnatural forces in the case of the tautochrone. We argue that interception of a moving target relies on the integration of the high-level cue of trajectory familiarity with low-level cues related to target kinematics.

Persistent Aerial Tracking

KAUST Repository

Mueller, Matthias

2016-04-13

In this thesis, we propose a new aerial video dataset and benchmark for low altitude UAV target tracking, as well as, a photo-realistic UAV simulator that can be coupled with tracking methods. Our benchmark provides the rst evaluation of many state of-the-art and popular trackers on 123 new and fully annotated HD video sequences captured from a low-altitude aerial perspective. Among the compared trackers, we determine which ones are the most suitable for UAV tracking both in terms of tracking accuracy and run-time. We also present a simulator that can be used to evaluate tracking algorithms in real-time scenarios before they are deployed on a UAV "in the field", as well as, generate synthetic but photo-realistic tracking datasets with free ground truth annotations to easily extend existing real-world datasets. Both the benchmark and simulator will be made publicly available to the vision community to further research in the area of object tracking from UAVs. Additionally, we propose a persistent, robust and autonomous object tracking system for unmanned aerial vehicles (UAVs) called Persistent Aerial Tracking (PAT). A computer vision and control strategy is applied to a diverse set of moving objects (e.g. humans, animals, cars, boats, etc.) integrating multiple UAVs with a stabilized RGB camera. A novel strategy is employed to successfully track objects over a long period, by \\'handing over the camera\\' from one UAV to another. We integrate the complete system into an off-the-shelf UAV, and obtain promising results showing the robustness of our solution in real-world aerial scenarios.

Robotics Vision-based Heuristic Reasoning for Underwater Target Tracking and Navigation

Directory of Open Access Journals (Sweden)

Chua Kia

2005-09-01

Full Text Available This paper presents a robotics vision-based heuristic reasoning system for underwater target tracking and navigation. This system is introduced to improve the level of automation of underwater Remote Operated Vehicles (ROVs operations. A prototype which combines computer vision with an underwater robotics system is successfully designed and developed to perform target tracking and intelligent navigation. This study focuses on developing image processing algorithms and fuzzy inference system for the analysis of the terrain. The vision system developed is capable of interpreting underwater scene by extracting subjective uncertainties of the object of interest. Subjective uncertainties are further processed as multiple inputs of a fuzzy inference system that is capable of making crisp decisions concerning where to navigate. The important part of the image analysis is morphological filtering. The applications focus on binary images with the extension of gray-level concepts. An open-loop fuzzy control system is developed for classifying the traverse of terrain. The great achievement is the system's capability to recognize and perform target tracking of the object of interest (pipeline in perspective view based on perceived condition. The effectiveness of this approach is demonstrated by computer and prototype simulations. This work is originated from the desire to develop robotics vision system with the ability to mimic the human expert's judgement and reasoning when maneuvering ROV in the traverse of the underwater terrain.

Robotics Vision-based Heuristic Reasoning for Underwater Target Tracking and Navigation

Directory of Open Access Journals (Sweden)

Chua Kia

2008-11-01

Full Text Available This paper presents a robotics vision-based heuristic reasoning system for underwater target tracking and navigation. This system is introduced to improve the level of automation of underwater Remote Operated Vehicles (ROVs operations. A prototype which combines computer vision with an underwater robotics system is successfully designed and developed to perform target tracking and intelligent navigation. This study focuses on developing image processing algorithms and fuzzy inference system for the analysis of the terrain. The vision system developed is capable of interpreting underwater scene by extracting subjective uncertainties of the object of interest. Subjective uncertainties are further processed as multiple inputs of a fuzzy inference system that is capable of making crisp decisions concerning where to navigate. The important part of the image analysis is morphological filtering. The applications focus on binary images with the extension of gray-level concepts. An open-loop fuzzy control system is developed for classifying the traverse of terrain. The great achievement is the system's capability to recognize and perform target tracking of the object of interest (pipeline in perspective view based on perceived condition. The effectiveness of this approach is demonstrated by computer and prototype simulations. This work is originated from the desire to develop robotics vision system with the ability to mimic the human expert's judgement and reasoning when maneuvering ROV in the traverse of the underwater terrain.

Persistent Aerial Tracking system for UAVs

KAUST Repository

Mueller, Matthias; Sharma, Gopal; Smith, Neil; Ghanem, Bernard

2016-01-01

In this paper, we propose a persistent, robust and autonomous object tracking system for unmanned aerial vehicles (UAVs) called Persistent Aerial Tracking (PAT). A computer vision and control strategy is applied to a diverse set of moving objects (e.g. humans, animals, cars, boats, etc.) integrating multiple UAVs with a stabilized RGB camera. A novel strategy is employed to successfully track objects over a long period, by ‘handing over the camera’ from one UAV to another. We evaluate several state-of-the-art trackers on the VIVID aerial video dataset and additional sequences that are specifically tailored to low altitude UAV target tracking. Based on the evaluation, we select the leading tracker and improve upon it by optimizing for both speed and performance, integrate the complete system into an off-the-shelf UAV, and obtain promising results showing the robustness of our solution in real-world aerial scenarios.

Persistent Aerial Tracking system for UAVs

KAUST Repository

Mueller, Matthias

2016-12-19

In this paper, we propose a persistent, robust and autonomous object tracking system for unmanned aerial vehicles (UAVs) called Persistent Aerial Tracking (PAT). A computer vision and control strategy is applied to a diverse set of moving objects (e.g. humans, animals, cars, boats, etc.) integrating multiple UAVs with a stabilized RGB camera. A novel strategy is employed to successfully track objects over a long period, by ‘handing over the camera’ from one UAV to another. We evaluate several state-of-the-art trackers on the VIVID aerial video dataset and additional sequences that are specifically tailored to low altitude UAV target tracking. Based on the evaluation, we select the leading tracker and improve upon it by optimizing for both speed and performance, integrate the complete system into an off-the-shelf UAV, and obtain promising results showing the robustness of our solution in real-world aerial scenarios.

Research on Key Technologies of Network Centric System Distributed Target Track Fusion

Directory of Open Access Journals (Sweden)

Yi Mao

2017-01-01

Full Text Available To realize common tactical picture in network-centered system, this paper proposes a layered architecture for distributed information processing and a method for distributed track fusion on the basis of analyzing the characteristics of network-centered systems. Basing on the noncorrelation of three-dimensional measurement of surveillance and reconnaissance sensors under polar coordinates, it also puts forward an algorithm for evaluating track quality (TQ using statistical decision theory. According to simulation results, the TQ value is associated with the measurement accuracy of sensors and the motion state of targets, which is well matched with the convergence process of tracking filters. Besides, the proposed algorithm has good reliability and timeliness in track quality evaluation.

An Energy-Efficient Target Tracking Framework in Wireless Sensor Networks

Directory of Open Access Journals (Sweden)

Zhijun Yu

2009-01-01

Full Text Available This study devises and evaluates an energy-efficient distributed collaborative signal and information processing framework for acoustic target tracking in wireless sensor networks. The distributed processing algorithm is based on mobile agent computing paradigm and sequential Bayesian estimation. At each time step, the short detection reports of cluster members will be collected by cluster head, and a sensor node with the highest signal-to-noise ratio (SNR is chosen there as reference node for time difference of arrive (TDOA calculation. During the mobile agent migration, the target state belief is transmitted among nodes and updated using the TDOA measurement of these fusion nodes one by one. The computing and processing burden is evenly distributed in the sensor network. To decrease the wireless communications, we propose to represent the belief by parameterized methods such as Gaussian approximation or Gaussian mixture model approximation. Furthermore, we present an attraction force function to handle the mobile agent migration planning problem, which is a combination of the node residual energy, useful information, and communication cost. Simulation examples demonstrate the estimation effectiveness and energy efficiency of the proposed distributed collaborative target tracking framework.

A new method of small target detection based on neural network

Science.gov (United States)

Hu, Jing; Hu, Yongli; Lu, Xinxin

2018-02-01

The detection and tracking of moving dim target in infrared image have been an research hotspot for many years. The target in each frame of images only occupies several pixels without any shape and structure information. Moreover, infrared small target is often submerged in complicated background with low signal-to-clutter ratio, making the detection very difficult. Different backgrounds exhibit different statistical properties, making it becomes extremely complex to detect the target. If the threshold segmentation is not reasonable, there may be more noise points in the final detection, which is unfavorable for the detection of the trajectory of the target. Single-frame target detection may not be able to obtain the desired target and cause high false alarm rate. We believe the combination of suspicious target detection spatially in each frame and temporal association for target tracking will increase reliability of tracking dim target. The detection of dim target is mainly divided into two parts, In the first part, we adopt bilateral filtering method in background suppression, after the threshold segmentation, the suspicious target in each frame are extracted, then we use LSTM(long short term memory) neural network to predict coordinates of target of the next frame. It is a brand-new method base on the movement characteristic of the target in sequence images which could respond to the changes in the relationship between past and future values of the values. Simulation results demonstrate proposed algorithm can effectively predict the trajectory of the moving small target and work efficiently and robustly with low false alarm.

Online Risk Prediction for Indoor Moving Objects

DEFF Research Database (Denmark)

Ahmed, Tanvir; Pedersen, Torben Bach; Calders, Toon

2016-01-01

Technologies such as RFID and Bluetooth have received considerable attention for tracking indoor moving objects. In a time-critical indoor tracking scenario such as airport baggage handling, a bag has to move through a sequence of locations until it is loaded into the aircraft. Inefficiency or in...... reduce the operation cost....

Comparison of Predictable Smooth Ocular and Combined Eye-Head Tracking Behaviour in Patients with Lesions Affecting the Brainstem and Cerebellum

Science.gov (United States)

Grant, Michael P.; Leigh, R. John; Seidman, Scott H.; Riley, David E.; Hanna, Joseph P.

1992-01-01

We compared the ability of eight normal subjects and 15 patients with brainstem or cerebellar disease to follow a moving visual stimulus smoothly with either the eyes alone or with combined eye-head tracking. The visual stimulus was either a laser spot (horizontal and vertical planes) or a large rotating disc (torsional plane), which moved at one sinusoidal frequency for each subject. The visually enhanced Vestibulo-Ocular Reflex (VOR) was also measured in each plane. In the horizontal and vertical planes, we found that if tracking gain (gaze velocity/target velocity) for smooth pursuit was close to 1, the gain of combined eye-hand tracking was similar. If the tracking gain during smooth pursuit was less than about 0.7, combined eye-head tracking was usually superior. Most patients, irrespective of diagnosis, showed combined eye-head tracking that was superior to smooth pursuit; only two patients showed the converse. In the torsional plane, in which optokinetic responses were weak, combined eye-head tracking was much superior, and this was the case in both subjects and patients. We found that a linear model, in which an internal ocular tracking signal cancelled the VOR, could account for our findings in most normal subjects in the horizontal and vertical planes, but not in the torsional plane. The model failed to account for tracking behaviour in most patients in any plane, and suggested that the brain may use additional mechanisms to reduce the internal gain of the VOR during combined eye-head tracking. Our results confirm that certain patients who show impairment of smooth-pursuit eye movements preserve their ability to smoothly track a moving target with combined eye-head tracking.

Modulation of high-frequency vestibuloocular reflex during visual tracking in humans

Science.gov (United States)

Das, V. E.; Leigh, R. J.; Thomas, C. W.; Averbuch-Heller, L.; Zivotofsky, A. Z.; Discenna, A. O.; Dell'Osso, L. F.

1995-01-01

1. Humans may visually track a moving object either when they are stationary or in motion. To investigate visual-vestibular interaction during both conditions, we compared horizontal smooth pursuit (SP) and active combined eye-head tracking (CEHT) of a target moving sinusoidally at 0.4 Hz in four normal subjects while the subjects were either stationary or vibrated in yaw at 2.8 Hz. We also measured the visually enhanced vestibuloocular reflex (VVOR) during vibration in yaw at 2.8 Hz over a peak head velocity range of 5-40 degrees/s. 2. We found that the gain of the VVOR at 2.8 Hz increased in all four subjects as peak head velocity increased (P modulation in vestibuloocular reflex gain occurred with increasing peak head velocity during a control condition when subjects were rotated in darkness. 3. During both horizontal SP and CEHT, tracking gains were similar, and the mean slip speed of the target's image on the retina was held below 5.5 degrees/s whether subjects were stationary or being vibrated at 2.8 Hz. During both horizontal SP and CEHT of target motion at 0.4 Hz, while subjects were vibrated in yaw, VVOR gain for the 2.8-Hz head rotations was similar to or higher than that achieved during fixation of a stationary target. This is in contrast to the decrease of VVOR gain that is reported while stationary subjects perform CEHT.(ABSTRACT TRUNCATED AT 250 WORDS).

Target Response Adaptation for Correlation Filter Tracking

KAUST Repository

Bibi, Adel Aamer

2016-09-16

Most correlation filter (CF) based trackers utilize the circulant structure of the training data to learn a linear filter that best regresses this data to a hand-crafted target response. These circularly shifted patches are only approximations to actual translations in the image, which become unreliable in many realistic tracking scenarios including fast motion, occlusion, etc. In these cases, the traditional use of a single centered Gaussian as the target response impedes tracker performance and can lead to unrecoverable drift. To circumvent this major drawback, we propose a generic framework that can adaptively change the target response from frame to frame, so that the tracker is less sensitive to the cases where circular shifts do not reliably approximate translations. To do that, we reformulate the underlying optimization to solve for both the filter and target response jointly, where the latter is regularized by measurements made using actual translations. This joint problem has a closed form solution and thus allows for multiple templates, kernels, and multi-dimensional features. Extensive experiments on the popular OTB100 benchmark show that our target adaptive framework can be combined with many CF trackers to realize significant overall performance improvement (ranging from 3 %-13.5% in precision and 3.2 %-13% in accuracy), especially in categories where this adaptation is necessary (e.g. fast motion, motion blur, etc.). © Springer International Publishing AG 2016.

Hic-Et-Nunc (Here-and-Now Encoding of a Moving Target for its Saccadic Foveation

Directory of Open Access Journals (Sweden)

Laurent Goffart

2012-10-01

Full Text Available The neural representation of a moving target undergoes a spatiotemporal “diffusion” while the associated retinal activity propagates toward the motor centers and recruits the appropriate muscles for its interception in the external world. Indeed, the divergent projections within the visual system and the transmissions of signals through multiple relays, with diverse conduction velocities and integration times, lead to activities that are spatially and temporally distributed across several brain regions. In spite of this neural “blurring”, accurate saccadic eye movements can be made to bring the image of a moving target onto the fovea. Such a performance indicates that the brain is able to rapidly estimate the current spatiotemporal coordinates of the target, at least at the time of saccade landing. We tested in the monkey the robustness of this estimate when a change in eye position and a delay are experimentally added before the animal launches a saccade toward a moving target and in the absence of visual feedback. These spatiotemporal perturbations were induced by a brief microstimulation in the deep superior colliculus. The results show that the interceptive saccades can remain accurate and relatively independent of the time taken to react and to foveate the target. We propose that the brain builds an estimate of the expected and current spatiotemporal (hic-et-nunc coordinates of the target and that this signal feeds the same local feedback loop as the mechanism proposed for guiding saccades toward a stationary target (Fleuriet and Goffart, 2012 Journal of Neuroscience 32 452–461.

Applying dual-laser spot positions measurement technology on a two-dimensional tracking measurement system

International Nuclear Information System (INIS)

Lee, Hau-Wei; Chen, Chieh-Li

2009-01-01

This paper presents a two-dimensional tracking measurement system with a tracking module, which consists of two stepping motors, two laser diodes and a four separated active areas segmented position sensitive detector (PSD). The PSD was placed on a two-dimensional moving stage and used as a tracking target. The two laser diodes in the tracking module were directly rotated to keep the laser spots on the origin of the PSD. The two-dimensional position of the target PSD on the moving stage is determined from the distance between the two motors and the tracking angles of the two laser diodes, which are rotated by the two stepping motors, respectively. In order to separate the four positional values of the two laser spots on one PSD, the laser diodes were modulated by two distinct frequencies. Multiple-laser spot position measurement technology was used to separate the four positional values of the two laser spots on the PSD. The experimental results show that the steady-state voltage shift rate is about 0.2% and dynamic cross-talk rate is smaller than 2% when the two laser spots are projected on one PSD at the same time. The measurement errors of the x and y axial positions of the two-dimensional tracking system were less than 1% in the measuring range of 20 mm. The results demonstrate that multiple-laser spot position measurement technology can be employed in a two-dimensional tracking measurement system

Exogenous Social Identity Cues Differentially Affect the Dynamic Tracking of Individual Target Faces

Science.gov (United States)

Allen, Roy; Gabbert, Fiona

2013-01-01

We report on an experiment to investigate the top-down effect of exogenous social identity cues on a multiple-identity tracking task, a paradigm well suited to investigate the processes of binding identity to spatial locations. Here we simulated an eyewitness event in which dynamic targets, all to be tracked with equal effort, were identified from…

Multi-UAV Doppler Information Fusion for Target Tracking Based on Distributed High Degrees Information Filters

Directory of Open Access Journals (Sweden)

Hamza Benzerrouk

2018-03-01

Full Text Available Multi-Unmanned Aerial Vehicle (UAV Doppler-based target tracking has not been widely investigated, specifically when using modern nonlinear information filters. A high-degree Gauss–Hermite information filter, as well as a seventh-degree cubature information filter (CIF, is developed to improve the fifth-degree and third-degree CIFs proposed in the most recent related literature. These algorithms are applied to maneuvering target tracking based on Radar Doppler range/range rate signals. To achieve this purpose, different measurement models such as range-only, range rate, and bearing-only tracking are used in the simulations. In this paper, the mobile sensor target tracking problem is addressed and solved by a higher-degree class of quadrature information filters (HQIFs. A centralized fusion architecture based on distributed information filtering is proposed, and yielded excellent results. Three high dynamic UAVs are simulated with synchronized Doppler measurement broadcasted in parallel channels to the control center for global information fusion. Interesting results are obtained, with the superiority of certain classes of higher-degree quadrature information filters.

Target tracking using a 2D radar

CSIR Research Space (South Africa)

Kriel, M

2012-08-01

Full Text Available stream_source_info Kriel_2012.pdf.txt stream_content_type text/plain stream_size 29522 Content-Encoding ISO-8859-1 stream_name Kriel_2012.pdf.txt Content-Type text/plain; charset=ISO-8859-1 737 33 Target Tracking Using....410634] 0.000019 [ 0.000020]4000.0 0 0 250.0 3D AASC 3D AASC 3D AASC Er ro r (m ) Er ro r (m ) E rr o r (m ) Time (s) 0 0 250.0Time (s) 0 0 250.0Time (s) AACT : AASC : AACT : AASC : AACT : 4000.0 4000.0 FIGURE 33...

EEG and Eye Tracking Signatures of Target Encoding during Structured Visual Search

Directory of Open Access Journals (Sweden)

Anne-Marie Brouwer

2017-05-01

Full Text Available EEG and eye tracking variables are potential sources of information about the underlying processes of target detection and storage during visual search. Fixation duration, pupil size and event related potentials (ERPs locked to the onset of fixation or saccade (saccade-related potentials, SRPs have been reported to differ dependent on whether a target or a non-target is currently fixated. Here we focus on the question of whether these variables also differ between targets that are subsequently reported (hits and targets that are not (misses. Observers were asked to scan 15 locations that were consecutively highlighted for 1 s in pseudo-random order. Highlighted locations displayed either a target or a non-target stimulus with two, three or four targets per trial. After scanning, participants indicated which locations had displayed a target. To induce memory encoding failures, participants concurrently performed an aurally presented math task (high load condition. In a low load condition, participants ignored the math task. As expected, more targets were missed in the high compared with the low load condition. For both conditions, eye tracking features distinguished better between hits and misses than between targets and non-targets (with larger pupil size and shorter fixations for missed compared with correctly encoded targets. In contrast, SRP features distinguished better between targets and non-targets than between hits and misses (with average SRPs showing larger P300 waveforms for targets than for non-targets. Single trial classification results were consistent with these averages. This work suggests complementary contributions of eye and EEG measures in potential applications to support search and detect tasks. SRPs may be useful to monitor what objects are relevant to an observer, and eye variables may indicate whether the observer should be reminded of them later.

Solar tracking system

Science.gov (United States)

Okandan, Murat; Nielson, Gregory N.

