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Sample records for spotlight sar images

  1. Sliding Spotlight Mode Imaging with GF-3 Spaceborne SAR Sensor

    Directory of Open Access Journals (Sweden)

    Qingjun Zhang

    2017-12-01

    Full Text Available Synthetic aperture radar (SAR sliding spotlight work mode can achieve high resolutions and wide swath (HRWS simultaneously by steering the radar antenna beam. This paper aims to obtain well focused images using sliding spotlight mode with the Chinese Gaofen-3 SAR sensor. We proposed an integrated imaging scheme with sliding spotlight echoes. In the imaging scheme, the two-step approach is applied to the spaceborne sliding spotlight SAR imaging algorithm, followed by the Doppler parameter estimation algorithm. The azimuth spectral folding phenomenon is overcome by the two-step approach. The results demonstrate a high Doppler parameter estimation accuracy. The proposed imaging process is accurate and highly efficient for sliding spotlight SAR mode.

  2. An implementation of a fast backprojection image formation algorithm for spotlight-mode SAR

    Science.gov (United States)

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

    2008-04-01

    In this paper we describe an algorithm for fast spotlight-mode synthetic aperture radar (SAR) image formation that employs backprojection as the core, but is implemented such that its compute time is comparable to the often-used Polar Format Algorithm (PFA). (Standard backprojection is so much slower than PFA that it is impractical to use in many operational scenarios.) We demonstrate the feasibility of the algorithm on real SAR phase history data sets and show some advantages in the SAR image formed by this technique.

  3. Generalized Chirp Scaling Combined with Baseband Azimuth Scaling Algorithm for Large Bandwidth Sliding Spotlight SAR Imaging.

    Science.gov (United States)

    Yi, Tianzhu; He, Zhihua; He, Feng; Dong, Zhen; Wu, Mnaqing

    2017-05-29

    This paper presents an efficient and precise imaging algorithm for the large bandwidth sliding spotlight synthetic aperture radar (SAR). The existing sub-aperture processing method based on the baseband azimuth scaling (BAS) algorithm cannot cope with the high order phase coupling along the range and azimuth dimensions. This coupling problem causes defocusing along the range and azimuth dimensions. This paper proposes a generalized chirp scaling (GCS)-BAS processing algorithm, which is based on the GCS algorithm. It successfully mitigates the deep focus along the range dimension of a sub-aperture of the large bandwidth sliding spotlight SAR, as well as high order phase coupling along the range and azimuth dimensions. Additionally, the azimuth focusing can be achieved by this azimuth scaling method. Simulation results demonstrate the ability of the GCS-BAS algorithm to process the large bandwidth sliding spotlight SAR data. It is proven that great improvements of the focus depth and imaging accuracy are obtained via the GCS-BAS algorithm.

  4. Comparison of polar formatting and back-projection algorithms for spotlight-mode SAR image formation

    Science.gov (United States)

    Jakowatz, Charles V., Jr.; Doren, Neall

    2006-05-01

    The convolution/back-projection (CBP) algorithm has recently once again been touted as the "gold standard" for spotlight-mode SAR image formation, as it is proclaimed to achieve better image quality than the well-known and often employed polar formatting algorithm (PFA). In addition, it has been suggested that PFA is less flexible than CBP in that PFA can only compute the SAR image on one grid and PFA cannot add or subtract pulses from the imaging process. The argument for CBP acknowledges the computational burden of CBP compared to PFA, but asserts that the increased image accuracy and flexibility of the formation process is warranted, at least in some imaging scenarios. Because CBP can now be sped up by the proper algorithm design, it becomes, according to this line of analysis, the clear algorithm of choice for SAR image formation. In this paper we reject the above conclusion by showing that PFA and CBP achieve the same image quality, and that PFA has complete flexibility, including choice of imaging plane, size of illuminated beam area to be imaged, resolution of the image, and others. We demonstrate these claims via formation of both simulated and real SAR imagery using both algorithms.

  5. Comparison of algorithms for use in real-time spotlight-mode SAR image formation

    Science.gov (United States)

    Jakowatz, Charles V., Jr.; Wahl, Daniel E.; Yocky, David A.; Bray, Brian K.; Bow, Wallace J., Jr.; Richards, John A.

    2004-09-01

    This paper compares three algorithms for potential use in a real-time, on-board implementation of spotlight-mode SAR image formation. These include: the polar formatting algorithm (PFA), the range migration algorithm (RMA), and the overlapped subapertures algorithm (OSA). We conclude that for any reasonable spotlight-mode imaging scenario, PFA is easily the algorithm of choice because its computational efficiency is significantly higher than that of either RMA or OSA. This comparison specifically includes cases in which wavefront curvature is sufficient to cause image defocus in conventional PFA, because a post-processing refocus step can be performed with PFA to yield excellent image quality for only a minimal increase in computation time. We demonstrate that real-time image formation for many imaging scenarios is achievable using PFA implemented on a single Pentium M processor. OSA is quite slow compared to PFA, especially for the case of moderate to high resolution (9 inches and better). RMA is not competitive with PFA for situations that do not require wavefront curvature correction. For those cases in which PFA requires post-processing to correct for wavefront curvature, RMA comes closer in efficiency to PFA, but is still outperformed by the modified PFA.

  6. Efficient sliding spotlight SAR raw signal simulation of extended scenes

    Directory of Open Access Journals (Sweden)

    Huang Pingping

    2011-01-01

    Full Text Available Abstract Sliding spotlight mode is a novel synthetic aperture radar (SAR imaging scheme with an achieved azimuth resolution better than stripmap mode and ground coverage larger than spotlight configuration. However, its raw signal simulation of extended scenes may not be efficiently implemented in the two-dimensional (2D Fourier transformed domain. This article presents a novel sliding spotlight raw signal simulation approach from the wide-beam SAR imaging modes. This approach can generate sliding spotlight raw signal not only from raw data evaluated by the simulators, but also from real data in the stripmap/spotlight mode. In order to obtain the desired raw data from conventional stripmap/spotlight mode, the azimuth time-varying filtering, which is implemented by de-rotation and low-pass filtering, is adopted. As raw signal of extended scenes in the stripmap/spotlight mode can efficiently be evaluated in the 2D Fourier domain, the proposed approach provides an efficient sliding spotlight SAR simulator of extended scenes. Simulation results validate this efficient simulator.

  7. Using frequency-scaling approach to process squint-mode spotlight SAR data

    Science.gov (United States)

    Sun, Jinping; Mao, Shiyi; Liu, Zhongkan; Hong, Wen Q.

    2001-08-01

    Frequency scaling approach is a new spotlight SAR image formation algorithm. It precisely performs the range cell migration correction for dechirped raw data without interpolation by using a novel frequency scaling operation while residual video phase is corrected simultaneously. The computation requirements are lower than the other spotlight SAR image formation approaches such as polar format algorithm and range migration algorithm. In this paper, frequency scaling algorithm is applied to process high squint spotlight data. The new squint illumination geometry is defined and some modifications to the basic algorithm are presented. Point target simulations up to 45 deg squint angle are carried out to show the validity of the algorithm.

  8. Geolocation with error analysis using imagery from an experimental spotlight SAR

    Science.gov (United States)

    Wonnacott, William Mark

    This dissertation covers the development of a geometry-based sensor model for a specific monostatic spotlight synthetic aperture radar (SAR) system---referred to as the ExSAR (for experimental SAR). This sensor model facilitates single- and multiple-image geopositioning with error analysis. It allows for the use of known ground control points in refining the collection geometry parameters (a process called image resection) and for the subsequent geopositioning of other points using the resected image. Theoretically, the model also allows for the potential recovery of bias-like, persistent errors common across multiple images. The model also includes multi-image correspondence equations to aid in the cross-image identification of conjugate points. The sensor model development begins with a generic, theoretical approach to the modeling of spotlight SAR. A closed-form solution to the range and range-rate condition equations and the corresponding error propagation equation are presented. (The SAR condition equations have traditionally been solved iteratively.) The application of the closed-form solution in the image-to-ground and ground-to-image transformations is documented. The theoretical work also includes a preliminary error sensitivity analysis and a treatment of the spotlight SAR resection process. The ExSAR-specific model is established and assessed with an extensive set of images collected using the experimental radar over arrays of ground control points. Using this set, the imagery metadata elements are assessed, and the optimal element set for geopositioning is determined. The ExSAR imagery is shown to be transformed to the ground plane in only one dimension. The eventual ExSAR sensor model is used with known elevations and single-image geopositioning to show a horizontal accuracy of 8.23 m (rms). With resection using five ground-surveyed control points per image, the horizontal accuracy of reserved check points is 0.45 m (rms). Resections using the same

  9. An Improved Doppler Rate Estimation Approach for Sliding Spotlight SAR Data Based on the Transposition Domain

    Directory of Open Access Journals (Sweden)

    She Xiao-qiang

    2014-08-01

    Full Text Available In image processing of high-resolution sliding spotlight SAR, it is important to know the Doppler rate with accuracy; however, traditional Doppler rate estimation algorithms are not very helpful because of the azimuth spectrum folding phenomenon. In this study, an algorithm that works on the transposition domain is proposed to solve this problem. Furthermore, the algorithm is also helpful in obtaining excellent focused images by embedding it in the two-step technique. Finally, the proposed algorithm is verified using computer simulations.

  10. Investigation on the separability of slums by multi-aspect TerraSAR-X dual-co-polarized high resolution spotlight images based on the multi-scale evaluation of local distributions

    Science.gov (United States)

    Schmitt, Andreas; Sieg, Tobias; Wurm, Michael; Taubenböck, Hannes

    2018-02-01

    Following recent advances in distinguishing settlements vs. non-settlement areas from latest SAR data, the question arises whether a further automatic intra-urban delineation and characterization of different structural types is possible. This paper studies the appearance of the structural type ;slums; in high resolution SAR images. Geocoded Kennaugh elements are used as backscatter information and Schmittlet indices as descriptor of local texture. Three cities with a significant share of slums (Cape Town, Manila, Mumbai) are chosen as test sites. These are imaged by TerraSAR-X in the dual-co-polarized high resolution spotlight mode in any available aspect angle. Representative distributions are estimated and fused by a robust approach. Our observations identify a high similarity of slums throughout all three test sites. The derived similarity maps are validated with reference data sets from visual interpretation and ground truth. The final validation strategy is based on completeness and correctness versus other classes in relation to the similarity. High accuracies (up to 87%) in identifying morphologic slums are reached for Cape Town. For Manila (up to 60%) and Mumbai (up to 54%), the distinction is more difficult due to their complex structural configuration. Concluding, high resolution SAR data can be suitable to automatically trace potential locations of slums. Polarimetric information and the incidence angle seem to have a negligible impact on the results whereas the intensity patterns and the passing direction of the satellite are playing a key role. Hence, the combination of intensity images (brightness) acquired from ascending and descending orbits together with Schmittlet indices (spatial pattern) promises best results. The transfer from the automatically recognized physical similarity to the semantic interpretation remains challenging.

  11. Convolution backprojection image reconstruction for spotlight mode synthetic aperture radar.

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    Desai, M D; Jenkins, W K

    1992-01-01

    Convolution backprojection (CBP) image reconstruction has been proposed as a means of producing high-resolution synthetic-aperture radar (SAR) images by processing data directly in the polar recording format which is the conventional recording format for spotlight mode SAR. The CBP algorithm filters each projection as it is recorded and then backprojects the ensemble of filtered projections to create the final image in a pixel-by-pixel format. CBP reconstruction produces high-quality images by handling the recorded data directly in polar format. The CBP algorithm requires only 1-D interpolation along the filtered projections to determine the precise values that must be contributed to the backprojection summation from each projection. The algorithm is thus able to produce higher quality images by eliminating the inaccuracies of 2-D interpolation, as well as using all the data recorded in the spectral domain annular sector more effectively. The computational complexity of the CBP algorithm is O(N (3)).

  12. Space-variant post-filtering for wavefront curvature correction in polar-formatted spotlight-mode SAR imagery

    Science.gov (United States)

    Doren, Neall Evan

    Wavefront curvature defocus effects occur in spotlight-mode SAR imagery when reconstructed via the well-known polar-formatting algorithm (PFA) under certain imaging scenarios. These include imaging at close range, using a very low radar center frequency, utilizing high resolution, and/or imaging very large scenes. Wavefront curvature effects arise from the unrealistic assumption of strictly planar wavefronts illuminating the imaged scene. This dissertation presents a method for the correction of wavefront curvature defocus effects under these scenarios, concentrating on the generalized, squint-mode imaging scenario and its computational aspects. This correction is accomplished through an efficient one-dimensional, image domain filter applied as a post-processing step to PFA. This post-filter, referred to as SVPF, is precalculated from a theoretical derivation of the wavefront curvature effect and varies as a function of scene location. Prior to SVPF, severe restrictions were placed on the imaged scene size in order to avoid defocus effects under these scenarios when using PFA. The SVPF algorithm eliminates the need for scene size restrictions when wavefront curvature effects are present, correcting for wavefront curvature in broadside as well as squinted collection modes while imposing little additional computational penalty for squinted images. This dissertation covers the theoretical development, implementation and analysis of the generalized, squint-mode SVPF algorithm (of which broadside-mode is a special case) and provides examples of its capabilities and limitations as well as offering guidelines for maximizing its computational efficiency. Tradeoffs between the PFA/SVPF combination and other spotlight-mode SAR image formation techniques are discussed with regard to computational burden, image quality, and imaging geometry constraints. It is demonstrated that other methods fail to exhibit a clear computational advantage over polar-formatting in conjunction

  13. Space-Variant Post-Filtering for Wavefront Curvature Correction in Polar-Formatted Spotlight-Mode SAR Imagery

    Energy Technology Data Exchange (ETDEWEB)

    DOREN,NEALL E.

    1999-10-01

    Wavefront curvature defocus effects occur in spotlight-mode SAR imagery when reconstructed via the well-known polar-formatting algorithm (PFA) under certain imaging scenarios. These include imaging at close range, using a very low radar center frequency, utilizing high resolution, and/or imaging very large scenes. Wavefront curvature effects arise from the unrealistic assumption of strictly planar wavefronts illuminating the imaged scene. This dissertation presents a method for the correction of wavefront curvature defocus effects under these scenarios, concentrating on the generalized: squint-mode imaging scenario and its computational aspects. This correction is accomplished through an efficient one-dimensional, image domain filter applied as a post-processing step to PF.4. This post-filter, referred to as SVPF, is precalculated from a theoretical derivation of the wavefront curvature effect and varies as a function of scene location. Prior to SVPF, severe restrictions were placed on the imaged scene size in order to avoid defocus effects under these scenarios when using PFA. The SVPF algorithm eliminates the need for scene size restrictions when wavefront curvature effects are present, correcting for wavefront curvature in broadside as well as squinted collection modes while imposing little additional computational penalty for squinted images. This dissertation covers the theoretical development, implementation and analysis of the generalized, squint-mode SVPF algorithm (of which broadside-mode is a special case) and provides examples of its capabilities and limitations as well as offering guidelines for maximizing its computational efficiency. Tradeoffs between the PFA/SVPF combination and other spotlight-mode SAR image formation techniques are discussed with regard to computational burden, image quality, and imaging geometry constraints. It is demonstrated that other methods fail to exhibit a clear computational advantage over polar-formatting in conjunction

  14. 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.

  15. Earthquake-Induced Building Damage Detection with Post-Event Sub-Meter VHR TerraSAR-X Staring Spotlight Imagery

    Directory of Open Access Journals (Sweden)

    Lixia Gong

    2016-10-01

    Full Text Available Compared with optical sensors, Synthetic Aperture Radar (SAR can provide important damage information due to its ability to map areas affected by earthquakes independently from weather conditions and solar illumination. In 2013, a new TerraSAR-X mode named staring spotlight (ST, whose azimuth resolution was improved to 0.24 m, was introduced for various applications. This data source made it possible to extract detailed information from individual buildings. In this paper, we present a new concept for individual building damage assessment using a post-event sub-meter very high resolution (VHR SAR image and a building footprint map. With the building footprint map, the original footprints of buildings can be located in the SAR image. Based on the building imaging analysis of a building in the SAR image, the features in the building footprint can be extracted to identify standing and collapsed buildings. Three machine learning classifiers, including random forest (RF, support vector machine (SVM and K-nearest neighbor (K-NN, are used in the experiments. The results show that the proposed method can obtain good overall accuracy, which is above 80% with the three classifiers. The efficiency of the proposed method is demonstrated based on samples of buildings using descending and ascending sub-meter VHR ST images, which were all acquired from the same area in old Beichuan County, China.

  16. Space-variant filtering for correction of wavefront curvature effects in spotlight-mode SAR imagery formed via polar formatting

    Science.gov (United States)

    Jakowatz, Charles V., Jr.; Wahl, Daniel E.; Thompson, Paul A.; Doren, Neall E.

    1997-07-01

    Wavefront curvature defocus effects can occur in spotlight- mode SAR imagery when reconstructed via the well-known polar formatting algorithm under certain scenarios that include imaging at close range, use of very low center frequency, and/or imaging of very large scenes. The range migration algorithm, also known as seismic migration, was developed to accommodate these wavefront curvature effects. However, the along-track upsampling of the phase history data required of the original version of range migration can in certain instances represent a major computational burden. A more recent version of migration processing, the frequency domain replication and downsampling (FReD) algorithm, obviates the need to upsample, and is accordingly more efficient. In this paper we demonstrate that the combination of traditional polar formatting with appropriate space-variant post- filtering for refocus can be as efficient or even more efficient than FReD under some imaging conditions, as demonstrated by the computer-simulated results in this paper. The post-filter can be pre-calculated from a theoretical derivation of the curvature effect. The conclusion is that the new polar formatting with post filtering algorithm should be considered as a viable candidate for a spotight-mode image formation processor when curvature effects are present.

  17. Research on Synthetic Aperture Radar Processing for the Spaceborne Sliding Spotlight Mode

    OpenAIRE

    Shijian Shen; Xin Nie; Xinggan Zhang

    2018-01-01

    Gaofen-3 (GF-3) is China’ first C-band multi-polarization synthetic aperture radar (SAR) satellite, which also provides the sliding spotlight mode for the first time. Sliding-spotlight mode is a novel mode to realize imaging with not only high resolution, but also wide swath. Several key technologies for sliding spotlight mode in spaceborne SAR with high resolution are investigated in this paper, mainly including the imaging parameters, the methods of velocity estimation and ambiguity elimina...

  18. SAR Image Enhancement using Particle Filters

    Data.gov (United States)

    National Aeronautics and Space Administration — In this paper, we propose a novel approach to reduce the noise in Synthetic Aperture Radar (SAR) images using particle filters. Interpretation of SAR images is a...

  19. 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...

  20. 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

  1. SAR Image Complex Pixel Representations

    Energy Technology Data Exchange (ETDEWEB)

    Doerry, Armin W. [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States)

    2015-03-01

    Complex pixel values for Synthetic Aperture Radar (SAR) images of uniform distributed clutter can be represented as either real/imaginary (also known as I/Q) values, or as Magnitude/Phase values. Generally, these component values are integers with limited number of bits. For clutter energy well below full-scale, Magnitude/Phase offers lower quantization noise than I/Q representation. Further improvement can be had with companding of the Magnitude value.

  2. Segmentation of SAR images

    Science.gov (United States)

    Kwok, Ronald

    1989-01-01

    The statistical characteristics of image speckle are reviewed. Existing segmentation techniques that have been used for speckle filtering, edge detection, and texture extraction are sumamrized. The relative effectiveness of each technique is briefly discussed.

  3. 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......([7]) is used. The EMISAR produces data with a geometrical resolution of 2.0 meters. The corrected image is tested against photogrammetric control measurements and an accuracy better than 0.5 pixel corresponding to 0.75 meters is obtained. The results indicate promising possibilities...... for the application of SAR data in the difficult process of map revision and updating....

  4. Bistatic SAR: Signal Processing and Image Formation.

    Energy Technology Data Exchange (ETDEWEB)

    Wahl, Daniel E.; Yocky, David A.

    2014-10-01

    This report describes the significant processing steps that were used to take the raw recorded digitized signals from the bistatic synthetic aperture RADAR (SAR) hardware built for the NCNS Bistatic SAR project to a final bistatic SAR image. In general, the process steps herein are applicable to bistatic SAR signals that include the direct-path signal and the reflected signal. The steps include preprocessing steps, data extraction to for a phase history, and finally, image format. Various plots and values will be shown at most steps to illustrate the processing for a bistatic COSMO SkyMed collection gathered on June 10, 2013 on Kirtland Air Force Base, New Mexico.

