WorldWideScience

Sample records for sar automatic target

  1. Demonstrator for Automatic Target Classification in SAR Imagery

    NARCIS (Netherlands)

    Wit, J.J.M. de; Broek, A.C. van den; Dekker, R.J.

    2006-01-01

    Due to the increasing use of unmanned aerial vehicles (UAV) for reconnaissance, surveillance, and target acquisition applications, the interest in synthetic aperture radar (SAR) systems is growing. In order to facilitate the processing of the enormous amount of SAR data on the ground, automatic

  2. Context and Quasi-Invariants in Automatic Target Recognition (ATR) with Synthetic Aperture Radar (SAR) Imagery

    National Research Council Canada - National Science Library

    Binford, Thomas

    2000-01-01

    .... Experiments based on conventional recognition techniques were conducted for comparisons. Study of persistent scattering confirms the feasibility of implementing a SAR ATR system using physical image features...

  3. Improving SAR Automatic Target Recognition Models with Transfer Learning from Simulated Data

    DEFF Research Database (Denmark)

    Malmgren-Hansen, David; Kusk, Anders; Dall, Jørgen

    2017-01-01

    SAR images. The simulated data set is obtained by adding a simulated object radar reflectivity to a terrain model of individual point scatters, prior to focusing. Our results show that a Convolutional Neural Network (Convnet) pretrained on simulated data has a great advantage over a Convnet trained...

  4. AUTOMATIC COREGISTRATION FOR MULTIVIEW SAR IMAGES IN URBAN AREAS

    Directory of Open Access Journals (Sweden)

    Y. Xiang

    2017-09-01

    Full Text Available Due to the high resolution property and the side-looking mechanism of SAR sensors, complex buildings structures make the registration of SAR images in urban areas becomes very hard. In order to solve the problem, an automatic and robust coregistration approach for multiview high resolution SAR images is proposed in the paper, which consists of three main modules. First, both the reference image and the sensed image are segmented into two parts, urban areas and nonurban areas. Urban areas caused by double or multiple scattering in a SAR image have a tendency to show higher local mean and local variance values compared with general homogeneous regions due to the complex structural information. Based on this criterion, building areas are extracted. After obtaining the target regions, L-shape structures are detected using the SAR phase congruency model and Hough transform. The double bounce scatterings formed by wall and ground are shown as strong L- or T-shapes, which are usually taken as the most reliable indicator for building detection. According to the assumption that buildings are rectangular and flat models, planimetric buildings are delineated using the L-shapes, then the reconstructed target areas are obtained. For the orignal areas and the reconstructed target areas, the SAR-SIFT matching algorithm is implemented. Finally, correct corresponding points are extracted by the fast sample consensus (FSC and the transformation model is also derived. The experimental results on a pair of multiview TerraSAR images with 1-m resolution show that the proposed approach gives a robust and precise registration performance, compared with the orignal SAR-SIFT method.

  5. Automatic Coregistration for Multiview SAR Images in Urban Areas

    Science.gov (United States)

    Xiang, Y.; Kang, W.; Wang, F.; You, H.

    2017-09-01

    Due to the high resolution property and the side-looking mechanism of SAR sensors, complex buildings structures make the registration of SAR images in urban areas becomes very hard. In order to solve the problem, an automatic and robust coregistration approach for multiview high resolution SAR images is proposed in the paper, which consists of three main modules. First, both the reference image and the sensed image are segmented into two parts, urban areas and nonurban areas. Urban areas caused by double or multiple scattering in a SAR image have a tendency to show higher local mean and local variance values compared with general homogeneous regions due to the complex structural information. Based on this criterion, building areas are extracted. After obtaining the target regions, L-shape structures are detected using the SAR phase congruency model and Hough transform. The double bounce scatterings formed by wall and ground are shown as strong L- or T-shapes, which are usually taken as the most reliable indicator for building detection. According to the assumption that buildings are rectangular and flat models, planimetric buildings are delineated using the L-shapes, then the reconstructed target areas are obtained. For the orignal areas and the reconstructed target areas, the SAR-SIFT matching algorithm is implemented. Finally, correct corresponding points are extracted by the fast sample consensus (FSC) and the transformation model is also derived. The experimental results on a pair of multiview TerraSAR images with 1-m resolution show that the proposed approach gives a robust and precise registration performance, compared with the orignal SAR-SIFT method.

  6. Physics of Automatic Target Recognition

    CERN Document Server

    Sadjadi, Firooz

    2007-01-01

    Physics of Automatic Target Recognition addresses the fundamental physical bases of sensing, and information extraction in the state-of-the art automatic target recognition field. It explores both passive and active multispectral sensing, polarimetric diversity, complex signature exploitation, sensor and processing adaptation, transformation of electromagnetic and acoustic waves in their interactions with targets, background clutter, transmission media, and sensing elements. The general inverse scattering, and advanced signal processing techniques and scientific evaluation methodologies being used in this multi disciplinary field will be part of this exposition. The issues of modeling of target signatures in various spectral modalities, LADAR, IR, SAR, high resolution radar, acoustic, seismic, visible, hyperspectral, in diverse geometric aspects will be addressed. The methods for signal processing and classification will cover concepts such as sensor adaptive and artificial neural networks, time reversal filt...

  7. Automatic Detection and Positioning of Ground Control Points Using TerraSAR-X Multiaspect Acquisitions

    Science.gov (United States)

    Montazeri, Sina; Gisinger, Christoph; Eineder, Michael; Zhu, Xiao xiang

    2018-05-01

    Geodetic stereo Synthetic Aperture Radar (SAR) is capable of absolute three-dimensional localization of natural Persistent Scatterer (PS)s which allows for Ground Control Point (GCP) generation using only SAR data. The prerequisite for the method to achieve high precision results is the correct detection of common scatterers in SAR images acquired from different viewing geometries. In this contribution, we describe three strategies for automatic detection of identical targets in SAR images of urban areas taken from different orbit tracks. Moreover, a complete work-flow for automatic generation of large number of GCPs using SAR data is presented and its applicability is shown by exploiting TerraSAR-X (TS-X) high resolution spotlight images over the city of Oulu, Finland and a test site in Berlin, Germany.

  8. Synthetic SAR Image Generation using Sensor, Terrain and Target Models

    DEFF Research Database (Denmark)

    Kusk, Anders; Abulaitijiang, Adili; Dall, Jørgen

    2016-01-01

    A tool to generate synthetic SAR images of objects set on a clutter background is described. The purpose is to generate images for training Automatic Target Recognition and Identification algorithms. The tool employs a commercial electromagnetic simulation program to calculate radar cross section...

  9. AUTOMATIC INTERPRETATION OF HIGH RESOLUTION SAR IMAGES: FIRST RESULTS OF SAR IMAGE SIMULATION FOR SINGLE BUILDINGS

    Directory of Open Access Journals (Sweden)

    J. Tao

    2012-09-01

    Full Text Available Due to the all-weather data acquisition capabilities, high resolution space borne Synthetic Aperture Radar (SAR plays an important role in remote sensing applications like change detection. However, because of the complex geometric mapping of buildings in urban areas, SAR images are often hard to interpret. SAR simulation techniques ease the visual interpretation of SAR images, while fully automatic interpretation is still a challenge. This paper presents a method for supporting the interpretation of high resolution SAR images with simulated radar images using a LiDAR digital surface model (DSM. Line features are extracted from the simulated and real SAR images and used for matching. A single building model is generated from the DSM and used for building recognition in the SAR image. An application for the concept is presented for the city centre of Munich where the comparison of the simulation to the TerraSAR-X data shows a good similarity. Based on the result of simulation and matching, special features (e.g. like double bounce lines, shadow areas etc. can be automatically indicated in SAR image.

  10. SAR Target Recognition via Supervised Discriminative Dictionary Learning and Sparse Representation of the SAR-HOG Feature

    Directory of Open Access Journals (Sweden)

    Shengli Song

    2016-08-01

    Full Text Available Automatic target recognition (ATR in synthetic aperture radar (SAR images plays an important role in both national defense and civil applications. Although many methods have been proposed, SAR ATR is still very challenging due to the complex application environment. Feature extraction and classification are key points in SAR ATR. In this paper, we first design a novel feature, which is a histogram of oriented gradients (HOG-like feature for SAR ATR (called SAR-HOG. Then, we propose a supervised discriminative dictionary learning (SDDL method to learn a discriminative dictionary for SAR ATR and propose a strategy to simplify the optimization problem. Finally, we propose a SAR ATR classifier based on SDDL and sparse representation (called SDDLSR, in which both the reconstruction error and the classification error are considered. Extensive experiments are performed on the MSTAR database under standard operating conditions and extended operating conditions. The experimental results show that SAR-HOG can reliably capture the structures of targets in SAR images, and SDDL can further capture subtle differences among the different classes. By virtue of the SAR-HOG feature and SDDLSR, the proposed method achieves the state-of-the-art performance on MSTAR database. Especially for the extended operating conditions (EOC scenario “Training 17 ∘ —Testing 45 ∘ ”, the proposed method improves remarkably with respect to the previous works.

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

    Directory of Open Access Journals (Sweden)

    Sungho Kim

    2016-07-01

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

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

    Science.gov (United States)

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

    2016-01-01

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

  13. SAR image dataset of military ground targets with multiple poses for ATR

    Science.gov (United States)

    Belloni, Carole; Balleri, Alessio; Aouf, Nabil; Merlet, Thomas; Le Caillec, Jean-Marc

    2017-10-01

    Automatic Target Recognition (ATR) is the task of automatically detecting and classifying targets. Recognition using Synthetic Aperture Radar (SAR) images is interesting because SAR images can be acquired at night and under any weather conditions, whereas optical sensors operating in the visible band do not have this capability. Existing SAR ATR algorithms have mostly been evaluated using the MSTAR dataset.1 The problem with the MSTAR is that some of the proposed ATR methods have shown good classification performance even when targets were hidden,2 suggesting the presence of a bias in the dataset. Evaluations of SAR ATR techniques are currently challenging due to the lack of publicly available data in the SAR domain. In this paper, we present a high resolution SAR dataset consisting of images of a set of ground military target models taken at various aspect angles, The dataset can be used for a fair evaluation and comparison of SAR ATR algorithms. We applied the Inverse Synthetic Aperture Radar (ISAR) technique to echoes from targets rotating on a turntable and illuminated with a stepped frequency waveform. The targets in the database consist of four variants of two 1.7m-long models of T-64 and T-72 tanks. The gun, the turret position and the depression angle are varied to form 26 different sequences of images. The emitted signal spanned the frequency range from 13 GHz to 18 GHz to achieve a bandwidth of 5 GHz sampled with 4001 frequency points. The resolution obtained with respect to the size of the model targets is comparable to typical values obtained using SAR airborne systems. Single polarized images (Horizontal-Horizontal) are generated using the backprojection algorithm.3 A total of 1480 images are produced using a 20° integration angle. The images in the dataset are organized in a suggested training and testing set to facilitate a standard evaluation of SAR ATR algorithms.

  14. SAR Target Recognition Using the Multi-aspect-aware Bidirectional LSTM Recurrent Neural Networks

    OpenAIRE

    Zhang, Fan; Hu, Chen; Yin, Qiang; Li, Wei; Li, Hengchao; Hong, Wen

    2017-01-01

    The outstanding pattern recognition performance of deep learning brings new vitality to the synthetic aperture radar (SAR) automatic target recognition (ATR). However, there is a limitation in current deep learning based ATR solution that each learning process only handle one SAR image, namely learning the static scattering information, while missing the space-varying information. It is obvious that multi-aspect joint recognition introduced space-varying scattering information should improve ...

  15. The Automatic Measurement of Targets

    DEFF Research Database (Denmark)

    Höhle, Joachim

    1997-01-01

    The automatic measurement of targets is demonstrated by means of a theoretical example and by an interactive measuring program for real imagery from a réseau camera. The used strategy is a combination of two methods: the maximum correlation coefficient and the correlation in the subpixel range...... interactive software is also part of a computer-assisted learning program on digital photogrammetry....

  16. THz-SAR Vibrating Target Imaging via the Bayesian Method

    Directory of Open Access Journals (Sweden)

    Bin Deng

    2017-01-01

    Full Text Available Target vibration bears important information for target recognition, and terahertz, due to significant micro-Doppler effects, has strong advantages for remotely sensing vibrations. In this paper, the imaging characteristics of vibrating targets with THz-SAR are at first analyzed. An improved algorithm based on an excellent Bayesian approach, that is, the expansion-compression variance-component (ExCoV method, has been proposed for reconstructing scattering coefficients of vibrating targets, which provides more robust and efficient initialization and overcomes the deficiencies of sidelobes as well as artifacts arising from the traditional correlation method. A real vibration measurement experiment of idle cars was performed to validate the range model. Simulated SAR data of vibrating targets and a tank model in a real background in 220 GHz show good performance at low SNR. Rapidly evolving high-power terahertz devices will offer viable THz-SAR application at a distance of several kilometers.

  17. 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.

  18. SAR Data Fusion Imaging Method Oriented to Target Feature Extraction

    Directory of Open Access Journals (Sweden)

    Yang Wei

    2015-02-01

    Full Text Available To deal with the difficulty for target outlines extracting precisely due to neglect of target scattering characteristic variation during the processing of high-resolution space-borne SAR data, a novel fusion imaging method is proposed oriented to target feature extraction. Firstly, several important aspects that affect target feature extraction and SAR image quality are analyzed, including curved orbit, stop-and-go approximation, atmospheric delay, and high-order residual phase error. Furthermore, the corresponding compensation methods are addressed as well. Based on the analysis, the mathematical model of SAR echo combined with target space-time spectrum is established for explaining the space-time-frequency change rule of target scattering characteristic. Moreover, a fusion imaging strategy and method under high-resolution and ultra-large observation angle range conditions are put forward to improve SAR quality by fusion processing in range-doppler and image domain. Finally, simulations based on typical military targets are used to verify the effectiveness of the fusion imaging method.

  19. SAR target recognition and posture estimation using spatial pyramid pooling within CNN

    Science.gov (United States)

    Peng, Lijiang; Liu, Xiaohua; Liu, Ming; Dong, Liquan; Hui, Mei; Zhao, Yuejin

    2018-01-01

    Many convolution neural networks(CNN) architectures have been proposed to strengthen the performance on synthetic aperture radar automatic target recognition (SAR-ATR) and obtained state-of-art results on targets classification on MSTAR database, but few methods concern about the estimation of depression angle and azimuth angle of targets. To get better effect on learning representation of hierarchies of features on both 10-class target classification task and target posture estimation tasks, we propose a new CNN architecture with spatial pyramid pooling(SPP) which can build high hierarchy of features map by dividing the convolved feature maps from finer to coarser levels to aggregate local features of SAR images. Experimental results on MSTAR database show that the proposed architecture can get high recognition accuracy as 99.57% on 10-class target classification task as the most current state-of-art methods, and also get excellent performance on target posture estimation tasks which pays attention to depression angle variety and azimuth angle variety. What's more, the results inspire us the application of deep learning on SAR target posture description.

  20. Automatic Mexico Gulf Oil Spill Detection from Radarsat-2 SAR Satellite Data Using Genetic Algorithm

    Science.gov (United States)

    Marghany, Maged

    2016-10-01

    In this work, a genetic algorithm is exploited for automatic detection of oil spills of small and large size. The route is achieved using arrays of RADARSAT-2 SAR ScanSAR Narrow single beam data obtained in the Gulf of Mexico. The study shows that genetic algorithm has automatically segmented the dark spot patches related to small and large oil spill pixels. This conclusion is confirmed by the receiveroperating characteristic (ROC) curve and ground data which have been documented. The ROC curve indicates that the existence of oil slick footprints can be identified with the area under the curve between the ROC curve and the no-discrimination line of 90%, which is greater than that of other surrounding environmental features. The small oil spill sizes represented 30% of the discriminated oil spill pixels in ROC curve. In conclusion, the genetic algorithm can be used as a tool for the automatic detection of oil spills of either small or large size and the ScanSAR Narrow single beam mode serves as an excellent sensor for oil spill patterns detection and surveying in the Gulf of Mexico.

  1. A Cloud-Based System for Automatic Hazard Monitoring from Sentinel-1 SAR Data

    Science.gov (United States)

    Meyer, F. J.; Arko, S. A.; Hogenson, K.; McAlpin, D. B.; Whitley, M. A.

    2017-12-01

    Despite the all-weather capabilities of Synthetic Aperture Radar (SAR), and its high performance in change detection, the application of SAR for operational hazard monitoring was limited in the past. This has largely been due to high data costs, slow product delivery, and limited temporal sampling associated with legacy SAR systems. Only since the launch of ESA's Sentinel-1 sensors have routinely acquired and free-of-charge SAR data become available, allowing—for the first time—for a meaningful contribution of SAR to disaster monitoring. In this paper, we present recent technical advances of the Sentinel-1-based SAR processing system SARVIEWS, which was originally built to generate hazard products for volcano monitoring centers. We outline the main functionalities of SARVIEWS including its automatic database interface to Sentinel-1 holdings of the Alaska Satellite Facility (ASF), and its set of automatic processing techniques. Subsequently, we present recent system improvements that were added to SARVIEWS and allowed for a vast expansion of its hazard services; specifically: (1) In early 2017, the SARVIEWS system was migrated into the Amazon Cloud, providing access to cloud capabilities such as elastic scaling of compute resources and cloud-based storage; (2) we co-located SARVIEWS with ASF's cloud-based Sentinel-1 archive, enabling the efficient and cost effective processing of large data volumes; (3) we integrated SARVIEWS with ASF's HyP3 system (http://hyp3.asf.alaska.edu/), providing functionality such as subscription creation via API or map interface as well as automatic email notification; (4) we automated the production chains for seismic and volcanic hazards by integrating SARVIEWS with the USGS earthquake notification service (ENS) and the USGS eruption alert system. Email notifications from both services are parsed and subscriptions are automatically created when certain event criteria are met; (5) finally, SARVIEWS-generated hazard products are now

  2. AN AUTOMATIC OPTICAL AND SAR IMAGE REGISTRATION METHOD USING ITERATIVE MULTI-LEVEL AND REFINEMENT MODEL

    Directory of Open Access Journals (Sweden)

    C. Xu

    2016-06-01

    Full Text Available Automatic image registration is a vital yet challenging task, particularly for multi-sensor remote sensing images. Given the diversity of the data, it is unlikely that a single registration algorithm or a single image feature will work satisfactorily for all applications. Focusing on this issue, the mainly contribution of this paper is to propose an automatic optical-to-SAR image registration method using –level and refinement model: Firstly, a multi-level strategy of coarse-to-fine registration is presented, the visual saliency features is used to acquire coarse registration, and then specific area and line features are used to refine the registration result, after that, sub-pixel matching is applied using KNN Graph. Secondly, an iterative strategy that involves adaptive parameter adjustment for re-extracting and re-matching features is presented. Considering the fact that almost all feature-based registration methods rely on feature extraction results, the iterative strategy improve the robustness of feature matching. And all parameters can be automatically and adaptively adjusted in the iterative procedure. Thirdly, a uniform level set segmentation model for optical and SAR images is presented to segment conjugate features, and Voronoi diagram is introduced into Spectral Point Matching (VSPM to further enhance the matching accuracy between two sets of matching points. Experimental results show that the proposed method can effectively and robustly generate sufficient, reliable point pairs and provide accurate registration.

  3. Automatic target detection using binary template matching

    Science.gov (United States)

    Jun, Dong-San; Sun, Sun-Gu; Park, HyunWook

    2005-03-01

    This paper presents a new automatic target detection (ATD) algorithm to detect targets such as battle tanks and armored personal carriers in ground-to-ground scenarios. Whereas most ATD algorithms were developed for forward-looking infrared (FLIR) images, we have developed an ATD algorithm for charge-coupled device (CCD) images, which have superior quality to FLIR images in daylight. The proposed algorithm uses fast binary template matching with an adaptive binarization, which is robust to various light conditions in CCD images and saves computation time. Experimental results show that the proposed method has good detection performance.

  4. Automatic measurement of target crossing speed

    Science.gov (United States)

    Wardell, Mark; Lougheed, James H.

    1992-11-01

    The motion of ground vehicle targets after a ballistic round is launched can be a major source of inaccuracy for small (handheld) anti-armour weapon systems. A method of automatically measuring the crossing component to compensate the fire control solution has been devised and tested against various targets in a range of environments. A photodetector array aligned with the sight's horizontal reticle obtains scene features, which are digitized and processed to separate target from sight motion. Relative motion of the target against the background is briefly monitored to deduce angular crossing rate and a compensating lead angle is introduced into the aim point. Research to gather quantitative data and optimize algorithm performance is described, and some results from field testing are presented.

  5. Utilization of a genetic algorithm for the automatic detection of oil spill from RADARSAT-2 SAR satellite data

    International Nuclear Information System (INIS)

    Marghany, Maged

    2014-01-01

    Highlights: • An oil platform located 70 km from the coast of Louisiana sank on Thursday. • Oil spill has backscatter values of −25 dB in RADARSAT-2 SAR. • Oil spill is portrayed in SCNB mode by shallower incidence angle. • Ideal detection of oil spills in SAR images requires moderate wind speeds. • Genetic algorithm is excellent tool for automatic detection of oil spill in RADARSAT-2 SAR data. - Abstract: In this work, a genetic algorithm is applied for the automatic detection of oil spills. The procedure is implemented using sequences from RADARSAT-2 SAR ScanSAR Narrow single-beam data acquired in the Gulf of Mexico. The study demonstrates that the implementation of crossover allows for the generation of an accurate oil spill pattern. This conclusion is confirmed by the receiver-operating characteristic (ROC) curve. The ROC curve indicates that the existence of oil slick footprints can be identified using the area between the ROC curve and the no-discrimination line of 90%, which is greater than that of other surrounding environmental features. In conclusion, the genetic algorithm can be used as a tool for the automatic detection of oil spills, and the ScanSAR Narrow single-beam mode serves as an excellent sensor for oil spill detection and survey

  6. A Context Dependent Automatic Target Recognition System

    Science.gov (United States)

    Kim, J. H.; Payton, D. W.; Olin, K. E.; Tseng, D. Y.

    1984-06-01

    This paper describes a new approach to automatic target recognizer (ATR) development utilizing artificial intelligent techniques. The ATR system exploits contextual information in its detection and classification processes to provide a high degree of robustness and adaptability. In the system, knowledge about domain objects and their contextual relationships is encoded in frames, separating it from low level image processing algorithms. This knowledge-based system demonstrates an improvement over the conventional statistical approach through the exploitation of diverse forms of knowledge in its decision-making process.

  7. A new automatic SAR-based flood mapping application hosted on the European Space Agency's grid processing on demand fast access to imagery environment

    Science.gov (United States)

    Hostache, Renaud; Chini, Marco; Matgen, Patrick; Giustarini, Laura

    2013-04-01

    There is a clear need for developing innovative processing chains based on earth observation (EO) data to generate products supporting emergency response and flood management at a global scale. Here an automatic flood mapping application is introduced. The latter is currently hosted on the Grid Processing on Demand (G-POD) Fast Access to Imagery (Faire) environment of the European Space Agency. The main objective of the online application is to deliver flooded areas using both recent and historical acquisitions of SAR data in an operational framework. It is worth mentioning that the method can be applied to both medium and high resolution SAR images. The flood mapping application consists of two main blocks: 1) A set of query tools for selecting the "crisis image" and the optimal corresponding pre-flood "reference image" from the G-POD archive. 2) An algorithm for extracting flooded areas using the previously selected "crisis image" and "reference image". The proposed method is a hybrid methodology, which combines histogram thresholding, region growing and change detection as an approach enabling the automatic, objective and reliable flood extent extraction from SAR images. The method is based on the calibration of a statistical distribution of "open water" backscatter values inferred from SAR images of floods. Change detection with respect to a pre-flood reference image helps reducing over-detection of inundated areas. The algorithms are computationally efficient and operate with minimum data requirements, considering as input data a flood image and a reference image. Stakeholders in flood management and service providers are able to log onto the flood mapping application to get support for the retrieval, from the rolling archive, of the most appropriate pre-flood reference image. Potential users will also be able to apply the implemented flood delineation algorithm. Case studies of several recent high magnitude flooding events (e.g. July 2007 Severn River flood

  8. Automatic target classification of man-made objects in synthetic aperture radar images using Gabor wavelet and neural network

    Science.gov (United States)

    Vasuki, Perumal; Roomi, S. Mohamed Mansoor

    2013-01-01

    Processing of synthetic aperture radar (SAR) images has led to the development of automatic target classification approaches. These approaches help to classify individual and mass military ground vehicles. This work aims to develop an automatic target classification technique to classify military targets like truck/tank/armored car/cannon/bulldozer. The proposed method consists of three stages via preprocessing, feature extraction, and neural network (NN). The first stage removes speckle noise in a SAR image by the identified frost filter and enhances the image by histogram equalization. The second stage uses a Gabor wavelet to extract the image features. The third stage classifies the target by an NN classifier using image features. The proposed work performs better than its counterparts, like K-nearest neighbor (KNN). The proposed work performs better on databases like moving and stationary target acquisition and recognition against the earlier methods by KNN.

  9. AUTOMATIC CALCULATION OF OIL SLICK AREA FROM MULTIPLE SAR ACQUISITIONS FOR DEEPWATER HORIZON OIL SPILL

    Directory of Open Access Journals (Sweden)

    B. Osmanoğlu

    2012-07-01

    Full Text Available The Deepwater Horizon oil spill occurred in the Gulf of Mexico in April 2010 and became the largest accidental marine oil spill in history. Oil leaked continuously between April 20th and July 15th of 2010, releasing about 780, 000m3 of crude oil into the Gulf of Mexico. The oil spill caused extensive economical and ecological damage to the areas it reached, affecting the marine and wildlife habitats along with fishing and tourism industries. For oil spill mitigation efforts, it is important to determine the areal extent, and most recent position of the contaminated area. Satellitebased oil pollution monitoring systems are being used for monitoring and in hazard response efforts. Due to their high accuracy, frequent acquisitions, large area coverage and day-and-night operation Synthetic Aperture Radar (SAR satellites are a major contributer of monitoring marine environments for oil spill detection. We developed a new algorithm for determining the extent of the oil spill from multiple SAR images, that are acquired with short temporal intervals using different sensors. Combining the multi-polarization data from Radarsat-2 (C-band, Envisat ASAR (C-band and Alos-PALSAR (L-band sensors, we calculate the extent of the oil spill with higher accuracy than what is possible from only one image. Short temporal interval between acquisitions (hours to days allow us to eliminate artifacts and increase accuracy. Our algorithm works automatically without any human intervention to deliver products in a timely manner in time critical operations. Acquisitions using different SAR sensors are radiometrically calibrated and processed individually to obtain oil spill area extent. Furthermore the algorithm provides probability maps of the areas that are classified as oil slick. This probability information is then combined with other acquisitions to estimate the combined probability map for the spill.

  10. A color hierarchy for automatic target selection.

    Directory of Open Access Journals (Sweden)

    Illia Tchernikov

    Full Text Available Visual processing of color starts at the cones in the retina and continues through ventral stream visual areas, called the parvocellular pathway. Motion processing also starts in the retina but continues through dorsal stream visual areas, called the magnocellular system. Color and motion processing are functionally and anatomically discrete. Previously, motion processing areas MT and MST have been shown to have no color selectivity to a moving stimulus; the neurons were colorblind whenever color was presented along with motion. This occurs when the stimuli are luminance-defined versus the background and is considered achromatic motion processing. Is motion processing independent of color processing? We find that motion processing is intrinsically modulated by color. Color modulated smooth pursuit eye movements produced upon saccading to an aperture containing a surface of coherently moving dots upon a black background. Furthermore, when two surfaces that differed in color were present, one surface was automatically selected based upon a color hierarchy. The strength of that selection depended upon the distance between the two colors in color space. A quantifiable color hierarchy for automatic target selection has wide-ranging implications from sports to advertising to human-computer interfaces.

  11. Effect of Antenna Pointing Errors on SAR Imaging Considering the Change of the Point Target Location

    Science.gov (United States)

    Zhang, Xin; Liu, Shijie; Yu, Haifeng; Tong, Xiaohua; Huang, Guoman

    2018-04-01

    Towards spaceborne spotlight SAR, the antenna is regulated by the SAR system with specific regularity, so the shaking of the internal mechanism is inevitable. Moreover, external environment also has an effect on the stability of SAR platform. Both of them will cause the jitter of the SAR platform attitude. The platform attitude instability will introduce antenna pointing error on both the azimuth and range directions, and influence the acquisition of SAR original data and ultimate imaging quality. In this paper, the relations between the antenna pointing errors and the three-axis attitude errors are deduced, then the relations between spaceborne spotlight SAR imaging of the point target and antenna pointing errors are analysed based on the paired echo theory, meanwhile, the change of the azimuth antenna gain is considered as the spotlight SAR platform moves ahead. The simulation experiments manifest the effects on spotlight SAR imaging caused by antenna pointing errors are related to the target location, that is, the pointing errors of the antenna beam will severely influence the area far away from the scene centre of azimuth direction in the illuminated scene.

  12. Grid infrastructure for automatic processing of SAR data for flood applications

    Science.gov (United States)

    Kussul, Natalia; Skakun, Serhiy; Shelestov, Andrii

    2010-05-01

    More and more geosciences applications are being put on to the Grids. Due to the complexity of geosciences applications that is caused by complex workflow, the use of computationally intensive environmental models, the need of management and integration of heterogeneous data sets, Grid offers solutions to tackle these problems. Many geosciences applications, especially those related to the disaster management and mitigations require the geospatial services to be delivered in proper time. For example, information on flooded areas should be provided to corresponding organizations (local authorities, civil protection agencies, UN agencies etc.) no more than in 24 h to be able to effectively allocate resources required to mitigate the disaster. Therefore, providing infrastructure and services that will enable automatic generation of products based on the integration of heterogeneous data represents the tasks of great importance. In this paper we present Grid infrastructure for automatic processing of synthetic-aperture radar (SAR) satellite images to derive flood products. In particular, we use SAR data acquired by ESA's ENVSAT satellite, and neural networks to derive flood extent. The data are provided in operational mode from ESA rolling archive (within ESA Category-1 grant). We developed a portal that is based on OpenLayers frameworks and provides access point to the developed services. Through the portal the user can define geographical region and search for the required data. Upon selection of data sets a workflow is automatically generated and executed on the resources of Grid infrastructure. For workflow execution and management we use Karajan language. The workflow of SAR data processing consists of the following steps: image calibration, image orthorectification, image processing with neural networks, topographic effects removal, geocoding and transformation to lat/long projection, and visualisation. These steps are executed by different software, and can be

  13. TargetNet: a web service for predicting potential drug-target interaction profiling via multi-target SAR models.

    Science.gov (United States)

    Yao, Zhi-Jiang; Dong, Jie; Che, Yu-Jing; Zhu, Min-Feng; Wen, Ming; Wang, Ning-Ning; Wang, Shan; Lu, Ai-Ping; Cao, Dong-Sheng

    2016-05-01

    Drug-target interactions (DTIs) are central to current drug discovery processes and public health fields. Analyzing the DTI profiling of the drugs helps to infer drug indications, adverse drug reactions, drug-drug interactions, and drug mode of actions. Therefore, it is of high importance to reliably and fast predict DTI profiling of the drugs on a genome-scale level. Here, we develop the TargetNet server, which can make real-time DTI predictions based only on molecular structures, following the spirit of multi-target SAR methodology. Naïve Bayes models together with various molecular fingerprints were employed to construct prediction models. Ensemble learning from these fingerprints was also provided to improve the prediction ability. When the user submits a molecule, the server will predict the activity of the user's molecule across 623 human proteins by the established high quality SAR model, thus generating a DTI profiling that can be used as a feature vector of chemicals for wide applications. The 623 SAR models related to 623 human proteins were strictly evaluated and validated by several model validation strategies, resulting in the AUC scores of 75-100 %. We applied the generated DTI profiling to successfully predict potential targets, toxicity classification, drug-drug interactions, and drug mode of action, which sufficiently demonstrated the wide application value of the potential DTI profiling. The TargetNet webserver is designed based on the Django framework in Python, and is freely accessible at http://targetnet.scbdd.com .

  14. TargetNet: a web service for predicting potential drug-target interaction profiling via multi-target SAR models

    Science.gov (United States)

    Yao, Zhi-Jiang; Dong, Jie; Che, Yu-Jing; Zhu, Min-Feng; Wen, Ming; Wang, Ning-Ning; Wang, Shan; Lu, Ai-Ping; Cao, Dong-Sheng

    2016-05-01

    Drug-target interactions (DTIs) are central to current drug discovery processes and public health fields. Analyzing the DTI profiling of the drugs helps to infer drug indications, adverse drug reactions, drug-drug interactions, and drug mode of actions. Therefore, it is of high importance to reliably and fast predict DTI profiling of the drugs on a genome-scale level. Here, we develop the TargetNet server, which can make real-time DTI predictions based only on molecular structures, following the spirit of multi-target SAR methodology. Naïve Bayes models together with various molecular fingerprints were employed to construct prediction models. Ensemble learning from these fingerprints was also provided to improve the prediction ability. When the user submits a molecule, the server will predict the activity of the user's molecule across 623 human proteins by the established high quality SAR model, thus generating a DTI profiling that can be used as a feature vector of chemicals for wide applications. The 623 SAR models related to 623 human proteins were strictly evaluated and validated by several model validation strategies, resulting in the AUC scores of 75-100 %. We applied the generated DTI profiling to successfully predict potential targets, toxicity classification, drug-drug interactions, and drug mode of action, which sufficiently demonstrated the wide application value of the potential DTI profiling. The TargetNet webserver is designed based on the Django framework in Python, and is freely accessible at http://targetnet.scbdd.com.

  15. Feature extraction for SAR target recognition based on supervised manifold learning

    International Nuclear Information System (INIS)

    Du, C; Zhou, S; Sun, J; Zhao, J

    2014-01-01

    On the basis of manifold learning theory, a new feature extraction method for Synthetic aperture radar (SAR) target recognition is proposed. First, the proposed algorithm estimates the within-class and between-class local neighbourhood surrounding each SAR sample. After computing the local tangent space for each neighbourhood, the proposed algorithm seeks for the optimal projecting matrix by preserving the local within-class property and simultaneously maximizing the local between-class separability. The use of uncorrelated constraint can also enhance the discriminating power of the optimal projecting matrix. Finally, the nearest neighbour classifier is applied to recognize SAR targets in the projected feature subspace. Experimental results on MSTAR datasets demonstrate that the proposed method can provide a higher recognition rate than traditional feature extraction algorithms in SAR target recognition

  16. SAR target recognition using behaviour library of different shapes in different incidence angles and polarisations

    Science.gov (United States)

    Fallahpour, Mojtaba Behzad; Dehghani, Hamid; Jabbar Rashidi, Ali; Sheikhi, Abbas

    2018-05-01

    Target recognition is one of the most important issues in the interpretation of the synthetic aperture radar (SAR) images. Modelling, analysis, and recognition of the effects of influential parameters in the SAR can provide a better understanding of the SAR imaging systems, and therefore facilitates the interpretation of the produced images. Influential parameters in SAR images can be divided into five general categories of radar, radar platform, channel, imaging region, and processing section, each of which has different physical, structural, hardware, and software sub-parameters with clear roles in the finally formed images. In this paper, for the first time, a behaviour library that includes the effects of polarisation, incidence angle, and shape of targets, as radar and imaging region sub-parameters, in the SAR images are extracted. This library shows that the created pattern for each of cylindrical, conical, and cubic shapes is unique, and due to their unique properties these types of shapes can be recognised in the SAR images. This capability is applied to data acquired with the Canadian RADARSAT1 satellite.

  17. Target discrimination method for SAR images based on semisupervised co-training

    Science.gov (United States)

    Wang, Yan; Du, Lan; Dai, Hui

    2018-01-01

    Synthetic aperture radar (SAR) target discrimination is usually performed in a supervised manner. However, supervised methods for SAR target discrimination may need lots of labeled training samples, whose acquirement is costly, time consuming, and sometimes impossible. This paper proposes an SAR target discrimination method based on semisupervised co-training, which utilizes a limited number of labeled samples and an abundant number of unlabeled samples. First, Lincoln features, widely used in SAR target discrimination, are extracted from the training samples and partitioned into two sets according to their physical meanings. Second, two support vector machine classifiers are iteratively co-trained with the extracted two feature sets based on the co-training algorithm. Finally, the trained classifiers are exploited to classify the test data. The experimental results on real SAR images data not only validate the effectiveness of the proposed method compared with the traditional supervised methods, but also demonstrate the superiority of co-training over self-training, which only uses one feature set.

  18. Automatic targeting of plasma spray gun

    International Nuclear Information System (INIS)

    Abbatiello, L.A.; Neal, R.E.

    1978-01-01

    A means for monitoring the material portion in the flame of a plasma spray gun during spraying operations is described. A collimated detector, sensitive to certain wavelengths of light emission, is used to locate the centroid of the material with each pass of the gun. The response from the detector is then relayed to the gun controller to be used to automatically realign the gun

  19. Automatic targeting of plasma spray gun

    Science.gov (United States)

    Abbatiello, Leonard A.; Neal, Richard E.

    1978-01-01

    A means for monitoring the material portion in the flame of a plasma spray gun during spraying operations is provided. A collimated detector, sensitive to certain wavelengths of light emission, is used to locate the centroid of the material with each pass of the gun. The response from the detector is then relayed to the gun controller to be used to automatically realign the gun.

  20. Urban-area extraction from polarimetric SAR image using combination of target decomposition and orientation angle

    Science.gov (United States)

    Zou, Bin; Lu, Da; Wu, Zhilu; Qiao, Zhijun G.

    2016-05-01

    The results of model-based target decomposition are the main features used to discriminate urban and non-urban area in polarimetric synthetic aperture radar (PolSAR) application. Traditional urban-area extraction methods based on modelbased target decomposition usually misclassified ground-trunk structure as urban-area or misclassified rotated urbanarea as forest. This paper introduces another feature named orientation angle to improve urban-area extraction scheme for the accurate mapping in urban by PolSAR image. The proposed method takes randomness of orientation angle into account for restriction of urban area first and, subsequently, implements rotation angle to improve results that oriented urban areas are recognized as double-bounce objects from volume scattering. ESAR L-band PolSAR data of the Oberpfaffenhofen Test Site Area was used to validate the proposed algorithm.

  1. Effects of Target Positioning Error on Motion Compensation for Airborne Interferometric SAR

    Directory of Open Access Journals (Sweden)

    Li Yin-wei

    2013-12-01

    Full Text Available The measurement inaccuracies of Inertial Measurement Unit/Global Positioning System (IMU/GPS as well as the positioning error of the target may contribute to the residual uncompensated motion errors in the MOtion COmpensation (MOCO approach based on the measurement of IMU/GPS. Aiming at the effects of target positioning error on MOCO for airborne interferometric SAR, the paper firstly deduces a mathematical model of residual motion error bring out by target positioning error under the condition of squint. And the paper analyzes the effects on the residual motion error caused by system sampling delay error, the Doppler center frequency error and reference DEM error which result in target positioning error based on the model. Then, the paper discusses the effects of the reference DEM error on the interferometric SAR image quality, the interferometric phase and the coherent coefficient. The research provides theoretical bases for the MOCO precision in signal processing of airborne high precision SAR and airborne repeat-pass interferometric SAR.

  2. Artificial Intelligence In Automatic Target Recognizers: Technology And Timelines

    Science.gov (United States)

    Gilmore, John F.

    1984-12-01

    The recognition of targets in thermal imagery has been a problem exhaustively analyzed in its current localized dimension. This paper discusses the application of artificial intelligence (AI) technology to automatic target recognition, a concept capable of expanding current ATR efforts into a new globalized dimension. Deficiencies of current automatic target recognition systems are reviewed in terms of system shortcomings. Areas of artificial intelligence which show the most promise in improving ATR performance are analyzed, and a timeline is formed in light of how near (as well as far) term artificial intelligence applications may exist. Current research in the area of high level expert vision systems is reviewed and the possible utilization of artificial intelligence architectures to improve low level image processing functions is also discussed. Additional application areas of relevance to solving the problem of automatic target recognition utilizing both high and low level processing are also explored.

  3. Rotating Parabolic-Reflector Antenna Target in SAR Data: Model, Characteristics, and Parameter Estimation

    Directory of Open Access Journals (Sweden)

    Bin Deng

    2013-01-01

    Full Text Available Parabolic-reflector antennas (PRAs, usually possessing rotation, are a particular type of targets of potential interest to the synthetic aperture radar (SAR community. This paper is aimed to investigate PRA’s scattering characteristics and then to extract PRA’s parameters from SAR returns, for supporting image interpretation and target recognition. We at first obtain both closed-form and numeric solutions to PRA’s backscattering by geometrical optics (GO, physical optics, and graphical electromagnetic computation, respectively. Based on the GO solution, a migratory scattering center model is at first presented for representing the movement of the specular point with aspect angle, and then a hybrid model, named the migratory/micromotion scattering center (MMSC model, is proposed for characterizing a rotating PRA in the SAR geometry, which incorporates PRA’s rotation into its migratory scattering center model. Additionally, we in detail analyze PRA’s radar characteristics on radar cross-section, high-resolution range profiles, time-frequency distribution, and 2D images, which also confirm the models proposed. A maximal likelihood estimator is developed for jointly solving the MMSC model for PRA’s multiple parameters by optimization. By exploiting the aforementioned characteristics, the coarse parameter estimation guarantees convergency upon global minima. The signatures recovered can be favorably utilized for SAR image interpretation and target recognition.

  4. Laser gated viewing : An enabler for Automatic Target Recognition?

    NARCIS (Netherlands)

    Bovenkamp, E.G.P.; Schutte, K.

    2010-01-01

    For many decades attempts to accomplish Automatic Target Recognition have been made using both visual and FLIR camera systems. A recurring problem in these approaches is the segmentation problem, which is the separation between the target and its background. This paper describes an approach to

  5. SAR Image Simulation of Ship Targets Based on Multi-Path Scattering

    Science.gov (United States)

    Guo, Y.; Wang, H.; Ma, H.; Li, K.; Xia, Z.; Hao, Y.; Guo, H.; Shi, H.; Liao, X.; Yue, H.

    2018-04-01

    Synthetic Aperture Radar (SAR) plays an important role in the classification and recognition of ship targets because of its all-weather working ability and fine resolution. In SAR images, besides the sea clutter, the influence of the sea surface on the radar echo is also known as the so-called multipath effect. These multipath effects will generate some extra "pseudo images", which may cause the distortion of the target image and affect the estimation of the characteristic parameters. In this paper,the multipath effect of rough sea surface and its influence on the estimation of ship characteristic parameters are studied. The imaging of the first and the secondary reflection of sea surface is presented . The artifacts not only overlap with the image of the target itself, but may also appear in the sea near the target area. It is difficult to distinguish them, and this artifact has an effect on the length and width of the ship.

  6. 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.

  7. Deep kernel learning method for SAR image target recognition

    Science.gov (United States)

    Chen, Xiuyuan; Peng, Xiyuan; Duan, Ran; Li, Junbao

    2017-10-01

    With the development of deep learning, research on image target recognition has made great progress in recent years. Remote sensing detection urgently requires target recognition for military, geographic, and other scientific research. This paper aims to solve the synthetic aperture radar image target recognition problem by combining deep and kernel learning. The model, which has a multilayer multiple kernel structure, is optimized layer by layer with the parameters of Support Vector Machine and a gradient descent algorithm. This new deep kernel learning method improves accuracy and achieves competitive recognition results compared with other learning methods.

  8. Automatic target alignment of the Helios laser system

    International Nuclear Information System (INIS)

    Liberman, I.; Viswanathan, V.K.; Klein, M.; Seery, B.D.

    1980-01-01

    An automatic target-alignment technique for the Helios laser facility is reported and verified experimentally. The desired alignment condition is completely described by an autocollimation test. A computer program examines the autocollimated return pattern from the surrogate target and correctly describes any changes required in mirror orientation to yield optimum targe alignment with either aberrated or misaligned beams. Automated on-line target alignment is thus shown to be feasible

  9. Accurate Analysis of Target Characteristic in Bistatic SAR Images: A Dihedral Corner Reflectors Case.

    Science.gov (United States)

    Ao, Dongyang; Li, Yuanhao; Hu, Cheng; Tian, Weiming

    2017-12-22

    The dihedral corner reflectors are the basic geometric structure of many targets and are the main contributions of radar cross section (RCS) in the synthetic aperture radar (SAR) images. In stealth technologies, the elaborate design of the dihedral corners with different opening angles is a useful approach to reduce the high RCS generated by multiple reflections. As bistatic synthetic aperture sensors have flexible geometric configurations and are sensitive to the dihedral corners with different opening angles, they specially fit for the stealth target detections. In this paper, the scattering characteristic of dihedral corner reflectors is accurately analyzed in bistatic synthetic aperture images. The variation of RCS with the changing opening angle is formulated and the method to design a proper bistatic radar for maximizing the detection capability is provided. Both the results of the theoretical analysis and the experiments show the bistatic SAR could detect the dihedral corners, under a certain bistatic angle which is related to the geometry of target structures.

  10. Verification of target motion effects on SAR imagery using the Gotcha GMTI challenge dataset

    Science.gov (United States)

    Hack, Dan E.; Saville, Michael A.

    2010-04-01

    This paper investigates the relationship between a ground moving target's kinematic state and its SAR image. While effects such as cross-range offset, defocus, and smearing appear well understood, their derivations in the literature typically employ simplifications of the radar/target geometry and assume point scattering targets. This study adopts a geometrical model for understanding target motion effects in SAR imagery, termed the target migration path, and focuses on experimental verification of predicted motion effects using both simulated and empirical datasets based on the Gotcha GMTI challenge dataset. Specifically, moving target imagery is generated from three data sources: first, simulated phase history for a moving point target; second, simulated phase history for a moving vehicle derived from a simulated Mazda MPV X-band signature; and third, empirical phase history from the Gotcha GMTI challenge dataset. Both simulated target trajectories match the truth GPS target position history from the Gotcha GMTI challenge dataset, allowing direct comparison between all three imagery sets and the predicted target migration path. This paper concludes with a discussion of the parallels between the target migration path and the measurement model within a Kalman filtering framework, followed by conclusions.

  11. Towards automatic SAR-optical stereogrammetry over urban areas using very high resolution imagery

    Science.gov (United States)

    Qiu, Chunping; Schmitt, Michael; Zhu, Xiao Xiang

    2018-04-01

    In this paper we discuss the potential and challenges regarding SAR-optical stereogrammetry for urban areas, using very-high-resolution (VHR) remote sensing imagery. Since we do this mainly from a geometrical point of view, we first analyze the height reconstruction accuracy to be expected for different stereogrammetric configurations. Then, we propose a strategy for simultaneous tie point matching and 3D reconstruction, which exploits an epipolar-like search window constraint. To drive the matching and ensure some robustness, we combine different established hand-crafted similarity measures. For the experiments, we use real test data acquired by the Worldview-2, TerraSAR-X and MEMPHIS sensors. Our results show that SAR-optical stereogrammetry using VHR imagery is generally feasible with 3D positioning accuracies in the meter-domain, although the matching of these strongly hetereogeneous multi-sensor data remains very challenging.

  12. Terrain feature recognition for synthetic aperture radar (SAR) imagery employing spatial attributes of targets

    Science.gov (United States)

    Iisaka, Joji; Sakurai-Amano, Takako

    1994-08-01

    This paper describes an integrated approach to terrain feature detection and several methods to estimate spatial information from SAR (synthetic aperture radar) imagery. Spatial information of image features as well as spatial association are key elements in terrain feature detection. After applying a small feature preserving despeckling operation, spatial information such as edginess, texture (smoothness), region-likeliness and line-likeness of objects, target sizes, and target shapes were estimated. Then a trapezoid shape fuzzy membership function was assigned to each spatial feature attribute. Fuzzy classification logic was employed to detect terrain features. Terrain features such as urban areas, mountain ridges, lakes and other water bodies as well as vegetated areas were successfully identified from a sub-image of a JERS-1 SAR image. In the course of shape analysis, a quantitative method was developed to classify spatial patterns by expanding a spatial pattern through the use of a series of pattern primitives.

  13. Dendritic Cell Targeted Chitosan Nanoparticles for Nasal DNA Immunization against SARS CoV Nucleocapsid Protein

    OpenAIRE

    Raghuwanshi, Dharmendra; Mishra, Vivek; Das, Dipankar; Kaur, Kamaljit; Suresh, Mavanur R.

    2012-01-01

    This work investigates the formulation and in vivo efficacy of dendritic cell (DC) targeted plasmid DNA loaded biotinylated chitosan nanoparticles for nasal immunization against nucleocapsid (N) protein of severe acute respiratory syndrome coronavirus (SARS-CoV) as antigen. The induction of antigen-specific mucosal and systemic immune response at the site of virus entry is a major challenge for vaccine design. Here, we designed a strategy for non-invasive receptor mediated gene delivery to na...

  14. Radar automatic target recognition (ATR) and non-cooperative target recognition (NCTR)

    CERN Document Server

    Blacknell, David

    2013-01-01

    The ability to detect and locate targets by day or night, over wide areas, regardless of weather conditions has long made radar a key sensor in many military and civil applications. However, the ability to automatically and reliably distinguish different targets represents a difficult challenge. Radar Automatic Target Recognition (ATR) and Non-Cooperative Target Recognition (NCTR) captures material presented in the NATO SET-172 lecture series to provide an overview of the state-of-the-art and continuing challenges of radar target recognition. Topics covered include the problem as applied to th

  15. An algorithm for 3D target scatterer feature estimation from sparse SAR apertures

    Science.gov (United States)

    Jackson, Julie Ann; Moses, Randolph L.

    2009-05-01

    We present an algorithm for extracting 3D canonical scattering features from complex targets observed over sparse 3D SAR apertures. The algorithm begins with complex phase history data and ends with a set of geometrical features describing the scene. The algorithm provides a pragmatic approach to initialization of a nonlinear feature estimation scheme, using regularization methods to deconvolve the point spread function and obtain sparse 3D images. Regions of high energy are detected in the sparse images, providing location initializations for scattering center estimates. A single canonical scattering feature, corresponding to a geometric shape primitive, is fit to each region via nonlinear optimization of fit error between the regularized data and parametric canonical scattering models. Results of the algorithm are presented using 3D scattering prediction data of a simple scene for both a densely-sampled and a sparsely-sampled SAR measurement aperture.

  16. Aircraft target detection algorithm based on high resolution spaceborne SAR imagery

    Science.gov (United States)

    Zhang, Hui; Hao, Mengxi; Zhang, Cong; Su, Xiaojing

    2018-03-01

    In this paper, an image classification algorithm for airport area is proposed, which based on the statistical features of synthetic aperture radar (SAR) images and the spatial information of pixels. The algorithm combines Gamma mixture model and MRF. The algorithm using Gamma mixture model to obtain the initial classification result. Pixel space correlation based on the classification results are optimized by the MRF technique. Additionally, morphology methods are employed to extract airport (ROI) region where the suspected aircraft target samples are clarified to reduce the false alarm and increase the detection performance. Finally, this paper presents the plane target detection, which have been verified by simulation test.

  17. 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.

  18. The SARS-coronavirus-host interactome: identification of cyclophilins as target for pan-coronavirus inhibitors.

    Directory of Open Access Journals (Sweden)

    Susanne Pfefferle

    2011-10-01

    Full Text Available Coronaviruses (CoVs are important human and animal pathogens that induce fatal respiratory, gastrointestinal and neurological disease. The outbreak of the severe acute respiratory syndrome (SARS in 2002/2003 has demonstrated human vulnerability to (Coronavirus CoV epidemics. Neither vaccines nor therapeutics are available against human and animal CoVs. Knowledge of host cell proteins that take part in pivotal virus-host interactions could define broad-spectrum antiviral targets. In this study, we used a systems biology approach employing a genome-wide yeast-two hybrid interaction screen to identify immunopilins (PPIA, PPIB, PPIH, PPIG, FKBP1A, FKBP1B as interaction partners of the CoV non-structural protein 1 (Nsp1. These molecules modulate the Calcineurin/NFAT pathway that plays an important role in immune cell activation. Overexpression of NSP1 and infection with live SARS-CoV strongly increased signalling through the Calcineurin/NFAT pathway and enhanced the induction of interleukin 2, compatible with late-stage immunopathogenicity and long-term cytokine dysregulation as observed in severe SARS cases. Conversely, inhibition of cyclophilins by cyclosporine A (CspA blocked the replication of CoVs of all genera, including SARS-CoV, human CoV-229E and -NL-63, feline CoV, as well as avian infectious bronchitis virus. Non-immunosuppressive derivatives of CspA might serve as broad-range CoV inhibitors applicable against emerging CoVs as well as ubiquitous pathogens of humans and livestock.

  19. 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

  20. Accurate Analysis of Target Characteristic in Bistatic SAR Images: A Dihedral Corner Reflectors Case

    Directory of Open Access Journals (Sweden)

    Dongyang Ao

    2017-12-01

    Full Text Available The dihedral corner reflectors are the basic geometric structure of many targets and are the main contributions of radar cross section (RCS in the synthetic aperture radar (SAR images. In stealth technologies, the elaborate design of the dihedral corners with different opening angles is a useful approach to reduce the high RCS generated by multiple reflections. As bistatic synthetic aperture sensors have flexible geometric configurations and are sensitive to the dihedral corners with different opening angles, they specially fit for the stealth target detections. In this paper, the scattering characteristic of dihedral corner reflectors is accurately analyzed in bistatic synthetic aperture images. The variation of RCS with the changing opening angle is formulated and the method to design a proper bistatic radar for maximizing the detection capability is provided. Both the results of the theoretical analysis and the experiments show the bistatic SAR could detect the dihedral corners, under a certain bistatic angle which is related to the geometry of target structures.

  1. Accurate Analysis of Target Characteristic in Bistatic SAR Images: A Dihedral Corner Reflectors Case

    Science.gov (United States)

    Ao, Dongyang; Hu, Cheng; Tian, Weiming

    2017-01-01

    The dihedral corner reflectors are the basic geometric structure of many targets and are the main contributions of radar cross section (RCS) in the synthetic aperture radar (SAR) images. In stealth technologies, the elaborate design of the dihedral corners with different opening angles is a useful approach to reduce the high RCS generated by multiple reflections. As bistatic synthetic aperture sensors have flexible geometric configurations and are sensitive to the dihedral corners with different opening angles, they specially fit for the stealth target detections. In this paper, the scattering characteristic of dihedral corner reflectors is accurately analyzed in bistatic synthetic aperture images. The variation of RCS with the changing opening angle is formulated and the method to design a proper bistatic radar for maximizing the detection capability is provided. Both the results of the theoretical analysis and the experiments show the bistatic SAR could detect the dihedral corners, under a certain bistatic angle which is related to the geometry of target structures. PMID:29271917

  2. 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.

  3. SAR Target Recognition Based on Multi-feature Multiple Representation Classifier Fusion

    Directory of Open Access Journals (Sweden)

    Zhang Xinzheng

    2017-10-01

    Full Text Available In this paper, we present a Synthetic Aperture Radar (SAR image target recognition algorithm based on multi-feature multiple representation learning classifier fusion. First, it extracts three features from the SAR images, namely principal component analysis, wavelet transform, and Two-Dimensional Slice Zernike Moments (2DSZM features. Second, we harness the sparse representation classifier and the cooperative representation classifier with the above-mentioned features to get six predictive labels. Finally, we adopt classifier fusion to obtain the final recognition decision. We researched three different classifier fusion algorithms in our experiments, and the results demonstrate thatusing Bayesian decision fusion gives thebest recognition performance. The method based on multi-feature multiple representation learning classifier fusion integrates the discrimination of multi-features and combines the sparse and cooperative representation classification performance to gain complementary advantages and to improve recognition accuracy. The experiments are based on the Moving and Stationary Target Acquisition and Recognition (MSTAR database,and they demonstrate the effectiveness of the proposed approach.

  4. The Effect of Topography on Target Decomposition of Polarimetric SAR Data

    Directory of Open Access Journals (Sweden)

    Sang-Eun Park

    2015-04-01

    Full Text Available Polarimetric target decomposition enables the interpretation of radar images more easily, mostly based on physical assumptions, i.e., fitting physically-based scattering models to the polarimetric SAR observations. However, the model-fitting result cannot be always successful. Particularly, the performance of model-fitting in sloping forests is still an open question. In this study, the effect of ground topography on the model-fitting-based polarimetric decomposition techniques is investigated. The estimation accuracy of each scattering component in the decomposition results are evaluated based on the simulated target matrix by using the incoherent vegetation scattering model that accounts for the tilted scattering surface beneath the forest canopy. Experimental results show that the surface and the double-bounce scattering components can be significantly misestimated due to the topographic slope, even when the volume scattering power is successfully estimated.

  5. The potential of targeted antibody prophylaxis in SARS outbreak control: a mathematic analysis

    NARCIS (Netherlands)

    Bogaards, Johannes Antonie; Putter, Hein; Jan Weverling, Gerrit; ter Meulen, Jan; Goudsmit, Jaap

    2007-01-01

    BACKGROUND: Severe acute respiratory syndrome (SARS) coronavirus-like viruses continue to circulate in animal reservoirs. If new mutants of SARS coronavirus do initiate another epidemic, administration of prophylactic antibodies to risk groups may supplement the stringent isolation procedures that

  6. Automatic target validation based on neuroscientific literature mining for tractography

    Directory of Open Access Journals (Sweden)

    Xavier eVasques

    2015-05-01

    Full Text Available Target identification for tractography studies requires solid anatomical knowledge validated by an extensive literature review across species for each seed structure to be studied. Manual literature review to identify targets for a given seed region is tedious and potentially subjective. Therefore, complementary approaches would be useful. We propose to use text-mining models to automatically suggest potential targets from the neuroscientific literature, full-text articles and abstracts, so that they can be used for anatomical connection studies and more specifically for tractography. We applied text-mining models to three structures: two well studied structures, since validated deep brain stimulation targets, the internal globus pallidus and the subthalamic nucleus and, the nucleus accumbens, an exploratory target for treating psychiatric disorders. We performed a systematic review of the literature to document the projections of the three selected structures and compared it with the targets proposed by text-mining models, both in rat and primate (including human. We ran probabilistic tractography on the nucleus accumbens and compared the output with the results of the text-mining models and literature review. Overall, text-mining the literature could find three times as many targets as two man-weeks of curation could. The overall efficiency of the text-mining against literature review in our study was 98% recall (at 36% precision, meaning that over all the targets for the three selected seeds, only one target has been missed by text-mining. We demonstrate that connectivity for a structure of interest can be extracted from a very large amount of publications and abstracts. We believe this tool will be useful in helping the neuroscience community to facilitate connectivity studies of particular brain regions. The text mining tools used for the study are part of the HBP Neuroinformatics Platform, publicly available at http://connectivity-brainer.rhcloud.com/.

  7. SAR Target Recognition via Local Sparse Representation of Multi-Manifold Regularized Low-Rank Approximation

    Directory of Open Access Journals (Sweden)

    Meiting Yu

    2018-02-01

    Full Text Available The extraction of a valuable set of features and the design of a discriminative classifier are crucial for target recognition in SAR image. Although various features and classifiers have been proposed over the years, target recognition under extended operating conditions (EOCs is still a challenging problem, e.g., target with configuration variation, different capture orientations, and articulation. To address these problems, this paper presents a new strategy for target recognition. We first propose a low-dimensional representation model via incorporating multi-manifold regularization term into the low-rank matrix factorization framework. Two rules, pairwise similarity and local linearity, are employed for constructing multiple manifold regularization. By alternately optimizing the matrix factorization and manifold selection, the feature representation model can not only acquire the optimal low-rank approximation of original samples, but also capture the intrinsic manifold structure information. Then, to take full advantage of the local structure property of features and further improve the discriminative ability, local sparse representation is proposed for classification. Finally, extensive experiments on moving and stationary target acquisition and recognition (MSTAR database demonstrate the effectiveness of the proposed strategy, including target recognition under EOCs, as well as the capability of small training size.

  8. An Improved Algorithm to Delineate Urban Targets with Model-Based Decomposition of PolSAR Data

    Directory of Open Access Journals (Sweden)

    Dingfeng Duan

    2017-10-01

    Full Text Available In model-based decomposition algorithms using polarimetric synthetic aperture radar (PolSAR data, urban targets are typically identified based on the existence of strong double-bounced scattering. However, urban targets with large azimuth orientation angles (AOAs produce strong volumetric scattering that appears similar to scattering characteristics from tree canopies. Due to scattering ambiguity, urban targets can be classified into the vegetation category if the same classification scheme of the model-based PolSAR decomposition algorithms is followed. To resolve the ambiguity and to reduce the misclassification eventually, we introduced a correlation coefficient that characterized scattering mechanisms of urban targets with variable AOAs. Then, an existing volumetric scattering model was modified, and a PolSAR decomposition algorithm developed. The validity and effectiveness of the algorithm were examined using four PolSAR datasets. The algorithm was valid and effective to delineate urban targets with a wide range of AOAs, and applicable to a broad range of ground targets from urban areas, and from upland and flooded forest stands.

  9. Automatic attraction of visual attention by supraletter features of former target strings

    DEFF Research Database (Denmark)

    Kyllingsbæk, Søren; Lommel, Sven Van; Bundesen, Claus

    2014-01-01

    , performance (d’) degraded on trials in which former targets were present, suggesting that the former targets automatically drew processing resources away from the current targets. Apparently, the two experiments showed automatic attraction of visual attention by supraletter features of former target strings....