2016-07-12

Solar tracking systems, as well as methods of using such solar tracking systems, are disclosed. More particularly, embodiments of the solar tracking systems include lateral supports horizontally positioned between uprights to support photovoltaic modules. The lateral supports may be raised and lowered along the uprights or translated to cause the photovoltaic modules to track the moving sun.

Passive Target Tracking in Non-cooperative Radar System Based on Particle Filtering

Institute of Scientific and Technical Information of China (English)

LI Shuo; TAO Ran

2006-01-01

We propose a target tracking method based on particle filtering(PF) to solve the nonlinear non-Gaussian target-tracking problem in the bistatic radar systems using external radiation sources. Traditional nonlinear state estimation method is extended Kalman filtering (EKF), which is to do the first level Taylor series extension. It will cause an inaccuracy or even a scatter estimation result on condition that there is either a highly nonlinear target or a large noise square-error. Besides, Kalman filtering is the optimal resolution under a Gaussian noise assumption, and is not suitable to the non-Gaussian condition. PF is a sort of statistic filtering based on Monte Carlo simulation that is using some random samples (particles) to simulate the posterior probability density of system random variables. This method can be used in any nonlinear random system. It can be concluded through simulation that PF can achieve higher accuracy than the traditional EKF.

Target Tracking Using SePDAF under Ambiguous Angles for Distributed Array Radar

Science.gov (United States)

Long, Teng; Zhang, Honggang; Zeng, Tao; Chen, Xinliang; Liu, Quanhua; Zheng, Le

2016-01-01

Distributed array radar can improve radar detection capability and measurement accuracy. However, it will suffer cyclic ambiguity in its angle estimates according to the spatial Nyquist sampling theorem since the large sparse array is undersampling. Consequently, the state estimation accuracy and track validity probability degrades when the ambiguous angles are directly used for target tracking. This paper proposes a second probability data association filter (SePDAF)-based tracking method for distributed array radar. Firstly, the target motion model and radar measurement model is built. Secondly, the fusion result of each radar’s estimation is employed to the extended Kalman filter (EKF) to finish the first filtering. Thirdly, taking this result as prior knowledge, and associating with the array-processed ambiguous angles, the SePDAF is applied to accomplish the second filtering, and then achieving a high accuracy and stable trajectory with relatively low computational complexity. Moreover, the azimuth filtering accuracy will be promoted dramatically and the position filtering accuracy will also improve. Finally, simulations illustrate the effectiveness of the proposed method. PMID:27618058

Comparative Analysis of Several Real-Time Systems for Tracking People and/or Moving Objects using GPS

OpenAIRE

Radinski, Gligorcho; Mileva, Aleksandra

2015-01-01

When we talk about real-time systems for tracking people and/or moving objects using a Global Positioning System (GPS), there are several categories of such systems and the ways in which they work. Some uses additional hardware to extend the functionality of the offered opportunities, some are free, some are too complex and cost too much money. This paper aims to provide a clearer picture of several such systems and to show results from a comparative analysis of some popular systems for trac...

Tool for Automated Retrieval of Generic Event Tracks (TARGET)

Science.gov (United States)

Clune, Thomas; Freeman, Shawn; Cruz, Carlos; Burns, Robert; Kuo, Kwo-Sen; Kouatchou, Jules

2013-01-01

Methods have been developed to identify and track tornado-producing mesoscale convective systems (MCSs) automatically over the continental United States, in order to facilitate systematic studies of these powerful and often destructive events. Several data sources were combined to ensure event identification accuracy. Records of watches and warnings issued by National Weather Service (NWS), and tornado locations and tracks from the Tornado History Project (THP) were used to locate MCSs in high-resolution precipitation observations and GOES infrared (11-micron) Rapid Scan Operation (RSO) imagery. Thresholds are then applied to the latter two data sets to define MCS events and track their developments. MCSs produce a broad range of severe convective weather events that are significantly affecting the living conditions of the populations exposed to them. Understanding how MCSs grow and develop could help scientists improve their weather prediction models, and also provide tools to decision-makers whose goals are to protect populations and their property. Associating storm cells across frames of remotely sensed images poses a difficult problem because storms evolve, split, and merge. Any storm-tracking method should include the following processes: storm identification, storm tracking, and quantification of storm intensity and activity. The spatiotemporal coordinates of the tracks will enable researchers to obtain other coincident observations to conduct more thorough studies of these events. In addition to their tracked locations, their areal extents, precipitation intensities, and accumulations all as functions of their evolutions in time were also obtained and recorded for these events. All parameters so derived can be catalogued into a moving object database (MODB) for custom queries. The purpose of this software is to provide a generalized, cross-platform, pluggable tool for identifying events within a set of scientific data based upon specified criteria with the

Some Aspects on Filter Design for Target Tracking

Directory of Open Access Journals (Sweden)

Bertil Ekstrand

2012-01-01

Full Text Available Tracking filter design is discussed. It is argued that the basis of the present stochastic paradigm is questionable. White process noise is not adequate as a model for target manoeuvring, stochastic least-square optimality is not relevant or required in practice, the fact that requirements are necessary for design is ignored, and root mean square (RMS errors are insufficient as performance measure. It is argued that there is no process noise and that the covariance of the assumed process noise contains the design parameters. Focus is on the basic tracking filter, the Kalman filter, which is convenient for clarity and simplicity, but the arguments and conclusions are relevant in general. For design the possibility of an observer transfer function approach is pointed out. The issues can also be considered as a consequence of the fact that there is a difference between estimation and design. The - filter is used for illustration.

Robotic radiosurgery. Treating tumors that move with respiration

International Nuclear Information System (INIS)

Urschel, Harold C. Jr.; Kresl, John J.; Luketich, James D.; Papiez, Lech; Timmerman, Robert D.; Schulz, Raymond A.

2007-01-01

Addresses in detail all aspects of the use of robotic radiosurgery to treat tumors of the lung, liver, and pancreas Includes full consideration of tumor tracking techniques, dosimetry, radiobiology, and fiducial placement strategies Written by leading experts Includes many high quality illustrations Stereotactic radiosurgery continues to evolve in ways that allow this powerful technology to reach and treat more tumors in more patients. This volume in the Robotic Radiosurgery series is devoted to theory and practice in the emerging field of stereotactic radiosurgery (also called stereotactic body radiation therapy) for extracranial tumors, particularly those that move as patients breathe. The book is divided into six sections. The first three sections address tumor motion due to respiration and tumor tracking techniques; dosimetry, radiobiology, and imaging; and fiducial placement systems. The fourth and fifth sections then discuss in depth the use of robotic radiosurgery to treat lung and abdominal tumors, respectively, and a final section explains emerging concepts and techniques. Within this framework, detailed information is provided on the technology and methodology for delivery of high doses of radiation to moving targets, radiobiological and radiological principles, and the challenges faced by clinicians performing extracranial stereotactic radiosurgery. Furthermore, there are thorough reviews of the general clinical literature on stereotactic radiation treatment of tumors of the lungs, liver, and pancreas, and the latest clinical data from clinicians conducting clinical studies using the CyberKnife registered Robotic Radiosurgery System. Special attention is given to the frameless robotic radiosurgery device known as the CyberKnife, the only image-guided radiosurgery system that utilizes intelligent robotics to track, detect, and correct for changes in tumor position during treatments. Tumors that move with respiration are treated with the CyberKnife using a

Robotic radiosurgery. Treating tumors that move with respiration

Energy Technology Data Exchange (ETDEWEB)

Urschel, Harold C. Jr. [Baylor University Medical Center, Dallas, TX (United States). Chair of Cardiovascular and Thoracic Surgical Research, Education and Clinical Excellence; Kresl, John J. [Arizona Oncology Services at St. Joseph' s Hospital and Medical Center, Phoenix, AZ (United States). Dept. of Radiation Oncology; Luketich, James D. [University of Pittsburgh Medical Center PUH, Pittsburgh, PA (United States). The Heart, Lung and Esophageal Surgery Inst.; Papiez, Lech; Timmerman, Robert D. [University of Texas Southwestern Medical Center, Dallas, TX (United States). Dept. of Radiation Oncology; Schulz, Raymond A. (eds.)

2007-07-01

Addresses in detail all aspects of the use of robotic radiosurgery to treat tumors of the lung, liver, and pancreas Includes full consideration of tumor tracking techniques, dosimetry, radiobiology, and fiducial placement strategies Written by leading experts Includes many high quality illustrations Stereotactic radiosurgery continues to evolve in ways that allow this powerful technology to reach and treat more tumors in more patients. This volume in the Robotic Radiosurgery series is devoted to theory and practice in the emerging field of stereotactic radiosurgery (also called stereotactic body radiation therapy) for extracranial tumors, particularly those that move as patients breathe. The book is divided into six sections. The first three sections address tumor motion due to respiration and tumor tracking techniques; dosimetry, radiobiology, and imaging; and fiducial placement systems. The fourth and fifth sections then discuss in depth the use of robotic radiosurgery to treat lung and abdominal tumors, respectively, and a final section explains emerging concepts and techniques. Within this framework, detailed information is provided on the technology and methodology for delivery of high doses of radiation to moving targets, radiobiological and radiological principles, and the challenges faced by clinicians performing extracranial stereotactic radiosurgery. Furthermore, there are thorough reviews of the general clinical literature on stereotactic radiation treatment of tumors of the lungs, liver, and pancreas, and the latest clinical data from clinicians conducting clinical studies using the CyberKnife {sup registered} Robotic Radiosurgery System. Special attention is given to the frameless robotic radiosurgery device known as the CyberKnife, the only image-guided radiosurgery system that utilizes intelligent robotics to track, detect, and correct for changes in tumor position during treatments. Tumors that move with respiration are treated with the Cyber

Low-Cost Radar Sensors for Personnel Detection and Tracking in Urban Areas

Science.gov (United States)

2007-01-31

progress on the reserach grant "Low-Cost Radar Sensors for Personnel Detection and Tracking in Urban Areas" during the period 1 May 2005 - 31 December...The limitations of the proposed system resulting from DOA ambiguity of multiple moving targets are studied. 2. METHODOLOGY Our radar receiver

Hemifield effects in multiple identity tracking.

Directory of Open Access Journals (Sweden)

Charlotte Hudson

Full Text Available In everyday life, we often need to attentively track moving objects. A previous study has claimed that this tracking occurs independently in the left and right visual hemifields (Alvarez & Cavanagh, 2005, Psychological Science,16, 637-647. Specifically, it was shown that observers were much more accurate at tracking objects that were spread over both visual hemifields as opposed to when all were confined to a single visual hemifield. In that study, observers were not required to remember the identities of the objects. Conversely, in real life, there is seldom any benefit to tracking an object unless you can also recall its identity. It has been predicted that when observers are required to remember the identities of the tracked objects a bilateral advantage should no longer be observed (Oksama & Hyönä, 2008, Cognitive Psychology, 56, 237-283. We tested this prediction and found that a bilateral advantage still occurred, though it was not as strong as when observers were not required to remember the identities of the targets. Even in the later case we found that tracking was not completely independent in the two visual hemifields. We present a combined model of multiple object tracking and multiple identity tracking that can explain our data.

An Energy-Efficient Sleep Strategy for Target Tracking Sensor Networks

Directory of Open Access Journals (Sweden)

Juan FENG

2014-02-01

Full Text Available Energy efficiency is very important for sensor networks since sensor nodes have limited energy supply from battery. So far, many researches have been focused on this issue, while less emphasis was placed on the optimal sleep time of each node. This paper proposed an adaptive energy conservation strategy for target tracking based on a grid network structure, where each node autonomously determines when and if to sleep. It allows sensor nodes far away from targets to sleep to save energy and guarantee the tracking accuracy. The proposed approach extend network lifetime by adopting an adaptive sleep scheduling scheme that combines the local power management (PM and the adaptive coordinate PM strategies to schedule the activities of sensor nodes. And each node can choose an optimal sleep time so as to make system adaptive and energy-efficient. We show the performance of our approach in terms of energy drop, comparing it to a naive approach, dynamic PM with fixed sleep time and the coordinate PM strategies. From the experimental results, it is readily seen that the efficiency of the proposed approach.

Target tracking and surveillance by fusing stereo and RFID information

Science.gov (United States)

Raza, Rana H.; Stockman, George C.

2012-06-01

Ensuring security in high risk areas such as an airport is an important but complex problem. Effectively tracking personnel, containers, and machines is a crucial task. Moreover, security and safety require understanding the interaction of persons and objects. Computer vision (CV) has been a classic tool; however, variable lighting, imaging, and random occlusions present difficulties for real-time surveillance, resulting in erroneous object detection and trajectories. Determining object ID via CV at any instance of time in a crowded area is computationally prohibitive, yet the trajectories of personnel and objects should be known in real time. Radio Frequency Identification (RFID) can be used to reliably identify target objects and can even locate targets at coarse spatial resolution, while CV provides fuzzy features for target ID at finer resolution. Our research demonstrates benefits obtained when most objects are "cooperative" by being RFID tagged. Fusion provides a method to simplify the correspondence problem in 3D space. A surveillance system can query for unique object ID as well as tag ID information, such as target height, texture, shape and color, which can greatly enhance scene analysis. We extend geometry-based tracking so that intermittent information on ID and location can be used in determining a set of trajectories of N targets over T time steps. We show that partial-targetinformation obtained through RFID can reduce computation time (by 99.9% in some cases) and also increase the likelihood of producing correct trajectories. We conclude that real-time decision-making should be possible if the surveillance system can integrate information effectively between the sensor level and activity understanding level.

Moving Target Photometry Using WISE and NEOWISE

Science.gov (United States)

Wright, Edward L.

2015-01-01

WISE band 1 observations have a significant noise contribution from confusion. The image subtraction done on W0855-0714 by Wright et al. (2014) shows that this noise source can be eliminated for sources that move by much more than the beamsize. This paper describes an analysis that includes a pattern of celestially fixed flux plus a source moving with a known trajectory. This technique allows the confusion noise to be modeled with nuisance parameters and removed even for sources that have not moved by many beamwidths. However, the detector noise is magnified if the motion is too small. Examples of the method applied to fast moving Y dwarfs and slow moving planets will be shown.

Object acquisition and tracking for space-based surveillance

Science.gov (United States)

1991-11-01

This report presents the results of research carried out by Space Computer Corporation under the U.S. government's Small Business Innovation Research (SBIR) Program. The work was sponsored by the Strategic Defense Initiative Organization and managed by the Office of Naval Research under Contracts N00014-87-C-0801 (Phase 1) and N00014-89-C-0015 (Phase 2). The basic purpose of this research was to develop and demonstrate a new approach to the detection of, and initiation of track on, moving targets using data from a passive infrared or visual sensor. This approach differs in very significant ways from the traditional approach of dividing the required processing into time dependent, object dependent, and data dependent processing stages. In that approach individual targets are first detected in individual image frames, and the detections are then assembled into tracks. That requires that the signal to noise ratio in each image frame be sufficient for fairly reliable target detection. In contrast, our approach bases detection of targets on multiple image frames, and, accordingly, requires a smaller signal to noise ratio. It is sometimes referred to as track before detect, and can lead to a significant reduction in total system cost. For example, it can allow greater detection range for a single sensor, or it can allow the use of smaller sensor optics. Both the traditional and track before detect approaches are applicable to systems using scanning sensors, as well as those which use staring sensors.

3D range-gated super-resolution imaging based on stereo matching for moving platforms and targets

Science.gov (United States)

Sun, Liang; Wang, Xinwei; Zhou, Yan

2017-11-01

3D range-gated superresolution imaging is a novel 3D reconstruction technique for target detection and recognition with good real-time performance. However, for moving targets or platforms such as airborne, shipborne, remote operated vehicle and autonomous vehicle, 3D reconstruction has a large error or failure. In order to overcome this drawback, we propose a method of stereo matching for 3D range-gated superresolution reconstruction algorithm. In experiment, the target is a doll of Mario with a height of 38cm at the location of 34m, and we obtain two successive frame images of the Mario. To confirm our method is effective, we transform the original images with translation, rotation, scale and perspective, respectively. The experimental result shows that our method has a good result of 3D reconstruction for moving targets or platforms.

An Adaptive Moving Target Imaging Method for Bistatic Forward-Looking SAR Using Keystone Transform and Optimization NLCS.

Science.gov (United States)

Li, Zhongyu; Wu, Junjie; Huang, Yulin; Yang, Haiguang; Yang, Jianyu

2017-01-23

Bistatic forward-looking SAR (BFSAR) is a kind of bistatic synthetic aperture radar (SAR) system that can image forward-looking terrain in the flight direction of an aircraft. Until now, BFSAR imaging theories and methods for a stationary scene have been researched thoroughly. However, for moving-target imaging with BFSAR, the non-cooperative movement of the moving target induces some new issues: (I) large and unknown range cell migration (RCM) (including range walk and high-order RCM); (II) the spatial-variances of the Doppler parameters (including the Doppler centroid and high-order Doppler) are not only unknown, but also nonlinear for different point-scatterers. In this paper, we put forward an adaptive moving-target imaging method for BFSAR. First, the large and unknown range walk is corrected by applying keystone transform over the whole received echo, and then, the relationships among the unknown high-order RCM, the nonlinear spatial-variances of the Doppler parameters, and the speed of the mover, are established. After that, using an optimization nonlinear chirp scaling (NLCS) technique, not only can the unknown high-order RCM be accurately corrected, but also the nonlinear spatial-variances of the Doppler parameters can be balanced. At last, a high-order polynomial filter is applied to compress the whole azimuth data of the moving target. Numerical simulations verify the effectiveness of the proposed method.

An Adaptive Moving Target Imaging Method for Bistatic Forward-Looking SAR Using Keystone Transform and Optimization NLCS

Directory of Open Access Journals (Sweden)

Zhongyu Li

2017-01-01

Full Text Available Bistatic forward-looking SAR (BFSAR is a kind of bistatic synthetic aperture radar (SAR system that can image forward-looking terrain in the flight direction of an aircraft. Until now, BFSAR imaging theories and methods for a stationary scene have been researched thoroughly. However, for moving-target imaging with BFSAR, the non-cooperative movement of the moving target induces some new issues: (I large and unknown range cell migration (RCM (including range walk and high-order RCM; (II the spatial-variances of the Doppler parameters (including the Doppler centroid and high-order Doppler are not only unknown, but also nonlinear for different point-scatterers. In this paper, we put forward an adaptive moving-target imaging method for BFSAR. First, the large and unknown range walk is corrected by applying keystone transform over the whole received echo, and then, the relationships among the unknown high-order RCM, the nonlinear spatial-variances of the Doppler parameters, and the speed of the mover, are established. After that, using an optimization nonlinear chirp scaling (NLCS technique, not only can the unknown high-order RCM be accurately corrected, but also the nonlinear spatial-variances of the Doppler parameters can be balanced. At last, a high-order polynomial filter is applied to compress the whole azimuth data of the moving target. Numerical simulations verify the effectiveness of the proposed method.

Visual Detection and Tracking System for a Spherical Amphibious Robot.

Science.gov (United States)

Guo, Shuxiang; Pan, Shaowu; Shi, Liwei; Guo, Ping; He, Yanlin; Tang, Kun

2017-04-15

With the goal of supporting close-range observation tasks of a spherical amphibious robot, such as ecological observations and intelligent surveillance, a moving target detection and tracking system was designed and implemented in this study. Given the restrictions presented by the amphibious environment and the small-sized spherical amphibious robot, an industrial camera and vision algorithms using adaptive appearance models were adopted to construct the proposed system. To handle the problem of light scattering and absorption in the underwater environment, the multi-scale retinex with color restoration algorithm was used for image enhancement. Given the environmental disturbances in practical amphibious scenarios, the Gaussian mixture model was used to detect moving targets entering the field of view of the robot. A fast compressive tracker with a Kalman prediction mechanism was used to track the specified target. Considering the limited load space and the unique mechanical structure of the robot, the proposed vision system was fabricated with a low power system-on-chip using an asymmetric and heterogeneous computing architecture. Experimental results confirmed the validity and high efficiency of the proposed system. The design presented in this paper is able to meet future demands of spherical amphibious robots in biological monitoring and multi-robot cooperation.