  5. 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 and calib......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...

  6. 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.

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

    DEFF Research Database (Denmark)

    Kusk, Anders; Abulaitijiang, Adili; Dall, Jørgen

    2016-01-01

    of the object using a CAD-model. The raw measurements are input to a SAR system and terrain model, which models thermal noise, terrain clutter, and SAR focusing to produce synthetic SAR images. Examples of SAR images at 0.3m and 0.1m resolution, and a comparison with real SAR imagery from the MSTAR dataset...

  8. 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.

  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. An Automatic and Novel SAR Image Registration Algorithm: A Case Study of the Chinese GF-3 Satellite

    Directory of Open Access Journals (Sweden)

    Yuming Xiang

    2018-02-01

    Full Text Available The Chinese GF-3 satellite launched in August 2016 is a Synthetic Aperture Radar (SAR satellite that has the largest number of imaging modes in the world. It achieves a free switch in the spotlight, stripmap, scanSAR, wave, global observation and other imaging modes. In order to further utilize GF-3 SAR images, an automatic and fast image registration procedure needs to be done. In this paper, we propose a novel image registration technique for GF-3 images of different imaging modes. The proposed algorithm consists of two stages: coarse registration and fine registration. In the first stage, we combine an adaptive sampling method with the SAR-SIFT algorithm to efficiently eliminate obvious translation, rotation and scale differences between the reference and sensed images. In the second stage, uniformly-distributed control points are extracted, then the fast normalized cross-correlation of an improved phase congruency model is utilized as a new similarity metric to match the reference image and the coarse-registered image in a local search region. Moreover, a selection strategy is used to remove outliers. Experimental results on several GF-3 SAR images of different imaging modes show that the proposed algorithm gives a robust, efficient and precise registration performance, compared with other state-of-the-art algorithms for SAR image registration.

  11. An Automatic and Novel SAR Image Registration Algorithm: A Case Study of the Chinese GF-3 Satellite.

    Science.gov (United States)

    Xiang, Yuming; Wang, Feng; You, Hongjian

    2018-02-24

    The Chinese GF-3 satellite launched in August 2016 is a Synthetic Aperture Radar (SAR) satellite that has the largest number of imaging modes in the world. It achieves a free switch in the spotlight, stripmap, scanSAR, wave, global observation and other imaging modes. In order to further utilize GF-3 SAR images, an automatic and fast image registration procedure needs to be done. In this paper, we propose a novel image registration technique for GF-3 images of different imaging modes. The proposed algorithm consists of two stages: coarse registration and fine registration. In the first stage, we combine an adaptive sampling method with the SAR-SIFT algorithm to efficiently eliminate obvious translation, rotation and scale differences between the reference and sensed images. In the second stage, uniformly-distributed control points are extracted, then the fast normalized cross-correlation of an improved phase congruency model is utilized as a new similarity metric to match the reference image and the coarse-registered image in a local search region. Moreover, a selection strategy is used to remove outliers. Experimental results on several GF-3 SAR images of different imaging modes show that the proposed algorithm gives a robust, efficient and precise registration performance, compared with other state-of-the-art algorithms for SAR image registration.

  12. 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...

  13. Autofocus Correction of Azimuth Phase Error and Residual Range Cell Migration in Spotlight SAR Polar Format Imagery

    OpenAIRE

    Mao, Xinhua; Zhu, Daiyin; Zhu, Zhaoda

    2012-01-01

    Synthetic aperture radar (SAR) images are often blurred by phase perturbations induced by uncompensated sensor motion and /or unknown propagation effects caused by turbulent media. To get refocused images, autofocus proves to be useful post-processing technique applied to estimate and compensate the unknown phase errors. However, a severe drawback of the conventional autofocus algorithms is that they are only capable of removing one-dimensional azimuth phase errors (APE). As the resolution be...

  14. Focusing, imaging, and ATR for the Gotcha 2008 wide angle SAR collection

    Science.gov (United States)

    Gianelli, Christopher D.; Xu, Luzhou

    2013-05-01

    The following work discusses IAA's approach to tackling the wide angle, circular spotlight, synthetic aperture radar (SAR) problem from the 2008 Gotcha wide angle SAR data set, which is publicly released, with unlimited distribution. This data set comes with a MATLAB image formation routine and attendant graphical user inter- face (GUI). We begin by introducing a simple approach to focusing the collected phase history data that utilizes point targets (quadrahedral targets) present in the scene. Two SAR imaging algorithms are then presented, namely, the data-independent backprojection (BP) algorithm and the data-adaptive sparse learning via itera- tive minimization (SLIM) algorithm. These imaging approaches are compared using the 2008 Gotcha wide angle SAR data to perform both a clutter discrimination experiment, as well as an automatic target recognition (ATR) experiment. The ATR system is composed of a target pose and target center estimation preprocessing system, and includes a novel target feature for the final classification stage. Empirical results obtained by applying the focusing approach and imaging algorithms to the 2008 Gotcha wide angle SAR data set are presented and described. The results presented highlight the benefit of applying the SLIM algorithm over its data-independent counterpart, as well as the utility of the novel target feature.

  15. Estimating IMU heading error from SAR images.

    Energy Technology Data Exchange (ETDEWEB)

    Doerry, Armin Walter

    2009-03-01

    Angular orientation errors of the real antenna for Synthetic Aperture Radar (SAR) will manifest as undesired illumination gradients in SAR images. These gradients can be measured, and the pointing error can be calculated. This can be done for single images, but done more robustly using multi-image methods. Several methods are provided in this report. The pointing error can then be fed back to the navigation Kalman filter to correct for problematic heading (yaw) error drift. This can mitigate the need for uncomfortable and undesired IMU alignment maneuvers such as S-turns.

  16. Enhancement of SAR images using fuzzy shrinkage technique in ...

    Indian Academy of Sciences (India)

    The synthetic aperture radar (SAR) images are mainly affected by speckle noise. Speckle degrades the features in the image and reduces the ability of a human observer to resolve fine detail, hence despeckling is very much required for SAR images. This paper presents speckle noise reduction in SAR images using a ...

  17. 3D Tomographic SAR Imaging in Densely Vegetated Mountainous Rural Areas in China and Sweden

    Science.gov (United States)

    Feng, L.; Muller, J. P., , Prof

    2017-12-01

    3D SAR Tomography (TomoSAR) and 4D SAR Differential Tomography (Diff-TomoSAR) exploit multi-baseline SAR data stacks to create an important new innovation of SAR Interferometry, to unscramble complex scenes with multiple scatterers mapped into the same SAR cell. In addition to this 3-D shape reconstruction and deformation solution in complex urban/infrastructure areas, and recent cryospheric ice investigations, emerging tomographic remote sensing applications include forest applications, e.g. tree height and biomass estimation, sub-canopy topographic mapping, and even search, rescue and surveillance. However, these scenes are characterized by temporal decorrelation of scatterers, orbital, tropospheric and ionospheric phase distortion and an open issue regarding possible height blurring and accuracy losses for TomoSAR applications particularly in densely vegetated mountainous rural areas. Thus, it is important to develop solutions for temporal decorrelation, orbital, tropospheric and ionospheric phase distortion.We report here on 3D imaging (especially in vertical layers) over densely vegetated mountainous rural areas using 3-D SAR imaging (SAR tomography) derived from data stacks of X-band COSMO-SkyMed Spotlight and L band ALOS-1 PALSAR data stacks over Dujiangyan Dam, Sichuan, China and L and P band airborne SAR data (BioSAR 2008 - ESA) in the Krycklan river catchment, Northern Sweden. The new TanDEM-X 12m DEM is used to assist co - registration of all the data stacks over China first. Then, atmospheric correction is being assessed using weather model data such as ERA-I, MERRA, MERRA-2, WRF; linear phase-topography correction and MODIS spectrometer correction will be compared and ionospheric correction methods are discussed to remove tropospheric and ionospheric delay. Then the new TomoSAR method with the TanDEM-X 12m DEM is described to obtain the number of scatterers inside each pixel, the scattering amplitude and phase of each scatterer and finally extract

  18. 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 sections...... of the object using a CAD-model. The raw measurements are input to a SAR system and terrain model, which models thermal noise, terrain clutter, and SAR focusing to produce synthetic SAR images. Examples of SAR images at 0.3m and 0.1m resolution, and a comparison with real SAR imagery from the MSTAR dataset...

  19. SAR Image Despeckling Via Structural Sparse Representation

    Science.gov (United States)

    Lu, Ting; Li, Shutao; Fang, Leyuan; Benediktsson, Jón Atli

    2016-12-01

    A novel synthetic aperture radar (SAR) image despeckling method based on structural sparse representation is introduced. The proposed method utilizes the fact that different regions in SAR images correspond to varying terrain reflectivity. Therefore, SAR images can be split into a heterogeneous class (with a varied terrain reflectivity) and a homogeneous class (with a constant terrain reflectivity). In the proposed method, different sparse representation based despeckling schemes are designed by combining the different region characteristics in SAR images. For heterogeneous regions with rich structure and texture information, structural dictionaries are learned to appropriately represent varied structural characteristics. Specifically, each patch in these regions is sparsely coded with the best fitted structural dictionary, thus good structure preservation can be obtained. For homogenous regions without rich structure and texture information, the highly redundant photometric self-similarity is exploited to suppress speckle noise without introducing artifacts. That is achieved by firstly learning the sub-dictionary, then simultaneously sparsely coding for each group of photometrically similar image patches. Visual and objective experimental results demonstrate the superiority of the proposed method over the-state-of-the-art methods.

  20. Research on Synthetic Aperture Radar Processing for the Spaceborne Sliding Spotlight Mode

    Directory of Open Access Journals (Sweden)

    Shijian Shen

    2018-02-01

    Full Text Available Gaofen-3 (GF-3 is China’ first C-band multi-polarization synthetic aperture radar (SAR satellite, which also provides the sliding spotlight mode for the first time. Sliding-spotlight mode is a novel mode to realize imaging with not only high resolution, but also wide swath. Several key technologies for sliding spotlight mode in spaceborne SAR with high resolution are investigated in this paper, mainly including the imaging parameters, the methods of velocity estimation and ambiguity elimination, and the imaging algorithms. Based on the chosen Convolution BackProjection (CBP and PFA (Polar Format Algorithm imaging algorithms, a fast implementation method of CBP and a modified PFA method suitable for sliding spotlight mode are proposed, and the processing flows are derived in detail. Finally, the algorithms are validated by simulations and measured data.

  1. Research on Synthetic Aperture Radar Processing for the Spaceborne Sliding Spotlight Mode.

    Science.gov (United States)

    Shen, Shijian; Nie, Xin; Zhang, Xinggan

    2018-02-03

    Gaofen-3 (GF-3) is China' first C-band multi-polarization synthetic aperture radar (SAR) satellite, which also provides the sliding spotlight mode for the first time. Sliding-spotlight mode is a novel mode to realize imaging with not only high resolution, but also wide swath. Several key technologies for sliding spotlight mode in spaceborne SAR with high resolution are investigated in this paper, mainly including the imaging parameters, the methods of velocity estimation and ambiguity elimination, and the imaging algorithms. Based on the chosen Convolution BackProjection (CBP) and PFA (Polar Format Algorithm) imaging algorithms, a fast implementation method of CBP and a modified PFA method suitable for sliding spotlight mode are proposed, and the processing flows are derived in detail. Finally, the algorithms are validated by simulations and measured data.

  2. Computational efficient unsupervised coastline detection from single-polarization 1-look SAR images of complex coastal environments

    Science.gov (United States)

    Garzelli, Andrea; Zoppetti, Claudia; Pinelli, Gianpaolo

    2017-10-01

    Coastline detection in synthetic aperture radar (SAR) images is crucial in many application fields, from coastal erosion monitoring to navigation, from damage assessment to security planning for port facilities. The backscattering difference between land and sea is not always documented in SAR imagery, due to the severe speckle noise, especially in 1-look data with high spatial resolution, high sea state, or complex coastal environments. This paper presents an unsupervised, computationally efficient solution to extract the coastline acquired by only one single-polarization 1-look SAR image. Extensive tests on Spotlight COSMO-SkyMed images of complex coastal environments and objective assessment demonstrate the validity of the proposed procedure which is compared to state-of-the-art methods through visual results and with an objective evaluation of the distance between the detected and the true coastline provided by regional authorities.

  3. Using Multi Resolution Census and Ranklet Transformation in Long Base Line SAR Image Matching

    Science.gov (United States)

    Ghannadi, M. A.; Saadat Seresht, M.; Motagh, M.; Eftekhari, A.

    2013-09-01

    Stereo radargrammetry is a mature technique for deriving height information from SAR image pairs. Generally height derived method by Radargrammetry consists of two stages: Images matching and space intersection. In this paper we propose a multi-step image matching algorithm founded on feature based matching. In this multi step algorithm, a SAR image is firstly filtered by a speckle suppression algorithm. a SIFT (Scale invariant feature transform) is used to extract feature points. Then we use non parametric Transformation as discriptor for the points extracted. Matching is sometimes more efficient when operating on image signals that have been transformed in some way, rather than operating on the pure intensity values themselves; In this article we use a pair of spotlight long base line TerraSAR-X images from JAM (IRAN). In a part with 700 × 700 pixels of these images 90 points are matched with using Ranklet algorithm. The mean absolute error of the corresponding points is 0.9 pixel. This match points number is 49 points with using multi resolution Census. The result shows that our proposed multi step image matching is superior to the Most FBM methods in terms of accuracy and number of matched points.

  4. USING MULTI RESOLUTION CENSUS AND RANKLET TRANSFORMATION IN LONG BASE LINE SAR IMAGE MATCHING

    Directory of Open Access Journals (Sweden)

    M. A. Ghannadi

    2013-09-01

    Full Text Available Stereo radargrammetry is a mature technique for deriving height information from SAR image pairs. Generally height derived method by Radargrammetry consists of two stages: Images matching and space intersection. In this paper we propose a multi-step image matching algorithm founded on feature based matching. In this multi step algorithm, a SAR image is firstly filtered by a speckle suppression algorithm. a SIFT (Scale invariant feature transform is used to extract feature points. Then we use non parametric Transformation as discriptor for the points extracted. Matching is sometimes more efficient when operating on image signals that have been transformed in some way, rather than operating on the pure intensity values themselves; In this article we use a pair of spotlight long base line TerraSAR-X images from JAM (IRAN. In a part with 700 × 700 pixels of these images 90 points are matched with using Ranklet algorithm. The mean absolute error of the corresponding points is 0.9 pixel. This match points number is 49 points with using multi resolution Census. The result shows that our proposed multi step image matching is superior to the Most FBM methods in terms of accuracy and number of matched points.

  5. 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.

  6. SAR Image despeckling via sparse representation

    Science.gov (United States)

    Wang, Zhongmei; Yang, Xiaomei; Zheng, Liang

    2014-11-01

    SAR image despeckling is an active research area in image processing due to its importance in improving the quality of image for object detection and classification.In this paper, a new approach is proposed for multiplicative noise in SAR image removal based on nonlocal sparse representation by dictionary learning and collaborative filtering. First, a image is divided into many patches, and then a cluster is formed by clustering log-similar image patches using Fuzzy C-means (FCM). For each cluster, an over-complete dictionary is computed using the K-SVD method that iteratively updates the dictionary and the sparse coefficients. The patches belonging to the same cluster are then reconstructed by a sparse combination of the corresponding dictionary atoms. The reconstructed patches are finally collaboratively aggregated to build the denoised image. The experimental results show that the proposed method achieves much better results than many state-of-the-art algorithms in terms of both objective evaluation index (PSNR and ENL) and subjective visual perception.

  7. 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

  8. High Resolution Processing with an Active Phased Array SAR

    NARCIS (Netherlands)

    Nijenboer, F.J.; Otten, M.P.G.

    1999-01-01

    The Dutch PHARUS system is a polarimetric active phased array SAR capable of performing advanced SAR modes. Advanced SAR modes that are being investigated are: spotlight SAR, sliding spotlight SAR, stepped frequency SAR and interferometric SAR. The flight experiments and automatic beam steering

  9. An Objective Evaluation of Four SAR Image Segmentation Algorithms

    National Research Council Canada - National Science Library

    Gregga, Jason

    2001-01-01

    .... A key step towards automated SAR image analysis is image segmentation. There are many segmentation algorithms, but they have not been tested on a common set of images, and there are no standard test methods...

  10. 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.

  11. Mitigating illumination gradients in a SAR image based on the image data and antenna beam pattern

    Science.gov (United States)

    Doerry, Armin W.

    2013-04-30

    Illumination gradients in a synthetic aperture radar (SAR) image of a target can be mitigated by determining a correction for pixel values associated with the SAR image. This correction is determined based on information indicative of a beam pattern used by a SAR antenna apparatus to illuminate the target, and also based on the pixel values associated with the SAR image. The correction is applied to the pixel values associated with the SAR image to produce corrected pixel values that define a corrected SAR image.

  12. Analysis of phenological changes of high vegetation in amplitude images of SAR time series

    Science.gov (United States)

    Ihrig, Ramona; Kuny, Silvia; Thiele, Antje; Hinz, Stefan

    2017-10-01

    In the task of damage detection based on SAR imagery, the handling of the textural similarity between heaps of debris surrounding damaged buildings and high vegetation poses to be a challenge. However, in previous work we showed that features exist that are sensitive to the small but distinct textural difference. Since, those analyses were based on a single data set containing only one phenological state of the vegetation, we have to analyze the stability of the textural feature used for separation. In this paper, based on one time series the variation of the SAR signature of high vegetation, especially forest areas, is studied due to phenological changes. The data are high resolution Spotlight amplitude images of TerraSAR-X, because similar data are used for damage detection. The considered textural features are statistical features of the first order as well as Haralick features. The evaluation is performed on non-overlapping patches in the forest areas and comprises the search of seasonal runs of the texture features. Additionally, the occurrence of deciduous and coniferous forests is analyzed to emphasize potential phenological differences between both species.

  13. Pre-Processes for Urban Areas Detection in SAR Images

    Science.gov (United States)

    Altay Açar, S.; Bayır, Ş.

    2017-11-01

    In this study, pre-processes for urban areas detection in synthetic aperture radar (SAR) images are examined. These pre-processes are image smoothing, thresholding and white coloured regions determination. Image smoothing is carried out to remove noises then thresholding is applied to obtain binary image. Finally, candidate urban areas are detected by using white coloured regions determination. All pre-processes are applied by utilizing the developed software. Two different SAR images which are acquired by TerraSAR-X are used in experimental study. Obtained results are shown visually.

  14. SAR moving target imaging using sparse and low-rank decomposition

    Science.gov (United States)

    Ni, Kang-Yu; Rao, Shankar

    2014-05-01

    We propose a method to image a complex scene with spotlight synthetic aperture radar (SAR) despite the presence of multiple moving targets. Many recent methods use sparsity-based reconstruction coupled with phase error corrections of moving targets to reconstruct stationary scenes. However, these methods rely on the assumption that the scene itself is sparse and thus unfortunately cannot handle realistic SAR scenarios with complex backgrounds consisting of more than just a few point targets. Our method makes use of sparse and low-rank (SLR) matrix decomposition, an efficient method for decomposing a low-rank matrix and sparse matrix from their sum. For detecting the moving targets and reconstructing the stationary background, SLR uses a convex optimization model that penalizes the nuclear norm of the low rank background structure and the L1 norm of the sparse moving targets. We propose an L1-norm regularization reconstruction method to form the input data matrix, which is grossly corrupted by the moving targets. Each column of the input matrix is a reconstructed SAR image with measurements from a small number of azimuth angles. The use of the L1-norm regularization and a sparse transform permits us to reconstruct the scene with significantly fewer measurements so that moving targets are approximately stationary. We demonstrate our SLR-based approach using simulations adapted from the GOTCHA Volumetric SAR data set. These simulations show that SLR can accurately image multiple moving targets with different individual motions in complex scenes where methods that assume a sparse scene would fail.