  10. WEIBULL MULTIPLICATIVE MODEL AND MACHINE LEARNING MODELS FOR FULL-AUTOMATIC DARK-SPOT DETECTION FROM SAR IMAGES

    Directory of Open Access Journals (Sweden)

    A. Taravat

    2013-09-01

    Full Text Available As a major aspect of marine pollution, oil release into the sea has serious biological and environmental impacts. Among remote sensing systems (which is a tool that offers a non-destructive investigation method, synthetic aperture radar (SAR can provide valuable synoptic information about the position and size of the oil spill due to its wide area coverage and day/night, and all-weather capabilities. In this paper we present a new automated method for oil-spill monitoring. A new approach is based on the combination of Weibull Multiplicative Model and machine learning techniques to differentiate between dark spots and the background. First, the filter created based on Weibull Multiplicative Model is applied to each sub-image. Second, the sub-image is segmented by two different neural networks techniques (Pulsed Coupled Neural Networks and Multilayer Perceptron Neural Networks. As the last step, a very simple filtering process is used to eliminate the false targets. The proposed approaches were tested on 20 ENVISAT and ERS2 images which contained dark spots. The same parameters were used in all tests. For the overall dataset, the average accuracies of 94.05 % and 95.20 % were obtained for PCNN and MLP methods, respectively. The average computational time for dark-spot detection with a 256 × 256 image in about 4 s for PCNN segmentation using IDL software which is the fastest one in this field at present. Our experimental results demonstrate that the proposed approach is very fast, robust and effective. The proposed approach can be applied to the future spaceborne SAR images.

  11. Weibull Multiplicative Model and Machine Learning Models for Full-Automatic Dark-Spot Detection from SAR Images

    Science.gov (United States)

    Taravat, A.; Del Frate, F.

    2013-09-01

    As a major aspect of marine pollution, oil release into the sea has serious biological and environmental impacts. Among remote sensing systems (which is a tool that offers a non-destructive investigation method), synthetic aperture radar (SAR) can provide valuable synoptic information about the position and size of the oil spill due to its wide area coverage and day/night, and all-weather capabilities. In this paper we present a new automated method for oil-spill monitoring. A new approach is based on the combination of Weibull Multiplicative Model and machine learning techniques to differentiate between dark spots and the background. First, the filter created based on Weibull Multiplicative Model is applied to each sub-image. Second, the sub-image is segmented by two different neural networks techniques (Pulsed Coupled Neural Networks and Multilayer Perceptron Neural Networks). As the last step, a very simple filtering process is used to eliminate the false targets. The proposed approaches were tested on 20 ENVISAT and ERS2 images which contained dark spots. The same parameters were used in all tests. For the overall dataset, the average accuracies of 94.05 % and 95.20 % were obtained for PCNN and MLP methods, respectively. The average computational time for dark-spot detection with a 256 × 256 image in about 4 s for PCNN segmentation using IDL software which is the fastest one in this field at present. Our experimental results demonstrate that the proposed approach is very fast, robust and effective. The proposed approach can be applied to the future spaceborne SAR images.

  12. Deep transfer learning for automatic target classification: MWIR to LWIR

    Science.gov (United States)

    Ding, Zhengming; Nasrabadi, Nasser; Fu, Yun

    2016-05-01

    Publisher's Note: This paper, originally published on 5/12/2016, was replaced with a corrected/revised version on 5/18/2016. If you downloaded the original PDF but are unable to access the revision, please contact SPIE Digital Library Customer Service for assistance. When dealing with sparse or no labeled data in the target domain, transfer learning shows its appealing performance by borrowing the supervised knowledge from external domains. Recently deep structure learning has been exploited in transfer learning due to its attractive power in extracting effective knowledge through multi-layer strategy, so that deep transfer learning is promising to address the cross-domain mismatch. In general, cross-domain disparity can be resulted from the difference between source and target distributions or different modalities, e.g., Midwave IR (MWIR) and Longwave IR (LWIR). In this paper, we propose a Weighted Deep Transfer Learning framework for automatic target classification through a task-driven fashion. Specifically, deep features and classifier parameters are obtained simultaneously for optimal classification performance. In this way, the proposed deep structures can extract more effective features with the guidance of the classifier performance; on the other hand, the classifier performance is further improved since it is optimized on more discriminative features. Furthermore, we build a weighted scheme to couple source and target output by assigning pseudo labels to target data, therefore we can transfer knowledge from source (i.e., MWIR) to target (i.e., LWIR). Experimental results on real databases demonstrate the superiority of the proposed algorithm by comparing with others.

  13. Generalized synthetic aperture radar automatic target recognition by convolutional neural network with joint use of two-dimensional principal component analysis and support vector machine

    Science.gov (United States)

    Zheng, Ce; Jiang, Xue; Liu, Xingzhao

    2017-10-01

    Convolutional neural network (CNN), as a vital part of the deep learning research field, has shown powerful potential for automatic target recognition (ATR) of synthetic aperture radar (SAR). However, the high complexity caused by the deep structure of CNN makes it difficult to generalize. An improved form of CNN with higher generalization capability and less probability of overfitting, which further improves the efficiency and robustness of the SAR ATR system, is proposed. The convolution layers of CNN are combined with a two-dimensional principal component analysis algorithm. Correspondingly, the kernel support vector machine is utilized as the classifier layer instead of the multilayer perceptron. The verification experiments are implemented using the moving and stationary target acquisition and recognition database, and the results validate the efficiency of the proposed method.

  14. Dendritic cell targeted chitosan nanoparticles for nasal DNA immunization against SARS CoV nucleocapsid protein.

    Science.gov (United States)

    Raghuwanshi, Dharmendra; Mishra, Vivek; Das, Dipankar; Kaur, Kamaljit; Suresh, Mavanur R

    2012-04-02

    This work investigates the formulation and in vivo efficacy of dendritic cell (DC) targeted plasmid DNA loaded biotinylated chitosan nanoparticles for nasal immunization against nucleocapsid (N) protein of severe acute respiratory syndrome coronavirus (SARS-CoV) as antigen. The induction of antigen-specific mucosal and systemic immune response at the site of virus entry is a major challenge for vaccine design. Here, we designed a strategy for noninvasive receptor mediated gene delivery to nasal resident DCs. The pDNA loaded biotinylated chitosan nanoparticles were prepared using a complex coacervation process and characterized for size, shape, surface charge, plasmid DNA loading and protection against nuclease digestion. The pDNA loaded biotinylated chitosan nanoparticles were targeted with bifunctional fusion protein (bfFp) vector for achieving DC selective targeting. The bfFp is a recombinant fusion protein consisting of truncated core-streptavidin fused with anti-DEC-205 single chain antibody (scFv). The core-streptavidin arm of fusion protein binds with biotinylated nanoparticles, while anti-DEC-205 scFv imparts targeting specificity to DC DEC-205 receptor. We demonstrate that intranasal administration of bfFp targeted formulations along with anti-CD40 DC maturation stimuli enhanced magnitude of mucosal IgA as well as systemic IgG against N protein. The strategy led to the detection of augmented levels of N protein specific systemic IgG and nasal IgA antibodies. However, following intranasal delivery of naked pDNA no mucosal and systemic immune responses were detected. A parallel comparison of targeted formulations using intramuscular and intranasal routes showed that the intramuscular route is superior for induction of systemic IgG responses compared with the intranasal route. Our results suggest that targeted pDNA delivery through a noninvasive intranasal route can be a strategy for designing low-dose vaccines.

  15. Simulation-Based Evaluation of Light Posts and Street Signs as 3-D Geolocation Targets in SAR Images

    Science.gov (United States)

    Auer, S.; Balss, U.

    2017-05-01

    The assignment of phase center positions (in 2D or 3D) derived from SAR data to physical object is challenging for many man-made structures such as buildings or bridges. In contrast, light poles and traffic signs are promising targets for tasks based on 3-D geolocation as they often show a prominent and spatially isolated appearance. For a detailed understanding of the nature of both targets, this paper presents results of a dedicated simulation case study, which is based on ray tracing methods (simulator RaySAR). For the first time, the appearance of the targets is analyzed in 2D (image plane) and 3D space (world coordinates of scene model) and reflecting surfaces are identified for related dominant image pixels. The case studies confirms the crucial impact of spatial resolution in the context of light poles and traffic signs and the appropriateness of light poles as target for 3-D geolocation in case of horizontal ground surfaces beneath.

  16. Automatic system of production, transfer and processing of coin targets for the production of metallic radioisotopes

    Science.gov (United States)

    Pellicioli, M.; Ouadi, A.; Marchand, P.; Foehrenbacher, T.; Schuler, J.; Dick-Schuler, N.; Brasse, D.

    2017-05-01

    The work presented in this paper gathers three main technical developments aiming at 1) optimizing nuclide production by the mean of solid targets 2) automatically transferring coin targets from vault to hotcell without human intervention 3) processing target dilution and purification in hotcell automatically. This system has been installed on a ACSI TR24 cyclotron in Strasbourg France.

  17. A Multi-Scale Flood Monitoring System Based on Fully Automatic MODIS and TerraSAR-X Processing Chains

    Directory of Open Access Journals (Sweden)

    Enrico Stein

    2013-10-01

    Full Text Available A two-component fully automated flood monitoring system is described and evaluated. This is a result of combining two individual flood services that are currently under development at DLR’s (German Aerospace Center Center for Satellite based Crisis Information (ZKI to rapidly support disaster management activities. A first-phase monitoring component of the system systematically detects potential flood events on a continental scale using daily-acquired medium spatial resolution optical data from the Moderate Resolution Imaging Spectroradiometer (MODIS. A threshold set controls the activation of the second-phase crisis component of the system, which derives flood information at higher spatial detail using a Synthetic Aperture Radar (SAR based satellite mission (TerraSAR-X. The proposed activation procedure finds use in the identification of flood situations in different spatial resolutions and in the time-critical and on demand programming of SAR satellite acquisitions at an early stage of an evolving flood situation. The automated processing chains of the MODIS (MFS and the TerraSAR-X Flood Service (TFS include data pre-processing, the computation and adaptation of global auxiliary data, thematic classification, and the subsequent dissemination of flood maps using an interactive web-client. The system is operationally demonstrated and evaluated via the monitoring two recent flood events in Russia 2013 and Albania/Montenegro 2013.

  18. Automatized target devices for radioisotope production at the RITs cyclotron

    International Nuclear Information System (INIS)

    Bogdanov, P.V.; Ivanov, V.V.; Karasev, B.G.

    1981-01-01

    An automation target device intended for isotope production on the internal beam of the RITs cyclotron is decribed. The target device comprises the following main units: target head, vacuum lock, charging device, transport system for bringing the target for charging; mechanism of target discharge transport device, control interlocking and signalling control system of target radiation power. The automation target device permits radioisotope production on the cyclotron in commercial scales with automation substitution of irradiated targets. The time of substitution of one of six targets makes up only 5 min. The time of charging a new group of targets to the charge device - 60 min. Contact of the personnel with irradiated targets is practically excluded and the necessity of entering the cyclotron room for maintenance of the plant is reduced to the minimum [ru

  19. Bayesian Methods and Confidence Intervals for Automatic Target Recognition of SAR Canonical Shapes

    Science.gov (United States)

    2014-03-27

    and DirectX [22]. The CUDA platform was developed by the NVIDIA Corporation to allow programmers access to the computational capabilities of the...were used for the intense repetitive computations. Developing CUDA software requires writing code for specialized compilers provided by NVIDIA and

  20. SIMULATION-BASED EVALUATION OF LIGHT POSTS AND STREET SIGNS AS 3-D GEOLOCATION TARGETS IN SAR IMAGES

    Directory of Open Access Journals (Sweden)

    S. Auer

    2017-05-01

    Full Text Available The assignment of phase center positions (in 2D or 3D derived from SAR data to physical object is challenging for many man-made structures such as buildings or bridges. In contrast, light poles and traffic signs are promising targets for tasks based on 3-D geolocation as they often show a prominent and spatially isolated appearance. For a detailed understanding of the nature of both targets, this paper presents results of a dedicated simulation case study, which is based on ray tracing methods (simulator RaySAR. For the first time, the appearance of the targets is analyzed in 2D (image plane and 3D space (world coordinates of scene model and reflecting surfaces are identified for related dominant image pixels. The case studies confirms the crucial impact of spatial resolution in the context of light poles and traffic signs and the appropriateness of light poles as target for 3-D geolocation in case of horizontal ground surfaces beneath.

  1. 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.

  2. 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.

  3. 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.

  4. Double Bounce Component in Cross-Polarimetric SAR from a New Scattering Target Decomposition

    Science.gov (United States)

    Hong, Sang-Hoon; Wdowinski, Shimon

    2013-08-01

    Common vegetation scattering theories assume that the Synthetic Aperture Radar (SAR) cross-polarization (cross-pol) signal represents solely volume scattering. We found this assumption incorrect based on SAR phase measurements acquired over the south Florida Everglades wetlands indicating that the cross-pol radar signal often samples the water surface beneath the vegetation. Based on these new observations, we propose that the cross-pol measurement consists of both volume scattering and double bounce components. The simplest multi-bounce scattering mechanism that generates cross-pol signal occurs by rotated dihedrals. Thus, we use the rotated dihedral mechanism with probability density function to revise some of the vegetation scattering theories and develop a three- component decomposition algorithm with single bounce, double bounce from both co-pol and cross-pol, and volume scattering components. We applied the new decomposition analysis to both urban and rural environments using Radarsat-2 quad-pol datasets. The decomposition of the San Francisco's urban area shows higher double bounce scattering and reduced volume scattering compared to other common three-component decomposition. The decomposition of the rural Everglades area shows that the relations between volume and cross-pol double bounce depend on the vegetation density. The new decomposition can be useful to better understand vegetation scattering behavior over the various surfaces and the estimation of above ground biomass using SAR observations.

  5. Rendezvous terminal phase automatic braking sequencing and targeting. [for space shuttle orbiter

    Science.gov (United States)

    Kachmar, P. M.

    1973-01-01

    The purpose of the rendezvous terminal phase braking program is to provide the means of automatically bringing the primary orbiter within desired station keeping boundaries relative to the target satellite. A detailed discussion is presented on the braking program and its navigation, targeting, and guidance functions.

  6. SAR: Stroke Authorship Recognition

    KAUST Repository

    Shaheen, Sara

    2015-10-15

    Are simple strokes unique to the artist or designer who renders them? If so, can this idea be used to identify authorship or to classify artistic drawings? Also, could training methods be devised to develop particular styles? To answer these questions, we propose the Stroke Authorship Recognition (SAR) approach, a novel method that distinguishes the authorship of 2D digitized drawings. SAR converts a drawing into a histogram of stroke attributes that is discriminative of authorship. We provide extensive classification experiments on a large variety of data sets, which validate SAR\\'s ability to distinguish unique authorship of artists and designers. We also demonstrate the usefulness of SAR in several applications including the detection of fraudulent sketches, the training and monitoring of artists in learning a particular new style and the first quantitative way to measure the quality of automatic sketch synthesis tools. © 2015 The Eurographics Association and John Wiley & Sons Ltd.

  7. ROADS CENTRE-AXIS EXTRACTION IN AIRBORNE SAR IMAGES: AN APPROACH BASED ON ACTIVE CONTOUR MODEL WITH THE USE OF SEMI-AUTOMATIC SEEDING

    Directory of Open Access Journals (Sweden)

    R. G. Lotte

    2013-05-01

    Full Text Available Research works dealing with computational methods for roads extraction have considerably increased in the latest two decades. This procedure is usually performed on optical or microwave sensors (radar imagery. Radar images offer advantages when compared to optical ones, for they allow the acquisition of scenes regardless of atmospheric and illumination conditions, besides the possibility of surveying regions where the terrain is hidden by the vegetation canopy, among others. The cartographic mapping based on these images is often manually accomplished, requiring considerable time and effort from the human interpreter. Maps for detecting new roads or updating the existing roads network are among the most important cartographic products to date. There are currently many studies involving the extraction of roads by means of automatic or semi-automatic approaches. Each of them presents different solutions for different problems, making this task a scientific issue still open. One of the preliminary steps for roads extraction can be the seeding of points belonging to roads, what can be done using different methods with diverse levels of automation. The identified seed points are interpolated to form the initial road network, and are hence used as an input for an extraction method properly speaking. The present work introduces an innovative hybrid method for the extraction of roads centre-axis in a synthetic aperture radar (SAR airborne image. Initially, candidate points are fully automatically seeded using Self-Organizing Maps (SOM, followed by a pruning process based on specific metrics. The centre-axis are then detected by an open-curve active contour model (snakes. The obtained results were evaluated as to their quality with respect to completeness, correctness and redundancy.

  8. Review of Current Aided/Automatic Target Acquisition Technology for Military Target Acquisition Tasks

    Science.gov (United States)

    2011-07-01

    radar [e.g., synthetic aperture radar (SAR)]. EO/IR includes multi- and hyperspectral imaging. Signal processing of data from nonimaging sensors, such...enhanced recognition ability. Other nonimage -based techniques, such as category theory,45 hierarchical systems,46 and gradient index flow,47 are possible...the battle- field. There is a plethora of imaging and nonimaging sensors on the battlefield that are being networked together for trans- mission of

  9. Multi-Stage System for Automatic Target Recognition

    Science.gov (United States)

    Chao, Tien-Hsin; Lu, Thomas T.; Ye, David; Edens, Weston; Johnson, Oliver

    2010-01-01

    A multi-stage automated target recognition (ATR) system has been designed to perform computer vision tasks with adequate proficiency in mimicking human vision. The system is able to detect, identify, and track targets of interest. Potential regions of interest (ROIs) are first identified by the detection stage using an Optimum Trade-off Maximum Average Correlation Height (OT-MACH) filter combined with a wavelet transform. False positives are then eliminated by the verification stage using feature extraction methods in conjunction with neural networks. Feature extraction transforms the ROIs using filtering and binning algorithms to create feature vectors. A feedforward back-propagation neural network (NN) is then trained to classify each feature vector and to remove false positives. The system parameter optimizations process has been developed to adapt to various targets and datasets. The objective was to design an efficient computer vision system that can learn to detect multiple targets in large images with unknown backgrounds. Because the target size is small relative to the image size in this problem, there are many regions of the image that could potentially contain the target. A cursory analysis of every region can be computationally efficient, but may yield too many false positives. On the other hand, a detailed analysis of every region can yield better results, but may be computationally inefficient. The multi-stage ATR system was designed to achieve an optimal balance between accuracy and computational efficiency by incorporating both models. The detection stage first identifies potential ROIs where the target may be present by performing a fast Fourier domain OT-MACH filter-based correlation. Because threshold for this stage is chosen with the goal of detecting all true positives, a number of false positives are also detected as ROIs. The verification stage then transforms the regions of interest into feature space, and eliminates false positives using an

  10. Automatic definition of targeted biological volumes for the radiotherapy applications

    International Nuclear Information System (INIS)

    Hatt, M.; Visvikis, D.; Cheze-Le-Rest, C.; Pradier, O.

    2009-01-01

    The proposed method: Fuzzy locally adaptive Bayesian (F.L.A.B.) showed its reliability and its precision on very complete collection of realistic simulated and real data. Its use in the context of radiotherapy allows to consider easily the studies implementation and scenari of dose painting or dose escalation, including in complex cases of heterogenous fixations. It is conceivable to apply F.L.A.B. on PET images with F.M.I.S.O. ( 18 F fluoro misonidazole) or F.L.T. (fluoro-L-thymidine) to complete the definition of the biological target volume. (N.C.)

  11. System for automatic x-ray-image analysis, measurement, and sorting of laser fusion targets

    International Nuclear Information System (INIS)

    Singleton, R.M.; Perkins, D.E.; Willenborg, D.L.

    1980-01-01

    This paper describes the Automatic X-Ray Image Analysis and Sorting (AXIAS) system which is designed to analyze and measure x-ray images of opaque hollow microspheres used as laser fusion targets. The x-ray images are first recorded on a high resolution film plate. The AXIAS system then digitizes and processes the images to accurately measure the target parameters and defects. The primary goals of the AXIAS system are: to provide extremely accurate and rapid measurements, to engineer a practical system for a routine production environment and to furnish the capability of automatically measuring an array of images for sorting and selection

  12. Modular Algorithm Testbed Suite (MATS): A Software Framework for Automatic Target Recognition

    Science.gov (United States)

    2017-01-01

    NAVAL SURFACE WARFARE CENTER PANAMA CITY DIVISION PANAMA CITY, FL 32407-7001 TECHNICAL REPORT NSWC PCD TR-2017-004 MODULAR ...31-01-2017 Technical Modular Algorithm Testbed Suite (MATS): A Software Framework for Automatic Target Recognition DR...flexible platform to facilitate the development and testing of ATR algorithms. To that end, NSWC PCD has created the Modular Algorithm Testbed Suite

  13. Region descriptors for automatic classification of small sea targets in infrared video

    NARCIS (Netherlands)

    Mouthaan, M.M.; Broek, S.P. van den; Hendriks, E.A.; Schwering, P.B.W.

    2011-01-01

    We evaluate the performance of different key-point detectors and region descriptors when used for automatic classification of small sea targets in infrared video. In our earlier research performed on this subject as well as in other literature, many different region descriptors have been proposed.

  14. p53 down-regulates SARS coronavirus replication and is targeted by the SARS-unique domain and PLpro via E3 ubiquitin ligase RCHY1

    Science.gov (United States)

    Ma-Lauer, Yue; Carbajo-Lozoya, Javier; Müller, Marcel A.; Deng, Wen; Lei, Jian; Meyer, Benjamin; Kusov, Yuri; von Brunn, Brigitte; Bairad, Dev Raj; Hünten, Sabine; Drosten, Christian; Hermeking, Heiko; Leonhardt, Heinrich; Mann, Matthias; Hilgenfeld, Rolf; von Brunn, Albrecht

    2016-01-01

    Highly pathogenic severe acute respiratory syndrome coronavirus (SARS-CoV) has developed strategies to inhibit host immune recognition. We identify cellular E3 ubiquitin ligase ring-finger and CHY zinc-finger domain-containing 1 (RCHY1) as an interacting partner of the viral SARS-unique domain (SUD) and papain-like protease (PLpro), and, as a consequence, the involvement of cellular p53 as antagonist of coronaviral replication. Residues 95–144 of RCHY1 and 389–652 of SUD (SUD-NM) subdomains are crucial for interaction. Association with SUD increases the stability of RCHY1 and augments RCHY1-mediated ubiquitination as well as degradation of p53. The calcium/calmodulin-dependent protein kinase II delta (CAMK2D), which normally influences RCHY1 stability by phosphorylation, also binds to SUD. In vivo phosphorylation shows that SUD does not regulate phosphorylation of RCHY1 via CAMK2D. Similarly to SUD, the PLpros from SARS-CoV, MERS-CoV, and HCoV-NL63 physically interact with and stabilize RCHY1, and thus trigger degradation of endogenous p53. The SARS-CoV papain-like protease is encoded next to SUD within nonstructural protein 3. A SUD–PLpro fusion interacts with RCHY1 more intensively and causes stronger p53 degradation than SARS-CoV PLpro alone. We show that p53 inhibits replication of infectious SARS-CoV as well as of replicons and human coronavirus NL63. Hence, human coronaviruses antagonize the viral inhibitor p53 via stabilizing RCHY1 and promoting RCHY1-mediated p53 degradation. SUD functions as an enhancer to strengthen interaction between RCHY1 and nonstructural protein 3, leading to a further increase in in p53 degradation. The significance of these findings is that down-regulation of p53 as a major player in antiviral innate immunity provides a long-sought explanation for delayed activities of respective genes. PMID:27519799

  15. Automatic Attraction of Visual Attention by Supraletter Features of Former Target Strings

    Directory of Open Access Journals (Sweden)

    Søren eKyllingsbæk

    2014-11-01

    Full Text Available Observers were trained to search for a particular horizontal string of 3 capital letters presented among similar strings consisting of exactly the same letters in different orders. The training was followed by a test in which the observers searched for a new target that was identical to one of the former distractors. The new distractor set consisted of the remaining former distractors plus the former target. On each trial, three letter-strings were displayed, which included the target string with a probability of .5. In Experiment 1, the strings were centered at different locations on the circumference of an imaginary circle around the fixation point. The training phase of Experiment 2 was similar, but in the test phase of the experiment, the strings were located in a vertical array centered on fixation, and in target-present arrays, the target always appeared at fixation. In both experiments, performance (d’ degraded on trials in which former targets were present, suggesting that the former targets automatically drew processing resources away from the current targets. Apparently, the two experiments showed automatic attraction of visual attention by supraletter features of former target strings.

  16. SAR: Stroke Authorship Recognition

    KAUST Repository

    Shaheen, Sara; Rockwood, Alyn; Ghanem, Bernard

    2015-01-01

    Are simple strokes unique to the artist or designer who renders them? If so, can this idea be used to identify authorship or to classify artistic drawings? Also, could training methods be devised to develop particular styles? To answer these questions, we propose the Stroke Authorship Recognition (SAR) approach, a novel method that distinguishes the authorship of 2D digitized drawings. SAR converts a drawing into a histogram of stroke attributes that is discriminative of authorship. We provide extensive classification experiments on a large variety of data sets, which validate SAR's ability to distinguish unique authorship of artists and designers. We also demonstrate the usefulness of SAR in several applications including the detection of fraudulent sketches, the training and monitoring of artists in learning a particular new style and the first quantitative way to measure the quality of automatic sketch synthesis tools. © 2015 The Eurographics Association and John Wiley & Sons Ltd.

  17. 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.

  18. A new type industrial total station based on target automatic collimation

    Science.gov (United States)

    Lao, Dabao; Zhou, Weihu; Ji, Rongyi; Dong, Dengfeng; Xiong, Zhi; Wei, Jiang

    2018-01-01

    In the case of industrial field measurement, the present measuring instruments work with manual operation and collimation, which give rise to low efficiency for field measurement. In order to solve the problem, a new type industrial total station is presented in this paper. The new instrument can identify and trace cooperative target automatically, in the mean time, coordinate of the target is measured in real time. For realizing the system, key technology including high precision absolutely distance measurement, small high accuracy angle measurement, target automatic collimation with vision, and quick precise controlling should be worked out. After customized system assemblage and adjustment, the new type industrial total station will be established. As the experiments demonstrated, the coordinate accuracy of the instrument is under 15ppm in the distance of 60m, which proved that the measuring system is feasible. The result showed that the total station can satisfy most industrial field measurement requirements.

  19. Scale invariant SURF detector and automatic clustering segmentation for infrared small targets detection

    Science.gov (United States)

    Zhang, Haiying; Bai, Jiaojiao; Li, Zhengjie; Liu, Yan; Liu, Kunhong

    2017-06-01

    The detection and discrimination of infrared small dim targets is a challenge in automatic target recognition (ATR), because there is no salient information of size, shape and texture. Many researchers focus on mining more discriminative information of targets in temporal-spatial. However, such information may not be available with the change of imaging environments, and the targets size and intensity keep changing in different imaging distance. So in this paper, we propose a novel research scheme using density-based clustering and backtracking strategy. In this scheme, the speeded up robust feature (SURF) detector is applied to capture candidate targets in single frame at first. And then, these points are mapped into one frame, so that target traces form a local aggregation pattern. In order to isolate the targets from noises, a newly proposed density-based clustering algorithm, fast search and find of density peak (FSFDP for short), is employed to cluster targets by the spatial intensive distribution. Two important factors of the algorithm, percent and γ , are exploited fully to determine the clustering scale automatically, so as to extract the trace with highest clutter suppression ratio. And at the final step, a backtracking algorithm is designed to detect and discriminate target trace as well as to eliminate clutter. The consistence and continuity of the short-time target trajectory in temporal-spatial is incorporated into the bounding function to speed up the pruning. Compared with several state-of-arts methods, our algorithm is more effective for the dim targets with lower signal-to clutter ratio (SCR). Furthermore, it avoids constructing the candidate target trajectory searching space, so its time complexity is limited to a polynomial level. The extensive experimental results show that it has superior performance in probability of detection (Pd) and false alarm suppressing rate aiming at variety of complex backgrounds.

  20. Staphylococcus aureus Quorum Regulator SarA Targeted Compound, 2-[(Methylaminomethyl]phenol Inhibits Biofilm and Down-Regulates Virulence Genes

    Directory of Open Access Journals (Sweden)

    P. Balamurugan

    2017-07-01

    Full Text Available Staphylococcus aureus is a widely acknowledged Gram-positive pathogen for forming biofilm and virulence gene expressions by quorum sensing (QS, a cell to cell communication process. The quorum regulator SarA of S. aureus up-regulates the expression of many virulence factors including biofilm formation to mediate pathogenesis and evasion of the host immune system in the late phases of growth. Thus, inhibiting the production or blocking SarA protein might influence the down-regulation of biofilm and virulence factors. In this context, here we have synthesized 2-[(Methylaminomethyl]phenol, which was specifically targeted toward the quorum regulator SarA through in silico approach in our previous study. The molecule has been evaluated in vitro to validate its antibiofilm activity against clinical S. aureus strains. In addition, antivirulence properties of the inhibitor were confirmed with the observation of a significant reduction in the expression of representative virulence genes like fnbA, hla and hld that are governed under S. aureus QS. Interestingly, the SarA targeted inhibitor showed negligible antimicrobial activity and markedly reduced the minimum inhibitory concentration of conventional antibiotics when used in combination making it a more attractive lead for further clinical tests.

  1. Bistatic SAR: Proof of Concept.

    Energy Technology Data Exchange (ETDEWEB)

    Yocky, David A.; Doren, Neall E.; Bacon, Terry A.; Wahl, Daniel E.; Eichel, Paul H.; Jakowatz, Charles V,; Delaplain, Gilbert G.; Dubbert, Dale F.; Tise, Bertice L.; White, Kyle R.

    2014-10-01

    Typical synthetic aperture RADAR (SAR) imaging employs a co-located RADAR transmitter and receiver. Bistatic SAR imaging separates the transmitter and receiver locations. A bistatic SAR configuration allows for the transmitter and receiver(s) to be in a variety of geometric alignments. Sandia National Laboratories (SNL) / New Mexico proposed the deployment of a ground-based RADAR receiver. This RADAR receiver was coupled with the capability of digitizing and recording the signal collected. SNL proposed the possibility of creating an image of targets the illuminating SAR observes. This document describes the developed hardware, software, bistatic SAR configuration, and its deployment to test the concept of a ground-based bistatic SAR. In the proof-of-concept experiments herein, the RADAR transmitter will be a commercial SAR satellite and the RADAR receiver will be deployed at ground level, observing and capturing RADAR ground/targets illuminated by the satellite system.

  2. 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.

  3. 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.

  4. Automatic target recognition performance losses in the presence of atmospheric and camera effects

    Science.gov (United States)

    Chen, Xiaohan; Schmid, Natalia A.

    2010-04-01

    The importance of networked automatic target recognition systems for surveillance applications is continuously increasing. Because of the requirement of a low cost and limited payload, these networks are traditionally equipped with lightweight, low-cost sensors such as electro-optical (EO) or infrared sensors. The quality of imagery acquired by these sensors critically depends on the environmental conditions, type and characteristics of sensors, and absence of occluding or concealing objects. In the past, a large number of efficient detection, tracking, and recognition algorithms have been designed to operate on imagery of good quality. However, detection and recognition limits under nonideal environmental and/or sensor-based distortions have not been carefully evaluated. We introduce a fully automatic target recognition system that involves a Haar-based detector to select potential regions of interest within images, performs adjustment of detected regions, segments potential targets using a region-based approach, identifies targets using Bessel K form-based encoding, and performs clutter rejection. We investigate the effects of environmental and camera conditions on target detection and recognition performance. Two databases are involved. One is a simulated database generated using a 3-D tool. The other database is formed by imaging 10 die-cast models of military vehicles from different elevation and orientation angles. The database contains imagery acquired both indoors and outdoors. The indoors data set is composed of clear and distorted images. The distortions include defocus blur, sided illumination, low contrast, shadows, and occlusions. All images in this database, however, have a uniform (blue) background. The indoors database is applied to evaluate the degradations of recognition performance due to camera and illumination effects. The database collected outdoors includes a real background and is much more complex to process. The numerical results

  5. An automatic controlled apparatus of target chamber for atomic spectra and level lifetime measurements

    International Nuclear Information System (INIS)

    Zhao Mengchun; Yang Zhihu

    1998-01-01

    An automatically controlled apparatus of target chamber was made to measure spectra of the excited atoms and lifetime of the excited levels. The hardware is composed of nine parts including a computer and a step-motor, while the software consists of three branch programs. The maximum movable distance of target position is 65 cm with a step-length of 8.3 μm and a precision of +- 18 μm per 2 mm. On account of simple structure and double protection, the apparatus exhibits flexibility and reliability in years service

  6. Morphological self-organizing feature map neural network with applications to automatic target recognition

    Science.gov (United States)

    Zhang, Shijun; Jing, Zhongliang; Li, Jianxun

    2005-01-01

    The rotation invariant feature of the target is obtained using the multi-direction feature extraction property of the steerable filter. Combining the morphological operation top-hat transform with the self-organizing feature map neural network, the adaptive topological region is selected. Using the erosion operation, the topological region shrinkage is achieved. The steerable filter based morphological self-organizing feature map neural network is applied to automatic target recognition of binary standard patterns and real-world infrared sequence images. Compared with Hamming network and morphological shared-weight networks respectively, the higher recognition correct rate, robust adaptability, quick training, and better generalization of the proposed method are achieved.

  7. Effects of TEL Confusers on Operator Target Acquisition Performance with SAR Imagery

    Science.gov (United States)

    1998-12-01

    efforts of everyone involved in the project; and Dr. Nick Patton, for providing assistance with several of the mathematical procedures in the document...processing known as the theory of signal detection (TSD) (Gescheider, 1985; Green & Swets, 1966; Macmillan & Creelman , 1991; Wilson, 1992). A TSD...localizations (Hacker & Ratcliff, 1979; Macmillan & Creelman , 1991). The index of bias in a target localization task provides a measure of the operator’s

  8. SAR image classification based on CNN in real and simulation datasets

    Science.gov (United States)

    Peng, Lijiang; Liu, Ming; Liu, Xiaohua; Dong, Liquan; Hui, Mei; Zhao, Yuejin

    2018-04-01

    Convolution neural network (CNN) has made great success in image classification tasks. Even in the field of synthetic aperture radar automatic target recognition (SAR-ATR), state-of-art results has been obtained by learning deep representation of features on the MSTAR benchmark. However, the raw data of MSTAR have shortcomings in training a SAR-ATR model because of high similarity in background among the SAR images of each kind. This indicates that the CNN would learn the hierarchies of features of backgrounds as well as the targets. To validate the influence of the background, some other SAR images datasets have been made which contains the simulation SAR images of 10 manufactured targets such as tank and fighter aircraft, and the backgrounds of simulation SAR images are sampled from the whole original MSTAR data. The simulation datasets contain the dataset that the backgrounds of each kind images correspond to the one kind of backgrounds of MSTAR targets or clutters and the dataset that each image shares the random background of whole MSTAR targets or clutters. In addition, mixed datasets of MSTAR and simulation datasets had been made to use in the experiments. The CNN architecture proposed in this paper are trained on all datasets mentioned above. The experimental results shows that the architecture can get high performances on all datasets even the backgrounds of the images are miscellaneous, which indicates the architecture can learn a good representation of the targets even though the drastic changes on background.

  9. Study of an automatized experimental device for the irradiation of a radioactive target

    International Nuclear Information System (INIS)

    Claverie, G.

    1996-01-01

    In order to solve the enigma of solar neutrinos, a team of physicians of the nuclear research center of Bordeaux-Gradignan and of the center of nuclear spectroscopy and mass spectroscopy of Orsay (France) decided to measure again the cross section of the beryllium-proton nuclear reaction at the lowest possible energies. This measurement requires the design of an automatized experimental device to irradiate in a specific way a beryllium target with an accelerated proton beam. The aim of this work is the study of such a device for an energy range of 800 to 300 KeV. This device comprises a particle multi-detector and a shutter for the irradiation of the target and the counting of the reaction products according to a programmable time sequence. The advantage of this setup is to allow an important bombardment of the target and to ensure its cooling. This device is automatically controlled thanks to a micro-controller, actuators (step motors and electrostatic deflector). It includes some beam diagnosis elements controlled by step motors and a target temperature monitoring system controlling a safety valve. The management of the experiment cell vacuum has led to the design of a vacuum monitor allowing the precise follow up of the vacuum and the control of the safety valves of the device. The nuclear instrumentation necessary to be implemented for this measurement is also presented. (J.S.)

  10. 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.

  11. The pan phosphoinositide 3-kinase/mammalian target of rapamycin inhibitor SAR245409 (voxtalisib/XL765) blocks survival, adhesion and proliferation of primary chronic lymphocytic leukemia cells.

    Science.gov (United States)

    Thijssen, R; Ter Burg, J; van Bochove, G G W; de Rooij, M F M; Kuil, A; Jansen, M H; Kuijpers, T W; Baars, J W; Virone-Oddos, A; Spaargaren, M; Egile, C; van Oers, M H J; Eldering, E; Kersten, M J; Kater, A P

    2016-02-01

    The phosphoinositide 3-kinases (PI3Ks) are critical components of the B-cell receptor (BCR) pathway and have an important role in the pathobiology of chronic lymphocytic leukemia (CLL). Inhibitors of PI3Kδ block BCR-mediated cross-talk between CLL cells and the lymph node microenvironment and provide significant clinical benefit to CLL patients. However, the PI3Kδ inhibitors applied thus far have limited direct impact on leukemia cell survival and thus are unlikely to eradicate the disease. The use of inhibitors of multiple isoforms of PI3K might lead to deeper remissions. Here we demonstrate that the pan-PI3K/mammalian target of rapamycin inhibitor SAR245409 (voxtalisib/XL765) was more pro-apoptotic to CLL cells--irrespective of their ATM/p53 status--than PI3Kα or PI3Kδ isoform selective inhibitors. Furthermore, SAR245409 blocked CLL survival, adhesion and proliferation. Moreover, SAR245409 was a more potent inhibitor of T-cell-mediated production of cytokines, which support CLL survival. Taken together, our in vitro data provide a rationale for the evaluation of a pan-PI3K inhibitor in CLL patients.

  12. SARS - Diagnosis

    Indian Academy of Sciences (India)

    SARS - Diagnosis. Mainly by exclusion of known causes of atypical pneumonia; * X ray Chest; * PCR on body fluids- primers defined by WHO centres available from website.-ve result does not exclude SARS. * Sequencing of amplicons; * Viral Cultures – demanding; * Antibody tests.

  13. Atlas-based automatic segmentation of head and neck organs at risk and nodal target volumes: a clinical validation.

    Science.gov (United States)

    Daisne, Jean-François; Blumhofer, Andreas

    2013-06-26

    Intensity modulated radiotherapy for head and neck cancer necessitates accurate definition of organs at risk (OAR) and clinical target volumes (CTV). This crucial step is time consuming and prone to inter- and intra-observer variations. Automatic segmentation by atlas deformable registration may help to reduce time and variations. We aim to test a new commercial atlas algorithm for automatic segmentation of OAR and CTV in both ideal and clinical conditions. The updated Brainlab automatic head and neck atlas segmentation was tested on 20 patients: 10 cN0-stages (ideal population) and 10 unselected N-stages (clinical population). Following manual delineation of OAR and CTV, automatic segmentation of the same set of structures was performed and afterwards manually corrected. Dice Similarity Coefficient (DSC), Average Surface Distance (ASD) and Maximal Surface Distance (MSD) were calculated for "manual to automatic" and "manual to corrected" volumes comparisons. In both groups, automatic segmentation saved about 40% of the corresponding manual segmentation time. This effect was more pronounced for OAR than for CTV. The edition of the automatically obtained contours significantly improved DSC, ASD and MSD. Large distortions of normal anatomy or lack of iodine contrast were the limiting factors. The updated Brainlab atlas-based automatic segmentation tool for head and neck Cancer patients is timesaving but still necessitates review and corrections by an expert.

  14. Atlas-based automatic segmentation of head and neck organs at risk and nodal target volumes: a clinical validation

    International Nuclear Information System (INIS)

    Daisne, Jean-François; Blumhofer, Andreas

    2013-01-01

    Intensity modulated radiotherapy for head and neck cancer necessitates accurate definition of organs at risk (OAR) and clinical target volumes (CTV). This crucial step is time consuming and prone to inter- and intra-observer variations. Automatic segmentation by atlas deformable registration may help to reduce time and variations. We aim to test a new commercial atlas algorithm for automatic segmentation of OAR and CTV in both ideal and clinical conditions. The updated Brainlab automatic head and neck atlas segmentation was tested on 20 patients: 10 cN0-stages (ideal population) and 10 unselected N-stages (clinical population). Following manual delineation of OAR and CTV, automatic segmentation of the same set of structures was performed and afterwards manually corrected. Dice Similarity Coefficient (DSC), Average Surface Distance (ASD) and Maximal Surface Distance (MSD) were calculated for “manual to automatic” and “manual to corrected” volumes comparisons. In both groups, automatic segmentation saved about 40% of the corresponding manual segmentation time. This effect was more pronounced for OAR than for CTV. The edition of the automatically obtained contours significantly improved DSC, ASD and MSD. Large distortions of normal anatomy or lack of iodine contrast were the limiting factors. The updated Brainlab atlas-based automatic segmentation tool for head and neck Cancer patients is timesaving but still necessitates review and corrections by an expert

  15. A multimodality segmentation framework for automatic target delineation in head and neck radiotherapy

    Energy Technology Data Exchange (ETDEWEB)

    Yang, Jinzhong; Aristophanous, Michalis, E-mail: MAristophanous@mdanderson.org [Department of Radiation Physics, The University of Texas MD Anderson Cancer Center, Houston, Texas 77030 (United States); Beadle, Beth M.; Garden, Adam S. [Department of Radiation Oncology, The University of Texas MD Anderson Cancer Center, Houston, Texas 77030 (United States); Schwartz, David L. [Department of Radiation Oncology, The University of Texas Southwestern Medical Center, Dallas, Texas 75390 (United States)

    2015-09-15

    Purpose: To develop an automatic segmentation algorithm integrating imaging information from computed tomography (CT), positron emission tomography (PET), and magnetic resonance imaging (MRI) to delineate target volume in head and neck cancer radiotherapy. Methods: Eleven patients with unresectable disease at the tonsil or base of tongue who underwent MRI, CT, and PET/CT within two months before the start of radiotherapy or chemoradiotherapy were recruited for the study. For each patient, PET/CT and T1-weighted contrast MRI scans were first registered to the planning CT using deformable and rigid registration, respectively, to resample the PET and magnetic resonance (MR) images to the planning CT space. A binary mask was manually defined to identify the tumor area. The resampled PET and MR images, the planning CT image, and the binary mask were fed into the automatic segmentation algorithm for target delineation. The algorithm was based on a multichannel Gaussian mixture model and solved using an expectation–maximization algorithm with Markov random fields. To evaluate the algorithm, we compared the multichannel autosegmentation with an autosegmentation method using only PET images. The physician-defined gross tumor volume (GTV) was used as the “ground truth” for quantitative evaluation. Results: The median multichannel segmented GTV of the primary tumor was 15.7 cm{sup 3} (range, 6.6–44.3 cm{sup 3}), while the PET segmented GTV was 10.2 cm{sup 3} (range, 2.8–45.1 cm{sup 3}). The median physician-defined GTV was 22.1 cm{sup 3} (range, 4.2–38.4 cm{sup 3}). The median difference between the multichannel segmented and physician-defined GTVs was −10.7%, not showing a statistically significant difference (p-value = 0.43). However, the median difference between the PET segmented and physician-defined GTVs was −19.2%, showing a statistically significant difference (p-value =0.0037). The median Dice similarity coefficient between the multichannel segmented

  16. A multimodality segmentation framework for automatic target delineation in head and neck radiotherapy.

    Science.gov (United States)

    Yang, Jinzhong; Beadle, Beth M; Garden, Adam S; Schwartz, David L; Aristophanous, Michalis

    2015-09-01

    To develop an automatic segmentation algorithm integrating imaging information from computed tomography (CT), positron emission tomography (PET), and magnetic resonance imaging (MRI) to delineate target volume in head and neck cancer radiotherapy. Eleven patients with unresectable disease at the tonsil or base of tongue who underwent MRI, CT, and PET/CT within two months before the start of radiotherapy or chemoradiotherapy were recruited for the study. For each patient, PET/CT and T1-weighted contrast MRI scans were first registered to the planning CT using deformable and rigid registration, respectively, to resample the PET and magnetic resonance (MR) images to the planning CT space. A binary mask was manually defined to identify the tumor area. The resampled PET and MR images, the planning CT image, and the binary mask were fed into the automatic segmentation algorithm for target delineation. The algorithm was based on a multichannel Gaussian mixture model and solved using an expectation-maximization algorithm with Markov random fields. To evaluate the algorithm, we compared the multichannel autosegmentation with an autosegmentation method using only PET images. The physician-defined gross tumor volume (GTV) was used as the "ground truth" for quantitative evaluation. The median multichannel segmented GTV of the primary tumor was 15.7 cm(3) (range, 6.6-44.3 cm(3)), while the PET segmented GTV was 10.2 cm(3) (range, 2.8-45.1 cm(3)). The median physician-defined GTV was 22.1 cm(3) (range, 4.2-38.4 cm(3)). The median difference between the multichannel segmented and physician-defined GTVs was -10.7%, not showing a statistically significant difference (p-value = 0.43). However, the median difference between the PET segmented and physician-defined GTVs was -19.2%, showing a statistically significant difference (p-value =0.0037). The median Dice similarity coefficient between the multichannel segmented and physician-defined GTVs was 0.75 (range, 0.55-0.84), and the

  17. A multimodality segmentation framework for automatic target delineation in head and neck radiotherapy

    International Nuclear Information System (INIS)

    Yang, Jinzhong; Aristophanous, Michalis; Beadle, Beth M.; Garden, Adam S.; Schwartz, David L.

    2015-01-01

    Purpose: To develop an automatic segmentation algorithm integrating imaging information from computed tomography (CT), positron emission tomography (PET), and magnetic resonance imaging (MRI) to delineate target volume in head and neck cancer radiotherapy. Methods: Eleven patients with unresectable disease at the tonsil or base of tongue who underwent MRI, CT, and PET/CT within two months before the start of radiotherapy or chemoradiotherapy were recruited for the study. For each patient, PET/CT and T1-weighted contrast MRI scans were first registered to the planning CT using deformable and rigid registration, respectively, to resample the PET and magnetic resonance (MR) images to the planning CT space. A binary mask was manually defined to identify the tumor area. The resampled PET and MR images, the planning CT image, and the binary mask were fed into the automatic segmentation algorithm for target delineation. The algorithm was based on a multichannel Gaussian mixture model and solved using an expectation–maximization algorithm with Markov random fields. To evaluate the algorithm, we compared the multichannel autosegmentation with an autosegmentation method using only PET images. The physician-defined gross tumor volume (GTV) was used as the “ground truth” for quantitative evaluation. Results: The median multichannel segmented GTV of the primary tumor was 15.7 cm"3 (range, 6.6–44.3 cm"3), while the PET segmented GTV was 10.2 cm"3 (range, 2.8–45.1 cm"3). The median physician-defined GTV was 22.1 cm"3 (range, 4.2–38.4 cm"3). The median difference between the multichannel segmented and physician-defined GTVs was −10.7%, not showing a statistically significant difference (p-value = 0.43). However, the median difference between the PET segmented and physician-defined GTVs was −19.2%, showing a statistically significant difference (p-value =0.0037). The median Dice similarity coefficient between the multichannel segmented and physician-defined GTVs was

  18. Robust Automatic Target Recognition via HRRP Sequence Based on Scatterer Matching

    Directory of Open Access Journals (Sweden)

    Yuan Jiang

    2018-02-01

    Full Text Available High resolution range profile (HRRP plays an important role in wideband radar automatic target recognition (ATR. In order to alleviate the sensitivity to clutter and target aspect, employing a sequence of HRRP is a promising approach to enhance the ATR performance. In this paper, a novel HRRP sequence-matching method based on singular value decomposition (SVD is proposed. First, the HRRP sequence is decoupled into the angle space and the range space via SVD, which correspond to the span of the left and the right singular vectors, respectively. Second, atomic norm minimization (ANM is utilized to estimate dominant scatterers in the range space and the Hausdorff distance is employed to measure the scatter similarity between the test and training data. Next, the angle space similarity between the test and training data is evaluated based on the left singular vector correlations. Finally, the range space matching result and the angle space correlation are fused with the singular values as weights. Simulation and outfield experimental results demonstrate that the proposed matching metric is a robust similarity measure for HRRP sequence recognition.

  19. A comparative study of automatic image segmentation algorithms for target tracking in MR‐IGRT

    Science.gov (United States)

    Feng, Yuan; Kawrakow, Iwan; Olsen, Jeff; Parikh, Parag J.; Noel, Camille; Wooten, Omar; Du, Dongsu; Mutic, Sasa

    2016-01-01

    On‐board magnetic resonance (MR) image guidance during radiation therapy offers the potential for more accurate treatment delivery. To utilize the real‐time image information, a crucial prerequisite is the ability to successfully segment and track regions of interest (ROI). The purpose of this work is to evaluate the performance of different segmentation algorithms using motion images (4 frames per second) acquired using a MR image‐guided radiotherapy (MR‐IGRT) system. Manual contours of the kidney, bladder, duodenum, and a liver tumor by an experienced radiation oncologist were used as the ground truth for performance evaluation. Besides the manual segmentation, images were automatically segmented using thresholding, fuzzy k‐means (FKM), k‐harmonic means (KHM), and reaction‐diffusion level set evolution (RD‐LSE) algorithms, as well as the tissue tracking algorithm provided by the ViewRay treatment planning and delivery system (VR‐TPDS). The performance of the five algorithms was evaluated quantitatively by comparing with the manual segmentation using the Dice coefficient and target registration error (TRE) measured as the distance between the centroid of the manual ROI and the centroid of the automatically segmented ROI. All methods were able to successfully segment the bladder and the kidney, but only FKM, KHM, and VR‐TPDS were able to segment the liver tumor and the duodenum. The performance of the thresholding, FKM, KHM, and RD‐LSE algorithms degraded as the local image contrast decreased, whereas the performance of the VP‐TPDS method was nearly independent of local image contrast due to the reference registration algorithm. For segmenting high‐contrast images (i.e., kidney), the thresholding method provided the best speed (<1 ms) with a satisfying accuracy (Dice=0.95). When the image contrast was low, the VR‐TPDS method had the best automatic contour. Results suggest an image quality determination procedure before segmentation and

  20. A comparative study of automatic image segmentation algorithms for target tracking in MR-IGRT.

    Science.gov (United States)

    Feng, Yuan; Kawrakow, Iwan; Olsen, Jeff; Parikh, Parag J; Noel, Camille; Wooten, Omar; Du, Dongsu; Mutic, Sasa; Hu, Yanle

    2016-03-01

    On-board magnetic resonance (MR) image guidance during radiation therapy offers the potential for more accurate treatment delivery. To utilize the real-time image information, a crucial prerequisite is the ability to successfully segment and track regions of interest (ROI). The purpose of this work is to evaluate the performance of different segmentation algorithms using motion images (4 frames per second) acquired using a MR image-guided radiotherapy (MR-IGRT) system. Manual contours of the kidney, bladder, duodenum, and a liver tumor by an experienced radiation oncologist were used as the ground truth for performance evaluation. Besides the manual segmentation, images were automatically segmented using thresholding, fuzzy k-means (FKM), k-harmonic means (KHM), and reaction-diffusion level set evolution (RD-LSE) algorithms, as well as the tissue tracking algorithm provided by the ViewRay treatment planning and delivery system (VR-TPDS). The performance of the five algorithms was evaluated quantitatively by comparing with the manual segmentation using the Dice coefficient and target registration error (TRE) measured as the distance between the centroid of the manual ROI and the centroid of the automatically segmented ROI. All methods were able to successfully segment the bladder and the kidney, but only FKM, KHM, and VR-TPDS were able to segment the liver tumor and the duodenum. The performance of the thresholding, FKM, KHM, and RD-LSE algorithms degraded as the local image contrast decreased, whereas the performance of the VP-TPDS method was nearly independent of local image contrast due to the reference registration algorithm. For segmenting high-contrast images (i.e., kidney), the thresholding method provided the best speed (<1 ms) with a satisfying accuracy (Dice=0.95). When the image contrast was low, the VR-TPDS method had the best automatic contour. Results suggest an image quality determination procedure before segmentation and a combination of different

  1. Convolutional neural network using generated data for SAR ATR with limited samples

    Science.gov (United States)

    Cong, Longjian; Gao, Lei; Zhang, Hui; Sun, Peng

    2018-03-01

    Being able to adapt all weather at all times, it has been a hot research topic that using Synthetic Aperture Radar(SAR) for remote sensing. Despite all the well-known advantages of SAR, it is hard to extract features because of its unique imaging methodology, and this challenge attracts the research interest of traditional Automatic Target Recognition(ATR) methods. With the development of deep learning technologies, convolutional neural networks(CNNs) give us another way out to detect and recognize targets, when a huge number of samples are available, but this premise is often not hold, when it comes to monitoring a specific type of ships. In this paper, we propose a method to enhance the performance of Faster R-CNN with limited samples to detect and recognize ships in SAR images.

  2. Assisting People with Multiple Disabilities by Improving Their Computer Pointing Efficiency with an Automatic Target Acquisition Program

    Science.gov (United States)

    Shih, Ching-Hsiang; Shih, Ching-Tien; Peng, Chin-Ling

    2011-01-01

    This study evaluated whether two people with multiple disabilities would be able to improve their pointing performance through an Automatic Target Acquisition Program (ATAP) and a newly developed mouse driver (i.e. a new mouse driver replaces standard mouse driver, and is able to monitor mouse movement and intercept click action). Initially, both…

  3. A Compact Methodology to Understand, Evaluate, and Predict the Performance of Automatic Target Recognition

    Science.gov (United States)

    Li, Yanpeng; Li, Xiang; Wang, Hongqiang; Chen, Yiping; Zhuang, Zhaowen; Cheng, Yongqiang; Deng, Bin; Wang, Liandong; Zeng, Yonghu; Gao, Lei

    2014-01-01

    This paper offers a compacted mechanism to carry out the performance evaluation work for an automatic target recognition (ATR) system: (a) a standard description of the ATR system's output is suggested, a quantity to indicate the operating condition is presented based on the principle of feature extraction in pattern recognition, and a series of indexes to assess the output in different aspects are developed with the application of statistics; (b) performance of the ATR system is interpreted by a quality factor based on knowledge of engineering mathematics; (c) through a novel utility called “context-probability” estimation proposed based on probability, performance prediction for an ATR system is realized. The simulation result shows that the performance of an ATR system can be accounted for and forecasted by the above-mentioned measures. Compared to existing technologies, the novel method can offer more objective performance conclusions for an ATR system. These conclusions may be helpful in knowing the practical capability of the tested ATR system. At the same time, the generalization performance of the proposed method is good. PMID:24967605

  4. Automatic gas-levitation system for vacuum deposition of laser-fusion targets

    International Nuclear Information System (INIS)

    Jordan, C.W.; Cameron, G.R.; Krenik, R.M.; Crane, J.K.

    1981-01-01

    An improved simple system has been developed to gas-levitate microspheres during vacuum-deposition processes. The automatic operation relies on two effects: a lateral stabilizing force provided by a centering-ring; and an automatically incremented gas metering system to offset weight increases during coating

  5. Automatic online adaptive radiation therapy techniques for targets with significant shape change: a feasibility study

    International Nuclear Information System (INIS)

    Court, Laurence E; Tishler, Roy B; Petit, Joshua; Cormack, Robert; Chin Lee

    2006-01-01

    This work looks at the feasibility of an online adaptive radiation therapy concept that would detect the daily position and shape of the patient, and would then correct the daily treatment to account for any changes compared with planning position. In particular, it looks at the possibility of developing algorithms to correct for large complicated shape change. For co-planar beams, the dose in an axial plane is approximately associated with the positions of a single multi-leaf collimator (MLC) pair. We start with a primary plan, and automatically generate several secondary plans with gantry angles offset by regular increments. MLC sequences for each plan are calculated keeping monitor units (MUs) and number of segments constant for a given beam (fluences are different). Bulk registration (3D) of planning and daily CT images gives global shifts. Slice-by-slice (2D) registration gives local shifts and rotations about the longitudinal axis for each axial slice. The daily MLC sequence is then created for each axial slice/MLC leaf pair combination, by taking the MLC positions from the pre-calculated plan with the nearest rotation, and shifting using a beam's-eye-view calculation to account for local linear shifts. A planning study was carried out using two head and neck region MR images of a healthy volunteer which were contoured to simulate a base-of-tongue treatment: one with the head straight (used to simulate the planning image) and the other with the head tilted to the left (the daily image). Head and neck treatment was chosen to evaluate this technique because of its challenging nature, with varying internal and external contours, and multiple degrees of freedom. Shape change was significant: on a slice-by-slice basis, local rotations in the daily image varied from 2 to 31 deg, and local shifts ranged from -0.2 to 0.5 cm and -0.4 to 0.0 cm in right-left and posterior-anterior directions, respectively. The adapted treatment gave reasonable target coverage (100%, 90

  6. Estimating Elevation Angles From SAR Crosstalk

    Science.gov (United States)

    Freeman, Anthony

    1994-01-01

    Scheme for processing polarimetric synthetic-aperture-radar (SAR) image data yields estimates of elevation angles along radar beam to target resolution cells. By use of estimated elevation angles, measured distances along radar beam to targets (slant ranges), and measured altitude of aircraft carrying SAR equipment, one can estimate height of target terrain in each resolution cell. Monopulselike scheme yields low-resolution topographical data.

  7. AUTOMATIC SHAPE-BASED TARGET EXTRACTION FOR CLOSE-RANGE PHOTOGRAMMETRY

    Directory of Open Access Journals (Sweden)

    X. Guo

    2016-06-01

    Full Text Available In order to perform precise identification and location of artificial coded targets in natural scenes, a novel design of circle-based coded target and the corresponding coarse-fine extraction algorithm are presented. The designed target separates the target box and coding box totally and owns an advantage of rotation invariance. Based on the original target, templates are prepared by three geometric transformations and are used as the input of shape-based template matching. Finally, region growing and parity check methods are used to extract the coded targets as final results. No human involvement is required except for the preparation of templates and adjustment of thresholds in the beginning, which is conducive to the automation of close-range photogrammetry. The experimental results show that the proposed recognition method for the designed coded target is robust and accurate.

  8. Combined DEM Extration Method from StereoSAR and InSAR

    Science.gov (United States)

    Zhao, Z.; Zhang, J. X.; Duan, M. Y.; Huang, G. M.; Yang, S. C.

    2015-06-01

    A pair of SAR images acquired from different positions can be used to generate digital elevation model (DEM). Two techniques exploiting this characteristic have been introduced: stereo SAR and interferometric SAR. They permit to recover the third dimension (topography) and, at the same time, to identify the absolute position (geolocation) of pixels included in the imaged area, thus allowing the generation of DEMs. In this paper, StereoSAR and InSAR combined adjustment model are constructed, and unify DEM extraction from InSAR and StereoSAR into the same coordinate system, and then improve three dimensional positioning accuracy of the target. We assume that there are four images 1, 2, 3 and 4. One pair of SAR images 1,2 meet the required conditions for InSAR technology, while the other pair of SAR images 3,4 can form stereo image pairs. The phase model is based on InSAR rigorous imaging geometric model. The master image 1 and the slave image 2 will be used in InSAR processing, but the slave image 2 is only used in the course of establishment, and the pixels of the slave image 2 are relevant to the corresponding pixels of the master image 1 through image coregistration coefficient, and it calculates the corresponding phase. It doesn't require the slave image in the construction of the phase model. In Range-Doppler (RD) model, the range equation and Doppler equation are a function of target geolocation, while in the phase equation, the phase is also a function of target geolocation. We exploit combined adjustment model to deviation of target geolocation, thus the problem of target solution is changed to solve three unkonwns through seven equations. The model was tested for DEM extraction under spaceborne InSAR and StereoSAR data and compared with InSAR and StereoSAR methods respectively. The results showed that the model delivered a better performance on experimental imagery and can be used for DEM extraction applications.

  9. A comparison of SAR ATR performance with information theoretic predictions

    Science.gov (United States)

    Blacknell, David

    2003-09-01

    Performance assessment of automatic target detection and recognition algorithms for SAR systems (or indeed any other sensors) is essential if the military utility of the system / algorithm mix is to be quantified. This is a relatively straightforward task if extensive trials data from an existing system is used. However, a crucial requirement is to assess the potential performance of novel systems as a guide to procurement decisions. This task is no longer straightforward since a hypothetical system cannot provide experimental trials data. QinetiQ has previously developed a theoretical technique for classification algorithm performance assessment based on information theory. The purpose of the study presented here has been to validate this approach. To this end, experimental SAR imagery of targets has been collected using the QinetiQ Enhanced Surveillance Radar to allow algorithm performance assessments as a number of parameters are varied. In particular, performance comparisons can be made for (i) resolutions up to 0.1m, (ii) single channel versus polarimetric (iii) targets in the open versus targets in scrubland and (iv) use versus non-use of camouflage. The change in performance as these parameters are varied has been quantified from the experimental imagery whilst the information theoretic approach has been used to predict the expected variation of performance with parameter value. A comparison of these measured and predicted assessments has revealed the strengths and weaknesses of the theoretical technique as will be discussed in the paper.

  10. Generation and assessment of turntable SAR data for the support of ATR development

    Science.gov (United States)

    Cohen, Marvin N.; Showman, Gregory A.; Sangston, K. James; Sylvester, Vincent B.; Gostin, Lamar; Scheer, C. Ruby

    1998-10-01

    Inverse synthetic aperture radar (ISAR) imaging on a turntable-tower test range permits convenient generation of high resolution two-dimensional images of radar targets under controlled conditions for testing SAR image processing and for supporting automatic target recognition (ATR) algorithm development. However, turntable ISAR images are often obtained under near-field geometries and hence may suffer geometric distortions not present in airborne SAR images. In this paper, turntable data collected at Georgia Tech's Electromagnetic Test Facility are used to begin to assess the utility of two- dimensional ISAR imaging algorithms in forming images to support ATR development. The imaging algorithms considered include a simple 2D discrete Fourier transform (DFT), a 2-D DFT with geometric correction based on image domain resampling, and a computationally-intensive geometric matched filter solution. Images formed with the various algorithms are used to develop ATR templates, which are then compared with an eye toward utilization in an ATR algorithm.

  11. SAR and LIDAR fusion: experiments and applications

    Science.gov (United States)

    Edwards, Matthew C.; Zaugg, Evan C.; Bradley, Joshua P.; Bowden, Ryan D.