Visual Detection and Tracking System for a Spherical Amphibious Robot

Science.gov (United States)

Guo, Shuxiang; Pan, Shaowu; Shi, Liwei; Guo, Ping; He, Yanlin; Tang, Kun

2017-01-01

With the goal of supporting close-range observation tasks of a spherical amphibious robot, such as ecological observations and intelligent surveillance, a moving target detection and tracking system was designed and implemented in this study. Given the restrictions presented by the amphibious environment and the small-sized spherical amphibious robot, an industrial camera and vision algorithms using adaptive appearance models were adopted to construct the proposed system. To handle the problem of light scattering and absorption in the underwater environment, the multi-scale retinex with color restoration algorithm was used for image enhancement. Given the environmental disturbances in practical amphibious scenarios, the Gaussian mixture model was used to detect moving targets entering the field of view of the robot. A fast compressive tracker with a Kalman prediction mechanism was used to track the specified target. Considering the limited load space and the unique mechanical structure of the robot, the proposed vision system was fabricated with a low power system-on-chip using an asymmetric and heterogeneous computing architecture. Experimental results confirmed the validity and high efficiency of the proposed system. The design presented in this paper is able to meet future demands of spherical amphibious robots in biological monitoring and multi-robot cooperation. PMID:28420134

Clustering and fault tolerance for target tracking using wireless sensor networks

International Nuclear Information System (INIS)

Bhatti, S.; Khanzada, S.; Memon, S.

2012-01-01

Over the last few years, the deployment of WSNs (Wireless Sensor Networks) has been fostered in diverse applications. WSN has great potential for a variety of domains ranging from scientific experiments to commercial applications. Due to the deployment of WSNs in dynamic and unpredictable environments. They have potential to cope with variety of faults. This paper proposes an energy-aware fault-tolerant clustering protocol for target tracking applications termed as the FITf (Fault Tolerant Target Tracking) protocol The identification of RNs (Redundant Nodes) makes SN (Sensor Node) fault tolerance plausible and the clustering endorsed recovery of sensors supervised by a faulty CH (Cluster Head). The FfTT protocol intends two steps of reducing energy consumption: first, by identifying RNs in the network; secondly, by restricting the numbers of SNs sending data to the CH. Simulations validate the scalability and low power consumption of the FITf protocol in comparison with LEACH protocol. (author)

Use of a track and vertex processor in a fixed-target charm experiment

International Nuclear Information System (INIS)

Schub, M.H.; Carey, T.A.; Hsiung, Y.B.; Kaplan, D.M.; Lee, C.; Miller, G.; Sa, J.; Teng, P.K.

1996-01-01

We have constructed and operated a high-speed parallel-pipelined track and vertex processor and used it to trigger data acquisition in a high-rate charm and beauty experiment at Fermilab. The processor uses information from hodoscopes and wire chambers to reconstruct tracks in the bend view of a magnetic spectrometer, and uses these tracks to find the corresponding tracks in a set of silicon-strip detectors. The processor then forms vertices and triggers the experiment if at least one vertex is downstream of the target. Under typical charm running conditions, with an interaction rate of ∼5 MHz, the processor rejects 80-90% of lower-level triggers while maintaining efficiency of ∼70% for two-prong D-meson decays. (orig.)

Automatic radar target recognition of objects falling on railway tracks

International Nuclear Information System (INIS)

Mroué, A; Heddebaut, M; Elbahhar, F; Rivenq, A; Rouvaen, J-M

2012-01-01

This paper presents an automatic radar target recognition procedure based on complex resonances using the signals provided by ultra-wideband radar. This procedure is dedicated to detection and identification of objects lying on railway tracks. For an efficient complex resonance extraction, a comparison between several pole extraction methods is illustrated. Therefore, preprocessing methods are presented aiming to remove most of the erroneous poles interfering with the discrimination scheme. Once physical poles are determined, a specific discrimination technique is introduced based on the Euclidean distances. Both simulation and experimental results are depicted showing an efficient discrimination of different targets including guided transport passengers

Cluster-based Dynamic Energy Management for Collaborative Target Tracking in Wireless Sensor Networks

Directory of Open Access Journals (Sweden)

Dao-Wei Bi

2007-07-01

Full Text Available A primary criterion of wireless sensor network is energy efficiency. Focused onthe energy problem of target tracking in wireless sensor networks, this paper proposes acluster-based dynamic energy management mechanism. Target tracking problem isformulated by the multi-sensor detection model as well as energy consumption model. Adistributed adaptive clustering approach is investigated to form a reasonable routingframework which has uniform cluster head distribution. Dijkstra’s algorithm is utilized toobtain optimal intra-cluster routing. Target position is predicted by particle filter. Thepredicted target position is adopted to estimate the idle interval of sensor nodes. Hence,dynamic awakening approach is exploited to prolong sleep time of sensor nodes so that theoperation energy consumption of wireless sensor network can be reduced. The sensornodes around the target wake up on time and act as sensing candidates. With the candidatesensor nodes and predicted target position, the optimal sensor node selection is considered.Binary particle swarm optimization is proposed to minimize the total energy consumptionduring collaborative sensing and data reporting. Experimental results verify that theproposed clustering approach establishes a low-energy communication structure while theenergy efficiency of wireless sensor networks is enhanced by cluster-based dynamic energymanagement.

Trade-Off Exploration for Target Tracking Application in a Customized Multiprocessor Architecture

Directory of Open Access Journals (Sweden)

Yassin El-Hillali

2009-01-01

Full Text Available This paper presents the design of an FPGA-based multiprocessor-system-on-chip (MPSoC architecture optimized for Multiple Target Tracking (MTT in automotive applications. An MTT system uses an automotive radar to track the speed and relative position of all the vehicles (targets within its field of view. As the number of targets increases, the computational needs of the MTT system also increase making it difficult for a single processor to handle it alone. Our implementation distributes the computational load among multiple soft processor cores optimized for executing specific computational tasks. The paper explains how we designed and profiled the MTT application to partition it among different processors. It also explains how we applied different optimizations to customize the individual processor cores to their assigned tasks and to assess their impact on performance and FPGA resource utilization. The result is a complete MTT application running on an optimized MPSoC architecture that fits in a contemporary medium-sized FPGA and that meets the application's real-time constraints.

Margin estimation and disturbances of irradiation field in layer-stacking carbon-ion beams for respiratory moving targets.

Science.gov (United States)

Tajiri, Shinya; Tashiro, Mutsumi; Mizukami, Tomohiro; Tsukishima, Chihiro; Torikoshi, Masami; Kanai, Tatsuaki

2017-11-01

Carbon-ion therapy by layer-stacking irradiation for static targets has been practised in clinical treatments. In order to apply this technique to a moving target, disturbances of carbon-ion dose distributions due to respiratory motion have been studied based on the measurement using a respiratory motion phantom, and the margin estimation given by the square root of the summation Internal margin2+Setup margin2 has been assessed. We assessed the volume in which the variation in the ratio of the dose for a target moving due to respiration relative to the dose for a static target was within 5%. The margins were insufficient for use with layer-stacking irradiation of a moving target, and an additional margin was required. The lateral movement of a target converts to the range variation, as the thickness of the range compensator changes with the movement of the target. Although the additional margin changes according to the shape of the ridge filter, dose uniformity of 5% can be achieved for a spherical target 93 mm in diameter when the upward range variation is limited to 5 mm and the additional margin of 2.5 mm is applied in case of our ridge filter. Dose uniformity in a clinical target largely depends on the shape of the mini-peak as well as on the bolus shape. We have shown the relationship between range variation and dose uniformity. In actual therapy, the upper limit of target movement should be considered by assessing the bolus shape. © The Author 2017. Published by Oxford University Press on behalf of The Japan Radiation Research Society and Japanese Society for Radiation Oncology.

Greenhouse gas emission trends and projections in Europe 2011. Tracking progress towards Kyoto and 2020 targets

Energy Technology Data Exchange (ETDEWEB)

Busche, J.; Scheffler, M.; Graichen, V. (Umweltbundesamt, Vienna (Austria)) (and others)

2011-10-15

At the end of 2010, the EU-15 was on track to achieve its Kyoto target but three EU-15 Member States (Austria, Italy and Luxembourg) were not on track to meet their burden-sharing targets. These countries must therefore seriously consider further action to ensure compliance, in particular revising their plans on using flexible mechanisms. Among the EEA member countries outside the EU, Liechtenstein and Switzerland were not on track to achieve their Kyoto target at the end of 2009. All other European countries are on track to meet their targets, either based on domestic emissions only or with the assistance of Kyoto mechanisms. The economic recession had a significant impact on the EU's total greenhouse gas (GHG) emission trends but a more limited effect on progress towards Kyoto targets. This is because emissions in the sectors covered by the EU Emissions Trading Scheme (ETS), which were most affected by the crisis, do not affect Kyoto compliance once ETS caps have been set. With existing national measures, Member States do not project enough emission reductions for the EU to meet its unilateral 20 % reduction commitment in 2020. Additional measures currently planned by Member States will help further reduce emissions but will be insufficient to achieve the important emission cuts needed in the longer term. By 2020 Member States must enhance their efforts to reduce emissions in non-EU ETS sectors, such as the residential, transport or agriculture sectors, where legally binding national targets have been set under the EU's 2009 climate and energy package. (Author)

ENERGY EFFICIENT TRACKING SYSTEM USING WIRELESS SENSORS

OpenAIRE

Thankaselvi Kumaresan; Sheryl Mathias; Digja Khanvilkar; Prof. Smita Dange

2014-01-01

One of the most important applications of wireless sensor networks (WSNs) is surveillance system, which is used to track moving targets. WSN is composed of a large number of low cost sensors which operate on the power derived from batteries. Energy efficiency is an important issue in WSN, which determines the network lifetime. Due to the need for continuous monitoring with 100% efficiency, keeping all the sensor nodes active permanently leads to fast draining of batteries. Hen...

Real-time object detection, tracking and occlusion reasoning

Science.gov (United States)

Divakaran, Ajay; Yu, Qian; Tamrakar, Amir; Sawhney, Harpreet Singh; Zhu, Jiejie; Javed, Omar; Liu, Jingen; Cheng, Hui; Eledath, Jayakrishnan

2018-02-27

A system for object detection and tracking includes technologies to, among other things, detect and track moving objects, such as pedestrians and/or vehicles, in a real-world environment, handle static and dynamic occlusions, and continue tracking moving objects across the fields of view of multiple different cameras.

Persistent Aerial Tracking

KAUST Repository

Mueller, Matthias

2016-01-01

persistent, robust and autonomous object tracking system for unmanned aerial vehicles (UAVs) called Persistent Aerial Tracking (PAT). A computer vision and control strategy is applied to a diverse set of moving objects (e.g. humans, animals, cars, boats, etc

Online 4D ultrasound guidance for real-time motion compensation by MLC tracking.

Science.gov (United States)

Ipsen, Svenja; Bruder, Ralf; O'Brien, Rick; Keall, Paul J; Schweikard, Achim; Poulsen, Per R

2016-10-01

With the trend in radiotherapy moving toward dose escalation and hypofractionation, the need for highly accurate targeting increases. While MLC tracking is already being successfully used for motion compensation of moving targets in the prostate, current real-time target localization methods rely on repeated x-ray imaging and implanted fiducial markers or electromagnetic transponders rather than direct target visualization. In contrast, ultrasound imaging can yield volumetric data in real-time (3D + time = 4D) without ionizing radiation. The authors report the first results of combining these promising techniques-online 4D ultrasound guidance and MLC tracking-in a phantom. A software framework for real-time target localization was installed directly on a 4D ultrasound station and used to detect a 2 mm spherical lead marker inside a water tank. The lead marker was rigidly attached to a motion stage programmed to reproduce nine characteristic tumor trajectories chosen from large databases (five prostate, four lung). The 3D marker position detected by ultrasound was transferred to a computer program for MLC tracking at a rate of 21.3 Hz and used for real-time MLC aperture adaption on a conventional linear accelerator. The tracking system latency was measured using sinusoidal trajectories and compensated for by applying a kernel density prediction algorithm for the lung traces. To measure geometric accuracy, static anterior and lateral conformal fields as well as a 358° arc with a 10 cm circular aperture were delivered for each trajectory. The two-dimensional (2D) geometric tracking error was measured as the difference between marker position and MLC aperture center in continuously acquired portal images. For dosimetric evaluation, VMAT treatment plans with high and low modulation were delivered to a biplanar diode array dosimeter using the same trajectories. Dose measurements with and without MLC tracking were compared to a static reference dose using 3%/3 mm and 2

An open source framework for tracking and state estimation ('Stone Soup')

Science.gov (United States)

Thomas, Paul A.; Barr, Jordi; Balaji, Bhashyam; White, Kruger

2017-05-01

The ability to detect and unambiguously follow all moving entities in a state-space is important in multiple domains both in defence (e.g. air surveillance, maritime situational awareness, ground moving target indication) and the civil sphere (e.g. astronomy, biology, epidemiology, dispersion modelling). However, tracking and state estimation researchers and practitioners have difficulties recreating state-of-the-art algorithms in order to benchmark their own work. Furthermore, system developers need to assess which algorithms meet operational requirements objectively and exhaustively rather than intuitively or driven by personal favourites. We have therefore commenced the development of a collaborative initiative to create an open source framework for production, demonstration and evaluation of Tracking and State Estimation algorithms. The initiative will develop a (MIT-licensed) software platform for researchers and practitioners to test, verify and benchmark a variety of multi-sensor and multi-object state estimation algorithms. The initiative is supported by four defence laboratories, who will contribute to the development effort for the framework. The tracking and state estimation community will derive significant benefits from this work, including: access to repositories of verified and validated tracking and state estimation algorithms, a framework for the evaluation of multiple algorithms, standardisation of interfaces and access to challenging data sets. Keywords: Tracking,

Tracking Maneuvering Group Target with Extension Predicted and Best Model Augmentation Method Adapted

Directory of Open Access Journals (Sweden)

Linhai Gan

2017-01-01

Full Text Available The random matrix (RM method is widely applied for group target tracking. The assumption that the group extension keeps invariant in conventional RM method is not yet valid, as the orientation of the group varies rapidly while it is maneuvering; thus, a new approach with group extension predicted is derived here. To match the group maneuvering, a best model augmentation (BMA method is introduced. The existing BMA method uses a fixed basic model set, which may lead to a poor performance when it could not ensure basic coverage of true motion modes. Here, a maneuvering group target tracking algorithm is proposed, where the group extension prediction and the BMA adaption are exploited. The performance of the proposed algorithm will be illustrated by simulation.

Online tracking of outdoor lighting variations for augmented reality with moving cameras.

Science.gov (United States)

Liu, Yanli; Granier, Xavier

2012-04-01

In augmented reality, one of key tasks to achieve a convincing visual appearance consistency between virtual objects and video scenes is to have a coherent illumination along the whole sequence. As outdoor illumination is largely dependent on the weather, the lighting condition may change from frame to frame. In this paper, we propose a full image-based approach for online tracking of outdoor illumination variations from videos captured with moving cameras. Our key idea is to estimate the relative intensities of sunlight and skylight via a sparse set of planar feature-points extracted from each frame. To address the inevitable feature misalignments, a set of constraints are introduced to select the most reliable ones. Exploiting the spatial and temporal coherence of illumination, the relative intensities of sunlight and skylight are finally estimated by using an optimization process. We validate our technique on a set of real-life videos and show that the results with our estimations are visually coherent along the video sequences.

Stem Cell Tracking Technologies for Neurological Regenerative Medicine Purposes

Directory of Open Access Journals (Sweden)

Yongtao Zheng

2017-01-01

Full Text Available The growing field of stem cell therapy is moving toward clinical trials in a variety of applications, particularly for neurological diseases. However, this translation of cell therapies into humans has prompted a need to create innovative and breakthrough methods for stem cell tracing, to explore the migration routes and its reciprocity with microenvironment targets in the body, to monitor and track the outcome after stem cell transplantation therapy, and to track the distribution and cell viability of transplanted cells noninvasively and longitudinally. Recently, a larger number of cell tracking methods in vivo were developed and applied in animals and humans, including magnetic resonance imaging, nuclear medicine imaging, and optical imaging. This review has been intended to summarize the current use of those imaging tools in tracking stem cells, detailing their main features and drawbacks, including image resolution, tissue penetrating depth, and biosafety aspects. Finally, we address that multimodality imaging method will be a more potential tracking tool in the future clinical application.

Robust infrared target tracking using discriminative and generative approaches

Science.gov (United States)

Asha, C. S.; Narasimhadhan, A. V.

2017-09-01

The process of designing an efficient tracker for thermal infrared imagery is one of the most challenging tasks in computer vision. Although a lot of advancement has been achieved in RGB videos over the decades, textureless and colorless properties of objects in thermal imagery pose hard constraints in the design of an efficient tracker. Tracking of an object using a single feature or a technique often fails to achieve greater accuracy. Here, we propose an effective method to track an object in infrared imagery based on a combination of discriminative and generative approaches. The discriminative technique makes use of two complementary methods such as kernelized correlation filter with spatial feature and AdaBoost classifier with pixel intesity features to operate in parallel. After obtaining optimized locations through discriminative approaches, the generative technique is applied to determine the best target location using a linear search method. Unlike the baseline algorithms, the proposed method estimates the scale of the target by Lucas-Kanade homography estimation. To evaluate the proposed method, extensive experiments are conducted on 17 challenging infrared image sequences obtained from LTIR dataset and a significant improvement of mean distance precision and mean overlap precision is accomplished as compared with the existing trackers. Further, a quantitative and qualitative assessment of the proposed approach with the state-of-the-art trackers is illustrated to clearly demonstrate an overall increase in performance.

Research on the algorithm of infrared target detection based on the frame difference and background subtraction method

Science.gov (United States)

Liu, Yun; Zhao, Yuejin; Liu, Ming; Dong, Liquan; Hui, Mei; Liu, Xiaohua; Wu, Yijian

2015-09-01

As an important branch of infrared imaging technology, infrared target tracking and detection has a very important scientific value and a wide range of applications in both military and civilian areas. For the infrared image which is characterized by low SNR and serious disturbance of background noise, an innovative and effective target detection algorithm is proposed in this paper, according to the correlation of moving target frame-to-frame and the irrelevance of noise in sequential images based on OpenCV. Firstly, since the temporal differencing and background subtraction are very complementary, we use a combined detection method of frame difference and background subtraction which is based on adaptive background updating. Results indicate that it is simple and can extract the foreground moving target from the video sequence stably. For the background updating mechanism continuously updating each pixel, we can detect the infrared moving target more accurately. It paves the way for eventually realizing real-time infrared target detection and tracking, when transplanting the algorithms on OpenCV to the DSP platform. Afterwards, we use the optimal thresholding arithmetic to segment image. It transforms the gray images to black-white images in order to provide a better condition for the image sequences detection. Finally, according to the relevance of moving objects between different frames and mathematical morphology processing, we can eliminate noise, decrease the area, and smooth region boundaries. Experimental results proves that our algorithm precisely achieve the purpose of rapid detection of small infrared target.

A Cubature-Principle-Assisted IMM-Adaptive UKF Algorithm for Maneuvering Target Tracking Caused by Sensor Faults

Directory of Open Access Journals (Sweden)

Huan Zhou

2017-09-01

Full Text Available Aimed at solving the problem of decreased filtering precision while maneuvering target tracking caused by non-Gaussian distribution and sensor faults, we developed an efficient interacting multiple model-unscented Kalman filter (IMM-UKF algorithm. By dividing the IMM-UKF into two links, the algorithm introduces the cubature principle to approximate the probability density of the random variable, after the interaction, by considering the external link of IMM-UKF, which constitutes the cubature-principle-assisted IMM method (CPIMM for solving the non-Gaussian problem, and leads to an adaptive matrix to balance the contribution of the state. The algorithm provides filtering solutions by considering the internal link of IMM-UKF, which is called a new adaptive UKF algorithm (NAUKF to address sensor faults. The proposed CPIMM-NAUKF is evaluated in a numerical simulation and two practical experiments including one navigation experiment and one maneuvering target tracking experiment. The simulation and experiment results show that the proposed CPIMM-NAUKF has greater filtering precision and faster convergence than the existing IMM-UKF. The proposed algorithm achieves a very good tracking performance, and will be effective and applicable in the field of maneuvering target tracking.

An efficient method of fuel ice formation in moving free-standing ICF/IFE targets

Science.gov (United States)

Aleksandrova, I. V.; Bazdenkov, S. V.; Chtcherbakov, V. I.; Gromov, A. I.; Koresheva, E. R.; Koshelev, E. A.; Osipov, I. E.; Yaguzinskiy, L. S.