  15. A beamforming algorithm for bistatic SAR image formation

    Science.gov (United States)

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

    2010-04-01

    Beamforming is a methodology for collection-mode-independent SAR image formation. It is essentially equivalent to backprojection. The authors have in previous papers developed this idea and discussed the advantages and disadvantages of the approach to monostatic SAR image formation vis-à-vis the more standard and time-tested polar formatting algorithm (PFA). In this paper we show that beamforming for bistatic SAR imaging leads again to a very simple image formation algorithm that requires a minimal number of lines of code and that allows the image to be directly formed onto a three-dimensional surface model, thus automatically creating an orthorectified image. The same disadvantage of beamforming applied to monostatic SAR imaging applies to the bistatic case, however, in that the execution time for the beamforming algorithm is quite long compared to that of PFA. Fast versions of beamforming do exist to help alleviate this issue. Results of image reconstructions from phase history data are presented.

  16. 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.

  17. Object Georeferencing in UAV-Based SAR Terrain Images

    OpenAIRE

    Łabowski Michał; Kaniewski Piotr; Serafin Piotr; Wajszczyk Bronisław

    2016-01-01

    Synthetic aperture radars (SAR) allow to obtain high resolution terrain images comparable with the resolution of optical methods. Radar imaging is independent on the weather conditions and the daylight. The process of analysis of the SAR images consists primarily of identifying of interesting objects. The ability to determine their geographical coordinates can increase usability of the solution from a user point of view. The paper presents a georeferencing method of the radar terrain images. ...

  18. Topography estimation using SAR image polarimetry

    Science.gov (United States)

    Sabry, Ramin; Mattar, Karim E.

    2014-10-01

    Polarization orientation angle (POA) correction to compensate for terrain effects on polarimetric SAR data has been investigated in the literature. POA rotation can be derived from digital elevation model (DEM) and/or from polarimetric SAR (PolSAR) data through covariance/coherency analysis. A robust analytic model connecting PolSAR data and products (e.g., POA) to target/scene terrain characteristics can serve two main objectives. First is to correct and calibrate PolSAR data acquired from different SARs when DEM is available. Second is to model terrain through inverse solution of POAs derived from PolSAR data analysis. This formalism has been developed and is presented here. Effectiveness of the technique in providing both forward (POAs from DEM) and inverse (DEM from POAs) solutions is explored through imagery product examples and simulations.

  19. 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.

  20. 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.

  1. 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.

  2. Raw Data-Based Motion Compensation for High-Resolution Sliding Spotlight Synthetic Aperture Radar.

    Science.gov (United States)

    Li, Ning; Niu, Shilin; Guo, Zhengwei; Liu, Yabo; Chen, Jiaqi

    2018-03-12

    For accurate motion compensation (MOCO) in airborne synthetic aperture radar (SAR) imaging, a high-precision inertial navigation system (INS) is required. However, an INS is not always precise enough or is sometimes not even included in airborne SAR systems. In this paper, a new, raw, data-based range-invariant motion compensation approach, which can effectively extract the displacements in the line-of-sight (LOS) direction, is proposed for high-resolution sliding spotlight SAR mode. In this approach, the sub-aperture radial accelerations of the airborne platform are estimated via a well-developed weighted total least square (WTLS) method considering the time-varying beam direction. The effectiveness of the proposed approach is validated by two airborne sliding spotlight C band SAR raw datasets containing different types of terrain, with a high spatial resolution of about 0.15 m in azimuth.

  3. Modeling amplitude SAR image with the Cauchy-Rayleigh mixture

    Science.gov (United States)

    Peng, Qiangqiang; Du, Qingyu; Yao, Yinwei; Huang, Huang

    2017-10-01

    In this paper, we introduce a novel mixture model of the SAR amplitude image, which is proposed as an approximation to the heavy-tailed Rayleigh model. The limitation of the heavy-tailed Rayleigh model in SAR image application is discussed. We also present an expectation-maximization (EM) algorithm based parameter estimation method for the Cauchy-Rayleigh mixture. We test the new model on some simulated data in order to confirm that is appropriate to the heavy-tailed Rayleigh model. The performance is evaluated by some statistic values (cumulative square errors (CSE) 0.99 and Kolmogorov-Smirnov distance (K-S) the performance of the proposed mixture model is tested on some real SAR images and compared with other models, including the heavy-tailed Rayleigh and Nakagami mixture models. The result indicates that the proposed model can be an optional statistical model for amplitude SAR images.

  4. 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.

  5. Visual Interpretation of SAR Images. (Visuele Interpretatie van SAR Beelden)

    National Research Council Canada - National Science Library

    Smith, A

    1999-01-01

    .... This project was a combined effort by TNO-FEL and TNO-TM. In the project polarimetric PHARUS images and high resolution RAMSES images were used for two experiments where people were tested for their ability to find targets and to interpret the terrain...

  6. Learning a Dilated Residual Network for SAR Image Despeckling

    Science.gov (United States)

    Zhang, Qiang; Yuan, Qiangqiang; Li, Jie; Yang, Zhen; Ma, Xiaoshuang

    2018-01-01

    In this paper, to break the limit of the traditional linear models for synthetic aperture radar (SAR) image despeckling, we propose a novel deep learning approach by learning a non-linear end-to-end mapping between the noisy and clean SAR images with a dilated residual network (SAR-DRN). SAR-DRN is based on dilated convolutions, which can both enlarge the receptive field and maintain the filter size and layer depth with a lightweight structure. In addition, skip connections and residual learning strategy are added to the despeckling model to maintain the image details and reduce the vanishing gradient problem. Compared with the traditional despeckling methods, the proposed method shows superior performance over the state-of-the-art methods on both quantitative and visual assessments, especially for strong speckle noise.

  7. Learning a Dilated Residual Network for SAR Image Despeckling

    Directory of Open Access Journals (Sweden)

    Qiang Zhang

    2018-01-01

    Full Text Available In this paper, to break the limit of the traditional linear models for synthetic aperture radar (SAR image despeckling, we propose a novel deep learning approach by learning a non-linear end-to-end mapping between the noisy and clean SAR images with a dilated residual network (SAR-DRN. SAR-DRN is based on dilated convolutions, which can both enlarge the receptive field and maintain the filter size and layer depth with a lightweight structure. In addition, skip connections and a residual learning strategy are added to the despeckling model to maintain the image details and reduce the vanishing gradient problem. Compared with the traditional despeckling methods, the proposed method shows a superior performance over the state-of-the-art methods in both quantitative and visual assessments, especially for strong speckle noise.

  8. Coastline detection with time series of SAR images

    Science.gov (United States)

    Ao, Dongyang; Dumitru, Octavian; Schwarz, Gottfried; Datcu, Mihai

    2017-10-01

    For maritime remote sensing, coastline detection is a vital task. With continuous coastline detection results from satellite image time series, the actual shoreline, the sea level, and environmental parameters can be observed to support coastal management and disaster warning. Established coastline detection methods are often based on SAR images and wellknown image processing approaches. These methods involve a lot of complicated data processing, which is a big challenge for remote sensing time series. Additionally, a number of SAR satellites operating with polarimetric capabilities have been launched in recent years, and many investigations of target characteristics in radar polarization have been performed. In this paper, a fast and efficient coastline detection method is proposed which comprises three steps. First, we calculate a modified correlation coefficient of two SAR images of different polarization. This coefficient differs from the traditional computation where normalization is needed. Through this modified approach, the separation between sea and land becomes more prominent. Second, we set a histogram-based threshold to distinguish between sea and land within the given image. The histogram is derived from the statistical distribution of the polarized SAR image pixel amplitudes. Third, we extract continuous coastlines using a Canny image edge detector that is rather immune to speckle noise. Finally, the individual coastlines derived from time series of .SAR images can be checked for changes.

  9. 3-D Target Location from Stereoscopic SAR Images

    Energy Technology Data Exchange (ETDEWEB)

    DOERRY,ARMIN W.

    1999-10-01

    SAR range-Doppler images are inherently 2-dimensional. Targets with a height offset lay over onto offset range and azimuth locations. Just which image locations are laid upon depends on the imaging geometry, including depression angle, squint angle, and target bearing. This is the well known layover phenomenon. Images formed with different aperture geometries will exhibit different layover characteristics. These differences can be exploited to ascertain target height information, in a stereoscopic manner. Depending on the imaging geometries, height accuracy can be on the order of horizontal position accuracies, thereby rivaling the best IFSAR capabilities in fine resolution SAR images. All that is required for this to work are two distinct passes with suitably different geometries from any plain old SAR.

  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. 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.

  12. Global Monitoring of Mountain Glaciers Using High-Resolution Spotlight Imaging from the International Space Station

    Science.gov (United States)

    Donnellan, A.; Green, J. J.; Bills, B. G.; Goguen, J.; Ansar, A.; Knight, R. L.; Hallet, B.; Scambos, T. A.; Thompson, L. G.; Morin, P. J.

    2013-12-01

    Mountain glaciers around the world are retreating rapidly, contributing about 20% to present-day sea level rise. Numerous studies have shown that mountain glaciers are sensitive to global environmental change. Temperate-latitude glaciers and snowpack provide water for over 1 billion people. Glaciers are a resource for irrigation and hydroelectric power, but also pose flood and avalanche hazards. Accurate mass balance assessments have been made for only 280 glaciers, yet there are over 130,000 in the World Glacier Inventory. The rate of glacier retreat or advance can be highly variable, is poorly sampled, and inadequately understood. Liquid water from ice front lakes, rain, melt, or sea water and debris from rocks, dust, or pollution interact with glacier ice often leading to an amplification of warming and further melting. Many mountain glaciers undergo rapid and episodic events that greatly change their mass balance or extent but are sparsely documented. Events include calving, outburst floods, opening of crevasses, or iceberg motion. Spaceborne high-resolution spotlight optical imaging provides a means of clarifying the relationship between the health of mountain glaciers and global environmental change. Digital elevation models (DEMs) can be constructed from a series of images from a range of perspectives collected by staring at a target during a satellite overpass. It is possible to collect imagery for 1800 targets per month in the ×56° latitude range, construct high-resolution DEMs, and monitor changes in high detail over time with a high-resolution optical telescope mounted on the International Space Station (ISS). Snow and ice type, age, and maturity can be inferred from different color bands as well as distribution of liquid water. Texture, roughness, albedo, and debris distribution can be estimated by measuring bidirectional reflectance distribution functions (BRDF) and reflectance intensity as a function of viewing angle. The non-sun-synchronous orbit

  13. UNSUPERVISED CHANGE DETECTION IN SAR IMAGES USING GAUSSIAN MIXTURE MODELS

    Directory of Open Access Journals (Sweden)

    E. Kiana

    2015-12-01

    Full Text Available In this paper, we propose a method for unsupervised change detection in Remote Sensing Synthetic Aperture Radar (SAR images. This method is based on the mixture modelling of the histogram of difference image. In this process, the difference image is classified into three classes; negative change class, positive change class and no change class. However the SAR images suffer from speckle noise, the proposed method is able to map the changes without speckle filtering. To evaluate the performance of this method, two dates of SAR data acquired by Uninhabited Aerial Vehicle Synthetic from an agriculture area are used. Change detection results show better efficiency when compared to the state-of-the-art methods.

  14. G0-WISHART Distribution Based Classification from Polarimetric SAR Images

    Science.gov (United States)

    Hu, G. C.; Zhao, Q. H.

    2017-09-01

    Enormous scientific and technical developments have been carried out to further improve the remote sensing for decades, particularly Polarimetric Synthetic Aperture Radar(PolSAR) technique, so classification method based on PolSAR images has getted much more attention from scholars and related department around the world. The multilook polarmetric G0-Wishart model is a more flexible model which describe homogeneous, heterogeneous and extremely heterogeneous regions in the image. Moreover, the polarmetric G0-Wishart distribution dose not include the modified Bessel function of the second kind. It is a kind of simple statistical distribution model with less parameter. To prove its feasibility, a process of classification has been tested with the full-polarized Synthetic Aperture Radar (SAR) image by the method. First, apply multilook polarimetric SAR data process and speckle filter to reduce speckle influence for classification result. Initially classify the image into sixteen classes by H/A/α decomposition. Using the ICM algorithm to classify feature based on the G0-Wshart distance. Qualitative and quantitative results show that the proposed method can classify polaimetric SAR data effectively and efficiently.

  15. High resolution deformation maps of Volcán de Colima, Mexico, derived from a year-long TerraSAR-X Spotlight time series

    Science.gov (United States)

    Salzer, Jacqueline; Nikkhoo, Mehdi; Walter, Thomas R.

    2015-04-01

    Volcán de Colima is a steep sloped explosive stratovolcano located in southern Central Mexico, and one of the most active volcanoes in North America. Major recent historical eruptions occured in 1818 (VEI 4) and 1913 (VEI 5), which removed several hundred meters from the summit of the volcanic edifice [1], and point towards the activity being marked by 100-year cycles which terminate in a large Plinian eruption. Also, five large flank collapse events have been identified during the Holocene [2]. Since the beginning of the most recent eruptiove period in 1998, the type of activity has been varying between predominantly explosive, dome building and dome collapse. Between 2007 and 2011, the activity at Colima was characterized by dome extrusion. The volcano then entered a period of low activity, which lasted until January 2013, when a series of explosions took place which initiated a new, still ongoing period of dome growth. The historical eruption of 1913, as well as the renewal of the activity in 2013, were both preceeded by longer periods of low activity, and only very limited short term precursors. The year 2012 at Volcán de Colima is therefore a good example to study volcanic activity in periods of quiescence, but leading up to an eruption. Furthermore, the possibility of a larger event in the future make it a particularly important volcano to study. We have acquired TerraSAR-X data in spotlight mode for ascending and descending tracks over Colima, obtaining a high spatial resolution of up to 2 m, and a temporal resolution of up to 11 days. Here we present the time series of the dome deformation between February and December 2012. We generated interferograms using an updated version of DORIS, accounting for the doppler variation in along track direction [3] and subsequently analysed the time series of the deformation pattern with the small baseline - persistent scatterer (PS) approach implemented in the StaMPS software. We removed the topographically correlated

  16. Single-Side Two-Location Spotlight Imaging for Building Based on MIMO Through-Wall-Radar

    Directory of Open Access Journals (Sweden)

    Yong Jia

    2016-09-01

    Full Text Available Through-wall-radar imaging is of interest for mapping the wall layout of buildings and for the detection of stationary targets within buildings. In this paper, we present an easy single-side two-location spotlight imaging method for both wall layout mapping and stationary target detection by utilizing multiple-input multiple-output (MIMO through-wall-radar. Rather than imaging for building walls directly, the images of all building corners are generated to speculate wall layout indirectly by successively deploying the MIMO through-wall-radar at two appropriate locations on only one side of the building and then carrying out spotlight imaging with two different squint-views. In addition to the ease of implementation, the single-side two-location squint-view detection also has two other advantages for stationary target imaging. The first one is the fewer multi-path ghosts, and the second one is the smaller region of side-lobe interferences from the corner images in comparison to the wall images. Based on Computer Simulation Technology (CST electromagnetic simulation software, we provide multiple sets of validation results where multiple binary panorama images with clear images of all corners and stationary targets are obtained by combining two single-location images with the use of incoherent additive fusion and two-dimensional cell-averaging constant-false-alarm-rate (2D CA-CFAR detection.

  17. 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...

  18. Polar format algorithm for SAR imaging with Matlab

    Science.gov (United States)

    Deming, Ross; Best, Matthew; Farrell, Sean

    2014-06-01

    Due to its computational efficiency, the polar format algorithm (PFA) is considered by many to be the workhorse for airborne synthetic aperture radar (SAR) imaging. PFA is implemented in spatial Fourier space, also known as "K-space", which is a convenient domain for understanding SAR performance metrics, sampling requirements, etc. In this paper the mathematics behind PFA are explained and computed examples are presented, both using simulated data, and experimental airborne radar data from the Air Force Research Laboratory (AFRL) Gotcha Challenge collect. In addition, a simple graphical method is described that can be used to model and predict wavefront curvature artifacts in PFA imagery, which are due to the limited validity of the underlying far-field approximation. The appendix includes Matlab code for computing SAR images using PFA.

  19. Unsupervised Classification of SAR Images using Hierarchical Agglomeration and EM

    NARCIS (Netherlands)

    K. Kayabol (Koray); V. Krylov; J. Zerubia; E. Salerno; A.E. Cetin; O. Salvetti

    2012-01-01

    htmlabstractWe implement an unsupervised classification algorithm for high resolution Synthetic Aperture Radar (SAR) images. The foundation of algorithm is based on Classification Expectation-Maximization (CEM). To get rid of two drawbacks of EM type algorithms, namely the initialization and the

  20. UWB front-end for SAR-based imaging system

    NARCIS (Netherlands)

    Monni, S.; Grooters, R.; Neto, A.; Nennie, F.A.

    2010-01-01

    A planarly fed UWB leaky lens antenna is presented integrated with wide band transmit and receive front-end electronics, to be used in a SAR-based imaging system. The unique non-dispersive characteristics of this antenna over a very wide bandwidth, together with the dual band front-end electronics

  1. An Advanced Rotation Invariant Descriptor for SAR Image Registration

    Directory of Open Access Journals (Sweden)

    Yuming Xiang

    2017-07-01

    Full Text Available The Scale-Invariant Feature Transform (SIFT algorithm and its many variants have been widely used in Synthetic Aperture Radar (SAR image registration. The SIFT-like algorithms maintain rotation invariance by assigning a dominant orientation for each keypoint, while the calculation of dominant orientation is not robust due to the effect of speckle noise in SAR imagery. In this paper, we propose an advanced local descriptor for SAR image registration to achieve rotation invariance without assigning a dominant orientation. Based on the improved intensity orders, we first divide a circular neighborhood into several sub-regions. Second, rotation-invariant ratio orientation histograms of each sub-region are proposed by accumulating the ratio values of different directions in a rotation-invariant coordinate system. The proposed descriptor is composed of the concatenation of the histograms of each sub-region. In order to increase the distinctiveness of the proposed descriptor, multiple image neighborhoods are aggregated. Experimental results on several satellite SAR images have shown an improvement in the matching performance over other state-of-the-art algorithms.

  2. 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.

  3. a SAR Image Registration Method Based on Sift Algorithm

    Science.gov (United States)

    Lu, W.; Yue, X.; Zhao, Y.; Han, C.

    2017-09-01

    In order to improve the stability and rapidity of synthetic aperture radar (SAR) images matching, an effective method was presented. Firstly, the adaptive smoothing filtering was employed for image denoising in image processing based on Wallis filtering to avoid the follow-up noise is amplified. Secondly, feature points were extracted by a simplified SIFT algorithm. Finally, the exact matching of the images was achieved with these points. Compared with the existing methods, it not only maintains the richness of features, but a-lso reduces the noise of the image. The simulation results show that the proposed algorithm can achieve better matching effect.

  4. Object Georeferencing in UAV-Based SAR Terrain Images

    Directory of Open Access Journals (Sweden)

    Łabowski Michał

    2016-12-01

    Full Text Available Synthetic aperture radars (SAR allow to obtain high resolution terrain images comparable with the resolution of optical methods. Radar imaging is independent on the weather conditions and the daylight. The process of analysis of the SAR images consists primarily of identifying of interesting objects. The ability to determine their geographical coordinates can increase usability of the solution from a user point of view. The paper presents a georeferencing method of the radar terrain images. The presented images were obtained from the SAR system installed on board an Unmanned Aerial Vehicle (UAV. The system was developed within a project under acronym WATSAR realized by the Military University of Technology and WB Electronics S.A. The source of the navigation data was an INS/GNSS system integrated by the Kalman filter with a feed-backward correction loop. The paper presents the terrain images obtained during flight tests and results of selected objects georeferencing with an assessment of the accuracy of the method.

  5. Mechanisms for SAR imaging of ocean surface phenomena: Theory and experiment

    Science.gov (United States)

    Vesecky, J. F.

    1983-01-01

    Understanding the SAR response to surface wave is a central issue in the analysis of SAR ocean images. The imaging mechanism for gravity waves and the practical question of just which characteristics of the ocean wave field can be measured remotely using SAR were examined. Assessments of wave imaging theory are based primarily on comparisons of the directional wave height variance spectrum psi (K) measured by in situ buoys with estimates from SAR images. Other criteria are also recommended, e.g., the effects of focus adjustments. It is assumed that fluctuations in SAR image intensity are proportional to fluctuations in ocean surface height. If this were true, the Fourier power spectrum of a SAR image and corresponding surface measurements of psi would coincide. Differences between SAR estimates based on this hypothesis and buoy measurements of psi are then used to begin the assessment of rival wave imaging theories.