    2013-05-01

    In recent years ARTEMIS, Inc. has developed a series of compact, versatile Synthetic Aperture Radar (SAR) systems which have been operated on a variety of small manned and unmanned aircraft. The multi-frequency-band SlimSAR has demonstrated a variety of capabilities including maritime and littoral target detection, ground moving target indication, polarimetry, interferometry, change detection, and foliage penetration. ARTEMIS also continues to build upon the radar's capabilities through fusion with other sensors, such as electro-optical and infrared camera gimbals and light detection and ranging (LIDAR) devices. In this paper we focus on experiments and applications employing SAR and LIDAR fusion. LIDAR is similar to radar in that it transmits a signal which, after being reflected or scattered by a target area, is recorded by the sensor. The differences are that a LIDAR uses a laser as a transmitter and optical sensors as a receiver, and the wavelengths used exhibit a very different scattering phenomenology than the microwaves used in radar, making SAR and LIDAR good complementary technologies. LIDAR is used in many applications including agriculture, archeology, geo-science, and surveying. Some typical data products include digital elevation maps of a target area and features and shapes extracted from the data. A set of experiments conducted to demonstrate the fusion of SAR and LIDAR data include a LIDAR DEM used in accurately processing the SAR data of a high relief area (mountainous, urban). Also, feature extraction is used in improving geolocation accuracy of the SAR and LIDAR data.

  12. Automatic Target Recognition in Synthetic Aperture Sonar Images Based on Geometrical Feature Extraction

    Directory of Open Access Journals (Sweden)

    J. Del Rio Vera

    2009-01-01

    Full Text Available This paper presents a new supervised classification approach for automated target recognition (ATR in SAS images. The recognition procedure starts with a novel segmentation stage based on the Hilbert transform. A number of geometrical features are then extracted and used to classify observed objects against a previously compiled database of target and non-target features. The proposed approach has been tested on a set of 1528 simulated images created by the NURC SIGMAS sonar model, achieving up to 95% classification accuracy.

  13. Large-scale automatic extraction of side effects associated with targeted anticancer drugs from full-text oncological articles.

    Science.gov (United States)

    Xu, Rong; Wang, QuanQiu

    2015-06-01

    Targeted anticancer drugs such as imatinib, trastuzumab and erlotinib dramatically improved treatment outcomes in cancer patients, however, these innovative agents are often associated with unexpected side effects. The pathophysiological mechanisms underlying these side effects are not well understood. The availability of a comprehensive knowledge base of side effects associated with targeted anticancer drugs has the potential to illuminate complex pathways underlying toxicities induced by these innovative drugs. While side effect association knowledge for targeted drugs exists in multiple heterogeneous data sources, published full-text oncological articles represent an important source of pivotal, investigational, and even failed trials in a variety of patient populations. In this study, we present an automatic process to extract targeted anticancer drug-associated side effects (drug-SE pairs) from a large number of high profile full-text oncological articles. We downloaded 13,855 full-text articles from the Journal of Oncology (JCO) published between 1983 and 2013. We developed text classification, relationship extraction, signaling filtering, and signal prioritization algorithms to extract drug-SE pairs from downloaded articles. We extracted a total of 26,264 drug-SE pairs with an average precision of 0.405, a recall of 0.899, and an F1 score of 0.465. We show that side effect knowledge from JCO articles is largely complementary to that from the US Food and Drug Administration (FDA) drug labels. Through integrative correlation analysis, we show that targeted drug-associated side effects positively correlate with their gene targets and disease indications. In conclusion, this unique database that we built from a large number of high-profile oncological articles could facilitate the development of computational models to understand toxic effects associated with targeted anticancer drugs. Copyright © 2015 Elsevier Inc. All rights reserved.

  14. Infrared variation reduction by simultaneous background suppression and target contrast enhancement for deep convolutional neural network-based automatic target recognition

    Science.gov (United States)

    Kim, Sungho

    2017-06-01

    Automatic target recognition (ATR) is a traditionally challenging problem in military applications because of the wide range of infrared (IR) image variations and the limited number of training images. IR variations are caused by various three-dimensional target poses, noncooperative weather conditions (fog and rain), and difficult target acquisition environments. Recently, deep convolutional neural network-based approaches for RGB images (RGB-CNN) showed breakthrough performance in computer vision problems, such as object detection and classification. The direct use of RGB-CNN to the IR ATR problem fails to work because of the IR database problems (limited database size and IR image variations). An IR variation-reduced deep CNN (IVR-CNN) to cope with the problems is presented. The problem of limited IR database size is solved by a commercial thermal simulator (OKTAL-SE). The second problem of IR variations is mitigated by the proposed shifted ramp function-based intensity transformation. This can suppress the background and enhance the target contrast simultaneously. The experimental results on the synthesized IR images generated by the thermal simulator (OKTAL-SE) validated the feasibility of IVR-CNN for military ATR applications.

  15. Sparse Representation Based SAR Vehicle Recognition along with Aspect Angle

    Directory of Open Access Journals (Sweden)

    Xiangwei Xing

    2014-01-01

    Full Text Available As a method of representing the test sample with few training samples from an overcomplete dictionary, sparse representation classification (SRC has attracted much attention in synthetic aperture radar (SAR automatic target recognition (ATR recently. In this paper, we develop a novel SAR vehicle recognition method based on sparse representation classification along with aspect information (SRCA, in which the correlation between the vehicle’s aspect angle and the sparse representation vector is exploited. The detailed procedure presented in this paper can be summarized as follows. Initially, the sparse representation vector of a test sample is solved by sparse representation algorithm with a principle component analysis (PCA feature-based dictionary. Then, the coefficient vector is projected onto a sparser one within a certain range of the vehicle’s aspect angle. Finally, the vehicle is classified into a certain category that minimizes the reconstruction error with the novel sparse representation vector. Extensive experiments are conducted on the moving and stationary target acquisition and recognition (MSTAR dataset and the results demonstrate that the proposed method performs robustly under the variations of depression angle and target configurations, as well as incomplete observation.

  16. Stereographic Targeting in Prostate Radiotherapy: Speed and Precision by Daily Automatic Positioning Corrections Using Kilovoltage/Megavoltage Image Pairs

    International Nuclear Information System (INIS)

    Mutanga, Theodore F.; Boer, Hans C.J. de; Wielen, Gerard J. van der; Wentzler, Davy; Barnhoorn, Jaco; Incrocci, Luca; Heijmen, Ben J.M.

    2008-01-01

    Purpose: A fully automated, fast, on-line prostate repositioning scheme using implanted markers, kilovoltage/megavoltage imaging, and remote couch movements has been developed and clinically applied. The initial clinical results of this stereographic targeting (SGT) method, as well as phantom evaluations, are presented. Methods and Materials: Using the SGT method, portal megavoltage images are acquired with the first two to six monitor units of a treatment beam, immediately followed by acquisition of an orthogonal kilovoltage image without gantry motion. The image pair is automatically analyzed to obtain the marker positions and three-dimensional prostate displacement and rotation. Remote control couch shifts are applied to correct for the displacement. The SGT performance was measured using both phantom images and images from 10 prostate cancer patients treated using SGT. Results: With phantom measurements, the accuracy of SGT was 0.5, 0.2, and 0.3 mm (standard deviation [SD]) for the left-right, craniocaudal, and anteroposterior directions, respectively, for translations and 0.5 o (SD) for the rotations around all axes. Clinically, the success rate for automatic marker detection was 99.5%, and the accuracy was 0.3, 0.5 and 0.8 mm (SD) in the left-right, craniocaudal, and anteroposterior axes. The SDs of the systematic center-of-mass positioning errors (Σ) were reduced from 4.0 mm to <0.5 mm for all axes. The corresponding SD of the random (σ) errors was reduced from 3.0 to <0.8 mm. These small residual errors were achieved with a treatment time extension of <1 min. Conclusion: Stereographic targeting yields systematic and random prostate positioning errors of <1 mm with <1 min of added treatment time

  17. Automatic detection of the unknown number point targets in FMICW radar signals

    Czech Academy of Sciences Publication Activity Database

    Rejfek, L.; Mošna, Zbyšek; Beran, L.; Fišer, O.; Dobrovolný, M.

    2017-01-01

    Roč. 4, č. 11 (2017), s. 116-120 ISSN 2313-626X R&D Projects: GA ČR(CZ) GA15-24688S Institutional support: RVO:68378289 Keywords : FMICW radar * 2D FFT * signal filtration * taraget detection * target parameter estimation Subject RIV: DG - Athmosphere Sciences, Meteorology OBOR OECD: Meteorology and atmospheric sciences http://science-gate.com/IJAAS/Articles/2017-4-11/18%202017-4-11-pp.116-120.pdf

  18. Keynote presentation : SAR systems

    NARCIS (Netherlands)

    Halsema, D. van; Otten, M.P.G.; Maas, A.P.M.; Bolt, R.J.; Anitori, L.

    2011-01-01

    Synthetic Aperture Radar (SAR) systems are becoming increasingly important sensors in as well the military environment as in the civilian market. In this keynote presentation an overview will be given over more than 2 decades of SAR system∼ and SAR application development at TNO in the Netherlands.

  19. Optical implementation of a feature-based neural network with application to automatic target recognition

    Science.gov (United States)

    Chao, Tien-Hsin; Stoner, William W.

    1993-01-01

    An optical neural network based on the neocognitron paradigm is introduced. A novel aspect of the architecture design is shift-invariant multichannel Fourier optical correlation within each processing layer. Multilayer processing is achieved by feeding back the ouput of the feature correlator interatively to the input spatial light modulator and by updating the Fourier filters. By training the neural net with characteristic features extracted from the target images, successful pattern recognition with intraclass fault tolerance and interclass discrimination is achieved. A detailed system description is provided. Experimental demonstrations of a two-layer neural network for space-object discrimination is also presented.

  20. Automatic target recognition using a feature-based optical neural network

    Science.gov (United States)

    Chao, Tien-Hsin

    1992-01-01

    An optical neural network based upon the Neocognitron paradigm (K. Fukushima et al. 1983) is introduced. A novel aspect of the architectural design is shift-invariant multichannel Fourier optical correlation within each processing layer. Multilayer processing is achieved by iteratively feeding back the output of the feature correlator to the input spatial light modulator and updating the Fourier filters. By training the neural net with characteristic features extracted from the target images, successful pattern recognition with intra-class fault tolerance and inter-class discrimination is achieved. A detailed system description is provided. Experimental demonstration of a two-layer neural network for space objects discrimination is also presented.

  1. SAR Raw Data Generation for Complex Airport Scenes

    Directory of Open Access Journals (Sweden)

    Jia Li

    2014-10-01

    Full Text Available The method of generating the SAR raw data of complex airport scenes is studied in this paper. A formulation of the SAR raw signal model of airport scenes is given. Via generating the echoes from the background, aircrafts and buildings, respectively, the SAR raw data of the unified SAR imaging geometry is obtained from their vector additions. The multipath scattering and the shadowing between the background and different ground covers of standing airplanes and buildings are analyzed. Based on the scattering characteristics, coupling scattering models and SAR raw data models of different targets are given, respectively. A procedure is given to generate the SAR raw data of airport scenes. The SAR images from the simulated raw data demonstrate the validity of the proposed method.

  2. Synthetic aperture design for increased SAR image rate

    Science.gov (United States)

    Bielek, Timothy P [Albuquerque, NM; Thompson, Douglas G [Albuqerque, NM; Walker, Bruce C [Albuquerque, NM

    2009-03-03

    High resolution SAR images of a target scene at near video rates can be produced by using overlapped, but nevertheless, full-size synthetic apertures. The SAR images, which respectively correspond to the apertures, can be analyzed in sequence to permit detection of movement in the target scene.

  3. SARS virus

    Indian Academy of Sciences (India)

    ... consequence.Protein spike similar. HE gene absent. 2787 nucleotides. Largest genome. Jumps species by genetic deletion. < 300 compounds screened. Glycyrrhizin (liquorics/mullatha) seems attractive. Antivirals not effective. Vaccines – animal model only in monkeys. Killed corona or knockout weakened virus as targets.

  4. New challenges for a SAR toolbox

    International Nuclear Information System (INIS)

    Loreaux, P.; Quin, G.

    2013-01-01

    High resolution multi-frequency synthetic aperture radar (SAR) imagery, available since early 2008, brings all weather capability and day/night operability in support of safeguards verification. Today, a combined approach of high resolution optical and radar imagery in monitoring exercise would enable looking at any area of interest on daily basis. One of the challenges is the co-registration of SAR images acquired with different acquisition mode and also with different optical images. We show in this paper the on-going research work to find a general co-register method and an automatic tool to detect changes. Before having an operational co-register tool, a method to find automatically tie points between SAR images acquired with different acquisition mode and with optical images has to be developed. Concerning an automatic change detection method we can conclude that the study of the Harmonic mean, Geometric mean and Arithmetic mean, enables several applications like change detection for SAR imagery. Thus, we developed the MAGMA (Method for Arithmetic and Geometric Means Analysis) change detection method. As shown in this paper, the MAGMA method improves the Maximum Likelihood techniques like GLRT, using Information-Theory concepts to detect changes between SAR amplitude images. The major improvement consists in a lower false detection rate, especially in low amplitude areas. The second improvement consists in a better location of the changes in clearly delimited areas, which enables precise interpretations. Results presented here reveal the potential of high resolution radar imagery for a baseline description of some sites, change detection based on repeat pass imagery acquisitions and site specific constraints in coherent change detection due to cover conditions. (A.C.)

  5. Prototype Automatic Target Screener.

    Science.gov (United States)

    1980-05-19

    JLIST OF TABLES I Table Page 1 PATS Modules 4 2 Vector Read/Write Command Format ( SEL4 ) 29 1 3 Read Vector Data Command Format ( SEL4 ) 30 J 4 Use Matrix...VECTOR READ/WRITE COMMAND FORMAT ( SEL4 ) S 1,4A Output 15 14 1:3 12 11 10 9 8 7 6 5 4 3 2 1 0 Da taI To VNUM VDIR V LEN InterfaceIT TNT = 1 Intensify...elements ! | 29 I TABLE 3. READ VECTOR DATA COMMAND FORMAT ( SEL4 ) SEL4 Read Vector Data Input 15 14 13 12 11 10 9 8 7 6 5 4 3 2 1 0 Da ta D D V To 0 A D

  6. Severe acute respiratory syndrome (SARS)

    Science.gov (United States)

    SARS; Respiratory failure - SARS ... Complications may include: Respiratory failure Liver failure Heart failure ... 366. McIntosh K, Perlman S. Coronaviruses, including severe acute respiratory syndrome (SARS) and Middle East respiratory syndrome (MERS). ...

  7. TerraSAR-X InSAR multipass analysis on Venice, Italy)

    Science.gov (United States)

    Nitti, D. O.; Nutricato, R.; Bovenga, F.; Refice, A.; Chiaradia, M. T.; Guerriero, L.

    2009-09-01

    The TerraSAR-X (copyright) mission, launched in 2007, carries a new X-band Synthetic Aperture Radar (SAR) sensor optimally suited for SAR interferometry (InSAR), thus allowing very promising application of InSAR techniques for the risk assessment on areas with hydrogeological instability and especially for multi-temporal analysis, such as Persistent Scatterer Interferometry (PSI) techniques, originally developed at Politecnico di Milano. The SPINUA (Stable Point INterferometry over Unurbanised Areas) technique is a PSI processing methodology which has originally been developed with the aim of detection and monitoring of coherent PS targets in non or scarcely-urbanized areas. The main goal of the present work is to describe successful applications of the SPINUA PSI technique in processing X-band data. Venice has been selected as test site since it is in favorable settings for PSI investigations (urban area containing many potential coherent targets such as buildings) and in view of the availability of a long temporal series of TerraSAR-X stripmap acquisitions (27 scenes in all). The Venice Lagoon is affected by land sinking phenomena, whose origins are both natural and man-induced. The subsidence of Venice has been intensively studied for decades by determining land displacements through traditional monitoring techniques (leveling and GPS) and, recently, by processing stacks of ERS/ENVISAT SAR data. The present work is focused on an independent assessment of application of PSI techniques to TerraSAR-X stripmap data for monitoring the stability of the Venice area. Thanks to its orbital repeat cycle of only 11 days, less than a third of ERS/ENVISAT C-band missions, the maximum displacement rate that can be unambiguously detected along the Line-of-Sight (LOS) with TerraSAR-X SAR data through PSI techniques is expected to be about twice the corresponding value of ESA C-band missions, being directly proportional to the sensor wavelength and inversely proportional to the

  8. 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.

  9. Design and realization of an active SAR calibrator for TerraSAR-X

    Science.gov (United States)

    Dummer, Georg; Lenz, Rainer; Lutz, Benjamin; Kühl, Markus; Müller-Glaser, Klaus D.; Wiesbeck, Werner

    2005-10-01

    TerraSAR-X is a new earth observing satellite which will be launched in spring 2006. It carries a high resolution X-band SAR sensor. For high image data quality, accurate ground calibration targets are necessary. This paper describes a novel system concept for an active and highly integrated, digitally controlled SAR system calibrator. A total of 16 active transponder and receiver systems and 17 receiver only systems will be fabricated for a calibration campaign. The calibration units serve for absolute radiometric calibration of the SAR image data. Additionally, they are equipped with an extra receiver path for two dimensional satellite antenna pattern recognition. The calibrator is controlled by a dedicated digital Electronic Control Unit (ECU). The different voltages needed by the calibrator and the ECU are provided by the third main unit called Power Management Unit (PMU).

  10. Use of SAR data for proliferation monitoring

    International Nuclear Information System (INIS)

    Lafitte, M.; Robin, J.P.

    2013-01-01

    Synthetic Aperture Radar (SAR) is an active and coherent system. SAR images are complex data which contain both amplitude and phase information. The analysis of single SAR data required a very good experience and a good understanding of SAR geometry regarding layover, shadowing, texture and speckle. Image analyst can depicts and describes most of the facilities related to nuclear proliferation and weapons of mass destruction (WMD). The Amplitude Change Detection (ACD) technique consists of a combination of two or three SAR amplitude data acquired with similar orbit and frequency parameters on different dates. That technique provides a very good overview of the changes and particularly regarding vehicles activity and constructions ongoing within the area of interest over the monitoring period. One of the particularities of the SAR systems is to be coherent. The phase of a single image is not exploitable. Thus when two or more SAR data have been acquired with identical orbit and frequency parameters, the phases shift are indicators of changes such as structural changes, terrain subsidence or motion. The Multi-Temporal Coherence (MTC) product merged the two type of information previously detailed: the ACD and coherence analysis. It consists of the combination of two amplitude images and the corresponding coherence computed image. The MTC image may highlights changes between two states of a target which on the ACD analysis appeared unchanged. EUSC uses the difference interferometry techniques in order to estimate volumes that have changed between two acquisition dates. The paper is followed by the slides of the presentation. (A.C.)

  11. Pulse-based internal calibration of polarimetric SAR

    DEFF Research Database (Denmark)

    Dall, Jørgen; Skou, Niels; Christensen, Erik Lintz

    1994-01-01

    Internal calibration greatly diminishes the dependence on calibration target deployment compared to external calibration. Therefore the Electromagnetics Institute (EMI) at the Technical University of Denmark (TUD) has equipped its polarimetric SAR, EMISAR, with several calibration loops and devel......Internal calibration greatly diminishes the dependence on calibration target deployment compared to external calibration. Therefore the Electromagnetics Institute (EMI) at the Technical University of Denmark (TUD) has equipped its polarimetric SAR, EMISAR, with several calibration loops...

  12. Satellite on-board real-time SAR processor prototype

    Science.gov (United States)

    Bergeron, Alain; Doucet, Michel; Harnisch, Bernd; Suess, Martin; Marchese, Linda; Bourqui, Pascal; Desnoyers, Nicholas; Legros, Mathieu; Guillot, Ludovic; Mercier, Luc; Châteauneuf, François

    2017-11-01

    A Compact Real-Time Optronic SAR Processor has been successfully developed and tested up to a Technology Readiness Level of 4 (TRL4), the breadboard validation in a laboratory environment. SAR, or Synthetic Aperture Radar, is an active system allowing day and night imaging independent of the cloud coverage of the planet. The SAR raw data is a set of complex data for range and azimuth, which cannot be compressed. Specifically, for planetary missions and unmanned aerial vehicle (UAV) systems with limited communication data rates this is a clear disadvantage. SAR images are typically processed electronically applying dedicated Fourier transformations. This, however, can also be performed optically in real-time. Originally the first SAR images were optically processed. The optical Fourier processor architecture provides inherent parallel computing capabilities allowing real-time SAR data processing and thus the ability for compression and strongly reduced communication bandwidth requirements for the satellite. SAR signal return data are in general complex data. Both amplitude and phase must be combined optically in the SAR processor for each range and azimuth pixel. Amplitude and phase are generated by dedicated spatial light modulators and superimposed by an optical relay set-up. The spatial light modulators display the full complex raw data information over a two-dimensional format, one for the azimuth and one for the range. Since the entire signal history is displayed at once, the processor operates in parallel yielding real-time performances, i.e. without resulting bottleneck. Processing of both azimuth and range information is performed in a single pass. This paper focuses on the onboard capabilities of the compact optical SAR processor prototype that allows in-orbit processing of SAR images. Examples of processed ENVISAT ASAR images are presented. Various SAR processor parameters such as processing capabilities, image quality (point target analysis), weight and

  13. The Radiometric Measurement Quantity for SAR Images

    OpenAIRE

    Döring, Björn J.; Schwerdt, Marco

    2013-01-01

    A Synthetic Aperture Radar (SAR) system measures among other quantities the terrain radar reflectivity. After image calibration, the pixel intensities are commonly expressed in terms of radar cross sections (for point targets) or as backscatter coefficients (for distributed targets), which are directly related. This paper argues that pixel intensities are not generally proportional to radar cross section or derived physical quantities. The paper further proposes to replace the inaccurate term...

  14. Molecular mechanisms of severe acute respiratory syndrome (SARS

    Directory of Open Access Journals (Sweden)

    Zabel Peter

    2005-01-01

    Full Text Available Abstract Severe acute respiratory syndrome (SARS is a new infectious disease caused by a novel coronavirus that leads to deleterious pulmonary pathological features. Due to its high morbidity and mortality and widespread occurrence, SARS has evolved as an important respiratory disease which may be encountered everywhere in the world. The virus was identified as the causative agent of SARS due to the efforts of a WHO-led laboratory network. The potential mutability of the SARS-CoV genome may lead to new SARS outbreaks and several regions of the viral genomes open reading frames have been identified which may contribute to the severe virulence of the virus. With regard to the pathogenesis of SARS, several mechanisms involving both direct effects on target cells and indirect effects via the immune system may exist. Vaccination would offer the most attractive approach to prevent new epidemics of SARS, but the development of vaccines is difficult due to missing data on the role of immune system-virus interactions and the potential mutability of the virus. Even in a situation of no new infections, SARS remains a major health hazard, as new epidemics may arise. Therefore, further experimental and clinical research is required to control the disease.

  15. An Adaptive Ship Detection Scheme for Spaceborne SAR Imagery

    Directory of Open Access Journals (Sweden)

    Xiangguang Leng

    2016-08-01

    Full Text Available With the rapid development of spaceborne synthetic aperture radar (SAR and the increasing need of ship detection, research on adaptive ship detection in spaceborne SAR imagery is of great importance. Focusing on practical problems of ship detection, this paper presents a highly adaptive ship detection scheme for spaceborne SAR imagery. It is able to process a wide range of sensors, imaging modes and resolutions. Two main stages are identified in this paper, namely: ship candidate detection and ship discrimination. Firstly, this paper proposes an adaptive land masking method using ship size and pixel size. Secondly, taking into account the imaging mode, incidence angle, and polarization channel of SAR imagery, it implements adaptive ship candidate detection in spaceborne SAR imagery by applying different strategies to different resolution SAR images. Finally, aiming at different types of typical false alarms, this paper proposes a comprehensive ship discrimination method in spaceborne SAR imagery based on confidence level and complexity analysis. Experimental results based on RADARSAT-1, RADARSAT-2, TerraSAR-X, RS-1, and RS-3 images demonstrate that the adaptive scheme proposed in this paper is able to detect ship targets in a fast, efficient and robust way.

  16. Robustness and precision of an automatic marker detection algorithm for online prostate daily targeting using a standard V-EPID.

    Science.gov (United States)

    Aubin, S; Beaulieu, L; Pouliot, S; Pouliot, J; Roy, R; Girouard, L M; Martel-Brisson, N; Vigneault, E; Laverdière, J

    2003-07-01

    An algorithm for the daily localization of the prostate using implanted markers and a standard video-based electronic portal imaging device (V-EPID) has been tested. Prior to planning, three gold markers were implanted in the prostate of seven patients. The clinical images were acquired with a BeamViewPlus 2.1 V-EPID for each field during the normal course radiotherapy treatment and are used off-line to determine the ability of the automatic marker detection algorithm to adequately and consistently detect the markers. Clinical images were obtained with various dose levels from ranging 2.5 to 75 MU. The algorithm is based on marker attenuation characterization in the portal image and spatial distribution. A total of 1182 clinical images were taken. The results show an average efficiency of 93% for the markers detected individually and 85% for the group of markers. This algorithm accomplishes the detection and validation in 0.20-0.40 s. When the center of mass of the group of implanted markers is used, then all displacements can be corrected to within 1.0 mm in 84% of the cases and within 1.5 mm in 97% of cases. The standard video-based EPID tested provides excellent marker detection capability even with low dose levels. The V-EPID can be used successfully with radiopaque markers and the automatic detection algorithm to track and correct the daily setup deviations due to organ motions.

  17. Crop Classification by Polarimetric SAR

    DEFF Research Database (Denmark)

    Skriver, Henning; Svendsen, Morten Thougaard; Nielsen, Flemming

    1999-01-01

    Polarimetric SAR-data of agricultural fields have been acquired by the Danish polarimetric L- and C-band SAR (EMISAR) during a number of missions at the Danish agricultural test site Foulum during 1995. The data are used to study the classification potential of polarimetric SAR data using...

  18. An Approach for Automatic Orientation of Big Point Clouds from the Stationary Scanners Based on the Spherical Targets

    Directory of Open Access Journals (Sweden)

    YAO Jili

    2015-04-01

    Full Text Available Terrestrial laser scanning (TLS technology has high speed of data acquisition, large amount of point cloud, long distance of measuring. However, there are some disadvantages such as distance limitation in target detecting, hysteresis in point clouds processing, low automation and weaknesses of adapting long-distance topographic survey. In this case, we put forward a method on long-range targets detecting in big point clouds orientation. The method firstly searches point cloud rings that contain targets according to their engineering coordinate system. Then the detected rings are divided into sectors to detect targets in a very short time so as to obtain central coordinates of these targets. Finally, the position and orientation parameters of scanner are calculated and point clouds in scanner's own coordinate system(SOCS are converted into engineering coordinate system. The method is able to be applied in ordinary computers for long distance topographic(the distance between scanner and targets ranges from 180 to 700 m survey in mountainous areas with targets radius of 0.162m.

  19. Global Rapid Flood Mapping System with Spaceborne SAR Data

    Science.gov (United States)

    Yun, S. H.; Owen, S. E.; Hua, H.; Agram, P. S.; Fattahi, H.; Liang, C.; Manipon, G.; Fielding, E. J.; Rosen, P. A.; Webb, F.; Simons, M.

    2017-12-01

    As part of the Advanced Rapid Imaging and Analysis (ARIA) project for Natural Hazards, at NASA's Jet Propulsion Laboratory and California Institute of Technology, we have developed an automated system that produces derived products for flood extent map generation using spaceborne SAR data. The system takes user's input of area of interest polygons and time window for SAR data search (pre- and post-event). Then the system automatically searches and downloads SAR data, processes them to produce coregistered SAR image pairs, and generates log amplitude ratio images from each pair. Currently the system is automated to support SAR data from the European Space Agency's Sentinel-1A/B satellites. We have used the system to produce flood extent maps from Sentinel-1 SAR data for the May 2017 Sri Lanka floods, which killed more than 200 people and displaced about 600,000 people. Our flood extent maps were delivered to the Red Cross to support response efforts. Earlier we also responded to the historic August 2016 Louisiana floods in the United States, which claimed 13 people's lives and caused over $10 billion property damage. For this event, we made synchronized observations from space, air, and ground in close collaboration with USGS and NOAA. The USGS field crews acquired ground observation data, and NOAA acquired high-resolution airborne optical imagery within the time window of +/-2 hours of the SAR data acquisition by JAXA's ALOS-2 satellite. The USGS coordinates of flood water boundaries were used to calibrate our flood extent map derived from the ALOS-2 SAR data, and the map was delivered to FEMA for estimating the number of households affected. Based on the lessons learned from this response effort, we customized the ARIA system automation for rapid flood mapping and developed a mobile friendly web app that can easily be used in the field for data collection. Rapid automatic generation of SAR-based global flood maps calibrated with independent observations from

  20. Bats and SARS

    Centers for Disease Control (CDC) Podcasts

    Bats are a natural reservoir for emerging viruses, among them henipaviruses and rabies virus variants. Dr. Nina Marano, Chief, Geographic Medicine and Health Promotion Branch, Division of Global Migration and Quarantine, CDC, explains connection between horseshoe bats and SARS coronavirus transmission.

  1. Bats and SARS

    Centers for Disease Control (CDC) Podcasts

    2006-11-08

    Bats are a natural reservoir for emerging viruses, among them henipaviruses and rabies virus variants. Dr. Nina Marano, Chief, Geographic Medicine and Health Promotion Branch, Division of Global Migration and Quarantine, CDC, explains connection between horseshoe bats and SARS coronavirus transmission.  Created: 11/8/2006 by Emerging Infectious Diseases.   Date Released: 11/17/2006.

  2. Data Analytics for SAR

    Energy Technology Data Exchange (ETDEWEB)

    Murphy, David Patrick [Los Alamos National Lab. (LANL), Los Alamos, NM (United States); Calef, Matthew Thomas [Los Alamos National Lab. (LANL), Los Alamos, NM (United States)

    2017-10-02

    We assess the ability of variants of anomalous change detection (ACD) to identify human activity associated with large outdoor music festivals as they are seen from synthetic aperture radar (SAR) imagery collected by the Sentinel-1 satellite constellation. We found that, with appropriate feature vectors, ACD using random-forest machine learning was most effective at identifying changes associated with the human activity.

  3. Automatic detection of multiple UXO-like targets using magnetic anomaly inversion and self-adaptive fuzzy c-means clustering

    Science.gov (United States)

    Yin, Gang; Zhang, Yingtang; Fan, Hongbo; Ren, Guoquan; Li, Zhining

    2017-12-01

    We have developed a method for automatically detecting UXO-like targets based on magnetic anomaly inversion and self-adaptive fuzzy c-means clustering. Magnetic anomaly inversion methods are used to estimate the initial locations of multiple UXO-like sources. Although these initial locations have some errors with respect to the real positions, they form dense clouds around the actual positions of the magnetic sources. Then we use the self-adaptive fuzzy c-means clustering algorithm to cluster these initial locations. The estimated number of cluster centroids represents the number of targets and the cluster centroids are regarded as the locations of magnetic targets. Effectiveness of the method has been demonstrated using synthetic datasets. Computational results show that the proposed method can be applied to the case of several UXO-like targets that are randomly scattered within in a confined, shallow subsurface, volume. A field test was carried out to test the validity of the proposed method and the experimental results show that the prearranged magnets can be detected unambiguously and located precisely.

  4. Unsupervised SBAS-DInSAR Processing of Space-borne SAR data for Earth Surface Displacement Time Series Generation

    Science.gov (United States)

    Casu, F.; de Luca, C.; Lanari, R.; Manunta, M.; Zinno, I.

    2016-12-01

    During the last 25 years, the Differential Synthetic Aperture Radar Interferometry (DInSAR) has played an important role for understanding the Earth's surface deformation and its dynamics. In particular, the large collections of SAR data acquired by a number of space-borne missions (ERS, ENVISAT, ALOS, RADARSAT, TerraSAR-X, COSMO-SkyMed) have pushed toward the development of advanced DInSAR techniques for monitoring the temporal evolution of the ground displacements with an high spatial density. Moreover, the advent of the Copernicus Sentinel-1 (S1) constellation is providing a further increase in the SAR data flow available to the Earth science community, due to its characteristics of global coverage strategy and free and open access data policy. Therefore, managing and storing such a huge amount of data, processing it in an effcient way and maximizing the available archives exploitation are becoming high priority issues. In this work we present some recent advances in the DInSAR field for dealing with the effective exploitation of the present and future SAR data archives. In particular, an efficient parallel SBAS implementation (namely P-SBAS) that takes benefit from high performance computing is proposed. Then, the P-SBAS migration to the emerging Cloud Computing paradigm is shown, together with extensive tests carried out in the Amazon's Elastic Cloud Compute (EC2) infrastructure. Finally, the integration of the P-SBAS processing chain within the ESA Geohazards Exploitation Platform (GEP), for setting up operational on-demand and systematic web tools, open to every user, aimed at automatically processing stacks of SAR data for the generation of SBAS displacement time series, is also illustrated. A number of experimental results obtained by using the ERS, ENVISAT and S1 data in areas characterized by volcanic, seismic and anthropogenic phenomena will be shown. This work is partially supported by: the DPC-CNR agreement, the EPOS-IP project and the ESA GEP project.

  5. Relevant Scatterers Characterization in SAR Images

    Science.gov (United States)

    Chaabouni, Houda; Datcu, Mihai

    2006-11-01

    Recognizing scenes in a single look meter resolution Synthetic Aperture Radar (SAR) images, requires the capability to identify relevant signal signatures in condition of variable image acquisition geometry, arbitrary objects poses and configurations. Among the methods to detect relevant scatterers in SAR images, we can mention the internal coherence. The SAR spectrum splitted in azimuth generates a series of images which preserve high coherence only for particular object scattering. The detection of relevant scatterers can be done by correlation study or Independent Component Analysis (ICA) methods. The present article deals with the state of the art for SAR internal correlation analysis and proposes further extensions using elements of inference based on information theory applied to complex valued signals. The set of azimuth looks images is analyzed using mutual information measures and an equivalent channel capacity is derived. The localization of the "target" requires analysis in a small image window, thus resulting in imprecise estimation of the second order statistics of the signal. For a better precision, a Hausdorff measure is introduced. The method is applied to detect and characterize relevant objects in urban areas.

  6. A new automatic synthetic aperture radar-based flood mapping application hosted on the European Space Agency's Grid Processing of Demand Fast Access to Imagery environment

    Science.gov (United States)

    Matgen, Patrick; Giustarini, Laura; Hostache, Renaud

    2012-10-01

    This paper introduces an automatic flood mapping application that is hosted on the Grid Processing on Demand (GPOD) Fast Access to Imagery (Faire) environment of the European Space Agency. The main objective of the online application is to deliver operationally flooded areas using both recent and historical acquisitions of SAR data. Having as a short-term target the flooding-related exploitation of data generated by the upcoming ESA SENTINEL-1 SAR mission, the flood mapping application consists of two building blocks: i) a set of query tools for selecting the "crisis image" and the optimal corresponding "reference image" from the G-POD archive and ii) an algorithm for extracting flooded areas via change detection using the previously selected "crisis image" and "reference image". Stakeholders in flood management and service providers are able to log onto the flood mapping application to get support for the retrieval, from the rolling archive, of the most appropriate reference image. Potential users will also be able to apply the implemented flood delineation algorithm. The latter combines histogram thresholding, region growing and change detection as an approach enabling the automatic, objective and reliable flood extent extraction from SAR images. Both algorithms are computationally efficient and operate with minimum data requirements. The case study of the high magnitude flooding event that occurred in July 2007 on the Severn River, UK, and that was observed with a moderateresolution SAR sensor as well as airborne photography highlights the performance of the proposed online application. The flood mapping application on G-POD can be used sporadically, i.e. whenever a major flood event occurs and there is a demand for SAR-based flood extent maps. In the long term, a potential extension of the application could consist in systematically extracting flooded areas from all SAR images acquired on a daily, weekly or monthly basis.

  7. Bistatic sAR data processing algorithms

    CERN Document Server

    Qiu, Xiaolan; Hu, Donghui

    2013-01-01

    Synthetic Aperture Radar (SAR) is critical for remote sensing. It works day and night, in good weather or bad. Bistatic SAR is a new kind of SAR system, where the transmitter and receiver are placed on two separate platforms. Bistatic SAR is one of the most important trends in SAR development, as the technology renders SAR more flexible and safer when used in military environments. Imaging is one of the most difficult and important aspects of bistatic SAR data processing. Although traditional SAR signal processing is fully developed, bistatic SAR has a more complex system structure, so sign

  8. ROBIN: a platform for evaluating automatic target recognition algorithms: I. Overview of the project and presentation of the SAGEM DS competition

    Science.gov (United States)

    Duclos, D.; Lonnoy, J.; Guillerm, Q.; Jurie, F.; Herbin, S.; D'Angelo, E.

    2008-04-01

    The last five years have seen a renewal of Automatic Target Recognition applications, mainly because of the latest advances in machine learning techniques. In this context, large collections of image datasets are essential for training algorithms as well as for their evaluation. Indeed, the recent proliferation of recognition algorithms, generally applied to slightly different problems, make their comparisons through clean evaluation campaigns necessary. The ROBIN project tries to fulfil these two needs by putting unclassified datasets, ground truths, competitions and metrics for the evaluation of ATR algorithms at the disposition of the scientific community. The scope of this project includes single and multi-class generic target detection and generic target recognition, in military and security contexts. From our knowledge, it is the first time that a database of this importance (several hundred thousands of visible and infrared hand annotated images) has been publicly released. Funded by the French Ministry of Defence (DGA) and by the French Ministry of Research, ROBIN is one of the ten Techno-vision projects. Techno-vision is a large and ambitious government initiative for building evaluation means for computer vision technologies, for various application contexts. ROBIN's consortium includes major companies and research centres involved in Computer Vision R&D in the field of defence: Bertin Technologies, CNES, ECA, DGA, EADS, INRIA, ONERA, MBDA, SAGEM, THALES. This paper, which first gives an overview of the whole project, is focused on one of ROBIN's key competitions, the SAGEM Defence Security database. This dataset contains more than eight hundred ground and aerial infrared images of six different vehicles in cluttered scenes including distracters. Two different sets of data are available for each target. The first set includes different views of each vehicle at close range in a "simple" background, and can be used to train algorithms. The second set

  9. Automatic Imitation

    Science.gov (United States)

    Heyes, Cecilia

    2011-01-01

    "Automatic imitation" is a type of stimulus-response compatibility effect in which the topographical features of task-irrelevant action stimuli facilitate similar, and interfere with dissimilar, responses. This article reviews behavioral, neurophysiological, and neuroimaging research on automatic imitation, asking in what sense it is "automatic"…

  10. Estimating the Doppler centroid of SAR data

    DEFF Research Database (Denmark)

    Madsen, Søren Nørvang

    1989-01-01

    attractive properties. An evaluation based on an existing SEASAT processor is reported. The time-domain algorithms are shown to be extremely efficient with respect to requirements on calculations and memory, and hence they are well suited to real-time systems where the Doppler estimation is based on raw SAR......After reviewing frequency-domain techniques for estimating the Doppler centroid of synthetic-aperture radar (SAR) data, the author describes a time-domain method and highlights its advantages. In particular, a nonlinear time-domain algorithm called the sign-Doppler estimator (SDE) is shown to have...... data. For offline processors where the Doppler estimation is performed on processed data, which removes the problem of partial coverage of bright targets, the ΔE estimator and the CDE (correlation Doppler estimator) algorithm give similar performance. However, for nonhomogeneous scenes it is found...

  11. WE-AB-BRA-09: Registration of Preoperative MRI to Intraoperative Radiographs for Automatic Vertebral Target Localization

    Energy Technology Data Exchange (ETDEWEB)

    De Silva, T; Uneri, A; Ketcha, M; Reaungamornrat, S; Goerres, J [Johns Hopkins University, Baltimore, MD (United States); Vogt, S; Kleinszig, G [Siemens Healthcare, Erlangen (Germany); Wolinsky, J [The Johns Hopkins Hospital, Baltimore, MD (United States); Siewerdsen, JH

    2016-06-15

    Purpose: Accurate localization of target vertebrae is essential to safe, effective spine surgery, but wrong-level surgery occurs with surprisingly high frequency. Recent research yielded the “LevelCheck” method for 3D-2D registration of preoperative CT to intraoperative radiographs, providing decision support for level localization. We report a new method (MR-LevelCheck) to perform 3D-2D registration based on preoperative MRI, presenting a solution for the increasingly common scenario in which MRI (not CT) is used for preoperative planning. Methods: Direct extension of LevelCheck is confounded by large mismatch in image intensity between MRI and radiographs. The proposed method overcomes such challenges with a simple vertebrae segmentation. Using seed points at centroids, vertebrae are segmented using continuous max-flow method and dilated by 1.8 mm to include surrounding cortical bone (inconspicuous in T2w-MRI). MRI projections are computed (analogous to DRR) using segmentation and registered to intraoperative radiographs. The method was tested in a retrospective IRB-approved study involving 11 patients undergoing cervical, thoracic, or lumbar spine surgery following preoperative MRI. Registration accuracy was evaluated in terms of projection-distance-error (PDE) between the true and estimated location of vertebrae in each radiograph. Results: The method successfully registered each preoperative MRI to intraoperative radiographs and maintained desirable properties of robustness against image content mismatch, and large capture range. Segmentation achieved Dice coefficient = 89.2 ± 2.3 and mean-absolute-distance (MAD) = 1.5 ± 0.3 mm. Registration demonstrated robust performance under realistic patient variations, with PDE = 4.0 ± 1.9 mm (median ± iqr) and converged with run-time = 23.3 ± 1.7 s. Conclusion: The MR-LevelCheck algorithm provides an important extension to a previously validated decision support tool in spine surgery by extending its utility to

  12. PHARUS : PHased ARray Universal SAR

    NARCIS (Netherlands)

    Paquay, M.H.A.; Vermeulen, B.C.B.; Koomen, P.J.; Hoogeboom, P.; Snoeij, P.; Pouwels, H.

    1996-01-01

    In the Netherlands, a polarimetric C-band aircraft SAR (Synthetic Aperture Radar) has been developed. The project is called PHARUS, an acronm for PHased ARray Universal SAR. This instrument serves remote sensing applications. The antenna system contains 48 active modules (expandable to 96). A module

  13. How infectious is SARS virus

    Indian Academy of Sciences (India)

    First page Back Continue Last page Overview Graphics. How infectious is SARS virus. Influenza: 1 patient infects ten people. SARS: 1 patient infects 2-4 people. Incubation period 10 days. Are there `silent´ cases ? Is quarantine enough ? How will it behave if and when it returns ?

  14. Restoration of polarimetric SAR images using simulated annealing

    DEFF Research Database (Denmark)

    Schou, Jesper; Skriver, Henning

    2001-01-01

    approach favoring one of the objectives. An algorithm for estimating the radar cross-section (RCS) for intensity SAR images has previously been proposed in the literature based on Markov random fields and the stochastic optimization method simulated annealing. A new version of the algorithm is presented......Filtering synthetic aperture radar (SAR) images ideally results in better estimates of the parameters characterizing the distributed targets in the images while preserving the structures of the nondistributed targets. However, these objectives are normally conflicting, often leading to a filtering...

  15. Improved SAR Image Coregistration Using Pixel-Offset Series

    KAUST Repository

    Wang, Teng

    2014-03-14

    Synthetic aperture radar (SAR) image coregistration is a key procedure before interferometric SAR (InSAR) time-series analysis can be started. However, many geophysical data sets suffer from severe decorrelation problems due to a variety of reasons, making precise coregistration a nontrivial task. Here, we present a new strategy that uses a pixel-offset series of detected subimage patches dominated by point-like targets (PTs) to improve SAR image coregistrations. First, all potentially coherent image pairs are coregistered in a conventional way. In this step, we propose a coregistration quality index for each image to rank its relative “significance” within the data set and to select a reference image for the SAR data set. Then, a pixel-offset series of detected PTs is made from amplitude maps to improve the geometrical mapping functions. Finally, all images are resampled depending on the pixel offsets calculated from the updated geometrical mapping functions. We used images from a rural region near the North Anatolian Fault in eastern Turkey to test the proposed method, and clear coregistration improvements were found based on amplitude stability. This enhanced the fact that the coregistration strategy should therefore lead to improved InSAR time-series analysis results.

  16. Improved SAR Image Coregistration Using Pixel-Offset Series

    KAUST Repository

    Wang, Teng; Jonsson, Sigurjon; Hanssen, Ramon F.

    2014-01-01

    Synthetic aperture radar (SAR) image coregistration is a key procedure before interferometric SAR (InSAR) time-series analysis can be started. However, many geophysical data sets suffer from severe decorrelation problems due to a variety of reasons, making precise coregistration a nontrivial task. Here, we present a new strategy that uses a pixel-offset series of detected subimage patches dominated by point-like targets (PTs) to improve SAR image coregistrations. First, all potentially coherent image pairs are coregistered in a conventional way. In this step, we propose a coregistration quality index for each image to rank its relative “significance” within the data set and to select a reference image for the SAR data set. Then, a pixel-offset series of detected PTs is made from amplitude maps to improve the geometrical mapping functions. Finally, all images are resampled depending on the pixel offsets calculated from the updated geometrical mapping functions. We used images from a rural region near the North Anatolian Fault in eastern Turkey to test the proposed method, and clear coregistration improvements were found based on amplitude stability. This enhanced the fact that the coregistration strategy should therefore lead to improved InSAR time-series analysis results.

  17. InSAR deformation monitoring of high risk landslides

    Science.gov (United States)

    Singhroy, V.; Li, J.

    2013-05-01

    During the past year there were at least twenty five media reports of landslides and seismic activities some fatal, occurring in various areas in Canada. These high risk geohazards sites requires high resolution monitoring both spatially and temporally for mitigation purposes, since they are near populated areas and energy, transportation and communication corridors. High resolution air photos, lidar and satellite images are quite common in areas where the landslides can be fatal. Radar interferometry (InSAR) techniques using images from several radar satellites are increasingly being used in slope stability assessment. This presentation provides examples of using high-resolution (1-3m) frequent revisits InSAR techniques from RADARSAT 2 and TerraSAR X to monitor several types of high-risk landslides affecting transportation and energy corridors and populated areas. We have analyses over 200 high resolution InSAR images over a three year period on geologically different landslides. The high-resolution InSAR images are effective in characterizing differential motion within these low velocity landslides. The low velocity landslides become high risk during the active wet spring periods. The wet soils are poor coherent targets and corner reflectors provide an effective means of InSAR monitoring the slope activities.

  18. Bistatic SAR: Imagery & Image Products.

    Energy Technology Data Exchange (ETDEWEB)

    Yocky, David A.; Wahl, Daniel E.; Jakowatz, Charles V,

    2014-10-01

    While typical SAR imaging employs a co-located (monostatic) RADAR transmitter and receiver, bistatic SAR imaging separates the transmitter and receiver locations. The transmitter and receiver geometry determines if the scattered signal is back scatter, forward scatter, or side scatter. The monostatic SAR image is backscatter. Therefore, depending on the transmitter/receiver collection geometry, the captured imagery may be quite different that that sensed at the monostatic SAR. This document presents imagery and image products formed from captured signals during the validation stage of the bistatic SAR research. Image quality and image characteristics are discussed first. Then image products such as two-color multi-view (2CMV) and coherent change detection (CCD) are presented.

  19. Modelling of potentially promising SARS protease inhibitors

    International Nuclear Information System (INIS)

    Plewczynski, Dariusz; Hoffmann, Marcin; Grotthuss, Marcin von; Knizewski, Lukasz; Rychewski, Leszek; Eitner, Krystian; Ginalski, Krzysztof

    2007-01-01

    In many cases, at the beginning of a high throughput screening experiment some information about active molecules is already available. Active compounds (such as substrate analogues, natural products and inhibitors of related proteins) are often identified in low throughput validation studies on a biochemical target. Sometimes the additional structural information is also available from crystallographic studies on protein and ligand complexes. In addition, the structural or sequence similarity of various protein targets yields a novel possibility for drug discovery. Co-crystallized compounds from homologous proteins can be used to design leads for a new target without co-crystallized ligands. In this paper we evaluate how far such an approach can be used in a real drug campaign, with severe acute respiratory syndrome (SARS) coronavirus providing an example. Our method is able to construct small molecules as plausible inhibitors solely on the basis of the set of ligands from crystallized complexes of a protein target, and other proteins from its structurally homologous family. The accuracy and sensitivity of the method are estimated here by the subsequent use of an electronic high throughput screening flexible docking algorithm. The best performing ligands are then used for a very restrictive similarity search for potential inhibitors of the SARS protease within the million compounds from the Ligand.Info small molecule meta-database. The selected molecules can be passed on for further experimental validation

  20. Modelling of potentially promising SARS protease inhibitors

    Energy Technology Data Exchange (ETDEWEB)

    Plewczynski, Dariusz [Interdisciplinary Centre for Mathematical and Computational Modelling, ICM, Warsaw University, Pawinskiego 5a Street, 02-106 Warsaw (Poland); Hoffmann, Marcin [BioInfoBank Institute, Limanowskiego 24A/16, 60-744 Poznan (Poland); Grotthuss, Marcin von [BioInfoBank Institute, Limanowskiego 24A/16, 60-744 Poznan (Poland); Knizewski, Lukasz [Interdisciplinary Centre for Mathematical and Computational Modelling, ICM, Warsaw University, Pawinskiego 5a Street, 02-106 Warsaw (Poland); Rychewski, Leszek [BioInfoBank Institute, Limanowskiego 24A/16, 60-744 Poznan (Poland); Eitner, Krystian [BioInfoBank Institute, Limanowskiego 24A/16, 60-744 Poznan (Poland); Ginalski, Krzysztof [Interdisciplinary Centre for Mathematical and Computational Modelling, ICM, Warsaw University, Pawinskiego 5a Street, 02-106 Warsaw (Poland)

    2007-07-18

    In many cases, at the beginning of a high throughput screening experiment some information about active molecules is already available. Active compounds (such as substrate analogues, natural products and inhibitors of related proteins) are often identified in low throughput validation studies on a biochemical target. Sometimes the additional structural information is also available from crystallographic studies on protein and ligand complexes. In addition, the structural or sequence similarity of various protein targets yields a novel possibility for drug discovery. Co-crystallized compounds from homologous proteins can be used to design leads for a new target without co-crystallized ligands. In this paper we evaluate how far such an approach can be used in a real drug campaign, with severe acute respiratory syndrome (SARS) coronavirus providing an example. Our method is able to construct small molecules as plausible inhibitors solely on the basis of the set of ligands from crystallized complexes of a protein target, and other proteins from its structurally homologous family. The accuracy and sensitivity of the method are estimated here by the subsequent use of an electronic high throughput screening flexible docking algorithm. The best performing ligands are then used for a very restrictive similarity search for potential inhibitors of the SARS protease within the million compounds from the Ligand.Info small molecule meta-database. The selected molecules can be passed on for further experimental validation.

  1. Cloaked similarity between HIV-1 and SARS-CoV suggests an anti-SARS strategy

    Directory of Open Access Journals (Sweden)

    Kliger Yossef

    2003-09-01

    Full Text Available Abstract Background Severe acute respiratory syndrome (SARS is a febrile respiratory illness. The disease has been etiologically linked to a novel coronavirus that has been named the SARS-associated coronavirus (SARS-CoV, whose genome was recently sequenced. Since it is a member of the Coronaviridae, its spike protein (S2 is believed to play a central role in viral entry by facilitating fusion between the viral and host cell membranes. The protein responsible for viral-induced membrane fusion of HIV-1 (gp41 differs in length, and has no sequence homology with S2. Results Sequence analysis reveals that the two viral proteins share the sequence motifs that construct their active conformation. These include (1 an N-terminal leucine/isoleucine zipper-like sequence, and (2 a C-terminal heptad repeat located upstream of (3 an aromatic residue-rich region juxtaposed to the (4 transmembrane segment. Conclusions This study points to a similar mode of action for the two viral proteins, suggesting that anti-viral strategy that targets the viral-induced membrane fusion step can be adopted from HIV-1 to SARS-CoV. Recently the FDA approved Enfuvirtide, a synthetic peptide corresponding to the C-terminal heptad repeat of HIV-1 gp41, as an anti-AIDS agent. Enfuvirtide and C34, another anti HIV-1 peptide, exert their inhibitory activity by binding to a leucine/isoleucine zipper-like sequence in gp41, thus inhibiting a conformational change of gp41 required for its activation. We suggest that peptides corresponding to the C-terminal heptad repeat of the S2 protein may serve as inhibitors for SARS-CoV entry.

  2. SAR Imagery Simulation of Ship Based on Electromagnetic Calculations and Sea Clutter Modelling for Classification Applications

    International Nuclear Information System (INIS)

    Ji, K F; Zhao, Z; Xing, X W; Zou, H X; Zhou, S L

    2014-01-01

    Ship detection and classification with space-borne SAR has many potential applications within the maritime surveillance, fishery activity management, monitoring ship traffic, and military security. While ship detection techniques with SAR imagery are well established, ship classification is still an open issue. One of the main reasons may be ascribed to the difficulties on acquiring the required quantities of real data of vessels under different observation and environmental conditions with precise ground truth. Therefore, simulation of SAR images with high scenario flexibility and reasonable computation costs is compulsory for ship classification algorithms development. However, the simulation of SAR imagery of ship over sea surface is challenging. Though great efforts have been devoted to tackle this difficult problem, it is far from being conquered. This paper proposes a novel scheme for SAR imagery simulation of ship over sea surface. The simulation is implemented based on high frequency electromagnetic calculations methods of PO, MEC, PTD and GO. SAR imagery of sea clutter is modelled by the representative K-distribution clutter model. Then, the simulated SAR imagery of ship can be produced by inserting the simulated SAR imagery chips of ship into the SAR imagery of sea clutter. The proposed scheme has been validated with canonical and complex ship targets over a typical sea scene

  3. On Signal Modeling of Moon-Based Synthetic Aperture Radar (SAR Imaging of Earth

    Directory of Open Access Journals (Sweden)

    Zhen Xu

    2018-03-01

    Full Text Available The Moon-based Synthetic Aperture Radar (Moon-Based SAR, using the Moon as a platform, has a great potential to offer global-scale coverage of the earth’s surface with a high revisit cycle and is able to meet the scientific requirements for climate change study. However, operating in the lunar orbit, Moon-Based SAR imaging is confined within a complex geometry of the Moon-Based SAR, Moon, and Earth, where both rotation and revolution have effects. The extremely long exposure time of Moon-Based SAR presents a curved moving trajectory and the protracted time-delay in propagation makes the “stop-and-go” assumption no longer valid. Consequently, the conventional SAR imaging technique is no longer valid for Moon-Based SAR. This paper develops a Moon-Based SAR theory in which a signal model is derived. The Doppler parameters in the context of lunar revolution with the removal of ‘stop-and-go’ assumption are first estimated, and then characteristics of Moon-Based SAR imaging’s azimuthal resolution are analyzed. In addition, a signal model of Moon-Based SAR and its two-dimensional (2-D spectrum are further derived. Numerical simulation using point targets validates the signal model and enables Doppler parameter estimation for image focusing.

  4. Tie Points Extraction for SAR Images Based on Differential Constraints

    Science.gov (United States)

    Xiong, X.; Jin, G.; Xu, Q.; Zhang, H.

    2018-04-01

    Automatically extracting tie points (TPs) on large-size synthetic aperture radar (SAR) images is still challenging because the efficiency and correct ratio of the image matching need to be improved. This paper proposes an automatic TPs extraction method based on differential constraints for large-size SAR images obtained from approximately parallel tracks, between which the relative geometric distortions are small in azimuth direction and large in range direction. Image pyramids are built firstly, and then corresponding layers of pyramids are matched from the top to the bottom. In the process, the similarity is measured by the normalized cross correlation (NCC) algorithm, which is calculated from a rectangular window with the long side parallel to the azimuth direction. False matches are removed by the differential constrained random sample consensus (DC-RANSAC) algorithm, which appends strong constraints in azimuth direction and weak constraints in range direction. Matching points in the lower pyramid images are predicted with the local bilinear transformation model in range direction. Experiments performed on ENVISAT ASAR and Chinese airborne SAR images validated the efficiency, correct ratio and accuracy of the proposed method.

  5. TIE POINTS EXTRACTION FOR SAR IMAGES BASED ON DIFFERENTIAL CONSTRAINTS

    Directory of Open Access Journals (Sweden)

    X. Xiong

    2018-04-01

    Full Text Available Automatically extracting tie points (TPs on large-size synthetic aperture radar (SAR images is still challenging because the efficiency and correct ratio of the image matching need to be improved. This paper proposes an automatic TPs extraction method based on differential constraints for large-size SAR images obtained from approximately parallel tracks, between which the relative geometric distortions are small in azimuth direction and large in range direction. Image pyramids are built firstly, and then corresponding layers of pyramids are matched from the top to the bottom. In the process, the similarity is measured by the normalized cross correlation (NCC algorithm, which is calculated from a rectangular window with the long side parallel to the azimuth direction. False matches are removed by the differential constrained random sample consensus (DC-RANSAC algorithm, which appends strong constraints in azimuth direction and weak constraints in range direction. Matching points in the lower pyramid images are predicted with the local bilinear transformation model in range direction. Experiments performed on ENVISAT ASAR and Chinese airborne SAR images validated the efficiency, correct ratio and accuracy of the proposed method.

  6. Research on the method of extracting DEM based on GBInSAR

    Science.gov (United States)

    Yue, Jianping; Yue, Shun; Qiu, Zhiwei; Wang, Xueqin; Guo, Leping

    2016-05-01

    Precise topographical information has a very important role in geology, hydrology, natural resources survey and deformation monitoring. The extracting DEM technology based on synthetic aperture radar interferometry (InSAR) obtains the three-dimensional elevation of the target area through the phase information of the radar image data. The technology has large-scale, high-precision, all-weather features. By changing track in the location of the ground radar system up and down, it can form spatial baseline. Then we can achieve the DEM of the target area by acquiring image data from different angles. Three-dimensional laser scanning technology can quickly, efficiently and accurately obtain DEM of target area, which can verify the accuracy of DEM extracted by GBInSAR. But research on GBInSAR in extracting DEM of the target area is a little. For lack of theory and lower accuracy problems in extracting DEM based on GBInSAR now, this article conducted research and analysis on its principle deeply. The article extracted the DEM of the target area, combined with GBInSAR data. Then it compared the DEM obtained by GBInSAR with the DEM obtained by three-dimensional laser scan data and made statistical analysis and normal distribution test. The results showed the DEM obtained by GBInSAR was broadly consistent with the DEM obtained by three-dimensional laser scanning. And its accuracy is high. The difference of both DEM approximately obeys normal distribution. It indicated that extracting the DEM of target area based on GBInSAR is feasible and provided the foundation for the promotion and application of GBInSAR.

  7. SAR calculation using FDTD simulations

    OpenAIRE

    Ferro, Francisco Nabais; Pinto, Guilherme Taveira; Pinho, Pedro

    2009-01-01

    The main intend of this work, is to determinate the Specific Absorption Rate (SAR) on human head tissues exposed to radiation caused by sources of 900 and 1800MHz, since those are the typical frequencies for mobile communications systems nowadays. In order to determinate the SAR, has been used the FDTD (Finite Difference Time Domain), which is a numeric method in time domain, obtained from the Maxwell equations in differential mode. In order to do this, a computational model from the human he...

  8. Beyond PSInSAR: the SQUEESAR Approach

    Science.gov (United States)

    Ferretti, A.; Novali, F.; Fumagalli, A.; Prati, C.; Rocca, F.; Rucci, A.

    2009-12-01

    After a decade since the first results on ERS data, Permanent Scatterer (PS) InSAR has become an operational technology for detecting and monitoring slow surface deformation phenomena such as subsidence and uplift, landslides, seismic fault creeping, volcanic inflation, etc. Processing procedures have been continuously updated, but the core of the algorithm has not been changed significantly. As well known, in PSInSAR, the main target is the identification of individual pixels that exhibit a “PS behavior”, i.e. they are only slightly affected by both temporal and geometrical decorrelation. Typically, these scatterers correspond to man-made objects, but PS have been identified also in non-urban areas, where exposed rocks or outcrops can indeed create good radar benchmarks and enable high-quality displacement measurements. Contrary to interferogram stacking techniques, PS analyses are carried out on a pixel-by-pixel basis, with no filtering of the interferograms, in order to preserve phase values from possible incoherent clutter surrounding good radar targets. In fact, any filtering process implies a spatial smoothing of the data that could compromise - rather than improve - phase coherence, at least for isolated PS. Although the PS approach usually allows one to retrieve high quality deformation measurements on a sparse grid of good radar targets, in some datasets it is quite evident how the number of pixels where some information can be extracted could be significantly increased by relaxing the hypothesis on target coherence and searching for pixels where the coherence level is high enough at least in some interferograms of the data-stack, not necessarily all. The idea of computing a “coherence matrix” for each pixel of the area of interest have been already proposed in previous papers, together with a statistical estimation of some physical parameters of interest (e.g. the average displacement rate) based on the covariance matrix. In past publications

  9. Using an active contour method to detect bilge dumps from SAR imagery

    CSIR Research Space (South Africa)

    Mdakane, Lizwe W

    2016-07-01

    Full Text Available An automatic approach to detect bilge dumping in synthetic aperture radar (SAR) images over Southern African oceans is proposed. The approach uses a threshold-based algorithm and a region-based active contour model (ACM) algorithm to achieve...