2004-04-01

Currently, research fields related to the elaboration of efficient layering methods for ICF/IFE applications are rapidly expanding. Significant progress has been made in the technology development based on rapid fuel layering inside moving free-standing targets (FST) which is referred to as the FST layering method. This paper presents our new results obtained in this area and describes technologically elegant solutions towards demonstrating a credible pathway for mass production of IFE cryogenic targets.

An efficient method of fuel ice formation in moving free-standing ICF/IFE targets

International Nuclear Information System (INIS)

Aleksandrova, I V; Bazdenkov, S V; Chtcherbakov, V I; Gromov, A I; Koresheva, E R; Koshelev, E A; Osipov, I E; Yaguzinskiy, L S

2004-01-01

Currently, research fields related to the elaboration of efficient layering methods for ICF/IFE applications are rapidly expanding. Significant progress has been made in the technology development based on rapid fuel layering inside moving free-standing targets (FST) which is referred to as the FST layering method. This paper presents our new results obtained in this area and describes technologically elegant solutions towards demonstrating a credible pathway for mass production of IFE cryogenic targets

Tracking 20 years of compound-to-target output from literature and patents.

Directory of Open Access Journals (Sweden)

Christopher Southan

Full Text Available The statistics of drug development output and declining yield of approved medicines has been the subject of many recent reviews. However, assessing research productivity that feeds development is more difficult. Here we utilise an extensive database of structure-activity relationships extracted from papers and patents. We have used this database to analyse published compounds cumulatively linked to nearly 4000 protein target identifiers from multiple species over the last 20 years. The compound output increases up to 2005 followed by a decline that parallels a fall in pharmaceutical patenting. Counts of protein targets have plateaued but not fallen. We extended these results by exploring compounds and targets for one large pharmaceutical company. In addition, we examined collective time course data for six individual protease targets, including average molecular weight of the compounds. We also tracked the PubMed profile of these targets to detect signals related to changes in compound output. Our results show that research compound output had decreased 35% by 2012. The major causative factor is likely to be a contraction in the global research base due to mergers and acquisitions across the pharmaceutical industry. However, this does not rule out an increasing stringency of compound quality filtration and/or patenting cost control. The number of proteins mapped to compounds on a yearly basis shows less decline, indicating the cumulative published target capacity of global research is being sustained in the region of 300 proteins for large companies. The tracking of six individual targets shows uniquely detailed patterns not discernible from cumulative snapshots. These are interpretable in terms of events related to validation and de-risking of targets that produce detectable follow-on surges in patenting. Further analysis of the type we present here can provide unique insights into the process of drug discovery based on the data it actually

Greenhouse gas emission trends and projections in Europe 2012. Tracking progress towards Kyoto and 2020 targets

Energy Technology Data Exchange (ETDEWEB)

Gores, S.; Scheffler, M.; Graichen, V. [Oeko-Institut (Oeko), Freiburg (Germany)] [and others

2012-10-15

At the end of 2011, almost all European countries were on track towards their Kyoto targets for 2008-2012. The EU-15 also remained on track to achieve its Kyoto target. Italy, however, was not on track. Spain plans to acquire a large quantity of Kyoto units through the KP's flexible mechanisms to achieve its target. With emission caps already set for the economic sectors under the EU Emissions Trading Scheme (EU ETS), emissions reductions during 2012 in the sectors outside the EU ETS together with reductions by carbon sinks will set the frame for how many Kyoto units Member States need to acquire to reach their individual targets. Hence, both the development and delivery of adequate plans to acquire enough Kyoto credits is becoming increasingly important. ETS emissions from 2008 to 2011 were on average 5 % below these caps, which results in an oversupply of allowances. The EU ETS is undergoing important changes in view of the third trading phase from 2013 to 2020. Most EU Member States project that in 2020, their emissions outside the EU ETS will be lower than their national targets set under the Climate and Energy Package. However, further efforts will be necessary to achieve longer term reductions. (Author)

Final Report for Bio-Inspired Approaches to Moving-Target Defense Strategies

Energy Technology Data Exchange (ETDEWEB)

Fink, Glenn A.; Oehmen, Christopher S.

2012-09-01

This report records the work and contributions of the NITRD-funded Bio-Inspired Approaches to Moving-Target Defense Strategies project performed by Pacific Northwest National Laboratory under the technical guidance of the National Security Agency’s R6 division. The project has incorporated a number of bio-inspired cyber defensive technologies within an elastic framework provided by the Digital Ants. This project has created the first scalable, real-world prototype of the Digital Ants Framework (DAF)[11] and integrated five technologies into this flexible, decentralized framework: (1) Ant-Based Cyber Defense (ABCD), (2) Behavioral Indicators, (3) Bioinformatic Clas- sification, (4) Moving-Target Reconfiguration, and (5) Ambient Collaboration. The DAF can be used operationally to decentralize many such data intensive applications that normally rely on collection of large amounts of data in a central repository. In this work, we have shown how these component applications may be decentralized and may perform analysis at the edge. Operationally, this will enable analytics to scale far beyond current limitations while not suffering from the bandwidth or computational limitations of centralized analysis. This effort has advanced the R6 Cyber Security research program to secure digital infrastructures by developing a dynamic means to adaptively defend complex cyber systems. We hope that this work will benefit both our client’s efforts in system behavior modeling and cyber security to the overall benefit of the nation.

Stimulus selection and tracking during urination: autoshaping directed behavior with toilet targets.

Science.gov (United States)

Siegel, R K

1977-01-01

A simple procedure is described for investigating stimuli selected as targets during urination in the commode. Ten normal males preferred a floating target that could be tracked to a series of stationary targets. This technique was used to bring misdirected urinations in a severely retarded male under rapid stimulus control of a floating target in the commode. The float stimulus was also evaluated with nine institionalized, moderately retarded males and results indicated rapid autoshaping of directed urination without the use of verbal instructions or conventional toilet training. The technique can be applied in training children to control misdirected urinations in institution for the retarded, in psychiatric wards with regressed populations, and in certain male school dormitories. PMID:885828

Inertial fusion energy target injection, tracking, and beam pointing

International Nuclear Information System (INIS)

Petzoldt, R.W.

1995-01-01

Several cryogenic targets must be injected each second into a reaction chamber. Required target speed is about 100 m/s. Required accuracy of the driver beams on target is a few hundred micrometers. Fuel strength is calculated to allow acceleration in excess of 10,000 m/s 2 if the fuel temperature is less than 17 K. A 0.1 μm thick dual membrane will allow nearly 2,000 m/s 2 acceleration. Acceleration is gradually increased and decreased over a few membrane oscillation periods (a few ms), to avoid added stress from vibrations which could otherwise cause a factor of two decrease in allowed acceleration. Movable shielding allows multiple targets to be in flight toward the reaction chamber at once while minimizing neutron heating of subsequent targets. The use of multiple injectors is recommended for redundancy which increases availability and allows a higher pulse rate. Gas gun, rail gun, induction accelerator, and electrostatic accelerator target injection devices are studied, and compared. A gas gun is the preferred device for indirect-drive targets due to its simplicity and proven reliability. With the gas gun, the amount of gas required for each target (about 10 to 100 mg) is acceptable. A revolver loading mechanism is recommended with a cam operated poppet valve to control the gas flow. Cutting vents near the muzzle of the gas gun barrel is recommended to improve accuracy and aid gas pumping. If a railgun is used, we recommend an externally applied magnetic field to reduce required current by an order of magnitude. Optical target tracking is recommended. Up/down counters are suggested to predict target arrival time. Target steering is shown to be feasible and would avoid the need to actively point the beams. Calculations show that induced tumble from electrostatically steering the target is not excessive

Acquisition, tracking, and pointing III; Proceedings of the Meeting, Orlando, FL, Mar. 27-29, 1989

Science.gov (United States)

Gowrinathan, Sankaran

1989-09-01

The present conference on components and sensors, image processing algorithms, and astronomical applications for pointing and tracking gives attention to a CCD daylight stellar sensor, an optical coordinate transfer assembly for precision boresight applications, a grating carousel mechanism for the HST high resolution spectrograph, an IR antiship-seeker simulator, line-of-sight stabilization using image motion compensation, the effects of illumination beam jitter on photodetection statistics, and the enhancement of armored vehicle fire control performance. Also discussed are active angular tracking with a photon-bucket, moving target estimation with autodyne detection, multiresolution object detection and segmentation, a beacon tracker and point-ahead system for optical communications, a precision-pointing mechanism for intersatellite optical communication, high-precision lunar tracking for laser ranging, multimirror beam control, and fundamental limits in the resolution of double-star targets.

Two-dimensional tracking of a motile micro-organism allowing high-resolution observation with various imaging techniques

International Nuclear Information System (INIS)

Oku, H.; Ogawa, N.; Ishikawa, M.; Hashimoto, K.

2005-01-01

In this article, a micro-organism tracking system using a high-speed vision system is reported. This system two dimensionally tracks a freely swimming micro-organism within the field of an optical microscope by moving a chamber of target micro-organisms based on high-speed visual feedback. The system we developed could track a paramecium using various imaging techniques, including bright-field illumination, dark-field illumination, and differential interference contrast, at magnifications of 5 times and 20 times. A maximum tracking duration of 300 s was demonstrated. Also, the system could track an object with a velocity of up to 35 000 μm/s (175 diameters/s), which is significantly faster than swimming micro-organisms

Chromatic Shadow Detection and Tracking for Moving Foreground Segmentation

DEFF Research Database (Denmark)

Huerta, Ivan; Holte, Michael Boelstoft; Moeslund, Thomas B.

2015-01-01

are usually detected as part of moving objects, thus affecting the performance of the final detection. In this paper we address the detection of both penumbra and umbra shadow regions. First, a novel bottom-up approach is presented based on gradient and colour models, which successfully discriminates between...... chromatic moving cast shadow regions and those regions detected as moving objects. In essence, those regions corresponding to potential shadows are detected based on edge partitioning and colour statistics. Subsequently (i) temporal similarities between textures and (ii) spatial similarities between...

The research of radar target tracking observed information linear filter method

Science.gov (United States)

Chen, Zheng; Zhao, Xuanzhi; Zhang, Wen

2018-05-01

Aiming at the problems of low precision or even precision divergent is caused by nonlinear observation equation in radar target tracking, a new filtering algorithm is proposed in this paper. In this algorithm, local linearization is carried out on the observed data of the distance and angle respectively. Then the kalman filter is performed on the linearized data. After getting filtered data, a mapping operation will provide the posteriori estimation of target state. A large number of simulation results show that this algorithm can solve above problems effectively, and performance is better than the traditional filtering algorithm for nonlinear dynamic systems.

Efficient DoA Tracking of Variable Number of Moving Stochastic EM Sources in Far-Field Using PNN-MLP Model

Directory of Open Access Journals (Sweden)

Zoran Stanković

2015-01-01

Full Text Available An efficient neural network-based approach for tracking of variable number of moving electromagnetic (EM sources in far-field is proposed in the paper. Electromagnetic sources considered here are of stochastic radiation nature, mutually uncorrelated, and at arbitrary angular distance. The neural network model is based on combination of probabilistic neural network (PNN and the Multilayer Perceptron (MLP networks and it performs real-time calculations in two stages, determining at first the number of moving sources present in an observed space sector in specific moments in time and then calculating their angular positions in azimuth plane. Once successfully trained, the neural network model is capable of performing an accurate and efficient direction of arrival (DoA estimation within the training boundaries which is illustrated on the appropriate example.

Millimeter wave radar system on a rotating platform for combined search and track functionality with SAR imaging

Science.gov (United States)

Aulenbacher, Uwe; Rech, Klaus; Sedlmeier, Johannes; Pratisto, Hans; Wellig, Peter

2014-10-01

Ground based millimeter wave radar sensors offer the potential for a weather-independent automatic ground surveillance at day and night, e.g. for camp protection applications. The basic principle and the experimental verification of a radar system concept is described, which by means of an extreme off-axis positioning of the antenna(s) combines azimuthal mechanical beam steering with the formation of a circular-arc shaped synthetic aperture (SA). In automatic ground surveillance the function of search and detection of moving ground targets is performed by means of the conventional mechanical scan mode. The rotated antenna structure designed as a small array with two or more RX antenna elements with simultaneous receiver chains allows to instantaneous track multiple moving targets (monopulse principle). The simultaneously operated SAR mode yields areal images of the distribution of stationary scatterers. For ground surveillance application this SAR mode is best suited for identifying possible threats by means of change detection. The feasibility of this concept was tested by means of an experimental radar system comprising of a 94 GHz (W band) FM-CW module with 1 GHz bandwidth and two RX antennas with parallel receiver channels, placed off-axis at a rotating platform. SAR mode and search/track mode were tested during an outdoor measurement campaign. The scenery of two persons walking along a road and partially through forest served as test for the capability to track multiple moving targets. For SAR mode verification an image of the area composed of roads, grassland, woodland and several man-made objects was reconstructed from the measured data.

Target-Searching on Percolation

International Nuclear Information System (INIS)

Yang Shijie

2005-01-01

We study target-searching processes on a percolation, on which a hunter tracks a target by smelling odors it emits. The odor intensity is supposed to be inversely proportional to the distance it propagates. The Monte Carlo simulation is performed on a 2-dimensional bond-percolation above the threshold. Having no idea of the location of the target, the hunter determines its moves only by random attempts in each direction. For lager percolation connectivity p ∼> 0.90, it reveals a scaling law for the searching time versus the distance to the position of the target. The scaling exponent is dependent on the sensitivity of the hunter. For smaller p, the scaling law is broken and the probability of finding out the target significantly reduces. The hunter seems trapped in the cluster of the percolation and can hardly reach the goal.

Interacting Multiple Model (IMM Fifth-Degree Spherical Simplex-Radial Cubature Kalman Filter for Maneuvering Target Tracking

Directory of Open Access Journals (Sweden)

Hua Liu

2017-06-01

Full Text Available For improving the tracking accuracy and model switching speed of maneuvering target tracking in nonlinear systems, a new algorithm named the interacting multiple model fifth-degree spherical simplex-radial cubature Kalman filter (IMM5thSSRCKF is proposed in this paper. The new algorithm is a combination of the interacting multiple model (IMM filter and the fifth-degree spherical simplex-radial cubature Kalman filter (5thSSRCKF. The proposed algorithm makes use of Markov process to describe the switching probability among the models, and uses 5thSSRCKF to deal with the state estimation of each model. The 5thSSRCKF is an improved filter algorithm, which utilizes the fifth-degree spherical simplex-radial rule to improve the filtering accuracy. Finally, the tracking performance of the IMM5thSSRCKF is evaluated by simulation in a typical maneuvering target tracking scenario. Simulation results show that the proposed algorithm has better tracking performance and quicker model switching speed when disposing maneuver models compared with the interacting multiple model unscented Kalman filter (IMMUKF, the interacting multiple model cubature Kalman filter (IMMCKF and the interacting multiple model fifth-degree cubature Kalman filter (IMM5thCKF.

Interacting Multiple Model (IMM) Fifth-Degree Spherical Simplex-Radial Cubature Kalman Filter for Maneuvering Target Tracking.

Science.gov (United States)

Liu, Hua; Wu, Wen

2017-06-13

For improving the tracking accuracy and model switching speed of maneuvering target tracking in nonlinear systems, a new algorithm named the interacting multiple model fifth-degree spherical simplex-radial cubature Kalman filter (IMM5thSSRCKF) is proposed in this paper. The new algorithm is a combination of the interacting multiple model (IMM) filter and the fifth-degree spherical simplex-radial cubature Kalman filter (5thSSRCKF). The proposed algorithm makes use of Markov process to describe the switching probability among the models, and uses 5thSSRCKF to deal with the state estimation of each model. The 5thSSRCKF is an improved filter algorithm, which utilizes the fifth-degree spherical simplex-radial rule to improve the filtering accuracy. Finally, the tracking performance of the IMM5thSSRCKF is evaluated by simulation in a typical maneuvering target tracking scenario. Simulation results show that the proposed algorithm has better tracking performance and quicker model switching speed when disposing maneuver models compared with the interacting multiple model unscented Kalman filter (IMMUKF), the interacting multiple model cubature Kalman filter (IMMCKF) and the interacting multiple model fifth-degree cubature Kalman filter (IMM5thCKF).

INFLUENCE OF STOCHASTIC NOISE STATISTICS ON KALMAN FILTER PERFORMANCE BASED ON VIDEO TARGET TRACKING

Institute of Scientific and Technical Information of China (English)

Chen Ken; Napolitano; Zhang Yun; Li Dong

2010-01-01

The system stochastic noises involved in Kalman filtering are preconditioned on being ideally white and Gaussian distributed. In this research,efforts are exerted on exploring the influence of the noise statistics on Kalman filtering from the perspective of video target tracking quality. The correlation of tracking precision to both the process and measurement noise covariance is investigated; the signal-to-noise power density ratio is defined; the contribution of predicted states and measured outputs to Kalman filter behavior is discussed; the tracking precision relative sensitivity is derived and applied in this study case. The findings are expected to pave the way for future study on how the actual noise statistics deviating from the assumed ones impacts on the Kalman filter optimality and degradation in the application of video tracking.

Transcom's next move: Improvements to DOE's transportation satellite tracking systems

International Nuclear Information System (INIS)

Harmon, L.H.; Harris, A.D. III; Driscoll, K.L.; Ellis, L.G.

1990-01-01

In today's society, the use of satellites is becoming the state-of-the-art method of tracking shipments. The United States Department of Energy (US DOE) has advanced technology in this area with its transportation tracking and communications system, TRANSCOM, which has been in operation for over one year. TRANSCOM was developed by DOE to monitor selected, unclassified shipments of radioactive materials across the country. With the latest technology in satellite communications, Long Range Navigation (Loran), and computer networks, TRANSCOM tracks shipments in near-real time, disseminates information on each shipment to authorized users of the system, and offers two-way communications between vehicle operators and TRANSCOM users anywhere in the country. TRANSCOM's successful tracking record, during fiscal year 1989, includes shipments of spent fuel, cesium, uranium hexafluoride, and demonstration shipments for the Waste Isolation Pilot Plant (WIPP). Plans for fiscal year 1990 include tracking additional shipments, implementing system enhancements designed to meet the users' needs, and continuing to research the technology of tracking systems so that TRANSCOM can provide its users with the newest technology available in satellite communications. 3 refs., 1 fig

Image and video based remote target localization and tracking on smartphones

Science.gov (United States)

Wang, Qia; Lobzhanidze, Alex; Jang, Hyun; Zeng, Wenjun; Shang, Yi; Yang, Jingyu

2012-06-01

Smartphones are becoming popular nowadays not only because of its communication functionality but also, more importantly, its powerful sensing and computing capability. In this paper, we describe a novel and accurate image and video based remote target localization and tracking system using the Android smartphones, by leveraging its built-in sensors such as camera, digital compass, GPS, etc. Even though many other distance estimation or localization devices are available, our all-in-one, easy-to-use localization and tracking system on low cost and commodity smartphones is first of its kind. Furthermore, smartphones' exclusive user-friendly interface has been effectively taken advantage of by our system to facilitate low complexity and high accuracy. Our experimental results show that our system works accurately and efficiently.

Automatically detect and track infrared small targets with kernel Fukunaga-Koontz transform and Kalman prediction

Science.gov (United States)

Liu, Ruiming; Liu, Erqi; Yang, Jie; Zeng, Yong; Wang, Fanglin; Cao, Yuan

2007-11-01

Fukunaga-Koontz transform (FKT), stemming from principal component analysis (PCA), is used in many pattern recognition and image-processing fields. It cannot capture the higher-order statistical property of natural images, so its detection performance is not satisfying. PCA has been extended into kernel PCA in order to capture the higher-order statistics. However, thus far there have been no researchers who have definitely proposed kernel FKT (KFKT) and researched its detection performance. For accurately detecting potential small targets from infrared images, we first extend FKT into KFKT to capture the higher-order statistical properties of images. Then a framework based on Kalman prediction and KFKT, which can automatically detect and track small targets, is developed. Results of experiments show that KFKT outperforms FKT and the proposed framework is competent to automatically detect and track infrared point targets.

Detection of Fast Moving and Accelerating Targets Compensating Range and Doppler Migration

Science.gov (United States)

2014-06-01

TR–2978 UNCLASSIFIED the chirp bandwidth is changed from pulse to pulse to realise the range migration com- pensation. Also, Dai et. al. [11] proposed...injected at different closing velocities and acceleration values . Figure 1(a) shows the range-Doppler map of a non-accelarating target moving at 100 knots...increase the noise floor. Hence, consideration must be given to establish a criteria for the combination processing to achieve a net SNR improvement for a

Catching moving targets: cancer stem cell hierarchies, therapy-resistance & considerations for clinical intervention.