  6. A New SAR Image Segmentation Algorithm for the Detection of Target and Shadow Regions

    Science.gov (United States)

    Huang, Shiqi; Huang, Wenzhun; Zhang, Ting

    2016-01-01

    The most distinctive characteristic of synthetic aperture radar (SAR) is that it can acquire data under all weather conditions and at all times. However, its coherent imaging mechanism introduces a great deal of speckle noise into SAR images, which makes the segmentation of target and shadow regions in SAR images very difficult. This paper proposes a new SAR image segmentation method based on wavelet decomposition and a constant false alarm rate (WD-CFAR). The WD-CFAR algorithm not only is insensitive to the speckle noise in SAR images but also can segment target and shadow regions simultaneously, and it is also able to effectively segment SAR images with a low signal-to-clutter ratio (SCR). Experiments were performed to assess the performance of the new algorithm on various SAR images. The experimental results show that the proposed method is effective and feasible and possesses good characteristics for general application. PMID:27924935

  7. SAR moving object imaging using sparsity imposing priors

    Science.gov (United States)

    Önhon, N. Özben; Çetin, Müjdat

    2017-12-01

    Synthetic aperture radar (SAR) returns from a scene with motion can be viewed as data from a stationary scene, but with phase errors due to motion. Based on this perspective, we formulate the problem of SAR imaging of motion-containing scenes as one of joint imaging and phase error compensation. The proposed method is based on the minimization of a cost function which involves sparsity-imposing regularization terms on the reflectivity field to be imaged, considering that it admits a sparse representation as well as on the spatial structure of the motion-related phase errors, reflecting the assumption that only a small percentage of the entire scene contains moving objects. To incorporate the spatial structure of the phase errors into the problem, we provide three different sparsity-enforcing prior terms. In order to achieve computational gains, we also present a two-step version of our approach, which first determines regions of interest that are likely to contain the moving objects and then applies our sparsity-driven approach for joint image reconstruction and autofocusing in such a spatially constrained setting. Our preliminary experiments demonstrate the effectiveness of this new moving target SAR imaging approach.

  8. Imaging manifestations of the cavitation in pulmonary parenchyma of SARS

    International Nuclear Information System (INIS)

    Yuan Chunwang; Zhao Dawei; Wang Wei; Jia Cuiyu; Bai Chunsheng

    2004-01-01

    Objective: To investigate the imaging appearances of cavitation in pulmonary parenchyma and the clinical features of the cases of SARS. Methods: Chest imaging films and clinical data of 180 patients with clinically confirmed SARS were analyzed retrospectively. The imaging manifestations of cavitation and the clinical features of the patients were observed and evaluated. Results: Of 180 patients, cavitations were showed in 5 (2.8%), which were all found through X-ray or CT scanning. Most of them were round or irregular, and had thick wall. The 5 patients all had been in hospital and treated with more dosage antibiotics, antivirus medicines and glucocorticoid for long time, the glucocorticoid was used for 25-65 d, and in the first 10-15 days the dosage was 160-240 mg per day. In hospitalization, one of them had been diagnosed diabetes mellitus, four had increased fasting blood sugar, the counts of white blood cells [(14.1-20.4) x 10 9 /L] increased significantly, the percent of neutrophils might increased also. Meanwhile, there was a continue increase of lactate dehydrogenase (228.00-475.00 U/L), glutamic dehydrogenase (10.08-60.00 U/L) and hydroxybutyrate dehydrogenase (190.00-444.00 U/L) in lab examination. Conclusion: SARS can cause cavitation in pulmonary parenchyma in posterior process of the disease. CT scanning can find the cavitation earlier and accurately, catching the imaging features of them is helpful in differential diagnosis, guiding therapy and estimating prognosis

  9. 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.

  10. Separated Component-Based Restoration of Speckled SAR Images

    Science.gov (United States)

    2013-01-01

    TYPE New Reprint 17. LIMITATION OF ABSTRACT UU 15. NUMBER OF PAGES 5d. PROJECT NUMBER 5e. TASK NUMBER 5f. WORK UNIT NUMBER 5c. PROGRAM ELEMENT...radar. I. INTRODUCTION COHERENT imaging systems such as synthetic aper -ture radar (SAR), holography, ultrasound, and synthetic aperture sonar suffer...noise variance by a factor of L. However, this often results in the reduction of the spatial resolution. Other types of speckle reduction methods are

  11. Circular SAR Optimization Imaging Method of Buildings

    Directory of Open Access Journals (Sweden)

    Wang Jian-feng

    2015-12-01

    Full Text Available The Circular Synthetic Aperture Radar (CSAR can obtain the entire scattering properties of targets because of its great ability of 360° observation. In this study, an optimal orientation of the CSAR imaging algorithm of buildings is proposed by applying a combination of coherent and incoherent processing techniques. FEKO software is used to construct the electromagnetic scattering modes and simulate the radar echo. The FEKO imaging results are compared with the isotropic scattering results. On comparison, the optimal azimuth coherent accumulation angle of CSAR imaging of buildings is obtained. Practically, the scattering directions of buildings are unknown; therefore, we divide the 360° echo of CSAR into many overlapped and few angle echoes corresponding to the sub-aperture and then perform an imaging procedure on each sub-aperture. Sub-aperture imaging results are applied to obtain the all-around image using incoherent fusion techniques. The polarimetry decomposition method is used to decompose the all-around image and further retrieve the edge information of buildings successfully. The proposed method is validated with P-band airborne CSAR data from Sichuan, China.

  12. Multi-Pixel Simultaneous Classification of PolSAR Image Using Convolutional Neural Networks

    OpenAIRE

    Lei Wang; Xin Xu; Hao Dong; Rong Gui; Fangling Pu

    2018-01-01

    Convolutional neural networks (CNN) have achieved great success in the optical image processing field. Because of the excellent performance of CNN, more and more methods based on CNN are applied to polarimetric synthetic aperture radar (PolSAR) image classification. Most CNN-based PolSAR image classification methods can only classify one pixel each time. Because all the pixels of a PolSAR image are classified independently, the inherent interrelation of different land covers is ignored. We us...

  13. Decreasing range resolution of a SAR image to permit correction of motion measurement errors beyond the SAR range resolution

    Science.gov (United States)

    Doerry, Armin W.; Heard, Freddie E.; Cordaro, J. Thomas

    2010-07-20

    Motion measurement errors that extend beyond the range resolution of a synthetic aperture radar (SAR) can be corrected by effectively decreasing the range resolution of the SAR in order to permit measurement of the error. Range profiles can be compared across the slow-time dimension of the input data in order to estimate the error. Once the error has been determined, appropriate frequency and phase correction can be applied to the uncompressed input data, after which range and azimuth compression can be performed to produce a desired SAR image.

  14. Object recognition of real targets using modelled SAR images

    Science.gov (United States)

    Zherdev, D. A.

    2017-12-01

    In this work the problem of recognition is studied using SAR images. The algorithm of recognition is based on the computation of conjugation indices with vectors of class. The support subspaces for each class are constructed by exception of the most and the less correlated vectors in a class. In the study we examine the ability of a significant feature vector size reduce that leads to recognition time decrease. The images of targets form the feature vectors that are transformed using pre-trained convolutional neural network (CNN).

  15. Scalable Track Detection in SAR CCD Images

    Energy Technology Data Exchange (ETDEWEB)

    Chow, James G [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Quach, Tu-Thach [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States)

    2017-03-01

    Existing methods to detect vehicle tracks in coherent change detection images, a product of combining two synthetic aperture radar images ta ken at different times of the same scene, rely on simple, fast models to label track pixels. These models, however, are often too simple to capture natural track features such as continuity and parallelism. We present a simple convolutional network architecture consisting of a series of 3-by-3 convolutions to detect tracks. The network is trained end-to-end to learn natural track features entirely from data. The network is computationally efficient and improves the F-score on a standard dataset to 0.988, up fr om 0.907 obtained by the current state-of-the-art method.

  16. GPU efficient SAR image despeckling using mixed norms

    Science.gov (United States)

    Özcan, Caner; Şen, Baha; Nar, Fatih

    2014-10-01

    Speckle noise which is inherent to Synthetic Aperture Radar (SAR) imaging obstructs various image exploitation tasks such as edge detection, segmentation, change detection, and target recognition. Therefore, speckle reduction is generally used as a first step which has to smooth out homogeneous regions while preserving edges and point scatterers. Traditional speckle reduction methods are fast and their memory consumption is insignificant. However, they are either good at smoothing homogeneous regions or preserving edges and point scatterers. State of the art despeckling methods are proposed to overcome this trade-off. However, they introduce another trade-off between denoising quality and resource consumption, thereby higher denoising quality requires higher computational load and/or memory consumption. In this paper, a local pixel-based total variation (TV) approach is proposed, which combines l2-norm and l1-norm in order to improve despeckling quality while keeping execution times reasonably short. Pixel-based approach allows efficient computation model with relatively low memory consumption. Their parallel implementations are also more efficient comparing to global TV approaches which generally require numerical solution of sparse linear systems. However, pixel-based approaches are trapped to local minima frequently hence despeckling quality is worse comparing to global TV approaches. Proposed method, namely mixed norm despeckling (MND), combines l2-norm and l1-norm in order to improve despeckling performance by alleviating local minima problem. All steps of the MND are parallelized using OpenMP on CPU and CUDA on GPU. Speckle reduction performance, execution time and memory consumption of the proposed method are shown using synthetic images and TerraSAR-X spot mode SAR images.

  17. OPTICAL-TO-SAR IMAGE REGISTRATION BASED ON GAUSSIAN MIXTURE MODEL

    Directory of Open Access Journals (Sweden)

    H. Wang

    2012-07-01

    Full Text Available Image registration is a fundamental in remote sensing applications such as inter-calibration and image fusion. Compared to other multi sensor image registration problems such as optical-to-IR, the registration for SAR and optical images has its specials. Firstly, the radiometric and geometric characteristics are different between SAR and optical images. Secondly, the feature extraction methods are heavily suffered with the speckle in SAR images. Thirdly, the structural information is more useful than the point features such as corners. In this work, we proposed a novel Gaussian Mixture Model (GMM based Optical-to-SAR image registration algorithm. The feature of line support region (LSR is used to describe the structural information and the orientation attributes are added into the GMM to avoid Expectation Maximization (EM algorithm falling into local extremum in feature sets matching phase. Through the experiments it proves that our algorithm is very robust for optical-to- SAR image registration problem.

  18. Ship Detection in GF-3 NSC Mode SAR Images

    Directory of Open Access Journals (Sweden)

    Liu Zeyu

    2017-10-01

    Full Text Available GF-3, the first C-band full-polarimetric Synthetic Aperture Radar (SAR satellite with a space resolution up to 1 m, has multiple strip and scan imaging modes. In this paper, we propose a maritime ship detection algorithm that detects ship targets via pixel classification in a Bayesian framework and employ effective enhancement methods to improve detection performance based on the data characteristics. We compare and analyze the results of detection experiments using the proposed algorithm with those of several Constant False Alarm Rate (CFAR algorithms. The experimental results verify the effectiveness of the proposed algorithm.

  19. Modified Multilook Cross Correlation technique for Doppler centroid estimation in SAR image signal processing

    Science.gov (United States)

    Bee Cheng, Sew

    Synthetic Aperture Radar (SAR) is one of the widely used remote sensing sensors which produces high resolution image by using advance signal processing technique. SAR managed to operate in all sorts of weather and cover wide range of area. To produce a high-quality image, accurate parameters such as Doppler centroid are required for precise SAR signal processing. In the azimuth matched filtering of SAR signal processing, Doppler centroid is an important azimuth parameter that helps to focus the image pixels. Doppler centroid has always been overlooked during SAR signal processing. It is due to the fact that estimation of Doppler centroid involved complicated calculation and increased computational load. Therefore, researcher used to apply only the approximate Doppler value which is not precise and cause defocus effort in the generated SAR image. In this study, several conventional Doppler centroid estimation algorithms are reviewed and developed using Matlab software program to extract the Doppler parameter from received SAR data, namely Spectrum Fit Algorithm, Wavelength Diversity Algorithm (WDA), Multilook Cross Correlation Algorithm (MLCC), and Multilook Beat Frequency Algorithm (MLBF). Two sets of SAR data are employed to evaluate the performance of each estimator, i.e. simulated point target data and RADARSAT-1 Vancouver scene raw data. These experiments gave a sense of accuracy for the estimated results together with computational time consumption. Point target is simulated to generate ideal case SAR data with pre-defined SAR system parameters.

  20. Focusing resonance signatures in ultra-wideband SAR images by allpass filtering.

    Science.gov (United States)

    Rau, R; McClellan, J H

    2000-01-01

    This correspondence shows that resonance signatures in ultra-wideband synthetic aperture radar (SAR) images, which are smeared out due to their late arrival time, can be focused and extracted by postfiltering the SAR images with special two-dimensional (2-D) allpass filters. A design algorithm for FIR approximations to the desired allpass filters based on radial slice approximations (RSA) is presented.

  1. 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.

  2. Urban Modelling Performance of Next Generation SAR Missions

    Science.gov (United States)

    Sefercik, U. G.; Yastikli, N.; Atalay, C.

    2017-09-01

    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.

  3. 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.

  4. 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.

  5. Convolutional Neural Network-based SAR Image Classification with Noisy Labels

    Directory of Open Access Journals (Sweden)

    Zhao Juanping

    2017-10-01

    Full Text Available SAR image classification is an important task in SAR image interpretation. Supervised learning methods, such as the Convolutional Neural Network (CNN, demand samples that are accurately labeled. However, this presents a major challenge in SAR image labeling. Due to their unique imaging mechanism, SAR images are seriously affected by speckle, geometric distortion, and incomplete structural information. Thus, SAR images have a strong non-intuitive property, which causes difficulties in SAR image labeling, and which results in the weakened learning and generalization performance of many classifiers (including CNN. In this paper, we propose a Probability Transition CNN (PTCNN for patch-level SAR image classification with noisy labels. Based on the classical CNN, PTCNN builds a bridge between noise-free labels and their noisy versions via a noisy-label transition layer. As such, we derive a new CNN model trained with a noisily labeled training dataset that can potentially revise noisy labels and improve learning capacity with noisily labeled data. We use a 16-class land cover dataset and the MSTAR dataset to demonstrate the effectiveness of our model. Our experimental results show the PTCNN model to be robust with respect to label noise and demonstrate its promising classification performance compared with the classical CNN model. Therefore, the proposed PTCNN model could lower the standards required regarding the quality of image labels and have a variety of practical applications.

  6. Multi-Pixel Simultaneous Classification of PolSAR Image Using Convolutional Neural Networks

    Directory of Open Access Journals (Sweden)

    Lei Wang

    2018-03-01

    Full Text Available Convolutional neural networks (CNN have achieved great success in the optical image processing field. Because of the excellent performance of CNN, more and more methods based on CNN are applied to polarimetric synthetic aperture radar (PolSAR image classification. Most CNN-based PolSAR image classification methods can only classify one pixel each time. Because all the pixels of a PolSAR image are classified independently, the inherent interrelation of different land covers is ignored. We use a fixed-feature-size CNN (FFS-CNN to classify all pixels in a patch simultaneously. The proposed method has several advantages. First, FFS-CNN can classify all the pixels in a small patch simultaneously. When classifying a whole PolSAR image, it is faster than common CNNs. Second, FFS-CNN is trained to learn the interrelation of different land covers in a patch, so it can use the interrelation of land covers to improve the classification results. The experiments of FFS-CNN are evaluated on a Chinese Gaofen-3 PolSAR image and other two real PolSAR images. Experiment results show that FFS-CNN is comparable with the state-of-the-art PolSAR image classification methods.

  7. Multi-Pixel Simultaneous Classification of PolSAR Image Using Convolutional Neural Networks.

    Science.gov (United States)

    Wang, Lei; Xu, Xin; Dong, Hao; Gui, Rong; Pu, Fangling

    2018-03-03

    Convolutional neural networks (CNN) have achieved great success in the optical image processing field. Because of the excellent performance of CNN, more and more methods based on CNN are applied to polarimetric synthetic aperture radar (PolSAR) image classification. Most CNN-based PolSAR image classification methods can only classify one pixel each time. Because all the pixels of a PolSAR image are classified independently, the inherent interrelation of different land covers is ignored. We use a fixed-feature-size CNN (FFS-CNN) to classify all pixels in a patch simultaneously. The proposed method has several advantages. First, FFS-CNN can classify all the pixels in a small patch simultaneously. When classifying a whole PolSAR image, it is faster than common CNNs. Second, FFS-CNN is trained to learn the interrelation of different land covers in a patch, so it can use the interrelation of land covers to improve the classification results. The experiments of FFS-CNN are evaluated on a Chinese Gaofen-3 PolSAR image and other two real PolSAR images. Experiment results show that FFS-CNN is comparable with the state-of-the-art PolSAR image classification methods.

  8. Severe Acute Respiratory Syndrome- SARS

    Indian Academy of Sciences (India)

    SARS – clinical features · Radiological features of lungs-showing progression of disease · cT Scan of SARS lungs · Imaging type,cost,therapy · SARS – Lung Pathology · SARS Pathology · SARS - Diagnosis · How did SARS spread ? Economics of Epidemics -SARS · How was SARS contained so fast ? Slide 16 · Slide 17.

  9. Fast Detection of Oil Spills and Ships Using SAR Images

    Directory of Open Access Journals (Sweden)

    Alberto Lupidi

    2017-03-01

    Full Text Available In this paper, we show the capabilities of a new maritime control system based on the processing of COSMO-SkyMed Synthetic Aperture Radar (SAR images. This system aims at fast detection of ships that may be responsible for illegal oil dumping. In particular, a novel detection algorithm based on the joint use of the significance parameter, wavelet correlator and a two-dimensional Constant False Alarm Rate (2D-CFAR is designed. Results show the effectiveness of such algorithms, which can be used by the maritime authorities to have a faster although still reliable response. The proposed algorithm, together with the short revisit time of the COSMO-SkyMed constellation, can help with tracking the scenario evolution from one acquisition to the next.

  10. Analysis of ROC on chest direct digital radiography (DR) after image processing in diagnosis of SARS

    Science.gov (United States)

    Lv, Guozheng; Lan, Rihui; Zeng, Qingsi; Zheng, Zhong

    2004-05-01

    The Severe Acute Respiratory Syndrome (SARS, also called Infectious Atypical Pneumonia), which initially broke out in late 2002, has threatened the public"s health seriously. How to confirm the patients contracting SARS becomes an urgent issue in diagnosis. This paper intends to evaluate the importance of Image Processing in the diagnosis on SARS at the early stage. Receiver Operating Characteristics (ROC) analysis has been employed in this study to compare the value of DR images in the diagnosis of SARS patients before and after image processing by Symphony Software supplied by E-Com Technology Ltd., and DR image study of 72 confirmed or suspected SARS patients were reviewed respectively. All the images taken from the studied patients were processed by Symphony. Both the original and processed images were taken into ROC analysis, based on which the ROC graph for each group of images has been produced as described below: For processed images: a = 1.9745, b = 1.4275, SA = 0.8714; For original images: a = 0.9066, b = 0.8310, SA = 0.7572; (a - intercept, b - slop, SA - Area below the curve). The result shows significant difference between the original images and processed images (P<0.01). In summary, the images processed by Symphony are superior to the original ones in detecting the opacity lesion, and increases the accuracy of SARS diagnosis.