  10. Localized landslide risk assessment with multi pass L band DInSAR analysis

    Science.gov (United States)

    Yun, HyeWon; Rack Kim, Jung; Lin, Shih-Yuan; Choi, YunSoo

    2014-05-01

    In terms of data availability and error correction, landslide forecasting by Differential Interferometric SAR (DInSAR) analysis is not easy task. Especially, the landslides by the anthropogenic construction activities frequently occurred in the localized cutting side of mountainous area. In such circumstances, it is difficult to attain sufficient enough accuracy because of the external factors inducing the error component in electromagnetic wave propagation. For instance, the local climate characteristics such as orographic effect and the proximity to water source can produce the significant anomalies in the water vapor distribution and consequently result in the error components of InSAR phase angle measurements. Moreover the high altitude parts of target area cause the stratified tropospheric delay error in DInSAR measurement. The other obstacle in DInSAR observation over the potential landside site is the vegetation canopy which causes the decorrelation of InSAR phase. Thus rather than C band sensor such as ENVISAT, ERS and RADARSAT, DInSAR analysis with L band ALOS PLASAR is more recommendable. Together with the introduction of L band DInSAR analysis, the improved DInSAR technique to cope all above obstacles is necessary. Thus we employed two approaches i.e. StaMPS/MTI (Stanford Method for Persistent Scatterers/Multi-Temporal InSAR, Hopper et al., 2007) which was newly developed for extracting the reliable deformation values through time series analysis and two pass DInSAR with the error term compensation based on the external weather information in this study. Since the water vapor observation from spaceborne radiometer is not feasible by the temporal gap in this case, the quantities from weather Research Forecasting (WRF) with 1 km spatial resolution was used to address the atmospheric phase error in two pass DInSAR analysis. Also it was observed that base DEM offset with time dependent perpendicular baselines of InSAR time series produce a significant error

  11. SAR Imagery Segmentation by Statistical Region Growing and Hierarchical Merging

    Energy Technology Data Exchange (ETDEWEB)

    Ushizima, Daniela Mayumi; Carvalho, E.A.; Medeiros, F.N.S.; Martins, C.I.O.; Marques, R.C.P.; Oliveira, I.N.S.

    2010-05-22

    This paper presents an approach to accomplish synthetic aperture radar (SAR) image segmentation, which are corrupted by speckle noise. Some ordinary segmentation techniques may require speckle filtering previously. Our approach performs radar image segmentation using the original noisy pixels as input data, eliminating preprocessing steps, an advantage over most of the current methods. The algorithm comprises a statistical region growing procedure combined with hierarchical region merging to extract regions of interest from SAR images. The region growing step over-segments the input image to enable region aggregation by employing a combination of the Kolmogorov-Smirnov (KS) test with a hierarchical stepwise optimization (HSWO) algorithm for the process coordination. We have tested and assessed the proposed technique on artificially speckled image and real SAR data containing different types of targets.

  12. Fast Superpixel Segmentation Algorithm for PolSAR Images

    Directory of Open Access Journals (Sweden)

    Zhang Yue

    2017-10-01

    Full Text Available As a pre-processing technique, superpixel segmentation algorithms should be of high computational efficiency, accurate boundary adherence and regular shape in homogeneous regions. A fast superpixel segmentation algorithm based on Iterative Edge Refinement (IER has shown to be applicable on optical images. However, it is difficult to obtain the ideal results when IER is applied directly to PolSAR images due to the speckle noise and small or slim regions in PolSAR images. To address these problems, in this study, the unstable pixel set is initialized as all the pixels in the PolSAR image instead of the initial grid edge pixels. In the local relabeling of the unstable pixels, the fast revised Wishart distance is utilized instead of the Euclidean distance in CIELAB color space. Then, a post-processing procedure based on dissimilarity measure is empolyed to remove isolated small superpixels as well as to retain the strong point targets. Finally, extensive experiments based on a simulated image and a real-world PolSAR image from Airborne Synthetic Aperture Radar (AirSAR are conducted, showing that the proposed algorithm, compared with three state-of-the-art methods, performs better in terms of several commonly used evaluation criteria with high computational efficiency, accurate boundary adherence, and homogeneous regularity.

  13. The SARVIEWS Project: Automated SAR Processing in Support of Operational Near Real-time Volcano Monitoring

    Science.gov (United States)

    Meyer, F. J.; Webley, P. W.; Dehn, J.; Arko, S. A.; McAlpin, D. B.; Gong, W.

    2016-12-01

    Volcanic eruptions are among the most significant hazards to human society, capable of triggering natural disasters on regional to global scales. In the last decade, remote sensing has become established in operational volcano monitoring. Centers like the Alaska Volcano Observatory rely heavily on remote sensing data from optical and thermal sensors to provide time-critical hazard information. Despite this high use of remote sensing data, the presence of clouds and a dependence on solar illumination often limit their impact on decision making. Synthetic Aperture Radar (SAR) systems are widely considered superior to optical sensors in operational monitoring situations, due to their weather and illumination independence. Still, the contribution of SAR to operational volcano monitoring has been limited in the past due to high data costs, long processing times, and low temporal sampling rates of most SAR systems. In this study, we introduce the automatic SAR processing system SARVIEWS, whose advanced data analysis and data integration techniques allow, for the first time, a meaningful integration of SAR into operational monitoring systems. We will introduce the SARVIEWS database interface that allows for automatic, rapid, and seamless access to the data holdings of the Alaska Satellite Facility. We will also present a set of processing techniques designed to automatically generate a set of SAR-based hazard products (e.g. change detection maps, interferograms, geocoded images). The techniques take advantage of modern signal processing and radiometric normalization schemes, enabling the combination of data from different geometries. Finally, we will show how SAR-based hazard information is integrated in existing multi-sensor decision support tools to enable joint hazard analysis with data from optical and thermal sensors. We will showcase the SAR processing system using a set of recent natural disasters (both earthquakes and volcanic eruptions) to demonstrate its

  14. Segmentation of Polarimetric SAR Images Usig Wavelet Transformation and Texture Features

    Science.gov (United States)

    Rezaeian, A.; Homayouni, S.; Safari, A.

    2015-12-01

    Polarimetric Synthetic Aperture Radar (PolSAR) sensors can collect useful observations from earth's surfaces and phenomena for various remote sensing applications, such as land cover mapping, change and target detection. These data can be acquired without the limitations of weather conditions, sun illumination and dust particles. As result, SAR images, and in particular Polarimetric SAR (PolSAR) are powerful tools for various environmental applications. Unlike the optical images, SAR images suffer from the unavoidable speckle, which causes the segmentation of this data difficult. In this paper, we use the wavelet transformation for segmentation of PolSAR images. Our proposed method is based on the multi-resolution analysis of texture features is based on wavelet transformation. Here, we use the information of gray level value and the information of texture. First, we produce coherency or covariance matrices and then generate span image from them. In the next step of proposed method is texture feature extraction from sub-bands is generated from discrete wavelet transform (DWT). Finally, PolSAR image are segmented using clustering methods as fuzzy c-means (FCM) and k-means clustering. We have applied the proposed methodology to full polarimetric SAR images acquired by the Uninhabited Aerial Vehicle Synthetic Aperture Radar (UAVSAR) L-band system, during July, in 2012 over an agricultural area in Winnipeg, Canada.

  15. SEGMENTATION OF POLARIMETRIC SAR IMAGES USIG WAVELET TRANSFORMATION AND TEXTURE FEATURES

    Directory of Open Access Journals (Sweden)

    A. Rezaeian

    2015-12-01

    Full Text Available Polarimetric Synthetic Aperture Radar (PolSAR sensors can collect useful observations from earth’s surfaces and phenomena for various remote sensing applications, such as land cover mapping, change and target detection. These data can be acquired without the limitations of weather conditions, sun illumination and dust particles. As result, SAR images, and in particular Polarimetric SAR (PolSAR are powerful tools for various environmental applications. Unlike the optical images, SAR images suffer from the unavoidable speckle, which causes the segmentation of this data difficult. In this paper, we use the wavelet transformation for segmentation of PolSAR images. Our proposed method is based on the multi-resolution analysis of texture features is based on wavelet transformation. Here, we use the information of gray level value and the information of texture. First, we produce coherency or covariance matrices and then generate span image from them. In the next step of proposed method is texture feature extraction from sub-bands is generated from discrete wavelet transform (DWT. Finally, PolSAR image are segmented using clustering methods as fuzzy c-means (FCM and k-means clustering. We have applied the proposed methodology to full polarimetric SAR images acquired by the Uninhabited Aerial Vehicle Synthetic Aperture Radar (UAVSAR L-band system, during July, in 2012 over an agricultural area in Winnipeg, Canada.

  16. Automatic Thermal Infrared Panoramic Imaging Sensor

    National Research Council Canada - National Science Library

    Gutin, Mikhail; Tsui, Eddy K; Gutin, Olga; Wang, Xu-Ming; Gutin, Alexey

    2006-01-01

    .... Automatic detection, location, and tracking of targets outside protected area ensures maximum protection and at the same time reduces the workload on personnel, increases reliability and confidence...

  17. The SARS-unique domain (SUD of SARS coronavirus contains two macrodomains that bind G-quadruplexes.

    Directory of Open Access Journals (Sweden)

    Jinzhi Tan

    2009-05-01

    Full Text Available Since the outbreak of severe acute respiratory syndrome (SARS in 2003, the three-dimensional structures of several of the replicase/transcriptase components of SARS coronavirus (SARS-CoV, the non-structural proteins (Nsps, have been determined. However, within the large Nsp3 (1922 amino-acid residues, the structure and function of the so-called SARS-unique domain (SUD have remained elusive. SUD occurs only in SARS-CoV and the highly related viruses found in certain bats, but is absent from all other coronaviruses. Therefore, it has been speculated that it may be involved in the extreme pathogenicity of SARS-CoV, compared to other coronaviruses, most of which cause only mild infections in humans. In order to help elucidate the function of the SUD, we have determined crystal structures of fragment 389-652 ("SUD(core" of Nsp3, which comprises 264 of the 338 residues of the domain. Both the monoclinic and triclinic crystal forms (2.2 and 2.8 A resolution, respectively revealed that SUD(core forms a homodimer. Each monomer consists of two subdomains, SUD-N and SUD-M, with a macrodomain fold similar to the SARS-CoV X-domain. However, in contrast to the latter, SUD fails to bind ADP-ribose, as determined by zone-interference gel electrophoresis. Instead, the entire SUD(core as well as its individual subdomains interact with oligonucleotides known to form G-quadruplexes. This includes oligodeoxy- as well as oligoribonucleotides. Mutations of selected lysine residues on the surface of the SUD-N subdomain lead to reduction of G-quadruplex binding, whereas mutations in the SUD-M subdomain abolish it. As there is no evidence for Nsp3 entering the nucleus of the host cell, the SARS-CoV genomic RNA or host-cell mRNA containing long G-stretches may be targets of SUD. The SARS-CoV genome is devoid of G-stretches longer than 5-6 nucleotides, but more extended G-stretches are found in the 3'-nontranslated regions of mRNAs coding for certain host-cell proteins

  18. Wave directional spectrum from SAR imagery

    Digital Repository Service at National Institute of Oceanography (India)

    Fernandes, A.A.; Sarma, Y.V.B.; Menon, H.B.; Vethamony, P.

    Gaussian smoothed SAR image spectra have been evaluated from 512 x 512 pixel subscenes of image mode ERS-1 SAR scenes off Goa, Visakhapatnam, Paradeep and Portugal. The two recently acquired scenes off Portugal showed the signature of swell...

  19. Novel Polarimetric SAR Interferometry Algorithms, Phase I

    Data.gov (United States)

    National Aeronautics and Space Administration — Polarimetric radar interferometry (PolInSAR) is a new SAR imaging mode that is rapidly becoming an important technique for bare earth topographic mapping, tree...

  20. SAR matrices: automated extraction of information-rich SAR tables from large compound data sets.

    Science.gov (United States)

    Wassermann, Anne Mai; Haebel, Peter; Weskamp, Nils; Bajorath, Jürgen

    2012-07-23

    We introduce the SAR matrix data structure that is designed to elucidate SAR patterns produced by groups of structurally related active compounds, which are extracted from large data sets. SAR matrices are systematically generated and sorted on the basis of SAR information content. Matrix generation is computationally efficient and enables processing of large compound sets. The matrix format is reminiscent of SAR tables, and SAR patterns revealed by different categories of matrices are easily interpretable. The structural organization underlying matrix formation is more flexible than standard R-group decomposition schemes. Hence, the resulting matrices capture SAR information in a comprehensive manner.

  1. The Performance Analysis Based on SAR Sample Covariance Matrix

    Directory of Open Access Journals (Sweden)

    Esra Erten

    2012-03-01

    Full Text Available Multi-channel systems appear in several fields of application in science. In the Synthetic Aperture Radar (SAR context, multi-channel systems may refer to different domains, as multi-polarization, multi-interferometric or multi-temporal data, or even a combination of them. Due to the inherent speckle phenomenon present in SAR images, the statistical description of the data is almost mandatory for its utilization. The complex images acquired over natural media present in general zero-mean circular Gaussian characteristics. In this case, second order statistics as the multi-channel covariance matrix fully describe the data. For practical situations however, the covariance matrix has to be estimated using a limited number of samples, and this sample covariance matrix follow the complex Wishart distribution. In this context, the eigendecomposition of the multi-channel covariance matrix has been shown in different areas of high relevance regarding the physical properties of the imaged scene. Specifically, the maximum eigenvalue of the covariance matrix has been frequently used in different applications as target or change detection, estimation of the dominant scattering mechanism in polarimetric data, moving target indication, etc. In this paper, the statistical behavior of the maximum eigenvalue derived from the eigendecomposition of the sample multi-channel covariance matrix in terms of multi-channel SAR images is simplified for SAR community. Validation is performed against simulated data and examples of estimation and detection problems using the analytical expressions are as well given.

  2. Urban Aerodynamic Roughness Length Mapping Using Multitemporal SAR Data

    Directory of Open Access Journals (Sweden)

    Fengli Zhang

    2017-01-01

    Full Text Available Aerodynamic roughness is very important to urban meteorological and climate studies. Radar remote sensing is considered to be an effective means for aerodynamic roughness retrieval because radar backscattering is sensitive to the surface roughness and geometric structure of a given target. In this paper, a methodology for aerodynamic roughness length estimation using SAR data in urban areas is introduced. The scale and orientation characteristics of backscattering of various targets in urban areas were firstly extracted and analyzed, which showed great potential of SAR data for urban roughness elements characterization. Then the ground truth aerodynamic roughness was calculated from wind gradient data acquired by the meteorological tower using fitting and iterative method. And then the optimal dimension of the upwind sector for the aerodynamic roughness calculation was determined through a correlation analysis between backscattering extracted from SAR data at various upwind sector areas and the aerodynamic roughness calculated from the meteorological tower data. Finally a quantitative relationship was set up to retrieve the aerodynamic roughness length from SAR data. Experiments based on ALOS PALSAR and COSMO-SkyMed data from 2006 to 2011 prove that the proposed methodology can provide accurate roughness length estimations for the spatial and temporal analysis of urban surface.

  3. Convolutional Neural Networks for SAR Image Segmentation

    DEFF Research Database (Denmark)

    Malmgren-Hansen, David; Nobel-Jørgensen, Morten

    2015-01-01

    Segmentation of Synthetic Aperture Radar (SAR) images has several uses, but it is a difficult task due to a number of properties related to SAR images. In this article we show how Convolutional Neural Networks (CNNs) can easily be trained for SAR image segmentation with good results. Besides...

  4. Imaging in severe acute respiratory syndrome (SARS)

    International Nuclear Information System (INIS)

    Antonio, G.E.; Wong, K.T.; Chu, W.C.W.; Hui, D.S.C.; Cheng, F.W.T.; Yuen, E.H.Y.; Chung, S.S.C.; Fok, T.F.; Sung, J.J.Y.; Ahuja, A.T.

    2003-01-01

    Severe acute respiratory syndrome (SARS) is a highly infectious disease caused by a novel coronavirus, and has become pandemic within a short period of time. Imaging plays an important role in the diagnosis, management and follow-up of patients with SARS. The current status of imaging in SARS is presented in this review

  5. Precision Rectification of Airborne SAR Image

    DEFF Research Database (Denmark)

    Dall, Jørgen; Liao, M.; Zhang, Zhe

    1997-01-01

    A simple and direct procedure for the rectification of a certain class of airborne SAR data is presented. The relief displacements of SAR data are effectively removed by means of a digital elevation model and the image is transformed to the ground coordinate system. SAR data from the Danish EMISAR...

  6. Permanent scatterer InSAR processing: Forsmark

    International Nuclear Information System (INIS)

    Dehls, John F.

    2006-04-01

    It has been speculated that slow, aseismic movement may be occurring along some of the fracture zones crosscutting the Forsmark area. The purpose of this study is to determine if it is possible to measure such movement using dInSAR. Differential SAR Interferometry (DInSAR) is a technique that compares the phases of multiple radar images of an area to measure surface change. The method has the potential to detect millimetric surface deformation along the sensor - target line-of-sight. Differences in phase between two images are easily viewed by combining, or interfering, the two phase-images. In the resulting image, the waves will either reinforce or cancel one another, depending upon the relative phases. The resulting image is called an interferogram and contains concentric bands of colour, or fringes, that are related to topography and/or surface deformation. New algorithms use many images acquired over a long time period to determine the movement history of individual objects, referred to as permanent scatterers. In the current project, standard PSInSAR processing was performed on 40 ERS-1 and ERS-2 scenes. The total area processed is approximately 1,500 km 2 . Slightly less than 20,000 permanent scatterers were identified.The highest densities were obtained along the coast and on the islands, where natural outcrops are more abundant. Two main classes of objects act as permanent scatterers in this area. The first are natural reflectors, such as rocks. The second are man-made reflectors, such as parts of buildings. Numerous local movements were found in the study area, relating to building subsidence, or compaction of anthropogenic fill. The dataset was divided into three groups for analysis, based upon the location of regional lineaments provided by SKB. Both statistical and geostatistical techniques were used. The median velocity of the three blocks did not differ by more than 0.2 mm/yr. This is not considered significant, given the possible magnitude of errors

  7. Permanent scatterer InSAR processing: Forsmark

    Energy Technology Data Exchange (ETDEWEB)

    Dehls, John F [Geological Survey of Norway, Trondheim (Norway)

    2006-04-15

    It has been speculated that slow, aseismic movement may be occurring along some of the fracture zones crosscutting the Forsmark area. The purpose of this study is to determine if it is possible to measure such movement using dInSAR. Differential SAR Interferometry (DInSAR) is a technique that compares the phases of multiple radar images of an area to measure surface change. The method has the potential to detect millimetric surface deformation along the sensor - target line-of-sight. Differences in phase between two images are easily viewed by combining, or interfering, the two phase-images. In the resulting image, the waves will either reinforce or cancel one another, depending upon the relative phases. The resulting image is called an interferogram and contains concentric bands of colour, or fringes, that are related to topography and/or surface deformation. New algorithms use many images acquired over a long time period to determine the movement history of individual objects, referred to as permanent scatterers. In the current project, standard PSInSAR processing was performed on 40 ERS-1 and ERS-2 scenes. The total area processed is approximately 1,500 km{sup 2}. Slightly less than 20,000 permanent scatterers were identified.The highest densities were obtained along the coast and on the islands, where natural outcrops are more abundant. Two main classes of objects act as permanent scatterers in this area. The first are natural reflectors, such as rocks. The second are man-made reflectors, such as parts of buildings. Numerous local movements were found in the study area, relating to building subsidence, or compaction of anthropogenic fill. The dataset was divided into three groups for analysis, based upon the location of regional lineaments provided by SKB. Both statistical and geostatistical techniques were used. The median velocity of the three blocks did not differ by more than 0.2 mm/yr. This is not considered significant, given the possible magnitude of

  8. Phase correction and error estimation in InSAR time series analysis

    Science.gov (United States)

    Zhang, Y.; Fattahi, H.; Amelung, F.

    2017-12-01

    During the last decade several InSAR time series approaches have been developed in response to the non-idea acquisition strategy of SAR satellites, such as large spatial and temporal baseline with non-regular acquisitions. The small baseline tubes and regular acquisitions of new SAR satellites such as Sentinel-1 allows us to form fully connected networks of interferograms and simplifies the time series analysis into a weighted least square inversion of an over-determined system. Such robust inversion allows us to focus more on the understanding of different components in InSAR time-series and its uncertainties. We present an open-source python-based package for InSAR time series analysis, called PySAR (https://yunjunz.github.io/PySAR/), with unique functionalities for obtaining unbiased ground displacement time-series, geometrical and atmospheric correction of InSAR data and quantifying the InSAR uncertainty. Our implemented strategy contains several features including: 1) improved spatial coverage using coherence-based network of interferograms, 2) unwrapping error correction using phase closure or bridging, 3) tropospheric delay correction using weather models and empirical approaches, 4) DEM error correction, 5) optimal selection of reference date and automatic outlier detection, 6) InSAR uncertainty due to the residual tropospheric delay, decorrelation and residual DEM error, and 7) variance-covariance matrix of final products for geodetic inversion. We demonstrate the performance using SAR datasets acquired by Cosmo-Skymed and TerraSAR-X, Sentinel-1 and ALOS/ALOS-2, with application on the highly non-linear volcanic deformation in Japan and Ecuador (figure 1). Our result shows precursory deformation before the 2015 eruptions of Cotopaxi volcano, with a maximum uplift of 3.4 cm on the western flank (fig. 1b), with a standard deviation of 0.9 cm (fig. 1a), supporting the finding by Morales-Rivera et al. (2017, GRL); and a post-eruptive subsidence on the same

  9. Research on Strong Clutter Suppression for Gaofen-3 Dual-Channel SAR/GMTI

    Directory of Open Access Journals (Sweden)

    Mingjie Zheng

    2018-03-01

    Full Text Available In spaceborne synthetic aperture radar (SAR, moving targets are almost buried in ground clutter due to the wide clutter Doppler spectrum and the restricted pulse repetition frequency (PRF, which increases the difficulty of moving target detection. Clutter suppression is one of the key issues in the spaceborne SAR moving target indicator operation. In this paper, we describe the clutter suppression principle and analyze the influence of amplitude and phase error on clutter suppression. In the following, a novel dual-channel SAR clutter suppression algorithm is proposed, which is suitable for the Gaofen-3(GF-3 SAR sensor. The proposed algorithm consists of three technique steps, namely adaptive two-dimensional (2D channel calibration, refined amplitude error correction and refined phase error correction. After channel error is corrected by these procedures, the clutter component, especially a strong clutter component, can be well suppressed. The validity of the proposed algorithm is verified by GF-3 SAR real data which demonstrates the ground moving-target indication (GMTI capability of GF-3 SAR sensor.

  10. Polarimetric scattering and SAR information retrieval

    CERN Document Server

    Jin, Ya-Qiu

    2013-01-01

    Taking an innovative look at Synthetic Aperture Radar (SAR), this practical reference fully covers new developments in SAR and its various methodologies and enables readers to interpret SAR imagery An essential reference on polarimetric Synthetic Aperture Radar (SAR), this book uses scattering theory and radiative transfer theory as a basis for its treatment of topics. It is organized to include theoretical scattering models and SAR data analysis techniques, and presents cutting-edge research on theoretical modelling of terrain surface. The book includes quantitative app

  11. Stalking SARS: CDC at Work

    Centers for Disease Control (CDC) Podcasts

    2014-05-22

    In this podcast for kids, the Kidtastics talk about the SARS outbreak and how CDC worked to solve the mystery.  Created: 5/22/2014 by National Center for Immunization and Respiratory Diseases (NCIRD).   Date Released: 5/22/2014.

  12. SARS – virus jumps species

    Indian Academy of Sciences (India)

    SARS – virus jumps species. Coronavirus reshuffles genes; Rotteir et al, Rotterdam showed the virus to jump from cats to mouse cells after single gene mutation ? Human disease due to virus jumping from wild or domestic animals; Present favourite animal - the cat; - edible or domestic.

  13. A strategy for Local Surface Stability Monitoring Using SAR Imagery

    Science.gov (United States)

    Kim, J.; Lan, C. W.; Lin, S. Y.; vanGasselt, S.; Yun, H.

    2017-12-01

    In order to provide sufficient facilities to satisfy a growing number of residents, nowadays there are many constructions and maintenance of infrastructures or buildings undergoing above and below the surface of urban area. In some cases we have learned that disasters might happen if the developments were conducted on unknown or geologically unstable ground or in over-developed areas. To avoid damages caused by such settings, it is essential to perform a regular monitoring scheme to understand the ground stability over the whole urban area. Through long-term monitoring, we firstly aim to observe surface stability over the construction sites. Secondly, we propose to implement an automatic extraction and tracking of suspicious unstable area. To achieve this, we used 12-days-interval C-band Sentinel-1A Synthetic Aperture Radar (SAR) images as the main source to perform regular monitoring. Differential Interferometric SAR (D-InSAR) technique was applied to generate interferograms. Together with the accumulation of updated Sentinel-1A SAR images, time series interferograms were formed accordingly. For the purpose of observing surface stability over known construction sites, the interferograms and the unwrapped products could be used to identify the surface displacement occurring before and after specific events. In addition, Small Baseline Subset (SBAS) and Permanent Scatterers (PS) approaches combining a set of unwrapped D-InSAR interferograms were also applied to derive displacement velocities over long-term periods. For some cases, we conducted the ascending and descending mode time series analysis to decompose three surface migration vectors and to precisely identify the risk pattern. Regarding the extraction of suspicious unstable areas, we propose to develop an automatic pattern recognition algorithm for the identification of specific fringe patterns involving various potential risks. The detected fringes were tracked in the time series interferograms and

  14. Analysis of the Effect of Radio Frequency Interference on Repeat Track Airborne InSAR System

    Directory of Open Access Journals (Sweden)

    Ding Bin

    2012-03-01

    Full Text Available The SAR system operating at low frequency is susceptible to Radio Frequency Interference (RFI from television station, radio station, and some other civil electronic facilities. The presence of RFI degrades the SAR image quality, and obscures the targets in the scene. Furthermore, RFI can cause interferometric phase error in repeat track InSAR system. In order to analyze the effect of RFI on interferometric phase of InSAR, real measured RFI signal are added on cone simulated SAR echoes. The imaging and interferometric processing results of both the RFI-contaminated and raw data are given. The effect of real measured RFI signal on repeat track InSAR system is analyzed. Finally, the imaging and interferometric processing results of both with and without RFI suppressed of the P band airborne repeat track InSAR real data are presented, which demonstrates the efficiency of the RFI suppression method in terms of decreasing the interferometric phase errors caused by RFI.

  15. a Statistical Texture Feature for Building Collapse Information Extraction of SAR Image

    Science.gov (United States)

    Li, L.; Yang, H.; Chen, Q.; Liu, X.

    2018-04-01

    Synthetic Aperture Radar (SAR) has become one of the most important ways to extract post-disaster collapsed building information, due to its extreme versatility and almost all-weather, day-and-night working capability, etc. In view of the fact that the inherent statistical distribution of speckle in SAR images is not used to extract collapsed building information, this paper proposed a novel texture feature of statistical models of SAR images to extract the collapsed buildings. In the proposed feature, the texture parameter of G0 distribution from SAR images is used to reflect the uniformity of the target to extract the collapsed building. This feature not only considers the statistical distribution of SAR images, providing more accurate description of the object texture, but also is applied to extract collapsed building information of single-, dual- or full-polarization SAR data. The RADARSAT-2 data of Yushu earthquake which acquired on April 21, 2010 is used to present and analyze the performance of the proposed method. In addition, the applicability of this feature to SAR data with different polarizations is also analysed, which provides decision support for the data selection of collapsed building information extraction.

  16. AN UNSUPERVISED CHANGE DETECTION BASED ON TEST STATISTIC AND KI FROM MULTI-TEMPORAL AND FULL POLARIMETRIC SAR IMAGES

    Directory of Open Access Journals (Sweden)

    J. Q. Zhao

    2016-06-01

    Full Text Available Accurate and timely change detection of Earth’s surface features is extremely important for understanding relationships and interactions between people and natural phenomena. Many traditional methods of change detection only use a part of polarization information and the supervised threshold selection. Those methods are insufficiency and time-costing. In this paper, we present a novel unsupervised change-detection method based on quad-polarimetric SAR data and automatic threshold selection to solve the problem of change detection. First, speckle noise is removed for the two registered SAR images. Second, the similarity measure is calculated by the test statistic, and automatic threshold selection of KI is introduced to obtain the change map. The efficiency of the proposed method is demonstrated by the quad-pol SAR images acquired by Radarsat-2 over Wuhan of China.

  17. A Basic Fourier Transform Pair for Slant Range-Doppler Modeling of Moving Scatterers for SAR Applications: Theory

    National Research Council Canada - National Science Library

    Sabry, R

    2007-01-01

    Considering the exploitation needs associated with the Synthetic Aperture Radar (SAR) applications involving moving and non-stationary targets, a fundamental spectral domain model for moving point and distribution of scatterers is presented...

  18. SARS and Population Health Technology

    OpenAIRE

    Eysenbach, Gunther

    2003-01-01

    The recent global outbreak of SARS (severe acute respiratory syndrome) provides an opportunity to study the use and impact of public health informatics and population health technology to detect and fight a global epidemic. Population health technology is the umbrella term for technology applications that have a population focus and the potential to improve public health. This includes the Internet, but also other technologies such as wireless devices, mobile phones, smart appliances, or smar...

  19. Population-based Post-crisis Psychological Distress: An Example From the SARS Outbreak in Taiwan

    Science.gov (United States)

    Peng, Eugene Yu-Chang; Lee, Ming-Been; Tsai, Shang-Ta; Yang, Chih-Chien; Morisky, Donald Edward; Tsai, Liang-Ting; Weng, Ya-Ling; Lyu, Shu-Yu

    2011-01-01

    Background/Purpose As a result of the severe acute respiratory syndrome (SARS) pandemic, the World Health Organization placed Taiwan on the travel alert list from May 21 to July 5, 2003. The aim of this study was to explore the post-crisis psychological distress among residents in Taiwan after the SARS epidemic. Methods The target population consisted of a nationwide representative sample of residents aged ≥ 18 years. Data were collected using computer assisted telephone interview systems by stratified random sampling according to geographic area. The survey (n = 1278) was conducted in November 2003, about 4 months after resolution of the SARS crisis in Taiwan. The maximum deviation of sampling error at the 95% confidence level was ± 2.74%. Psychological distress was measured by a question related to subject’s changes in perception of life, plus the five-item Brief Symptom Rating Scale. Multivariate logistic regression was used to examine the correlation of psychological distress. Results About 9.2% of the participants reported that their perceptions of life became more pessimistic following the SARS crisis. The prevalence of psychiatric morbidity was 11.7%. Major predictors of higher levels of pessimism after the SARS epidemic included demographic factors, perception of SARS and pre-paredness, knowing people or having personal experiences of SARS-related discrimination, and individual worries and psychiatric morbidity. The correlates of symptomatic cases, as indicated by the five-item Brief Symptom Rating Scale, included age ≥ 50 years, senior high school graduate, and worries about recurrence of SARS. Conclusion Psychological distress was significantly correlated with demographic factors and perception regarding the SARS epidemic. It is suggested that marketing of mental health education should be segmented according to age and education level, which should enhance crisis communication for newly emerging infectious diseases among community populations

  20. Analysis on Vertical Scattering Signatures in Forestry with PolInSAR

    Science.gov (United States)

    Guo, Shenglong; Li, Yang; Zhang, Jingjing; Hong, Wen

    2014-11-01

    We apply accurate topographic phase to the Freeman-Durden decomposition for polarimetric SAR interferometry (PolInSAR) data. The cross correlation matrix obtained from PolInSAR observations can be decomposed into three scattering mechanisms matrices accounting for the odd-bounce, double-bounce and volume scattering. We estimate the phase based on the Random volume over Ground (RVoG) model, and as the initial input parameter of the numerical method which is used to solve the parameters of decomposition. In addition, the modified volume scattering model introduced by Y. Yamaguchi is applied to the PolInSAR target decomposition in forest areas rather than the pure random volume scattering as proposed by Freeman-Durden to make best fit to the actual measured data. This method can accurately retrieve the magnitude associated with each mechanism and their vertical location along the vertical dimension. We test the algorithms with L- and P- band simulated data.

  1. SARS-related perceptions in Hong Kong.

    Science.gov (United States)

    Lau, Joseph T F; Yang, Xilin; Pang, Ellie; Tsui, H Y; Wong, Eric; Wing, Yun Kwok

    2005-03-01

    To understand different aspects of community responses related to severe acute respiratory syndrome (SARS), 2 population-based, random telephone surveys were conducted in June 2003 and January 2004 in Hong Kong. More than 70% of respondents would avoid visiting hospitals or mainland China to avoid contracting SARS. Most respondents believed that SARS could be transmitted through droplets, fomites, sewage, and animals. More than 90% believed that public health measures were efficacious means of prevention; 40.4% believed that SARS would resurge in Hong Kong; and approximately equals 70% would then wear masks in public places. High percentages of respondents felt helpless, horrified, and apprehensive because of SARS. Approximately 16% showed signs of posttraumatic symptoms, and approximately equals 40% perceived increased stress in family or work settings. The general public in Hong Kong has been very vigilant about SARS but needs to be more psychologically prepared to face a resurgence of the epidemic.

  2. Cleavage of spike protein of SARS coronavirus by protease factor Xa is associated with viral infectivity

    International Nuclear Information System (INIS)

    Du, Lanying; Kao, Richard Y.; Zhou, Yusen; He, Yuxian; Zhao, Guangyu; Wong, Charlotte; Jiang, Shibo; Yuen, Kwok-Yung; Jin, Dong-Yan; Zheng, Bo-Jian

    2007-01-01

    The spike (S) protein of SARS coronavirus (SARS-CoV) has been known to recognize and bind to host receptors, whose conformational changes then facilitate fusion between the viral envelope and host cell membrane, leading to viral entry into target cells. However, other functions of SARS-CoV S protein such as proteolytic cleavage and its implications to viral infection are incompletely understood. In this study, we demonstrated that the infection of SARS-CoV and a pseudovirus bearing the S protein of SARS-CoV was inhibited by a protease inhibitor Ben-HCl. Also, the protease Factor Xa, a target of Ben-HCl abundantly expressed in infected cells, was able to cleave the recombinant and pseudoviral S protein into S1 and S2 subunits, and the cleavage was inhibited by Ben-HCl. Furthermore, this cleavage correlated with the infectivity of the pseudovirus. Taken together, our study suggests a plausible mechanism by which SARS-CoV cleaves its S protein to facilitate viral infection

  3. SARS-related Perceptions in Hong Kong

    OpenAIRE

    Lau, Joseph T.F.; Yang, Xilin; Pang, Ellie; Tsui, H.Y.; Wong, Eric; Wing, Yun Kwok

    2005-01-01

    To understand different aspects of community responses related to severe acute respiratory syndrome (SARS), 2 population-based, random telephone surveys were conducted in June 2003 and January 2004 in Hong Kong. More than 70% of respondents would avoid visiting hospitals or mainland China to avoid contracting SARS. Most respondents believed that SARS could be transmitted through droplets, fomites, sewage, and animals. More than 90% believed that public health measures were efficacious means o...

  4. SAR system development for UAV multicopter platforms

    OpenAIRE

    Escartin Martínez, Antonio

    2015-01-01

    SAR system development for UAV multicopter platforms This thesis describes the optimization of a synthetic aperture radar (SAR) at X-band and its integration into an unmanned aerial vehicle (UAV) of type octocopter. For such optimization the SAR system functionality was extended from singlepol to fulpol and it has been optimized at hardware level in order to improve its quality against noise figure. After its integration into the octocopter platform, its features has been used in order to ...

  5. SAR processing in the cloud for oil detection in the Arctic

    Science.gov (United States)

    Garron, J.; Stoner, C.; Meyer, F. J.

    2016-12-01

    A new world of opportunity is being thawed from the ice of the Arctic, driven by decreased persistent Arctic sea-ice cover, increases in shipping, tourism, natural resource development. Tools that can automatically monitor key sea ice characteristics and potential oil spills are essential for safe passage in these changing waters. Synthetic aperture radar (SAR) data can be used to discriminate sea ice types and oil on the ocean surface and also for feature tracking. Additionally, SAR can image the earth through the night and most weather conditions. SAR data is volumetrically large and requires significant computing power to manipulate. Algorithms designed to identify key environmental features, like oil spills, in SAR imagery require secondary processing, and are computationally intensive, which can functionally limit their application in a real-time setting. Cloud processing is designed to manage big data and big data processing jobs by means of small cycles of off-site computations, eliminating up-front hardware costs. Pairing SAR data with cloud processing has allowed us to create and solidify a processing pipeline for SAR data products in the cloud to compare operational algorithms efficiency and effectiveness when run using an Alaska Satellite Facility (ASF) defined Amazon Machine Image (AMI). The products created from this secondary processing, were compared to determine which algorithm was most accurate in Arctic feature identification, and what operational conditions were required to produce the results on the ASF defined AMI. Results will be used to inform a series of recommendations to oil-spill response data managers and SAR users interested in expanding their analytical computing power.

  6. Autofocus algorithm for curvilinear SAR imaging

    Science.gov (United States)

    Bleszynski, E.; Bleszynski, M.; Jaroszewicz, T.

    2012-05-01

    We describe an approach to autofocusing for large apertures on curved SAR trajectories. It is a phase-gradient type method in which phase corrections compensating trajectory perturbations are estimated not directly from the image itself, but rather on the basis of partial" SAR data { functions of the slow and fast times { recon- structed (by an appropriate forward-projection procedure) from windowed scene patches, of sizes comparable to distances between distinct targets or localized features of the scene. The resulting partial data" can be shown to contain the same information on the phase perturbations as that in the original data, provided the frequencies of the perturbations do not exceed a quantity proportional to the patch size. The algorithm uses as input a sequence of conventional scene images based on moderate-size subapertures constituting the full aperture for which the phase corrections are to be determined. The subaperture images are formed with pixel sizes comparable to the range resolution which, for the optimal subaperture size, should be also approximately equal the cross-range resolution. The method does not restrict the size or shape of the synthetic aperture and can be incorporated in the data collection process in persistent sensing scenarios. The algorithm has been tested on the publicly available set of GOTCHA data, intentionally corrupted by random-walk-type trajectory uctuations (a possible model of errors caused by imprecise inertial navigation system readings) of maximum frequencies compatible with the selected patch size. It was able to eciently remove image corruption for apertures of sizes up to 360 degrees.

  7. Multifrequency OFDM SAR in Presence of Deception Jamming

    Directory of Open Access Journals (Sweden)

    Schuerger Jonathan

    2010-01-01

    Full Text Available Orthogonal frequency division multiplexing (OFDM is considered in this paper from the perspective of usage in imaging radar scenarios with deception jamming. OFDM radar signals are inherently multifrequency waveforms, composed of a number of subbands which are orthogonal to each other. While being employed extensively in communications, OFDM has not found comparatively wide use in radar, and, particularly, in synthetic aperture radar (SAR applications. In this paper, we aim to show the advantages of OFDM-coded radar signals with random subband composition when used in deception jamming scenarios. Two approaches to create a radar signal by the jammer are considered: instantaneous frequency (IF estimator and digital-RF-memory- (DRFM- based reproducer. In both cases, the jammer aims to create a copy of a valid target image via resending the radar signal at prescribed time intervals. Jammer signals are derived and used in SAR simulations with three types of signal models: OFDM, linear frequency modulated (LFM, and frequency-hopped (FH. Presented results include simulated peak side lobe (PSL and peak cross-correlation values for random OFDM signals, as well as simulated SAR imagery with IF and DRFM jammers'-induced false targets.

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

    Science.gov (United States)

    Libby, Vibeke; Kadar, Ivan

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

  9. Initial assessment of an airborne Ku-band polarimetric SAR.

    Energy Technology Data Exchange (ETDEWEB)

    Raynal, Ann Marie; Doerry, Armin Walter

    2013-02-01

    Polarimetric synthetic aperture radar (SAR) has been used for a variety of dual-use research applications since the 1940s. By measuring the direction of the electric field vector from radar echoes, polarimetry may enhance an analysts understanding of scattering effects for both earth monitoring and tactical surveillance missions. Polarimetry may provide insight into surface types, materials, or orientations for natural and man-made targets. Polarimetric measurements may also be used to enhance the contrast between scattering surfaces such as man-made objects and their surroundings. This report represents an initial assessment of the utility of, and applications for, polarimetric SAR at Ku-band for airborne or unmanned aerial systems.

  10. SAR Agriculture Rice Production Estimation (SARPE)

    Science.gov (United States)

    Raimadoya, M.

    2013-12-01

    SAR imageries, determine the target planting season to be linked. In this case the radar image only acquired two time series: the date of 26/10/2012 (stripmap) and 10/31/2012 (scanSAR) for series-1, and the date of 19/11/2012 (stripmap) and 11/24/2012 ( scanSAR) for series-2. The end result of this study is a model of crop growth status at the village, district and county level compared to KATAM. The County of Subang was used as a pilot exercise, and then was replicated into the two other counties (Karawang and Indramayu). Status of plant growth is divided into five phases: fallow wet, young vegetation, old vegetation, generative (pre-harvest), and dry fallow. The process of plant growth status was started with the determination of the majority in each rice field as a benchmark. This was followed by the creation of status recapitulation at the village, district, and ultimately at the county level. The county results were then compared with KATAM. Further replication to the rest of the other counties in the West Java Province, can only be done after the related PESBAK was improved in accordance to the area base standard requirement.

  11. Sentinel-3 SAR Altimetry Toolbox

    Science.gov (United States)

    Benveniste, Jerome; Lucas, Bruno; DInardo, Salvatore

    2015-04-01

    The prime objective of the SEOM (Scientific Exploitation of Operational Missions) element is to federate, support and expand the large international research community that the ERS, ENVISAT and the Envelope programmes have build up over the last 20 years for the future European operational Earth Observation missions, the Sentinels. Sentinel-3 builds directly on a proven heritage of ERS-2 and Envisat, and CryoSat-2, with a dual-frequency (Ku and C band) advanced Synthetic Aperture Radar Altimeter (SRAL) that provides measurements at a resolution of ~300m in SAR mode along track. Sentinel-3 will provide exact measurements of sea-surface height along with accurate topography measurements over sea ice, ice sheets, rivers and lakes. The first of the two Sentinels is expected to be launched in early 2015. The current universal altimetry toolbox is BRAT (Basic Radar Altimetry Toolbox) which can read all previous and current altimetry mission's data, but it does not have the capabilities to read the upcoming Sentinel-3 L1 and L2 products. ESA will endeavour to develop and supply this capability to support the users of the future Sentinel-3 SAR Altimetry Mission. BRAT is a collection of tools and tutorial documents designed to facilitate the processing of radar altimetry data. This project started in 2005 from the joint efforts of ESA (European Space Agency) and CNES (Centre National d'Etudes Spatiales), and it is freely available at http://earth.esa.int/brat. The tools enable users to interact with the most common altimetry data formats, the BratGUI is the front-end for the powerful command line tools that are part of the BRAT suite. BRAT can also be used in conjunction with Matlab/IDL (via reading routines) or in C/C++/Fortran via a programming API, allowing the user to obtain desired data, bypassing the data-formatting hassle. BRAT can be used simply to visualise data quickly, or to translate the data into other formats such as netCDF, ASCII text files, KML (Google Earth

  12. Optimisation of high-performance liquid chromatography with diode array detection using an automatic peak tracking procedure based on augmented iterative target transformation factor analysis

    NARCIS (Netherlands)

    van Zomeren, Paul; Hoogvorst, A.; Coenegracht, P.M J; de Jong, G.J.

    2004-01-01

    An automated method for the optimisation of high-performance liquid chromatography is developed. First of all, the sample of interest is analysed with various eluent compositions. All obtained data are combined into one augmented data matrix. Subsequently, augmented iterative target transformation

  13. Geometric calibration of ERS satellite SAR images

    DEFF Research Database (Denmark)

    Mohr, Johan Jacob; Madsen, Søren Nørvang

    2001-01-01

    Geometric calibration of the European Remote Sensing (ERS) Satellite synthetic aperture radar (SAR) slant range images is important in relation to mapping areas without ground reference points and also in relation to automated processing. The relevant SAR system parameters are discussed...

  14. PHARUS: A C-band Airborne SAR

    NARCIS (Netherlands)

    Hoogeboom, P.; Koomen, P.J.; Pouwels, H.; Snoeij, P.

    1990-01-01

    In The Netherlands a plan to design aircraft and build a polarimetric C-band SAR system of a novel design, called PHARUS (PHased Array Universal SAR) is carried out by three institutes. These institutes are the Physics and Electronics Laboratory TNO in The Hague (prime contractor and project

  15. SARS – Koch´Postulates proved.

    Indian Academy of Sciences (India)

    SARS – Koch´Postulates proved. Novel coronavirus identified from fluids of patients. Virus cultured in Vero cell line. Sera of patients have antibodies to virus. Cultured virus produces disease in Macaque monkeys. -produces specific immune response; -isolated virus is SARS CoV; -pathology similar to human.

  16. Underwater Topography Detection in Coastal Areas Using Fully Polarimetric SAR Data

    Directory of Open Access Journals (Sweden)

    Xiaolin Bian

    2017-06-01

    Full Text Available Fully polarimetric synthetic aperture radar (SAR can provide detailed information on scattering mechanisms that could enable the target or structure to be identified. This paper presents a method to detect underwater topography in coastal areas using high resolution fully polarimetric SAR data, while less prior information is required. The method is based on the shoaling and refraction of long surface gravity waves as they propagate shoreward. First, the surface scattering component is obtained by polarization decomposition. Then, wave fields are retrieved from the two-dimensional (2D spectra by the Fast Fourier Transformation (FFT. Finally, shallow water depths are estimated from the dispersion relation. Applicability and effectiveness of the proposed methodology are tested by using C-band fine quad-polarization mode RADARSAT-2 SAR data over the near-shore area of the Hainan province, China. By comparing with the values from an official electronic navigational chart (ENC, the estimated water depths are in good agreement with them. The average relative error of the detected results from the scattering mechanisms based method and single polarization SAR data are 9.73% and 11.53% respectively. The validation results indicate that the scattering mechanisms based methodology is more effective than only using the single polarization SAR data for underwater topography detection, and will inspire further research on underwater topography detection with fully polarimetric SAR data.

  17. Correcting Spatial Variance of RCM for GEO SAR Imaging Based on Time-Frequency Scaling

    Science.gov (United States)

    Yu, Ze; Lin, Peng; Xiao, Peng; Kang, Lihong; Li, Chunsheng

    2016-01-01

    Compared with low-Earth orbit synthetic aperture radar (SAR), a geosynchronous (GEO) SAR can have a shorter revisit period and vaster coverage. However, relative motion between this SAR and targets is more complicated, which makes range cell migration (RCM) spatially variant along both range and azimuth. As a result, efficient and precise imaging becomes difficult. This paper analyzes and models spatial variance for GEO SAR in the time and frequency domains. A novel algorithm for GEO SAR imaging with a resolution of 2 m in both the ground cross-range and range directions is proposed, which is composed of five steps. The first is to eliminate linear azimuth variance through the first azimuth time scaling. The second is to achieve RCM correction and range compression. The third is to correct residual azimuth variance by the second azimuth time-frequency scaling. The fourth and final steps are to accomplish azimuth focusing and correct geometric distortion. The most important innovation of this algorithm is implementation of the time-frequency scaling to correct high-order azimuth variance. As demonstrated by simulation results, this algorithm can accomplish GEO SAR imaging with good and uniform imaging quality over the entire swath. PMID:27428974

  18. Rapid Mapping Of Floods Using SAR Data: Opportunities And Critical Aspects

    Science.gov (United States)

    Pulvirenti, Luca; Pierdicca, Nazzareno; Chini, Marco

    2013-04-01

    The potentiality of spaceborne Synthetic Aperture Radar (SAR) for flood mapping was demonstrated by several past investigations. The synoptic view, the capability to operate in almost all-weather conditions and during both day time and night time and the sensitivity of the microwave band to water are the key features that make SAR data useful for monitoring inundation events. In addition, their high spatial resolution, which can reach 1m with the new generation of X-band instruments such as TerraSAR-X and COSMO-SkyMed (CSK), allows emergency managers to use flood maps at very high spatial resolution. CSK gives also the possibility of performing frequent observations of regions hit by floods, thanks to the four-satellite constellation. Current research on flood mapping using SAR is focused on the development of automatic algorithms to be used in near real time applications. The approaches are generally based on the low radar return from smooth open water bodies that behave as specular reflectors and appear dark in SAR images. The major advantage of automatic algorithms is the computational efficiency that makes them suitable for rapid mapping purposes. The choice of the threshold value that, in this kind of algorithms, separates flooded from non-flooded areas is a critical aspect because it depends on the characteristics of the observed scenario and on system parameters. To deal with this aspect an algorithm for automatic detection of the regions of low backscatter has been developed. It basically accomplishes three steps: 1) division of the SAR image in a set of non-overlapping sub-images or splits; 2) selection of inhomogeneous sub-images that contain (at least) two populations of pixels, one of which is formed by dark pixels; 3) the application in sequence of an automatic thresholding algorithm and a region growing algorithm in order to produce a homogeneous map of flooded areas. Besides the aforementioned choice of the threshold, rapid mapping of floods may

  19. Deep learning for SAR image formation

    Science.gov (United States)

    Mason, Eric; Yonel, Bariscan; Yazici, Birsen

    2017-04-01

    The recent success of deep learning has lead to growing interest in applying these methods to signal processing problems. This paper explores the applications of deep learning to synthetic aperture radar (SAR) image formation. We review deep learning from a perspective relevant to SAR image formation. Our objective is to address SAR image formation in the presence of uncertainties in the SAR forward model. We present a recurrent auto-encoder network architecture based on the iterative shrinkage thresholding algorithm (ISTA) that incorporates SAR modeling. We then present an off-line training method using stochastic gradient descent and discuss the challenges and key steps of learning. Lastly, we show experimentally that our method can be used to form focused images in the presence of phase uncertainties. We demonstrate that the resulting algorithm has faster convergence and decreased reconstruction error than that of ISTA.

  20. SARS: systematic review of treatment effects.

    Directory of Open Access Journals (Sweden)

    Lauren J Stockman

    2006-09-01

    Full Text Available BACKGROUND: The SARS outbreak of 2002-2003 presented clinicians with a new, life-threatening disease for which they had no experience in treating and no research on the effectiveness of treatment options. The World Health Organization (WHO expert panel on SARS treatment requested a systematic review and comprehensive summary of treatments used for SARS-infected patients in order to guide future treatment and identify priorities for research. METHODS AND FINDINGS: In response to the WHO request we conducted a systematic review of the published literature on ribavirin, corticosteroids, lopinavir and ritonavir (LPV/r, type I interferon (IFN, intravenous immunoglobulin (IVIG, and SARS convalescent plasma from both in vitro studies and in SARS patients. We also searched for clinical trial evidence of treatment for acute respiratory distress syndrome. Sources of data were the literature databases MEDLINE, EMBASE, BIOSIS, and the Cochrane Central Register of Controlled Trials (CENTRAL up to February 2005. Data from publications were extracted and evidence within studies was classified using predefined criteria. In total, 54 SARS treatment studies, 15 in vitro studies, and three acute respiratory distress syndrome studies met our inclusion criteria. Within in vitro studies, ribavirin, lopinavir, and type I IFN showed inhibition of SARS-CoV in tissue culture. In SARS-infected patient reports on ribavirin, 26 studies were classified as inconclusive, and four showed possible harm. Seven studies of convalescent plasma or IVIG, three of IFN type I, and two of LPV/r were inconclusive. In 29 studies of steroid use, 25 were inconclusive and four were classified as causing possible harm. CONCLUSIONS: Despite an extensive literature reporting on SARS treatments, it was not possible to determine whether treatments benefited patients during the SARS outbreak. Some may have been harmful. Clinical trials should be designed to validate a standard protocol for dosage

  1. Automatic face morphing for transferring facial animation

    NARCIS (Netherlands)

    Bui Huu Trung, B.H.T.; Bui, T.D.; Poel, Mannes; Heylen, Dirk K.J.; Nijholt, Antinus; Hamza, H.M.

    2003-01-01

    In this paper, we introduce a novel method of automatically finding the training set of RBF networks for morphing a prototype face to represent a new face. This is done by automatically specifying and adjusting corresponding feature points on a target face. The RBF networks are then used to transfer

  2. SARS and population health technology.

    Science.gov (United States)

    Eysenbach, Gunther

    2003-01-01

    The recent global outbreak of SARS (severe acute respiratory syndrome) provides an opportunity to study the use and impact of public health informatics and population health technology to detect and fight a global epidemic. Population health technology is the umbrella term for technology applications that have a population focus and the potential to improve public health. This includes the Internet, but also other technologies such as wireless devices, mobile phones, smart appliances, or smart homes. In the context of an outbreak or bioterrorism attack, such technologies may help to gather intelligence and detect diseases early, and communicate and exchange information electronically worldwide. Some of the technologies brought forward during the SARS epidemic may have been primarily motivated by marketing efforts, or were more directed towards reassuring people that "something is being done," ie, fighting an "epidemic of fear." To understand "fear epidemiology" is important because early warning systems monitoring data from a large number of people may not be able to discriminate between a biological epidemic and an epidemic of fear. The need for critical evaluation of all of these technologies is stressed.

  3. SAR image regularization with fast approximate discrete minimization.

    Science.gov (United States)

    Denis, Loïc; Tupin, Florence; Darbon, Jérôme; Sigelle, Marc

    2009-07-01

    Synthetic aperture radar (SAR) images, like other coherent imaging modalities, suffer from speckle noise. The presence of this noise makes the automatic interpretation of images a challenging task and noise reduction is often a prerequisite for successful use of classical image processing algorithms. Numerous approaches have been proposed to filter speckle noise. Markov random field (MRF) modelization provides a convenient way to express both data fidelity constraints and desirable properties of the filtered image. In this context, total variation minimization has been extensively used to constrain the oscillations in the regularized image while preserving its edges. Speckle noise follows heavy-tailed distributions, and the MRF formulation leads to a minimization problem involving nonconvex log-likelihood terms. Such a minimization can be performed efficiently by computing minimum cuts on weighted graphs. Due to memory constraints, exact minimization, although theoretically possible, is not achievable on large images required by remote sensing applications. The computational burden of the state-of-the-art algorithm for approximate minimization (namely the alpha -expansion) is too heavy specially when considering joint regularization of several images. We show that a satisfying solution can be reached, in few iterations, by performing a graph-cut-based combinatorial exploration of large trial moves. This algorithm is applied to joint regularization of the amplitude and interferometric phase in urban area SAR images.

  4. Radiometric Performance of the TerraSAR-X Mission over More Than Ten Years of Operation

    Directory of Open Access Journals (Sweden)

    Marco Schwerdt

    2018-05-01

    Full Text Available The TerraSAR-X mission, based on two satellites, has produced SAR data products of high quality for a number of scientific and commercial applications for more than ten years. To guarantee the stability and the reliability of these highly accurate SAR data products, both systems were first accurately calibrated during their respective commissioning phases and have been permanently monitored since then. Based on a short description of the methods applied, this paper focuses on the radiometric performance including the gain and phase properties of the transmit/receiver modules, the antenna pattern checked by evaluating scenes acquired over uniformly distributed targets and the radiometric stability derived from permanently deployed point targets. The outcome demonstrates the remarkable performance of both systems since their respective launch.

  5. Automatic definition of targeted biological volumes for the radiotherapy applications; Definition automatique des volumes biologiques cibles pour les applications de radiotherapie

    Energy Technology Data Exchange (ETDEWEB)

    Hatt, M.; Visvikis, D. [LaTIM, U650 Inserm, 29 - Brest (France); Cheze-Le-Rest, C. [Service de medecine nucleaire, 29 - Brest (France); Pradier, O. [Service de radiotherapie, 29 - Brest (France)

    2009-10-15

    The proposed method: Fuzzy locally adaptive Bayesian (F.L.A.B.) showed its reliability and its precision on very complete collection of realistic simulated and real data. Its use in the context of radiotherapy allows to consider easily the studies implementation and scenari of dose painting or dose escalation, including in complex cases of heterogenous fixations. It is conceivable to apply F.L.A.B. on PET images with F.M.I.S.O. ({sup 18}F fluoro misonidazole) or F.L.T. (fluoro-L-thymidine) to complete the definition of the biological target volume. (N.C.)

  6. Yeast based small molecule screen for inhibitors of SARS-CoV.

    Directory of Open Access Journals (Sweden)

    Matthew Frieman

    Full Text Available Severe acute respiratory coronavirus (SARS-CoV emerged in 2002, resulting in roughly 8000 cases worldwide and 10% mortality. The animal reservoirs for SARS-CoV precursors still exist and the likelihood of future outbreaks in the human population is high. The SARS-CoV papain-like protease (PLP is an attractive target for pharmaceutical development because it is essential for virus replication and is conserved among human coronaviruses. A yeast-based assay was established for PLP activity that relies on the ability of PLP to induce a pronounced slow-growth phenotype when expressed in S. cerevisiae. Induction of the slow-growth phenotype was shown to take place over a 60-hour time course, providing the basis for conducting a screen for small molecules that restore growth by inhibiting the function of PLP. Five chemical suppressors of the slow-growth phenotype were identified from the 2000 member NIH Diversity Set library. One of these, NSC158362, potently inhibited SARS-CoV replication in cell culture without toxic effects on cells, and it specifically inhibited SARS-CoV replication but not influenza virus replication. The effect of NSC158362 on PLP protease, deubiquitinase and anti-interferon activities was investigated but the compound did not alter these activities. Another suppressor, NSC158011, demonstrated the ability to inhibit PLP protease activity in a cell-based assay. The identification of these inhibitors demonstrated a strong functional connection between the PLP-based yeast assay, the inhibitory compounds, and SARS-CoV biology. Furthermore the data with NSC158362 suggest a novel mechanism for inhibition of SARS-CoV replication that may involve an unknown activity of PLP, or alternatively a direct effect on a cellular target that modifies or bypasses PLP function in yeast and mammalian cells.

  7. Wave directional spectrum from SAR imagery

    Digital Repository Service at National Institute of Oceanography (India)

    Fernandes, A.A.; Sarma, Y.V.B.; Menon, H.B.; Vethamony, P.

    < 2m and the zero-crossing period during the satellite overpass is small (< 6s, �O�O < 60m). We therefore utilized the visit of one of the authors (Sarma) to the Southampton Oceanographic Centre, U.K., to procure two ERS-1 digital image mode SAR...-dimensional FFT as well as a computer program for downloading SAR data from CCT. Finally we owe a debt of gratitude to J C da Silva, Southampton Oceanographic Centre, U K for sharing some of his SAR data with us. References Allan T. D. (Ed) (1983...

  8. Group Dynamics in Automatic Imitation.

    Science.gov (United States)

    Gleibs, Ilka H; Wilson, Neil; Reddy, Geetha; Catmur, Caroline

    Imitation-matching the configural body movements of another individual-plays a crucial part in social interaction. We investigated whether automatic imitation is not only influenced by who we imitate (ingroup vs. outgroup member) but also by the nature of an expected interaction situation (competitive vs. cooperative). In line with assumptions from Social Identity Theory), we predicted that both social group membership and the expected situation impact on the level of automatic imitation. We adopted a 2 (group membership target: ingroup, outgroup) x 2 (situation: cooperative, competitive) design. The dependent variable was the degree to which participants imitated the target in a reaction time automatic imitation task. 99 female students from two British Universities participated. We found a significant two-way interaction on the imitation effect. When interacting in expectation of cooperation, imitation was stronger for an ingroup target compared to an outgroup target. However, this was not the case in the competitive condition where imitation did not differ between ingroup and outgroup target. This demonstrates that the goal structure of an expected interaction will determine the extent to which intergroup relations influence imitation, supporting a social identity approach.

  9. Generation of human antibody fragments recognizing distinct epitopes of the nucleocapsid (N SARS-CoV protein using a phage display approach

    Directory of Open Access Journals (Sweden)

    Grasso Felicia

    2005-09-01

    Full Text Available Abstract Background Severe acute respiratory syndrome (SARS-CoV is a newly emerging virus that causes SARS with high mortality rate in infected people. Successful control of the global SARS epidemic will require rapid and sensitive diagnostic tests to monitor its spread, as well as, the development of vaccines and new antiviral compounds including neutralizing antibodies that effectively prevent or treat this disease. Methods The human synthetic single-chain fragment variable (scFv ETH-2 phage antibody library was used for the isolation of scFvs against the nucleocapsid (N protein of SARS-CoV using a bio panning-based strategy. The selected scFvs were characterized under genetics-molecular aspects and for SARS-CoV N protein detection in ELISA, western blotting and immunocytochemistry. Results Human scFv antibodies to N protein of SARS-CoV can be easily isolated by selecting the ETH-2 phage library on immunotubes coated with antigen. These in vitro selected human scFvs specifically recognize in ELISA and western blotting studies distinct epitopes in N protein domains and detect in immunohistochemistry investigations SARS-CoV particles in infected Vero cells. Conclusion The human scFv antibodies isolated and described in this study represent useful reagents for rapid detection of N SARS-CoV protein and SARS virus particles in infected target cells.

  10. SAR Tomography for Terrestrial Snow Stratigraphy

    Science.gov (United States)

    Lei, Y.; Xu, X.; Baldi, C.; Bleser, J. W. D.; Yueh, S. H.; Elder, K.

    2017-12-01

    Traditional microwave observation of snowpack includes brightness temperature and backscatter. The single baseline configuration and loss of phase information hinders the retrieval of snow stratigraphy information from microwave observations. In this paper, we are investigating the tomography of polarimetric SAR to measure snow stratigraphy. In the past two years, we have developed a homodyne frequency modulated continuous wave radar (FMCW), operation at three earth exploration satellite bands within the X-band and Ku-band spectrums (centered at 9.6 GHz, 13.5 GHz, and 17.2 GHz) at Jet Propulsion Laboratory. The transceiver is mounted to a dual-axis planar scanner (60cm in each direction), which translates the antenna beams across the target area creating a tomographic baseline in two directions. Dual-antenna architecture was implemented to improve the isolation between the transmitter and receiver. This technique offers a 50 dB improvement in signal-to-noise ratio versus conventional single-antenna FMCW radar systems. With current setting, we could have around 30cm vertical resolution. The system was deployed on a ground based tower at the Fraser Experimental Forest (FEF) Headquarters, near Fraser, CO, USA (39.847°N, 105.912°W) from February 1 to April 30, 2017 and run continuously with some gaps for required optional supports. FEF is a 93-km2 research watershed in the heart of the central Rocky Mountains approximately 80-km West of Denver. During the campaign, in situ measurements of snow depth and other snowpack properties were performed every week for comparison with the remotely sensed data. A network of soil moisture sensors, time-lapse cameras, acoustic depth sensors, laser depth sensor and meteorological instruments was installed next to the site to collect in situ measurements of snow, weather, and soil conditions. Preliminary tomographic processing of ground based SAR data of snowpack at X- and Ku- band has revealed the presence of multiple layers within

  11. The impact of curved satellite tracks on SAR focusing

    DEFF Research Database (Denmark)

    Mohr, Johan Jacob; Madsen, Søren Nørvang

    2000-01-01

    This paper addresses the geometric effect of processing single look complex synthetic aperture radar (SAR) data to a reference squint angle different from that given by the center of the real antenna beam. For data acquired on a straight flight line, the required transformation of radar coordinat...... from one Doppler reference to another is independent of the target elevation but for data acquired from a satellite orbit over a rotating Earth that is not true. Also the effect of ignoring Earth rotation is addressed....