LENUS (Irish Health Repository)

Gasch, Claudia

2017-01-01

It is widely believed that targeting the tumour-initiating cancer stem cell (CSC) component of malignancy has great therapeutic potential, particularly in therapy-resistant disease. However, despite concerted efforts, CSC-targeting strategies have not been efficiently translated to the clinic. This is partly due to our incomplete understanding of the mechanisms underlying CSC therapy-resistance. In particular, the relationship between therapy-resistance and the organisation of CSCs as Stem-Progenitor-Differentiated cell hierarchies has not been widely studied. In this review we argue that modern clinical strategies should appreciate that the CSC hierarchy is a dynamic target that contains sensitive and resistant components and expresses a collection of therapy-resisting mechanisms. We propose that the CSC hierarchy at primary presentation changes in response to clinical intervention, resulting in a recurrent malignancy that should be targeted differently. As such, addressing the hierarchical organisation of CSCs into our bench-side theory should expedite translation of CSC-targeting to bed-side practice. In conclusion, we discuss strategies through which we can catch these moving clinical targets to specifically compromise therapy-resistant disease.

Fast motion-including dose error reconstruction for VMAT with and without MLC tracking

DEFF Research Database (Denmark)

Ravkilde, Thomas; Keall, Paul J.; Grau, Cai

2014-01-01

of the algorithm for reconstruction of dose and motion-induced dose errors throughout the tracking and non-tracking beam deliveries was quantified. Doses were reconstructed with a mean dose difference relative to the measurements of -0.5% (5.5% standard deviation) for cumulative dose. More importantly, the root...... validate a simple model for fast motion-including dose error reconstruction applicable to intrafractional QA of MLC tracking treatments of moving targets. MLC tracking experiments were performed on a standard linear accelerator with prototype MLC tracking software guided by an electromagnetic transponder......-mean-square deviation between reconstructed and measured motion-induced 3%/3 mm γ failure rates (dose error) was 2.6%. The mean computation time for each calculation of dose and dose error was 295 ms. The motion-including dose reconstruction allows accurate temporal and spatial pinpointing of errors in absorbed dose...

Automatic Moving Object Segmentation for Freely Moving Cameras

Directory of Open Access Journals (Sweden)

Yanli Wan

2014-01-01

Full Text Available This paper proposes a new moving object segmentation algorithm for freely moving cameras which is very common for the outdoor surveillance system, the car build-in surveillance system, and the robot navigation system. A two-layer based affine transformation model optimization method is proposed for camera compensation purpose, where the outer layer iteration is used to filter the non-background feature points, and the inner layer iteration is used to estimate a refined affine model based on the RANSAC method. Then the feature points are classified into foreground and background according to the detected motion information. A geodesic based graph cut algorithm is then employed to extract the moving foreground based on the classified features. Unlike the existing global optimization or the long term feature point tracking based method, our algorithm only performs on two successive frames to segment the moving foreground, which makes it suitable for the online video processing applications. The experiment results demonstrate the effectiveness of our algorithm in both of the high accuracy and the fast speed.

Computationally Efficient DOA Tracking Algorithm in Monostatic MIMO Radar with Automatic Association

Directory of Open Access Journals (Sweden)

Huaxin Yu

2014-01-01

Full Text Available We consider the problem of tracking the direction of arrivals (DOA of multiple moving targets in monostatic multiple-input multiple-output (MIMO radar. A low-complexity DOA tracking algorithm in monostatic MIMO radar is proposed. The proposed algorithm obtains DOA estimation via the difference between previous and current covariance matrix of the reduced-dimension transformation signal, and it reduces the computational complexity and realizes automatic association in DOA tracking. Error analysis and Cramér-Rao lower bound (CRLB of DOA tracking are derived in the paper. The proposed algorithm not only can be regarded as an extension of array-signal-processing DOA tracking algorithm in (Zhang et al. (2008, but also is an improved version of the DOA tracking algorithm in (Zhang et al. (2008. Furthermore, the proposed algorithm has better DOA tracking performance than the DOA tracking algorithm in (Zhang et al. (2008. The simulation results demonstrate effectiveness of the proposed algorithm. Our work provides the technical support for the practical application of MIMO radar.

Optimal path planning for video-guided smart munitions via multitarget tracking

Science.gov (United States)

Borkowski, Jeffrey M.; Vasquez, Juan R.

2006-05-01

An advent in the development of smart munitions entails autonomously modifying target selection during flight in order to maximize the value of the target being destroyed. A unique guidance law can be constructed that exploits both attribute and kinematic data obtained from an onboard video sensor. An optimal path planning algorithm has been developed with the goals of obstacle avoidance and maximizing the value of the target impacted by the munition. Target identification and classification provides a basis for target value which is used in conjunction with multi-target tracks to determine an optimal waypoint for the munition. A dynamically feasible trajectory is computed to provide constraints on the waypoint selection. Results demonstrate the ability of the autonomous system to avoid moving obstacles and revise target selection in flight.

Infrared Small Moving Target Detection via Saliency Histogram and Geometrical Invariability

Directory of Open Access Journals (Sweden)

Minjie Wan

2017-06-01

Full Text Available In order to detect both bright and dark small moving targets effectively in infrared (IR video sequences, a saliency histogram and geometrical invariability based method is presented in this paper. First, a saliency map that roughly highlights the salient regions of the original image is obtained by tuning its amplitude spectrum in the frequency domain. Then, a saliency histogram is constructed by means of averaging the accumulated saliency value of each gray level in the map, through which bins corresponding to bright target and dark target are assigned with large values in the histogram. Next, single-frame detection of candidate targets is accomplished by a binarized segmentation using an adaptive threshold, and their centroid coordinates with sub-pixel accuracy are calculated through a connected components labeling method as well as a gray-weighted criterion. Finally, considering the motion characteristics in consecutive frames, an inter-frame false alarm suppression method based on geometrical invariability is developed to improve the precision rate further. Quantitative analyses demonstrate the detecting precision of this proposed approach can be up to 97% and Receiver Operating Characteristic (ROC curves further verify our method outperforms other state-of-the-arts methods in both detection rate and false alarm rate.

Vehicle track interaction safety standards

Science.gov (United States)

2014-04-02

Vehicle/Track Interaction (VTI) Safety Standards aim to : reduce the risk of derailments and other accidents attributable : to the dynamic interaction between moving vehicles and the : track over which they operate. On March 13, 2013, the Federal : R...

State-of-the-Art Mobile Intelligence: Enabling Robots to Move Like Humans by Estimating Mobility with Artificial Intelligence

Directory of Open Access Journals (Sweden)

Xue-Bo Jin

2018-03-01

Full Text Available Mobility is a significant robotic task. It is the most important function when robotics is applied to domains such as autonomous cars, home service robots, and autonomous underwater vehicles. Despite extensive research on this topic, robots still suffer from difficulties when moving in complex environments, especially in practical applications. Therefore, the ability to have enough intelligence while moving is a key issue for the success of robots. Researchers have proposed a variety of methods and algorithms, including navigation and tracking. To help readers swiftly understand the recent advances in methodology and algorithms for robot movement, we present this survey, which provides a detailed review of the existing methods of navigation and tracking. In particular, this survey features a relation-based architecture that enables readers to easily grasp the key points of mobile intelligence. We first outline the key problems in robot systems and point out the relationship among robotics, navigation, and tracking. We then illustrate navigation using different sensors and the fusion methods and detail the state estimation and tracking models for target maneuvering. Finally, we address several issues of deep learning as well as the mobile intelligence of robots as suggested future research topics. The contributions of this survey are threefold. First, we review the literature of navigation according to the applied sensors and fusion method. Second, we detail the models for target maneuvering and the existing tracking based on estimation, such as the Kalman filter and its series developed form, according to their model-construction mechanisms: linear, nonlinear, and non-Gaussian white noise. Third, we illustrate the artificial intelligence approach—especially deep learning methods—and discuss its combination with the estimation method.

Automatic Association of Chats and Video Tracks for Activity Learning and Recognition in Aerial Video Surveillance

Directory of Open Access Journals (Sweden)

Riad I. Hammoud

2014-10-01

Full Text Available We describe two advanced video analysis techniques, including video-indexed by voice annotations (VIVA and multi-media indexing and explorer (MINER. VIVA utilizes analyst call-outs (ACOs in the form of chat messages (voice-to-text to associate labels with video target tracks, to designate spatial-temporal activity boundaries and to augment video tracking in challenging scenarios. Challenging scenarios include low-resolution sensors, moving targets and target trajectories obscured by natural and man-made clutter. MINER includes: (1 a fusion of graphical track and text data using probabilistic methods; (2 an activity pattern learning framework to support querying an index of activities of interest (AOIs and targets of interest (TOIs by movement type and geolocation; and (3 a user interface to support streaming multi-intelligence data processing. We also present an activity pattern learning framework that uses the multi-source associated data as training to index a large archive of full-motion videos (FMV. VIVA and MINER examples are demonstrated for wide aerial/overhead imagery over common data sets affording an improvement in tracking from video data alone, leading to 84% detection with modest misdetection/false alarm results due to the complexity of the scenario. The novel use of ACOs and chat Sensors 2014, 14 19844 messages in video tracking paves the way for user interaction, correction and preparation of situation awareness reports.

Automatic association of chats and video tracks for activity learning and recognition in aerial video surveillance.

Science.gov (United States)

Hammoud, Riad I; Sahin, Cem S; Blasch, Erik P; Rhodes, Bradley J; Wang, Tao

2014-10-22

We describe two advanced video analysis techniques, including video-indexed by voice annotations (VIVA) and multi-media indexing and explorer (MINER). VIVA utilizes analyst call-outs (ACOs) in the form of chat messages (voice-to-text) to associate labels with video target tracks, to designate spatial-temporal activity boundaries and to augment video tracking in challenging scenarios. Challenging scenarios include low-resolution sensors, moving targets and target trajectories obscured by natural and man-made clutter. MINER includes: (1) a fusion of graphical track and text data using probabilistic methods; (2) an activity pattern learning framework to support querying an index of activities of interest (AOIs) and targets of interest (TOIs) by movement type and geolocation; and (3) a user interface to support streaming multi-intelligence data processing. We also present an activity pattern learning framework that uses the multi-source associated data as training to index a large archive of full-motion videos (FMV). VIVA and MINER examples are demonstrated for wide aerial/overhead imagery over common data sets affording an improvement in tracking from video data alone, leading to 84% detection with modest misdetection/false alarm results due to the complexity of the scenario. The novel use of ACOs and chat Sensors 2014, 14 19844 messages in video tracking paves the way for user interaction, correction and preparation of situation awareness reports.

Data association approaches in bearings-only multi-target tracking

Science.gov (United States)

Xu, Benlian; Wang, Zhiquan

2008-03-01

According to requirements of time computation complexity and correctness of data association of the multi-target tracking, two algorithms are suggested in this paper. The proposed Algorithm 1 is developed from the modified version of dual Simplex method, and it has the advantage of direct and explicit form of the optimal solution. The Algorithm 2 is based on the idea of Algorithm 1 and rotational sort method, it combines not only advantages of Algorithm 1, but also reduces the computational burden, whose complexity is only 1/ N times that of Algorithm 1. Finally, numerical analyses are carried out to evaluate the performance of the two data association algorithms.

Extending Track Analysis from Animals in the Lab to Moving Objects Anywhere

NARCIS (Netherlands)

Dommelen, W. van; Laar, P.J.L.J. van de; Noldus, L.P.J.J.

2013-01-01

In this chapter we compare two application domains in which the tracking of objects and the analysis of their movements are core activities, viz. animal tracking and vessel tracking. More specifically, we investigate whether EthoVision XT, a research tool for video tracking and analysis of the

Laminated track design for inductrack maglev systems

Science.gov (United States)

Post, Richard F.

2004-07-06

A magnet configuration comprising a pair of Halbach arrays magnetically and structurally connected together are positioned with respect to each other so that a first component of their fields substantially cancels at a first plane between them, and a second component of their fields substantially adds at this first plane. A track is located between the pair of Halbach arrays and a propulsion mechanism is provided for moving the pair of Halbach arrays along the track. When the pair of Halbach arrays move along the track and the track is not located at the first plane, a current is induced in the windings and a restoring force is exerted on the pair of Halbach arrays.

Human tracking in thermal images using adaptive particle filters with online random forest learning

Science.gov (United States)

Ko, Byoung Chul; Kwak, Joon-Young; Nam, Jae-Yeal

2013-11-01

This paper presents a fast and robust human tracking method to use in a moving long-wave infrared thermal camera under poor illumination with the existence of shadows and cluttered backgrounds. To improve the human tracking performance while minimizing the computation time, this study proposes an online learning of classifiers based on particle filters and combination of a local intensity distribution (LID) with oriented center-symmetric local binary patterns (OCS-LBP). Specifically, we design a real-time random forest (RF), which is the ensemble of decision trees for confidence estimation, and confidences of the RF are converted into a likelihood function of the target state. First, the target model is selected by the user and particles are sampled. Then, RFs are generated using the positive and negative examples with LID and OCS-LBP features by online learning. The learned RF classifiers are used to detect the most likely target position in the subsequent frame in the next stage. Then, the RFs are learned again by means of fast retraining with the tracked object and background appearance in the new frame. The proposed algorithm is successfully applied to various thermal videos as tests and its tracking performance is better than those of other methods.

Quantitative analysis of the improvement in omnidirectional maritime surveillance and tracking due to real-time image enhancement

Science.gov (United States)

de Villiers, Jason P.; Bachoo, Asheer K.; Nicolls, Fred C.; le Roux, Francois P. J.

2011-05-01

Tracking targets in a panoramic image is in many senses the inverse problem of tracking targets with a narrow field of view camera on a pan-tilt pedestal. In a narrow field of view camera tracking a moving target, the object is constant and the background is changing. A panoramic camera is able to model the entire scene, or background, and those areas it cannot model well are the potential targets and typically subtended far fewer pixels in the panoramic view compared to the narrow field of view. The outputs of an outward staring array of calibrated machine vision cameras are stitched into a single omnidirectional panorama and used to observe False Bay near Simon's Town, South Africa. A ground truth data-set was created by geo-aligning the camera array and placing a differential global position system receiver on a small target boat thus allowing its position in the array's field of view to be determined. Common tracking techniques including level-sets, Kalman filters and particle filters were implemented to run on the central processing unit of the tracking computer. Image enhancement techniques including multi-scale tone mapping, interpolated local histogram equalisation and several sharpening techniques were implemented on the graphics processing unit. An objective measurement of each tracking algorithm's robustness in the presence of sea-glint, low contrast visibility and sea clutter - such as white caps is performed on the raw recorded video data. These results are then compared to those obtained with the enhanced video data.

Glucose administration prior to a divided attention task improves tracking performance but not word recognition: evidence against differential memory enhancement?

Science.gov (United States)

Scholey, Andrew B; Sünram-Lea, Sandra I; Greer, Joanna; Elliott, Jade; Kennedy, David O

2009-01-01

The cognition-enhancing effects of glucose administration to humans have been well-documented; however, it remains unclear whether this effect preferentially targets episodic memory or other cognitive domains. The effect of glucose on the allocation of attentional resources during memory encoding was assessed using a sensitive dual-attention paradigm. One hundred and twenty volunteers (mean age 21.60, SD 4.89, 77 females) took part in this randomised, double-blind, placebo-controlled, parallel groups study where each consumed a 25-g glucose drink or a placebo. Half of the participants in each drink condition attempted to track a moving on-screen target during auditory word presentation. The distance between the cursor and the tracking target was used as an index of attentional cost during encoding. Effects of drink and tracking on recognition memory and drink on tracking performance were assessed. Self-rated appetite and mood were co-monitored. Co-performing the tracking task significantly impaired memory performance irrespective of drink condition. In the placebo-tracking condition, there was a cost to tracking manifest as greater deviation from target during and immediately following word presentation. Compared with placebo, the glucose drink significantly improved tracking performance during encoding. There were significant time-related changes in thirst and alertness ratings but these were not differentially affected by drink or tracking conditions. Tracking but not memory was enhanced by glucose. This finding suggests that, under certain task conditions, glucose administrations does not preferentially enhance memory performance. One mechanism through which glucose acts as a cognition enhancer is through allowing greater allocation of attentional resources.

Moving-window dynamic optimization: design of stimulation profiles for walking.

Science.gov (United States)

Dosen, Strahinja; Popović, Dejan B

2009-05-01

The overall goal of the research is to improve control for electrical stimulation-based assistance of walking in hemiplegic individuals. We present the simulation for generating offline input (sensors)-output (intensity of muscle stimulation) representation of walking that serves in synthesizing a rule-base for control of electrical stimulation for restoration of walking. The simulation uses new algorithm termed moving-window dynamic optimization (MWDO). The optimization criterion was to minimize the sum of the squares of tracking errors from desired trajectories with the penalty function on the total muscle efforts. The MWDO was developed in the MATLAB environment and tested using target trajectories characteristic for slow-to-normal walking recorded in healthy individual and a model with the parameters characterizing the potential hemiplegic user. The outputs of the simulation are piecewise constant intensities of electrical stimulation and trajectories generated when the calculated stimulation is applied to the model. We demonstrated the importance of this simulation by showing the outputs for healthy and hemiplegic individuals, using the same target trajectories. Results of the simulation show that the MWDO is an efficient tool for analyzing achievable trajectories and for determining the stimulation profiles that need to be delivered for good tracking.

Scanning mid-IR laser apparatus with eye tracking for refractive surgery

Science.gov (United States)

Telfair, William B.; Yoder, Paul R., Jr.; Bekker, Carsten; Hoffman, Hanna J.; Jensen, Eric F.

1999-06-01

A robust, real-time, dynamic eye tracker has been integrated with the short pulse mid-infrared laser scanning delivery system previously described. This system employs a Q- switched Nd:YAG laser pumped optical parametric oscillator operating at 2.94 micrometers. Previous ablation studies on human cadaver eyes and in-vivo cat eyes demonstrated very smooth ablations with extremely low damage levels similar to results with an excimer. A 4-month healing study with cats indicated no adverse healing effects. In order to treat human eyes, the tracker is required because the eyes move during the procedure due to both voluntary and involuntary motions such as breathing, heartbeat, drift, loss of fixation, saccades and microsaccades. Eye tracking techniques from the literature were compared. A limbus tracking system was best for this application. Temporal and spectral filtering techniques were implemented to reduce tracking errors, reject stray light, and increase signal to noise ratio. The expanded-capability system (IRVision AccuScan 2000 Laser System) has been tested in the lab on simulated eye targets, glass eyes, cadaver eyes, and live human subjects. Circular targets ranging from 10-mm to 14-mm diameter were successfully tracked. The tracker performed beyond expectations while the system performed myopic photorefractive keratectomy procedures on several legally blind human subjects.

Management of the interplay effect when using dynamic MLC sequences to treat moving targets

International Nuclear Information System (INIS)

Court, Laurence E.; Wagar, Matthew; Ionascu, Dan; Berbeco, Ross; Chin, Lee

2008-01-01

Interplay between organ motion and leaf motion has been shown to generally have a small dosimetric impact for most clinical intensity-modulated radiation therapy treatments. However, it has also been shown that for some MLC sequences there can be large daily variations in the delivered dose, depending on details of patient motion or the number of fractions. This study investigates guidelines for dynamic MLC sequences that will keep daily dose variations due to the interplay between organ motion and leaf motion within 10%. Dose distributions for a range of MLC separations (0.2-5.0 cm) and displacements between adjacent MLCs (0-1.5 cm) were exported from ECLIPSE to purpose-written software, which simulated the dose distribution delivered to a moving target. Target motion parallel and perpendicular to the MLC motion was investigated for a range of amplitudes (0.5-4.0 cm), periods (1.5-10 s), and MLC speeds (0.1-3.0 cm/s) with target motions modeled as sin 6 . Results were confirmed experimentally by measuring the dose delivered to an ion chamber array in a moving phantom for different MLC sequences. The simulation results were used to identify MLC sequences that kept dose variations within 10% compared to the dose delivered with no motion. The maximum allowable MLC speed, when target motion is parallel to the MLC motion, was found to be a simple function of target period and MLC separation. When the target motion is perpendicular to MLC motion, the maximum allowable MLC speed can be described as a function of MLC separation and the displacement of adjacent MLCs. These guidelines were successfully applied to two-dimensional motion, and a simple program was written to import MLC sequence files and evaluate whether the maximum daily dose discrepancy caused by the interplay effect will be larger than 10%. This software was experimentally evaluated, and found to conservatively predict whether a given MLC sequence could give large daily dose discrepancies

Spatio-temporal features for tracking and quadruped/biped discrimination

Science.gov (United States)

Rickman, Rick; Copsey, Keith; Bamber, David C.; Page, Scott F.