  11. TerraSAR-X mission

    Science.gov (United States)

    Werninghaus, Rolf

    2004-01-01

    The TerraSAR-X is a German national SAR- satellite system for scientific and commercial applications. It is the continuation of the scientifically and technologically successful radar missions X-SAR (1994) and SRTM (2000) and will bring the national technology developments DESA and TOPAS into operational use. The space segment of TerraSAR-X is an advanced high-resolution X-Band radar satellite. The system design is based on a sound market analysis performed by Infoterra. The TerraSAR-X features an advanced high-resolution X-Band Synthetic Aperture Radar based on the active phased array technology which allows the operation in Spotlight-, Stripmap- and ScanSAR Mode with various polarizations. It combines the ability to acquire high resolution images for detailed analysis as well as wide swath images for overview applications. In addition, experimental modes like the Dual Receive Antenna Mode allow for full-polarimetric imaging as well as along track interferometry, i.e. moving target identification. The Ground Segment is optimized for flexible response to (scientific and commercial) User requests and fast image product turn-around times. The TerraSAR-X mission will serve two main goals. The first goal is to provide the strongly supportive scientific community with multi-mode X-Band SAR data. The broad spectrum of scientific application areas include Hydrology, Geology, Climatology, Oceanography, Environmental Monitoring and Disaster Monitoring as well as Cartography (DEM Generation) and Interferometry. The second goal is the establishment of a commercial EO-market in Europe which is driven by Infoterra. The commercial goal is the development of a sustainable EO-business so that the e.g. follow-on systems can be completely financed by industry from the profit. Due to its commercial potential, the TerraSAR-X project will be implemented based on a public-private partnership with the Astrium GmbH. This paper will describe first the mission objectives as well as the

  12. A Refined Algorithm On The Estimation Of Residual Motion Errors In Airborne SAR Images

    Science.gov (United States)

    Zhong, Xuelian; Xiang, Maosheng; Yue, Huanyin; Guo, Huadong

    2010-10-01

    Due to the lack of accuracy in the navigation system, residual motion errors (RMEs) frequently appear in the airborne SAR image. For very high resolution SAR imaging and repeat-pass SAR interferometry, the residual motion errors must be estimated and compensated. We have proposed a new algorithm before to estimate the residual motion errors for an individual SAR image. It exploits point-like targets distributed along the azimuth direction, and not only corrects the phase, but also improves the azimuth focusing. But the required point targets are selected by hand, which is time- and labor-consuming. In addition, the algorithm is sensitive to noises. In this paper, a refined algorithm is proposed aiming at these two shortcomings. With real X-band airborne SAR data, the feasibility and accuracy of the refined algorithm are demonstrated.

  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. Accelerating Spaceborne SAR Imaging Using Multiple CPU/GPU Deep Collaborative Computing.

    Science.gov (United States)

    Zhang, Fan; Li, Guojun; Li, Wei; Hu, Wei; Hu, Yuxin

    2016-04-07

    With the development of synthetic aperture radar (SAR) technologies in recent years, the huge amount of remote sensing data brings challenges for real-time imaging processing. Therefore, high performance computing (HPC) methods have been presented to accelerate SAR imaging, especially the GPU based methods. In the classical GPU based imaging algorithm, GPU is employed to accelerate image processing by massive parallel computing, and CPU is only used to perform the auxiliary work such as data input/output (IO). However, the computing capability of CPU is ignored and underestimated. In this work, a new deep collaborative SAR imaging method based on multiple CPU/GPU is proposed to achieve real-time SAR imaging. Through the proposed tasks partitioning and scheduling strategy, the whole image can be generated with deep collaborative multiple CPU/GPU computing. In the part of CPU parallel imaging, the advanced vector extension (AVX) method is firstly introduced into the multi-core CPU parallel method for higher efficiency. As for the GPU parallel imaging, not only the bottlenecks of memory limitation and frequent data transferring are broken, but also kinds of optimized strategies are applied, such as streaming, parallel pipeline and so on. Experimental results demonstrate that the deep CPU/GPU collaborative imaging method enhances the efficiency of SAR imaging on single-core CPU by 270 times and realizes the real-time imaging in that the imaging rate outperforms the raw data generation rate.

  15. Advanced L-Band SAR System Concepts for High-Resolution Ultra-Wide-Swath SAR Imaging

    OpenAIRE

    Krieger, Gerhard; Queiroz de Almeida, Felipe; Huber, Sigurd; Villano, Michelangelo; Younis, Marwan; Moreira, Alberto; del Castillo, Javier; Rodriguez-Cassola, Marc; Prats, Pau; Petrolati, Daniele; Ludwig, Michael; Buck, C.; Suess, Martin; Gebert, Nicolas

    2017-01-01

    This paper reviews multichannel SAR instrument architectures, modes and processing techniques for the imaging of ultra-wide swaths with high azimuth resolution. The review includes both direct radiating arrays and reflector-based system architectures that are operated in either a single-transmit multiple-receive (SIMO) or in a multiple-transmit multiple-receive (MIMO) mode. The work has been conducted by DLR under the ESA contract -Advanced Processing Techniques for Next Generation Multichann...

  16. Airborne SAR Real-time Imaging Algorithm Design and Implementation with CUDA on NVIDIA GPU

    Directory of Open Access Journals (Sweden)

    Meng Da-di

    2013-12-01

    Full Text Available Synthetic Aperture Radar (SAR image processing requires huge computation amount. Traditionally, this task runs on the workstation or server based on Central Processing Unit (CPU and is rather time-consuming, hence real-time processing of SAR data is impossible. Based on Compute Unified Device Architecture (CUDA technology, a new plan of SAR imaging algorithm operated on NVIDIA Graphic Processing Unit (GPU is proposed. The new proposal makes it possible that the data processing procedure and CPU/GPU data exchanging execute concurrently, especially when SAR data size exceeds total GPU global memory size. Multi-GPU is suitably supported by the new proposal and all of computational resources are fully exploited. It is shown by experiment on NVIDIA K20C and INTEL E5645 that the proposed solution accelerates SAR data processing by tens of times. Consequently, the GPU based SAR processing system with the proposed solution embedded is much more power saving and portable, which makes it qualified to be a real-time SAR data processing system. Experiment shows that SAR data of 36 Mega points can be processed in real-time per second by K20C with the new solution equipped.

  17. Segmentation-Based PolSAR Image Classification Using Visual Features: RHLBP and Color Features

    Directory of Open Access Journals (Sweden)

    Jian Cheng

    2015-05-01

    Full Text Available A segmentation-based fully-polarimetric synthetic aperture radar (PolSAR image classification method that incorporates texture features and color features is designed and implemented. This method is based on the framework that conjunctively uses statistical region merging (SRM for segmentation and support vector machine (SVM for classification. In the segmentation step, we propose an improved local binary pattern (LBP operator named the regional homogeneity local binary pattern (RHLBP to guarantee the regional homogeneity in PolSAR images. In the classification step, the color features extracted from false color images are applied to improve the classification accuracy. The RHLBP operator and color features can provide discriminative information to separate those pixels and regions with similar polarimetric features, which are from different classes. Extensive experimental comparison results with conventional methods on L-band PolSAR data demonstrate the effectiveness of our proposed method for PolSAR image classification.

  18. Ship Detection in SAR Image Based on the Alpha-stable Distribution.

    Science.gov (United States)

    Wang, Changcheng; Liao, Mingsheng; Li, Xiaofeng

    2008-08-22

    This paper describes an improved Constant False Alarm Rate (CFAR) ship detection algorithm in spaceborne synthetic aperture radar (SAR) image based on Alphastable distribution model. Typically, the CFAR algorithm uses the Gaussian distribution model to describe statistical characteristics of a SAR image background clutter. However, the Gaussian distribution is only valid for multilook SAR images when several radar looks are averaged. As sea clutter in SAR images shows spiky or heavy-tailed characteristics, the Gaussian distribution often fails to describe background sea clutter. In this study, we replace the Gaussian distribution with the Alpha-stable distribution, which is widely used in impulsive or spiky signal processing, to describe the background sea clutter in SAR images. In our proposed algorithm, an initial step for detecting possible ship targets is employed. Then, similar to the typical two-parameter CFAR algorithm, a local process is applied to the pixel identified as possible target. A RADARSAT-1 image is used to validate this Alpha-stable distribution based algorithm. Meanwhile, known ship location data during the time of RADARSAT-1 SAR image acquisition is used to validate ship detection results. Validation results show improvements of the new CFAR algorithm based on the Alpha-stable distribution over the CFAR algorithm based on the Gaussian distribution.

  19. Ship Detection in SAR Image Based on the Alpha-stable Distribution

    Directory of Open Access Journals (Sweden)

    Xiaofeng Li

    2008-08-01

    Full Text Available This paper describes an improved Constant False Alarm Rate (CFAR ship detection algorithm in spaceborne synthetic aperture radar (SAR image based on Alphastable distribution model. Typically, the CFAR algorithm uses the Gaussian distribution model to describe statistical characteristics of a SAR image background clutter. However, the Gaussian distribution is only valid for multilook SAR images when several radar looks are averaged. As sea clutter in SAR images shows spiky or heavy-tailed characteristics, the Gaussian distribution often fails to describe background sea clutter. In this study, we replace the Gaussian distribution with the Alpha-stable distribution, which is widely used in impulsive or spiky signal processing, to describe the background sea clutter in SAR images. In our proposed algorithm, an initial step for detecting possible ship targets is employed. Then, similar to the typical two-parameter CFAR algorithm, a local process is applied to the pixel identified as possible target. A RADARSAT-1 image is used to validate this Alpha-stable distribution based algorithm. Meanwhile, known ship location data during the time of RADARSAT-1 SAR image acquisition is used to validate ship detection results. Validation results show improvements of the new CFAR algorithm based on the Alpha-stable distribution over the CFAR algorithm based on the Gaussian distribution.

  20. Change Detection in SAR Images Based on Deep Semi-NMF and SVD Networks

    Directory of Open Access Journals (Sweden)

    Feng Gao

    2017-05-01

    Full Text Available With the development of Earth observation programs, more and more multi-temporal synthetic aperture radar (SAR data are available from remote sensing platforms. Therefore, it is demanding to develop unsupervised methods for SAR image change detection. Recently, deep learning-based methods have displayed promising performance for remote sensing image analysis. However, these methods can only provide excellent performance when the number of training samples is sufficiently large. In this paper, a novel simple method for SAR image change detection is proposed. The proposed method uses two singular value decomposition (SVD analyses to learn the non-linear relations between multi-temporal images. By this means, the proposed method can generate more representative feature expressions with fewer samples. Therefore, it provides a simple yet effective way to be designed and trained easily. Firstly, deep semi-nonnegative matrix factorization (Deep Semi-NMF is utilized to select pixels that have a high probability of being changed or unchanged as samples. Next, image patches centered at these sample pixels are generated from the input multi-temporal SAR images. Then, we build SVD networks, which are comprised of two SVD convolutional layers and one histogram feature generation layer. Finally, pixels in both multi-temporal SAR images are classified by the SVD networks, and then the final change map can be obtained. The experimental results of three SAR datasets have demonstrated the effectiveness and robustness of the proposed method.

  1. SAR Images Statistical Modeling and Classification Based on the Mixture of Alpha-Stable Distributions

    Directory of Open Access Journals (Sweden)

    Fangling Pu

    2013-05-01

    Full Text Available This paper proposes the mixture of Alpha-stable (MAS distributions for modeling statistical property of Synthetic Aperture Radar (SAR images in a supervised Markovian classification algorithm. Our work is motivated by the fact that natural scenes consist of various reflectors with different types that are typically concentrated within a small area, and SAR images generally exhibit sharp peaks, heavy tails, and even multimodal statistical property, especially at high resolution. Unimodal distributions do not fit such statistical property well, and thus a multimodal approach is necessary. Driven by the multimodality and impulsiveness of high resolution SAR images histogram, we utilize the mixture of Alpha-stable distributions to describe such characteristics. A pseudo-simulated annealing (PSA estimator based on Markov chain Monte Carlo (MCMC is present to efficiently estimate model parameters of the mixture of Alpha-stable distributions. To validate the proposed PSA estimator, we apply it to simulated data and compare its performance to that of a state-of-the-art estimator. Finally, we exploit the MAS distributions and a Markovian context for SAR images classification. The effectiveness of the proposed classifier is demonstrated by experiments on TerraSAR-X images, which verifies the validity of the MAS distributions for modeling and classification of SAR images.

  2. Pixel Classification of SAR ice images using ANFIS-PSO Classifier

    Directory of Open Access Journals (Sweden)

    G. Vasumathi

    2016-12-01

    Full Text Available Synthetic Aperture Radar (SAR is playing a vital role in taking extremely high resolution radar images. It is greatly used to monitor the ice covered ocean regions. Sea monitoring is important for various purposes which includes global climate systems and ship navigation. Classification on the ice infested area gives important features which will be further useful for various monitoring process around the ice regions. Main objective of this paper is to classify the SAR ice image that helps in identifying the regions around the ice infested areas. In this paper three stages are considered in classification of SAR ice images. It starts with preprocessing in which the speckled SAR ice images are denoised using various speckle removal filters; comparison is made on all these filters to find the best filter in speckle removal. Second stage includes segmentation in which different regions are segmented using K-means and watershed segmentation algorithms; comparison is made between these two algorithms to find the best in segmenting SAR ice images. The last stage includes pixel based classification which identifies and classifies the segmented regions using various supervised learning classifiers. The algorithms includes Back propagation neural networks (BPN, Fuzzy Classifier, Adaptive Neuro Fuzzy Inference Classifier (ANFIS classifier and proposed ANFIS with Particle Swarm Optimization (PSO classifier; comparison is made on all these classifiers to propose which classifier is best suitable for classifying the SAR ice image. Various evaluation metrics are performed separately at all these three stages.

  3. 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...

  4. 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...

  5. A novel SAR image precise-matching method based on SIFT algorithm

    Science.gov (United States)

    Yan, Wenwen; Li, Bin; Yang, Dekun; Tian, Jinwen; Yu, Qiong

    2013-10-01

    As for SAR image, it has a relatively great geometric distortion, and contains a lot of speckle noise. So a lot of research has been done to find a good method for SAR image matching. SIFT (Scale Invariant Feature Transform) has been proved to a good algorithm for the SAR image matching. This operator can dispose of matching problem such as rotation, affine distortion and noise. In this passage, firstly, in the preprocessing process, we use BM3D to denoise the image which can perform well comparing to other denoise method. Then, regardless of traditional SIFT-RANSAC method, SIFT-TC is used to complete image matching. By using this method, the image matching is proved to have better predominance in the matching efficiency, speed and robustness.

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

    Directory of Open Access Journals (Sweden)

    Ze Yu

    2016-07-01

    Full Text Available 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.

  7. ERROR ESTIMATION AND UNAMBIGUOUS RECONSTRUCTION FOR CHINESE FIRST DUAL-CHANNEL SPACEBORNE SAR IMAGING

    Directory of Open Access Journals (Sweden)

    T. Jin

    2017-09-01

    Full Text Available Multichannel synthetic aperture radar (SAR is a significant breakthrough to the inherent limitation between high-resolution and wide-swath (HRWS faced with conventional SAR. Error estimation and unambiguous reconstruction are two crucial techniques for obtaining high-quality imagery. This paper demonstrates the experimental results of the two techniques for Chinese first dualchannel spaceborne SAR imaging. The model of Chinese Gaofen-3 dual-channel mode is established and the mechanism of channel mismatches is first discussed. Particularly, we propose a digital beamforming (DBF process composed of the subspace-based error estimation algorithm and the reconstruction algorithm before imaging. The results exhibit the effective suppression of azimuth ambiguities with the proposed DBF process, and indicate the feasibility of this technique for future HRWS SAR systems.

  8. Tie Point Extraction for SAR Images with Same Side-looking Direction from Different Trajectories Based on Differential Constraints

    Directory of Open Access Journals (Sweden)

    JIN Guowang

    2018-01-01

    Full Text Available In order to extract tie points for SAR image block adjustment automatically and steadily,a method of tie point extraction based on differential constraints for SAR images with same side-looking direction from different trajectories is presented.It is aiming at SAR images with same side-looking direction and approximately parallel tracks,whose relative geometric distortion is small in azimuth and large in range.Firstly,image pyramids are built for two SAR images,and then these images are matched with correlation coefficient calculated by rectangular window with increased azimuth side from the top layer to the bottom layer.Mismatched points are removed by RANSAC algorithm with differential constraints.Coordinates for points in lower pyramid images are estimated with global bilinear transformation model in azimuth and local bilinear transformation model in range.Experiments performed on Envisat ASAR images and Chinese airborne SAR images validated the proposed method.

  9. Feature Fusion Based Road Extraction for HJ-1-C SAR Image

    Directory of Open Access Journals (Sweden)

    Lu Ping-ping

    2014-06-01

    Full Text Available Road network extraction in SAR images is one of the key tasks of military and civilian technologies. To solve the issues of road extraction of HJ-1-C SAR images, a road extraction algorithm is proposed based on the integration of ratio and directional information. Due to the characteristic narrow dynamic range and low signal to noise ratio of HJ-1-C SAR images, a nonlinear quantization and an image filtering method based on a multi-scale autoregressive model are proposed here. A road extraction algorithm based on information fusion, which considers ratio and direction information, is also proposed. By processing Radon transformation, main road directions can be extracted. Cross interferences can be suppressed, and the road continuity can then be improved by the main direction alignment and secondary road extraction. The HJ-1-C SAR image acquired in Wuhan, China was used to evaluate the proposed method. The experimental results show good performance with correctness (80.5% and quality (70.1% when applied to a SAR image with complex content.

  10. First Image Products from EcoSAR - Osa Peninsula, Costa Rica

    Science.gov (United States)

    Osmanoglu, Batuhan; Lee, SeungKuk; Rincon, Rafael; Fatuyinbo, Lola; Bollian, Tobias; Ranson, Jon

    2016-01-01

    Designed especially for forest ecosystem studies, EcoSAR employs state-of-the-art digital beamforming technology to generate wide-swath, high-resolution imagery. EcoSARs dual antenna single-pass imaging capability eliminates temporal decorrelation from polarimetric and interferometric analysis, increasing the signal strength and simplifying models used to invert forest structure parameters. Antennae are physically separated by 25 meters providing single pass interferometry. In this mode the radar is most sensitive to topography. With 32 active transmit and receive channels, EcoSARs digital beamforming is an order of magnitude more versatile than the digital beamforming employed on the upcoming NISAR mission. EcoSARs long wavelength (P-band, 435 MHz, 69 cm) measurements can be used to simulate data products for ESAs future BIOMASS mission, allowing scientists to develop algorithms before the launch of the satellite. EcoSAR can also be deployed to collect much needed data where BIOMASS satellite wont be allowed to collect data (North America, Europe and Arctic), filling in the gaps to keep a watchful eye on the global carbon cycle. EcoSAR can play a vital role in monitoring, reporting and verification schemes of internationals programs such as UN-REDD (United Nations Reducing Emissions from Deforestation and Degradation) benefiting global society. EcoSAR was developed and flown with support from NASA Earth Sciences Technology Offices Instrument Incubator Program.

  11. SAR image enhancement via post-correlation signal processing

    Science.gov (United States)

    Matthews, N. D.; Kaupp, V. H.; Waite, W. P.; Macdonald, H. C.

    1984-01-01

    Seventeen interpreters ranked sets of computer-generated radar imagery to assess the value of post-correlation processing on the interpretability of SAR (synthetic aperture radar) imagery. The post-correlation processing evaluated amounts to a nonlinear mapping of the signal exiting a digital correlator and allows full use of signal bandwidth for improving the spatial resolution or for noise reduction. The results indicate that it is reasonable to hypothesize an optimal SAR presentation format for specific applications even though this study was too limited to be specific.

  12. Estimation and Removing of Anisotropic Scattering for Multiaspect Polarimetric SAR Image

    Directory of Open Access Journals (Sweden)

    Li Yang

    2015-06-01

    Full Text Available Multiaspect Synthetic Aperture Radar (SAR can generate high resolution images and target scattering signatures in different azimuth angles from the coherent integration of all subaperture images. However, mixed anisotropic scatters limit the application of traditional imaging theory. Anisotropic scattering may introduce errors in polarimetric parameters by decreasing the reliability of terrain classification and detection of variability. Thus a method is proposed for estimating and removing anisotropic scattering in multiaspect polarimetric SAR images. The proposed algorithm is based on the maximum likelihood and likelihood-ratio tests for the two-class case, while considering the speckle effect, the mechanism of removing the anisotropic scattering, and the monotonicity of the Constant False Alarm Rate (CFAR detection function. We compare the polarimetric entropy before and after removing the anisotropic subapertures, and then validate the algorithm's potential in retrieving the target signature using a P-band quad-pol airborne SAR with circular trajectory.

  13. Target detection in SAR images via radiometric multi-resolution analysis

    Science.gov (United States)

    Hu, Jingwen; Xia, Gui-Song; Sun, Hong

    2013-10-01

    This paper presents a target detection method in synthetic aperture radar (SAR) images with radiometric multiresolution analysis (RMA). The idea is that target saliency can be efficiently computed by comparing the statistics of targets and those of the local background around them. In order to compute reliable statistics of targets, which usually involve a small number of pixels, RMA is adopted. The RMA preprocessing method performs well in stabilizing the statistical characteristics of SAR images. It can effectively restrain the speckle noise while keep the statistical characteristics of the original image. Based on the computed target saliency, adaptive decision thresholds are got by using the constant false alarm rate (CFAR) target detection framework. Our experiments on real SAR images show that the proposed method can achieve better performance compared with the traditional cell average-constant false alarm rate (CA-CFAR) method.