  12. Association of acute adverse effects with high local SAR induced in the brain from prolonged RF head and neck hyperthermia

    International Nuclear Information System (INIS)

    Adibzadeh, F; Verhaart, R F; Rijnen, Z; Franckena, M; Van Rhoon, G C; Paulides, M M; Verduijn, G M; Fortunati, V

    2015-01-01

    To provide an adequate level of protection for humans from exposure to radio-frequency (RF) electromagnetic fields (EMF) and to assure that any adverse health effects are avoided. The basic restrictions in terms of the specific energy absorption rate (SAR) were prescribed by IEEE and ICNIRP. An example of a therapeutic application of non-ionizing EMF is hyperthermia (HT), in which intense RF energy is focused at a target region. Deep HT in the head and neck (H and N) region involves inducing energy at 434 MHz for 60 min on target. Still, stray exposure of the brain is considerable, but to date only very limited side-effects were observed. The objective of this study is to investigate the stringency of the current basic restrictions by relating the induced EM dose in the brain of patients treated with deep head and neck (H and N) HT to the scored acute health effects. We performed a simulation study to calculate the induced peak 10 g spatial-averaged SAR (psSAR 10g ) in the brains of 16 selected H and N patients who received the highest SAR exposure in the brain, i.e. who had the minimum brain-target distance and received high forwarded power during treatment. The results show that the maximum induced SAR in the brain of the patients can exceed the current basic restrictions (IEEE and ICNIRP) on psSAR 10g for occupational environments by 14 times. Even considering the high local SAR in the brain, evaluation of acute effects by the common toxicity criteria (CTC) scores revealed no indication of a serious acute neurological effect. In addition, this study provides pioneering quantitative human data on the association between maximum brain SAR level and acute adverse effects when brains are exposed to prolonged RF EMF. (paper)

  13. Monitoring informal settlements using SAR polarimetry

    CSIR Research Space (South Africa)

    Kleynhans, W

    2012-10-01

    Full Text Available for settlement mapping and detection has remained largely unexplored in Southern Africa. The objective of this study is to investigate the possible role that SAR polarimetry could play in the monitoring of informal settlements....

  14. Work session on the SAR. Pt. 2

    International Nuclear Information System (INIS)

    Burkart, K.

    1980-01-01

    The present paper contains the tables of the contribution of K. Burkart 'Work Session on the SAR' to the IAEA Interregional Training Course held in Sept/Oct. 1980 at the Kernforschungszentrum Karlsruhe. (RW)

  15. Image based SAR product simulation for analysis

    Science.gov (United States)

    Domik, G.; Leberl, F.

    1987-01-01

    SAR product simulation serves to predict SAR image gray values for various flight paths. Input typically consists of a digital elevation model and backscatter curves. A new method is described of product simulation that employs also a real SAR input image for image simulation. This can be denoted as 'image-based simulation'. Different methods to perform this SAR prediction are presented and advantages and disadvantages discussed. Ascending and descending orbit images from NASA's SIR-B experiment were used for verification of the concept: input images from ascending orbits were converted into images from a descending orbit; the results are compared to the available real imagery to verify that the prediction technique produces meaningful image data.

  16. Attribute Learning for SAR Image Classification

    Directory of Open Access Journals (Sweden)

    Chu He

    2017-04-01

    Full Text Available This paper presents a classification approach based on attribute learning for high spatial resolution Synthetic Aperture Radar (SAR images. To explore the representative and discriminative attributes of SAR images, first, an iterative unsupervised algorithm is designed to cluster in the low-level feature space, where the maximum edge response and the ratio of mean-to-variance are included; a cross-validation step is applied to prevent overfitting. Second, the most discriminative clustering centers are sorted out to construct an attribute dictionary. By resorting to the attribute dictionary, a representation vector describing certain categories in the SAR image can be generated, which in turn is used to perform the classifying task. The experiments conducted on TerraSAR-X images indicate that those learned attributes have strong visual semantics, which are characterized by bright and dark spots, stripes, or their combinations. The classification method based on these learned attributes achieves better results.

  17. SARS Patients and Their Close Contacts

    Science.gov (United States)

    ... Outreach Workers VIII. Infection Control for Laboratory and Pathology Procedures IX. Occupational Health Issues Appendix I1 Appendix ... SARS was recognized as a global threat in March 2003, after first appearing in Southern China in ...

  18. Multiple Input - Multiple Output (MIMO) SAR

    Data.gov (United States)

    National Aeronautics and Space Administration — This effort will research and implement advanced Multiple-Input Multiple-Output (MIMO) Synthetic Aperture Radar (SAR) techniques which have the potential to improve...

  19. Automatic segmentation of the clinical target volume and organs at risk in the planning CT for rectal cancer using deep dilated convolutional neural networks.

    Science.gov (United States)

    Men, Kuo; Dai, Jianrong; Li, Yexiong

    2017-12-01

    Delineation of the clinical target volume (CTV) and organs at risk (OARs) is very important for radiotherapy but is time-consuming and prone to inter-observer variation. Here, we proposed a novel deep dilated convolutional neural network (DDCNN)-based method for fast and consistent auto-segmentation of these structures. Our DDCNN method was an end-to-end architecture enabling fast training and testing. Specifically, it employed a novel multiple-scale convolutional architecture to extract multiple-scale context features in the early layers, which contain the original information on fine texture and boundaries and which are very useful for accurate auto-segmentation. In addition, it enlarged the receptive fields of dilated convolutions at the end of networks to capture complementary context features. Then, it replaced the fully connected layers with fully convolutional layers to achieve pixel-wise segmentation. We used data from 278 patients with rectal cancer for evaluation. The CTV and OARs were delineated and validated by senior radiation oncologists in the planning computed tomography (CT) images. A total of 218 patients chosen randomly were used for training, and the remaining 60 for validation. The Dice similarity coefficient (DSC) was used to measure segmentation accuracy. Performance was evaluated on segmentation of the CTV and OARs. In addition, the performance of DDCNN was compared with that of U-Net. The proposed DDCNN method outperformed the U-Net for all segmentations, and the average DSC value of DDCNN was 3.8% higher than that of U-Net. Mean DSC values of DDCNN were 87.7% for the CTV, 93.4% for the bladder, 92.1% for the left femoral head, 92.3% for the right femoral head, 65.3% for the intestine, and 61.8% for the colon. The test time was 45 s per patient for segmentation of all the CTV, bladder, left and right femoral heads, colon, and intestine. We also assessed our approaches and results with those in the literature: our system showed superior

  20. SAR Ambiguity Study for the Cassini Radar

    Science.gov (United States)

    Hensley, Scott; Im, Eastwood; Johnson, William T. K.

    1993-01-01

    The Cassini Radar's synthetic aperture radar (SAR) ambiguity analysis is unique with respect to other spaceborne SAR ambiguity analyses owing to the non-orbiting spacecraft trajectory, asymmetric antenna pattern, and burst mode of data collection. By properly varying the pointing, burst mode timing, and radar parameters along the trajectory this study shows that the signal-to-ambiguity ratio of better than 15 dB can be achieved for all images obtained by the Cassini Radar.

  1. Around the laboratories: Rutherford: Successful tests on bubble chamber target technique; Stanford (SLAC): New storage rings proposal; Berkeley: The HAPPE project to examine cosmic rays with superconducting magnets; The 60th birthday of Professor N.N. Bogolyubov; Argonne: Performance of the automatic film measuring system POLLY II

    CERN Multimedia

    1969-01-01

    Around the laboratories: Rutherford: Successful tests on bubble chamber target technique; Stanford (SLAC): New storage rings proposal; Berkeley: The HAPPE project to examine cosmic rays with superconducting magnets; The 60th birthday of Professor N.N. Bogolyubov; Argonne: Performance of the automatic film measuring system POLLY II

  2. SARS: Key factors in crisis management.

    Science.gov (United States)

    Tseng, Hsin-Chao; Chen, Thai-Form; Chou, Shieu-Ming

    2005-03-01

    This study was conducted at a single hospital selected in Taipei during the SARS (Severe Acute Respiratory Syndrome) outbreak from March to July, 2003 in Taiwan. During this period of time, 104 SARS patients were admitted to the hospital. There were no negative reports related to the selected hospital despite its being located right in the center of an area struck by the epidemic. The purpose of this study was to identify the key factors enabling the hospital to survive SARS unscathed. Data were collected from in-depth interviews with the nursing directors and nursing managers of the SARS units, along with a review of relevant hospital documents. The five key elements identified as survival factors during this SARS crisis are as follows: 1. good control of timing for crisis management, 2. careful decision-making, 3. thorough implementation, 4. effective communication, and 5. trust between management and employees. The results of this study reconfirmed the selected hospital as a model for good crisis management during the SARS epidemic.

  3. Silencing of SARS-CoV spike gene by small interfering RNA in HEK 293T cells

    International Nuclear Information System (INIS)

    Qin Zhaoling; Zhao Ping; Zhang Xiaolian; Yu Jianguo; Cao Mingmei; Zhao Lanjuan; Luan Jie; Qi Zhongtian

    2004-01-01

    Two candidate small interfering RNAs (siRNAs) corresponding to severe acute respiratory syndrome-associated coronavirus (SARS-CoV) spike gene were designed and in vitro transcribed to explore the possibility of silencing SARS-CoV S gene. The plasmid pEGFP-optS, which contains the codon-optimized SARS-CoV S gene and expresses spike-EGFP fusion protein (S-EGFP) as silencing target and expressing reporter, was transfected with siRNAs into HEK 293T cells. At various time points of posttransfection, the levels of S-EGFP expression and amounts of spike mRNA transcript were detected by fluorescence microscopy, flow cytometry, Western blot, and real-time quantitative PCR, respectively. The results showed that the cells transfected with pEGFP-optS expressed S-EGFP fusion protein at a higher level compared with those transfected with pEGFP-S, which contains wildtype SARS-CoV spike gene sequence. The green fluorescence, mean fluorescence intensity, and SARS-CoV S RNA transcripts were found significantly reduced, and the expression of SARS-CoV S glycoprotein was strongly inhibited in those cells co-transfected with either EGFP- or S-specific siRNAs. Our findings demonstrated that the S-specific siRNAs used in this study were able to specifically and effectively inhibit SARS-CoV S glycoprotein expression in cultured cells through blocking the accumulation of S mRNA, which may provide an approach for studies on the functions of SARS-CoV S gene and development of novel prophylactic or therapeutic agents for SARS-CoV

  4. On the Design of Radar Corner Reflectors for Deformation Monitoring in Multi-Frequency InSAR

    Directory of Open Access Journals (Sweden)

    Matthew C. Garthwaite

    2017-06-01

    Full Text Available Trihedral corner reflectors are being increasingly used as point targets in deformation monitoring studies using interferometric synthetic aperture radar (InSAR techniques. The frequency and size dependence of the corner reflector Radar Cross Section (RCS means that no single design can perform equally in all the possible imaging modes and radar frequencies available on the currently orbiting Synthetic Aperture Radar (SAR satellites. Therefore, either a corner reflector design tailored to a specific data type or a compromise design for multiple data types is required. In this paper, I outline the practical and theoretical considerations that need to be made when designing appropriate radar targets, with a focus on supporting multi-frequency SAR data. These considerations are tested by performing field experiments on targets of different size using SAR images from TerraSAR-X, COSMO-SkyMed and RADARSAT-2. Phase noise behaviour in SAR images can be estimated by measuring the Signal-to-Clutter ratio (SCR in individual SAR images. The measured SCR of a point target is dependent on its RCS performance and the influence of clutter near to the deployed target. The SCR is used as a metric to estimate the expected InSAR displacement error incurred by the design of each target and to validate these observations against theoretical expectations. I find that triangular trihedral corner reflectors as small as 1 m in dimension can achieve a displacement error magnitude of a tenth of a millimetre or less in medium-resolution X-band data. Much larger corner reflectors (2.5 m or greater are required to achieve the same displacement error magnitude in medium-resolution C-band data. Compromise designs should aim to satisfy the requirements of the lowest SAR frequency to be used, providing that these targets will not saturate the sensor of the highest frequency to be used. Finally, accurate boresight alignment of the corner reflector can be critical to the overall

  5. Robust tie points selection for InSAR image coregistration

    Science.gov (United States)

    Skanderi, Takieddine; Chabira, Boulerbah; Afifa, Belkacem; Belhadj Aissa, Aichouche

    2013-10-01

    Image coregistration is an important step in SAR interferometry which is a well known method for DEM generation and surface displacement monitoring. A practical and widely used automatic coregistration algorithm is based on selecting a number of tie points in the master image and looking for the correspondence of each point in the slave image using correlation technique. The characteristics of these points, their number and their distribution have a great impact on the reliability of the estimated transformation. In this work, we present a method for automatic selection of suitable tie points that are well distributed over the common area without decreasing the desired tie points' number. First we select candidate points using Harris operator. Then from these points we select tie points depending on their cornerness measure (the highest first). Once a tie point is selected, its correspondence is searched for in the slave image, if the similarity measure maximum is less than a given threshold or it is at the border of the search window, this point is discarded and we proceed to the next Harris point, else, the cornerness of the remaining candidates Harris points are multiplied by a spatially radially increasing function centered at the selected point to disadvantage the points in a neighborhood of a radius determined from the size of the common area and the desired number of points. This is repeated until the desired number of points is selected. Results of an ERS1/2 tandem pair are presented and discussed.

  6. Classification of agricultural fields using time series of dual polarimetry TerraSAR-X images

    Directory of Open Access Journals (Sweden)

    S. Mirzaee

    2014-10-01

    Full Text Available Due to its special imaging characteristics, Synthetic Aperture Radar (SAR has become an important source of information for a variety of remote sensing applications dealing with environmental changes. SAR images contain information about both phase and intensity in different polarization modes, making them sensitive to geometrical structure and physical properties of the targets such as dielectric and plant water content. In this study we investigate multi temporal changes occurring to different crop types due to phenological changes using high-resolution TerraSAR-X imagers. The dataset includes 17 dual-polarimetry TSX data acquired from June 2012 to August 2013 in Lorestan province, Iran. Several features are extracted from polarized data and classified using support vector machine (SVM classifier. Training samples and different features employed in classification are also assessed in the study. Results show a satisfactory accuracy for classification which is about 0.91 in kappa coefficient.

  7. Non-Cooperative Bistatic SAR Clock Drift Compensation for Tomographic Acquisitions

    Directory of Open Access Journals (Sweden)

    Mario Azcueta

    2017-10-01

    Full Text Available In the last years, an important amount of research has been headed towards the measurement of above-ground forest biomass with polarimetric Synthetic Aperture Radar (SAR tomography techniques. This has motivated the proposal of future bistatic SAR missions, like the recent non-cooperative SAOCOM-CS and PARSIFAL from CONAE and ESA. It is well known that the quality of SAR tomography is directly related to the phase accuracy of the interferometer that, in the case of non-cooperative systems, can be particularly affected by the relative drift between onboard clocks. In this letter, we provide insight on the impact of the clock drift error on bistatic interferometry, as well as propose a correction algorithm to compensate its effect. The accuracy of the compensation is tested on simulated acquisitions over volumetric targets, estimating the final impact on tomographic profiles.

  8. Dynamics of SARS-coronavirus HR2 domain in the prefusion and transition states

    Science.gov (United States)

    McReynolds, Susanna; Jiang, Shaokai; Rong, Lijun; Caffrey, Michael

    2009-12-01

    The envelope glycoproteins S1 and S2 of severe acute respiratory syndrome coronavirus (SARS-CoV) mediate viral entry by conformational change from a prefusion state to a postfusion state that enables fusion of the viral and target membranes. In this work we present the characterization of the dynamic properties of the SARS-CoV S2-HR2 domain (residues 1141-1193 of S) in the prefusion and newly discovered transition states by NMR 15N relaxation studies. The dynamic properties of the different states, which are stabilized under different experimental conditions, extend the current model of viral membrane fusion and give insight into the design of structure-based antagonists of SARS-CoV in particular, as well as other enveloped viruses such as HIV.

  9. RESEARCH ON COORDINATE TRANSFORMATION METHOD OF GB-SAR IMAGE SUPPORTED BY 3D LASER SCANNING TECHNOLOGY

    Directory of Open Access Journals (Sweden)

    P. Wang

    2018-04-01

    Full Text Available In the image plane of GB-SAR, identification of deformation distribution is usually carried out by artificial interpretation. This method requires analysts to have adequate experience of radar imaging and target recognition, otherwise it can easily cause false recognition of deformation target or region. Therefore, it is very meaningful to connect two-dimensional (2D plane coordinate system with the common three-dimensional (3D terrain coordinate system. To improve the global accuracy and reliability of the transformation from 2D coordinates of GB-SAR images to local 3D coordinates, and overcome the limitation of traditional similarity transformation parameter estimation method, 3D laser scanning data is used to assist the transformation of GB-SAR image coordinates. A straight line fitting method for calculating horizontal angle was proposed in this paper. After projection into a consistent imaging plane, we can calculate horizontal rotation angle by using the linear characteristics of the structure in radar image and the 3D coordinate system. Aided by external elevation information by 3D laser scanning technology, we completed the matching of point clouds and pixels on the projection plane according to the geometric projection principle of GB-SAR imaging realizing the transformation calculation of GB-SAR image coordinates to local 3D coordinates. Finally, the effectiveness of the method is verified by the GB-SAR deformation monitoring experiment on the high slope of Geheyan dam.

  10. Research on Coordinate Transformation Method of Gb-Sar Image Supported by 3d Laser Scanning Technology

    Science.gov (United States)

    Wang, P.; Xing, C.

    2018-04-01

    In the image plane of GB-SAR, identification of deformation distribution is usually carried out by artificial interpretation. This method requires analysts to have adequate experience of radar imaging and target recognition, otherwise it can easily cause false recognition of deformation target or region. Therefore, it is very meaningful to connect two-dimensional (2D) plane coordinate system with the common three-dimensional (3D) terrain coordinate system. To improve the global accuracy and reliability of the transformation from 2D coordinates of GB-SAR images to local 3D coordinates, and overcome the limitation of traditional similarity transformation parameter estimation method, 3D laser scanning data is used to assist the transformation of GB-SAR image coordinates. A straight line fitting method for calculating horizontal angle was proposed in this paper. After projection into a consistent imaging plane, we can calculate horizontal rotation angle by using the linear characteristics of the structure in radar image and the 3D coordinate system. Aided by external elevation information by 3D laser scanning technology, we completed the matching of point clouds and pixels on the projection plane according to the geometric projection principle of GB-SAR imaging realizing the transformation calculation of GB-SAR image coordinates to local 3D coordinates. Finally, the effectiveness of the method is verified by the GB-SAR deformation monitoring experiment on the high slope of Geheyan dam.

  11. An ice-motion tracking system at the Alaska SAR facility

    Science.gov (United States)

    Kwok, Ronald; Curlander, John C.; Pang, Shirley S.; Mcconnell, Ross

    1990-01-01

    An operational system for extracting ice-motion information from synthetic aperture radar (SAR) imagery is being developed as part of the Alaska SAR Facility. This geophysical processing system (GPS) will derive ice-motion information by automated analysis of image sequences acquired by radars on the European ERS-1, Japanese ERS-1, and Canadian RADARSAT remote sensing satellites. The algorithm consists of a novel combination of feature-based and area-based techniques for the tracking of ice floes that undergo translation and rotation between imaging passes. The system performs automatic selection of the image pairs for input to the matching routines using an ice-motion estimator. It is designed to have a daily throughput of ten image pairs. A description is given of the GPS system, including an overview of the ice-motion-tracking algorithm, the system architecture, and the ice-motion products that will be available for distribution to geophysical data users.

  12. The effect of inhibition of PP1 and TNFα signaling on pathogenesis of SARS coronavirus

    Energy Technology Data Exchange (ETDEWEB)

    McDermott, Jason E.; Mitchell, Hugh D.; Gralinski, Lisa E.; Eisfeld, Amie J.; Josset, Laurence; Bankhead, Armand; Neumann, Gabriele; Tilton, Susan C.; Schäfer, Alexandra; Li, Chengjun; Fan, Shufang; McWeeney, Shannon; Baric, Ralph S.; Katze, Michael G.; Waters, Katrina M.

    2016-09-23

    The complex interplay between viral replication and host immune response during infection remains poorly understood. While many viruses are known to employ antiimmune strategies to facilitate their replication, highly pathogenic virus infections can also cause an excessive immune response that exacerbates, rather than reduces pathogenicity. To investigate this dichotomy in severe acute respiratory syndrome coronavirus (SARS-CoV), we developed a transcriptional network model of SARS-CoV infection in mice and used the model to prioritize candidate regulatory targets for further investigation. We validated our predictions in 18 different knockout (KO) mouse strains, showing that network topology provides significant predictive power to identify genes that are important for viral infection. We identified a novel player in the immune response to virus infection, Kepi, an inhibitory subunit of the protein phosphatase 1 (PP1) complex, which protects against SARS-CoV pathogenesis. We also found that receptors for the proinflammatory cytokine, tumor necrosis factor alpha (TNFα), promote pathogenesis through a parallel feed-forward circuit that promotes inflammation. These results are consistent with previous studies showing the role of over-stimulation of the inflammatory response to SARS-CoV in pathogenesis. We conclude that the critical balance between immune response and inflammation can be manipulated to improve the outcome of the infection. Further, our study provides two potential therapeutic strategies for mitigating the effects of SARS-CoV infection, and may provide insight into treatment strategies for Middle East Respiratory Syndrome Coronavirus (MERS-CoV).

  13. Convolutional neural networks based on augmented training samples for synthetic aperture radar target recognition

    Science.gov (United States)

    Yan, Yue

    2018-03-01

    A synthetic aperture radar (SAR) automatic target recognition (ATR) method based on the convolutional neural networks (CNN) trained by augmented training samples is proposed. To enhance the robustness of CNN to various extended operating conditions (EOCs), the original training images are used to generate the noisy samples at different signal-to-noise ratios (SNRs), multiresolution representations, and partially occluded images. Then, the generated images together with the original ones are used to train a designed CNN for target recognition. The augmented training samples can contrapuntally improve the robustness of the trained CNN to the covered EOCs, i.e., the noise corruption, resolution variance, and partial occlusion. Moreover, the significantly larger training set effectively enhances the representation capability for other conditions, e.g., the standard operating condition (SOC), as well as the stability of the network. Therefore, better performance can be achieved by the proposed method for SAR ATR. For experimental evaluation, extensive experiments are conducted on the Moving and Stationary Target Acquisition and Recognition dataset under SOC and several typical EOCs.

  14. Tracking lava flow emplacement on the east rift zone of Kilauea, Hawai’i with synthetic aperture radar (SAR) coherence

    Science.gov (United States)

    Dietterich, Hannah R.; Poland, Michael P.; Schmidt, David; Cashman, Katharine V.; Sherrod, David R.; Espinosa, Arkin Tapia

    2012-01-01

    Lava flow mapping is both an essential component of volcano monitoring and a valuable tool for investigating lava flow behavior. Although maps are traditionally created through field surveys, remote sensing allows an extraordinary view of active lava flows while avoiding the difficulties of mapping on location. Synthetic aperture radar (SAR) imagery, in particular, can detect changes in a flow field by comparing two images collected at different times with SAR coherence. New lava flows radically alter the scattering properties of the surface, making the radar signal decorrelated in SAR coherence images. We describe a new technique, SAR Coherence Mapping (SCM), to map lava flows automatically from coherence images independent of look angle or satellite path. We use this approach to map lava flow emplacement during the Pu‘u ‘Ō‘ō-Kupaianaha eruption at Kīlauea, Hawai‘i. The resulting flow maps correspond well with field mapping and better resolve the internal structure of surface flows, as well as the locations of active flow paths. However, the SCM technique is only moderately successful at mapping flows that enter vegetation, which is also often decorrelated between successive SAR images. Along with measurements of planform morphology, we are able to show that the length of time a flow stays decorrelated after initial emplacement is linearly related to the flow thickness. Finally, we use interferograms obtained after flow surfaces become correlated to show that persistent decorrelation is caused by post-emplacement flow subsidence.

  15. Human monoclonal antibody as prophylaxis for SARS coronavirus infection in ferrets

    NARCIS (Netherlands)

    ter Meulen, Jan; Bakker, Alexander B. H.; van den Brink, Edward N.; Weverling, Gerrit J.; Martina, Byron E. E.; Haagmans, Bart L.; Kuiken, Thijs; de Kruif, John; Preiser, Wolfgang; Spaan, Willy; Gelderblom, Hans R.; Goudsmit, Jaap; Osterhaus, Albert D. M. E.

    2004-01-01

    SARS coronavirus continues to cause sporadic cases of severe acute respiratory syndrome (SARS) in China. No active or passive immunoprophylaxis for disease induced by SARS coronavirus is available. We investigated prophylaxis of SARS coronavirus infection with a neutralising human monoclonal

  16. Detection and characterization of ship targets using CryoSat-2 altimeter waveforms

    OpenAIRE

    G?mez-Enri, Jesus; Scozzari, Andrea; Soldovieri, Francesco; Coca, Josep; Vignudelli, Stefano

    2016-01-01

    This article describes an investigation of the new possibilities offered by SAR altimetry compared with conventional altimetry in the detection and characterization of non-ocean targets. We explore the capabilities of the first SAR altimeter installed on the European Space Agency satellite CryoSat-2 for the detection and characterization of ships. We propose a methodology for the detection of anomalous targets in the radar signals, based on the advantages of SAR/Doppler processing over conven...

  17. Utility of Characterizing and Monitoring Suspected Underground Nuclear Sites with VideoSAR

    Science.gov (United States)

    Dauphin, S. M.; Yocky, D. A.; Riley, R.; Calloway, T. M.; Wahl, D. E.

    2016-12-01

    Sandia National Laboratories proposed using airborne synthetic aperture RADAR (SAR) collected in VideoSAR mode to characterize the Underground Nuclear Explosion Signature Experiment (UNESE) test bed site at the Nevada National Security Site (NNSS). The SNL SAR collected airborne, Ku-band (16.8 GHz center frequency), 0.2032 meter ground resolution over NNSS in August 2014 and X-band (9.6 GHz), 0.1016 meter ground resolution fully-polarimetric SAR in April 2015. This paper reports the findings of processing and exploiting VideoSAR for creating digital elevation maps, detecting cultural artifacts and exploiting full-circle polarimetric signatures. VideoSAR collects a continuous circle of phase history data, therefore, imagery can be formed over the 360-degrees of the site. Since the Ku-band VideoSAR had two antennas suitable for interferometric digital elevation mapping (DEM), DEMs could be generated over numerous aspect angles, filling in holes created by targets with height by imaging from all sides. Also, since the X-band VideoSAR was fully-polarimetric, scattering signatures could be gleaned from all angles also. Both of these collections can be used to find man-made objects and changes in elevation that might indicate testing activities. VideoSAR provides a unique, coherent measure of ground objects allowing one to create accurate DEMS, locate man-made objects, and identify scattering signatures via polarimetric exploitation. Sandia National Laboratories is a multi-program laboratory managed and operated by Sandia Corporation, a wholly owned subsidiary of Lockheed Martin Corporation, for the U.S. Department of Energy's National Nuclear Security Administration under contract DE-AC04-94AL85000. The authors would like to thank the National Nuclear Security Administration, Defense Nuclear Nonproliferation Research and Development, for sponsoring this work. We would also like to thank the Underground Nuclear Explosion Signatures Experiment team, a multi

  18. Finding weak points automatically

    International Nuclear Information System (INIS)

    Archinger, P.; Wassenberg, M.

    1999-01-01

    Operators of nuclear power stations have to carry out material tests at selected components by regular intervalls. Therefore a full automaticated test, which achieves a clearly higher reproducibility, compared to part automaticated variations, would provide a solution. In addition the full automaticated test reduces the dose of radiation for the test person. (orig.) [de

  19. Automatic Target Recognition for Hyperspectral Imagery

    Science.gov (United States)

    2012-03-01

    covariance matrix of the current processing window (Smetek, 2007). RX scores are then compared to a given threshold, Trx , and if RX is greater than Trx ...the pixel is labeled as an anomaly. Trx is based on the χ2-distribution with p degrees of freedom and p is the dimensionality of the data (Smetek

  20. Composite Classifiers for Automatic Target Recognition

    National Research Council Canada - National Science Library

    Wang, Lin-Cheng

    1998-01-01

    ...) using forward-looking infrared (FLIR) imagery. Two existing classifiers, one based on learning vector quantization and the other on modular neural networks, are used as the building blocks for our composite classifiers...

  1. Accelerated Scientific InSAR Processing, Phase I

    Data.gov (United States)

    National Aeronautics and Space Administration — Neva Ridge Technologies proposes to develop a suite of software tools for the analysis of SAR and InSAR data, focused on having a robust and adopted capability well...

  2. Simultaneous Observation Data of GB-SAR/PiSAR to Detect Flooding in an Urban Area

    Directory of Open Access Journals (Sweden)

    Manabu Watanabe

    2010-01-01

    Full Text Available We analyzed simultaneous observation data with ground-based synthetic aperture radar (GB-SAR and airborne SAR (PiSAR over a flood test site at which a simple house was constructed in a field. The PiSAR σ∘ under flood condition was 0.9 to 3.4 dB higher than that under nonflood condition. GB-SAR gives high spatial resolution as we could identify a single scattering component and a double bounce component from the house. GB-SAR showed that the σ∘ difference between the flooding and nonflooding conditions came from the double bounce scattering. We also confirm that the entropy is a sensitive parameter in the eigenvalue decomposition parameters, if the scattering process is dominated by the double bounce scattering. We conclude that σ∘ and entropy are a good parameter to be used to detect flooding, not only in agricultural and forest regions, but also in urban areas. We also conclude that GB-SAR is a powerful tool to supplement satellite and airborne observation, which has a relatively low spatial resolution.

  3. Simultaneous Observation Data of GB-SAR/PiSAR to Detect Flooding in an Urban Area

    Directory of Open Access Journals (Sweden)

    Shimada Masanobu

    2010-01-01

    Full Text Available Abstract We analyzed simultaneous observation data with ground-based synthetic aperture radar (GB-SAR and airborne SAR (PiSAR over a flood test site at which a simple house was constructed in a field. The PiSAR under flood condition was 0.9 to 3.4 dB higher than that under nonflood condition. GB-SAR gives high spatial resolution as we could identify a single scattering component and a double bounce component from the house. GB-SAR showed that the difference between the flooding and nonflooding conditions came from the double bounce scattering. We also confirm that the entropy is a sensitive parameter in the eigenvalue decomposition parameters, if the scattering process is dominated by the double bounce scattering. We conclude that and entropy are a good parameter to be used to detect flooding, not only in agricultural and forest regions, but also in urban areas. We also conclude that GB-SAR is a powerful tool to supplement satellite and airborne observation, which has a relatively low spatial resolution.

  4. Automatic exchange unit for control rod drive device

    International Nuclear Information System (INIS)

    Nasu, Seiji; Sasaki, Masayoshi.

    1982-01-01

    Purpose: To enable automatic reoperation and continuation without external power interruption remedy device at the time of recovering the interrupted power soruce during automatic positioning operation. Constitution: In case of an automatic exchange unit for a control rod drive device of the control type for setting the deviation between the positioning target position and the present position of the device to zero, the position data of the drive device of the positioning target value of the device is automatically read, and an interlock of operation inhibit is applied to a control system until the data reading is completed and automatic operation start or restart conditions are sequentially confirmed. After the confirmation, the interlock is released to start the automatic operation or reoperation. Accordingly, the automatic operation can be safely restarted and continued. (Yoshihara, H.)

  5. Infrastructure monitoring with spaceborne SAR sensors

    CERN Document Server

    ANGHEL, ANDREI; CACOVEANU, REMUS

    2017-01-01

    This book presents a novel non-intrusive infrastructure monitoring technique based on the detection and tracking of scattering centers in spaceborne SAR images. The methodology essentially consists of refocusing each available SAR image on an imposed 3D point cloud associated to the envisaged infrastructure element and identifying the reliable scatterers to be monitored by means of four dimensional (4D) tomography. The methodology described in this book provides a new perspective on infrastructure monitoring with spaceborne SAR images, is based on a standalone processing chain, and brings innovative technical aspects relative to conventional approaches. The book is intended primarily for professionals and researchers working in the area of critical infrastructure monitoring by radar remote sensing.

  6. Compact Polarimetric SAR Ship Detection with m-δ Decomposition Using Visual Attention Model

    Directory of Open Access Journals (Sweden)

    Lu Xu

    2016-09-01

    Full Text Available A few previous studies have illustrated the potentials of compact polarimetric Synthetic Aperture Radar (CP SAR in ship detection. In this paper, we design a ship detection algorithm of CP SAR from the perspective of computer vision. A ship detection algorithm using the pulsed cosine transform (PCT visual attention model is proposed to suppress background clutter and highlight conspicuous ship targets. It is the first time that a visual attention model is introduced to CP SAR application. The proposed algorithm is a quick and complete framework for practical use. Polarimetric features—the relative phase δ and volume scattering component—are extracted from m-δ decomposition to eliminate false alarms and modify the PCT model. The constant false alarm rate (CFAR algorithm based on lognormal distribution is adopted to detect ship targets, after a clutter distribution fitting procedure of the modified saliency map. The proposed method is then tested on three simulated circular-transmit-linear-receive (CTLR mode images, which covering East Sea of China. Compared with the detection results of SPAN and the saliency map with only single-channel amplitude, the proposed method achieves the highest detection rates and the lowest misidentification rate and highest figure of merit, proving the effectiveness of polarimetric information of compact polarimetric SAR ship detection and the enhancement from the visual attention model.

  7. PRF Ambiguity Detrmination for Radarsat ScanSAR System

    Science.gov (United States)

    Jin, Michael Y.

    1998-01-01

    PRF ambiguity is a potential problem for a spaceborne SAR operated at high frequencies. For a strip mode SAR, there were several approaches to solve this problem. This paper, however, addresses PRF ambiguity determination algorithms suitable for a burst mode SAR system such as the Radarsat ScanSAR. The candidate algorithms include the wavelength diversity algorithm, range look cross correlation algorithm, and multi-PRF algorithm.

  8. Fast iterative censoring CFAR algorithm for ship detection from SAR images

    Science.gov (United States)

    Gu, Dandan; Yue, Hui; Zhang, Yuan; Gao, Pengcheng

    2017-11-01

    Ship detection is one of the essential techniques for ship recognition from synthetic aperture radar (SAR) images. This paper presents a fast iterative detection procedure to eliminate the influence of target returns on the estimation of local sea clutter distributions for constant false alarm rate (CFAR) detectors. A fast block detector is first employed to extract potential target sub-images; and then, an iterative censoring CFAR algorithm is used to detect ship candidates from each target blocks adaptively and efficiently, where parallel detection is available, and statistical parameters of G0 distribution fitting local sea clutter well can be quickly estimated based on an integral image operator. Experimental results of TerraSAR-X images demonstrate the effectiveness of the proposed technique.

  9. SARS Risk Perception, Knowledge, Precautions, and Information Sources, the Netherlands

    Science.gov (United States)

    Aro, Arja R.; Oenema, Anke; de Zwart, Onno; Richardus, Jan Hendrik; Bishop, George D.

    2004-01-01

    Severe acute respiratory syndrome (SARS)–related risk perceptions, knowledge, precautionary actions, and information sources were studied in the Netherlands during the 2003 SARS outbreak. Although respondents were highly aware of the SARS outbreak, the outbreak did not result in unnecessary precautionary actions or fears. PMID:15496256

  10. Science data collection with polarimetric SAR

    DEFF Research Database (Denmark)

    Dall, Jørgen; Woelders, Kim; Madsen, Søren Nørvang

    1996-01-01

    Discusses examples on the use of polarimetric SAR in a number of Earth science studies. The studies are presently being conducted by the Danish Center for Remote Sensing. A few studies of the European Space Agency's EMAC programme are also discussed. The Earth science objectives are presented......, and the potential of polarimetric SAR is discussed and illustrated with data collected by the Danish airborne EMISAR system during a number of experiments in 1994 and 1995. The presentation will include samples of data acquired for the different studies...

  11. Satellite sar detection of hurricane helene (2006)

    DEFF Research Database (Denmark)

    Ju, Lian; Cheng, Yongcun; Xu, Qing

    2013-01-01

    In this paper, the wind structure of hurricane Helene (2006) over the Atlantic Ocean is investigated from a C-band RADARSAT-1 synthetic aperture radar (SAR) image acquired on 20 September 2006. First, the characteristics, e.g., the center, scale and area of the hurricane eye (HE) are determined. ...... observations from the stepped frequency microwave radiometer (SFMR) on NOAA P3 aircraft. All the results show the capability of hurricane monitoring by satellite SAR. Copyright © 2013 by the International Society of Offshore and Polar Engineers (ISOPE)....

  12. The planned Alaska SAR Facility - An overview

    Science.gov (United States)

    Carsey, Frank; Weeks, Wilford

    1987-01-01

    The Alaska SAR Facility (ASF) is described in an overview fashion. The facility consists of three major components, a Receiving Ground System, a SAR Processing System and an Analysis and Archiving System; the ASF Program also has a Science Working Team and the requisite management and operations systems. The ASF is now an approved and fully funded activity; detailed requirements and science background are presented for the facility to be implemented for data from the European ERS-1, the Japanese ERS-1 and Radarsat.

  13. Geologic mapping in Greenland with polarimetric SAR

    DEFF Research Database (Denmark)

    Dall, Jørgen; Madsen, Søren Nørvang; Brooks, C. K.

    1995-01-01

    The application of synthetic aperture radar (SAR) for geologic mapping in Greenland is investigated by the Danish Center for Remote Sensing (DCRS) in co-operation with the Danish Lithosphere Centre (DLC). In 1994 a pilot project was conducted in East Greenland. The Danish airborne SAR, EMISAR...... mapping is complicated by an extreme topography leading to massive shadowing, foreshortening and layover. An artifact characterised by high cross-polarisation is observed behind many sharp mountain ridges. A multi-reflection hypothesis has been investigated without finding the ultimate proof...

  14. Long term landslide monitoring with Ground Based SAR

    Science.gov (United States)

    Monserrat, Oriol; Crosetto, Michele; Luzi, Guido; Gili, Josep; Moya, Jose; Corominas, Jordi

    2014-05-01

    In the last decade, Ground-Based (GBSAR) has proven to be a reliable microwave Remote Sensing technique in several application fields, especially for unstable slopes monitoring. GBSAR can provide displacement measurements over few squared kilometres areas and with a very high spatial and temporal resolution. This work is focused on the use of GBSAR technique for long term landslide monitoring based on a particular data acquisition configuration, which is called discontinuous GBSAR (D-GBSAR). In the most commonly used GBSAR configuration, the radar is left installed in situ, acquiring data periodically, e.g. every few minutes. Deformations are estimated by processing sets of GBSAR images acquired during several weeks or months, without moving the system. By contrast, in the D-GBSAR the radar is installed and dismounted at each measurement campaign, revisiting a given site periodically. This configuration is useful to monitor slow deformation phenomena. In this work, two alternative ways for exploiting the D-GBSAR technique will be presented: the DInSAR technique and the Amplitude based Technique. The former is based on the exploitation of the phase component of the acquired SAR images and it allows providing millimetric precision on the deformation estimates. However, this technique presents several limitations like the reduction of measurable points with an increase in the period of observation, the ambiguous nature of the phase measurements, and the influence of the atmospheric phase component that can make it non applicable in some cases, specially when working in natural environments. The second approach, that is based on the use of the amplitude component of GB-SAR images combined with a image matching technique, will allow the estimation of the displacements over specific targets avoiding two of the limitations commented above: the phase unwrapping and atmosphere contribution but reducing the deformation measurement precision. Two successful examples of D

  15. A new implementation of full resolution SBAS-DInSAR processing chain for the effective monitoring of structures and infrastructures

    Science.gov (United States)

    Bonano, Manuela; Buonanno, Sabatino; Ojha, Chandrakanta; Berardino, Paolo; Lanari, Riccardo; Zeni, Giovanni; Manunta, Michele

    2017-04-01

    The advanced DInSAR technique referred to as Small BAseline Subset (SBAS) algorithm has already largely demonstrated its effectiveness to carry out multi-scale and multi-platform surface deformation analyses relevant to both natural and man-made hazards. Thanks to its capability to generate displacement maps and long-term deformation time series at both regional (low resolution analysis) and local (full resolution analysis) spatial scales, it allows to get more insights on the spatial and temporal patterns of localized displacements relevant to single buildings and infrastructures over extended urban areas, with a key role in supporting risk mitigation and preservation activities. The extensive application of the multi-scale SBAS-DInSAR approach in many scientific contexts has gone hand in hand with new SAR satellite mission development, characterized by different frequency bands, spatial resolution, revisit times and ground coverage. This brought to the generation of huge DInSAR data stacks to be efficiently handled, processed and archived, with a strong impact on both the data storage and the computational requirements needed for generating the full resolution SBAS-DInSAR results. Accordingly, innovative and effective solutions for the automatic processing of massive SAR data archives and for the operational management of the derived SBAS-DInSAR products need to be designed and implemented, by exploiting the high efficiency (in terms of portability, scalability and computing performances) of the new ICT methodologies. In this work, we present a novel parallel implementation of the full resolution SBAS-DInSAR processing chain, aimed at investigating localized displacements affecting single buildings and infrastructures relevant to very large urban areas, relying on different granularity level parallelization strategies. The image granularity level is applied in most steps of the SBAS-DInSAR processing chain and exploits the multiprocessor systems with distributed

  16. On Sea Ice Characterisation By Multi-Frequency SAR

    Science.gov (United States)

    Grahn, Jakob; Brekke, Camilla; Eltoft, Torbjorn; Holt, Benjamin

    2013-12-01

    By means of polarimetric target decomposition, quad-pol SAR data of sea ice is analysed at two frequency bands. In particular, the non negative eigenvalue decomposition (NNED) is applied on L- and C-band NASA/JPL AIR- SAR data acquired over the Beaufort sea in 2004. The de- composition separates the scattered radar signal into three types, dominated by double, volume and single bounce scattering respectively. Using ground truth derived from RADARSAT-1 and meteorological data, we investigate how the different frequency bands compare in terms of these scattering types. The ground truth contains multi year ice and three types of first year ice of different age and thickness. We find that C-band yields a higher scattered intensity in most ice and scattering types, as well as a more homogeneous intensity. L-band on the other hand yields more pronounced deformation features, such as ridges. The mean intensity contrast between the two thinnest ice types is highest in the double scattering component of C- band, although the contrast of the total signal is greater in L-band. This may indicate that the choice of polarimetric parameters is important for discriminating thin ice types.

  17. Feature discrimination/identification based upon SAR return variations

    Science.gov (United States)

    Rasco, W. A., Sr.; Pietsch, R.

    1978-01-01

    A study of the statistics of The look-to-look variation statistics in the returns recorded in-flight by a digital, realtime SAR system are analyzed. The determination that the variations in the look-to-look returns from different classes do carry information content unique to the classes was illustrated by a model based on four variants derived from four look in-flight SAR data under study. The model was limited to four classes of returns: mowed grass on a athletic field, rough unmowed grass and weeds on a large vacant field, young fruit trees in a large orchard, and metal mobile homes and storage buildings in a large mobile home park. The data population in excess of 1000 returns represented over 250 individual pixels from the four classes. The multivariant discriminant model operated on the set of returns for each pixel and assigned that pixel to one of the four classes, based on the target variants and the probability distribution function of the four variants for each class.

  18. Transfer Learning with Convolutional Neural Networks for SAR Ship Recognition

    Science.gov (United States)

    Zhang, Di; Liu, Jia; Heng, Wang; Ren, Kaijun; Song, Junqiang

    2018-03-01

    Ship recognition is the backbone of marine surveillance systems. Recent deep learning methods, e.g. Convolutional Neural Networks (CNNs), have shown high performance for optical images. Learning CNNs, however, requires a number of annotated samples to estimate numerous model parameters, which prevents its application to Synthetic Aperture Radar (SAR) images due to the limited annotated training samples. Transfer learning has been a promising technique for applications with limited data. To this end, a novel SAR ship recognition method based on CNNs with transfer learning has been developed. In this work, we firstly start with a CNNs model that has been trained in advance on Moving and Stationary Target Acquisition and Recognition (MSTAR) database. Next, based on the knowledge gained from this image recognition task, we fine-tune the CNNs on a new task to recognize three types of ships in the OpenSARShip database. The experimental results show that our proposed approach can obviously increase the recognition rate comparing with the result of merely applying CNNs. In addition, compared to existing methods, the proposed method proves to be very competitive and can learn discriminative features directly from training data instead of requiring pre-specification or pre-selection manually.

  19. Satellite SAR data assessment for Silk Road archaeological prospection

    Science.gov (United States)

    Chen, Fulong; Lasaponara, Rosa; Masini, Nicola; Yang, Ruixia

    2015-04-01

    direction of observed targets is beneficial for improved detection of potential linear remains (e.g. Great Wall in Han-dynasty surrounding the Yumen Frontier Pass) owing to the formation of dihedral and helix scatterings based on the theory of radar physics. Morevorer, spatial resolution of multi-mode SAR images for archaeology was compared in the sites of Niya, Yumen Frontier Pass and suspected protectorate of the western regions. Results indicated that high resolution tended to easier detection of ancient targets through the identification of backscattering anomalies. Finally, interferometric analysis was also evaluated to provide complementary information rather than the backscattering. The variation of coherence is closely related to the physical parameters of observed surface, e.g. soil moisture, mild-relief as well as materials; and consequently it is useful for the relic feature enhancement and identification, validated by the PALSAR coherence images in Niya site. Acknowledgement This research was performed within the framework of the project "Smart management of cultural heritage sites in Italy and China: Earth Observation and pilot projects", funded by the Italian Ministry of Foreign Affairs and the Hundred Talents Program of the Institute of Remote Sensing and Digital Earth, Chinese Academy of Sciences (Y2ZZ27101B). The PALSAR data were provided by the European Space Agency to the authors through the Category-1 Project Id. 28640. Reference [1] Lasaponara R., Masini N. 2013, Satellite Synthetic Aperture Radar in Archaeology and Cultural Landscape: An Overview. Archaeological Prospection, 20, 71-78, doi: 10.1002/arp.1452 [2] Chen F., Masini N., Yang R., Milillo P., Feng D., Lasaponara R., 2015 A Space View of Radar Archaeological Marks: First Applications of COSMO-SkyMed X-Band Data. Remote Sens. 2015, 7, 24-50; doi:10.3390/rs70100024. [3] Cigna, F.; Tapete, D.; Lasaponara, R.; Masini, N. Amplitude change detection with Envisat ASAR to image the cultural landscape

  20. SARS knowledge, perceptions, and behaviors: a comparison between Finns and the Dutch during the SARS outbreak in 2003

    NARCIS (Netherlands)

    Vartti, A.M.; Oenema, A.; Schreck, M.; Uutela, A.; Zwart, de O.; Brug, J.; Aro, A.R.

    2009-01-01

    BACKGROUND: The SARS outbreak served to test both local and international outbreak management and risk communication practices. PURPOSE: The study compares SARS knowledge, perceptions, behaviors, and information between Finns and the Dutch during the SARS outbreak in 2003. METHOD: The participants

  1. Operational SAR Data Processing in GIS Environments for Rapid Disaster Mapping

    Science.gov (United States)

    Bahr, Thomas

    2014-05-01

    DEM without the need of ground control points. This step includes radiometric calibration. (3) A subsequent change detection analysis generates the final map showing the extent of the flash flood on Nov. 5th 2010. The underlying algorithms are provided by three different sources: Geocoding & radiometric calibration (2) is a standard functionality from the commercial SARscape Toolbox for ArcGIS. This toolbox is extended by the filter tool (1), which is called from the SARscape modules in ENVI. The change detection analysis (3) is based on ENVI processing routines and scripted with IDL. (2) and (3) are integrated with ArcGIS using a predefined Python interface. These 3 processing steps are combined using the ArcGIS ModelBuilder to create a new model for rapid disaster mapping in ArcGIS, based on SAR data. Moreover, this model can be dissolved from its desktop environment and published to users across the ArcGIS Server enterprise. Thus disaster zones, e.g. after severe flooding, can be automatically identified and mapped to support local task forces - using an operational workflow for SAR image analysis, which can be executed by the responsible operators without SAR expert knowledge.

  2. SAR Image Classification Based on Its Texture Features

    Institute of Scientific and Technical Information of China (English)

    LI Pingxiang; FANG Shenghui

    2003-01-01

    SAR images not only have the characteristics of all-ay, all-eather, but also provide object information which is different from visible and infrared sensors. However, SAR images have some faults, such as more speckles and fewer bands. The authors conducted the experiments of texture statistics analysis on SAR image features in order to improve the accuracy of SAR image interpretation.It is found that the texture analysis is an effective method for improving the accuracy of the SAR image interpretation.

  3. CFAR Edge Detector for Polarimetric SAR Images

    DEFF Research Database (Denmark)

    Schou, Jesper; Skriver, Henning; Nielsen, Allan Aasbjerg

    2003-01-01

    Finding the edges between different regions in an image is one of the fundamental steps of image analysis, and several edge detectors suitable for the special statistics of synthetic aperture radar (SAR) intensity images have previously been developed. In this paper, a new edge detector for polar...

  4. Discovery and SAR of hydantoin TACE inhibitors

    Energy Technology Data Exchange (ETDEWEB)

    Yu, Wensheng; Guo, Zhuyan; Orth, Peter; Madison, Vincent; Chen, Lei; Dai, Chaoyang; Feltz, Robert J.; Girijavallabhan, Vinay M.; Kim, Seong Heon; Kozlowski, Joseph A.; Lavey, Brian J.; Li, Dansu; Lundell, Daniel; Niu, Xiaoda; Piwinski, John J.; Popovici-Muller, Janeta; Rizvi, Razia; Rosner, Kristin E.; Shankar, Bandarpalle B.; Shih, Neng-Yang; Siddiqui, M.A.; Sun, J.; Tong, L.; Umland, S.; Wong, M.K.; Yang, D.Y.; Zhou, G. (Merck)

    2010-09-03

    We disclose inhibitors of TNF-{alpha} converting enzyme (TACE) designed around a hydantoin zinc binding moiety. Crystal structures of inhibitors bound to TACE revealed monodentate coordination of the hydantoin to the zinc. SAR, X-ray, and modeling designs are described. To our knowledge, these are the first reported X-ray structures of TACE with a hydantoin zinc ligand.

  5. Digital demodulator for wide bandwidth SAR

    DEFF Research Database (Denmark)

    Jørgensen, Jørn Hjelm

    2000-01-01

    A novel approach to the design of efficient digital quadrature demodulators for wide bandwidth SAR systems is described. Efficiency is obtained by setting the intermediate frequency to 1/4 the ADC sampling frequency. One channel is made filter-free by synchronizing the local oscillator...

  6. Offshore wind mapping Mediterranean area using SAR

    DEFF Research Database (Denmark)

    Calaudi, Rosamaria; Arena, Felice; Badger, Merete

    2013-01-01

    Satellite observations of the ocean surface, for example from Synthetic Aperture Radars (SAR), provide information about the spatial wind variability over large areas. This is of special interest in the Mediterranean Sea, where spatial wind information is only provided by sparse buoys, often with...

  7. Automatic Photoelectric Telescope Service

    International Nuclear Information System (INIS)

    Genet, R.M.; Boyd, L.J.; Kissell, K.E.; Crawford, D.L.; Hall, D.S.; BDM Corp., McLean, VA; Kitt Peak National Observatory, Tucson, AZ; Dyer Observatory, Nashville, TN)

    1987-01-01

    Automatic observatories have the potential of gathering sizable amounts of high-quality astronomical data at low cost. The Automatic Photoelectric Telescope Service (APT Service) has realized this potential and is routinely making photometric observations of a large number of variable stars. However, without observers to provide on-site monitoring, it was necessary to incorporate special quality checks into the operation of the APT Service at its multiple automatic telescope installation on Mount Hopkins. 18 references

  8. Automatic Fiscal Stabilizers

    Directory of Open Access Journals (Sweden)

    Narcis Eduard Mitu

    2013-11-01

    Full Text Available Policies or institutions (built into an economic system that automatically tend to dampen economic cycle fluctuations in income, employment, etc., without direct government intervention. For example, in boom times, progressive income tax automatically reduces money supply as incomes and spendings rise. Similarly, in recessionary times, payment of unemployment benefits injects more money in the system and stimulates demand. Also called automatic stabilizers or built-in stabilizers.

  9. Peptide Mimicrying Between SARS Coronavirus Spike Protein and Human Proteins Reacts with SARS Patient Serum

    Directory of Open Access Journals (Sweden)

    K.-Y. Hwa

    2008-01-01

    Full Text Available Molecular mimicry, defined as similar structures shared by molecules from dissimilar genes or proteins, is a general strategy used by pathogens to infect host cells. Severe acute respiratory syndrome (SARS is a new human respiratory infectious disease caused by SARS coronavirus (SARS-CoV. The spike (S protein of SARS-CoV plays an important role in the virus entry into a cell. In this study, eleven synthetic peptides from the S protein were selected based on its sequence homology with human proteins. Two of the peptides D07 (residues 927–937 and D08 (residues 942–951 were recognized by the sera of SARS patients. Murine hyperimmune sera against these peptides bound to proteins of human lung epithelial cells A549. Another peptide D10 (residues 490–502 stimulated A549 to proliferate and secrete IL-8. The present results suggest that the selected S protein regions, which share sequence homology with human proteins, may play important roles in SARS-CoV infection.

  10. The Seamless SAR Archive (SSARA) Project and Other SAR Activities at UNAVCO

    Science.gov (United States)

    Baker, S.; Crosby, C. J.; Meertens, C. M.; Fielding, E. J.; Bryson, G.; Buechler, B.; Nicoll, J.; Baru, C.

    2014-12-01

    The seamless synthetic aperture radar archive (SSARA) implements a seamless distributed access system for SAR data and derived data products (i.e. interferograms). SSARA provides a unified application programming interface (API) for SAR data search and results at the Alaska Satellite Facility and UNAVCO (WInSAR and EarthScope data archives) through the use of simple web services. A federated query service was developed using the unified APIs, providing users a single search interface for both archives. Interest from the international community has prompted an effort to incorporate ESA's Virtual Archive 4 Geohazard Supersites and Natural Laboratories (GSNL) collections and other archives into the federated query service. SSARA also provides Digital Elevation Model access for topographic correction via a simple web service through OpenTopography and tropospheric correction products through JPL's OSCAR service. Additionally, UNAVCO provides data storage capabilities for WInSAR PIs with approved TerraSAR-X and ALOS-2 proposals which allows easier distribution to US collaborators on associated proposals and facilitates data access through the SSARA web services. Further work is underway to incorporate federated data discovery for GSNL across SAR, GPS, and seismic datasets provided by web services from SSARA, GSAC, and COOPEUS.

  11. Spaceborne Differential SAR Interferometry: Data Analysis Tools for Deformation Measurement

    Directory of Open Access Journals (Sweden)

    Michele Crosetto

    2011-02-01

    Full Text Available This paper is focused on spaceborne Differential Interferometric SAR (DInSAR for land deformation measurement and monitoring. In the last two decades several DInSAR data analysis procedures have been proposed. The objective of this paper is to describe the DInSAR data processing and analysis tools developed at the Institute of Geomatics in almost ten years of research activities. Four main DInSAR analysis procedures are described, which range from the standard DInSAR analysis based on a single interferogram to more advanced Persistent Scatterer Interferometry (PSI approaches. These different procedures guarantee a sufficient flexibility in DInSAR data processing. In order to provide a technical insight into these analysis procedures, a whole section discusses their main data processing and analysis steps, especially those needed in PSI analyses. A specific section is devoted to the core of our PSI analysis tools: the so-called 2+1D phase unwrapping procedure, which couples a 2D phase unwrapping, performed interferogram-wise, with a kind of 1D phase unwrapping along time, performed pixel-wise. In the last part of the paper, some examples of DInSAR results are discussed, which were derived by standard DInSAR or PSI analyses. Most of these results were derived from X-band SAR data coming from the TerraSAR-X and CosmoSkyMed sensors.

  12. Automatic differentiation bibliography

    Energy Technology Data Exchange (ETDEWEB)

    Corliss, G.F. [comp.

    1992-07-01

    This is a bibliography of work related to automatic differentiation. Automatic differentiation is a technique for the fast, accurate propagation of derivative values using the chain rule. It is neither symbolic nor numeric. Automatic differentiation is a fundamental tool for scientific computation, with applications in optimization, nonlinear equations, nonlinear least squares approximation, stiff ordinary differential equation, partial differential equations, continuation methods, and sensitivity analysis. This report is an updated version of the bibliography which originally appeared in Automatic Differentiation of Algorithms: Theory, Implementation, and Application.

  13. Proteolytic activation of the SARS-coronavirus spike protein: cutting enzymes at the cutting edge of antiviral research.

    Science.gov (United States)

    Simmons, Graham; Zmora, Pawel; Gierer, Stefanie; Heurich, Adeline; Pöhlmann, Stefan

    2013-12-01

    The severe acute respiratory syndrome (SARS) pandemic revealed that zoonotic transmission of animal coronaviruses (CoV) to humans poses a significant threat to public health and warrants surveillance and the development of countermeasures. The activity of host cell proteases, which cleave and activate the SARS-CoV spike (S) protein, is essential for viral infectivity and constitutes a target for intervention. However, the identities of the proteases involved have been unclear. Pioneer studies identified cathepsins and type II transmembrane serine proteases as cellular activators of SARS-CoV and demonstrated that several emerging viruses might exploit these enzymes to promote their spread. Here, we will review the proteolytic systems hijacked by SARS-CoV for S protein activation, we will discuss their contribution to viral spread in the host and we will outline antiviral strategies targeting these enzymes. This paper forms part of a series of invited articles in Antiviral Research on "From SARS to MERS: 10years of research on highly pathogenic human coronaviruses.'' Copyright © 2013 Elsevier B.V. All rights reserved.

  14. ANALYSIS OF MULTIPATH PIXELS IN SAR IMAGES

    Directory of Open Access Journals (Sweden)

    J. W. Zhao

    2016-06-01

    Full Text Available As the received radar signal is the sum of signal contributions overlaid in one single pixel regardless of the travel path, the multipath effect should be seriously tackled as the multiple bounce returns are added to direct scatter echoes which leads to ghost scatters. Most of the existing solution towards the multipath is to recover the signal propagation path. To facilitate the signal propagation simulation process, plenty of aspects such as sensor parameters, the geometry of the objects (shape, location, orientation, mutual position between adjacent buildings and the physical parameters of the surface (roughness, correlation length, permittivitywhich determine the strength of radar signal backscattered to the SAR sensor should be given in previous. However, it's not practical to obtain the highly detailed object model in unfamiliar area by field survey as it's a laborious work and time-consuming. In this paper, SAR imaging simulation based on RaySAR is conducted at first aiming at basic understanding of multipath effects and for further comparison. Besides of the pre-imaging simulation, the product of the after-imaging, which refers to radar images is also taken into consideration. Both Cosmo-SkyMed ascending and descending SAR images of Lupu Bridge in Shanghai are used for the experiment. As a result, the reflectivity map and signal distribution map of different bounce level are simulated and validated by 3D real model. The statistic indexes such as the phase stability, mean amplitude, amplitude dispersion, coherence and mean-sigma ratio in case of layover are analyzed with combination of the RaySAR output.

  15. Performance Analysis of Satellite Missions for Multi-Temporal SAR Interferometry

    Directory of Open Access Journals (Sweden)

    Fabio Bovenga

    2018-04-01

    Full Text Available Multi-temporal InSAR (MTI applications pose challenges related to the availability of coherent scattering from the ground surface, the complexity of the ground deformations, atmospheric artifacts, and visibility problems related to ground elevation. Nowadays, several satellite missions are available providing interferometric SAR data at different wavelengths, spatial resolutions, and revisit time. A new and interesting opportunity is provided by Sentinel-1, which has a spatial resolution comparable to that of previous ESA C-band sensors, and revisit times improved by up to 6 days. According to these different SAR space-borne missions, the present work discusses current and future opportunities of MTI applications in terms of ground instability monitoring. Issues related to coherent target detection, mean velocity precision, and product geo-location are addressed through a simple theoretical model assuming backscattering mechanisms related to point scatterers. The paper also presents an example of a multi-sensor ground instability investigation over Lesina Marina, a village in Southern Italy lying over a gypsum diapir, where a hydration process, involving the underlying anhydride, causes a smooth uplift and the formation of scattered sinkholes. More than 20 years of MTI SAR data have been processed, coming from both legacy ERS and ENVISAT missions, and latest-generation RADARSAT-2, COSMO-SkyMed, and Sentinel-1A sensors. Results confirm the presence of a rather steady uplift process, with limited to null variations throughout the whole monitored time-period.

  16. Performance Analysis of Satellite Missions for Multi-Temporal SAR Interferometry.

    Science.gov (United States)

    Bovenga, Fabio; Belmonte, Antonella; Refice, Alberto; Pasquariello, Guido; Nutricato, Raffaele; Nitti, Davide O; Chiaradia, Maria T

    2018-04-27

    Multi-temporal InSAR (MTI) applications pose challenges related to the availability of coherent scattering from the ground surface, the complexity of the ground deformations, atmospheric artifacts, and visibility problems related to ground elevation. Nowadays, several satellite missions are available providing interferometric SAR data at different wavelengths, spatial resolutions, and revisit time. A new and interesting opportunity is provided by Sentinel-1, which has a spatial resolution comparable to that of previous ESA C-band sensors, and revisit times improved by up to 6 days. According to these different SAR space-borne missions, the present work discusses current and future opportunities of MTI applications in terms of ground instability monitoring. Issues related to coherent target detection, mean velocity precision, and product geo-location are addressed through a simple theoretical model assuming backscattering mechanisms related to point scatterers. The paper also presents an example of a multi-sensor ground instability investigation over Lesina Marina, a village in Southern Italy lying over a gypsum diapir, where a hydration process, involving the underlying anhydride, causes a smooth uplift and the formation of scattered sinkholes. More than 20 years of MTI SAR data have been processed, coming from both legacy ERS and ENVISAT missions, and latest-generation RADARSAT-2, COSMO-SkyMed, and Sentinel-1A sensors. Results confirm the presence of a rather steady uplift process, with limited to null variations throughout the whole monitored time-period.