2012-05-01

Techniques such as SIFT and SURF facilitate efficient and robust image processing operations through the use of sparse and compact spatial feature descriptors and show much potential for defence and security applications. This paper considers the extension of such techniques to include information from the temporal domain, to improve utility in applications involving moving imagery within video data. In particular, the paper demonstrates how spatio-temporal descriptors can be used very effectively as the basis of a target tracking system and as target discriminators which can distinguish between bipeds and quadrupeds. Results using sequences of video imagery of walking humans and dogs are presented, and the relative merits of the approach are discussed.

Context effects on smooth pursuit and manual interception of a disappearing target.

Science.gov (United States)

Kreyenmeier, Philipp; Fooken, Jolande; Spering, Miriam

2017-07-01

In our natural environment, we interact with moving objects that are surrounded by richly textured, dynamic visual contexts. Yet most laboratory studies on vision and movement show visual objects in front of uniform gray backgrounds. Context effects on eye movements have been widely studied, but it is less well known how visual contexts affect hand movements. Here we ask whether eye and hand movements integrate motion signals from target and context similarly or differently, and whether context effects on eye and hand change over time. We developed a track-intercept task requiring participants to track the initial launch of a moving object ("ball") with smooth pursuit eye movements. The ball disappeared after a brief presentation, and participants had to intercept it in a designated "hit zone." In two experiments ( n = 18 human observers each), the ball was shown in front of a uniform or a textured background that either was stationary or moved along with the target. Eye and hand movement latencies and speeds were similarly affected by the visual context, but eye and hand interception (eye position at time of interception, and hand interception timing error) did not differ significantly between context conditions. Eye and hand interception timing errors were strongly correlated on a trial-by-trial basis across all context conditions, highlighting the close relation between these responses in manual interception tasks. Our results indicate that visual contexts similarly affect eye and hand movements but that these effects may be short-lasting, affecting movement trajectories more than movement end points. NEW & NOTEWORTHY In a novel track-intercept paradigm, human observers tracked a briefly shown object moving across a textured, dynamic context and intercepted it with their finger after it had disappeared. Context motion significantly affected eye and hand movement latency and speed, but not interception accuracy; eye and hand position at interception were

Search and Tracking of an Unknown Number of Targets by a Team of Autonomous Agents Utilizing Time-evolving Partition Classification

OpenAIRE

Wood, Jared Gregory

2011-01-01

The advancement of computing technology has enabled the practical development of intelligent autonomous systems. Intelligent autonomous systems can be used to perform difficult sensing tasks. One such sensing task is to search for and track targets over large geographic areas. Searching for and tracking targets over geographic areas has important applications. These applications include search and rescue, boarder patrol, and reconnaissance. Inherent in applications such as these is the need ...

MO-FG-BRD-02: Real-Time Imaging and Tracking Techniques for Intrafractional Motion Management: MV Tracking

Energy Technology Data Exchange (ETDEWEB)

Berbeco, R. [Brigham and Women’s Hospital and Dana-Farber Cancer Institute (United States)

2015-06-15

Intrafraction target motion is a prominent complicating factor in the accurate targeting of radiation within the body. Methods compensating for target motion during treatment, such as gating and dynamic tumor tracking, depend on the delineation of target location as a function of time during delivery. A variety of techniques for target localization have been explored and are under active development; these include beam-level imaging of radio-opaque fiducials, fiducial-less tracking of anatomical landmarks, tracking of electromagnetic transponders, optical imaging of correlated surrogates, and volumetric imaging within treatment delivery. The Joint Imaging and Therapy Symposium will provide an overview of the techniques for real-time imaging and tracking, with special focus on emerging modes of implementation across different modalities. In particular, the symposium will explore developments in 1) Beam-level kilovoltage X-ray imaging techniques, 2) EPID-based megavoltage X-ray tracking, 3) Dynamic tracking using electromagnetic transponders, and 4) MRI-based soft-tissue tracking during radiation delivery. Learning Objectives: Understand the fundamentals of real-time imaging and tracking techniques Learn about emerging techniques in the field of real-time tracking Distinguish between the advantages and disadvantages of different tracking modalities Understand the role of real-time tracking techniques within the clinical delivery work-flow.

MO-FG-BRD-04: Real-Time Imaging and Tracking Techniques for Intrafractional Motion Management: MR Tracking

Energy Technology Data Exchange (ETDEWEB)

Low, D. [University of California Los Angeles: Real-Time Imaging and Tracking Techniques for Intrafractional Motion Management: MR Tracking (United States)

2015-06-15

Intrafraction target motion is a prominent complicating factor in the accurate targeting of radiation within the body. Methods compensating for target motion during treatment, such as gating and dynamic tumor tracking, depend on the delineation of target location as a function of time during delivery. A variety of techniques for target localization have been explored and are under active development; these include beam-level imaging of radio-opaque fiducials, fiducial-less tracking of anatomical landmarks, tracking of electromagnetic transponders, optical imaging of correlated surrogates, and volumetric imaging within treatment delivery. The Joint Imaging and Therapy Symposium will provide an overview of the techniques for real-time imaging and tracking, with special focus on emerging modes of implementation across different modalities. In particular, the symposium will explore developments in 1) Beam-level kilovoltage X-ray imaging techniques, 2) EPID-based megavoltage X-ray tracking, 3) Dynamic tracking using electromagnetic transponders, and 4) MRI-based soft-tissue tracking during radiation delivery. Learning Objectives: Understand the fundamentals of real-time imaging and tracking techniques Learn about emerging techniques in the field of real-time tracking Distinguish between the advantages and disadvantages of different tracking modalities Understand the role of real-time tracking techniques within the clinical delivery work-flow.

MO-FG-BRD-03: Real-Time Imaging and Tracking Techniques for Intrafractional Motion Management: EM Tracking

Energy Technology Data Exchange (ETDEWEB)

Keall, P. [University of Sydney (Australia)

2015-06-15

Intrafraction target motion is a prominent complicating factor in the accurate targeting of radiation within the body. Methods compensating for target motion during treatment, such as gating and dynamic tumor tracking, depend on the delineation of target location as a function of time during delivery. A variety of techniques for target localization have been explored and are under active development; these include beam-level imaging of radio-opaque fiducials, fiducial-less tracking of anatomical landmarks, tracking of electromagnetic transponders, optical imaging of correlated surrogates, and volumetric imaging within treatment delivery. The Joint Imaging and Therapy Symposium will provide an overview of the techniques for real-time imaging and tracking, with special focus on emerging modes of implementation across different modalities. In particular, the symposium will explore developments in 1) Beam-level kilovoltage X-ray imaging techniques, 2) EPID-based megavoltage X-ray tracking, 3) Dynamic tracking using electromagnetic transponders, and 4) MRI-based soft-tissue tracking during radiation delivery. Learning Objectives: Understand the fundamentals of real-time imaging and tracking techniques Learn about emerging techniques in the field of real-time tracking Distinguish between the advantages and disadvantages of different tracking modalities Understand the role of real-time tracking techniques within the clinical delivery work-flow.

MO-FG-BRD-04: Real-Time Imaging and Tracking Techniques for Intrafractional Motion Management: MR Tracking

International Nuclear Information System (INIS)

Low, D.

2015-01-01

Intrafraction target motion is a prominent complicating factor in the accurate targeting of radiation within the body. Methods compensating for target motion during treatment, such as gating and dynamic tumor tracking, depend on the delineation of target location as a function of time during delivery. A variety of techniques for target localization have been explored and are under active development; these include beam-level imaging of radio-opaque fiducials, fiducial-less tracking of anatomical landmarks, tracking of electromagnetic transponders, optical imaging of correlated surrogates, and volumetric imaging within treatment delivery. The Joint Imaging and Therapy Symposium will provide an overview of the techniques for real-time imaging and tracking, with special focus on emerging modes of implementation across different modalities. In particular, the symposium will explore developments in 1) Beam-level kilovoltage X-ray imaging techniques, 2) EPID-based megavoltage X-ray tracking, 3) Dynamic tracking using electromagnetic transponders, and 4) MRI-based soft-tissue tracking during radiation delivery. Learning Objectives: Understand the fundamentals of real-time imaging and tracking techniques Learn about emerging techniques in the field of real-time tracking Distinguish between the advantages and disadvantages of different tracking modalities Understand the role of real-time tracking techniques within the clinical delivery work-flow

MO-FG-BRD-03: Real-Time Imaging and Tracking Techniques for Intrafractional Motion Management: EM Tracking

International Nuclear Information System (INIS)

Keall, P.

2015-01-01

Intrafraction target motion is a prominent complicating factor in the accurate targeting of radiation within the body. Methods compensating for target motion during treatment, such as gating and dynamic tumor tracking, depend on the delineation of target location as a function of time during delivery. A variety of techniques for target localization have been explored and are under active development; these include beam-level imaging of radio-opaque fiducials, fiducial-less tracking of anatomical landmarks, tracking of electromagnetic transponders, optical imaging of correlated surrogates, and volumetric imaging within treatment delivery. The Joint Imaging and Therapy Symposium will provide an overview of the techniques for real-time imaging and tracking, with special focus on emerging modes of implementation across different modalities. In particular, the symposium will explore developments in 1) Beam-level kilovoltage X-ray imaging techniques, 2) EPID-based megavoltage X-ray tracking, 3) Dynamic tracking using electromagnetic transponders, and 4) MRI-based soft-tissue tracking during radiation delivery. Learning Objectives: Understand the fundamentals of real-time imaging and tracking techniques Learn about emerging techniques in the field of real-time tracking Distinguish between the advantages and disadvantages of different tracking modalities Understand the role of real-time tracking techniques within the clinical delivery work-flow

MO-FG-BRD-02: Real-Time Imaging and Tracking Techniques for Intrafractional Motion Management: MV Tracking

International Nuclear Information System (INIS)

Berbeco, R.

2015-01-01

Intrafraction target motion is a prominent complicating factor in the accurate targeting of radiation within the body. Methods compensating for target motion during treatment, such as gating and dynamic tumor tracking, depend on the delineation of target location as a function of time during delivery. A variety of techniques for target localization have been explored and are under active development; these include beam-level imaging of radio-opaque fiducials, fiducial-less tracking of anatomical landmarks, tracking of electromagnetic transponders, optical imaging of correlated surrogates, and volumetric imaging within treatment delivery. The Joint Imaging and Therapy Symposium will provide an overview of the techniques for real-time imaging and tracking, with special focus on emerging modes of implementation across different modalities. In particular, the symposium will explore developments in 1) Beam-level kilovoltage X-ray imaging techniques, 2) EPID-based megavoltage X-ray tracking, 3) Dynamic tracking using electromagnetic transponders, and 4) MRI-based soft-tissue tracking during radiation delivery. Learning Objectives: Understand the fundamentals of real-time imaging and tracking techniques Learn about emerging techniques in the field of real-time tracking Distinguish between the advantages and disadvantages of different tracking modalities Understand the role of real-time tracking techniques within the clinical delivery work-flow

A robotic approach to 4D real-time tumor tracking for radiotherapy

International Nuclear Information System (INIS)

Buzurovic, I; Yu, Y; Huang, K; Podder, T K

2011-01-01

Respiratory and cardiac motions induce displacement and deformation of the tumor volumes in various internal organs. To accommodate this undesired movement and other errors, physicians incorporate a large margin around the tumor to delineate the planning target volume, so that the clinical target volume receives the prescribed radiation dose under any scenario. Consequently, a large volume of healthy tissue is irradiated and sometimes it is difficult to spare critical organs adjacent to the tumor. In this study we have proposed a novel approach to the 4D active tracking and dynamic delivery incorporating the tumor motion prediction technique. This method has been applied to the two commercially available robotic treatment couches. The proposed algorithm can predict the tumor position and the robotic systems are able to continuously track the tumor during radiation dose delivery. Therefore a precise dose is given to a moving target while the dose to the nearby critical organs is reduced to improve the patient treatment outcome. The efficacy of the proposed method has been investigated by extensive computer simulation. The tumor tracking method is simulated for two couches: HexaPOD robotic couch and ELEKTA Precise Table. The comparison results have been presented in this paper. In order to assess the clinical significance, dosimetric effects of the proposed method have been analyzed.

Rapid Automated Target Segmentation and Tracking on 4D Data without Initial Contours

International Nuclear Information System (INIS)

Chebrolu, V.V.; Chebrolu, V.V.; Saenz, D.; Tewatia, D.; Paliwal, B.R.; Chebrolu, V.V.; Saenz, D.; Paliwal, B.R.; Sethares, W.A.; Cannon, G.

2014-01-01

To achieve rapid automated delineation of gross target volume (GTV) and to quantify changes in volume/position of the target for radiotherapy planning using four-dimensional (4D) CT. Methods and Materials. Novel morphological processing and successive localization (MPSL) algorithms were designed and implemented for achieving auto segmentation. Contours automatically generated using MPSL method were compared with contours generated using state-of-the-art deformable registration methods (using Elastix © and MIMV ista software). Metrics such as the Dice similarity coefficient, sensitivity, and positive predictive value (PPV) were analyzed. The target motion tracked using the centroid of the GTV estimated using MPSL method was compared with motion tracked using deformable registration methods. Results. MPSL algorithm segmented the GTV in 4DCT images in 27.0 ±11.1 seconds per phase ( 512 ×512 resolution) as compared to 142.3±11.3 seconds per phase for deformable registration based methods in 9 cases. Dice coefficients between MPSL generated GTV contours and manual contours (considered as ground-truth) were 0.865 ± 0.037. In comparison, the Dice coefficients between ground-truth and contours generated using deformable registration based methods were 0.909 ± 0.051. Conclusions. The MPSL method achieved similar segmentation accuracy as compared to state-of-the-art deformable registration based segmentation methods, but with significant reduction in time required for GTV segmentation.

Rapid Automated Target Segmentation and Tracking on 4D Data without Initial Contours

Directory of Open Access Journals (Sweden)

Venkata V. Chebrolu

2014-01-01

Full Text Available Purpose. To achieve rapid automated delineation of gross target volume (GTV and to quantify changes in volume/position of the target for radiotherapy planning using four-dimensional (4D CT. Methods and Materials. Novel morphological processing and successive localization (MPSL algorithms were designed and implemented for achieving autosegmentation. Contours automatically generated using MPSL method were compared with contours generated using state-of-the-art deformable registration methods (using Elastix© and MIMVista software. Metrics such as the Dice similarity coefficient, sensitivity, and positive predictive value (PPV were analyzed. The target motion tracked using the centroid of the GTV estimated using MPSL method was compared with motion tracked using deformable registration methods. Results. MPSL algorithm segmented the GTV in 4DCT images in 27.0±11.1 seconds per phase (512×512 resolution as compared to 142.3±11.3 seconds per phase for deformable registration based methods in 9 cases. Dice coefficients between MPSL generated GTV contours and manual contours (considered as ground-truth were 0.865±0.037. In comparison, the Dice coefficients between ground-truth and contours generated using deformable registration based methods were 0.909 ± 0.051. Conclusions. The MPSL method achieved similar segmentation accuracy as compared to state-of-the-art deformable registration based segmentation methods, but with significant reduction in time required for GTV segmentation.

Rapid Automated Target Segmentation and Tracking on 4D Data without Initial Contours.

Science.gov (United States)

Chebrolu, Venkata V; Saenz, Daniel; Tewatia, Dinesh; Sethares, William A; Cannon, George; Paliwal, Bhudatt R

2014-01-01

Purpose. To achieve rapid automated delineation of gross target volume (GTV) and to quantify changes in volume/position of the target for radiotherapy planning using four-dimensional (4D) CT. Methods and Materials. Novel morphological processing and successive localization (MPSL) algorithms were designed and implemented for achieving autosegmentation. Contours automatically generated using MPSL method were compared with contours generated using state-of-the-art deformable registration methods (using Elastix© and MIMVista software). Metrics such as the Dice similarity coefficient, sensitivity, and positive predictive value (PPV) were analyzed. The target motion tracked using the centroid of the GTV estimated using MPSL method was compared with motion tracked using deformable registration methods. Results. MPSL algorithm segmented the GTV in 4DCT images in 27.0 ± 11.1 seconds per phase (512 × 512 resolution) as compared to 142.3 ± 11.3 seconds per phase for deformable registration based methods in 9 cases. Dice coefficients between MPSL generated GTV contours and manual contours (considered as ground-truth) were 0.865 ± 0.037. In comparison, the Dice coefficients between ground-truth and contours generated using deformable registration based methods were 0.909 ± 0.051. Conclusions. The MPSL method achieved similar segmentation accuracy as compared to state-of-the-art deformable registration based segmentation methods, but with significant reduction in time required for GTV segmentation.

Graph Model Based Indoor Tracking

DEFF Research Database (Denmark)

Jensen, Christian Søndergaard; Lu, Hua; Yang, Bin

2009-01-01

The tracking of the locations of moving objects in large indoor spaces is important, as it enables a range of applications related to, e.g., security and indoor navigation and guidance. This paper presents a graph model based approach to indoor tracking that offers a uniform data management...

A low-complexity interacting multiple model filter for maneuvering target tracking

KAUST Repository

Khalid, Syed Safwan; Abrar, Shafayat

2017-01-01

In this work, we address the target tracking problem for a coordinate-decoupled Markovian jump-mean-acceleration based maneuvering mobility model. A novel low-complexity alternative to the conventional interacting multiple model (IMM) filter is proposed for this class of mobility models. The proposed tracking algorithm utilizes a bank of interacting filters where the interactions are limited to the mixing of the mean estimates, and it exploits a fixed off-line computed Kalman gain matrix for the entire filter bank. Consequently, the proposed filter does not require matrix inversions during on-line operation which significantly reduces its complexity. Simulation results show that the performance of the low-complexity proposed scheme remains comparable to that of the traditional (highly-complex) IMM filter. Furthermore, we derive analytical expressions that iteratively evaluate the transient and steady-state performance of the proposed scheme, and establish the conditions that ensure the stability of the proposed filter. The analytical findings are in close accordance with the simulated results.

A low-complexity interacting multiple model filter for maneuvering target tracking

KAUST Repository

Khalid, Syed Safwan

2017-01-22

In this work, we address the target tracking problem for a coordinate-decoupled Markovian jump-mean-acceleration based maneuvering mobility model. A novel low-complexity alternative to the conventional interacting multiple model (IMM) filter is proposed for this class of mobility models. The proposed tracking algorithm utilizes a bank of interacting filters where the interactions are limited to the mixing of the mean estimates, and it exploits a fixed off-line computed Kalman gain matrix for the entire filter bank. Consequently, the proposed filter does not require matrix inversions during on-line operation which significantly reduces its complexity. Simulation results show that the performance of the low-complexity proposed scheme remains comparable to that of the traditional (highly-complex) IMM filter. Furthermore, we derive analytical expressions that iteratively evaluate the transient and steady-state performance of the proposed scheme, and establish the conditions that ensure the stability of the proposed filter. The analytical findings are in close accordance with the simulated results.

Surrounding Moving Obstacle Detection for Autonomous Driving Using Stereo Vision

Directory of Open Access Journals (Sweden)

Hao Sun

2013-06-01

Full Text Available Detection and tracking surrounding moving obstacles such as vehicles and pedestrians are crucial for the safety of mobile robotics and autonomous vehicles. This is especially the case in urban driving scenarios. This paper presents a novel framework for surrounding moving obstacles detection using binocular stereo vision. The contributions of our work are threefold. Firstly, a multiview feature matching scheme is presented for simultaneous stereo correspondence and motion correspondence searching. Secondly, the multiview geometry constraint derived from the relative camera positions in pairs of consecutive stereo views is exploited for surrounding moving obstacles detection. Thirdly, an adaptive particle filter is proposed for tracking of multiple moving obstacles in surrounding areas. Experimental results from real-world driving sequences demonstrate the effectiveness and robustness of the proposed framework.

Advanced cell therapies: targeting, tracking and actuation of cells with magnetic particles.