  14. Azimuth Ambiguities Removal in Littoral Zones Based on Multi-Temporal SAR Images

    Directory of Open Access Journals (Sweden)

    Xiangguang Leng

    2017-08-01

    Full Text Available Synthetic aperture radar (SAR is one of the most important techniques for ocean monitoring. Azimuth ambiguities are a real problem in SAR images today, which can cause performance degradation in SAR ocean applications. In particular, littoral zones can be strongly affected by land-based sources, whereas they are usually regions of interest (ROI. Given the presence of complexity and diversity in littoral zones, azimuth ambiguities removal is a tough problem. As SAR sensors can have a repeat cycle, multi-temporal SAR images provide new insight into this problem. A method for azimuth ambiguities removal in littoral zones based on multi-temporal SAR images is proposed in this paper. The proposed processing chain includes co-registration, local correlation, binarization, masking, and restoration steps. It is designed to remove azimuth ambiguities caused by fixed land-based sources. The idea underlying the proposed method is that sea surface is dynamic, whereas azimuth ambiguities caused by land-based sources are constant. Thus, the temporal consistence of azimuth ambiguities is higher than sea clutter. It opens up the possibilities to use multi-temporal SAR data to remove azimuth ambiguities. The design of the method and the experimental procedure are based on images from the Sentinel data hub of Europe Space Agency (ESA. Both Interferometric Wide Swath (IW and Stripmap (SM mode images are taken into account to validate the proposed method. This paper also presents two RGB composition methods for better azimuth ambiguities visualization. Experimental results show that the proposed method can remove azimuth ambiguities in littoral zones effectively.

  15. Target Detection in SAR Images Based on a Level Set Approach

    Energy Technology Data Exchange (ETDEWEB)

    Marques, Regis C.P.; Medeiros, Fatima N.S.; Ushizima, Daniela M.

    2008-09-01

    This paper introduces a new framework for point target detection in synthetic aperture radar (SAR) images. We focus on the task of locating reflective small regions using alevel set based algorithm. Unlike most of the approaches in image segmentation, we address an algorithm which incorporates speckle statistics instead of empirical parameters and also discards speckle filtering. The curve evolves according to speckle statistics, initially propagating with a maximum upward velocity in homogeneous areas. Our approach is validated by a series of tests on synthetic and real SAR images and compared with three other segmentation algorithms, demonstrating that it configures a novel and efficient method for target detection purpose.

  16. The recognition of extended targets - SAR images for level and hilly terrain

    Science.gov (United States)

    Stiles, J. A.; Frost, V. S.; Holtzman, J. C.; Shanmugam, K. S.

    1982-01-01

    Radar image simulation techniques are used to determine the character of SAR images of area-extensive targets, for the cases of flat underlying terrain and of moderate relief, with a view to the severity of elevation change effects on the detection and recognition of boundaries and shapes. The experiment, which demonstrated these effects on shapes and boundaries, was performed in order to establish Seasat-A SAR performance. Attention is given to the geometry/propagation effects in range perspective imaging that must be known for information extraction.

  17. Individual Building Extraction from TerraSAR-X Images Based on Ontological Semantic Analysis

    Directory of Open Access Journals (Sweden)

    Rong Gui

    2016-08-01

    Full Text Available Accurate building information plays a crucial role for urban planning, human settlements and environmental management. Synthetic aperture radar (SAR images, which deliver images with metric resolution, allow for analyzing and extracting detailed information on urban areas. In this paper, we consider the problem of extracting individual buildings from SAR images based on domain ontology. By analyzing a building scattering model with different orientations and structures, the building ontology model is set up to express multiple characteristics of individual buildings. Under this semantic expression framework, an object-based SAR image segmentation method is adopted to provide homogeneous image objects, and three categories of image object features are extracted. Semantic rules are implemented by organizing image object features, and the individual building objects expression based on an ontological semantic description is formed. Finally, the building primitives are used to detect buildings among the available image objects. Experiments on TerraSAR-X images of Foshan city, China, with a spatial resolution of 1.25 m × 1.25 m, have shown the total extraction rates are above 84%. The results indicate the ontological semantic method can exactly extract flat-roof and gable-roof buildings larger than 250 pixels with different orientations.

  18. Offshore Wind Resource Estimation in 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...

  19. A Comparative Analysis of Computed and Measured SAR Images of Complex Targets

    Science.gov (United States)

    2012-05-01

    catamaran ferry, “HSC Alboran”, showing the actual configuration. Figure 5: CAD model of the catamaran ferry HCS Alboran; top: original model, bottom...range 4.4 “Alboran”, a catamaran ferry Figure 21: Two measured SAR images of the catamaran ferry, “Alboran”; image captured at

  20. A CFAR algorithm for layover and shadow detection in InSAR images based on kernel density estimation

    Science.gov (United States)

    Qin, Xianxiang; Zhou, Shilin; Zou, Huanxin; Ren, Yun

    2013-07-01

    In this paper, a novel CFAR algorithm for detecting layover and shadow areas in Interferometric synthetic aperture radar (InSAR) images is proposed. Firstly, the probability density function (PDF) of the square root amplitude of InSAR image is estimated by the kernel density estimation. Then, a CFAR algorithm combining with the morphological method for detecting both layover and shadow is presented. Finally, the proposed algorithm is evaluated on a real InSAR image obtained by TerraSAR-X system. The experimental results have validated the effectiveness of the proposed method.

  1. Image Enhancement and Speckle Reduction of Full Polarimetric SAR Data by Gaussian Markov Random Field

    Science.gov (United States)

    Mahdian, M.; Motagh, M.; Akbari, V.

    2013-09-01

    In recent years, the use of Polarimetric Synthetic Aperture Radar (PolSAR) data in different applications dramatically has been increased. In SAR imagery an interference phenomenon with random behavior exists which is called speckle noise. The interpretation of data encounters some troubles due to the presence of speckle which can be considered as a multiplicative noise affecting all coherent imaging systems. Indeed, speckle degrade radiometric resolution of PolSAR images, therefore it is needful to perform speckle filtering on the SAR data type. Markov Random Field (MRF) has proven to be a powerful method for drawing out eliciting contextual information from remotely sensed images. In the present paper, a probability density function (PDF), which is fitted well with the PolSAR data based on the goodness-of-fit test, is first obtained for the pixel-wise analysis. Then the contextual smoothing is achieved with the MRF method. This novel speckle reduction method combines an advanced statistical distribution with spatial contextual information for PolSAR data. These two parts of information are combined based on weighted summation of pixel-wise and contextual models. This approach not only preserves edge information in the images, but also improves signal-to-noise ratio of the results. The method maintains the mean value of original signal in the homogenous areas and preserves the edges of features in the heterogeneous regions. Experiments on real medium resolution ALOS data from Tehran, and also high resolution full polarimetric SAR data over the Oberpfaffenhofen test-site in Germany, demonstrate the effectiveness of the algorithm compared with well-known despeckling methods.

  2. Mechanisms of SAR Imaging of Shallow Water Topography of the Subei Bank

    Directory of Open Access Journals (Sweden)

    Shuangshang Zhang

    2017-11-01

    Full Text Available In this study, the C-band radar backscatter features of the shallow water topography of Subei Bank in the Southern Yellow Sea are statistically investigated using 25 ENVISAT (Environmental Satellite ASAR (advanced synthetic aperture radar and ERS-2 (European Remote-Sensing Satellite-2 SAR images acquired between 2006 and 2010. Different bathymetric features are found on SAR imagery under different sea states. Under low to moderate wind speeds (3.1~6.3 m/s, the wide bright patterns with an average width of 6 km are shown and correspond to sea surface imprints of tidal channels formed by two adjacent sand ridges, while the sand ridges appear as narrower (only 1 km wide, fingerlike, quasi-linear features on SAR imagery in high winds (5.4~13.9 m/s. Two possible SAR imaging mechanisms of coastal bathymetry are proposed in the case where the flow is parallel to the major axes of tidal channels or sand ridges. When the surface Ekman current is opposite to the mean tidal flow, two vortexes will converge at the central line of the tidal channel in the upper layer and form a convergent zone over the sea surface. Thus, the tidal channels are shown as wide and bright stripes on SAR imagery. For the SAR imaging of sand ridges, all the SAR images were acquired at low tidal levels. In this case, the ocean surface waves are possibly broken up under strong winds when propagating from deep water to the shallower water, which leads to an increase of surface roughness over the sand ridges.

  3. An Azimuth Antenna Pattern Estimation Method Based on Doppler Spectrum in SAR Ocean Images.

    Science.gov (United States)

    Meng, Hui; Wang, Xiaoqing; Chong, Jinsong

    2018-04-03

    In synthetic aperture radar (SAR) ocean remote sensing, it is very difficult to estimate an accurate azimuth antenna pattern (AAP) from low-scattering SAR images without strong scattering targets. Therefore, an azimuth antenna pattern estimation method based on Doppler spectrum in SAR ocean images is proposed in this paper. In order to preserve the complete AAP information, an azimuth unweighted matched filter is used to re-image the SAR raw data in the proposed method. Then, the shape factor of AAP can be obtained by linear statistics of the relationship between Doppler center and edge frequency spectrum in Doppler spectrum of each distance gate. In addition, the impact of the uniformity and signal-to-noise ratio of SAR ocean images on the estimation results are also analyzed by simulation. Finally, the feasibility of proposed method is verified by data from ERS-2 (European remote sensing satellite (ERS) was the European Space Agency's first Earth-observing satellite). Experimental results show that the AAP estimated by proposed method has a good estimation result.

  4. Multi-Core DSP Based Parallel Architecture for FMCW SAR Real-Time Imaging

    Directory of Open Access Journals (Sweden)

    C. F. Gu

    2015-12-01

    Full Text Available This paper presents an efficient parallel processing architecture using multi-core Digital Signal Processor (DSP to improve the capability of real-time imaging for Frequency Modulated Continuous Wave Synthetic Aperture Radar (FMCW SAR. With the application of the proposed processing architecture, the imaging algorithm is modularized, and each module is efficiently realized by the proposed processing architecture. In each module, the data processing of different cores is executed in parallel, also the data transmission and data processing of each core are synchronously carried out, so that the processing time for SAR imaging is reduced significantly. Specifically, the time of corner turning operation, which is very time-consuming, is ignored under computationally intensive case. The proposed parallel architecture is applied to a compact Ku-band FMCW SAR prototype to achieve real-time imageries with 34 cm x 51 cm (range x azimuth resolution.

  5. 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.

  6. A NEW 2D OTSU FOR WATER EXTRACTION FROM SAR IMAGE

    Directory of Open Access Journals (Sweden)

    Y. Guo

    2017-09-01

    Full Text Available SAR image segmentation is a crucial step that heavily influences the performance of image interpretation. The texture factor to replace the neighborhood mean dimension in the traditional Otsu method is proposed in this work, aiming at the problem that the SAR image has unique characteristics and the original 2D Otsu method only considers the pixel neighborhood mean information. In this paper, TerraSAR image with the single band and single polarization is used to water extraction. Firstly, the semantic function is used to analyze the structural characteristics of the sample image to determine the optimal parameters of the texture information extraction. Then, calculate the textural measures such as contrast, entropy, homogeneity, mean and second moment based on gray level co-occurrence matrix(GLCM method. The results are compared with the artificially marked images and the results of the original 2D Otsu.The experimental results achieve higher objective values, which shows the proposed algorithm using texture factor has a high practical value for SAR Image water segmentation.

  7. Time domain SAR raw data simulation using CST and image focusing of 3D objects

    Science.gov (United States)

    Saeed, Adnan; Hellwich, Olaf

    2017-10-01

    This paper presents the use of a general purpose electromagnetic simulator, CST, to simulate realistic synthetic aperture radar (SAR) raw data of three-dimensional objects. Raw data is later focused in MATLAB using range-doppler algorithm. Within CST Microwave Studio a replica of TerraSAR-X chirp signal is incident upon a modeled Corner Reflector (CR) whose design and material properties are identical to that of the real one. Defining mesh and other appropriate settings reflected wave is measured at several distant points within a line parallel to the viewing direction. This is analogous to an array antenna and is synthesized to create a long aperture for SAR processing. The time domain solver in CST is based on the solution of differential form of Maxwells equations. Exported data from CST is arranged into a 2-d matrix of axis range and azimuth. Hilbert transform is applied to convert the real signal to complex data with phase information. Range compression, range cell migration correction (RCMC), and azimuth compression are applied in time domain to obtain the final SAR image. This simulation can provide valuable information to clarify which real world objects cause images suitable for high accuracy identification in the SAR images.

  8. Separated Component-Based Restoration of Speckled SAR Images

    Science.gov (United States)

    2014-01-01

    systems such as SAR, holography , ultra- sound, and synthetic aperture sonar suffer from a multiplicative noise known as speckle [1]. Speckle appears when...Award from the Office of Technology Commercialization, and an Outstanding GEMSTONE Mentor Award from the Honors College. He received the Outstanding...and Technology (University of London), London, England, in 1980 and 1984, respectively. From October 1984 to December 1984 he worked for IBM (UK) as a

  9. The artificial object detection and current velocity measurement using SAR ocean surface images

    Science.gov (United States)

    Alpatov, Boris; Strotov, Valery; Ershov, Maksim; Muraviev, Vadim; Feldman, Alexander; Smirnov, Sergey

    2017-10-01

    Due to the fact that water surface covers wide areas, remote sensing is the most appropriate way of getting information about ocean environment for vessel tracking, security purposes, ecological studies and others. Processing of synthetic aperture radar (SAR) images is extensively used for control and monitoring of the ocean surface. Image data can be acquired from Earth observation satellites, such as TerraSAR-X, ERS, and COSMO-SkyMed. Thus, SAR image processing can be used to solve many problems arising in this field of research. This paper discusses some of them including ship detection, oil pollution control and ocean currents mapping. Due to complexity of the problem several specialized algorithm are necessary to develop. The oil spill detection algorithm consists of the following main steps: image preprocessing, detection of dark areas, parameter extraction and classification. The ship detection algorithm consists of the following main steps: prescreening, land masking, image segmentation combined with parameter measurement, ship orientation estimation and object discrimination. The proposed approach to ocean currents mapping is based on Doppler's law. The results of computer modeling on real SAR images are presented. Based on these results it is concluded that the proposed approaches can be used in maritime applications.

  10. Ka-band InSAR Imaging and Analysis Based on IMU Data

    Directory of Open Access Journals (Sweden)

    Shi Jun

    2014-02-01

    Full Text Available Compared with other bands, the millimeter wave Interferometric Synthetic Aperture Radar (InSAR has high accuracy and small size, which is a hot topic in InSAR research. On the other hand, shorter wavelength causes difficulties in 2D imaging and interferometric phase extraction. In this study, the imaging and phase performance of the streaming Back Projection (BP method combined with IMU data are analyzed and discussed on the basis of actual Ka-band InSAR data. It is found that because the wavelength of the Ka-band is short, it is more sensitive to the antenna phase-center history. To ensure the phase-preserving capacity, the IMU data must be used with accurate motion error compensation. Furthermore, during data processing, we verify the flat-earth-removing capacity of the BP algorithm that calculates and compensates the master and slave antenna phase centers individually.

  11. A comparative study on methods of improving SCR for ship detection in SAR image

    Science.gov (United States)

    Lang, Haitao; Shi, Hongji; Tao, Yunhong; Ma, Li

    2017-10-01

    Knowledge about ship positions plays a critical role in a wide range of maritime applications. To improve the performance of ship detector in SAR image, an effective strategy is improving the signal-to-clutter ratio (SCR) before conducting detection. In this paper, we present a comparative study on methods of improving SCR, including power-law scaling (PLS), max-mean and max-median filter (MMF1 and MMF2), method of wavelet transform (TWT), traditional SPAN detector, reflection symmetric metric (RSM), scattering mechanism metric (SMM). The ability of SCR improvement to SAR image and ship detection performance associated with cell- averaging CFAR (CA-CFAR) of different methods are evaluated on two real SAR data.

  12. COUPLING REGULAR TESSELLATION WITH RJMCMC ALGORITHM TO SEGMENT SAR IMAGE WITH UNKNOWN NUMBER OF CLASSES

    Directory of Open Access Journals (Sweden)

    Y. Wang

    2016-06-01

    Full Text Available This paper presents a Synthetic Aperture Radar (SAR image segmentation approach with unknown number of classes, which is based on regular tessellation and Reversible Jump Markov Chain Monte Carlo (RJMCMC' algorithm. First of all, an image domain is portioned into a set of blocks by regular tessellation. The image is modeled on the assumption that intensities of its pixels in each homogeneous region satisfy an identical and independent Gamma distribution. By Bayesian paradigm, the posterior distribution is obtained to build the region-based image segmentation model. Then, a RJMCMC algorithm is designed to simulate from the segmentation model to determine the number of homogeneous regions and segment the image. In order to further improve the segmentation accuracy, a refined operation is performed. To illustrate the feasibility and effectiveness of the proposed approach, two real SAR image is tested.

  13. Discrimination of Oil Slicks and Lookalikes in Polarimetric SAR Images Using CNN.

    Science.gov (United States)

    Guo, Hao; Wu, Danni; An, Jubai

    2017-08-09

    Oil slicks and lookalikes (e.g., plant oil and oil emulsion) all appear as dark areas in polarimetric Synthetic Aperture Radar (SAR) images and are highly heterogeneous, so it is very difficult to use a single feature that can allow classification of dark objects in polarimetric SAR images as oil slicks or lookalikes. We established multi-feature fusion to support the discrimination of oil slicks and lookalikes. In the paper, simple discrimination analysis is used to rationalize a preferred features subset. The features analyzed include entropy, alpha, and Single-bounce Eigenvalue Relative Difference (SERD) in the C-band polarimetric mode. We also propose a novel SAR image discrimination method for oil slicks and lookalikes based on Convolutional Neural Network (CNN). The regions of interest are selected as the training and testing samples for CNN on the three kinds of polarimetric feature images. The proposed method is applied to a training data set of 5400 samples, including 1800 crude oil, 1800 plant oil, and 1800 oil emulsion samples. In the end, the effectiveness of the method is demonstrated through the analysis of some experimental results. The classification accuracy obtained using 900 samples of test data is 91.33%. It is here observed that the proposed method not only can accurately identify the dark spots on SAR images but also verify the ability of the proposed algorithm to classify unstructured features.

  14. Multichannel High Resolution Wide Swath SAR Imaging for Hypersonic Air Vehicle with Curved Trajectory.

    Science.gov (United States)

    Zhou, Rui; Sun, Jinping; Hu, Yuxin; Qi, Yaolong

    2018-01-31

    Synthetic aperture radar (SAR) equipped on the hypersonic air vehicle in near space has many advantages over the conventional airborne SAR. However, its high-speed maneuvering characteristics with curved trajectory result in serious range migration, and exacerbate the contradiction between the high resolution and wide swath. To solve this problem, this paper establishes the imaging geometrical model matched with the flight trajectory of the hypersonic platform and the multichannel azimuth sampling model based on the displaced phase center antenna (DPCA) technology. Furthermore, based on the multichannel signal reconstruction theory, a more efficient spectrum reconstruction model using discrete Fourier transform is proposed to obtain the azimuth uniform sampling data. Due to the high complexity of the slant range model, it is difficult to deduce the processing algorithm for SAR imaging. Thus, an approximate range model is derived based on the minimax criterion, and the optimal second-order approximate coefficients of cosine function are obtained using the two-population coevolutionary algorithm. On this basis, aiming at the problem that the traditional Omega-K algorithm cannot compensate the residual phase with the difficulty of Stolt mapping along the range frequency axis, this paper proposes an Exact Transfer Function (ETF) algorithm for SAR imaging, and presents a method of range division to achieve wide swath imaging. Simulation results verify the effectiveness of the ETF imaging algorithm.

  15. Pre-processing SAR image stream to facilitate compression for transport on bandwidth-limited-link

    Science.gov (United States)

    Rush, Bobby G.; Riley, Robert

    2015-09-29

    Pre-processing is applied to a raw VideoSAR (or similar near-video rate) product to transform the image frame sequence into a product that resembles more closely the type of product for which conventional video codecs are designed, while sufficiently maintaining utility and visual quality of the product delivered by the codec.