  17. A noncovalent class of papain-like protease/deubiquitinase inhibitors blocks SARS virus replication

    Energy Technology Data Exchange (ETDEWEB)

    Ratia, Kiira; Pegan, Scott; Takayama, Jun; Sleeman, Katrina; Coughlin, Melissa; Baliji, Surendranath; Chaudhuri, Rima; Fu, Wentao; Prabhakar, Bellur S.; Johnson, Michael E.; Baker, Susan C.; Ghosh, Arun K.; Mesecar, Andrew D. (Loyola); (Purdue); (UIC)

    2008-10-27

    We report the discovery and optimization of a potent inhibitor against the papain-like protease (PLpro) from the coronavirus that causes severe acute respiratory syndrome (SARS-CoV). This unique protease is not only responsible for processing the viral polyprotein into its functional units but is also capable of cleaving ubiquitin and ISG15 conjugates and plays a significant role in helping SARS-CoV evade the human immune system. We screened a structurally diverse library of 50,080 compounds for inhibitors of PLpro and discovered a noncovalent lead inhibitor with an IC{sub 50} value of 20 {mu}M, which was improved to 600 nM via synthetic optimization. The resulting compound, GRL0617, inhibited SARS-CoV viral replication in Vero E6 cells with an EC{sub 50} of 15 {mu}M and had no associated cytotoxicity. The X-ray structure of PLpro in complex with GRL0617 indicates that the compound has a unique mode of inhibition whereby it binds within the S4-S3 subsites of the enzyme and induces a loop closure that shuts down catalysis at the active site. These findings provide proof-of-principle that PLpro is a viable target for development of antivirals directed against SARS-CoV, and that potent noncovalent cysteine protease inhibitors can be developed with specificity directed toward pathogenic deubiquitinating enzymes without inhibiting host DUBs.

  18. Azimuth Phase Coding for Range Ambiguity Suppression in SAR

    DEFF Research Database (Denmark)

    Dall, Jørgen; Kusk, Anders

    2004-01-01

    A novel ambiguity suppression technique is proposed. Range ambiguities in synthetic aperture radar (SAR) images are eliminated with an azimuth filter after having applied an azimuth phase modulation to the transmitted pulses and a corresponding demodulation to the received pulses. The technique...... excels by actually eliminating the ambiguities rather than just defocusing them as most other techniques do. This makes the proposed technique applicable to distributed targets. The range ambiguity suppression permits the pulse repetition frequency (PRF) to exceed the upper limit otherwise defined...... by the antenna elevation dimension. The fundamental antenna area constraint still applies, but the PRF can be chosen with more freedom. In addition to ambiguity suppression, potential applications include nadir return elimination and signal-to-noise ratio improvement....

  19. LARGE OIL SPILL CLASSIFICATION USING SAR IMAGES BASED ON SPATIAL HISTOGRAM

    Directory of Open Access Journals (Sweden)

    I. Schvartzman

    2016-06-01

    Full Text Available Among the different types of marine pollution, oil spill is a major threat to the sea ecosystems. Remote sensing is used in oil spill response. Synthetic Aperture Radar (SAR is an active microwave sensor that operates under all weather conditions and provides information about the surface roughness and covers large areas at a high spatial resolution. SAR is widely used to identify and track pollutants in the sea, which may be due to a secondary effect of a large natural disaster or by a man-made one . The detection of oil spill in SAR imagery relies on the decrease of the backscattering from the sea surface, due to the increased viscosity, resulting in a dark formation that contrasts with the brightness of the surrounding area. Most of the use of SAR images for oil spill detection is done by visual interpretation. Trained interpreters scan the image, and mark areas of low backscatter and where shape is a-symmetrical. It is very difficult to apply this method for a wide area. In contrast to visual interpretation, automatic detection algorithms were suggested and are mainly based on scanning dark formations, extracting features, and applying big data analysis. We propose a new algorithm that applies a nonlinear spatial filter that detects dark formations and is not susceptible to noises, such as internal or speckle. The advantages of this algorithm are both in run time and the results retrieved. The algorithm was tested in genesimulations as well as on COSMO-SkyMed images, detecting the Deep Horizon oil spill in the Gulf of Mexico (occurred on 20/4/2010. The simulation results show that even in a noisy environment, oil spill is detected. Applying the algorithm to the Deep Horizon oil spill, the algorithm classified the oil spill better than focusing on dark formation algorithm. Furthermore, the results were validated by the National Oceanic and Atmospheric Administration (NOAA data.

  20. Large Oil Spill Classification Using SAR Images Based on Spatial Histogram

    Science.gov (United States)

    Schvartzman, I.; Havivi, S.; Maman, S.; Rotman, S. R.; Blumberg, D. G.

    2016-06-01

    Among the different types of marine pollution, oil spill is a major threat to the sea ecosystems. Remote sensing is used in oil spill response. Synthetic Aperture Radar (SAR) is an active microwave sensor that operates under all weather conditions and provides information about the surface roughness and covers large areas at a high spatial resolution. SAR is widely used to identify and track pollutants in the sea, which may be due to a secondary effect of a large natural disaster or by a man-made one . The detection of oil spill in SAR imagery relies on the decrease of the backscattering from the sea surface, due to the increased viscosity, resulting in a dark formation that contrasts with the brightness of the surrounding area. Most of the use of SAR images for oil spill detection is done by visual interpretation. Trained interpreters scan the image, and mark areas of low backscatter and where shape is a-symmetrical. It is very difficult to apply this method for a wide area. In contrast to visual interpretation, automatic detection algorithms were suggested and are mainly based on scanning dark formations, extracting features, and applying big data analysis. We propose a new algorithm that applies a nonlinear spatial filter that detects dark formations and is not susceptible to noises, such as internal or speckle. The advantages of this algorithm are both in run time and the results retrieved. The algorithm was tested in genesimulations as well as on COSMO-SkyMed images, detecting the Deep Horizon oil spill in the Gulf of Mexico (occurred on 20/4/2010). The simulation results show that even in a noisy environment, oil spill is detected. Applying the algorithm to the Deep Horizon oil spill, the algorithm classified the oil spill better than focusing on dark formation algorithm. Furthermore, the results were validated by the National Oceanic and Atmospheric Administration (NOAA) data.

  1. POST-DISASTER DAMAGE ASSESSMENT THROUGH COHERENT CHANGE DETECTION ON SAR IMAGERY

    Directory of Open Access Journals (Sweden)

    L. Guida

    2018-04-01

    Full Text Available Damage assessment is a fundamental step to support emergency response and recovery activities in a post-earthquake scenario. In recent years, UAVs and satellite optical imagery was applied to assess major structural damages before technicians could reach the areas affected by the earthquake. However, bad weather conditions may harm the quality of these optical assessments, thus limiting the practical applicability of these techniques. In this paper, the application of Synthetic Aperture Radar (SAR imagery is investigated and a novel approach to SAR-based damage assessment is presented. Coherent Change Detection (CCD algorithms on multiple interferometrically pre-processed SAR images of the area affected by the seismic event are exploited to automatically detect potential damages to buildings and other physical structures. As a case study, the 2016 Central Italy earthquake involving the cities of Amatrice and Accumoli was selected. The main contribution of the research outlined above is the integration of a complex process, requiring the coordination of a variety of methods and tools, into a unitary framework, which allows end-to-end application of the approach from SAR data pre-processing to result visualization in a Geographic Information System (GIS. A prototype of this pipeline was implemented, and the outcomes of this methodology were validated through an extended comparison with traditional damage assessment maps, created through photo-interpretation of high resolution aerial imagery. The results indicate that the proposed methodology is able to perform damage detection with a good level of accuracy, as most of the detected points of change are concentrated around highly damaged buildings.

  2. Post-Disaster Damage Assessment Through Coherent Change Detection on SAR Imagery

    Science.gov (United States)

    Guida, L.; Boccardo, P.; Donevski, I.; Lo Schiavo, L.; Molinari, M. E.; Monti-Guarnieri, A.; Oxoli, D.; Brovelli, M. A.

    2018-04-01

    Damage assessment is a fundamental step to support emergency response and recovery activities in a post-earthquake scenario. In recent years, UAVs and satellite optical imagery was applied to assess major structural damages before technicians could reach the areas affected by the earthquake. However, bad weather conditions may harm the quality of these optical assessments, thus limiting the practical applicability of these techniques. In this paper, the application of Synthetic Aperture Radar (SAR) imagery is investigated and a novel approach to SAR-based damage assessment is presented. Coherent Change Detection (CCD) algorithms on multiple interferometrically pre-processed SAR images of the area affected by the seismic event are exploited to automatically detect potential damages to buildings and other physical structures. As a case study, the 2016 Central Italy earthquake involving the cities of Amatrice and Accumoli was selected. The main contribution of the research outlined above is the integration of a complex process, requiring the coordination of a variety of methods and tools, into a unitary framework, which allows end-to-end application of the approach from SAR data pre-processing to result visualization in a Geographic Information System (GIS). A prototype of this pipeline was implemented, and the outcomes of this methodology were validated through an extended comparison with traditional damage assessment maps, created through photo-interpretation of high resolution aerial imagery. The results indicate that the proposed methodology is able to perform damage detection with a good level of accuracy, as most of the detected points of change are concentrated around highly damaged buildings.

  3. Software for Generating Troposphere Corrections for InSAR Using GPS and Weather Model Data

    Science.gov (United States)

    Moore, Angelyn W.; Webb, Frank H.; Fishbein, Evan F.; Fielding, Eric J.; Owen, Susan E.; Granger, Stephanie L.; Bjoerndahl, Fredrik; Loefgren, Johan; Fang, Peng; Means, James D.; hide

    2013-01-01

    Atmospheric errors due to the troposphere are a limiting error source for spaceborne interferometric synthetic aperture radar (InSAR) imaging. This software generates tropospheric delay maps that can be used to correct atmospheric artifacts in InSAR data. The software automatically acquires all needed GPS (Global Positioning System), weather, and Digital Elevation Map data, and generates a tropospheric correction map using a novel algorithm for combining GPS and weather information while accounting for terrain. Existing JPL software was prototypical in nature, required a MATLAB license, required additional steps to acquire and ingest needed GPS and weather data, and did not account for topography in interpolation. Previous software did not achieve a level of automation suitable for integration in a Web portal. This software overcomes these issues. GPS estimates of tropospheric delay are a source of corrections that can be used to form correction maps to be applied to InSAR data, but the spacing of GPS stations is insufficient to remove short-wavelength tropospheric artifacts. This software combines interpolated GPS delay with weather model precipitable water vapor (PWV) and a digital elevation model to account for terrain, increasing the spatial resolution of the tropospheric correction maps and thus removing short wavelength tropospheric artifacts to a greater extent. It will be integrated into a Web portal request system, allowing use in a future L-band SAR Earth radar mission data system. This will be a significant contribution to its technology readiness, building on existing investments in in situ space geodetic networks, and improving timeliness, quality, and science value of the collected data

  4. Interseismic Deformation along the Red River Fault from InSAR Measurements

    Science.gov (United States)

    Chen, J.; Li, Z.; Clarke, P. J.

    2017-12-01

    The Red River Fault (RRF) zone is a profound geological discontinuity separating South China from Indochina. Right lateral movements along this >900 km fault are considered to accommodate the extrusion of SE China. Crustal deformation monitoring at high resolution is the key to understand the present-day mode of deformation in this zone and its interaction with the adjacent regions. This is the first study to measure the interseismic deformation of the entire fault with ALOS-1/2 and Sentinel-1 observations. Nine ascending tracks of ALOS-1 data between 2007 and 2011 are collected from the Alaska Satellite Facility (ASF), four descending tracks of Sentinel-1 data are acquired every 24 days since October 2014, and ALOS-2 data are being systematically acquired since 2014. The long wavelength (L-band) of ALOS-1/2 and short temporal baseline of Sentinel-1 ensure good coherence to overcome the limitations of heavy vegetation and variable climate in the region. Stacks of interferograms are generated by our automatic processing chain based on the InSAR Scientific Computing Environment (ISCE) software, ionospheric errors are estimated and corrected using the split-spectrum method (Fattahi et al., IEEE Trans. Geosci. Remote Sens., 2017) and the tropospheric delays are calibrated using the Generic Atmospheric Correction Online Service for InSAR (GACOS: http://ceg-research.ncl.ac.uk/v2/gacos) with high-resolution ECMWF products (Yu et al., J. Geophys. Res., 2017). Time series analysis is performed to determine the interseismic deformation rate of the RRF using the in-house InSAR time series with atmospheric estimation model (InSAR TS + AEM) package based on the Small Baseline Subset (SBAS) algorithm. Our results reveal the decrease of slip rate from north to south. We map the interseismic strain rate field to characterize the deformation patterns and seismic hazard throughout the RRF zone.

  5. Ship Analysis and Detection in High-resolution Pol-SAR Imagery Based on Peak Zone

    Directory of Open Access Journals (Sweden)

    Xu Cheng-bin

    2015-06-01

    Full Text Available To deal with the problem of false alarm in the ship detection, a method base on proportion of spiral scattering in the peak zone is proposed. By comparing the proportion of spiral scattering in the peak zone, which is available from Krogager decomposition, the ships and interfering targets are identified and analyzed. The effectiveness of this method is justified with C-band full-polarization data from RADARSAT-2. The result show that this method can discriminate ships from interfering targets such as island, water-break, nautical platforms and bridges, thus reducing the false alarm rate of ship targets detection in SAR images.

  6. Neural Bases of Automaticity

    Science.gov (United States)

    Servant, Mathieu; Cassey, Peter; Woodman, Geoffrey F.; Logan, Gordon D.

    2018-01-01

    Automaticity allows us to perform tasks in a fast, efficient, and effortless manner after sufficient practice. Theories of automaticity propose that across practice processing transitions from being controlled by working memory to being controlled by long-term memory retrieval. Recent event-related potential (ERP) studies have sought to test this…

  7. Automatic control systems engineering

    International Nuclear Information System (INIS)

    Shin, Yun Gi

    2004-01-01

    This book gives descriptions of automatic control for electrical electronics, which indicates history of automatic control, Laplace transform, block diagram and signal flow diagram, electrometer, linearization of system, space of situation, state space analysis of electric system, sensor, hydro controlling system, stability, time response of linear dynamic system, conception of root locus, procedure to draw root locus, frequency response, and design of control system.

  8. Automatic Camera Control

    DEFF Research Database (Denmark)

    Burelli, Paolo; Preuss, Mike

    2014-01-01

    Automatically generating computer animations is a challenging and complex problem with applications in games and film production. In this paper, we investigate howto translate a shot list for a virtual scene into a series of virtual camera configurations — i.e automatically controlling the virtual...

  9. Automatic differentiation of functions

    International Nuclear Information System (INIS)

    Douglas, S.R.

    1990-06-01

    Automatic differentiation is a method of computing derivatives of functions to any order in any number of variables. The functions must be expressible as combinations of elementary functions. When evaluated at specific numerical points, the derivatives have no truncation error and are automatically found. The method is illustrated by simple examples. Source code in FORTRAN is provided

  10. Characterizing and estimating noise in InSAR and InSAR time series with MODIS

    Science.gov (United States)

    Barnhart, William D.; Lohman, Rowena B.

    2013-01-01

    InSAR time series analysis is increasingly used to image subcentimeter displacement rates of the ground surface. The precision of InSAR observations is often affected by several noise sources, including spatially correlated noise from the turbulent atmosphere. Under ideal scenarios, InSAR time series techniques can substantially mitigate these effects; however, in practice the temporal distribution of InSAR acquisitions over much of the world exhibit seasonal biases, long temporal gaps, and insufficient acquisitions to confidently obtain the precisions desired for tectonic research. Here, we introduce a technique for constraining the magnitude of errors expected from atmospheric phase delays on the ground displacement rates inferred from an InSAR time series using independent observations of precipitable water vapor from MODIS. We implement a Monte Carlo error estimation technique based on multiple (100+) MODIS-based time series that sample date ranges close to the acquisitions times of the available SAR imagery. This stochastic approach allows evaluation of the significance of signals present in the final time series product, in particular their correlation with topography and seasonality. We find that topographically correlated noise in individual interferograms is not spatially stationary, even over short-spatial scales (<10 km). Overall, MODIS-inferred displacements and velocities exhibit errors of similar magnitude to the variability within an InSAR time series. We examine the MODIS-based confidence bounds in regions with a range of inferred displacement rates, and find we are capable of resolving velocities as low as 1.5 mm/yr with uncertainties increasing to ∼6 mm/yr in regions with higher topographic relief.

  11. Annual review in automatic programming

    CERN Document Server

    Goodman, Richard

    2014-01-01

    Annual Review in Automatic Programming, Volume 2 is a collection of papers that discusses the controversy about the suitability of COBOL as a common business oriented language, and the development of different common languages for scientific computation. A couple of papers describes the use of the Genie system in numerical calculation and analyzes Mercury autocode in terms of a phrase structure language, such as in the source language, target language, the order structure of ATLAS, and the meta-syntactical language of the assembly program. Other papers explain interference or an ""intermediate

  12. Spaceborne Polarimetric SAR Interferometry: Performance Analysis and Mission Concepts

    Directory of Open Access Journals (Sweden)

    Shane R. Cloude

    2005-12-01

    Full Text Available We investigate multichannel imaging radar systems employing coherent combinations of polarimetry and interferometry (Pol-InSAR. Such systems are well suited for the extraction of bio- and geophysical parameters by evaluating the combined scattering from surfaces and volumes. This combination leads to several important differences between the design of Pol-InSAR sensors and conventional single polarisation SAR interferometers. We first highlight these differences and then investigate the Pol-InSAR performance of two proposed spaceborne SAR systems (ALOS/PalSAR and TerraSAR-L operating in repeat-pass mode. For this, we introduce the novel concept of a phase tube which enables (1 a quantitative assessment of the Pol-InSAR performance, (2 a comparison between different sensor configurations, and (3 an optimization of the instrument settings for different Pol-InSAR applications. The phase tube may hence serve as an interface between system engineers and application-oriented scientists. The performance analysis reveals major limitations for even moderate levels of temporal decorrelation. Such deteriorations may be avoided in single-pass sensor configurations and we demonstrate the potential benefits from the use of future bi- and multistatic SAR interferometers.

  13. Multi-linear sparse reconstruction for SAR imaging based on higher-order SVD

    Science.gov (United States)

    Gao, Yu-Fei; Gui, Guan; Cong, Xun-Chao; Yang, Yue; Zou, Yan-Bin; Wan, Qun

    2017-12-01

    This paper focuses on the spotlight synthetic aperture radar (SAR) imaging for point scattering targets based on tensor modeling. In a real-world scenario, scatterers usually distribute in the block sparse pattern. Such a distribution feature has been scarcely utilized by the previous studies of SAR imaging. Our work takes advantage of this structure property of the target scene, constructing a multi-linear sparse reconstruction algorithm for SAR imaging. The multi-linear block sparsity is introduced into higher-order singular value decomposition (SVD) with a dictionary constructing procedure by this research. The simulation experiments for ideal point targets show the robustness of the proposed algorithm to the noise and sidelobe disturbance which always influence the imaging quality of the conventional methods. The computational resources requirement is further investigated in this paper. As a consequence of the algorithm complexity analysis, the present method possesses the superiority on resource consumption compared with the classic matching pursuit method. The imaging implementations for practical measured data also demonstrate the effectiveness of the algorithm developed in this paper.

  14. Aircraft Segmentation in SAR Images Based on Improved Active Shape Model

    Science.gov (United States)

    Zhang, X.; Xiong, B.; Kuang, G.

    2018-04-01

    In SAR image interpretation, aircrafts are the important targets arousing much attention. However, it is far from easy to segment an aircraft from the background completely and precisely in SAR images. Because of the complex structure, different kinds of electromagnetic scattering take place on the aircraft surfaces. As a result, aircraft targets usually appear to be inhomogeneous and disconnected. It is a good idea to extract an aircraft target by the active shape model (ASM), since combination of the geometric information controls variations of the shape during the contour evolution. However, linear dimensionality reduction, used in classic ACM, makes the model rigid. It brings much trouble to segment different types of aircrafts. Aiming at this problem, an improved ACM based on ISOMAP is proposed in this paper. ISOMAP algorithm is used to extract the shape information of the training set and make the model flexible enough to deal with different aircrafts. The experiments based on real SAR data shows that the proposed method achieves obvious improvement in accuracy.

  15. Federated query services provided by the Seamless SAR Archive project

    Science.gov (United States)

    Baker, S.; Bryson, G.; Buechler, B.; Meertens, C. M.; Crosby, C. J.; Fielding, E. J.; Nicoll, J.; Youn, C.; Baru, C.

    2013-12-01

    The NASA Advancing Collaborative Connections for Earth System Science (ACCESS) seamless synthetic aperture radar (SAR) archive (SSARA) project is a 2-year collaboration between UNAVCO, the Alaska Satellite Facility (ASF), the Jet Propulsion Laboratory (JPL), and OpenTopography at the San Diego Supercomputer Center (SDSC) to design and implement a seamless distributed access system for SAR data and derived data products (i.e. interferograms). A major milestone for the first year of the SSARA project was a unified application programming interface (API) for SAR data search and results at ASF and UNAVCO (WInSAR and EarthScope data archives) through the use of simple web services. A federated query service was developed using the unified APIs, providing users a single search interface for both archives (http://www.unavco.org/ws/brokered/ssara/sar/search). A command line client that utilizes this new service is provided as an open source utility for the community on GitHub (https://github.com/bakerunavco/SSARA). Further API development and enhancements added more InSAR specific keywords and quality control parameters (Doppler centroid, faraday rotation, InSAR stack size, and perpendicular baselines). To facilitate InSAR processing, the federated query service incorporated URLs for DEM (from OpenTopography) and tropospheric corrections (from the JPL OSCAR service) in addition to the URLs for SAR data. This federated query service will provide relevant QC metadata for selecting pairs of SAR data for InSAR processing and all the URLs necessary for interferogram generation. Interest from the international community has prompted an effort to incorporate other SAR data archives (the ESA Virtual Archive 4 and the DLR TerraSAR-X_SSC Geohazard Supersites and Natural Laboratories collections) into the federated query service which provide data for researchers outside the US and North America.

  16. SAR Product Improvements and Enhancements - SARprises

    Science.gov (United States)

    2013-09-30

    paper on current fields at Orkney, Scotland, was accepted for publication in IEEE - TGARS and is currently in press (available on IEEE Xplore as Early...Sea surface velocity vector retrieval using dual-beam interferometry: First demonstration, IEEE TGARS, 43, 2494- 2502, 2005. [2] Chapron, B., F...Bight by airborne along-track interferometric SAR, Proc. IGARSS 2002, 1822-1824, IEEE , 2002. [4] Bjerklie, D.M., S.L. Dingman, C.J. Vorosmarty, C.H

  17. Atmospheric Phase Delay in Sentinel SAR Interferometry

    Science.gov (United States)

    Krishnakumar, V.; Monserrat, O.; Crosetto, M.; Crippa, B.

    2018-04-01

    The repeat-pass Synthetic Aperture Radio Detection and Ranging (RADAR) Interferometry (InSAR) has been a widely used geodetic technique for observing the Earth's surface, especially for mapping the Earth's topography and deformations. However, InSAR measurements are prone to atmospheric errors. RADAR waves traverse the Earth's atmosphere twice and experience a delay due to atmospheric refraction. The two major layers of the atmosphere (troposphere and ionosphere) are mainly responsible for this delay in the propagating RADAR wave. Previous studies have shown that water vapour and clouds present in the troposphere and the Total Electron Content (TEC) of the ionosphere are responsible for the additional path delay in the RADAR wave. The tropospheric refractivity is mainly dependent on pressure, temperature and partial pressure of water vapour. The tropospheric refractivity leads to an increase in the observed range. These induced propagation delays affect the quality of phase measurement and introduce errors in the topography and deformation fields. The effect of this delay was studied on a differential interferogram (DInSAR). To calculate the amount of tropospheric delay occurred, the meteorological data collected from the Spanish Agencia Estatal de Meteorología (AEMET) and MODIS were used. The interferograms generated from Sentinel-1 carrying C-band Synthetic Aperture RADAR Single Look Complex (SLC) images acquired on the study area are used. The study area consists of different types of scatterers exhibiting different coherence. The existing Saastamoinen model was used to perform a quantitative evaluation of the phase changes caused by pressure, temperature and humidity of the troposphere during the study. Unless the phase values due to atmospheric disturbances are not corrected, it is difficult to obtain accurate measurements. Thus, the atmospheric error correction is essential for all practical applications of DInSAR to avoid inaccurate height and deformation

  18. ATMOSPHERIC PHASE DELAY IN SENTINEL SAR INTERFEROMETRY

    Directory of Open Access Journals (Sweden)

    V. Krishnakumar

    2018-04-01

    Full Text Available The repeat-pass Synthetic Aperture Radio Detection and Ranging (RADAR Interferometry (InSAR has been a widely used geodetic technique for observing the Earth’s surface, especially for mapping the Earth’s topography and deformations. However, InSAR measurements are prone to atmospheric errors. RADAR waves traverse the Earth’s atmosphere twice and experience a delay due to atmospheric refraction. The two major layers of the atmosphere (troposphere and ionosphere are mainly responsible for this delay in the propagating RADAR wave. Previous studies have shown that water vapour and clouds present in the troposphere and the Total Electron Content (TEC of the ionosphere are responsible for the additional path delay in the RADAR wave. The tropospheric refractivity is mainly dependent on pressure, temperature and partial pressure of water vapour. The tropospheric refractivity leads to an increase in the observed range. These induced propagation delays affect the quality of phase measurement and introduce errors in the topography and deformation fields. The effect of this delay was studied on a differential interferogram (DInSAR. To calculate the amount of tropospheric delay occurred, the meteorological data collected from the Spanish Agencia Estatal de Meteorología (AEMET and MODIS were used. The interferograms generated from Sentinel-1 carrying C-band Synthetic Aperture RADAR Single Look Complex (SLC images acquired on the study area are used. The study area consists of different types of scatterers exhibiting different coherence. The existing Saastamoinen model was used to perform a quantitative evaluation of the phase changes caused by pressure, temperature and humidity of the troposphere during the study. Unless the phase values due to atmospheric disturbances are not corrected, it is difficult to obtain accurate measurements. Thus, the atmospheric error correction is essential for all practical applications of DInSAR to avoid inaccurate

  19. Multiplier-free filters for wideband SAR

    DEFF Research Database (Denmark)

    Dall, Jørgen; Christensen, Erik Lintz

    2001-01-01

    This paper derives a set of parameters to be optimized when designing filters for digital demodulation and range prefiltering in SAR systems. Aiming at an implementation in field programmable gate arrays (FPGAs), an approach for the design of multiplier-free filters is outlined. Design results...... are presented in terms of filter complexity and performance. One filter has been coded in VHDL and preliminary results indicate that the filter can meet a 2 GHz input sample rate....

  20. Isolation and characterization of a bat SARS-like coronavirus that uses the ACE2 receptor.

    Science.gov (United States)

    Ge, Xing-Yi; Li, Jia-Lu; Yang, Xing-Lou; Chmura, Aleksei A; Zhu, Guangjian; Epstein, Jonathan H; Mazet, Jonna K; Hu, Ben; Zhang, Wei; Peng, Cheng; Zhang, Yu-Ji; Luo, Chu-Ming; Tan, Bing; Wang, Ning; Zhu, Yan; Crameri, Gary; Zhang, Shu-Yi; Wang, Lin-Fa; Daszak, Peter; Shi, Zheng-Li

    2013-11-28

    The 2002-3 pandemic caused by severe acute respiratory syndrome coronavirus (SARS-CoV) was one of the most significant public health events in recent history. An ongoing outbreak of Middle East respiratory syndrome coronavirus suggests that this group of viruses remains a key threat and that their distribution is wider than previously recognized. Although bats have been suggested to be the natural reservoirs of both viruses, attempts to isolate the progenitor virus of SARS-CoV from bats have been unsuccessful. Diverse SARS-like coronaviruses (SL-CoVs) have now been reported from bats in China, Europe and Africa, but none is considered a direct progenitor of SARS-CoV because of their phylogenetic disparity from this virus and the inability of their spike proteins to use the SARS-CoV cellular receptor molecule, the human angiotensin converting enzyme II (ACE2). Here we report whole-genome sequences of two novel bat coronaviruses from Chinese horseshoe bats (family: Rhinolophidae) in Yunnan, China: RsSHC014 and Rs3367. These viruses are far more closely related to SARS-CoV than any previously identified bat coronaviruses, particularly in the receptor binding domain of the spike protein. Most importantly, we report the first recorded isolation of a live SL-CoV (bat SL-CoV-WIV1) from bat faecal samples in Vero E6 cells, which has typical coronavirus morphology, 99.9% sequence identity to Rs3367 and uses ACE2 from humans, civets and Chinese horseshoe bats for cell entry. Preliminary in vitro testing indicates that WIV1 also has a broad species tropism. Our results provide the strongest evidence to date that Chinese horseshoe bats are natural reservoirs of SARS-CoV, and that intermediate hosts may not be necessary for direct human infection by some bat SL-CoVs. They also highlight the importance of pathogen-discovery programs targeting high-risk wildlife groups in emerging disease hotspots as a strategy for pandemic preparedness.

  1. Feature-Based Nonlocal Polarimetric SAR Filtering

    Directory of Open Access Journals (Sweden)

    Xiaoli Xing

    2017-10-01

    Full Text Available Polarimetric synthetic aperture radar (PolSAR images are inherently contaminated by multiplicative speckle noise, which complicates the image interpretation and image analyses. To reduce the speckle effect, several adaptive speckle filters have been developed based on the weighted average of the similarity measures commonly depending on the model or probability distribution, which are often affected by the distribution parameters and modeling texture components. In this paper, a novel filtering method introduces the coefficient of variance ( CV and Pauli basis (PB to measure the similarity, and the two features are combined with the framework of the nonlocal mean filtering. The CV is used to describe the complexity of various scenes and distinguish the scene heterogeneity; moreover, the Pauli basis is able to express the polarimetric information in PolSAR image processing. This proposed filtering combines the CV and Pauli basis to improve the estimation accuracy of the similarity weights. Then, the similarity of the features is deduced according to the test statistic. Subsequently, the filtering is proceeded by using the nonlocal weighted estimation. The performance of the proposed filter is tested with the simulated images and real PolSAR images, which are acquired by AIRSAR system and ESAR system. The qualitative and quantitative experiments indicate the validity of the proposed method by comparing with the widely-used despeckling methods.

  2. Induction of Th1 type response by DNA vaccinations with N, M, and E genes against SARS-CoV in mice

    International Nuclear Information System (INIS)

    Jin Huali; Xiao Chong; Chen Ze; Kang Youmin; Ma Yijie; Zhu Kaichun; Xie Qifa; Tu Yixian; Yu Yang; Wang Bin

    2005-01-01

    Vaccination against the SARS-CoV infection is an attractive means to control the spread of viruses in public. In this study, we employed a DNA vaccine technology with the levamisole, our newly discovered chemical adjuvant, to generate Th1 type of response. To avoid the enhancement antibody issue, genes encoding the nucleocapsid, membrane, and envelope protein of SARS-CoV were cloned and their expressions in mammalian cells were determined. After the intramuscular introduction into animals, we observed that the constructs of the E, M, and N genes could induce high levels of specific antibodies, T cell proliferations, IFN-γ, DTH responses, and in vivo cytotoxic T cells activities specifically against SARS-CoV antigens. The highest immune responses were generated by the construct encoding the nucleocapsid protein. The results suggest that the N, M, and E genes could be used as the targets to prevent SARS-CoV infection in the DNA vaccine development

  3. Polarimetric SAR image classification based on discriminative dictionary learning model

    Science.gov (United States)

    Sang, Cheng Wei; Sun, Hong

    2018-03-01

    Polarimetric SAR (PolSAR) image classification is one of the important applications of PolSAR remote sensing. It is a difficult high-dimension nonlinear mapping problem, the sparse representations based on learning overcomplete dictionary have shown great potential to solve such problem. The overcomplete dictionary plays an important role in PolSAR image classification, however for PolSAR image complex scenes, features shared by different classes will weaken the discrimination of learned dictionary, so as to degrade classification performance. In this paper, we propose a novel overcomplete dictionary learning model to enhance the discrimination of dictionary. The learned overcomplete dictionary by the proposed model is more discriminative and very suitable for PolSAR classification.

  4. Low-SAR metamaterial-inspired printed monopole antenna

    Science.gov (United States)

    Hossain, M. I.; Faruque, M. R. I.; Islam, M. T.; Ali, M. T.

    2017-01-01

    In this paper, a low-SAR metamaterial-embedded planar monopole antenna is introduced for a wireless communication system. A printed monopole antenna is designed for modern mobile, which operates in GSM, UMTS, LTE, WLAN, and Bluetooth frequency bands. A metamaterial structure is designed to use in the mobile handset with a multi-band printed monopole antenna. The finite integration technique of the CST microwave studio is used in this study. The measurement of antenna performances is taken in an anechoic chamber, and the SAR values are measured using COMOSAR system. The results indicate that metamaterial structure leads to reduce SAR without affecting antenna performance significantly. According to the measured results, the metamaterial attachment leads to reduce 87.7% peak SAR, 68.2% 1-g SAR, and 46.78% 10-g SAR compared to antenna without metamaterial.

  5. Monitoring Building Deformation with InSAR: Experiments and Validation

    Science.gov (United States)

    Yang, Kui; Yan, Li; Huang, Guoman; Chen, Chu; Wu, Zhengpeng

    2016-01-01

    Synthetic Aperture Radar Interferometry (InSAR) techniques are increasingly applied for monitoring land subsidence. The advantages of InSAR include high accuracy and the ability to cover large areas; nevertheless, research validating the use of InSAR on building deformation is limited. In this paper, we test the monitoring capability of the InSAR in experiments using two landmark buildings; the Bohai Building and the China Theater, located in Tianjin, China. They were selected as real examples to compare InSAR and leveling approaches for building deformation. Ten TerraSAR-X images spanning half a year were used in Permanent Scatterer InSAR processing. These extracted InSAR results were processed considering the diversity in both direction and spatial distribution, and were compared with true leveling values in both Ordinary Least Squares (OLS) regression and measurement of error analyses. The detailed experimental results for the Bohai Building and the China Theater showed a high correlation between InSAR results and the leveling values. At the same time, the two Root Mean Square Error (RMSE) indexes had values of approximately 1 mm. These analyses show that a millimeter level of accuracy can be achieved by means of InSAR technique when measuring building deformation. We discuss the differences in accuracy between OLS regression and measurement of error analyses, and compare the accuracy index of leveling in order to propose InSAR accuracy levels appropriate for monitoring buildings deformation. After assessing the advantages and limitations of InSAR techniques in monitoring buildings, further applications are evaluated. PMID:27999403

  6. Monitoring Building Deformation with InSAR: Experiments and Validation

    Directory of Open Access Journals (Sweden)

    Kui Yang

    2016-12-01

    Full Text Available Synthetic Aperture Radar Interferometry (InSAR techniques are increasingly applied for monitoring land subsidence. The advantages of InSAR include high accuracy and the ability to cover large areas; nevertheless, research validating the use of InSAR on building deformation is limited. In this paper, we test the monitoring capability of the InSAR in experiments using two landmark buildings; the Bohai Building and the China Theater, located in Tianjin, China. They were selected as real examples to compare InSAR and leveling approaches for building deformation. Ten TerraSAR-X images spanning half a year were used in Permanent Scatterer InSAR processing. These extracted InSAR results were processed considering the diversity in both direction and spatial distribution, and were compared with true leveling values in both Ordinary Least Squares (OLS regression and measurement of error analyses. The detailed experimental results for the Bohai Building and the China Theater showed a high correlation between InSAR results and the leveling values. At the same time, the two Root Mean Square Error (RMSE indexes had values of approximately 1 mm. These analyses show that a millimeter level of accuracy can be achieved by means of InSAR technique when measuring building deformation. We discuss the differences in accuracy between OLS regression and measurement of error analyses, and compare the accuracy index of leveling in order to propose InSAR accuracy levels appropriate for monitoring buildings deformation. After assessing the advantages and limitations of InSAR techniques in monitoring buildings, further applications are evaluated.

  7. SAR11 bacteria linked to ocean anoxia and nitrogen loss

    DEFF Research Database (Denmark)

    Tsementzi, Despina; Wu, Jieying; Deutsch, Samuel

    2016-01-01

    Bacteria of the SAR11 clade constitute up to one half of all microbial cells in the oxygen-rich surface ocean. SAR11 bacteria are also abundant in oxygen minimum zones (OMZs), where oxygen falls below detection and anaerobic microbes have vital roles in converting bioavailable nitrogen to N2 gas...... activity. These results link SAR11 to pathways of ocean nitrogen loss, redefining the ecological niche of Earth’s most abundant organismal group....

  8. Prototype Theory Based Feature Representation for PolSAR Images

    OpenAIRE

    Huang Xiaojing; Yang Xiangli; Huang Pingping; Yang Wen

    2016-01-01

    This study presents a new feature representation approach for Polarimetric Synthetic Aperture Radar (PolSAR) image based on prototype theory. First, multiple prototype sets are generated using prototype theory. Then, regularized logistic regression is used to predict similarities between a test sample and each prototype set. Finally, the PolSAR image feature representation is obtained by ensemble projection. Experimental results of an unsupervised classification of PolSAR images show that our...

  9. Improved GO/PO method and its application to wideband SAR image of conducting objects over rough surface

    Science.gov (United States)

    Jiang, Wang-Qiang; Zhang, Min; Nie, Ding; Jiao, Yong-Chang

    2018-04-01

    To simulate the multiple scattering effect of target in synthetic aperture radar (SAR) image, the hybrid method GO/PO method, which combines the geometrical optics (GO) and physical optics (PO), is employed to simulate the scattering field of target. For ray tracing is time-consuming, the Open Graphics Library (OpenGL) is usually employed to accelerate the process of ray tracing. Furthermore, the GO/PO method is improved for the simulation in low pixel situation. For the improved GO/PO method, the pixels are arranged corresponding to the rectangular wave beams one by one, and the GO/PO result is the sum of the contribution values of all the rectangular wave beams. To get high-resolution SAR image, the wideband echo signal is simulated which includes information of many electromagnetic (EM) waves with different frequencies. Finally, the improved GO/PO method is used to simulate the SAR image of targets above rough surface. And the effects of reflected rays and the size of pixel matrix on the SAR image are also discussed.

  10. Thai Automatic Speech Recognition

    National Research Council Canada - National Science Library

    Suebvisai, Sinaporn; Charoenpornsawat, Paisarn; Black, Alan; Woszczyna, Monika; Schultz, Tanja

    2005-01-01

    .... We focus on the discussion of the rapid deployment of ASR for Thai under limited time and data resources, including rapid data collection issues, acoustic model bootstrap, and automatic generation of pronunciations...

  11. Automatic Payroll Deposit System.

    Science.gov (United States)

    Davidson, D. B.

    1979-01-01

    The Automatic Payroll Deposit System in Yakima, Washington's Public School District No. 7, directly transmits each employee's salary amount for each pay period to a bank or other financial institution. (Author/MLF)

  12. Automatic Test Systems Aquisition

    National Research Council Canada - National Science Library

    1994-01-01

    We are providing this final memorandum report for your information and use. This report discusses the efforts to achieve commonality in standards among the Military Departments as part of the DoD policy for automatic test systems (ATS...

  13. Evaluation of the Wishart test statistics for polarimetric SAR data

    DEFF Research Database (Denmark)

    Skriver, Henning; Nielsen, Allan Aasbjerg; Conradsen, Knut

    2003-01-01

    A test statistic for equality of two covariance matrices following the complex Wishart distribution has previously been used in new algorithms for change detection, edge detection and segmentation in polarimetric SAR images. Previously, the results for change detection and edge detection have been...... quantitatively evaluated. This paper deals with the evaluation of segmentation. A segmentation performance measure originally developed for single-channel SAR images has been extended to polarimetric SAR images, and used to evaluate segmentation for a merge-using-moment algorithm for polarimetric SAR data....

  14. SAR Subsets for Selected Field Sites, 2007-2010

    Data.gov (United States)

    National Aeronautics and Space Administration — ABSTRACT: This data set provides Synthetic Aperture Radar (SAR) images for 42 selected sites from various terrestrial ecology and meteorological monitoring networks...

  15. SAR Subsets for Selected Field Sites, 2007-2010

    Data.gov (United States)

    National Aeronautics and Space Administration — This data set provides Synthetic Aperture Radar (SAR) images for 42 selected sites from various terrestrial ecology and meteorological monitoring networks including...

  16. Applications of SAR Interferometry in Earth and Environmental Science Research

    Science.gov (United States)

    Zhou, Xiaobing; Chang, Ni-Bin; Li, Shusun

    2009-01-01

    This paper provides a review of the progress in regard to the InSAR remote sensing technique and its applications in earth and environmental sciences, especially in the past decade. Basic principles, factors, limits, InSAR sensors, available software packages for the generation of InSAR interferograms were summarized to support future applications. Emphasis was placed on the applications of InSAR in seismology, volcanology, land subsidence/uplift, landslide, glaciology, hydrology, and forestry sciences. It ends with a discussion of future research directions. PMID:22573992

  17. Applications of SAR Interferometry in Earth and Environmental Science Research

    Directory of Open Access Journals (Sweden)

    Xiaobing Zhou

    2009-03-01

    Full Text Available This paper provides a review of the progress in regard to the InSAR remote sensing technique and its applications in earth and environmental sciences, especially in the past decade. Basic principles, factors, limits, InSAR sensors, available software packages for the generation of InSAR interferograms were summarized to support future applications. Emphasis was placed on the applications of InSAR in seismology, volcanology, land subsidence/uplift, landslide, glaciology, hydrology, and forestry sciences. It ends with a discussion of future research directions.

  18. Applications of SAR Interferometry in Earth and Environmental Science Research.

    Science.gov (United States)

    Zhou, Xiaobing; Chang, Ni-Bin; Li, Shusun

    2009-01-01

    This paper provides a review of the progress in regard to the InSAR remote sensing technique and its applications in earth and environmental sciences, especially in the past decade. Basic principles, factors, limits, InSAR sensors, available software packages for the generation of InSAR interferograms were summarized to support future applications. Emphasis was placed on the applications of InSAR in seismology, volcanology, land subsidence/uplift, landslide, glaciology, hydrology, and forestry sciences. It ends with a discussion of future research directions.

  19. Genome organization of the SARS-CoV

    DEFF Research Database (Denmark)

    Xu, Jing; Hu, Jianfei; Wang, Jing

    2003-01-01

    Annotation of the genome sequence of the SARS-CoV (severe acute respiratory syndrome-associated coronavirus) is indispensable to understand its evolution and pathogenesis. We have performed a full annotation of the SARS-CoV genome sequences by using annotation programs publicly available or devel......Annotation of the genome sequence of the SARS-CoV (severe acute respiratory syndrome-associated coronavirus) is indispensable to understand its evolution and pathogenesis. We have performed a full annotation of the SARS-CoV genome sequences by using annotation programs publicly available...

  20. Method for the irradiation of single targets

    International Nuclear Information System (INIS)

    Krimmel, E.; Dullnig, H.

    1977-01-01

    The invention pertains to a system for the irradiation of single targets with particle beams. The targets all have frames around them. The system consists of an automatic advance leading into a high-vacuum chamber, and a positioning element which guides one target after the other into the irradiation position, at right angles to the automatic advance, and back into the automatic advance after irradiation. (GSCH) [de

  1. Brand and automaticity

    OpenAIRE

    Liu, J.

    2008-01-01

    A presumption of most consumer research is that consumers endeavor to maximize the utility of their choices and are in complete control of their purchasing and consumption behavior. However, everyday life experience suggests that many of our choices are not all that reasoned or conscious. Indeed, automaticity, one facet of behavior, is indispensable to complete the portrait of consumers. Despite its importance, little attention is paid to how the automatic side of behavior can be captured and...

  2. Position automatic determination technology

    International Nuclear Information System (INIS)

    1985-10-01

    This book tells of method of position determination and characteristic, control method of position determination and point of design, point of sensor choice for position detector, position determination of digital control system, application of clutch break in high frequency position determination, automation technique of position determination, position determination by electromagnetic clutch and break, air cylinder, cam and solenoid, stop position control of automatic guide vehicle, stacker crane and automatic transfer control.

  3. Automatic intelligent cruise control

    OpenAIRE

    Stanton, NA; Young, MS

    2006-01-01

    This paper reports a study on the evaluation of automatic intelligent cruise control (AICC) from a psychological perspective. It was anticipated that AICC would have an effect upon the psychology of driving—namely, make the driver feel like they have less control, reduce the level of trust in the vehicle, make drivers less situationally aware, but might reduce the workload and make driving might less stressful. Drivers were asked to drive in a driving simulator under manual and automatic inte...

  4. Comparison Of Semi-Automatic And Automatic Slick Detection Algorithms For Jiyeh Power Station Oil Spill, Lebanon

    Science.gov (United States)

    Osmanoglu, B.; Ozkan, C.; Sunar, F.

    2013-10-01

    After air strikes on July 14 and 15, 2006 the Jiyeh Power Station started leaking oil into the eastern Mediterranean Sea. The power station is located about 30 km south of Beirut and the slick covered about 170 km of coastline threatening the neighboring countries Turkey and Cyprus. Due to the ongoing conflict between Israel and Lebanon, cleaning efforts could not start immediately resulting in 12 000 to 15 000 tons of fuel oil leaking into the sea. In this paper we compare results from automatic and semi-automatic slick detection algorithms. The automatic detection method combines the probabilities calculated for each pixel from each image to obtain a joint probability, minimizing the adverse effects of atmosphere on oil spill detection. The method can readily utilize X-, C- and L-band data where available. Furthermore wind and wave speed observations can be used for a more accurate analysis. For this study, we utilize Envisat ASAR ScanSAR data. A probability map is generated based on the radar backscatter, effect of wind and dampening value. The semi-automatic algorithm is based on supervised classification. As a classifier, Artificial Neural Network Multilayer Perceptron (ANN MLP) classifier is used since it is more flexible and efficient than conventional maximum likelihood classifier for multisource and multi-temporal data. The learning algorithm for ANN MLP is chosen as the Levenberg-Marquardt (LM). Training and test data for supervised classification are composed from the textural information created from SAR images. This approach is semiautomatic because tuning the parameters of classifier and composing training data need a human interaction. We point out the similarities and differences between the two methods and their results as well as underlining their advantages and disadvantages. Due to the lack of ground truth data, we compare obtained results to each other, as well as other published oil slick area assessments.

  5. Power Transmission Tower Series Extraction in PolSAR Image Based on Time-Frequency Analysis and A-Contrario Theory

    Directory of Open Access Journals (Sweden)

    Dongqing Peng

    2016-11-01

    Full Text Available Based on Time-Frequency (TF analysis and a-contrario theory, this paper presents a new approach for extraction of linear arranged power transmission tower series in Polarimetric Synthetic Aperture Radar (PolSAR images. Firstly, the PolSAR multidimensional information is analyzed using a linear TF decomposition approach. The stationarity of each pixel is assessed by testing the maximum likelihood ratio statistics of the coherency matrix. Then, based on the maximum likelihood log-ratio image, a Cell-Averaging Constant False Alarm Rate (CA-CFAR detector with Weibull clutter background and a post-processing operator is used to detect point-like targets in the image. Finally, a searching approach based on a-contrario theory is applied to extract the linear arranged targets from detected point-like targets. The experimental results on three sets of PolSAR data verify the effectiveness of this approach.

  6. The use of multifrequency and polarimetric SIR-C/X-SAR data in geologic studies of Bir Safsaf, Egypt

    Science.gov (United States)

    Schaber, G.G.; McCauley, J.F.; Breed, C.S.

    1997-01-01

    Bir Safsaf, within the hyperarid 'core' of the Sahara in the Western Desert of Egypt, was recognized following the SIR-A and SIR-B missions in the 1980s as one of the key localities in northeast Africa, where penetration of dry sand by radar signals delineates previously unknown, sand-buried paleodrainage valleys ('radar-rivers') of middle Tertiary to Quaternary age. The Bir Safsaf area was targeted as a focal point for further research in sand penetration and geologic mapping using the multifrequency and polarimetric SIR-C/X-SAR sensors. Analysis of the SIR-C/X-SAR data from Bir Safsaf provides important new information on the roles of multiple SAR frequency and polarimetry in portraying specific types of geologic units, materials, and structures mostly hidden from view on the ground and on Landsat TM images by a relatively thin, but extensive blanket of blow sand. Basement rock units (granitoids and gneisses) and the fractures associated with them at Bir Safsaf are shown here for the first time to be clearly delineated using C- and L-band SAR images. The detectability of most geologic features is dependent primarily on radar frequency, as shown for wind erosion patterns in bedrock at X-band (3 cm wavelength), and for geologic units and sand and clay-filled fractures in weathered crystal-line basement rocks at C-band (6 cm) and L-band (24 cm). By contrast, Quaternary paleodrainage channels are detectable at all three radar frequencies owing, among other things, to an usually thin cover of blow sand. The SIR-C/X-SAR data investigated to date enable us to make specific recommendations about the utility of certain radar sensor configurations for geologic and paleoenvironmental reconnaissance in desert regions.Analysis of the shuttle imaging radar-C/X-synthetic aperture radar (SIR-C/X-SAR) data from Bir Safsaf provides important new information on the roles of multiple SAR frequency and polarimetry in portraying specific types of geologic units, materials, and

  7. Joint synthetic aperture radar plus ground moving target indicator from single-channel radar using compressive sensing

    Science.gov (United States)

    Thompson, Douglas; Hallquist, Aaron; Anderson, Hyrum

    2017-10-17

    The various embodiments presented herein relate to utilizing an operational single-channel radar to collect and process synthetic aperture radar (SAR) and ground moving target indicator (GMTI) imagery from a same set of radar returns. In an embodiment, data is collected by randomly staggering a slow-time pulse repetition interval (PRI) over a SAR aperture such that a number of transmitted pulses in the SAR aperture is preserved with respect to standard SAR, but many of the pulses are spaced very closely enabling movers (e.g., targets) to be resolved, wherein a relative velocity of the movers places them outside of the SAR ground patch. The various embodiments of image reconstruction can be based on compressed sensing inversion from undersampled data, which can be solved efficiently using such techniques as Bregman iteration. The various embodiments enable high-quality SAR reconstruction, and high-quality GMTI reconstruction from the same set of radar returns.

  8. MULTI-TEMPORAL SAR INTERFEROMETRY FOR LANDSLIDE MONITORING

    Directory of Open Access Journals (Sweden)

    R. Dwivedi

    2016-06-01

    Full Text Available In the past few years, SAR Interferometry specially InSAR and D-InSAR were extensively used for deformation monitoring related applications. Due to temporal and spatial decorrelation in dense vegetated areas, effectiveness of InSAR and D-InSAR observations were always under scrutiny. Multi-temporal InSAR methods are developed in recent times to retrieve the deformation signal from pixels with different scattering characteristics. Presently, two classes of multi-temporal InSAR algorithms are available- Persistent Scatterer (PS and Small Baseline (SB methods. This paper discusses the Stanford Method for Persistent Scatterer (StaMPS based PS-InSAR and the Small Baselines Subset (SBAS techniques to estimate the surface deformation in Tehri dam reservoir region in Uttarkhand, India. Both PS-InSAR and SBAS approaches used sixteen ENVISAT ASAR C-Band images for generating single master and multiple master interferograms stack respectively and their StaMPS processing resulted in time series 1D-Line of Sight (LOS mean velocity maps which are indicative of deformation in terms of movement towards and away from the satellites. From 1D LOS velocity maps, localization of landslide is evident along the reservoir rim area which was also investigated in the previous studies. Both PS-InSAR and SBAS effectively extract measurement pixels in the study region, and the general results provided by both approaches show a similar deformation pattern along the Tehri reservoir region. Further, we conclude that StaMPS based PS-InSAR method performs better in terms of extracting more number of measurement pixels and in the estimation of mean Line of Sight (LOS velocity as compared to SBAS method. It is also proposed to take up a few major landslides area in Uttarakhand for slope stability assessment.

  9. Mutation of Asn28 Disrupts the Dimerization and Enzymatic Activity of SARS 3CL

    Energy Technology Data Exchange (ETDEWEB)

    Barrila, J.; Gabelli, S; Bacha, U; Amzel, M; Freire, E

    2010-01-01

    Coronaviruses are responsible for a significant proportion of annual respiratory and enteric infections in humans and other mammals. The most prominent of these viruses is the severe acute respiratory syndrome coronavirus (SARS-CoV) which causes acute respiratory and gastrointestinal infection in humans. The coronavirus main protease, 3CL{sup pro}, is a key target for broad-spectrum antiviral development because of its critical role in viral maturation and high degree of structural conservation among coronaviruses. Dimerization is an indispensable requirement for the function of SARS 3CL{sup pro} and is regulated through mechanisms involving both direct and long-range interactions in the enzyme. While many of the binding interactions at the dimerization interface have been extensively studied, those that are important for long-range control are not well-understood. Characterization of these dimerization mechanisms is important for the structure-based design of new treatments targeting coronavirus-based infections. Here we report that Asn28, a residue 11 {angstrom} from the closest residue in the opposing monomer, is essential for the enzymatic activity and dimerization of SARS 3CLpro. Mutation of this residue to alanine almost completely inactivates the enzyme and results in a 19.2-fold decrease in the dimerization K{sub d}. The crystallographic structure of the N28A mutant determined at 2.35 {angstrom} resolution reveals the critical role of Asn28 in maintaining the structural integrity of the active site and in orienting key residues involved in binding at the dimer interface and substrate catalysis. These findings provide deeper insight into complex mechanisms regulating the activity and dimerization of SARS 3CL{sup pro}.

  10. Impact of the Regulators SigB, Rot, SarA and sarS on the Toxic Shock Tst Promoter and TSST-1 Expression in Staphylococcus aureus.

    Directory of Open Access Journals (Sweden)

    Diego O Andrey

    Full Text Available Staphylococcus aureus is an important pathogen manifesting virulence through diverse disease forms, ranging from acute skin infections to life-threatening bacteremia or systemic toxic shock syndromes. In the latter case, the prototypical superantigen is TSST-1 (Toxic Shock Syndrome Toxin 1, encoded by tst(H, and carried on a mobile genetic element that is not present in all S. aureus strains. Transcriptional regulation of tst is only partially understood. In this study, we dissected the role of sarA, sarS (sarH1, RNAIII, rot, and the alternative stress sigma factor sigB (σB. By examining tst promoter regulation predominantly in the context of its native sequence within the SaPI1 pathogenicity island of strain RN4282, we discovered that σB emerged as a particularly important tst regulator. We did not detect a consensus σB site within the tst promoter, and thus the effect of σB is likely indirect. We found that σB strongly repressed the expression of the toxin via at least two distinct regulatory pathways dependent upon sarA and agr. Furthermore rot, a member of SarA family, was shown to repress tst expression when overexpressed, although its deletion had no consistent measurable effect. We could not find any detectable effect of sarS, either by deletion or overexpression, suggesting that this regulator plays a minimal role in TSST-1 expression except when combined with disruption of sarA. Collectively, our results extend our understanding of complex multifactorial regulation of tst, revealing several layers of negative regulation. In addition to environmental stimuli thought to impact TSST-1 production, these findings support a model whereby sporadic mutation in a few key negative regulators can profoundly affect and enhance TSST-1 expression.

  11. Bioinformatics analysis of SARS coronavirus genome polymorphism

    Directory of Open Access Journals (Sweden)

    Pavlović-Lažetić Gordana M

    2004-05-01

    Full Text Available Abstract Background We have compared 38 isolates of the SARS-CoV complete genome. The main goal was twofold: first, to analyze and compare nucleotide sequences and to identify positions of single nucleotide polymorphism (SNP, insertions and deletions, and second, to group them according to sequence similarity, eventually pointing to phylogeny of SARS-CoV isolates. The comparison is based on genome polymorphism such as insertions or deletions and the number and positions of SNPs. Results The nucleotide structure of all 38 isolates is presented. Based on insertions and deletions and dissimilarity due to SNPs, the dataset of all the isolates has been qualitatively classified into three groups each having their own subgroups. These are the A-group with "regular" isolates (no insertions / deletions except for 5' and 3' ends, the B-group of isolates with "long insertions", and the C-group of isolates with "many individual" insertions and deletions. The isolate with the smallest average number of SNPs, compared to other isolates, has been identified (TWH. The density distribution of SNPs, insertions and deletions for each group or subgroup, as well as cumulatively for all the isolates is also presented, along with the gene map for TWH. Since individual SNPs may have occurred at random, positions corresponding to multiple SNPs (occurring in two or more isolates are identified and presented. This result revises some previous results of a similar type. Amino acid changes caused by multiple SNPs are also identified (for the annotated sequences, as well as presupposed amino acid changes for non-annotated ones. Exact SNP positions for the isolates in each group or subgroup are presented. Finally, a phylogenetic tree for the SARS-CoV isolates has been produced using the CLUSTALW program, showing high compatibility with former qualitative classification. Conclusions The comparative study of SARS-CoV isolates provides essential information for genome

  12. Two dimensional estimates from ocean SAR images

    Directory of Open Access Journals (Sweden)

    J. M. Le Caillec

    1996-01-01

    Full Text Available Synthetic Aperture Radar (SAR images of the ocean yield a lot of information on the sea-state surface providing that the mapping process between the surface and the image is clearly defined. However it is well known that SAR images exhibit non-gaussian statistics and that the motion of the scatterers on the surface, while the image is being formed, may yield to nonlinearities. The detection and quantification of these nonlinearities are made possible by using Higher Order Spectra (HOS methods and more specifically, bispectrum estimation. The development of the latter method allowed us to find phase relations between different parts of the image and to recognise their level of coupling, i.e. if and how waves of different wavelengths interacted nonlinearly. This information is quite important as the usual models assume strong nonlinearities when the waves are propagating in the azimuthal direction (i.e. along the satellite track and almost no nonlinearities when propagating in the range direction. In this paper, the mapping of the ocean surface to the SAR image is reinterpreted and a specific model (i.e. a Second Order Volterra Model is introduced. The nonlinearities are thus explained as either produced by a nonlinear system or due to waves propagating into selected directions (azimuth or range and interacting during image formation. It is shown that quadratic nonlinearities occur for waves propagating near the range direction while for those travelling in the azimuthal direction the nonlinearities, when present, are mostly due to wave interactions but are almost completely removed by the filtering effect coming from the surface motion itself (azimuth cut-off. An inherent quadratic interaction filtering (azimuth high pass filter is also present. But some other effects, apparently nonlinear, are not detected with the methods described here, meaning that either the usual relation developed for the Ocean-to-SAR transform is somewhat incomplete

  13. Cross-calibration of interferometric SAR data

    DEFF Research Database (Denmark)

    Dall, Jørgen

    2003-01-01

    Generation of digital elevation models from interferometric synthetic aperture radar (SAR) data is a well established technique. Achieving a high geometric fidelity calls for a calibration accounting for inaccurate navigation data and system parameters as well as system imperfections. Fully...... automated calibration techniques are preferable, especially for operational mapping. The author presents one such technique, called cross-calibration. Though developed for single-pass interferometry, it may be applicable to multi-pass interferometry, too. Cross-calibration requires stability during mapping...... ground control point is often needed. The paper presents the principles and mathematics of the cross-calibration technique and illustrates its successful application to EMISAR data....

  14. Detection of land degradation with polarimetric SAR

    Science.gov (United States)

    Ray, Terrill W.; Farr, Tom G.; Van Zyl, Jakob J.

    1992-01-01

    Multispectral radar polarimeter data were collected over the Manix Basin Area of the Mojave desert using an airborne SAR. An analysis of the data reveals unusual polarization responses which are attributed to the formation of wind ripples on the surfaces of fields that have been abandoned for more than 5 years. This hypothesis has been confirmed through field observations, and a second-order perturbation model is shown to effectively model the polarization responses. The results demonstrate the usefulness of remote sensing techniques for the study of land degradation at synoptic scales.

  15. An Adaptive Ship Detection Algorithm for Hrws SAR Images Under Complex Background: Application to SENTINEL1A Data

    Science.gov (United States)

    He, G.; Xia, Z.; Chen, H.; Li, K.; Zhao, Z.; Guo, Y.; Feng, P.

    2018-04-01

    Real-time ship detection using synthetic aperture radar (SAR) plays a vital role in disaster emergency and marine security. Especially the high resolution and wide swath (HRWS) SAR images, provides the advantages of high resolution and wide swath synchronously, significantly promotes the wide area ocean surveillance performance. In this study, a novel method is developed for ship target detection by using the HRWS SAR images. Firstly, an adaptive sliding window is developed to propose the suspected ship target areas, based upon the analysis of SAR backscattering intensity images. Then, backscattering intensity and texture features extracted from the training samples of manually selected ship and non-ship slice images, are used to train a support vector machine (SVM) to classify the proposed ship slice images. The approach is verified by using the Sentinl1A data working in interferometric wide swath mode. The results demonstrate the improvement performance of the proposed method over the constant false alarm rate (CFAR) method, where the classification accuracy improved from 88.5 % to 96.4 % and the false alarm rate mitigated from 11.5 % to 3.6 % compared with CFAR respectively.