Science.gov (United States)

Connell, John J; Patrick, P Stephen; Yu, Yichao; Lythgoe, Mark F; Kalber, Tammy L

2015-01-01

Regenerative medicine would greatly benefit from a new platform technology that enabled measurable, controllable and targeting of stem cells to a site of disease or injury in the body. Superparamagnetic iron-oxide nanoparticles offer attractive possibilities in biomedicine and can be incorporated into cells, affording a safe and reliable means of tagging. This review describes three current and emerging methods to enhance regenerative medicine using magnetic particles to guide therapeutic cells to a target organ; track the cells using MRI and assess their spatial localization with high precision and influence the behavior of the cell using magnetic actuation. This approach is complementary to the systemic injection of cell therapies, thus expanding the horizon of stem cell therapeutics.

Detection of Moving Targets Based on Doppler Spectrum Analysis Technique for Passive Coherent Radar

Directory of Open Access Journals (Sweden)

Zhao Yao-dong

2013-06-01

Full Text Available A novel method of moving targets detection taking Doppler spectrum analysis technique for Passive Coherent Radar (PCR is provided. After dividing the receiving signals into segments as pulse series, it utilizes the technique of pulse compress and Doppler processing to detect and locate the targets. Based on the algorithm for Pulse-Doppler (PD radar, the equipollence between continuous and pulsed wave in match filtering is proved and details of this method are introduced. To compare it with the traditional method of Cross-Ambiguity Function (CAF calculation, the relationship and mathematical modes of them are analyzed, with some suggestions on parameters choosing. With little influence to the gain of targets, the method can greatly promote the processing efficiency. The validity of the proposed method is demonstrated by offline processing real collected data sets and simulation results.

Performance limits for exo-clutter Ground Moving Target Indicator (GMTI) radar.

Energy Technology Data Exchange (ETDEWEB)

Doerry, Armin Walter

2010-09-01

The performance of a Ground Moving Target Indicator (GMTI) radar system depends on a variety of factors, many which are interdependent in some manner. It is often difficult to 'get your arms around' the problem of ascertaining achievable performance limits, and yet those limits exist and are dictated by physics. This report identifies and explores those limits, and how they depend on hardware system parameters and environmental conditions. Ultimately, this leads to a characterization of parameters that offer optimum performance for the overall GMTI radar system. While the information herein is not new to the literature, its collection into a single report hopes to offer some value in reducing the 'seek time'.

Large scale tracking algorithms

Energy Technology Data Exchange (ETDEWEB)

Hansen, Ross L. [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Love, Joshua Alan [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Melgaard, David Kennett [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Karelitz, David B. [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Pitts, Todd Alan [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Zollweg, Joshua David [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Anderson, Dylan Z. [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Nandy, Prabal [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Whitlow, Gary L. [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Bender, Daniel A. [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Byrne, Raymond Harry [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States)

2015-01-01

Low signal-to-noise data processing algorithms for improved detection, tracking, discrimination and situational threat assessment are a key research challenge. As sensor technologies progress, the number of pixels will increase signi cantly. This will result in increased resolution, which could improve object discrimination, but unfortunately, will also result in a significant increase in the number of potential targets to track. Many tracking techniques, like multi-hypothesis trackers, suffer from a combinatorial explosion as the number of potential targets increase. As the resolution increases, the phenomenology applied towards detection algorithms also changes. For low resolution sensors, "blob" tracking is the norm. For higher resolution data, additional information may be employed in the detection and classfication steps. The most challenging scenarios are those where the targets cannot be fully resolved, yet must be tracked and distinguished for neighboring closely spaced objects. Tracking vehicles in an urban environment is an example of such a challenging scenario. This report evaluates several potential tracking algorithms for large-scale tracking in an urban environment.

Estimation of direction of arrival of a moving target using subspace based approaches

Science.gov (United States)

Ghosh, Ripul; Das, Utpal; Akula, Aparna; Kumar, Satish; Sardana, H. K.

2016-05-01

In this work, array processing techniques based on subspace decomposition of signal have been evaluated for estimation of direction of arrival of moving targets using acoustic signatures. Three subspace based approaches - Incoherent Wideband Multiple Signal Classification (IWM), Least Square-Estimation of Signal Parameters via Rotation Invariance Techniques (LS-ESPRIT) and Total Least Square- ESPIRIT (TLS-ESPRIT) are considered. Their performance is compared with conventional time delay estimation (TDE) approaches such as Generalized Cross Correlation (GCC) and Average Square Difference Function (ASDF). Performance evaluation has been conducted on experimentally generated data consisting of acoustic signatures of four different types of civilian vehicles moving in defined geometrical trajectories. Mean absolute error and standard deviation of the DOA estimates w.r.t. ground truth are used as performance evaluation metrics. Lower statistical values of mean error confirm the superiority of subspace based approaches over TDE based techniques. Amongst the compared methods, LS-ESPRIT indicated better performance.

Effects of wrist tendon vibration on arm tracking in people poststroke.

Science.gov (United States)

Conrad, Megan O; Scheidt, Robert A; Schmit, Brian D

2011-09-01

The goal of this study was to evaluate the influence of wrist tendon vibration on a multijoint elbow/shoulder tracking task. We hypothesized that tendon vibration applied at the wrist musculature would improve upper arm tracking performance in chronic stroke survivors through increased, Ia-afferent feedback to the central nervous system (CNS). To test this hypothesis, 10 chronic stroke and 5 neurologically intact subjects grasped the handle of a planar robot as they tracked a target through a horizontal figure-8 pattern. A total of 36 trials were completed by each subject. During the middle trials, 70-Hz tendon vibration was applied at the wrist flexor tendons. Position, velocity, and electromyography data were evaluated to compare the quality of arm movements before, during, and after trials with concurrent vibration. Despite tracking a target that moved at a constant velocity, hand trajectories appeared to be segmented, displaying alternating intervals of acceleration and deceleration. Segments were identifiable in tangential velocity data as single-peaked, bell-shaped speed pulses. When tendon vibration was applied at the wrist musculature, stroke subjects experienced improved tracking performance in that hand path lengths and peak speed variability decreased, whereas movement smoothness increased. These performance improvements were accompanied by decreases in the muscle activity during movement. Possible mechanisms behind improved movement control in response to tendon vibration may include improved sensorimotor integration or improved cortical modulation of spinal reflex activity.

30 CFR 75.1003-2 - Requirements for movement of off-track mining equipment in areas of active workings where...

Science.gov (United States)

2010-07-01

... moving or transporting operations. (d) The frames of off-track mining equipment being moved or... and the frames of off-track mining equipment being moved in-track and trolley entries, except that... the trolley wires or trolley feeder wires only from outby the unit of equipment being moved or...

Development of an FPGA Based Embedded System for High Speed Object Tracking

Directory of Open Access Journals (Sweden)

Chandrashekar MATHAM

2010-01-01

Full Text Available This paper deals with the development and implementation of system on chip (SOC for object tracking using histograms. To acquire the distance and velocity information of moving vehicles such as military tanks, to identify the type of target within the range from 100 m to 3 km and to estimate the movements of the vehicle. The VHDL code is written for the above objectives and implemented using Xilinx’s VERTEX-4 based PCI card family.

AAVSO Target Tool: A Web-Based Service for Tracking Variable Star Observations (Abstract)

Science.gov (United States)

Burger, D.; Stassun, K. G.; Barnes, C.; Kafka, S.; Beck, S.; Li, K.

2018-06-01

(Abstract only) The AAVSO Target Tool is a web-based interface for bringing stars in need of observation to the attention of AAVSOís network of amateur and professional astronomers. The site currently tracks over 700 targets of interest, collecting data from them on a regular basis from AAVSOís servers and sorting them based on priority. While the target tool does not require a login, users can obtain visibility times for each target by signing up and entering a telescope location. Other key features of the site include filtering by AAVSO observing section, sorting by different variable types, formatting the data for printing, and exporting the data to a CSV file. The AAVSO Target Tool builds upon seven years of experience developing web applications for astronomical data analysis, most notably on Filtergraph (Burger, D., et al. 2013, Astronomical Data Analysis Software and Systems XXII, Astronomical Society of the Pacific, San Francisco, 399), and is built using the web2py web framework based on the python programming language. The target tool is available at http://filtergraph.com/aavso.

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

Tracking of multimodal therapeutic nanocomplexes targeting breast cancer in vivo.

Science.gov (United States)

Bardhan, Rizia; Chen, Wenxue; Bartels, Marc; Perez-Torres, Carlos; Botero, Maria F; McAninch, Robin Ward; Contreras, Alejandro; Schiff, Rachel; Pautler, Robia G; Halas, Naomi J; Joshi, Amit

2010-12-08

Nanoparticle-based therapeutics with local delivery and external electromagnetic field modulation holds extraordinary promise for soft-tissue cancers such as breast cancer; however, knowledge of the distribution and fate of nanoparticles in vivo is crucial for clinical translation. Here we demonstrate that multiple diagnostic capabilities can be introduced in photothermal therapeutic nanocomplexes by simultaneously enhancing both near-infrared fluorescence and magnetic resonance imaging (MRI). We track nanocomplexes in vivo, examining the influence of HER2 antibody targeting on nanocomplex distribution over 72 h. This approach provides valuable, detailed information regarding the distribution and fate of complex nanoparticles designed for specific diagnostic and therapeutic functions.

Robot Tracking of Human Subjects in Field Environments

Science.gov (United States)

Graham, Jeffrey; Shillcutt, Kimberly

2003-01-01

Future planetary exploration will involve both humans and robots. Understanding and improving their interaction is a main focus of research in the Intelligent Systems Branch at NASA's Johnson Space Center. By teaming intelligent robots with astronauts on surface extra-vehicular activities (EVAs), safety and productivity can be improved. The EVA Robotic Assistant (ERA) project was established to study the issues of human-robot teams, to develop a testbed robot to assist space-suited humans in exploration tasks, and to experimentally determine the effectiveness of an EVA assistant robot. A companion paper discusses the ERA project in general, its history starting with ASRO (Astronaut-Rover project), and the results of recent field tests in Arizona. This paper focuses on one aspect of the research, robot tracking, in greater detail: the software architecture and algorithms. The ERA robot is capable of moving towards and/or continuously following mobile or stationary targets or sequences of targets. The contributions made by this research include how the low-level pose data is assembled, normalized and communicated, how the tracking algorithm was generalized and implemented, and qualitative performance reports from recent field tests.

Remote-controlled flexible pose measurement system and method for a moving target in wind tunnel

Directory of Open Access Journals (Sweden)

Wei LIU

2018-01-01

Full Text Available The measurement of position and attitude parameters for the isolated target from a high-speed aircraft is a great challenge in the field of wind tunnel simulation technology. This paper proposes a remote-controlled flexible pose measurement system in wind tunnel conditions for the separation of a target from an aircraft. The position and attitude parameters of a moving object are obtained by utilizing a single camera with a focal length and camera orientation that can be changed based on different measurement conditions. Using this proposed system and method, both the flexibility and efficiency of the pose measurement system can be enhanced in wind tunnel conditions to meet the measurement requirements of different objects and experiments, which is also useful for the development of an intelligent position and attitude measurement system. The position and the focal length of the camera also can be controlled remotely during measurements to enlarge both the vertical and horizontal measurement range of this system. Experiments are conducted in the laboratory to measure the position and attitude of moving objects with high flexibility and efficiency, and the measurement precision of the measurement system is also verified through experiments.

Weighted Optimization-Based Distributed Kalman Filter for Nonlinear Target Tracking in Collaborative Sensor Networks.

Science.gov (United States)

Chen, Jie; Li, Jiahong; Yang, Shuanghua; Deng, Fang

2017-11-01

The identification of the nonlinearity and coupling is crucial in nonlinear target tracking problem in collaborative sensor networks. According to the adaptive Kalman filtering (KF) method, the nonlinearity and coupling can be regarded as the model noise covariance, and estimated by minimizing the innovation or residual errors of the states. However, the method requires large time window of data to achieve reliable covariance measurement, making it impractical for nonlinear systems which are rapidly changing. To deal with the problem, a weighted optimization-based distributed KF algorithm (WODKF) is proposed in this paper. The algorithm enlarges the data size of each sensor by the received measurements and state estimates from its connected sensors instead of the time window. A new cost function is set as the weighted sum of the bias and oscillation of the state to estimate the "best" estimate of the model noise covariance. The bias and oscillation of the state of each sensor are estimated by polynomial fitting a time window of state estimates and measurements of the sensor and its neighbors weighted by the measurement noise covariance. The best estimate of the model noise covariance is computed by minimizing the weighted cost function using the exhaustive method. The sensor selection method is in addition to the algorithm to decrease the computation load of the filter and increase the scalability of the sensor network. The existence, suboptimality and stability analysis of the algorithm are given. The local probability data association method is used in the proposed algorithm for the multitarget tracking case. The algorithm is demonstrated in simulations on tracking examples for a random signal, one nonlinear target, and four nonlinear targets. Results show the feasibility and superiority of WODKF against other filtering algorithms for a large class of systems.

Design of a covert RFID tag network for target discovery and target information routing.

Science.gov (United States)

Pan, Qihe; Narayanan, Ram M

2011-01-01

Radio frequency identification (RFID) tags are small electronic devices working in the radio frequency range. They use wireless radio communications to automatically identify objects or people without the need for line-of-sight or contact, and are widely used in inventory tracking, object location, environmental monitoring. This paper presents a design of a covert RFID tag network for target discovery and target information routing. In the design, a static or very slowly moving target in the field of RFID tags transmits a distinct pseudo-noise signal, and the RFID tags in the network collect the target information and route it to the command center. A map of each RFID tag's location is saved at command center, which can determine where a RFID tag is located based on each RFID tag's ID. We propose the target information collection method with target association and clustering, and we also propose the information routing algorithm within the RFID tag network. The design and operation of the proposed algorithms are illustrated through examples. Simulation results demonstrate the effectiveness of the design.

A difference tracking algorithm based on discrete sine transform

Science.gov (United States)

Liu, HaoPeng; Yao, Yong; Lei, HeBing; Wu, HaoKun

2018-04-01

Target tracking is an important field of computer vision. The template matching tracking algorithm based on squared difference matching (SSD) and standard correlation coefficient (NCC) matching is very sensitive to the gray change of image. When the brightness or gray change, the tracking algorithm will be affected by high-frequency information. Tracking accuracy is reduced, resulting in loss of tracking target. In this paper, a differential tracking algorithm based on discrete sine transform is proposed to reduce the influence of image gray or brightness change. The algorithm that combines the discrete sine transform and the difference algorithm maps the target image into a image digital sequence. The Kalman filter predicts the target position. Using the Hamming distance determines the degree of similarity between the target and the template. The window closest to the template is determined the target to be tracked. The target to be tracked updates the template. Based on the above achieve target tracking. The algorithm is tested in this paper. Compared with SSD and NCC template matching algorithms, the algorithm tracks target stably when image gray or brightness change. And the tracking speed can meet the read-time requirement.

MO-FG-BRD-01: Real-Time Imaging and Tracking Techniques for Intrafractional Motion Management: Introduction and KV Tracking

International Nuclear Information System (INIS)

Fahimian, B.

2015-01-01

Intrafraction target motion is a prominent complicating factor in the accurate targeting of radiation within the body. Methods compensating for target motion during treatment, such as gating and dynamic tumor tracking, depend on the delineation of target location as a function of time during delivery. A variety of techniques for target localization have been explored and are under active development; these include beam-level imaging of radio-opaque fiducials, fiducial-less tracking of anatomical landmarks, tracking of electromagnetic transponders, optical imaging of correlated surrogates, and volumetric imaging within treatment delivery. The Joint Imaging and Therapy Symposium will provide an overview of the techniques for real-time imaging and tracking, with special focus on emerging modes of implementation across different modalities. In particular, the symposium will explore developments in 1) Beam-level kilovoltage X-ray imaging techniques, 2) EPID-based megavoltage X-ray tracking, 3) Dynamic tracking using electromagnetic transponders, and 4) MRI-based soft-tissue tracking during radiation delivery. Learning Objectives: Understand the fundamentals of real-time imaging and tracking techniques Learn about emerging techniques in the field of real-time tracking Distinguish between the advantages and disadvantages of different tracking modalities Understand the role of real-time tracking techniques within the clinical delivery work-flow

MO-FG-BRD-01: Real-Time Imaging and Tracking Techniques for Intrafractional Motion Management: Introduction and KV Tracking

Energy Technology Data Exchange (ETDEWEB)

Fahimian, B. [Stanford University (United States)

2015-06-15

Intrafraction target motion is a prominent complicating factor in the accurate targeting of radiation within the body. Methods compensating for target motion during treatment, such as gating and dynamic tumor tracking, depend on the delineation of target location as a function of time during delivery. A variety of techniques for target localization have been explored and are under active development; these include beam-level imaging of radio-opaque fiducials, fiducial-less tracking of anatomical landmarks, tracking of electromagnetic transponders, optical imaging of correlated surrogates, and volumetric imaging within treatment delivery. The Joint Imaging and Therapy Symposium will provide an overview of the techniques for real-time imaging and tracking, with special focus on emerging modes of implementation across different modalities. In particular, the symposium will explore developments in 1) Beam-level kilovoltage X-ray imaging techniques, 2) EPID-based megavoltage X-ray tracking, 3) Dynamic tracking using electromagnetic transponders, and 4) MRI-based soft-tissue tracking during radiation delivery. Learning Objectives: Understand the fundamentals of real-time imaging and tracking techniques Learn about emerging techniques in the field of real-time tracking Distinguish between the advantages and disadvantages of different tracking modalities Understand the role of real-time tracking techniques within the clinical delivery work-flow.

Robust Detection of Moving Human Target in Foliage-Penetration Environment Based on Hough Transform

Directory of Open Access Journals (Sweden)

P. Lei

2014-04-01

Full Text Available Attention has been focused on the robust moving human target detection in foliage-penetration environment, which presents a formidable task in a radar system because foliage is a rich scattering environment with complex multipath propagation and time-varying clutter. Generally, multiple-bounce returns and clutter are additionally superposed to direct-scatter echoes. They obscure true target echo and lead to poor visual quality time-range image, making target detection particular difficult. Consequently, an innovative approach is proposed to suppress clutter and mitigate multipath effects. In particular, a clutter suppression technique based on range alignment is firstly applied to suppress the time-varying clutter and the instable antenna coupling. Then entropy weighted coherent integration (EWCI algorithm is adopted to mitigate the multipath effects. In consequence, the proposed method effectively reduces the clutter and ghosting artifacts considerably. Based on the high visual quality image, the target trajectory is detected robustly and the radial velocity is estimated accurately with the Hough transform (HT. Real data used in the experimental results are provided to verify the proposed method.

A Student’s t Mixture Probability Hypothesis Density Filter for Multi-Target Tracking with Outliers

Science.gov (United States)

Liu, Zhuowei; Chen, Shuxin; Wu, Hao; He, Renke; Hao, Lin

2018-01-01

In multi-target tracking, the outliers-corrupted process and measurement noises can reduce the performance of the probability hypothesis density (PHD) filter severely. To solve the problem, this paper proposed a novel PHD filter, called Student’s t mixture PHD (STM-PHD) filter. The proposed filter models the heavy-tailed process noise and measurement noise as a Student’s t distribution as well as approximates the multi-target intensity as a mixture of Student’s t components to be propagated in time. Then, a closed PHD recursion is obtained based on Student’s t approximation. Our approach can make full use of the heavy-tailed characteristic of a Student’s t distribution to handle the situations with heavy-tailed process and the measurement noises. The simulation results verify that the proposed filter can overcome the negative effect generated by outliers and maintain a good tracking accuracy in the simultaneous presence of process and measurement outliers. PMID:29617348

Teaching Braille Line Tracking Using Stimulus Fading

Science.gov (United States)

Scheithauer, Mindy C.; Tiger, Jeffrey H.

2014-01-01

Line tracking is a prerequisite skill for braille literacy that involves moving one's finger horizontally across a line of braille text and identifying when a line ends so the reader may reset his or her finger on the subsequent line. Current procedures for teaching line tracking are incomplete, because they focus on tracking lines with only…

Force-field compensation in a manual tracking task.