  16. Mini-SAR: An Imaging Radar for the Chandrayaan-1 Mission to the Moon

    Science.gov (United States)

    Spudis, Paul D.; Bussey, Ben; Lichtenberg, Chris; Marinelli, Bill; Nozette, Stewart

    2005-01-01

    The debate on the presence of ice at the poles of the Moon continues. We will fly a small imaging radar on the Indian Chandrayaan mission to the Moon, to be launched in September, 2007. Mini-SAR will map the scattering properties of the lunar poles, determining the presence and extent of polar ice.

  17. SAR and Infrared Image Fusion in Complex Contourlet Domain Based on Joint Sparse Representation

    Directory of Open Access Journals (Sweden)

    Wu Yiquan

    2017-08-01

    Full Text Available To investigate the problems of the large grayscale difference between infrared and Synthetic Aperture Radar (SAR images and their fusion image not being fit for human visual perception, we propose a fusion method for SAR and infrared images in the complex contourlet domain based on joint sparse representation. First, we perform complex contourlet decomposition of the infrared and SAR images. Then, we employ the KSingular Value Decomposition (K-SVD method to obtain an over-complete dictionary of the low-frequency components of the two source images. Using a joint sparse representation model, we then generate a joint dictionary. We obtain the sparse representation coefficients of the low-frequency components of the source images in the joint dictionary by the Orthogonal Matching Pursuit (OMP method and select them using the selection maximization strategy. We then reconstruct these components to obtain the fused low-frequency components and fuse the high-frequency components using two criteria——the coefficient of visual sensitivity and the degree of energy matching. Finally, we obtain the fusion image by the inverse complex contourlet transform. Compared with the three classical fusion methods and recently presented fusion methods, e.g., that based on the Non-Subsampled Contourlet Transform (NSCT and another based on sparse representation, the method we propose in this paper can effectively highlight the salient features of the two source images and inherit their information to the greatest extent.

  18. Semi-supervised Learning for Classification of Polarimetric SAR Images Based on SVM-Wishart

    Directory of Open Access Journals (Sweden)

    Hua Wen-qiang

    2015-02-01

    Full Text Available In this study, we propose a new semi-supervised classification method for Polarimetric SAR (PolSAR images, aiming at handling the issue that the number of train set is small. First, considering the scattering characters of PolSAR data, this method extracts multiple scattering features using target decomposition approach. Then, a semi-supervised learning model is established based on a co-training framework and Support Vector Machine (SVM. Both labeled and unlabeled data are utilized in this model to obtain high classification accuracy. Third, a recovery scheme based on the Wishart classifier is proposed to improve the classification performance. From the experiments conducted in this study, it is evident that the proposed method performs more effectively compared with other traditional methods when the number of train set is small.

  19. Wavelet-based SAR image despeckling and information extraction, using particle filter.

    Science.gov (United States)

    Gleich, Dusan; Datcu, Mihai

    2009-10-01

    This paper proposes a new-wavelet-based synthetic aperture radar (SAR) image despeckling algorithm using the sequential Monte Carlo method. A model-based Bayesian approach is proposed. This paper presents two methods for SAR image despeckling. The first method, called WGGPF, models a prior with Generalized Gaussian (GG) probability density function (pdf) and the second method, called WGMPF, models prior with a Generalized Gaussian Markov random field (GGMRF). The likelihood pdf is modeled using a Gaussian pdf. The GGMRF model is used because it enables texture parameter estimation. The prior is modeled using GG pdf, when texture parameters are not needed. A particle filter is used for drawing particles from the prior for different shape parameters of GG pdf. When the GGMRF prior is used, the particles are drawn from prior in order to estimate noise-free wavelet coefficients and for those coefficients the texture parameter is changed in order to obtain the best textural parameters. The texture parameters are changed for a predefined set of shape parameters of GGMRF. The particles with the highest weights represents the final noise-free estimate with corresponding textural parameters. The despeckling algorithms are compared with the state-of-the-art methods using synthetic and real SAR data. The experimental results show that the proposed despeckling algorithms efficiently remove noise and proposed methods are comparable with the state-of-the-art methods regarding objective measurements. The proposed WGMPF preserves textures of the real, high-resolution SAR images well.

  20. An efficient two-objective automatic SAR image segmentation framework using artificial immune system

    Science.gov (United States)

    Yang, Dongdong; Niu, Ruican; Fei, Rong; Jiang, Qiaoyong; Li, Hongye; Cao, Zijian

    2015-12-01

    Here, an efficient multi-objective automatic segmentation framework (MASF) is formulated and applied to synthetic aperture radar (SAR) image unsupervised classification. In the framework, three important issues are presented: 1) two reasonable image preprocessing techniques, including spatial filtering and watershed operator, are discussed at the initial stage of the framework; 2)then, an efficient immune multi-objective optimization algorithm with uniform clone, adaptive selection by online nondominated solutions, and dynamic deletion in diversity maintenance is proposed; 3 two very simple, but very efficient conflicting clustering validity indices are incorporated into the framework and simultaneously optimized. Two simulated SAR data and two complicated real images are used to quantitatively validate its effectiveness. In addition, four other state-of-the-art image segmentation methods are employed for comparison.

  1. 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.

  2. Geodetic SAR Tomography

    NARCIS (Netherlands)

    Zhu, Xiao Xiang; Montazeri, Sina; Gisinger, Christoph; Hanssen, R.F.; Bamler, Richard

    2016-01-01

    In this paper, we propose a framework referred to as 'geodetic synthetic aperture radar (SAR) tomography' that fuses the SAR imaging geodesy and tomographic SAR inversion (TomoSAR) approaches to obtain absolute 3-D positions of a large amount of natural scatterers. The methodology is applied on

  3. A comparison of SAR imaging algorithms for high-squint angle trajectories

    Science.gov (United States)

    Horvath, Matthew S.; Rigling, Brian D.

    2011-06-01

    This paper explores the effect of squint angle on the phase errors introduced by the linear phase assumption in the polar format algorithm for SAR imaging. The maximum scene radius for an allowable phase error is derived as a function of squint angle and other parameters. Simulated phase histories for a variety of squint angles are generated and imaged to demonstrate the bound and the effects encountered when it is exceeded.

  4. Probability Density Components Analysis: A New Approach to Treatment and Classification of SAR Images

    Directory of Open Access Journals (Sweden)

    Osmar Abílio de Carvalho Júnior

    2014-04-01

    Full Text Available Speckle noise (salt and pepper is inherent to synthetic aperture radar (SAR, which causes a usual noise-like granular aspect and complicates the image classification. In SAR image analysis, the spatial information might be a particular benefit for denoising and mapping classes characterized by a statistical distribution of the pixel intensities from a complex and heterogeneous spectral response. This paper proposes the Probability Density Components Analysis (PDCA, a new alternative that combines filtering and frequency histogram to improve the classification procedure for the single-channel synthetic aperture radar (SAR images. This method was tested on L-band SAR data from the Advanced Land Observation System (ALOS Phased-Array Synthetic-Aperture Radar (PALSAR sensor. The study area is localized in the Brazilian Amazon rainforest, northern Rondônia State (municipality of Candeias do Jamari, containing forest and land use patterns. The proposed algorithm uses a moving window over the image, estimating the probability density curve in different image components. Therefore, a single input image generates an output with multi-components. Initially the multi-components should be treated by noise-reduction methods, such as maximum noise fraction (MNF or noise-adjusted principal components (NAPCs. Both methods enable reducing noise as well as the ordering of multi-component data in terms of the image quality. In this paper, the NAPC applied to multi-components provided large reductions in the noise levels, and the color composites considering the first NAPC enhance the classification of different surface features. In the spectral classification, the Spectral Correlation Mapper and Minimum Distance were used. The results obtained presented as similar to the visual interpretation of optical images from TM-Landsat and Google Maps.

  5. The Role of Resolution in the Estimation of Fractal Dimension Maps From SAR Data

    Directory of Open Access Journals (Sweden)

    Gerardo Di Martino

    2017-12-01

    Full Text Available This work is aimed at investigating the role of resolution in fractal dimension map estimation, analyzing the role of the different surface spatial scales involved in the considered estimation process. The study is performed using a data set of actual Cosmo/SkyMed Synthetic Aperture Radar (SAR images relevant to two different areas, the region of Bidi in Burkina Faso and the city of Naples in Italy, acquired in stripmap and enhanced spotlight modes. The behavior of fractal dimension maps in the presence of areas with distinctive characteristics from the viewpoint of land-cover and surface features is discussed. Significant differences among the estimated maps are obtained in the presence of fine textural details, which significantly affect the fractal dimension estimation for the higher resolution spotlight images. The obtained results show that if we are interested in obtaining a reliable estimate of the fractal dimension of the observed natural scene, stripmap images should be chosen in view of both economic and computational considerations. In turn, the combination of fractal dimension maps obtained from stripmap and spotlight images can be used to identify areas on the scene presenting non-fractal behavior (e.g., urban areas. Along this guideline, a simple example of stripmap-spotlight data fusion is also presented.

  6. Exploiting Deep Matching and SAR Data for the Geo-Localization Accuracy Improvement of Optical Satellite Images

    Directory of Open Access Journals (Sweden)

    Nina Merkle

    2017-06-01

    Full Text Available Improving the geo-localization of optical satellite images is an important pre-processing step for many remote sensing tasks like monitoring by image time series or scene analysis after sudden events. These tasks require geo-referenced and precisely co-registered multi-sensor data. Images captured by the high resolution synthetic aperture radar (SAR satellite TerraSAR-X exhibit an absolute geo-location accuracy within a few decimeters. These images represent therefore a reliable source to improve the geo-location accuracy of optical images, which is in the order of tens of meters. In this paper, a deep learning-based approach for the geo-localization accuracy improvement of optical satellite images through SAR reference data is investigated. Image registration between SAR and optical images requires few, but accurate and reliable matching points. These are derived from a Siamese neural network. The network is trained using TerraSAR-X and PRISM image pairs covering greater urban areas spread over Europe, in order to learn the two-dimensional spatial shifts between optical and SAR image patches. Results confirm that accurate and reliable matching points can be generated with higher matching accuracy and precision with respect to state-of-the-art approaches.

  7. EXTRACTION OF COASTLINES WITH FUZZY APPROACH USING SENTINEL-1 SAR IMAGE

    Directory of Open Access Journals (Sweden)

    N. Demir

    2016-06-01

    Full Text Available Coastlines are important features for water resources, sea products, energy resources etc. Coastlines are changed dynamically, thus automated methods are necessary for analysing and detecting the changes along the coastlines. In this study, Sentinel-1 C band SAR image has been used to extract the coastline with fuzzy logic approach. The used SAR image has VH polarisation and 10x10m. spatial resolution, covers 57 sqkm area from the south-east of Puerto-Rico. Additionally, radiometric calibration is applied to reduce atmospheric and orbit error, and speckle filter is used to reduce the noise. Then the image is terrain-corrected using SRTM digital surface model. Classification of SAR image is a challenging task since SAR and optical sensors have very different properties. Even between different bands of the SAR sensors, the images look very different. So, the classification of SAR image is difficult with the traditional unsupervised methods. In this study, a fuzzy approach has been applied to distinguish the coastal pixels than the land surface pixels. The standard deviation and the mean, median values are calculated to use as parameters in fuzzy approach. The Mean-standard-deviation (MS Large membership function is used because the large amounts of land and ocean pixels dominate the SAR image with large mean and standard deviation values. The pixel values are multiplied with 1000 to easify the calculations. The mean is calculated as 23 and the standard deviation is calculated as 12 for the whole image. The multiplier parameters are selected as a: 0.58, b: 0.05 to maximize the land surface membership. The result is evaluated using airborne LIDAR data, only for the areas where LIDAR dataset is available and secondly manually digitized coastline. The laser points which are below 0,5 m are classified as the ocean points. The 3D alpha-shapes algorithm is used to detect the coastline points from LIDAR data. Minimum distances are calculated between the

  8. Potential and limitations of high resolution multitemporal sar images in river morphology

    Science.gov (United States)

    Mitidieri, Francesco; Nicolina Papa, Maria; Amitrano, Donato; Ruello, Giuseppe

    2017-04-01

    In this study we test the capability of satellite synthetic aperture radar (SAR) images to enrich the monitoring of river geomorphological processes. A case study on the Italian River Orco is presented; a set of 100 COSMO-SkyMed stripmap images (from October 2008 to December 2016) from Italian Space Agency was employed. All the data, acquired with medium look angle (almost 30°) and HH polarization for increasing the land-water contrast, were processed in order to calibrate, register and reduce the speckle effect. Moreover, the optimal weighting multi-temporal De Grandi filter was adopted to allow an effective extraction of the water surfaces contour. This method was applied to extract water contours over the entire historical series of SAR datasets available. Thanks to the generated information we were able to monitor the lateral dynamic of the water channels and infer on the relations between low or peak flow and river morphology. Multi-temporal SAR images were compared to orthophotos and in situ measurements (performed at the same time of a SAR acquisition) in terms of river features extraction (e.g. active channel, vegetated islands) and measurements of morphometric parameters (e.g. reach length, channel width, curvature and sinuosity). Results of this comparison highlighted the potential offered by the use of SAR technology, with some limitations. In particular, good performances were reached by the extraction of the active channel and vegetated island compared to the ones obtained using the orthophotos. On the other hand, some issues were encountered in extracting water surfaces where riffles exhibit surface waves having heights greater than the wavelength of the electromagnetic signal of SAR, which causes a low land-water contrast. Hence, given the high spatial (3 m) and temporal resolution (15 days) of SAR images and the all-weather all-time acquisition conditions, a significant enhancement in the river management capabilities is possible, in particular

  9. Saliency Map Generation for SAR Images with Bayes Theory and Heterogeneous Clutter Model

    Directory of Open Access Journals (Sweden)

    Deliang Xiang

    2017-12-01

    Full Text Available Saliency map generation in synthetic aperture radar (SAR imagery has become a promising research area, since it has a close relationship with quick potential target identification, rescue services, etc. Due to the multiplicative speckle noise and complex backscattering in SAR imagery, producing satisfying results is still challenging. This paper proposes a new saliency map generation approach for SAR imagery using Bayes theory and a heterogeneous clutter model, i.e., the G 0 model. With Bayes theory, the ratio of the probability density functions (PDFs in the target and background areas contributes to the saliency. Local and global background areas lead to different saliency measures, i.e., local saliency and global saliency, which are combined to make a final saliency measure. To measure the saliency of targets of different sizes, multiscale saliency enhancement is conducted with different region sizes of target and background areas. After collecting all of the salient regions in the image, the result is refined by considering the image’s immediate context. The saliency of regions that are far away from the focus of attention is suppressed. Experimental results with two single-polarization and two multi-polarization SAR images demonstrate that the proposed method has better speckle noise robustness, higher accuracy, and more stability in saliency map generation both with and without the complex background than state-of-the-art methods. The saliency map accuracy can achieve above 95% with four datasets, which is about 5–20% higher than other methods.

  10. Ship Detection in High-Resolution Dual-Polarization SAR Amplitude Images

    Directory of Open Access Journals (Sweden)

    Gui Gao

    2013-01-01

    Full Text Available A constant false alarm rate (CFAR detecting method for ships in high-resolution dual-polarization synthetic aperture radar (SAR amplitude images has been proposed in this paper. First, by the production of amplitude images from two polarimetric channels, a novel detector simply called the PMA detector has been constructed. We testified that the PMA detector could improve the signal-to-clutter ratio (SCR and make the discrimination of a ship from clutter more easily. Second, the PMA detector’s statistical model has been described by the well-known distribution when facing complex sea background. The experiments performed on measured dual-polarization TerraSAR-X images demonstrate the good performance of the proposed CFAR detecting method.

  11. MREG V1.1 : a multi-scale image registration algorithm for SAR applications.

    Energy Technology Data Exchange (ETDEWEB)

    Eichel, Paul H.

    2013-08-01

    MREG V1.1 is the sixth generation SAR image registration algorithm developed by the Signal Processing&Technology Department for Synthetic Aperture Radar applications. Like its predecessor algorithm REGI, it employs a powerful iterative multi-scale paradigm to achieve the competing goals of sub-pixel registration accuracy and the ability to handle large initial offsets. Since it is not model based, it allows for high fidelity tracking of spatially varying terrain-induced misregistration. Since it does not rely on image domain phase, it is equally adept at coherent and noncoherent image registration. This document provides a brief history of the registration processors developed by Dept. 5962 leading up to MREG V1.1, a full description of the signal processing steps involved in the algorithm, and a user's manual with application specific recommendations for CCD, TwoColor MultiView, and SAR stereoscopy.

  12. Patch diameter limits for tiered subaperture SAR image formation algorithms

    Science.gov (United States)

    Doerry, Armin W.

    1995-06-01

    Synthetic aperture radar image formation algorithms typically use transform techniques that often require trading between image resolution, algorithm efficiency, and focused image scene size limits. This is due to assumptions for the data such as simplified (often straight-line) flight paths, simplified imaging geometry, and simplified models for phase functions. Many errors in such assumptions are typically untreatable due to their dependance on both data domain positions and image domain positions. The result is that large scenes often require inefficient multiple image formation iterations, followed by a mosaicking operation of the focused image patches. One class of image formation algorithms that perform favorably divides the spatial and frequency apertures into subapertures, and perhaps those subapertures into sub- subapertures, and so on, in a tiered subaperture fashion. This allows a gradual shift from data domain into image domain that allows correcting many types of errors that limit other image formation algorithms, even in a dynamic motion environment, thereby allowing large focused image patches without mosaicking. This paper presents and compared focused patch diameter limits for tiered subaperture image formation algorithms, for various numbers of tiers of subapertures. Examples are given that show orders-of-magnitude improvement in non- mosaicked focused image patch size over traditional polar format processing, and that patch size limits increase with the number of tiers of subapertures, although with diminishing returns.

  13. Oil Spill Detection by SAR Images: Dark Formation Detection, Feature Extraction and Classification Algorithms

    Directory of Open Access Journals (Sweden)

    Konstantinos N. Topouzelis

    2008-10-01

    Full Text Available This paper provides a comprehensive review of the use of Synthetic Aperture Radar images (SAR for detection of illegal discharges from ships. It summarizes the current state of the art, covering operational and research aspects of the application. Oil spills are seriously affecting the marine ecosystem and cause political and scientific concern since they seriously effect fragile marine and coastal ecosystem. The amount of pollutant discharges and associated effects on the marine environment are important parameters in evaluating sea water quality. Satellite images can improve the possibilities for the detection of oil spills as they cover large areas and offer an economical and easier way of continuous coast areas patrolling. SAR images have been widely used for oil spill detection. The present paper gives an overview of the methodologies used to detect oil spills on the radar images. In particular we concentrate on the use of the manual and automatic approaches to distinguish oil spills from other natural phenomena. We discuss the most common techniques to detect dark formations on the SAR images, the features which are extracted from the detected dark formations and the most used classifiers. Finally we conclude with discussion of suggestions for further research. The references throughout the review can serve as starting point for more intensive studies on the subject.

  14. Oil Spill Detection by SAR Images: Dark Formation Detection, Feature Extraction and Classification Algorithms.

    Science.gov (United States)

    Topouzelis, Konstantinos N

    2008-10-23

    This paper provides a comprehensive review of the use of Synthetic Aperture Radar images (SAR) for detection of illegal discharges from ships. It summarizes the current state of the art, covering operational and research aspects of the application. Oil spills are seriously affecting the marine ecosystem and cause political and scientific concern since they seriously effect fragile marine and coastal ecosystem. The amount of pollutant discharges and associated effects on the marine environment are important parameters in evaluating sea water quality. Satellite images can improve the possibilities for the detection of oil spills as they cover large areas and offer an economical and easier way of continuous coast areas patrolling. SAR images have been widely used for oil spill detection. The present paper gives an overview of the methodologies used to detect oil spills on the radar images. In particular we concentrate on the use of the manual and automatic approaches to distinguish oil spills from other natural phenomena. We discuss the most common techniques to detect dark formations on the SAR images, the features which are extracted from the detected dark formations and the most used classifiers. Finally we conclude with discussion of suggestions for further research. The references throughout the review can serve as starting point for more intensive studies on the subject.

  15. Regional SAR Image Segmentation Based on Fuzzy Clustering with Gamma Mixture Model

    Science.gov (United States)

    Li, X. L.; Zhao, Q. H.; Li, Y.