  16. Mapping mountain meadow with high resolution and polarimetric SAR data

    International Nuclear Information System (INIS)

    Tian, Bangsen; Li, Zhen; Xu, Juan; Fu, Sitao; Liu, Jiuli

    2014-01-01

    This paper presents a method to map the large grassland in the eastern margin of the Tibetan Plateau with the high resolution polarimetric SAR (PolSAR) imagery. When PolSAR imagery is used for land cover classification, the brightness of a SAR image is affected by topography due to varying projection between ground and image coordinates. The objective of this paper is twofold: (1) we first extend the theory of SAR terrain correction to the polarimetric case, to utilize the entire available polarimetric signature, where correction is performed explicitly based on a matrix format like covariance matrix. (2) Next, the orthoectified PolSAR is applied to classify mountain meadow and investigate the potential of PolSAR in mapping grassland. In this paper, the gamma naught radiometric correction estimates the local illuminated area at each grid point in the radar geometry. Then, each element of the coherency matrix is divided by the local area to produce a polarimetric product. Secondly, the impact of radiometric correction upon classification accuracy is investigated. A supervised classification is performed on the orthorectified Radarsat-2 PolSAR to map the spatial distribution of meadow and evaluate monitoring capabilities of mountain meadow

  17. Calibration of SAR probes in waveguide at 900 MHz

    International Nuclear Information System (INIS)

    Jokela, K.; Puranen, L.; Hyysalo, P.

    1998-01-01

    The radiation safety tests for hand-held mobile phones require precise calibration of the small electric field probes used for the measurement of SAR in phantoms simulating the human body. In this study a calibration based on a rectangular waveguide was developed for SAR calibrations at 900 MHz

  18. Training Convolutional Neural Networks for Translational Invariance on SAR ATR

    DEFF Research Database (Denmark)

    Malmgren-Hansen, David; Engholm, Rasmus; Østergaard Pedersen, Morten

    2016-01-01

    In this paper we present a comparison of the robustness of Convolutional Neural Networks (CNN) to other classifiers in the presence of uncertainty of the objects localization in SAR image. We present a framework for simulating simple SAR images, translating the object of interest systematically...

  19. Multi-look polarimetric SAR image filtering using simulated annealing

    DEFF Research Database (Denmark)

    Schou, Jesper

    2000-01-01

    Based on a previously published algorithm capable of estimating the radar cross-section in synthetic aperture radar (SAR) intensity images, a new filter is presented utilizing multi-look polarimetric SAR images. The underlying mean covariance matrix is estimated from the observed sample covariance...

  20. The Danish polarimetric SAR for remote sensing applications

    DEFF Research Database (Denmark)

    Christensen, Erik Lintz; Madsen, Søren Nørvang; Dall, Jørgen

    1994-01-01

    Presents the Danish polarimetric SAR system, EMISAR, and the approach taken in the system design to achieve a reliable high performance system. The design and implementation of the antenna system as well as the analog and digital hardware are discussed. The SAR utilises a dual polarised microstri...

  1. Project PHARUS: Towards a polarimetric C-band airborne SAR

    NARCIS (Netherlands)

    Hoogeboom, P.; Koomen, P.J.; Otten, M.P.G.; Pouwels, H.; Snoeij, P.

    1989-01-01

    A few years ago three institutes in the Netherlands developed a plan to design and build a polarimetric C-band aircraft SAR system of a novel design, called PHARUS (PHased Array Universal SAR), meant as a replacement for our current digital SLAR system. These institutes are the Physics and

  2. Crop Classification Using Short-Revisit Multitemporal SAR Data

    DEFF Research Database (Denmark)

    Skriver, Henning; Mattia, Francesco; Satalino, Giuseppe

    2011-01-01

    Classification of crops and other land cover types is an important application of both optical/infrared and SAR satellite data. It is already an import application of present satellite systems, as it will be for planned missions, such as the Sentinels. An airborne SAR data set with a short revisi...

  3. Rapid Automatic Motor Encoding of Competing Reach Options

    Directory of Open Access Journals (Sweden)

    Jason P. Gallivan

    2017-02-01

    Full Text Available Mounting neural evidence suggests that, in situations in which there are multiple potential targets for action, the brain prepares, in parallel, competing movements associated with these targets, prior to implementing one of them. Central to this interpretation is the idea that competing viewed targets, prior to selection, are rapidly and automatically transformed into corresponding motor representations. Here, by applying target-specific, gradual visuomotor rotations and dissociating, unbeknownst to participants, the visual direction of potential targets from the direction of the movements required to reach the same targets, we provide direct evidence for this provocative idea. Our results offer strong empirical support for theories suggesting that competing action options are automatically represented in terms of the movements required to attain them. The rapid motor encoding of potential targets may support the fast optimization of motor costs under conditions of target uncertainty and allow the motor system to inform decisions about target selection.

  4. A New Method Based on Two-Stage Detection Mechanism for Detecting Ships in High-Resolution SAR Images

    Directory of Open Access Journals (Sweden)

    Xu Yongli

    2017-01-01

    Full Text Available Ship detection in synthetic aperture radar (SAR remote sensing images, being a fundamental but challenging problem in the field of satellite image analysis, plays an important role for a wide range of applications and is receiving significant attention in recent years. Aiming at the requirements of ship detection in high-resolution SAR images, the accuracy, the intelligent level, a better real-time operation and processing efficiency, The characteristics of ocean background and ship target in high-resolution SAR images were analyzed, we put forward a ship detection algorithm in high-resolution SAR images. The algorithm consists of two detection stages: The first step designs a pre-training classifier based on improved spectral residual visual model to obtain the visual salient regions containing ship targets quickly, then achieve the purpose of probably detection of ships. In the second stage, considering the Bayesian theory of binary hypothesis detection, a local maximum posterior probability (MAP classifier is designed for the classification of pixels. After the parameter estimation and judgment criterion, the classification of pixels are carried out in the target areas to achieve the classification of two types of pixels in the salient regions. In the paper, several types of satellite image data, such as TerraSAR-X (TS-X, Radarsat-2, are used to evaluate the performance of detection methods. Comparing with classical CFAR detection algorithms, experimental results show that the algorithm can achieve a better effect of suppressing false alarms, which caused by the speckle noise and ocean clutter background inhomogeneity. At the same time, the detection speed is increased by 25% to 45%.

  5. Automatic Program Development

    DEFF Research Database (Denmark)

    Automatic Program Development is a tribute to Robert Paige (1947-1999), our accomplished and respected colleague, and moreover our good friend, whose untimely passing was a loss to our academic and research community. We have collected the revised, updated versions of the papers published in his...... honor in the Higher-Order and Symbolic Computation Journal in the years 2003 and 2005. Among them there are two papers by Bob: (i) a retrospective view of his research lines, and (ii) a proposal for future studies in the area of the automatic program derivation. The book also includes some papers...... by members of the IFIP Working Group 2.1 of which Bob was an active member. All papers are related to some of the research interests of Bob and, in particular, to the transformational development of programs and their algorithmic derivation from formal specifications. Automatic Program Development offers...

  6. Precise Determination of the Baseline Between the TerraSAR-X and TanDEM-X Satellites

    Science.gov (United States)

    Koenig, Rolf; Rothacher, Markus; Michalak, Grzegorz; Moon, Yongjin

    TerraSAR-X, launched on June 15, 2007, and TanDEM-X, to be launched in September 2009, both carry the Tracking, Occultation and Ranging (TOR) category A payload instrument package. The TOR consists of a high-precision dual-frequency GPS receiver, called Integrated GPS Occultation Receiver (IGOR), for precise orbit determination and atmospheric sounding and a Laser retro-reflector (LRR) serving as target for the global Satellite Laser Ranging (SLR) ground station network. The TOR is supplied by the GeoForschungsZentrum Potsdam (GFZ) Germany, and the Center for Space Research (CSR), Austin, Texas. The objective of the German/US collaboration is twofold: provision of atmospheric profiles for use in numerical weather predictions and climate studies from the occultation data and precision SAR data processing based on precise orbits and atmospheric products. For the scientific objectives of the TanDEM- X mission, i.e., bi-static SAR together with TerraSAR-X, the dual-frequency GPS receiver is of vital importance for the millimeter level determination of the baseline or distance between the two spacecrafts. The paper discusses the feasibility of generating millimeter baselines by the example of GRACE, where for validation the distance between the two GRACE satellites is directly available from the micrometer-level intersatellite link measurements. The distance of the GRACE satellites is some 200 km, the distance of the TerraSAR-X/TanDEM-X formation will be some 200 meters. Therefore the proposed approach is then subject to a simulation of the foreseen TerraSAR-X/TanDEM-X formation. The effect of varying space environmental conditions, of possible phase center variations, multi path, and of varying center of mass of the spacecrafts are evaluated and discussed.

  7. INVENTORY OF IRRIGATED RICE ECOSYSTEM USING POLARIMETRIC SAR DATA

    Directory of Open Access Journals (Sweden)

    P. Srikanth

    2012-08-01

    Full Text Available An attempt has been made in the current study to assess the potential of polarimetric SAR data for inventory of kharif rice and the major competing crop like cotton. In the process, physical process of the scattering mechanisms occurring in rice and cotton crops at different phonological stages was studied through the use of temporal Radarsat 2 Fine quadpol SAR data. The temporal dynamics of the volume, double and odd bounce, entropy, anisotropy, alpha parameters and polarimertic signatures, classification through isodata clustering and Wishart techniques were assessed. The Wishart (H-a classification showed higher overall as well as rice and cotton crop accuracies compared to the isodata clustering from Freeman 3-component decomposition. The classification of temporal SAR data sets independently showed that the rice crop forecasting can be advanced with the use of appropriate single date polarimetric SAR data rather than using temporal SAR amplitude data sets with the single polarization in irrigated rice ecosystems

  8. Assessing ScanSAR Interferometry for Deformation Studies

    Science.gov (United States)

    Buckley, S. M.; Gudipati, K.

    2007-12-01

    There is a trend in civil satellite SAR mission design to implement an imaging strategy that incorporates both stripmap mode and ScanSAR imaging. This represents a compromise between high resolution data collection and a desire for greater spatial coverage and more frequent revisit times. However, mixed mode imaging can greatly reduce the number of stripmap images available for measuring subtle ground deformation. Although ScanSAR-ScanSAR and ScanSAR-stripmap repeat-pass interferometry have been demonstrated, these approaches are infrequently used for single interferogram formation and nonexistent for InSAR time series analysis. For future mission design, e.g., a dedicated US InSAR mission, the effect of various ScanSAR system parameter choices on InSAR time series analysis also remains unexplored. Our objective is to determine the utility of ScanSAR differential interferometry. We will demonstrate the use of ScanSAR interferograms for several previous deformation studies: localized and broad-scale urban land subsidence, tunneling, volcanic surface movements and several examples associated with the seismic cycle. We also investigate the effect of various ScanSAR burst synchronization levels on our ability to detect and make quality measurements of deformation. To avoid the issues associated with Envisat ScanSAR burst alignment and to exploit a decade of InSAR measurements, we simulate ScanSAR data by bursting (throwing away range lines of) ERS-1/2 data. All the burst mode datasets are processed using a Modified SPECAN algorithm. To investigate the effects of burst misalignment, a number of cases with varying degrees of burst overlap are considered. In particular, we look at phase decorrelation as a function of percentage of burst overlap. Coherence clearly reduces as the percentage of overlap decreases and we find a useful threshold of 40-70% burst overlap depending on the study site. In order to get a more generalized understanding for different surface conditions

  9. Guided SAR image despeckling with probabilistic non local weights

    Science.gov (United States)

    Gokul, Jithin; Nair, Madhu S.; Rajan, Jeny

    2017-12-01

    SAR images are generally corrupted by granular disturbances called speckle, which makes visual analysis and detail extraction a difficult task. Non Local despeckling techniques with probabilistic similarity has been a recent trend in SAR despeckling. To achieve effective speckle suppression without compromising detail preservation, we propose an improvement for the existing Generalized Guided Filter with Bayesian Non-Local Means (GGF-BNLM) method. The proposed method (Guided SAR Image Despeckling with Probabilistic Non Local Weights) replaces parametric constants based on heuristics in GGF-BNLM method with dynamically derived values based on the image statistics for weight computation. Proposed changes make GGF-BNLM method adaptive and as a result, significant improvement is achieved in terms of performance. Experimental analysis on SAR images shows excellent speckle reduction without compromising feature preservation when compared to GGF-BNLM method. Results are also compared with other state-of-the-art and classic SAR depseckling techniques to demonstrate the effectiveness of the proposed method.

  10. A novel ship CFAR detection algorithm based on adaptive parameter enhancement and wake-aided detection in SAR images

    Science.gov (United States)

    Meng, Siqi; Ren, Kan; Lu, Dongming; Gu, Guohua; Chen, Qian; Lu, Guojun

    2018-03-01

    Synthetic aperture radar (SAR) is an indispensable and useful method for marine monitoring. With the increase of SAR sensors, high resolution images can be acquired and contain more target structure information, such as more spatial details etc. This paper presents a novel adaptive parameter transform (APT) domain constant false alarm rate (CFAR) to highlight targets. The whole method is based on the APT domain value. Firstly, the image is mapped to the new transform domain by the algorithm. Secondly, the false candidate target pixels are screened out by the CFAR detector to highlight the target ships. Thirdly, the ship pixels are replaced by the homogeneous sea pixels. And then, the enhanced image is processed by Niblack algorithm to obtain the wake binary image. Finally, normalized Hough transform (NHT) is used to detect wakes in the binary image, as a verification of the presence of the ships. Experiments on real SAR images validate that the proposed transform does enhance the target structure and improve the contrast of the image. The algorithm has a good performance in the ship and ship wake detection.

  11. Application of Satellite SAR for Discovery and Quantification of Natural Marine Oil Seeps

    Science.gov (United States)

    Amos, J.; Lai, R.; Zimmer, B.; Leiva, A.; MacDonald, I.

    2006-12-01

    Natural marine oil seeps discharge gassy drops from the seafloor. Oil drops and gas bubbles reach the surface from water depths as great as 3000m. The oil spreads rapidly, forming an invisible layer that drifts down-wind and down-current in long, linear streaks called slicks. Oil slicks are visible in SAR data because the surfactant dampens capillary waves and reduces backscatter. Application of SAR as an exploration tool in energy prospecting is well-established. We have applied this technique for discovering the chemosynthetic communities that colonize the seafloor in the vicinity of deep-water seeps on the continental margin of the Gulf of Mexico. The management goal for this effort is to prevent harmful impact to these communities resulting from exploration or production activities. The scientific goals are to delineate the zoogeography of the chemosynthetic fauna, which is widespread on continental margins, and to establish study sites where their life history can be investigated. In the course of an ongoing, multidisciplinary study in the spring and summer of 2006, we explored 20 possible sites where SAR and geophysical data indicated seeps might occur. SAR was only partly diagnostic: all sites with SAR-detected slicks were found to have biologic communities, but communities were also found at geophysical anomalies that did not produce slicks. We acquired over 60 RADARSAT SAR images from the northern Gulf of Mexico in cooperation with the Alaska Satellite Facility. The ship RV ATLANTIS was at sea during the acquisition and collected synoptic weather and oceanographic data. To automate interpretation of large image dataset we have employed texture recognition with use of a library of textons applied iteratively to the images. This treatment shows promise in distinguishing floating oil from false targets generated by rain fronts and other phenomena. One goal of the analysis is to delineate bounding boxes to quantify the ocean area covered by the thin oil layer

  12. Automatic text summarization

    CERN Document Server

    Torres Moreno, Juan Manuel

    2014-01-01

    This new textbook examines the motivations and the different algorithms for automatic document summarization (ADS). We performed a recent state of the art. The book shows the main problems of ADS, difficulties and the solutions provided by the community. It presents recent advances in ADS, as well as current applications and trends. The approaches are statistical, linguistic and symbolic. Several exemples are included in order to clarify the theoretical concepts.  The books currently available in the area of Automatic Document Summarization are not recent. Powerful algorithms have been develop

  13. Automatic Ultrasound Scanning

    DEFF Research Database (Denmark)

    Moshavegh, Ramin

    on the user adjustments on the scanner interface to optimize the scan settings. This explains the huge interest in the subject of this PhD project entitled “AUTOMATIC ULTRASOUND SCANNING”. The key goals of the project have been to develop automated techniques to minimize the unnecessary settings...... on the scanners, and to improve the computer-aided diagnosis (CAD) in ultrasound by introducing new quantitative measures. Thus, four major issues concerning automation of the medical ultrasound are addressed in this PhD project. They touch upon gain adjustments in ultrasound, automatic synthetic aperture image...

  14. Automatic NAA. Saturation activities

    International Nuclear Information System (INIS)

    Westphal, G.P.; Grass, F.; Kuhnert, M.

    2008-01-01

    A system for Automatic NAA is based on a list of specific saturation activities determined for one irradiation position at a given neutron flux and a single detector geometry. Originally compiled from measurements of standard reference materials, the list may be extended also by the calculation of saturation activities from k 0 and Q 0 factors, and f and α values of the irradiation position. A systematic improvement of the SRM approach is currently being performed by pseudo-cyclic activation analysis, to reduce counting errors. From these measurements, the list of saturation activities is recalculated in an automatic procedure. (author)

  15. Landslide Kinematical Analysis through Inverse Numerical Modelling and Differential SAR Interferometry

    Science.gov (United States)

    Castaldo, R.; Tizzani, P.; Lollino, P.; Calò, F.; Ardizzone, F.; Lanari, R.; Guzzetti, F.; Manunta, M.

    2015-11-01

    The aim of this paper is to propose a methodology to perform inverse numerical modelling of slow landslides that combines the potentialities of both numerical approaches and well-known remote-sensing satellite techniques. In particular, through an optimization procedure based on a genetic algorithm, we minimize, with respect to a proper penalty function, the difference between the modelled displacement field and differential synthetic aperture radar interferometry (DInSAR) deformation time series. The proposed methodology allows us to automatically search for the physical parameters that characterize the landslide behaviour. To validate the presented approach, we focus our analysis on the slow Ivancich landslide (Assisi, central Italy). The kinematical evolution of the unstable slope is investigated via long-term DInSAR analysis, by exploiting about 20 years of ERS-1/2 and ENVISAT satellite acquisitions. The landslide is driven by the presence of a shear band, whose behaviour is simulated through a two-dimensional time-dependent finite element model, in two different physical scenarios, i.e. Newtonian viscous flow and a deviatoric creep model. Comparison between the model results and DInSAR measurements reveals that the deviatoric creep model is more suitable to describe the kinematical evolution of the landslide. This finding is also confirmed by comparing the model results with the available independent inclinometer measurements. Our analysis emphasizes that integration of different data, within inverse numerical models, allows deep investigation of the kinematical behaviour of slow active landslides and discrimination of the driving forces that govern their deformation processes.

  16. Relations of SARS-Related Stressors and Coping to Chinese College Students' Psychological Adjustment during the 2003 Beijing SARS Epidemic

    Science.gov (United States)

    Main, Alexandra; Zhou, Qing; Ma, Yue; Luecken, Linda J.; Liu, Xin

    2011-01-01

    This study examined the main and interactive relations of stressors and coping related to severe acute respiratory syndrome (SARS) with Chinese college students' psychological adjustment (psychological symptoms, perceived general health, and life satisfaction) during the 2003 Beijing SARS epidemic. All the constructs were assessed by self-report…

  17. 3D Monitoring of Buildings Using TerraSAR-X InSAR, DInSAR and PolSAR Capacities

    Directory of Open Access Journals (Sweden)

    Flora Weissgerber

    2017-09-01

    Full Text Available The rapid expansion of cities increases the need of urban remote sensing for a large scale monitoring. This paper provides greater understanding of how TerraSAR-X (TSX high-resolution abilities enable to reach the spatial precision required to monitor individual buildings, through the use of a 4 year temporal stack of 100 images over Paris (France. Three different SAR modes are investigated for this purpose. First a method involving a whole time-series is proposed to measure realistic heights of buildings. Then, we show that the small wavelength of TSX makes the interferometric products very sensitive to the ordinary building-deformation, and that daily deformation can be measured over the entire building with a centimetric accuracy, and without any a priori on the deformation evolution, even when neglecting the impact of the atmosphere. Deformations up to 4 cm were estimated for the Eiffel Tower and up to 1 cm for other lower buildings. These deformations were analyzed and validated with weather and in situ local data. Finally, four TSX polarimetric images were used to investigate geometric and dielectric properties of buildings under the deterministic framework. Despite of the resolution loss of this mode, the possibility to estimate the structural elements of a building orientations and their relative complexity in the spatial organization are demonstrated.

  18. The Ecosystems SAR (EcoSAR) an Airborne P-band Polarimetric InSAR for the Measurement of Vegetation Structure, Biomass and Permafrost

    Science.gov (United States)

    Rincon, Rafael F.; Fatoyinbo, Temilola; Ranson, K. Jon; Osmanoglu, Batuhan; Sun, Guoqing; Deshpande, Manohar D.; Perrine, Martin L.; Du Toit, Cornelis F.; Bonds, Quenton; Beck, Jaclyn; hide

    2014-01-01

    EcoSAR is a new synthetic aperture radar (SAR) instrument being developed at the NASA/ Goddard Space Flight Center (GSFC) for the polarimetric and interferometric measurements of ecosystem structure and biomass. The instrument uses a phased-array beamforming architecture and supports full polarimetric measurements and single pass interferometry. This Instrument development is part of NASA's Earth Science Technology Office Instrument Incubator Program (ESTO IIP).

  19. Automatic creation of simulation configuration

    International Nuclear Information System (INIS)

    Oudot, G.; Poizat, F.

    1993-01-01

    SIPA, which stands for 'Simulator for Post Accident', includes: 1) a sophisticated software oriented workshop SWORD (which stands for 'Software Workshop Oriented towards Research and Development') designed in the ADA language including integrated CAD system and software tools for automatic generation of simulation software and man-machine interface in order to operate run-time simulation; 2) a 'simulator structure' based on hardware equipment and software for supervision and communications; 3) simulation configuration generated by SWORD, operated under the control of the 'simulator structure' and run on a target computer. SWORD has already been used to generate two simulation configurations (French 900 MW and 1300 MW nuclear power plants), which are now fully operational on the SIPA training simulator. (Z.S.) 1 ref

  20. Special hydrogen target (Prop. 210)

    International Nuclear Information System (INIS)

    Halliday, C.E.

    1979-11-01

    This guide contains a description of the electrical control and automatic vacuum systems for the Special Hydrogen Target (Prop. 210) together with the flow diagram and the mimic control panel layout for the system. (U.K.)

  1. Neural networks for oil spill detection using TerraSAR-X data

    Science.gov (United States)

    Avezzano, Ruggero G.; Velotto, Domenico; Soccorsi, Matteo; Del Frate, Fabio; Lehner, Susanne

    2011-11-01

    The increased amount of available Synthetic Aperture Radar (SAR) images involves a growing workload on the operators at analysis centers. In addition, even if the operators go through extensive training to learn manual oil spill detection, they can provide different and subjective responses. Hence, the upgrade and improvements of algorithms for automatic detection that can help in screening the images and prioritizing the alarms are of great benefit. In this paper we present the potentialities of TerraSAR-X (TS-X) data and Neural Network algorithms for oil spills detection. The radar on board satellite TS-X provides X-band images with a resolution of up to 1m. Such resolution can be very effective in the monitoring of coastal areas to prevent sea oil pollution. The network input is a vector containing the values of a set of features characterizing an oil spill candidate. The network output gives the probability for the candidate to be a real oil spill. Candidates with a probability less than 50% are classified as look-alikes. The overall classification performances have been evaluated on a data set of 50 TS-X images containing more than 150 examples of certified oil spills and well-known look-alikes (e.g. low wind areas, wind shadows, biogenic films). The preliminary classification results are satisfactory with an overall detection accuracy above 80%.

  2. Correction of Dynamic Characteristics of SAR Cryogenic GTE on Consumption of Gasified Fuel

    Science.gov (United States)

    Bukin, V. A.; Gimadiev, A. G.; Gangisetty, G.

    2018-01-01

    When the gas turbine engines (GTE) NK-88 were developed for liquid hydrogen and NK-89 for liquefied natural gas, performance of the systems with a turbo-pump unitary was improved and its proved without direct regulation of the flow of a cryogenic fuel, which was supplied by a centrifugal pump of the turbo-pump unit (TPU) Command from the “kerosene” system. Such type of the automatic control system (SAR) has the property of partial “neutralization” of the delay caused by gasification of the fuel. This does not require any measurements in the cryogenic medium, and the failure of the centrifugal cryogenic pump does not lead to engine failure. On the other hand, the system without direct regulation of the flow of cryogenic fuel has complex internal dynamic connections, their properties are determined by the characteristics of the incoming units and assemblies, and it is difficult to maintain accurate the maximum boundary level and minimum fuel consumption due to the influence of a booster pressure change. Direct regulation of the consumption of cryogenic fuel (prior to its gasification) is the preferred solution, since for using traditional liquid and gaseous fuels this is the main and proven method. The scheme of correction of dynamic characteristics of a single-loop SAR GTE for the consumption of a liquefied cryogenic fuel with a flow rate correction in its gasified state, which ensures the dynamic properties of the system is not worse than for NK-88 and NK-89 engines.

  3. Predicting Intra-Urban Population Densities in Africa using SAR and Optical Remote Sensing Data

    Science.gov (United States)

    Linard, C.; Steele, J.; Forget, Y.; Lopez, J.; Shimoni, M.

    2017-12-01

    The population of Africa is predicted to double over the next 40 years, driving profound social, environmental and epidemiological changes within rapidly growing cities. Estimations of within-city variations in population density must be improved in order to take urban heterogeneities into account and better help urban research and decision making, especially for vulnerability and health assessments. Satellite remote sensing offers an effective solution for mapping settlements and monitoring urbanization at different spatial and temporal scales. In Africa, the urban landscape is covered by slums and small houses, where the heterogeneity is high and where the man-made materials are natural. Innovative methods that combine optical and SAR data are therefore necessary for improving settlement mapping and population density predictions. An automatic method was developed to estimate built-up densities using recent and archived optical and SAR data and a multi-temporal database of built-up densities was produced for 48 African cities. Geo-statistical methods were then used to study the relationships between census-derived population densities and satellite-derived built-up attributes. Best predictors were combined in a Random Forest framework in order to predict intra-urban variations in population density in any large African city. Models show significant improvement of our spatial understanding of urbanization and urban population distribution in Africa in comparison to the state of the art.

  4. Applications of Environmental Remote Sensing by HJ-1C SAR Imageries

    Directory of Open Access Journals (Sweden)

    Tian Wei

    2014-06-01

    Full Text Available The HJ-1C satellite was successfully launched in November 19, 2012. The HJ-1C and HJ-1A/1B satellites, which were launched in September 06, 2008, constitute the “2+1” small satellite constellation for environmental and disaster monitoring. This study focuses on the analysis and evaluation of the satellite performance with respect to environmental remote sensing, including land use interpretation, land cover classification, oil spill identification, retrieval of sea waves, and monitoring of coastal mariculture. The data used in this study cover the city of Beijing and the sea of the Fujian Province. Nine HJ-1C satellite images (level-2, S band, VV Pol, strip mode, 5 m resolution from December 2012 to January 2013 are used. The conclusions are as follows: (1 the HJ-1C SAR images can be used to manually identify farmland, woodland, roads, rivers, urban construction, and rural residential areas; (2 the accuracy of the automatic land cover classification increased significantly when the HJ-1C SAR and HJ-1B CCD fusion images are used; (3 the HJ-1C satellite can be used to identify oil spills, to invert wave parameters, and to extract information regarding inshore aquaculture.

  5. DInSAR time series generation within a cloud computing environment: from ERS to Sentinel-1 scenario

    Science.gov (United States)

    Casu, Francesco; Elefante, Stefano; Imperatore, Pasquale; Lanari, Riccardo; Manunta, Michele; Zinno, Ivana; Mathot, Emmanuel; Brito, Fabrice; Farres, Jordi; Lengert, Wolfgang

    2013-04-01

    One of the techniques that will strongly benefit from the advent of the Sentinel-1 system is Differential SAR Interferometry (DInSAR), which has successfully demonstrated to be an effective tool to detect and monitor ground displacements with centimetre accuracy. The geoscience communities (volcanology, seismicity, …), as well as those related to hazard monitoring and risk mitigation, make extensively use of the DInSAR technique and they will take advantage from the huge amount of SAR data acquired by Sentinel-1. Indeed, such an information will successfully permit the generation of Earth's surface displacement maps and time series both over large areas and long time span. However, the issue of managing, processing and analysing the large Sentinel data stream is envisaged by the scientific community to be a major bottleneck, particularly during crisis phases. The emerging need of creating a common ecosystem in which data, results and processing tools are shared, is envisaged to be a successful way to address such a problem and to contribute to the information and knowledge spreading. The Supersites initiative as well as the ESA SuperSites Exploitation Platform (SSEP) and the ESA Cloud Computing Operational Pilot (CIOP) projects provide effective answers to this need and they are pushing towards the development of such an ecosystem. It is clear that all the current and existent tools for querying, processing and analysing SAR data are required to be not only updated for managing the large data stream of Sentinel-1 satellite, but also reorganized for quickly replying to the simultaneous and highly demanding user requests, mainly during emergency situations. This translates into the automatic and unsupervised processing of large amount of data as well as the availability of scalable, widely accessible and high performance computing capabilities. The cloud computing environment permits to achieve all of these objectives, particularly in case of spike and peak

  6. Cliff : the automatized zipper

    NARCIS (Netherlands)

    Baharom, M.Z.; Toeters, M.J.; Delbressine, F.L.M.; Bangaru, C.; Feijs, L.M.G.

    2016-01-01

    It is our strong believe that fashion - more specifically apparel - can support us so much more in our daily life than it currently does. The Cliff project takes the opportunity to create a generic automatized zipper. It is a response to the struggle by elderly, people with physical disability, and

  7. Automatic Complexity Analysis

    DEFF Research Database (Denmark)

    Rosendahl, Mads

    1989-01-01

    One way to analyse programs is to to derive expressions for their computational behaviour. A time bound function (or worst-case complexity) gives an upper bound for the computation time as a function of the size of input. We describe a system to derive such time bounds automatically using abstract...

  8. Automatic Oscillating Turret.

    Science.gov (United States)

    1981-03-01

    Final Report: February 1978 ZAUTOMATIC OSCILLATING TURRET SYSTEM September 1980 * 6. PERFORMING 01G. REPORT NUMBER .J7. AUTHOR(S) S. CONTRACT OR GRANT...o....e.... *24 APPENDIX P-4 OSCILLATING BUMPER TURRET ...................... 25 A. DESCRIPTION 1. Turret Controls ...Other criteria requirements were: 1. Turret controls inside cab. 2. Automatic oscillation with fixed elevation to range from 20* below the horizontal to

  9. Reactor component automatic grapple

    International Nuclear Information System (INIS)

    Greenaway, P.R.

    1982-01-01

    A grapple for handling nuclear reactor components in a medium such as liquid sodium which, upon proper seating and alignment of the grapple with the component as sensed by a mechanical logic integral to the grapple, automatically seizes the component. The mechanical logic system also precludes seizure in the absence of proper seating and alignment. (author)

  10. Automatic sweep circuit

    International Nuclear Information System (INIS)

    Keefe, D.J.

    1980-01-01

    An automatically sweeping circuit for searching for an evoked response in an output signal in time with respect to a trigger input is described. Digital counters are used to activate a detector at precise intervals, and monitoring is repeated for statistical accuracy. If the response is not found then a different time window is examined until the signal is found

  11. Automatic sweep circuit

    Science.gov (United States)

    Keefe, Donald J.

    1980-01-01

    An automatically sweeping circuit for searching for an evoked response in an output signal in time with respect to a trigger input. Digital counters are used to activate a detector at precise intervals, and monitoring is repeated for statistical accuracy. If the response is not found then a different time window is examined until the signal is found.

  12. Recursive automatic classification algorithms

    Energy Technology Data Exchange (ETDEWEB)

    Bauman, E V; Dorofeyuk, A A

    1982-03-01

    A variational statement of the automatic classification problem is given. The dependence of the form of the optimal partition surface on the form of the classification objective functional is investigated. A recursive algorithm is proposed for maximising a functional of reasonably general form. The convergence problem is analysed in connection with the proposed algorithm. 8 references.

  13. Automatic Commercial Permit Sets

    Energy Technology Data Exchange (ETDEWEB)

    Grana, Paul [Folsom Labs, Inc., San Francisco, CA (United States)

    2017-12-21

    Final report for Folsom Labs’ Solar Permit Generator project, which has successfully completed, resulting in the development and commercialization of a software toolkit within the cloud-based HelioScope software environment that enables solar engineers to automatically generate and manage draft documents for permit submission.

  14. Rheticus Displacement: an Automatic Geo-Information Service Platform for Ground Instabilities Detection and Monitoring

    Science.gov (United States)

    Chiaradia, M. T.; Samarelli, S.; Agrimano, L.; Lorusso, A. P.; Nutricato, R.; Nitti, D. O.; Morea, A.; Tijani, K.

    2016-12-01

    Rheticus® is an innovative cloud-based data and services hub able to deliver Earth Observation added-value products through automatic complex processes and a minimum interaction with human operators. This target is achieved by means of programmable components working as different software layers in a modern enterprise system which relies on SOA (service-oriented-architecture) model. Due to its architecture, where every functionality is well defined and encapsulated in a standalone component, Rheticus is potentially highly scalable and distributable allowing different configurations depending on the user needs. Rheticus offers a portfolio of services, ranging from the detection and monitoring of geohazards and infrastructural instabilities, to marine water quality monitoring, wildfires detection or land cover monitoring. In this work, we outline the overall cloud-based platform and focus on the "Rheticus Displacement" service, aimed at providing accurate information to monitor movements occurring across landslide features or structural instabilities that could affect buildings or infrastructures. Using Sentinel-1 (S1) open data images and Multi-Temporal SAR Interferometry techniques (i.e., SPINUA), the service is complementary to traditional survey methods, providing a long-term solution to slope instability monitoring. Rheticus automatically browses and accesses (on a weekly basis) the products of the rolling archive of ESA S1 Scientific Data Hub; S1 data are then handled by a mature running processing chain, which is responsible of producing displacement maps immediately usable to measure with sub-centimetric precision movements of coherent points. Examples are provided, concerning the automatic displacement map generation process, as well as the integration of point and distributed scatterers, the integration of multi-sensors displacement maps (e.g., Sentinel-1 IW and COSMO-SkyMed HIMAGE), the combination of displacement rate maps acquired along both ascending

  15. Inhibition of severe acute respiratory syndrome coronavirus replication in a lethal SARS-CoV BALB/c mouse model by stinging nettle lectin, Urtica dioica agglutinin

    Science.gov (United States)

    Kumaki, Yohichi; Wandersee, Miles K.; Smith, Aaron J.; Zhou, Yanchen; Simmons, Graham; Nelson, Nathan M.; Bailey, Kevin W.; Vest, Zachary G.; Li, Joseph K.-K.; Chan, Paul Kay-Sheung; Smee, Donald F.; Barnard, Dale L.

    2011-01-01

    Urtica dioica agglutinin (UDA) is a small plant monomeric lectin, 8.7 kDa in size, with an N-acetylglucosamine specificity that inhibits viruses from Nidovirales in vitro. In the current study, we first examined the efficacy of UDA on the replication of different SARS-CoV strains in Vero 76 cells. UDA inhibited virus replication in a dose-dependent manner and reduced virus yields of the Urbani strain by 90% at 1.1 ± 0.4 µg/ml in Vero 76 cells. Then, UDA was tested for efficacy in a lethal SARS-CoV-infected BALB/c mouse model. BALB/c mice were infected with two LD50 (575 PFU) of virus for 4 hours before the mice were treated intraperitoneally with UDA at 20, 10, 5 or 0 mg/kg/day for 4 days. Treatment with UDA at 5 mg/kg significantly protected the mice against a lethal infection with mouse-adapted SARS-CoV (p<0.001), but did not significantly reduce virus lung titers. All virus-infected mice receiving UDA treatments were also significantly protected against weight loss (p<0.001). UDA also effectively reduced lung pathology scores. At day 6 after virus exposure, all groups of mice receiving UDA had much lower lung weights than did the placebo-treated mice. Thus, our data suggest that UDA treatment of SARS infection in mice leads to a substantial therapeutic effect that protects mice against death and weight loss. Furthermore, the mode of action of UDA in vitro was further investigated using live SARS-CoV Urbani strain virus and retroviral particles pseudotyped with SARS-CoV spike (S). UDA specifically inhibited the replication of live SARS-CoV or SARS-CoV pseudotyped virus when added just before, but not after, adsorption. These data suggested that UDA likely inhibits SARS-CoV infection by targeting early stages of the replication cycle, namely, adsorption or penetration. In addition, we demonstrated that UDA neutralizes the virus infectivity, presumably by binding to the SARS-CoV spike (S) glycoprotein. Finally, the target molecule for inhibition of virus

  16. Inhibition of severe acute respiratory syndrome coronavirus replication in a lethal SARS-CoV BALB/c mouse model by stinging nettle lectin, Urtica dioica agglutinin.

    Science.gov (United States)

    Kumaki, Yohichi; Wandersee, Miles K; Smith, Aaron J; Zhou, Yanchen; Simmons, Graham; Nelson, Nathan M; Bailey, Kevin W; Vest, Zachary G; Li, Joseph K-K; Chan, Paul Kay-Sheung; Smee, Donald F; Barnard, Dale L

    2011-04-01

    Urtica dioica agglutinin (UDA) is a small plant monomeric lectin, 8.7 kDa in size, with an N-acetylglucosamine specificity that inhibits viruses from Nidovirales in vitro. In the current study, we first examined the efficacy of UDA on the replication of different SARS-CoV strains in Vero 76 cells. UDA inhibited virus replication in a dose-dependent manner and reduced virus yields of the Urbani strain by 90% at 1.1 ± 0.4 μg/ml in Vero 76 cells. Then, UDA was tested for efficacy in a lethal SARS-CoV-infected BALB/c mouse model. BALB/c mice were infected with two LD50 (575 PFU) of virus for 4 h before the mice were treated intraperitoneally with UDA at 20, 10, 5 or 0 mg/kg/day for 4 days. Treatment with UDA at 5 mg/kg significantly protected the mice against a lethal infection with mouse-adapted SARS-CoV (p < 0.001), but did not significantly reduce virus lung titers. All virus-infected mice receiving UDA treatments were also significantly protected against weight loss (p < 0.001). UDA also effectively reduced lung pathology scores. At day 6 after virus exposure, all groups of mice receiving UDA had much lower lung weights than did the placebo-treated mice. Thus, our data suggest that UDA treatment of SARS infection in mice leads to a substantial therapeutic effect that protects mice against death and weight loss. Furthermore, the mode of action of UDA in vitro was further investigated using live SARS-CoV Urbani strain virus and retroviral particles pseudotyped with SARS-CoV spike (S). UDA specifically inhibited the replication of live SARS-CoV or SARS-CoV pseudotyped virus when added just before, but not after, adsorption. These data suggested that UDA likely inhibits SARS-CoV infection by targeting early stages of the replication cycle, namely, adsorption or penetration. In addition, we demonstrated that UDA neutralizes the virus infectivity, presumably by binding to the SARS-CoV spike (S) glycoprotein. Finally, the target molecule for the inhibition of virus

  17. La articulación del lenguaje surrealista de César Moro

    Directory of Open Access Journals (Sweden)

    Gabriel Ramos

    2015-07-01

    Full Text Available César Moro’s work represents the main achievement of surrealism in Latin American Literature. His poetic strategy is best defined in La tortuga ecuestre, where he reaches the maximum width of his artistic attainment. His style is characterized by a variant of automatism, which is supported by plenty of nominal phrases, repetitions, anaphors, etc., from where the poem’s rhythm is derived. Moro’s surrealist discourse proposes the destruction of previous orders of perception and experience. The lover’s discourse is established through the tension between the persistence of desire, and the presence and absence of the beloved. It is constantly broken down, thus recreating the world, its Nature and its sense.

  18. Potential inundated coastal area estimation in Shanghai with multi-platform SAR and altimetry data

    Science.gov (United States)

    Ma, Guanyu; Yang, Tianliang; Zhao, Qing; Kubanek, Julia; Pepe, Antonio; Dong, Hongbin; Sun, Zhibin

    2017-09-01

    As global warming problem is becoming serious in recent decades, the global sea level is continuously rising. This will cause damages to the coastal deltas with the characteristics of low-lying land, dense population, and developed economy. Continuously reclamation costal intertidal and wetland areas are making Shanghai, the mega city of Yangtze River Delta, more vulnerable to sea level rise. In this paper, we investigate the land subsidence temporal evolution of patterns and processes on a stretch of muddy coast located between the Yangtze River Estuary and Hangzou Bay with differential synthetic aperture radar interferometry (DInSAR) analyses. By exploiting a set of 31 SAR images acquired by the ENVISAT/ASAR from February 2007 to May 2010 and a set of 48 SAR images acquired by the COSMO-SkyMed (CSK) sensors from December 2013 to March 2016, coherent point targets as long as land subsidence velocity maps and time series are identified by using the Small Baseline Subset (SBAS) algorithm. With the DInSAR constrained land subsidence model, we predict the land subsidence trend and the expected cumulative subsidence in 2020, 2025 and 2030. Meanwhile, we used altimetrydata and densely distributed in the coastal region are identified (EEMD) algorithm to obtain the average sea level rise rate in the East China Sea. With the land subsidence predictions, sea level rise predictions, and high-precision digital elevation model (DEM), we analyze the combined risk of land subsidence and sea level rise on the coastal areas of Shanghai. The potential inundated areas are mapped under different scenarios.

  19. Method of Monitoring Urban Area Deformation Based on Differential TomoSAR

    Directory of Open Access Journals (Sweden)

    WANG Aichun

    2016-12-01

    Full Text Available While the use of differential TomoSAR based on compressive sensing (CS makes it possible to solve the layover problem and reconstruct the deformation information of an observed urban area scene acquired by moderate-high resolution SAR satellite, the performance of the reconstruction decreases for a sparse and structural observed scene due to ignoring the structural characteristics of the observed scene. To deal with this issue, the method for differential SAR tomography based on Khatri-Rao subspace and block compressive sensing (KRS-BCS is proposed. The proposed method changes the reconstruction of the sparse and structural observed scene into a BCS problem under Khatri-Rao subspace, using the structure information of the observed scene and Khatri-Rao product property of the reconstructed observation matrix for differential TomoSAR, such that the KRS-BCS problem is efficiently solved with a block sparse l1/l2 norm optimization signal model, and the performance of resolution capability and reconstruction estimation is compared and analyzed qualitatively and quantitatively by the theoretical analysis and the simulation experiments, all of the results show the propose KRS-BCS method practicably overcomes the problems of CS method, as well as, quite maintains the high resolution characteristics, effectively reduces the probability of false scattering target and greatly improves the reconstruction accurate of scattering point. Finally, the application is taking the urban area of the Mobara(in Chiba, Japan as the test area and using 34 ENVISAT-ASAR images, the accuracy is verifying with the reference deformations derived from first level point data and GPS tracking data, the results show the trend is consistent and the overall deviation is small between reconstruction deformations of the propose KRS-BCS method and the reference deformations, and the accuracy is high in the estimation of the urban area deformation.

  20. NASA's NI-SAR Observing Strategy and Data Availability for Agricultural Monitoring and Assessment

    Science.gov (United States)

    Siqueira, P.; Dubayah, R.; Kellndorfer, J. M.; Saatchi, S. S.; Chapman, B. D.

    2014-12-01

    The monitoring and characterization of global crop development by remote sensing is a complex task, in part, because of the time varying nature of the target and the diversity of crop types and agricultural practices that vary worldwide. While some of these difficulties are overcome with the availability of national and market-derived resources (e.g. publication of crop statistics by the USDA and FAO), monitoring by remote sensing has the ability of augmenting those resources to better identify changes over time, and to provide timely assessments for the current year's production. Of the remote sensing techniques that are used for agricultural applications, optical observations of NDVI from Landsat, AVHRR, MODIS and similar sensors have historically provided the majority of data that is used by the community. In addition, radiometer and radar sensors, are often used for estimating soil moisture and structural information for these agricultural regions. The combination of these remote sensing datasets and national resources constitutes the state of the art for crop monitoring and yield forecasts. To help improve these crop monitoring efforts in the future, the joint NASA-ISRO SAR mission known as NI-SAR is being planned for launch in 2020, and will have L- and S-band fully polarimetric radar systems, a fourteen day repeat period, and a swath width on the order of several hundred kilometers. To address the needs of the science and applications communities that NI-SAR will support, the systems observing strategy is currently being planned such that data rate and the system configuration will address the needs of the community. In this presentation, a description of the NI-SAR system will be given along with the currently planned observing strategy and derived products that will be relevant to the overall GEOGLAM initiative.

  1. Speckle Filtering of GF-3 Polarimetric SAR Data with Joint Restriction Principle.

    Science.gov (United States)

    Xie, Jinwei; Li, Zhenfang; Zhou, Chaowei; Fang, Yuyuan; Zhang, Qingjun

    2018-05-12

    Polarimetric SAR (PolSAR) scattering characteristics of imagery are always obtained from the second order moments estimation of multi-polarization data, that is, the estimation of covariance or coherency matrices. Due to the extra-paths that signal reflected from separate scatterers within the resolution cell has to travel, speckle noise always exists in SAR images and has a severe impact on the scattering performance, especially on single look complex images. In order to achieve high accuracy in estimating covariance or coherency matrices, three aspects are taken into consideration: (1) the edges and texture of the scene are distinct after speckle filtering; (2) the statistical characteristic should be similar to the object pixel; and (3) the polarimetric scattering signature should be preserved, in addition to speckle reduction. In this paper, a joint restriction principle is proposed to meet the requirement. Three different restriction principles are introduced to the processing of speckle filtering. First, a new template, which is more suitable for the point or line targets, is designed to ensure the morphological consistency. Then, the extent sigma filter is used to restrict the pixels in the template aforementioned to have an identical statistic characteristic. At last, a polarimetric similarity factor is applied to the same pixels above, to guarantee the similar polarimetric features amongst the optional pixels. This processing procedure is named as speckle filtering with joint restriction principle and the approach is applied to GF-3 polarimetric SAR data acquired in San Francisco, CA, USA. Its effectiveness of keeping the image sharpness and preserving the scattering mechanism as well as speckle reduction is validated by the comparison with boxcar filters and refined Lee filter.

  2. Advanced Differential Radar Interferometry (A-DInSAR) as integrative tool for a structural geological analysis

    Science.gov (United States)

    Crippa, B.; Calcagni, L.; Rossi, G.; Sternai, P.

    2009-04-01

    Advanced Differential SAR interferometry (A-DInSAR) is a technique monitoring large-coverage surface deformations using a stack of interferograms generated from several complex SLC SAR images, acquired over the same target area at different times. In this work are described the results of a procedure to calculate terrain motion velocity on highly correlated pixels (E. Biescas, M. Crosetto, M. Agudo, O. Monserrat e B. Crippa: Two Radar Interferometric Approaches to Monitor Slow and Fast Land Deformation, 2007) in two area Gemona - Friuli, Northern Italy, Pollino - Calabria, Southern Italy, and, furthermore, are presented some consideration, based on successful examples of the present analysis. The choice of these pixels whose displacement velocity is calculated depends on the dispersion index value (DA) or using coherence values along the stack interferograms. A-DInSAR technique allows to obtain highly reliable velocity values of the vertical displacement. These values concern the movement of minimum surfaces of about 80m2 at the maximum resolution and the minimum velocity that can be recognized is of the order of mm/y. Because of the high versatility of the technology, because of the large dimensions of the area that can be analyzed (of about 10000Km2) and because of the high precision and reliability of the results obtained, we think it is possible to exploit radar interferometry to obtain some important information about the structural context of the studied area, otherwise very difficult to recognize. Therefore we propose radar interferometry as a valid investigation tool whose results must be considered as an important integration of the data collected in fieldworks.

  3. Building damage assessment from PolSAR data using texture parameters of statistical model

    Science.gov (United States)

    Li, Linlin; Liu, Xiuguo; Chen, Qihao; Yang, Shuai

    2018-04-01

    Accurate building damage assessment is essential in providing decision support for disaster relief and reconstruction. Polarimetric synthetic aperture radar (PolSAR) has become one of the most effective means of building damage assessment, due to its all-day/all-weather ability and richer backscatter information of targets. However, intact buildings that are not parallel to the SAR flight pass (termed oriented buildings) and collapsed buildings share similar scattering mechanisms, both of which are dominated by volume scattering. This characteristic always leads to misjudgments between assessments of collapsed buildings and oriented buildings from PolSAR data. Because the collapsed buildings and the intact buildings (whether oriented or parallel buildings) have different textures, a novel building damage assessment method is proposed in this study to address this problem by introducing texture parameters of statistical models. First, the logarithms of the estimated texture parameters of different statistical models are taken as a new texture feature to describe the collapse of the buildings. Second, the collapsed buildings and intact buildings are distinguished using an appropriate threshold. Then, the building blocks are classified into three levels based on the building block collapse rate. Moreover, this paper also discusses the capability for performing damage assessment using texture parameters from different statistical models or using different estimators. The RADARSAT-2 and ALOS-1 PolSAR images are used to present and analyze the performance of the proposed method. The results show that using the texture parameters avoids the problem of confusing collapsed and oriented buildings and improves the assessment accuracy. The results assessed by using the K/G0 distribution texture parameters estimated based on the second moment obtain the highest extraction accuracies. For the RADARSAT-2 and ALOS-1 data, the overall accuracy (OA) for these three types of

  4. Ground Subsidence over Beijing-Tianjin-Hebei Region during Three Periods of 1992 to 2014 Monitored by Interferometric SAR

    Directory of Open Access Journals (Sweden)

    ZHANG Yonghong

    2016-09-01

    Full Text Available The Beijing-Tianjin-Hebei region suffers the most serious ground subsidence in China, which has caused huge economic losses every year. Therefore, ground subsidence was listed as an important mission in the project of geographic conditions monitoring over Beijing-Tianjin-Hebei launched by the National Administration of Surveying, Mapping and Geoinformation in 2013. In this paper, we propose a methodology of ground subsidence monitoring over wide area, which is entitled "multiple master-image coherent target small-baseline interferometric SAR (MCTSB-InSAR". MCTSB-InSAR is an improved time series InSAR technique with some unique features. SAR datasets used for ground subsidence monitoring over the Beijing-Tianjin-Hebei region include ERS-1/2 SAR images acquired between 1992 to 2000, ENVISAT ASAR images acquired between 2003 to 2010 and RADARSAT-2 images acquired between 2012 to 2014. This research represents a first ever effort on mapping ground subsidence over Beijing-Tianjin-Hebei region and over such as a long time span in China. In comparison with more than 120 leveling measurements collected in Beijing and Tianjin, the derived subsidence velocity has the accuracy of 8.7mm/year (1992—2000, 4.7mm/year (2003—2010, and 5.4mm/year (2012—2014 respectively. The spatial-temporal characteristics of the development of ground subsidence in Beijing and Tianjin are analyzed. In general, ground subsidence in Beijing kept continuously expanding in the period of 1992 to 2014. While, ground subsidence in Tianjin had already been serious in 1990s, had dramatically expanded during 2000s, and started to alleviate in recent years. The monitoring result is of high significance for prevention and mitigation of ground subsidence disaster, for making development plan, for efficient and effective utilization of water resource, and for adjustment of economic framework of this region. The result also indicates the effectiveness and reliability of the MCTSB-InSAR

  5. Using PS-InSAR data in landslide hazard management: the case of Veneto Region (NE Italy)

    Science.gov (United States)

    Floris, Mario; Viganò, Alessandro; Busnardo, Enrico; Arziliero, Luciano; Zanette, Doriano

    2013-04-01

    The Project Persistent Scatterers Interferometry, performed by the Italian Ministry of Environment and Territory of the Sea (METS) in the framework of the Extraordinary Plan of Environmental Remote Sensing, has made available a high quantity of data useful for local Authorities (Regions, Provinces, and Municipalities) in the management of the main geological hazards, such as landslides, subsidence, and sinkholes. The main output of the Project consists of ground displacements and velocities measured at target points over the entire Italian territory by using PS-InSAR processing technique applied to SAR data acquired by satellites ESA (European Space Agency) ERS-1 and ERS-2 (Earth Resources Satellite) and ENVISAT (Environmental Satellite) in the period 1992-2010. Description and results of the Project are available for public browsing at the geoportal of the METS (http://www.pcn.minambiente.it). On the basis of PS-InSAR data, several studies have been recently performed for the identification and characterization of landslides both at small and large scale. These studies led to a more precise delimitation of instable areas and to a better evaluation of the state of activity of mass movements. But, as now well known, interferometry techniques can't be applied to the whole territory due to geometric distortions in SAR data acquisition and to ground conditions. In this work we analyze the potentiality of PS-InSAR data from the Project Persistent Scatterers Interferometry in landslide hazard management of the Veneto Region, located in the north-eastern part of Italy. A synthetic description on the main features of landslides affecting the Region is reported, then the percentage of instabilities where PS-InSAR data can be used, is calculated. At the scale of the entire Region we suggest to follow the method proposed in the scientific literature to evaluate the state of activity of landslides on the basis of the measured velocities at the ground surface, while at local

  6. PolSAR Land Cover Classification Based on Roll-Invariant and Selected Hidden Polarimetric Features in the Rotation Domain

    Directory of Open Access Journals (Sweden)

    Chensong Tao

    2017-07-01

    Full Text Available Land cover classification is an important application for polarimetric synthetic aperture radar (PolSAR. Target polarimetric response is strongly dependent on its orientation. Backscattering responses of the same target with different orientations to the SAR flight path may be quite different. This target orientation diversity effect hinders PolSAR image understanding and interpretation. Roll-invariant polarimetric features such as entropy, anisotropy, mean alpha angle, and total scattering power are independent of the target orientation and are commonly adopted for PolSAR image classification. On the other aspect, target orientation diversity also contains rich information which may not be sensed by roll-invariant polarimetric features. In this vein, only using the roll-invariant polarimetric features may limit the final classification accuracy. To address this problem, this work uses the recently reported uniform polarimetric matrix rotation theory and a visualization and characterization tool of polarimetric coherence pattern to investigate hidden polarimetric features in the rotation domain along the radar line of sight. Then, a feature selection scheme is established and a set of hidden polarimetric features are selected in the rotation domain. Finally, a classification method is developed using the complementary information between roll-invariant and selected hidden polarimetric features with a support vector machine (SVM/decision tree (DT classifier. Comparison experiments are carried out with NASA/JPL AIRSAR and multi-temporal UAVSAR data. For AIRSAR data, the overall classification accuracy of the proposed classification method is 95.37% (with SVM/96.38% (with DT, while that of the conventional classification method is 93.87% (with SVM/94.12% (with DT, respectively. Meanwhile, for multi-temporal UAVSAR data, the mean overall classification accuracy of the proposed method is up to 97.47% (with SVM/99.39% (with DT, which is also higher

  7. SAR Study of Mobile Phones as a function of Antenna Q

    DEFF Research Database (Denmark)

    Bahramzy, Pevand; Svendsen, Simon; Jagielski, Ole

    2015-01-01

    density associated with high-Q antennas. The higher energy stored in the electric and magnetic near-field components can result in higher SAR. Hence, SAR study of high-Q antennas is necessary which, if not addressed, might not comply with the SAR safety guidelines. In this paper, SAR as a function...

  8. Spacial Variation in SAR Images of Different Resolution for Agricultural Fields

    DEFF Research Database (Denmark)

    Sandholt, Inge; Skriver, Henning

    1999-01-01

    The spatial variation in two types of Synthetic Aperture Radar (SAR) images covering agricultural fields is analysed. C-band polarimetric SAR data from the Danish airborne SAR, EMISAR, have been compared to space based ERS-1 C-band SAR with respect to scale and effect of polarization. The general...

  9. A Novel Fusion-Based Ship Detection Method from Pol-SAR Images

    Directory of Open Access Journals (Sweden)

    Wenguang Wang

    2015-09-01

    Full Text Available A novel fusion-based ship detection method from polarimetric Synthetic Aperture Radar (Pol-SAR images is proposed in this paper. After feature extraction and constant false alarm rate (CFAR detection, the detection results of HH channel, diplane scattering by Pauli decomposition and helical factor by Barnes decomposition are fused together. The confirmed targets and potential target pixels can be obtained after the fusion process. Using the difference degree of the target, potential target pixels can be classified. The fusion-based ship detection method works accurately by utilizing three different features comprehensively. The result of applying the technique to measured Airborne Synthetic Radar (AIRSAR data shows that the novel detection method can achieve better performance in both ship’s detection and ship’s shape preservation compared to the result of K-means clustering method and the Notch Filter method.

  10. SAR-based change detection using hypothesis testing and Markov random field modelling

    Science.gov (United States)

    Cao, W.; Martinis, S.

    2015-04-01

    The objective of this study is to automatically detect changed areas caused by natural disasters from bi-temporal co-registered and calibrated TerraSAR-X data. The technique in this paper consists of two steps: Firstly, an automatic coarse detection step is applied based on a statistical hypothesis test for initializing the classification. The original analytical formula as proposed in the constant false alarm rate (CFAR) edge detector is reviewed and rewritten in a compact form of the incomplete beta function, which is a builtin routine in commercial scientific software such as MATLAB and IDL. Secondly, a post-classification step is introduced to optimize the noisy classification result in the previous step. Generally, an optimization problem can be formulated as a Markov random field (MRF) on which the quality of a classification is measured by an energy function. The optimal classification based on the MRF is related to the lowest energy value. Previous studies provide methods for the optimization problem using MRFs, such as the iterated conditional modes (ICM) algorithm. Recently, a novel algorithm was presented based on graph-cut theory. This method transforms a MRF to an equivalent graph and solves the optimization problem by a max-flow/min-cut algorithm on the graph. In this study this graph-cut algorithm is applied iteratively to improve the coarse classification. At each iteration the parameters of the energy function for the current classification are set by the logarithmic probability density function (PDF). The relevant parameters are estimated by the method of logarithmic cumulants (MoLC). Experiments are performed using two flood events in Germany and Australia in 2011 and a forest fire on La Palma in 2009 using pre- and post-event TerraSAR-X data. The results show convincing coarse classifications and considerable improvement by the graph-cut post-classification step.

  11. RESEARCH ON AIRBORNE SAR IMAGING BASED ON ESC ALGORITHM

    Directory of Open Access Journals (Sweden)

    X. T. Dong

    2017-09-01

    Full Text Available Due to the ability of flexible, accurate, and fast obtaining abundant information, airborne SAR is significant in the field of Earth Observation and many other applications. Optimally the flight paths are straight lines, but in reality it is not the case since some portion of deviation from the ideal path is impossible to avoid. A small disturbance from the ideal line will have a major effect on the signal phase, dramatically deteriorating the quality of SAR images and data. Therefore, to get accurate echo information and radar images, it is essential to measure and compensate for nonlinear motion of antenna trajectories. By means of compensating each flying trajectory to its reference track, MOCO method corrects linear phase error and quadratic phase error caused by nonlinear antenna trajectories. Position and Orientation System (POS data is applied to acquiring accuracy motion attitudes and spatial positions of antenna phase centre (APC. In this paper, extend chirp scaling algorithm (ECS is used to deal with echo data of airborne SAR. An experiment is done using VV-Polarization raw data of C-band airborne SAR. The quality evaluations of compensated SAR images and uncompensated SAR images are done in the experiment. The former always performs better than the latter. After MOCO processing, azimuth ambiguity is declined, peak side lobe ratio (PSLR effectively improves and the resolution of images is improved obviously. The result shows the validity and operability of the imaging process for airborne SAR.

  12. Research on Airborne SAR Imaging Based on Esc Algorithm

    Science.gov (United States)

    Dong, X. T.; Yue, X. J.; Zhao, Y. H.; Han, C. M.

    2017-09-01

    Due to the ability of flexible, accurate, and fast obtaining abundant information, airborne SAR is significant in the field of Earth Observation and many other applications. Optimally the flight paths are straight lines, but in reality it is not the case since some portion of deviation from the ideal path is impossible to avoid. A small disturbance from the ideal line will have a major effect on the signal phase, dramatically deteriorating the quality of SAR images and data. Therefore, to get accurate echo information and radar images, it is essential to measure and compensate for nonlinear motion of antenna trajectories. By means of compensating each flying trajectory to its reference track, MOCO method corrects linear phase error and quadratic phase error caused by nonlinear antenna trajectories. Position and Orientation System (POS) data is applied to acquiring accuracy motion attitudes and spatial positions of antenna phase centre (APC). In this paper, extend chirp scaling algorithm (ECS) is used to deal with echo data of airborne SAR. An experiment is done using VV-Polarization raw data of C-band airborne SAR. The quality evaluations of compensated SAR images and uncompensated SAR images are done in the experiment. The former always performs better than the latter. After MOCO processing, azimuth ambiguity is declined, peak side lobe ratio (PSLR) effectively improves and the resolution of images is improved obviously. The result shows the validity and operability of the imaging process for airborne SAR.

  13. The experience of SARS-related stigma at Amoy Gardens.

    Science.gov (United States)

    Lee, Sing; Chan, Lydia Y Y; Chau, Annie M Y; Kwok, Kathleen P S; Kleinman, Arthur

    2005-11-01

    Severe Acute Respiratory Syndrome (SARS) possesses characteristics that render it particularly prone to stigmatization. SARS-related stigma, despite its salience for public health and stigma research, has had little examination. This study combines survey and case study methods to examine subjective stigma among residents of Amoy Gardens (AG), the first officially recognized site of community outbreak of SARS in Hong Kong. A total of 903 residents of AG completed a self-report questionnaire derived from two focus groups conducted toward the end of the 3-month outbreak. Case studies of two residents who lived in Block E, the heart of the SARS epidemic at AG, complement the survey data. Findings show that stigma affected most residents and took various forms of being shunned, insulted, marginalized, and rejected in the domains of work, interpersonal relationships, use of services and schooling. Stigma was also associated with psychosomatic distress. Residents' strategies for diminishing stigma varied with gender, age, education, occupation, and proximity to perceived risk factors for SARS such as residential location, previous SARS infection and the presence of ex-SARS household members. Residents attributed stigma to government mismanagement, contagiousness of the mysterious SARS virus, and alarmist media reporting. Stigma clearly decreased, but never completely disappeared, after the outbreak. The findings confirm and add to existing knowledge on the varied origins, correlates, and impacts of stigma. They also highlight the synergistic roles of inconsistent health policy responses and risk miscommunication by the media in rapidly amplifying stigma toward an unfamiliar illness. While recognizing the intrinsically stigmatizing nature of public health measures to control SARS, we recommend that a consistent inter-sectoral approach is needed to minimize stigma and to make an effective health response to future outbreaks.