Directory of Open Access Journals (Sweden)

Valentina Squeri

2010-06-01

Full Text Available This study addresses force/movement control in a dynamic "hybrid" task: the master sub-task is continuous manual tracking of a target moving along an eight-shaped Lissajous figure, with the tracking error as the primary performance index; the slave sub-task is compensation of a disturbing curl viscous field, compatibly with the primary performance index. The two sub-tasks are correlated because the lateral force the subject must exert on the eight-shape must be proportional to the longitudinal movement speed in order to perform a good tracking. The results confirm that visuo-manual tracking is characterized by an intermittent control mechanism, in agreement with previous work; the novel finding is that the overall control patterns are not altered by the presence of a large deviating force field, if compared with the undisturbed condition. It is also found that the control of interaction-forces is achieved by a combination of arm stiffness properties and direct force control, as suggested by the systematic lateral deviation of the trajectories from the nominal path and the comparison between perturbed trials and catch trials. The coordination of the two sub-tasks is quickly learnt after the activation of the deviating force field and is achieved by a combination of force and the stiffness components (about 80% vs. 20%, which is a function of the implicit accuracy of the tracking task.

Geometric accuracy of a novel gimbals based radiation therapy tumor tracking system.

Science.gov (United States)

Depuydt, Tom; Verellen, Dirk; Haas, Olivier; Gevaert, Thierry; Linthout, Nadine; Duchateau, Michael; Tournel, Koen; Reynders, Truus; Leysen, Katrien; Hoogeman, Mischa; Storme, Guy; De Ridder, Mark

2011-03-01

VERO is a novel platform for image guided stereotactic body radiotherapy. Orthogonal gimbals hold the linac-MLC assembly allowing real-time moving tumor tracking. This study determines the geometric accuracy of the tracking. To determine the tracking error, an 1D moving phantom produced sinusoidal motion with frequencies up to 30 breaths per minute (bpm). Tumor trajectories of patients were reproduced using a 2D robot and pursued with the gimbals tracking system prototype. Using the moving beam light field and a digital-camera-based detection unit tracking errors, system lag and equivalence of pan/tilt performance were measured. The system lag was 47.7 ms for panning and 47.6 ms for tilting. Applying system lag compensation, sinusoidal motion tracking was accurate, with a tracking error 90% percentile E(90%)tracking errors were below 0.14 mm. The 2D tumor trajectories were tracked with an average E(90%) of 0.54 mm, and tracking error standard deviations of 0.20 mm for pan and 0.22 mm for tilt. In terms of dynamic behavior, the gimbaled linac of the VERO system showed to be an excellent approach for providing accurate real-time tumor tracking in radiation therapy. Copyright © 2011 Elsevier Ireland Ltd. All rights reserved.

Enhanced Algorithms for EO/IR Electronic Stabilization, Clutter Suppression, and Track-Before-Detect for Multiple Low Observable Targets

Science.gov (United States)

Tartakovsky, A.; Brown, A.; Brown, J.

The paper describes the development and evaluation of a suite of advanced algorithms which provide significantly-improved capabilities for finding, fixing, and tracking multiple ballistic and flying low observable objects in highly stressing cluttered environments. The algorithms have been developed for use in satellite-based staring and scanning optical surveillance suites for applications including theatre and intercontinental ballistic missile early warning, trajectory prediction, and multi-sensor track handoff for midcourse discrimination and intercept. The functions performed by the algorithms include electronic sensor motion compensation providing sub-pixel stabilization (to 1/100 of a pixel), as well as advanced temporal-spatial clutter estimation and suppression to below sensor noise levels, followed by statistical background modeling and Bayesian multiple-target track-before-detect filtering. The multiple-target tracking is performed in physical world coordinates to allow for multi-sensor fusion, trajectory prediction, and intercept. Output of detected object cues and data visualization are also provided. The algorithms are designed to handle a wide variety of real-world challenges. Imaged scenes may be highly complex and infinitely varied -- the scene background may contain significant celestial, earth limb, or terrestrial clutter. For example, when viewing combined earth limb and terrestrial scenes, a combination of stationary and non-stationary clutter may be present, including cloud formations, varying atmospheric transmittance and reflectance of sunlight and other celestial light sources, aurora, glint off sea surfaces, and varied natural and man-made terrain features. The targets of interest may also appear to be dim, relative to the scene background, rendering much of the existing deployed software useless for optical target detection and tracking. Additionally, it may be necessary to detect and track a large number of objects in the threat cloud

Evaluating Moving Target Defense with PLADD

Energy Technology Data Exchange (ETDEWEB)

Jones, Stephen T. [Sandia National Laboratories (SNL-NM), Albuquerque, NM (United States); Outkin, Alexander V. [Sandia National Laboratories (SNL-NM), Albuquerque, NM (United States); Gearhart, Jared Lee [Sandia National Laboratories (SNL-NM), Albuquerque, NM (United States); Hobbs, Jacob Aaron [Sandia National Laboratories (SNL-NM), Albuquerque, NM (United States); Siirola, John Daniel [Sandia National Laboratories (SNL-NM), Albuquerque, NM (United States); Phillips, Cynthia A. [Sandia National Laboratories (SNL-NM), Albuquerque, NM (United States); Verzi, Stephen Joseph [Sandia National Laboratories (SNL-NM), Albuquerque, NM (United States); Tauritz, Daniel [Sandia National Laboratories (SNL-NM), Albuquerque, NM (United States); Mulder, Samuel A. [Sandia National Laboratories (SNL-NM), Albuquerque, NM (United States); Naugle, Asmeret Bier [Sandia National Laboratories (SNL-NM), Albuquerque, NM (United States)

2015-09-15

This project evaluates the effectiveness of moving target defense (MTD) techniques using a new game we have designed, called PLADD, inspired by the game FlipIt [28]. PLADD extends FlipIt by incorporating what we believe are key MTD concepts. We have analyzed PLADD and proven the existence of a defender strategy that pushes a rational attacker out of the game, demonstrated how limited the strategies available to an attacker are in PLADD, and derived analytic expressions for the expected utility of the game’s players in multiple game variants. We have created an algorithm for finding a defender’s optimal PLADD strategy. We show that in the special case of achieving deterrence in PLADD, MTD is not always cost effective and that its optimal deployment may shift abruptly from not using MTD at all to using it as aggressively as possible. We believe our effort provides basic, fundamental insights into the use of MTD, but conclude that a truly practical analysis requires model selection and calibration based on real scenarios and empirical data. We propose several avenues for further inquiry, including (1) agents with adaptive capabilities more reflective of real world adversaries, (2) the presence of multiple, heterogeneous adversaries, (3) computational game theory-based approaches such as coevolution to allow scaling to the real world beyond the limitations of analytical analysis and classical game theory, (4) mapping the game to real-world scenarios, (5) taking player risk into account when designing a strategy (in addition to expected payoff), (6) improving our understanding of the dynamic nature of MTD-inspired games by using a martingale representation, defensive forecasting, and techniques from signal processing, and (7) using adversarial games to develop inherently resilient cyber systems.

An ML-Based Radial Velocity Estimation Algorithm for Moving Targets in Spaceborne High-Resolution and Wide-Swath SAR Systems

Directory of Open Access Journals (Sweden)

Tingting Jin

2017-04-01

Full Text Available Multichannel synthetic aperture radar (SAR is a significant breakthrough to the inherent limitation between high-resolution and wide-swath (HRWS compared with conventional SAR. Moving target indication (MTI is an important application of spaceborne HRWS SAR systems. In contrast to previous studies of SAR MTI, the HRWS SAR mainly faces the problem of under-sampled data of each channel, causing single-channel imaging and processing to be infeasible. In this study, the estimation of velocity is equivalent to the estimation of the cone angle according to their relationship. The maximum likelihood (ML based algorithm is proposed to estimate the radial velocity in the existence of Doppler ambiguities. After that, the signal reconstruction and compensation for the phase offset caused by radial velocity are processed for a moving target. Finally, the traditional imaging algorithm is applied to obtain a focused moving target image. Experiments are conducted to evaluate the accuracy and effectiveness of the estimator under different signal-to-noise ratios (SNR. Furthermore, the performance is analyzed with respect to the motion ship that experiences interference due to different distributions of sea clutter. The results verify that the proposed algorithm is accurate and efficient with low computational complexity. This paper aims at providing a solution to the velocity estimation problem in the future HRWS SAR systems with multiple receive channels.

Improved nano-particle tracking analysis

International Nuclear Information System (INIS)

Walker, John G

2012-01-01

Nano-particle tracking is a method to estimate a particle size distribution by tracking the movements of individual particles, using multiple images of particles moving under Brownian motion. A novel method to recover a particle size distribution from nano-particle tracking data is described. Unlike a simple histogram-based method, the method described is able to account for the finite number of steps in each particle track and consequently for the measurement uncertainty in the step-length data. Computer simulation and experimental results are presented to demonstrate the performance of the approach compared with the current method. (paper)

Advances in image compression and automatic target recognition; Proceedings of the Meeting, Orlando, FL, Mar. 30, 31, 1989

Science.gov (United States)

Tescher, Andrew G. (Editor)

1989-01-01

Various papers on image compression and automatic target recognition are presented. Individual topics addressed include: target cluster detection in cluttered SAR imagery, model-based target recognition using laser radar imagery, Smart Sensor front-end processor for feature extraction of images, object attitude estimation and tracking from a single video sensor, symmetry detection in human vision, analysis of high resolution aerial images for object detection, obscured object recognition for an ATR application, neural networks for adaptive shape tracking, statistical mechanics and pattern recognition, detection of cylinders in aerial range images, moving object tracking using local windows, new transform method for image data compression, quad-tree product vector quantization of images, predictive trellis encoding of imagery, reduced generalized chain code for contour description, compact architecture for a real-time vision system, use of human visibility functions in segmentation coding, color texture analysis and synthesis using Gibbs random fields.

Moving objects management models, techniques and applications

CERN Document Server

Meng, Xiaofeng; Xu, Jiajie

2014-01-01

This book describes the topics of moving objects modeling and location tracking, indexing and querying, clustering, location uncertainty, traffic aware navigation and privacy issues as well as the application to intelligent transportation systems.

Position Affects Performance in Multiple-Object Tracking in Rugby Union Players

Directory of Open Access Journals (Sweden)

Andrés Martín

2017-09-01

Full Text Available We report an experiment that examines the performance of rugby union players and a control group composed of graduate student with no sport experience, in a multiple-object tracking task. It compares the ability of 86 high level rugby union players grouped as Backs and Forwards and the control group, to track a subset of randomly moving targets amongst the same number of distractors. Several difficulties were included in the experimental design in order to evaluate possible interactions between the relevant variables. Results show that the performance of the Backs is better than that of the other groups, but the occurrence of interactions precludes an isolated groups analysis. We interpret the results within the framework of visual attention and discuss both, the implications of our results and the practical consequences.

Track reconstruction in the emulsion-lead target of the OPERA experiment using the ESS microscope

Science.gov (United States)

Arrabito, L.; Bozza, C.; Buontempo, S.; Consiglio, L.; Cozzi, M.; D'Ambrosio, N.; DeLellis, G.; DeSerio, M.; Di Capua, F.; Di Ferdinando, D.; Di Marco, N.; Ereditato, A.; Esposito, L. S.; Fini, R. A.; Giacomelli, G.; Giorgini, M.; Grella, G.; Ieva, M.; Janicsko Csathy, J.; Juget, F.; Kreslo, I.; Laktineh, I.; Manai, K.; Mandrioli, G.; Marotta, A.; Migliozzi, P.; Monacelli, P.; Moser, U.; Muciaccia, M. T.; Pastore, A.; Patrizii, L.; Petukhov, Y.; Pistillo, C.; Pozzato, M.; Romano, G.; Rosa, G.; Russo, A.; Savvinov, N.; Schembri, A.; Scotto Lavina, L.; Simone, S.; Sioli, M.; Sirignano, C.; Sirri, G.; Strolin, P.; Tioukov, V.; Waelchli, T.

2007-05-01

The OPERA experiment, designed to conclusively prove the existence of νμ→ντ oscillations in the atmospheric sector, makes use of a massive lead-nuclear emulsion target to observe the appearance of ντ's in the CNGS νμ beam. The location and analysis of the neutrino interactions in quasi real-time required the development of fast computer-controlled microscopes able to reconstruct particle tracks with sub-micron precision and high efficiency at a speed of ~20 cm2/h. This paper describes the performance in particle track reconstruction of the European Scanning System, a novel automatic microscope for the measurement of emulsion films developed for OPERA.

Track reconstruction in the emulsion-lead target of the OPERA experiment using the ESS microscope

International Nuclear Information System (INIS)

Arrabito, L; Bozza, C; Buontempo, S

2007-01-01

The OPERA experiment, designed to conclusively prove the existence of ν μ →ν τ oscillations in the atmospheric sector, makes use of a massive lead-nuclear emulsion target to observe the appearance of ν τ 's in the CNGS ν μ beam. The location and analysis of the neutrino interactions in quasi real-time required the development of fast computer-controlled microscopes able to reconstruct particle tracks with sub-micron precision and high efficiency at a speed of ∼20 cm 2 /h. This paper describes the performance in particle track reconstruction of the European Scanning System, a novel automatic microscope for the measurement of emulsion films developed for OPERA

Tracking the impact of depression in a perspective-taking task.

Science.gov (United States)

Ferguson, Heather J; Cane, James

2017-11-01

Research has identified impairments in Theory of Mind (ToM) abilities in depressed patients, particularly in relation to tasks involving empathetic responses and belief reasoning. We aimed to build on this research by exploring the relationship between depressed mood and cognitive ToM, specifically visual perspective-taking ability. High and low depressed participants were eye-tracked as they completed a perspective-taking task, in which they followed the instructions of a 'director' to move target objects (e.g. a "teapot with spots on") around a grid, in the presence of a temporarily-ambiguous competitor object (e.g. a "teapot with stars on"). Importantly, some of the objects in the grid were occluded from the director's (but not the participant's) view. Results revealed no group-based difference in participants' ability to use perspective cues to identify the target object. All participants were faster to select the target object when the competitor was only available to the participant, compared to when the competitor was mutually available to the participant and director. Eye-tracking measures supported this pattern, revealing that perspective directed participants' visual search immediately upon hearing the ambiguous object's name (e.g. "teapot"). We discuss how these results fit with previous studies that have shown a negative relationship between depression and ToM.

An Automatic Multi-Target Independent Analysis Framework for Non-Planar Infrared-Visible Registration.

Science.gov (United States)

Sun, Xinglong; Xu, Tingfa; Zhang, Jizhou; Zhao, Zishu; Li, Yuankun

2017-07-26

In this paper, we propose a novel automatic multi-target registration framework for non-planar infrared-visible videos. Previous approaches usually analyzed multiple targets together and then estimated a global homography for the whole scene, however, these cannot achieve precise multi-target registration when the scenes are non-planar. Our framework is devoted to solving the problem using feature matching and multi-target tracking. The key idea is to analyze and register each target independently. We present a fast and robust feature matching strategy, where only the features on the corresponding foreground pairs are matched. Besides, new reservoirs based on the Gaussian criterion are created for all targets, and a multi-target tracking method is adopted to determine the relationships between the reservoirs and foreground blobs. With the matches in the corresponding reservoir, the homography of each target is computed according to its moving state. We tested our framework on both public near-planar and non-planar datasets. The results demonstrate that the proposed framework outperforms the state-of-the-art global registration method and the manual global registration matrix in all tested datasets.

A comparison of gantry-mounted x-ray-based real-time target tracking methods.

Science.gov (United States)

Montanaro, Tim; Nguyen, Doan Trang; Keall, Paul J; Booth, Jeremy; Caillet, Vincent; Eade, Thomas; Haddad, Carol; Shieh, Chun-Chien

2018-03-01

-posterior direction. Inferred traces often exhibit higher interdimensional correlation, which are not true representation of thoracic/abdominal motion and may underestimate kV-based tracking errors. The use of internal traces acquired from systems such as Calypso is advised for future kV-based tracking studies. The Gaussian PDF method is the most accurate 2D-3D inference method for tracking thoracic/abdominal targets. Motion magnitude has significant impact on 2D-3D inference error, and should be considered when estimating kV-based tracking error. © 2018 American Association of Physicists in Medicine.

An image-free opto-mechanical system for creating virtual environments and imaging neuronal activity in freely moving Caenorhabditis elegans.

Directory of Open Access Journals (Sweden)

Serge Faumont

Full Text Available Non-invasive recording in untethered animals is arguably the ultimate step in the analysis of neuronal function, but such recordings remain elusive. To address this problem, we devised a system that tracks neuron-sized fluorescent targets in real time. The system can be used to create virtual environments by optogenetic activation of sensory neurons, or to image activity in identified neurons at high magnification. By recording activity in neurons of freely moving C. elegans, we tested the long-standing hypothesis that forward and reverse locomotion are generated by distinct neuronal circuits. Surprisingly, we found motor neurons that are active during both types of locomotion, suggesting a new model of locomotion control in C. elegans. These results emphasize the importance of recording neuronal activity in freely moving animals and significantly expand the potential of imaging techniques by providing a mean to stabilize fluorescent targets.

Adaptive estimation for control of uncertain nonlinear systems with applications to target tracking

Science.gov (United States)

Madyastha, Venkatesh Kattigari

2005-08-01

Design of nonlinear observers has received considerable attention since the early development of methods for linear state estimation. The most popular approach is the extended Kalman filter (EKF), that goes through significant degradation in the presence of nonlinearities, particularly if unmodeled dynamics are coupled to the process and the measurement. For uncertain nonlinear systems, adaptive observers have been introduced to estimate the unknown state variables where no priori information about the unknown parameters is available. While establishing global results, these approaches are applicable only to systems transformable to output feedback form. Over the recent years, neural network (NN) based identification and estimation schemes have been proposed that relax the assumptions on the system at the price of sacrificing on the global nature of the results. However, most of the NN based adaptive observer approaches in the literature require knowledge of the full dimension of the system, therefore may not be suitable for systems with unmodeled dynamics. We first propose a novel approach to nonlinear state estimation from the perspective of augmenting a linear time invariant observer with an adaptive element. The class of nonlinear systems treated here are finite but of otherwise unknown dimension. The objective is to improve the performance of the linear observer when applied to a nonlinear system. The approach relies on the ability of the NNs to approximate the unknown dynamics from finite time histories of available measurements. Next we investigate nonlinear state estimation from the perspective of adaptively augmenting an existing time varying observer, such as an EKF. EKFs find their applications mostly in target tracking problems. The proposed approaches are robust to unmodeled dynamics, including unmodeled disturbances. Lastly, we consider the problem of adaptive estimation in the presence of feedback control for a class of uncertain nonlinear systems

A neurocomputational model of figure-ground discrimination and target tracking.

Science.gov (United States)

Sun, H; Liu, L; Guo, A

1999-01-01

A neurocomputational model is presented for figureground discrimination and target tracking. In the model, the elementary motion detectors of the correlation type, the computational modules of saccadic and smooth pursuit eye movement, an oscillatory neural-network motion perception module and a selective attention module are involved. It is shown that through the oscillatory amplitude and frequency encoding, and selective synchronization of phase oscillators, the figure and the ground can be successfully discriminated from each other. The receptive fields developed by hidden units of the networks were surprisingly similar to the actual receptive fields and columnar organization found in the primate visual cortex. It is suggested that equivalent mechanisms may exist in the primate visual cortex to discriminate figure-ground in both temporal and spatial domains.

A Novel Sensor Selection and Power Allocation Algorithm for Multiple-Target Tracking in an LPI Radar Network

Directory of Open Access Journals (Sweden)

Ji She

2016-12-01

Full Text Available Radar networks are proven to have numerous advantages over traditional monostatic and bistatic radar. With recent developments, radar networks have become an attractive platform due to their low probability of intercept (LPI performance for target tracking. In this paper, a joint sensor selection and power allocation algorithm for multiple-target tracking in a radar network based on LPI is proposed. It is found that this algorithm can minimize the total transmitted power of a radar network on the basis of a predetermined mutual information (MI threshold between the target impulse response and the reflected signal. The MI is required by the radar network system to estimate target parameters, and it can be calculated predictively with the estimation of target state. The optimization problem of sensor selection and power allocation, which contains two variables, is non-convex and it can be solved by separating power allocation problem from sensor selection problem. To be specific, the optimization problem of power allocation can be solved by using the bisection method for each sensor selection scheme. Also, the optimization problem of sensor selection can be solved by a lower complexity algorithm based on the allocated powers. According to the simulation results, it can be found that the proposed algorithm can effectively reduce the total transmitted power of a radar network, which can be conducive to improving LPI performance.