  14. FlexSAR, a high quality, flexible, cost effective, prototype SAR system

    Science.gov (United States)

    Jensen, Mark; Knight, Chad; Haslem, Brent

    2016-05-01

    The FlexSAR radar system was designed to be a high quality, low-cost, flexible research prototype instrument. Radar researchers and practitioners often desire the ability to prototype new or advanced configurations, yet the ability to enhance or upgrade existing radar systems can be cost prohibitive. FlexSAR answers the need for a flexible radar system that can be extended easily, with minimal cost and time expenditures. The design approach focuses on reducing the resources required for developing and validating new advanced radar modalities. Such an approach fosters innovation and provides risk reduction since actual radar data can be collected in the appropriate mode, processed, and analyzed early in the development process. This allows for an accurate, detailed understanding of the corresponding trade space. This paper is a follow-on to last years paper and discusses the advancements that have been made to the FlexSAR system. The overall system architecture is discussed and presented along with several examples illustrating the system utility.

  15. SARS in Singapore: surveillance strategies in a globalising city.

    Science.gov (United States)

    Teo, Peggy; Yeoh, Brenda S A; Ong, Shir Nee

    2005-06-01

    Public health measures employed to fight against the spread of SARS need to be guided by biomedical knowledge as well as an understanding of the social science aspects of the disease. Using Singapore as a case study, we explore how the state constructs the disease and implements measures targeted at creating a ring of defense around the island and using surveillance to monitor and prevent its spread. While there is support, there is also resentment among some Singaporeans who complain that their right to privacy has been invaded and that over surveillance may have actually occurred. Marginalisation and discrimination have not only affected the local population but in this open economy which is striving to achieve global city status, businesses, tourism, foreign talent, foreign contract workers and foreign students studying in Singapore have also been negatively affected. While Singapore has been applauded by WHO and used as an example of quick and effective response, a holistic approach to the management of infectious disease must address the social implications of strategies that are drawn from medical knowledge alone because it impinges on the social lives of people and how people interact with each other under stressful circumstances.

  16. Alaska Synthetic Aperture Radar (SAR) Facility science data processing architecture

    Science.gov (United States)

    Hilland, Jeffrey E.; Bicknell, Thomas; Miller, Carol L.

    1991-01-01

    The paper describes the architecture of the Alaska SAR Facility (ASF) at Fairbanks, being developed to generate science data products for supporting research in sea ice motion, ice classification, sea-ice-ocean interaction, glacier behavior, ocean waves, and hydrological and geological study areas. Special attention is given to the individual substructures of the ASF: the Receiving Ground Station (RGS), the SAR Processor System, and the Interactive Image Analysis System. The SAR data will be linked to the RGS by the ESA ERS-1 and ERS-2, the Japanese ERS-1, and the Canadian Radarsat.

  17. SAR antenna design for ambiguity and multipath suppression

    DEFF Research Database (Denmark)

    Christensen, Erik Lintz; Dich, Mikael

    1993-01-01

    A high resolution airborne synthetic aperture radar (SAR) has been developed at the Electromagnetics Institute (EMI) for remote sensing applications. The paper considers the radiation of antennas for a SAR system from a systems perspective. The basic specifications of an idealised antenna...... are obtained from the required swath and the azimuth footprint needed for the SAR processing. The radiation from a real antenna causes unwanted signal returns that lead to intensity variations (multipath) and ghost echoes (ambiguity). Additional specifications are deduced by considering these signals...

  18. SAR image effects on coherence and coherence estimation.

    Energy Technology Data Exchange (ETDEWEB)

    Bickel, Douglas Lloyd

    2014-01-01

    Radar coherence is an important concept for imaging radar systems such as synthetic aperture radar (SAR). This document quantifies some of the effects in SAR which modify the coherence. Although these effects can disrupt the coherence within a single SAR image, this report will focus on the coherence between separate images, such as for coherent change detection (CCD) processing. There have been other presentations on aspects of this material in the past. The intent of this report is to bring various issues that affect the coherence together in a single report to support radar engineers in making decisions about these matters.

  19. Program Merges SAR Data on Terrain and Vegetation Heights

    Science.gov (United States)

    Siqueira, Paul; Hensley, Scott; Rodriguez, Ernesto; Simard, Marc

    2007-01-01

    X/P Merge is a computer program that estimates ground-surface elevations and vegetation heights from multiple sets of data acquired by the GeoSAR instrument [a terrain-mapping synthetic-aperture radar (SAR) system that operates in the X and bands]. X/P Merge software combines data from X- and P-band digital elevation models, SAR backscatter magnitudes, and interferometric correlation magnitudes into a simplified set of output topographical maps of ground-surface elevation and tree height.

  20. Mapping and monitoring renewable resources with space SAR

    Science.gov (United States)

    Ulaby, F. T.; Brisco, B.; Dobson, M. C.; Moezzi, S.

    1983-01-01

    The SEASAT-A SAR and SIR-A imagery was examined to evaluate the quality and type of information that can be extracted and used to monitor renewable resources on Earth. Two tasks were carried out: (1) a land cover classification study which utilized two sets of imagery acquired by the SEASAT-A SAR, one set by SIR-A, and one LANDSAT set (4 bands); and (2) a change detection to examine differences between pairs of SEASAT-A SAR images and relates them to hydrologic and/or agronomic variations in the scene.

  1. Wind mapping offshore in coastal Mediterranean area using SAR images

    DEFF Research Database (Denmark)

    Calaudi, Rosamaria; Arena, Felice; Badger, Merete

    Satellite observations of the ocean surface from Synthetic Aperture Radars (SAR) provide information about the spatial wind variability over large areas. This is of special interest in the Mediterranean, where spatial wind information is only provided by sparse buoys, often with long periods...... of missing data. Here, we focus on evaluating the use of SAR for offshore wind mapping. Preliminary results from the analysis of SAR-based ocean winds in Mediterranean areas show interesting large scale wind flow features consistent with results from previous studies using numerical models and space borne...

  2. Segment-based change detection for polarimetric SAR data

    DEFF Research Database (Denmark)

    Skriver, Henning; Nielsen, Allan Aasbjerg; Conradsen, Knut

    2006-01-01

    that is needed compared to single polarisation SAR to provide reliable and robust detection of changes. Polarimetric SAR data will be available from satellites in the near future, e.g. the Japanese ALOS, the Canadian Radarsat-2 and the German TerraSAR-X. An appropriate way of representing multi-look fully...... be split into a number of smaller fields, a building may be removed from or added to some area, hedgerows may be removed/added or other type of vegetated areas may be partly removed or added. In this case, ambiguities may arise when segments have changed shape and extent from one image to another...

  3. LTE modem power consumption, SAR and RF signal strength emulation

    DEFF Research Database (Denmark)

    Musiige, Deogratius; Vincent, Laulagnet; Anton, François

    2012-01-01

    This paper presents a new methodology for emulating the LTE modem power consumption, emitted SAR and RF signal strength when transmitting an LTE signal. The inputs of the methodology are: modem logical/protocol commands, time advance, near-field specifier, and antenna characteristics. The power...... emulation model(s) are computed by a two layer 451 neural network based on physical power measurements. SAR is emulated by polynomial interpolation models based on FDTD simulations. The accuracies of the mathematical function approximations for the emulation models of power and SAR are 5.19% and 3...

  4. From genome to antivirals: SARS as a test tube.

    Science.gov (United States)

    Kliger, Yossef; Levanon, Erez Y; Gerber, Doron

    2005-03-01

    The severe acute respiratory syndrome (SARS) epidemic brought into the spotlight the need for rapid development of effective anti-viral drugs against newly emerging viruses. Researchers have leveraged the 20-year battle against AIDS into a variety of possible treatments for SARS. Most prominently, based solely on viral genome information, silencers of viral genes, viral-enzyme blockers and viral-entry inhibitors were suggested as potential therapeutic agents for SARS. In particular, inhibitors of viral entry, comprising therapeutic peptides, were based on the recently launched anti-HIV drug enfuvirtide. This could represent one of the most direct routes from genome sequencing to the discovery of antiviral drugs.

  5. The lessons of SARS in Hong Kong.

    Science.gov (United States)

    Lai, Thomas Sik To; Yu, Wai Cho

    2010-02-01

    Severe acute respiratory syndrome (SARS) is a novel coronavirus infection which broke out in Hong Kong in March 2003. Princess Margaret Hospital was designated to manage this new, mysterious and serious disease. Healthcare workers had to work under extremely stressful and often risky conditions to care for patients. Despite manpower and equipment reinforcements, staff infection occurred as a result of bodily exhaustion, working in an unfamiliar environment and lapses in infection control. Patients suffered even more, not only due to physical discomfort, but also because of the fear of isolation and death away from family and friends. Health authorities learnt their lessons in the outbreak and formulated emergency plans for future infectious disease epidemics. The healthcare infrastructure has been examined and upgraded with regard to intensive care capacity, infection control measures, professional training, manpower deployment, staff facilities, and stockpiling of drugs and personal protective equipment.

  6. Culture, attribution and automaticity: a social cognitive neuroscience view.

    Science.gov (United States)

    Mason, Malia F; Morris, Michael W

    2010-06-01

    A fundamental challenge facing social perceivers is identifying the cause underlying other people's behavior. Evidence indicates that East Asian perceivers are more likely than Western perceivers to reference the social context when attributing a cause to a target person's actions. One outstanding question is whether this reflects a culture's influence on automatic or on controlled components of causal attribution. After reviewing behavioral evidence that culture can shape automatic mental processes as well as controlled reasoning, we discuss the evidence in favor of cultural differences in automatic and controlled components of causal attribution more specifically. We contend that insights emerging from social cognitive neuroscience research can inform this debate. After introducing an attribution framework popular among social neuroscientists, we consider findings relevant to the automaticity of attribution, before speculating how one could use a social neuroscience approach to clarify whether culture affects automatic, controlled or both types of attribution processes.

  7. Ship Detection in Gaofen-3 SAR Images Based on Sea Clutter Distribution Analysis and Deep Convolutional Neural Network.

    Science.gov (United States)

    An, Quanzhi; Pan, Zongxu; You, Hongjian

    2018-01-24

    Target detection is one of the important applications in the field of remote sensing. The Gaofen-3 (GF-3) Synthetic Aperture Radar (SAR) satellite launched by China is a powerful tool for maritime monitoring. This work aims at detecting ships in GF-3 SAR images using a new land masking strategy, the appropriate model for sea clutter and a neural network as the discrimination scheme. Firstly, the fully convolutional network (FCN) is applied to separate the sea from the land. Then, by analyzing the sea clutter distribution in GF-3 SAR images, we choose the probability distribution model of Constant False Alarm Rate (CFAR) detector from K-distribution, Gamma distribution and Rayleigh distribution based on a tradeoff between the sea clutter modeling accuracy and the computational complexity. Furthermore, in order to better implement CFAR detection, we also use truncated statistic (TS) as a preprocessing scheme and iterative censoring scheme (ICS) for boosting the performance of detector. Finally, we employ a neural network to re-examine the results as the discrimination stage. Experiment results on three GF-3 SAR images verify the effectiveness and efficiency of this approach.

  8. [Epidemiological perspectives on SARS and avian influenza].

    Science.gov (United States)

    del Rey Calero, Juan

    2004-01-01

    SARS is a respiratory infection caused by Coronavirus (Nidoviruses, RNA) from which 3 groups are known. Group 1 affects dogs, cats, pigs, and the human agent is 229 E. Group 2 affects bovines or rodents, and the human agent is OC43. And group 3 corresponds to the avian pathology.... The epidemics emerged on February 2003 in Guangdong, South China, due to consumption of exotic animals (Civeta, etc.), and it spread through interperson contagion to other regions in Asia, America and Europe. Incubation period is about 2-7 days. Transmission Of the virus is person-to person, but also by excretions and residual water. Basic reproductive rate is 2 to 4, and it is considered that 2.7 persons are infected from the initial case. In June 2003, SARS affected over 8,000 people and 774 were killed. Mortality approaches to 10%, and it is higher among older people rising up to 50% in those aged over 65 years. It is important to quickly establish action protocols regarding clinical, epidemiological and prevention aspects. Avian influenza is an infection caused by type A Influenza Orthomixovirus, in which migration birds and wild ducks are the main reservoir. Avian viruses correspond to H5, H7, H9. In 1997 it was observed that type AH5N1 jumped interspecies barrier and affected 18 humans, and 6 of them died. At the end of 2003 and in 2004 this type of poultry flu was described in Asia. FAO has emphasized that sacrifice of chicken in affected farms is the most effective measure to fight against the disease. It has also been established suppression of imports from these countries. There is no evidence on interperson contagion from chicken contagion, nor on food-borne contagion to humans.

  9. Radionuclide release calculations for SAR-08

    International Nuclear Information System (INIS)

    Thomson, Gavin; Miller, Alex; Smith, Graham; Jackson, Duncan

    2008-04-01

    Following a review by the Swedish regulatory authorities of the post-closure safety assessment of the SFR 1 disposal facility for low and intermediate waste (L/ILW), SAFE, the SKB has prepared an updated assessment called SAR-08. This report describes the radionuclide release calculations that have been undertaken as part of SAR-08. The information, assumptions and data used in the calculations are reported and the results are presented. The calculations address issues raised in the regulatory review, but also take account of new information including revised inventory data. The scenarios considered include the main case of expected behaviour of the system, with variants; low probability releases, and so-called residual scenarios. Apart from these scenario uncertainties, data uncertainties have been examined using a probabilistic approach. Calculations have been made using the AMBER software. This allows all the component features of the assessment model to be included in one place. AMBER has been previously used to reproduce results the corresponding calculations in the SAFE assessment. It is also used in demonstration of the IAEA's near surface disposal assessment methodology ISAM and has been subject to very substantial verification tests and has been used in verifying other assessment codes. Results are presented as a function of time for the release of radionuclides from the near field, and then from the far field into the biosphere. Radiological impacts of the releases are reported elsewhere. Consideration is given to each radionuclide and to each component part of the repository. The releases from the entire repository are also presented. The peak releases rates are, for most scenarios, due to organic C-14. Other radionuclides which contribute to peak release rates include inorganic C-14, Ni-59 and Ni-63. (author)

  10. Radionuclide release calculations for SAR-08

    Energy Technology Data Exchange (ETDEWEB)

    Thomson, Gavin; Miller, Alex; Smith, Graham; Jackson, Duncan (Enviros Consulting Ltd, Wolverhampton (United Kingdom))

    2008-04-15

    Following a review by the Swedish regulatory authorities of the post-closure safety assessment of the SFR 1 disposal facility for low and intermediate waste (L/ILW), SAFE, the SKB has prepared an updated assessment called SAR-08. This report describes the radionuclide release calculations that have been undertaken as part of SAR-08. The information, assumptions and data used in the calculations are reported and the results are presented. The calculations address issues raised in the regulatory review, but also take account of new information including revised inventory data. The scenarios considered include the main case of expected behaviour of the system, with variants; low probability releases, and so-called residual scenarios. Apart from these scenario uncertainties, data uncertainties have been examined using a probabilistic approach. Calculations have been made using the AMBER software. This allows all the component features of the assessment model to be included in one place. AMBER has been previously used to reproduce results the corresponding calculations in the SAFE assessment. It is also used in demonstration of the IAEA's near surface disposal assessment methodology ISAM and has been subject to very substantial verification tests and has been used in verifying other assessment codes. Results are presented as a function of time for the release of radionuclides from the near field, and then from the far field into the biosphere. Radiological impacts of the releases are reported elsewhere. Consideration is given to each radionuclide and to each component part of the repository. The releases from the entire repository are also presented. The peak releases rates are, for most scenarios, due to organic C-14. Other radionuclides which contribute to peak release rates include inorganic C-14, Ni-59 and Ni-63. (author)

  11. A NEW SAR CLASSIFICATION SCHEME FOR SEDIMENTS ON INTERTIDAL FLATS BASED ON MULTI-FREQUENCY POLARIMETRIC SAR IMAGERY

    Directory of Open Access Journals (Sweden)

    W. Wang

    2017-11-01

    Full Text Available We present a new classification scheme for muddy and sandy sediments on exposed intertidal flats, which is based on synthetic aperture radar (SAR data, and use ALOS-2 (L-band, Radarsat-2 (C-band and TerraSAR-X (X-band fully polarimetric SAR imagery to demonstrate its effectiveness. Four test sites on the German North Sea coast were chosen, which represent typical surface compositions of different sediments, vegetation, and habitats, and of which a large amount of SAR is used for our analyses. Both Freeman-Durden and Cloude-Pottier polarimetric decomposition are utilized, and an additional descriptor called Double-Bounce Eigenvalue Relative Difference (DERD is introduced into the feature sets instead of the original polarimetric intensity channels. The classification is conducted following Random Forest theory, and the results are verified using ground truth data from field campaigns and an existing classification based on optical imagery. In addition, the use of Kennaugh elements for classification purposes is demonstrated using both fully and dual-polarization multi-frequency and multi-temporal SAR data. Our results show that the proposed classification scheme can be applied for the discrimination of muddy and sandy sediments using L-, C-, and X-band SAR images, while SAR imagery acquired at short wavelengths (C- and X-band can also be used to detect more detailed features such as bivalve beds on intertidal flats.

  12. Automatic indexing, compiling and classification

    International Nuclear Information System (INIS)

    Andreewsky, Alexandre; Fluhr, Christian.

    1975-06-01

    A review of the principles of automatic indexing, is followed by a comparison and summing-up of work by the authors and by a Soviet staff from the Moscou INFORM-ELECTRO Institute. The mathematical and linguistic problems of the automatic building of thesaurus and automatic classification are examined [fr

  13. Crustal Deformation Caused by Earthquake Detected by InSAR Technique Using ALOS/PALSAR Data

    Science.gov (United States)

    Miyagi, Y.; Nishimura, Y.; Takahashi, H.; Shimada, M.

    2007-12-01

    earthquakes on 15th November 2006 in Kuril Islands and on 1st April 2007 in Solomon Islands as examples. The former earthquake (M8.3) in Kuril Islands was accompanied by tsunami and several meter of faulting. Simushir Island is situated about 200 km west of the epicenter, and has been observed by the PALSAR before and after the earthquake. Using differential InSAR technique, several fringes are detected and we presume that they show a co-seismic deformation. The latter earthquake (M8.1) in Solomon Islands was accompanied by large tsunami and caused a considerable damage in the area. The PALSAR has been observed these islands before and after the earthquake and detected an extensive co-seismic deformation areally using same technique as above. Then we try to compare these deformation to those induced from a fault model, and they show a good agreement. Compared with the amplitude image before the earthquake, several appearances of land area like uplift are recognized in the amplitude image after the earthquake. We went to the Solomon Islands in the end of July and confirmed the uplift. Additionally, we introduce a recent result of PALSAR data which targets at the M8.1 earthquake occurred in near the coast of central Peru on 15th August 2007. In the interferogram, extensive information of crustal deformation is detected.

  14. Automatization of welding

    International Nuclear Information System (INIS)

    Iwabuchi, Masashi; Tomita, Jinji; Nishihara, Katsunori.

    1978-01-01

    Automatization of welding is one of the effective measures for securing high degree of quality of nuclear power equipment, as well as for correspondence to the environment at the site of plant. As the latest ones of the automatic welders practically used for welding of nuclear power apparatuses in factories of Toshiba and IHI, those for pipes and lining tanks are described here. The pipe welder performs the battering welding on the inside of pipe end as the so-called IGSCC countermeasure and the succeeding butt welding through the same controller. The lining tank welder is able to perform simultaneous welding of two parallel weld lines on a large thin plate lining tank. Both types of the welders are demonstrating excellent performance at the shops as well as at the plant site. (author)

  15. Automatic structural scene digitalization.

    Science.gov (United States)

    Tang, Rui; Wang, Yuhan; Cosker, Darren; Li, Wenbin

    2017-01-01

    In this paper, we present an automatic system for the analysis and labeling of structural scenes, floor plan drawings in Computer-aided Design (CAD) format. The proposed system applies a fusion strategy to detect and recognize various components of CAD floor plans, such as walls, doors, windows and other ambiguous assets. Technically, a general rule-based filter parsing method is fist adopted to extract effective information from the original floor plan. Then, an image-processing based recovery method is employed to correct information extracted in the first step. Our proposed method is fully automatic and real-time. Such analysis system provides high accuracy and is also evaluated on a public website that, on average, archives more than ten thousands effective uses per day and reaches a relatively high satisfaction rate.

  16. Automatic trend estimation

    CERN Document Server

    Vamos¸, C˘alin

    2013-01-01

    Our book introduces a method to evaluate the accuracy of trend estimation algorithms under conditions similar to those encountered in real time series processing. This method is based on Monte Carlo experiments with artificial time series numerically generated by an original algorithm. The second part of the book contains several automatic algorithms for trend estimation and time series partitioning. The source codes of the computer programs implementing these original automatic algorithms are given in the appendix and will be freely available on the web. The book contains clear statement of the conditions and the approximations under which the algorithms work, as well as the proper interpretation of their results. We illustrate the functioning of the analyzed algorithms by processing time series from astrophysics, finance, biophysics, and paleoclimatology. The numerical experiment method extensively used in our book is already in common use in computational and statistical physics.

  17. Three-dimensional Reconstruction Method Study Based on Interferometric Circular SAR

    Directory of Open Access Journals (Sweden)

    Hou Liying

    2016-10-01

    Full Text Available Circular Synthetic Aperture Radar (CSAR can acquire targets’ scattering information in all directions by a 360° observation, but a single-track CSAR cannot efficiently obtain height scattering information for a strong directive scatter. In this study, we examine the typical target of the three-dimensional circular SAR interferometry theoryand validate the theory in a darkroom experiment. We present a 3D reconstruction of the actual tank metal model of interferometric CSAR for the first time, verify the validity of the method, and demonstrate the important potential applications of combining 3D reconstruction with omnidirectional observation.

  18. Inversion Algorithms and PS Detection in SAR Tomography, Case Study of Bucharest City

    Directory of Open Access Journals (Sweden)

    C. Dănişor

    2016-06-01

    Full Text Available Synthetic Aperture Radar (SAR tomography can reconstruct the elevation profile of each pixel based on a set of co-registered complex images of a scene. Its main advantage over classical interferometric methods consists in the capability to improve the detection of single persistent scatterers as well as to enable the detection of multiple scatterers interfering within the same pixel. In this paper, three tomographic algorithms are compared and applied to a dataset of 32 images to generate the elevation map of dominant scatterers from a scene. Targets which present stable proprieties over time - Persistent Scatterers (PS are then detected based on reflectivity functions reconstructed with Capon filtering.

  19. A combined use of multispectral and SAR images for ship detection and characterization through object based image analysis

    Science.gov (United States)

    Aiello, Martina; Gianinetto, Marco

    2017-10-01

    Marine routes represent a huge portion of commercial and human trades, therefore surveillance, security and environmental protection themes are gaining increasing importance. Being able to overcome the limits imposed by terrestrial means of monitoring, ship detection from satellite has recently prompted a renewed interest for a continuous monitoring of illegal activities. This paper describes an automatic Object Based Image Analysis (OBIA) approach to detect vessels made of different materials in various sea environments. The combined use of multispectral and SAR images allows for a regular observation unrestricted by lighting and atmospheric conditions and complementarity in terms of geographic coverage and geometric detail. The method developed adopts a region growing algorithm to segment the image in homogeneous objects, which are then classified through a decision tree algorithm based on spectral and geometrical properties. Then, a spatial analysis retrieves the vessels' position, length and heading parameters and a speed range is associated. Optimization of the image processing chain is performed by selecting image tiles through a statistical index. Vessel candidates are detected over amplitude SAR images using an adaptive threshold Constant False Alarm Rate (CFAR) algorithm prior the object based analysis. Validation is carried out by comparing the retrieved parameters with the information provided by the Automatic Identification System (AIS), when available, or with manual measurement when AIS data are not available. The estimation of length shows R2=0.85 and estimation of heading R2=0.92, computed as the average of R2 values obtained for both optical and radar images.

  20. Automatic food decisions

    DEFF Research Database (Denmark)

    Mueller Loose, Simone

    Consumers' food decisions are to a large extent shaped by automatic processes, which are either internally directed through learned habits and routines or externally influenced by context factors and visual information triggers. Innovative research methods such as eye tracking, choice experiments...... and food diaries allow us to better understand the impact of unconscious processes on consumers' food choices. Simone Mueller Loose will provide an overview of recent research insights into the effects of habit and context on consumers' food choices....

  1. Automatic LOD selection

    OpenAIRE

    Forsman, Isabelle

    2017-01-01

    In this paper a method to automatically generate transition distances for LOD, improving image stability and performance is presented. Three different methods were tested all measuring the change between two level of details using the spatial frequency. The methods were implemented as an optional pre-processing step in order to determine the transition distances from multiple view directions. During run-time both view direction based selection and the furthest distance for each direction was ...

  2. Feature-based RNN target recognition

    Science.gov (United States)

    Bakircioglu, Hakan; Gelenbe, Erol

    1998-09-01

    Detection and recognition of target signatures in sensory data obtained by synthetic aperture radar (SAR), forward- looking infrared, or laser radar, have received considerable attention in the literature. In this paper, we propose a feature based target classification methodology to detect and classify targets in cluttered SAR images, that makes use of selective signature data from sensory data, together with a neural network technique which uses a set of trained networks based on the Random Neural Network (RNN) model (Gelenbe 89, 90, 91, 93) which is trained to act as a matched filter. We propose and investigate radial features of target shapes that are invariant to rotation, translation, and scale, to characterize target and clutter signatures. These features are then used to train a set of learning RNNs which can be used to detect targets within clutter with high accuracy, and to classify the targets or man-made objects from natural clutter. Experimental data from SAR imagery is used to illustrate and validate the proposed method, and to calculate Receiver Operating Characteristics which illustrate the performance of the proposed algorithm.

  3. Change detection in a time series of polarimetric SAR data by an omnibus test statistic and its factorization (Conference Presentation)

    Science.gov (United States)

    Nielsen, Allan A.; Conradsen, Knut; Skriver, Henning

    2016-10-01

    ., Skriver, H., Nielsen, A. A., and Conradsen, K., "CFAR edge detector for polarimetric SAR images," IEEE Transactions on Geoscience and Remote Sensing 41(1): 20-32, 2003. [4] van Zyl, J. J. and Ulaby, F. T., "Scattering matrix representation for simple targets," in Radar Polarimetry for Geoscience Applications, Ulaby, F. T. and Elachi, C., eds., Artech, Norwood, MA (1990). [5] Canty, M. J., Image Analysis, Classification and Change Detection in Remote Sensing,with Algorithms for ENVI/IDL and Python, Taylor & Francis, CRC Press, third revised ed. (2014). [6] Nielsen, A. A., Conradsen, K., and Skriver, H., "Change detection in full and dual polarization, single- and multi-frequency SAR data," IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing 8(8): 4041-4048, 2015. [7] Conradsen, K., Nielsen, A. A., and Skriver, H., "Determining the points of change in time series of polarimetric SAR data," IEEE Transactions on Geoscience and Remote Sensing 54(5), 3007-3024, 2016. [9] Christensen, E. L., Skou, N., Dall, J., Woelders, K., rgensen, J. H. J., Granholm, J., and Madsen, S. N., "EMISAR: An absolutely calibrated polarimetric L- and C-band SAR," IEEE Transactions on Geoscience and Remote Sensing 36: 1852-1865 (1998).

  4. SAR China Land Mapping Project: Development, Production and Potential Applications

    International Nuclear Information System (INIS)

    Zhang, Lu; Guo, Huadong; Liu, Guang; Fu, Wenxue; Yan, Shiyong; Song, Rui; Ji, Peng; Wang, Xinyuan

    2014-01-01

    Large-area, seamless synthetic aperture radar (SAR) mosaics can reflect overall environmental conditions and highlight general trends in observed areas from a macroscopic standpoint, and effectively support research at the global scale, which is in high demand now across scientific fields. The SAR China Land Mapping Project (SCLM), supported by the Digital Earth Science Platform Project initiated and managed by the Center for Earth Observation and Digital Earth, Chinese Academy of Sciences (CEODE), is introduced in this paper. This project produced a large-area SAR mosaic dataset and generated the first complete seamless SAR map covering the entire land area of China using EnviSat-ASAR images. The value of the mosaic map is demonstrated by some potential applications in studies of urban distribution, rivers and lakes, geologic structures, geomorphology and paleoenvironmental change

  5. Vegetation Parameter Extraction Using Dual Baseline Polarimetric SAR Interferometry Data

    Science.gov (United States)

    Zhang, H.; Wang, C.; Chen, X.; Tang, Y.

    2009-04-01

    For vegetation parameter inversion, the single baseline polarimetric SAR interferometry (POLinSAR) technique, such as the three-stage method and the ESPRIT algorithm, is limited by the observed data with the minimum ground to volume amplitude ration, which effects the estimation of the effective phase center for the vegetation canopy or the surface, and thus results in the underestimated vegetation height. In order to remove this effect of the single baseline inversion techniques in some extend, another baseline POLinSAR data is added on vegetation parameter estimation in this paper, and a dual baseline POLinSAR technique for the extraction of the vegetation parameter is investigated and improved to reduce the dynamic bias for the vegetation parameter estimation. Finally, the simulated data and real data are used to validate this dual baseline technique.

  6. Environmental/Noise Effects on VHF/UHF UWB SAR

    National Research Council Canada - National Science Library

    Ralston, James

    1998-01-01

    This paper presents a straightforward approach to estimating the impact of natural environmental noise on an overall system noise temperature for very high frequency/ultrahigh frequency synthetic aperture radar (VHF/UHF SAR...

  7. Eutelsat 2: SAR-10009 nickel-hydrogen battery

    Science.gov (United States)

    Miller, Lee

    1991-01-01

    The topics are presented in viewgraph form and include SAR-10009 design features, specific energy, analyses and testing, redundant structural insulation, electronics, corrosion protection, battery cell life cycle tests, and spacecraft launches.

  8. The economic impact of SARS in Beijing, China.

    Science.gov (United States)

    Beutels, Philippe; Jia, Na; Zhou, Qing-Yi; Smith, Richard; Cao, Wu-Chun; de Vlas, Sake J

    2009-11-01

    To document the impact of the severe acute respiratory syndrome (SARS) outbreak in Beijing on indicators of social and economic activity. Associations between time series of daily and monthly SARS cases and deaths and volume of public train, airplane and cargo transport, tourism, household consumption patterns and gross domestic product growth in Beijing were investigated using the cross-correlation function. Significant correlation coefficients were found for all indicators except wholesale accounts and expenditures on necessities, with the most significant correlations occurring with a delay of 1 day to 1 month. Especially leisure activities, local and international transport and tourism were affected by SARS particularly in May 2003. Much of this consumption was merely postponed; but irrecoverable losses to the tourist sector alone were estimated at about US$ 1.4 bn, or 300 times the cost of treatment for SARS cases in Beijing.

  9. RAMP AMM-1 SAR Image Mosaic of Antarctica

    Data.gov (United States)

    National Aeronautics and Space Administration — In 1997, the Canadian RADARSAT-1 satellite was rotated in orbit so that its Synthetic Aperture Radar (SAR) antenna looked south towards Antarctica. This permitted...

  10. Wavelet Filter Banks for Super-Resolution SAR Imaging

    Science.gov (United States)

    Sheybani, Ehsan O.; Deshpande, Manohar; Memarsadeghi, Nargess

    2011-01-01

    This paper discusses Innovative wavelet-based filter banks designed to enhance the analysis of super resolution Synthetic Aperture Radar (SAR) images using parametric spectral methods and signal classification algorithms, SAR finds applications In many of NASA's earth science fields such as deformation, ecosystem structure, and dynamics of Ice, snow and cold land processes, and surface water and ocean topography. Traditionally, standard methods such as Fast-Fourier Transform (FFT) and Inverse Fast-Fourier Transform (IFFT) have been used to extract Images from SAR radar data, Due to non-parametric features of these methods and their resolution limitations and observation time dependence, use of spectral estimation and signal pre- and post-processing techniques based on wavelets to process SAR radar data has been proposed. Multi-resolution wavelet transforms and advanced spectral estimation techniques have proven to offer efficient solutions to this problem.

  11. A Stepped Frequency CW SAR for Lightweight UAV Operation

    National Research Council Canada - National Science Library

    Morrison, Keith

    2005-01-01

    A stepped-frequency continuous wave (SF-CW) synthetic aperture radar (SAR), with frequency-agile waveforms and real-time intelligent signal processing algorithms, is proposed for operation from a lightweight UAV platform...

  12. Methodology of dose calculation for the SRS SAR

    International Nuclear Information System (INIS)

    Price, J.B.

    1991-07-01

    The Savannah River Site (SRS) Safety Analysis Report (SAR) covering K reactor operation assesses a spectrum of design basis accidents. The assessment includes estimation of the dose consequences from the analyzed accidents. This report discusses the methodology used to perform the dose analysis reported in the SAR and also includes the quantified doses. Doses resulting from postulated design basis reactor accidents in Chapter 15 of the SAR are discussed, as well as an accident in which three percent of the fuel melts. Doses are reported for both atmospheric and aqueous releases. The methodology used to calculate doses from these accidents as reported in the SAR is consistent with NRC guidelines and industry standards. The doses from the design basis accidents for the SRS reactors are below the limits set for commercial reactors by the NRC and also meet industry criteria. A summary of doses for various postulated accidents is provided

  13. Stellwagen Bank National Marine Sanctuary - Synthetic Aperture Radar (SAR) Imagery

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This geodatabase contains Synthetic Aperture Radar images (SAR), which consist of a fine resolution (12.5-50m), two-dimensional radar backscatter map of the...

  14. Massachusetts Bay - Internal wave packets digitized from SAR imagery

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This feature class contains internal wave packets digitized from SAR imagery at 1:350,000 scale in Massachusetts Bay. Internal waves are nonsinusoidal waves that...

  15. Change detection in polarimetric SAR data over several time points

    DEFF Research Database (Denmark)

    Conradsen, Knut; Nielsen, Allan Aasbjerg; Skriver, Henning

    2014-01-01

    A test statistic for the equality of several variance-covariance matrices following the complex Wishart distribution is introduced. The test statistic is applied successfully to detect change in C-band EMISAR polarimetric SAR data over four time points.......A test statistic for the equality of several variance-covariance matrices following the complex Wishart distribution is introduced. The test statistic is applied successfully to detect change in C-band EMISAR polarimetric SAR data over four time points....

  16. Comparing satellite SAR and wind farm wake models

    DEFF Research Database (Denmark)

    Hasager, Charlotte Bay; Vincent, P.; Husson, R.

    2015-01-01

    . These extend several tens of kilometres downwind e.g. 70 km. Other SAR wind maps show near-field fine scale details of wake behind rows of turbines. The satellite SAR wind farm wake cases are modelled by different wind farm wake models including the PARK microscale model, the Weather Research and Forecasting...... (WRF) model in high resolution and WRF with coupled microscale parametrization....

  17. Literature-Related Discovery: Potential Treatments and Preventives for SARS

    Science.gov (United States)

    2010-01-01

    We recently demonstrated that kefir modulates the immune response in mice, increasing the number of IgA+ cells in the intestinal and bronchial...retrieval and analysis of the core SARS literature and literatures related directly to the core SARS literature (e.g., immune system component literatures...According to recent reviews of the pandemic, none of the drugs worked. Those who recovered did so by natural means; their immune systems were

  18. SAR image formation with azimuth interpolation after azimuth transform

    Science.gov (United States)

    Doerry,; Armin W. , Martin; Grant D. , Holzrichter; Michael, W [Albuquerque, NM

    2008-07-08

    Two-dimensional SAR data can be processed into a rectangular grid format by subjecting the SAR data to a Fourier transform operation, and thereafter to a corresponding interpolation operation. Because the interpolation operation follows the Fourier transform operation, the interpolation operation can be simplified, and the effect of interpolation errors can be diminished. This provides for the possibility of both reducing the re-grid processing time, and improving the image quality.

  19. Nano(Q)SAR: Challenges, pitfalls and perspectives.

    Science.gov (United States)

    Tantra, Ratna; Oksel, Ceyda; Puzyn, Tomasz; Wang, Jian; Robinson, Kenneth N; Wang, Xue Z; Ma, Cai Y; Wilkins, Terry

    2015-01-01

    Regulation for nanomaterials is urgently needed, and the drive to adopt an intelligent testing strategy is evident. Such a strategy will not only provide economic benefits but will also reduce moral and ethical concerns arising from animal testing. For regulatory purposes, such an approach is promoted by REACH, particularly the use of quantitative structure-activity relationships [(Q)SAR] as a tool for the categorisation of compounds according to their physicochemical and toxicological properties. In addition to compounds, (Q)SAR has also been applied to nanomaterials in the form of nano(Q)SAR. Although (Q)SAR in chemicals is well established, nano(Q)SAR is still in early stages of development and its successful uptake is far from reality. This article aims to identify some of the pitfalls and challenges associated with nano-(Q)SARs in relation to the categorisation of nanomaterials. Our findings show clear gaps in the research framework that must be addressed if we are to have reliable predictions from such models. Three major barriers were identified: the need to improve quality of experimental data in which the models are developed from, the need to have practical guidelines for the development of the nano(Q)SAR models and the need to standardise and harmonise activities for the purpose of regulation. Of these three, the first, i.e. the need to improve data quality requires immediate attention, as it underpins activities associated with the latter two. It should be noted that the usefulness of data in the context of nano-(Q)SAR modelling is not only about the quantity of data but also about the quality, consistency and accessibility of those data.

  20. One carbon metabolism in SAR11 pelagic marine bacteria.

    Directory of Open Access Journals (Sweden)

    Jing Sun

    Full Text Available The SAR11 Alphaproteobacteria are the most abundant heterotrophs in the oceans and are believed to play a major role in mineralizing marine dissolved organic carbon. Their genomes are among the smallest known for free-living heterotrophic cells, raising questions about how they successfully utilize complex organic matter with a limited metabolic repertoire. Here we show that conserved genes in SAR11 subgroup Ia (Candidatus Pelagibacter ubique genomes encode pathways for the oxidation of a variety of one-carbon compounds and methyl functional groups from methylated compounds. These pathways were predicted to produce energy by tetrahydrofolate (THF-mediated oxidation, but not to support the net assimilation of biomass from C1 compounds. Measurements of cellular ATP content and the oxidation of (14C-labeled compounds to (14CO(2 indicated that methanol, formaldehyde, methylamine, and methyl groups from glycine betaine (GBT, trimethylamine (TMA, trimethylamine N-oxide (TMAO, and dimethylsulfoniopropionate (DMSP were oxidized by axenic cultures of the SAR11 strain Ca. P. ubique HTCC1062. Analyses of metagenomic data showed that genes for C1 metabolism occur at a high frequency in natural SAR11 populations. In short term incubations, natural communities of Sargasso Sea microbial plankton expressed a potential for the oxidation of (14C-labeled formate, formaldehyde, methanol and TMAO that was similar to cultured SAR11 cells and, like cultured SAR11 cells, incorporated a much larger percentage of pyruvate and glucose (27-35% than of C1 compounds (2-6% into biomass. Collectively, these genomic, cellular and environmental data show a surprising capacity for demethylation and C1 oxidation in SAR11 cultures and in natural microbial communities dominated by SAR11, and support the conclusion that C1 oxidation might be a significant conduit by which dissolved organic carbon is recycled to CO(2 in the upper ocean.

  1. Global Distribution Adjustment and Nonlinear Feature Transformation for Automatic Colorization

    Directory of Open Access Journals (Sweden)

    Terumasa Aoki

    2018-01-01

    Full Text Available Automatic colorization is generally classified into two groups: propagation-based methods and reference-based methods. In reference-based automatic colorization methods, color image(s are used as reference(s to reconstruct original color of a gray target image. The most important task here is to find the best matching pairs for all pixels between reference and target images in order to transfer color information from reference to target pixels. A lot of attractive local feature-based image matching methods have already been developed for the last two decades. Unfortunately, as far as we know, there are no optimal matching methods for automatic colorization because the requirements for pixel matching in automatic colorization are wholly different from those for traditional image matching. To design an efficient matching algorithm for automatic colorization, clustering pixel with low computational cost and generating descriptive feature vector are the most important challenges to be solved. In this paper, we present a novel method to address these two problems. In particular, our work concentrates on solving the second problem (designing a descriptive feature vector; namely, we will discuss how to learn a descriptive texture feature using scaled sparse texture feature combining with a nonlinear transformation to construct an optimal feature descriptor. Our experimental results show our proposed method outperforms the state-of-the-art methods in terms of robustness for color reconstruction for automatic colorization applications.

  2. An analytical solution for improved HIFU SAR estimation

    International Nuclear Information System (INIS)

    Dillon, C R; Vyas, U; Christensen, D A; Roemer, R B; Payne, A

    2012-01-01

    Accurate determination of the specific absorption rates (SARs) present during high intensity focused ultrasound (HIFU) experiments and treatments provides a solid physical basis for scientific comparison of results among HIFU studies and is necessary to validate and improve SAR predictive software, which will improve patient treatment planning, control and evaluation. This study develops and tests an analytical solution that significantly improves the accuracy of SAR values obtained from HIFU temperature data. SAR estimates are obtained by fitting the analytical temperature solution for a one-dimensional radial Gaussian heating pattern to the temperature versus time data following a step in applied power and evaluating the initial slope of the analytical solution. The analytical method is evaluated in multiple parametric simulations for which it consistently (except at high perfusions) yields maximum errors of less than 10% at the center of the focal zone compared with errors up to 90% and 55% for the commonly used linear method and an exponential method, respectively. For high perfusion, an extension of the analytical method estimates SAR with less than 10% error. The analytical method is validated experimentally by showing that the temperature elevations predicted using the analytical method's SAR values determined for the entire 3D focal region agree well with the experimental temperature elevations in a HIFU-heated tissue-mimicking phantom. (paper)

  3. SAR11 Bacteria: The Most Abundant Plankton in the Oceans.

    Science.gov (United States)

    Giovannoni, Stephen J

    2017-01-03

    SAR11 is a group of small, carbon-oxidizing bacteria that reach a global estimated population size of 2.4×10 28 cells-approximately 25% of all plankton. They are found throughout the oceans but reach their largest numbers in stratified, oligotrophic gyres, which are an expanding habitat in the warming oceans. SAR11 likely had a Precambrian origin and, over geological time, evolved into the niche of harvesting labile, low-molecular-weight dissolved organic matter (DOM). SAR11 cells are minimal in size and complexity, a phenomenon known as streamlining that is thought to benefit them by lowering the material costs of replication and maximizing transport functions that are essential to competition at ultralow nutrient concentrations. One of the surprises in SAR11 metabolism is their ability to both oxidize and produce a variety of volatile organic compounds that can diffuse into the atmosphere. SAR11 cells divide slowly and lack many forms of regulation commonly used by bacterial cells to adjust to changing environmental conditions. As a result of genome reduction, they require an unusual range of nutrients, which leads to complex biochemical interactions with other plankton. The study of SAR11 is providing insight into the biogeochemistry of labile DOM and is affecting microbiology beyond marine science by providing a model for understanding the evolution and function of streamlined cells.

  4. URBAN MODELLING PERFORMANCE OF NEXT GENERATION SAR MISSIONS

    Directory of Open Access Journals (Sweden)

    U. G. Sefercik

    2017-09-01

    Full Text Available In synthetic aperture radar (SAR technology, urban mapping and modelling have become possible with revolutionary missions TerraSAR-X (TSX and Cosmo-SkyMed (CSK since 2007. These satellites offer 1m spatial resolution in high-resolution spotlight imaging mode and capable for high quality digital surface model (DSM acquisition for urban areas utilizing interferometric SAR (InSAR technology. With the advantage of independent generation from seasonal weather conditions, TSX and CSK DSMs are much in demand by scientific users. The performance of SAR DSMs is influenced by the distortions such as layover, foreshortening, shadow and double-bounce depend up on imaging geometry. In this study, the potential of DSMs derived from convenient 1m high-resolution spotlight (HS InSAR pairs of CSK and TSX is validated by model-to-model absolute and relative accuracy estimations in an urban area. For the verification, an airborne laser scanning (ALS DSM of the study area was used as the reference model. Results demonstrated that TSX and CSK urban DSMs are compatible in open, built-up and forest land forms with the absolute accuracy of 8–10 m. The relative accuracies based on the coherence of neighbouring pixels are superior to absolute accuracies both for CSK and TSX.

  5. Evaluation of Polarimetric SAR Decomposition for Classifying Wetland Vegetation Types

    Directory of Open Access Journals (Sweden)

    Sang-Hoon Hong

    2015-07-01

    Full Text Available The Florida Everglades is the largest subtropical wetland system in the United States and, as with subtropical and tropical wetlands elsewhere, has been threatened by severe environmental stresses. It is very important to monitor such wetlands to inform management on the status of these fragile ecosystems. This study aims to examine the applicability of TerraSAR-X quadruple polarimetric (quad-pol synthetic aperture radar (PolSAR data for classifying wetland vegetation in the Everglades. We processed quad-pol data using the Hong & Wdowinski four-component decomposition, which accounts for double bounce scattering in the cross-polarization signal. The calculated decomposition images consist of four scattering mechanisms (single, co- and cross-pol double, and volume scattering. We applied an object-oriented image analysis approach to classify vegetation types with the decomposition results. We also used a high-resolution multispectral optical RapidEye image to compare statistics and classification results with Synthetic Aperture Radar (SAR observations. The calculated classification accuracy was higher than 85%, suggesting that the TerraSAR-X quad-pol SAR signal had a high potential for distinguishing different vegetation types. Scattering components from SAR acquisition were particularly advantageous for classifying mangroves along tidal channels. We conclude that the typical scattering behaviors from model-based decomposition are useful for discriminating among different wetland vegetation types.

  6. Chinese HJ-1C SAR And Its Wind Mapping Capability

    Science.gov (United States)

    Huang, Weigen; Chen, Fengfeng; Yang, Jingsong; Fu, Bin; Chen, Peng; Zhang, Chan

    2010-04-01

    Chinese Huan Jing (HJ)-1C synthetic aperture radar (SAR) satellite has been planed to be launched in 2010. HJ-1C satellite will fly in a sun-synchronous polar orbit of 500-km altitude. SAR will be the only sensor on board the satellite. It operates in S band with VV polarization. Its image mode has the incidence angles 25°and 47°at the near and far sides of the swath respectively. There are two selectable SAR modes of operation, which are fine resolution beams and standard beams respectively. The sea surface wind mapping capability of the SAR has been examined using M4S radar imaging model developed by Romeiser. The model is based on Bragg scattering theory in a composite surface model expansion. It accounts for contributions of the full ocean wave spectrum to the radar backscatter from ocean surface. The model reproduces absolute normalized radar cross section (NRCS) values for wide ranges of wind speeds. The model results of HJ-1C SAR have been compared with the model results of Envisat ASAR. It shows that HJ-1C SAR is as good as Envisat ASAR at sea surface wind mapping.

  7. Playback system designed for X-Band SAR

    International Nuclear Information System (INIS)

    Yuquan, Liu; Changyong, Dou

    2014-01-01

    SAR(Synthetic Aperture Radar) has extensive application because it is daylight and weather independent. In particular, X-Band SAR strip map, designed by Institute of Remote Sensing and Digital Earth, Chinese Academy of Sciences, provides high ground resolution images, at the same time it has a large spatial coverage and a short acquisition time, so it is promising in multi-applications. When sudden disaster comes, the emergency situation acquires radar signal data and image as soon as possible, in order to take action to reduce loss and save lives in the first time. This paper summarizes a type of X-Band SAR playback processing system designed for disaster response and scientific needs. It describes SAR data workflow includes the payload data transmission and reception process. Playback processing system completes signal analysis on the original data, providing SAR level 0 products and quick image. Gigabit network promises radar signal transmission efficiency from recorder to calculation unit. Multi-thread parallel computing and ping pong operation can ensure computation speed. Through gigabit network, multi-thread parallel computing and ping pong operation, high speed data transmission and processing meet the SAR radar data playback real time requirement

  8. Playback system designed for X-Band SAR

    Science.gov (United States)

    Yuquan, Liu; Changyong, Dou

    2014-03-01

    SAR(Synthetic Aperture Radar) has extensive application because it is daylight and weather independent. In particular, X-Band SAR strip map, designed by Institute of Remote Sensing and Digital Earth, Chinese Academy of Sciences, provides high ground resolution images, at the same time it has a large spatial coverage and a short acquisition time, so it is promising in multi-applications. When sudden disaster comes, the emergency situation acquires radar signal data and image as soon as possible, in order to take action to reduce loss and save lives in the first time. This paper summarizes a type of X-Band SAR playback processing system designed for disaster response and scientific needs. It describes SAR data workflow includes the payload data transmission and reception process. Playback processing system completes signal analysis on the original data, providing SAR level 0 products and quick image. Gigabit network promises radar signal transmission efficiency from recorder to calculation unit. Multi-thread parallel computing and ping pong operation can ensure computation speed. Through gigabit network, multi-thread parallel computing and ping pong operation, high speed data transmission and processing meet the SAR radar data playback real time requirement.

  9. The Intercomparison of X-Band SAR Images from COSMO‑SkyMed and TerraSAR-X Satellites: Case Studies

    Directory of Open Access Journals (Sweden)

    Simone Pettinato

    2013-06-01

    Full Text Available The analysis of experimental data collected by X-band SAR of COSMO-SkyMed (CSK® and TerraSAR-X (TSX images on the same surface types has shown significant differences in the signal level of the two sensors. In order to investigate the possibility of combining data from the two instruments, a study was carried out by comparing images collected with similar orbital and sensor parameters (e.g., incidence angle, polarization, look angle at approximately the same date on two Italian agricultural test sites. Several homogenous agricultural fields within the observed area common to the two sensors were selected. Some forest plots have also been considered and used as a reference target. Direct comparisons were then performed between CSK and TSX images in different acquisition modes. The analysis carried out on the agricultural fields showed that, in general, the backscattering coefficient is higher in TSX Stripmap images with respect to CSK-Himage (about 3 dB, while CSK-Ping Pong data showed values lower than TSX of about 4.8 dB. Finally, a difference in backscattering of about 2.5 dB was pointed out between CSK-Himage and Ping-Pong images on agricultural fields. These results, achieved on bare soils, have also been compared with simulations performed by using the Advanced Integral Equation Model (AIEM.

  10. InSAR Scientific Computing Environment

    Science.gov (United States)

    Rosen, Paul A.; Sacco, Gian Franco; Gurrola, Eric M.; Zabker, Howard A.

    2011-01-01

    This computing environment is the next generation of geodetic image processing technology for repeat-pass Interferometric Synthetic Aperture (InSAR) sensors, identified by the community as a needed capability to provide flexibility and extensibility in reducing measurements from radar satellites and aircraft to new geophysical products. This software allows users of interferometric radar data the flexibility to process from Level 0 to Level 4 products using a variety of algorithms and for a range of available sensors. There are many radar satellites in orbit today delivering to the science community data of unprecedented quantity and quality, making possible large-scale studies in climate research, natural hazards, and the Earth's ecosystem. The proposed DESDynI mission, now under consideration by NASA for launch later in this decade, would provide time series and multiimage measurements that permit 4D models of Earth surface processes so that, for example, climate-induced changes over time would become apparent and quantifiable. This advanced data processing technology, applied to a global data set such as from the proposed DESDynI mission, enables a new class of analyses at time and spatial scales unavailable using current approaches. This software implements an accurate, extensible, and modular processing system designed to realize the full potential of InSAR data from future missions such as the proposed DESDynI, existing radar satellite data, as well as data from the NASA UAVSAR (Uninhabited Aerial Vehicle Synthetic Aperture Radar), and other airborne platforms. The processing approach has been re-thought in order to enable multi-scene analysis by adding new algorithms and data interfaces, to permit user-reconfigurable operation and extensibility, and to capitalize on codes already developed by NASA and the science community. The framework incorporates modern programming methods based on recent research, including object-oriented scripts controlling legacy and

  11. Wake-based ship route estimation in high-resolution SAR images

    Science.gov (United States)

    Graziano, M. Daniela; Rufino, Giancarlo; D'Errico, Marco

    2014-10-01

    This paper presents a novel algorithm for wake detection in Synthetic Aperture Radar images of the sea. The algorithm has been conceived as part of a ship traffic monitoring system, in charge of ship detection validation and to estimate ship route features, such as heading and ground speed. In addition, it has been intended to be adequate for inclusion in an automatic procedure without human operator supervision. The algorithm exploits the Radon transform to identify the images ship wake on the basis of the well known theoretical characteristics of the wakes' geometry and components, that are the turbulent wake, the narrow-V wakes, and the Kelvin arms, as well as the typical appearance of such components in Synthetic Aperture Radar images of the sea as bright or dark linear feature. Examples of application to high-resolution X-band Synthetic Aperture Radar products (COSMOSkymed and TerraSAR-X) are reported, both for wake detection and ship route estimation, showing the achieved quality and reliability of wake detection, adequacy to automatic procedures, as well as speed measure accuracy.

  12. Automatic quantitative renal scintigraphy

    International Nuclear Information System (INIS)

    Valeyre, J.; Deltour, G.; Delisle, M.J.; Bouchard, A.

    1976-01-01

    Renal scintigraphy data may be analyzed automatically by the use of a processing system coupled to an Anger camera (TRIDAC-MULTI 8 or CINE 200). The computing sequence is as follows: normalization of the images; background noise subtraction on both images; evaluation of mercury 197 uptake by the liver and spleen; calculation of the activity fractions on each kidney with respect to the injected dose, taking into account the kidney depth and the results referred to normal values; edition of the results. Automation minimizes the scattering parameters and by its simplification is a great asset in routine work [fr

  13. AUTOMATIC FREQUENCY CONTROL SYSTEM

    Science.gov (United States)

    Hansen, C.F.; Salisbury, J.D.

    1961-01-10

    A control is described for automatically matching the frequency of a resonant cavity to that of a driving oscillator. The driving oscillator is disconnected from the cavity and a secondary oscillator is actuated in which the cavity is the frequency determining element. A low frequency is mixed with the output of the driving oscillator and the resultant lower and upper sidebands are separately derived. The frequencies of the sidebands are compared with the secondary oscillator frequency. deriving a servo control signal to adjust a tuning element in the cavity and matching the cavity frequency to that of the driving oscillator. The driving oscillator may then be connected to the cavity.

  14. Automatic dipole subtraction

    International Nuclear Information System (INIS)

    Hasegawa, K.

    2008-01-01

    The Catani-Seymour dipole subtraction is a general procedure to treat infrared divergences in real emission processes at next-to-leading order in QCD. We automatized the procedure in a computer code. The code is useful especially for the processes with many parton legs. In this talk, we first explain the algorithm of the dipole subtraction and the whole structure of our code. After that we show the results for some processes where the infrared divergences of real emission processes are subtracted. (author)

  15. Automatic programmable air ozonizer

    International Nuclear Information System (INIS)

    Gubarev, S.P.; Klosovsky, A.V.; Opaleva, G.P.; Taran, V.S.; Zolototrubova, M.I.

    2015-01-01

    In this paper we describe a compact, economical, easy to manage auto air ozonator developed at the Institute of Plasma Physics of the NSC KIPT. It is designed for sanitation, disinfection of premises and cleaning the air from foreign odors. A distinctive feature of the developed device is the generation of a given concentration of ozone, approximately 0.7 maximum allowable concentration (MAC), and automatic maintenance of a specified level. This allows people to be inside the processed premises during operation. The microprocessor controller to control the operation of the ozonator was developed

  16. 基于MRF的多时相SAR影像非监督变化检测%Unsupervised Change Detection in Multitemporal SAR Images Using MRF Models

    Institute of Scientific and Technical Information of China (English)

    江利明; 廖明生; 张路; 林珲

    2007-01-01

    An unsupervised change-detection method that considers the spatial contextual information in a log-ratio difference image generated from multitemporal SAR images is proposed. A Markov random filed (MRF) model is particularly employed to exploit statistical spatial correlation of intensity levels among neighboring pixels. Under the assumption of the independency of pixels and mixed Gaussian distribution in the log-ratio difference image, a stochastic and iterative EM-MPM change-detection algorithm based on an MRF model is developed. The EM-MPM algorithm is based on a maximiser of posterior marginals (MPM) algorithm for image segmentation and an expectation-maximum (EM) algorithm for parameter estimation in a completely automatic way. The experiment results obtained on multitemporal ERS-2 SAR images show the effectiveness of the proposed method.

  17. Selection of SARS-Coronavirus-specific B cell epitopes by phage peptide library screening and evaluation of the immunological effect of epitope-based peptides on mice

    International Nuclear Information System (INIS)

    Yu Hua; Jiang Lifang; Fang Danyun; Yan Huijun; Zhou Jingjiao; Zhou Junmei; Liang Yu; Gao Yang; Zhao, Wei; Long Beiguo

    2007-01-01

    Antibodies to SARS-Coronavirus (SARS-CoV)-specific B cell epitopes might recognize the pathogen and interrupt its adherence to and penetration of host cells. Hence, these epitopes could be useful for diagnosis and as vaccine constituents. Using the phage-displayed peptide library screening method and purified Fab fragments of immunoglobulin G (IgG Fab) from normal human sera and convalescent sera from SARS-CoV-infected patients as targets, 11 B cell epitopes of SARS-CoV spike glycoprotein (S protein) and membrane protein (M protein) were screened. After a bioinformatics tool was used to analyze these epitopes, four epitope-based S protein dodecapeptides corresponding to the predominant epitopes were chosen for synthesis. Their antigenic specificities and immunogenicities were studied in vitro and in vivo. Flow cytometry and ELISPOT analysis of lymphocytes as well as a serologic analysis of antibody showed that these peptides could trigger a rapid, highly effective, and relatively safe immune response in BALB/c mice. These findings might aid development of SARS diagnostics and vaccines. Moreover, the role of S and M proteins as important surface antigens is confirmed

  18. NEAR REAL-TIME AUTOMATIC MARINE VESSEL DETECTION ON OPTICAL SATELLITE IMAGES

    Directory of Open Access Journals (Sweden)

    G. Máttyus

    2013-05-01

    Full Text Available Vessel monitoring and surveillance is important for maritime safety and security, environment protection and border control. Ship monitoring systems based on Synthetic-aperture Radar (SAR satellite images are operational. On SAR images the ships made of metal with sharp edges appear as bright dots and edges, therefore they can be well distinguished from the water. Since the radar is independent from the sun light and can acquire images also by cloudy weather and rain, it provides a reliable service. Vessel detection from spaceborne optical images (VDSOI can extend the SAR based systems by providing more frequent revisit times and overcoming some drawbacks of the SAR images (e.g. lower spatial resolution, difficult human interpretation. Optical satellite images (OSI can have a higher spatial resolution thus enabling the detection of smaller vessels and enhancing the vessel type classification. The human interpretation of an optical image is also easier than as of SAR image. In this paper I present a rapid automatic vessel detection method which uses pattern recognition methods, originally developed in the computer vision field. In the first step I train a binary classifier from image samples of vessels and background. The classifier uses simple features which can be calculated very fast. For the detection the classifier is slided along the image in various directions and scales. The detector has a cascade structure which rejects most of the background in the early stages which leads to faster execution. The detections are grouped together to avoid multiple detections. Finally the position, size(i.e. length and width and heading of the vessels is extracted from the contours of the vessel. The presented method is parallelized, thus it runs fast (in minutes for 16000 × 16000 pixels image on a multicore computer, enabling near real-time applications, e.g. one hour from image acquisition to end user.

  19. Near Real-Time Automatic Marine Vessel Detection on Optical Satellite Images

    Science.gov (United States)

    Máttyus, G.

    2013-05-01

    Vessel monitoring and surveillance is important for maritime safety and security, environment protection and border control. Ship monitoring systems based on Synthetic-aperture Radar (SAR) satellite images are operational. On SAR images the ships made of metal with sharp edges appear as bright dots and edges, therefore they can be well distinguished from the water. Since the radar is independent from the sun light and can acquire images also by cloudy weather and rain, it provides a reliable service. Vessel detection from spaceborne optical images (VDSOI) can extend the SAR based systems by providing more frequent revisit times and overcoming some drawbacks of the SAR images (e.g. lower spatial resolution, difficult human interpretation). Optical satellite images (OSI) can have a higher spatial resolution thus enabling the detection of smaller vessels and enhancing the vessel type classification. The human interpretation of an optical image is also easier than as of SAR image. In this paper I present a rapid automatic vessel detection method which uses pattern recognition methods, originally developed in the computer vision field. In the first step I train a binary classifier from image samples of vessels and background. The classifier uses simple features which can be calculated very fast. For the detection the classifier is slided along the image in various directions and scales. The detector has a cascade structure which rejects most of the background in the early stages which leads to faster execution. The detections are grouped together to avoid multiple detections. Finally the position, size(i.e. length and width) and heading of the vessels is extracted from the contours of the vessel. The presented method is parallelized, thus it runs fast (in minutes for 16000 × 16000 pixels image) on a multicore computer, enabling near real-time applications, e.g. one hour from image acquisition to end user.

  20. Disentangling Complexity in Bayesian Automatic Adaptive Quadrature

    Science.gov (United States)

    Adam, Gheorghe; Adam, Sanda

    2018-02-01

    The paper describes a Bayesian automatic adaptive quadrature (BAAQ) solution for numerical integration which is simultaneously robust, reliable, and efficient. Detailed discussion is provided of three main factors which contribute to the enhancement of these features: (1) refinement of the m-panel automatic adaptive scheme through the use of integration-domain-length-scale-adapted quadrature sums; (2) fast early problem complexity assessment - enables the non-transitive choice among three execution paths: (i) immediate termination (exceptional cases); (ii) pessimistic - involves time and resource consuming Bayesian inference resulting in radical reformulation of the problem to be solved; (iii) optimistic - asks exclusively for subrange subdivision by bisection; (3) use of the weaker accuracy target from the two possible ones (the input accuracy specifications and the intrinsic integrand properties respectively) - results in maximum possible solution accuracy under minimum possible computing time.