    2017-09-01

    Most of stochastic based fuzzy clustering algorithms are pixel-based, which can not effectively overcome the inherent speckle noise in SAR images. In order to deal with the problem, a regional SAR image segmentation algorithm based on fuzzy clustering with Gamma mixture model is proposed in this paper. First, initialize some generating points randomly on the image, the image domain is divided into many sub-regions using Voronoi tessellation technique. Each sub-region is regarded as a homogeneous area in which the pixels share the same cluster label. Then, assume the probability of the pixel to be a Gamma mixture model with the parameters respecting to the cluster which the pixel belongs to. The negative logarithm of the probability represents the dissimilarity measure between the pixel and the cluster. The regional dissimilarity measure of one sub-region is defined as the sum of the measures of pixels in the region. Furthermore, the Markov Random Field (MRF) model is extended from pixels level to Voronoi sub-regions, and then the regional objective function is established under the framework of fuzzy clustering. The optimal segmentation results can be obtained by the solution of model parameters and generating points. Finally, the effectiveness of the proposed algorithm can be proved by the qualitative and quantitative analysis from the segmentation results of the simulated and real SAR images.

  16. Potential of TCPInSAR in Monitoring Linear Infrastructure with a Small Dataset of SAR Images: Application of the Donghai Bridge, China

    Directory of Open Access Journals (Sweden)

    Lei Zhang

    2018-03-01

    Full Text Available Reliably monitoring deformation associated with linear infrastructures, such as long-span bridges, is vitally important to assess their structural health. In this paper, we attempt to employ satellite interferometric synthetic aperture radar (InSAR to map the deformation of Donghai Bridge over a half of an annual cycle. The bridge, as the fourth longest cross-sea bridge in the world, located in the north of Hangzhou Bay, East China Sea where the featureless sea surface largely occupied the radar image raises challenges to accurately co-register the coherent points along the bridge. To tackle the issues due to co-registration and the limited number of synthetic aperture radar (SAR images, we adopt the termed temporarily-coherent point (TCP InSAR (TCPInSAR technique to process the radar images. TCPs that are not necessarily coherent during the whole observation period can be identified within every two SAR acquisitions during the co-registration procedure based on the statistics of azimuth and range offsets. In the process, co-registration is performed only using the offsets of these TCPs, leading to improved interferometric phases and the local Delaunay triangulation is used to construct point pairs to reduce the atmospheric artifacts along the bridge. With the TCPInSAR method the deformation rate along the bridge is estimated with no need of phase unwrapping. The achieved result reveals that the Donghai Bridge suffered a line-of-sight (LOS deformation rate up to −2.3 cm/year from January 2009 to July 2009 at the cable-stayed part, which is likely due to the thermal expansion of cables.

  17. Testing sensitivity of the LISFLOOD subgrid hydraulic model to SAR image derived information

    Science.gov (United States)

    Wood, Melissa; Bates, Paul; Neal, Jeff; Hostache, Renaud; Matgen, Patrick; Chini, Marco; Giustarini, Laura

    2013-04-01

    There has been much interest in the use of Synthetic Aperture Radar (SAR) images to indirectly estimate flood extent and flood elevation to aid the understanding of fluvial flood inundation processes. SAR remote sensing satellites are capable of all-weather day/night observations that can discriminate between land and smooth open water surfaces over large scales. By combining SAR derived information with 2D hydraulic models and terrain data, the mechanisms of flooding can be better simulated therefore enabling more accurate and reliable flood forecasting. The objective of this study is to test the sensitivity of a LISFLOOD subgrid 2D model to its main parameters (i.e. roughness coefficient, river bathymetry) using SAR derived flood extent maps. Because of SAR imaging techniques and processing steps used to derive the flood information, any SAR-derived flood extent image will contain inherent uncertainty. We therefore use the uncertainty of the SAR information to obtain a range of plausible parameters to test sensitivity of the hydraulic model. LISFLOOD is a distributed 2D model developed at the University of Bristol and designed for use with larger ungauged river catchments. The version used employs a subgrid procedure which allows any size of river channel below that of the grid resolution to be represented. This procedure has been shown to improve hydraulic connectivity within the modelled flooded area and thus improve flood prediction for data sparse areas. A hydrodynamic LISFLOOD subgrid model of the River Severn at Tewkesbury covering a domain area of 50x70km and including the confluence with a major tributary (the River Avon) will be utilised. A complete storm hydrograph will be used as inflow to the model to simulate the full flood event. Surveyed cross section and gauged daily flows are also available for the River Severn. Therefore, the model results using variable parameters can be compared against results obtained from ground observations to further

  18. Integrated Shoreline Extraction Approach with Use of Rasat MS and SENTINEL-1A SAR Images

    Science.gov (United States)

    Demir, N.; Oy, S.; Erdem, F.; Şeker, D. Z.; Bayram, B.

    2017-09-01

    Shorelines are complex ecosystems and highly important socio-economic environments. They may change rapidly due to both natural and human-induced effects. Determination of movements along the shoreline and monitoring of the changes are essential for coastline management, modeling of sediment transportation and decision support systems. Remote sensing provides an opportunity to obtain rapid, up-to-date and reliable information for monitoring of shoreline. In this study, approximately 120 km of Antalya-Kemer shoreline which is under the threat of erosion, deposition, increasing of inhabitants and urbanization and touristic hotels, has been selected as the study area. In the study, RASAT pansharpened and SENTINEL-1A SAR images have been used to implement proposed shoreline extraction methods. The main motivation of this study is to combine the land/water body segmentation results of both RASAT MS and SENTINEL-1A SAR images to improve the quality of the results. The initial land/water body segmentation has been obtained using RASAT image by means of Random Forest classification method. This result has been used as training data set to define fuzzy parameters for shoreline extraction from SENTINEL-1A SAR image. Obtained results have been compared with the manually digitized shoreline. The accuracy assessment has been performed by calculating perpendicular distances between reference data and extracted shoreline by proposed method. As a result, the mean difference has been calculated around 1 pixel.

  19. Unsupervised SAR Image Segmentation Based on a Hierarchical TMF Model in the Discrete Wavelet Domain for Sea Area Detection

    Directory of Open Access Journals (Sweden)

    Jiajing Wang

    2014-01-01

    Full Text Available Unsupervised synthetic aperture radar (SAR image segmentation is a fundamental preliminary processing step required for sea area detection in military applications. The purpose of this step is to classify large image areas into different segments to assist with identification of the sea area and the ship target within the image. The recently proposed triplet Markov field (TMF model has been successfully used for segmentation of nonstationary SAR images. This letter presents a hierarchical TMF model in the discrete wavelet domain of unsupervised SAR image segmentation for sea area detection, which we have named the wavelet hierarchical TMF (WHTMF model. The WHTMF model can precisely capture the global and local image characteristics in the two-pass computation of posterior distribution. The multiscale likelihood and the multiscale energy function are constructed to capture the intrascale and intrascale dependencies in a random field (X,U. To model the SAR data related to radar backscattering sources, the Gaussian distribution is utilized. The effectiveness of the proposed model for SAR image segmentation is evaluated using synthesized and real SAR data.

  20. Severe Acute Respiratory Syndrome- SARS

    Indian Academy of Sciences (India)

    Table of contents. Severe Acute Respiratory Syndrome- SARS · PowerPoint Presentation · Slide 3 · Global pattern of SARS epidemic · Slide 5 · SARS – clinical features · Radiological features of lungs-showing progression of disease · cT Scan of SARS lungs · Imaging type,cost,therapy · SARS – Lung Pathology.

  1. Two-dimensional Fast ESPRIT Algorithm for Linear Array SAR Imaging

    Directory of Open Access Journals (Sweden)

    Zhao Yi-chao

    2015-10-01

    Full Text Available The linear array Synthetic Aperture Radar (SAR system is a popular research tool, because it can realize three-dimensional imaging. However, owning to limitations of the aircraft platform and actual conditions, resolution improvement is difficult in cross-track and along-track directions. In this study, a twodimensional fast Estimation of Signal Parameters by Rotational Invariance Technique (ESPRIT algorithm for linear array SAR imaging is proposed to overcome these limitations. This approach combines the Gerschgorin disks method and the ESPRIT algorithm to estimate the positions of scatterers in cross and along-rack directions. Moreover, the reflectivity of scatterers is obtained by a modified pairing method based on “region growing”, replacing the least-squares method. The simulation results demonstrate the applicability of the algorithm with high resolution, quick calculation, and good real-time response.

  2. Aircraft Detection in High-Resolution SAR Images Based on a Gradient Textural Saliency Map

    Directory of Open Access Journals (Sweden)

    Yihua Tan

    2015-09-01

    Full Text Available This paper proposes a new automatic and adaptive aircraft target detection algorithm in high-resolution synthetic aperture radar (SAR images of airport. The proposed method is based on gradient textural saliency map under the contextual cues of apron area. Firstly, the candidate regions with the possible existence of airport are detected from the apron area. Secondly, directional local gradient distribution detector is used to obtain a gradient textural saliency map in the favor of the candidate regions. In addition, the final targets will be detected by segmenting the saliency map using CFAR-type algorithm. The real high-resolution airborne SAR image data is used to verify the proposed algorithm. The results demonstrate that this algorithm can detect aircraft targets quickly and accurately, and decrease the false alarm rate.

  3. Aircraft Detection in High-Resolution SAR Images Based on a Gradient Textural Saliency Map.

    Science.gov (United States)

    Tan, Yihua; Li, Qingyun; Li, Yansheng; Tian, Jinwen

    2015-09-11

    This paper proposes a new automatic and adaptive aircraft target detection algorithm in high-resolution synthetic aperture radar (SAR) images of airport. The proposed method is based on gradient textural saliency map under the contextual cues of apron area. Firstly, the candidate regions with the possible existence of airport are detected from the apron area. Secondly, directional local gradient distribution detector is used to obtain a gradient textural saliency map in the favor of the candidate regions. In addition, the final targets will be detected by segmenting the saliency map using CFAR-type algorithm. The real high-resolution airborne SAR image data is used to verify the proposed algorithm. The results demonstrate that this algorithm can detect aircraft targets quickly and accurately, and decrease the false alarm rate.

  4. Polarimetric SAR Image Classification Using Multiple-feature Fusion and Ensemble Learning

    Directory of Open Access Journals (Sweden)

    Sun Xun

    2016-12-01

    Full Text Available In this paper, we propose a supervised classification algorithm for Polarimetric Synthetic Aperture Radar (PolSAR images using multiple-feature fusion and ensemble learning. First, we extract different polarimetric features, including extended polarimetric feature space, Hoekman, Huynen, H/alpha/A, and fourcomponent scattering features of PolSAR images. Next, we randomly select two types of features each time from all feature sets to guarantee the reliability and diversity of later ensembles and use a support vector machine as the basic classifier for predicting classification results. Finally, we concatenate all prediction probabilities of basic classifiers as the final feature representation and employ the random forest method to obtain final classification results. Experimental results at the pixel and region levels show the effectiveness of the proposed algorithm.

  5. Two-Stage Multi-Task Representation Learning for Synthetic Aperture Radar (SAR) Target Images Classification.

    Science.gov (United States)

    Zhang, Xinzheng; Wang, Yijian; Tan, Zhiying; Li, Dong; Liu, Shujun; Wang, Tao; Li, Yongming

    2017-11-01

    In this paper, we propose a two-stage multi-task learning representation method for the classification of synthetic aperture radar (SAR) target images. The first stage of the proposed approach uses multi-features joint sparse representation learning, modeled as a ℓ 2 , 1 -norm regularized multi-task sparse learning problem, to find an effective subset of training samples. Then, a new dictionary is constructed based on the training subset. The second stage of the method is to perform target images classification based on the new dictionary, utilizing multi-task collaborative representation. The proposed algorithm not only exploits the discrimination ability of multiple features but also greatly reduces the interference of atoms that are irrelevant to the test sample, thus effectively improving classification performance. Conducted with the Moving and Stationary Target Acquisition and Recognition (MSTAR) public SAR database, experimental results show that the proposed approach is effective and superior to many state-of-the-art methods.

  6. Discrimination of Different Water Layers with TerraSAR X Images in "La Albufera de Valencia"

    Science.gov (United States)

    García Fernández, M. A.; Miguelsanz Muñoz, P.

    2009-04-01

    To analyze the capabilities of TerraSAR X Strip Map images in order to discriminate different water layers in the "Parque de la Albufera de Valencia", Spain, a test project was carried out. This place is a rice crop area under European and National Agro environmental regulation which obliges to preserve the habitat and to keep the rice plots flooded out of crop season, from October to January

  7. Mapping Winter Wheat with Multi-Temporal SAR and Optical Images in an Urban Agricultural Region.

    Science.gov (United States)

    Zhou, Tao; Pan, Jianjun; Zhang, Peiyu; Wei, Shanbao; Han, Tao

    2017-05-25

    Winter wheat is the second largest food crop in China. It is important to obtain reliable winter wheat acreage to guarantee the food security for the most populous country in the world. This paper focuses on assessing the feasibility of in-season winter wheat mapping and investigating potential classification improvement by using SAR (Synthetic Aperture Radar) images, optical images, and the integration of both types of data in urban agricultural regions with complex planting structures in Southern China. Both SAR (Sentinel-1A) and optical (Landsat-8) data were acquired, and classification using different combinations of Sentinel-1A-derived information and optical images was performed using a support vector machine (SVM) and a random forest (RF) method. The interference coherence and texture images were obtained and used to assess the effect of adding them to the backscatter intensity images on the classification accuracy. The results showed that the use of four Sentinel-1A images acquired before the jointing period of winter wheat can provide satisfactory winter wheat classification accuracy, with an F1 measure of 87.89%. The combination of SAR and optical images for winter wheat mapping achieved the best F1 measure-up to 98.06%. The SVM was superior to RF in terms of the overall accuracy and the kappa coefficient, and was faster than RF, while the RF classifier was slightly better than SVM in terms of the F1 measure. In addition, the classification accuracy can be effectively improved by adding the texture and coherence images to the backscatter intensity data.

  8. Saharasar: An Interactive SAR Image Database for Desert Mapping

    Science.gov (United States)

    Lopez, S.; Paillou, Ph.

    2017-06-01

    We present a dedicated tool for accessing radar images acquired by the ALOS/PALSAR mission over Sahara and Arabia. We developed a dedicated web site, using the Mapserver web mapping server and the Cesium javascript library.

  9. 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.

  10. The imaging algorithm of millimeter-wave forward-looking SAR

    Science.gov (United States)

    Chen, Lei; Li, Xingguang; Chen, Dianren

    2017-01-01

    It is studied a new type millimeter-wave forward-looking synthetic aperture radar (SAR) imaging algorithm in this paper, analyzes the imaging principle, echo model of point target is given, deduced the forward-looking synthetic aperture radar RD imaging algorithm, and using MATLAB imaging simulation of point target in 6, a point target simulation results from the peak of 64 * 64 slice contour and azimuth, distance to the envelope of the imaging results were analyzed, found that the distance and azimuth focusing effect is good and the side lobe does not appear distorted and tilted, proved that the system of the millimeter wave synthetic aperture radar imaging of forward-looking , simulation results demonstrate the validity of the system.

  11. Fast Vessel Detection in Gaofen-3 SAR Images with Ultrafine Strip-Map Mode.

    Science.gov (United States)

    Pan, Zongxu; Liu, Lei; Qiu, Xiaolan; Lei, Bin

    2017-07-05

    This study aims to detect vessels with lengths ranging from about 70 to 300 m, in Gaofen-3 (GF-3) SAR images with ultrafine strip-map (UFS) mode as fast as possible. Based on the analysis of the characteristics of vessels in GF-3 SAR imagery, an effective vessel detection method is proposed in this paper. Firstly, the iterative constant false alarm rate (CFAR) method is employed to detect the potential ship pixels. Secondly, the mean-shift operation is applied on each potential ship pixel to identify the candidate target region. During the mean-shift process, we maintain a selection matrix recording which pixels can be taken, and these pixels are called as the valid points of the candidate target. The l 1 norm regression is used to extract the principal axis and detect the valid points. Finally, two kinds of false alarms, the bright line and the azimuth ambiguity, are removed by comparing the valid area of the candidate target with a pre-defined value and computing the displacement between the true target and the corresponding replicas respectively. Experimental results on three GF-3 SAR images with UFS mode demonstrate the effectiveness and efficiency of the proposed method.

  12. Monitoring of surface deformation via InSAR imaging for petroleum engineering applications

    Energy Technology Data Exchange (ETDEWEB)

    Yuan, Y.; Zhang, X. [National Key Lab of LIESMARS, (China)

    2004-07-01

    Interferometric synthetic aperture radar imaging (InSAR) is emerging as a method of monitoring minute deformations of the ground surface. Inversion of the surface deformation is also being developed to understand the casual effect underground. These techniques therefore have potential applications in petroleum engineering, in such fields as reservoir management, monitoring of subsurface waste re-injection, subsidence monitoring and overburden/casing integrity assessment. In-situ bitumen recovery from Canadian oil sands reservoirs, including cyclic steam stimulation or the SAGD process, is one area that could potentially utilize the new technology. InSAR yields an area view of the deformation in contrast to discrete point-based measurements provided by existing methods. Resolution down to the centimeter or sub-centimeter level is possible. This paper discusses these two new techniques along with typical examples.

  13. Improved SAR Amplitude Image Offset Measurements for Deriving Three-Dimensional Coseismic Displacements

    KAUST Repository

    Wang, Teng

    2015-02-03

    Offsets of synthetic aperture radar (SAR) images have played an important role in deriving complete three-dimensional (3-D) surface displacement fields in geoscientific applications. However, offset maps often suffer from multiple outliers and patch-like artifacts, because the standard offset-measurement method is a regular moving-window operation that does not consider the scattering characteristics of the ground. Here, we show that by focusing the offset measurements on predetected strong reflectors, the reliability and accuracy of SAR offsets can be significantly improved. Application to the 2011 Van (Turkey) earthquake reveals a clear deformation signal from an otherwise decorrelated interferogram, making derivation of the 3-D coseismic displacement field possible. Our proposed method can improve mapping of coseismic deformation and other ground displacements, such as glacier flow and landslide movement when strong reflectors exist.

  14. A Novel General Imaging Formation Algorithm for GNSS-Based Bistatic SAR.

    Science.gov (United States)

    Zeng, Hong-Cheng; Wang, Peng-Bo; Chen, Jie; Liu, Wei; Ge, LinLin; Yang, Wei

    2016-02-26

    Global Navigation Satellite System (GNSS)-based bistatic Synthetic Aperture Radar (SAR) recently plays a more and more significant role in remote sensing applications for its low-cost and real-time global coverage capability. In this paper, a general imaging formation algorithm was proposed for accurately and efficiently focusing GNSS-based bistatic SAR data, which avoids the interpolation processing in traditional back projection algorithms (BPAs). A two-dimensional point target spectrum model was firstly presented, and the bulk range cell migration correction (RCMC) was consequently derived for reducing range cell migration (RCM) and coarse focusing. As the bulk RCMC seriously changes the range history of the radar signal, a modified and much more efficient hybrid correlation operation was introduced for compensating residual phase errors. Simulation results were presented based on a general geometric topology with non-parallel trajectories and unequal velocities for both transmitter and receiver platforms, showing a satisfactory performance by the proposed method.

  15. Synthetic aperture radar imaging simulator for pulse envelope evaluation

    Science.gov (United States)

    Balster, Eric J.; Scarpino, Frank A.; Kordik, Andrew M.; Hill, Kerry L.

    2017-10-01

    A simulator for spotlight synthetic aperture radar (SAR) image formation is presented. The simulator produces radar returns from a virtual radar positioned at an arbitrary distance and altitude. The radar returns are produced from a source image, where the return is a weighted summation of linear frequency-modulated (LFM) pulse signals delayed by the distance of each pixel in the image to the radar. The imagery is resampled into polar format to ensure consistent range profiles to the position of the radar. The SAR simulator provides a capability enabling the objective analysis of formed SAR imagery, comparing it to an original source image. This capability allows for analysis of various SAR signal processing techniques previously determined by impulse response function (IPF) analysis. The results suggest that IPF analysis provides results that may not be directly related to formed SAR image quality. Instead, the SAR simulator uses image quality metrics, such as peak signal-to-noise ratio (PSNR) and structured similarity index (SSIM), for formed SAR image quality analysis. To showcase the capability of the SAR simulator, it is used to investigate the performance of various envelopes applied to LFM pulses. A power-raised cosine window with a power p=0.35 and roll-off factor of β=0.15 is shown to maximize the quality of the formed SAR images by improving PSNR by 0.84 dB and SSIM by 0.06 from images formed utilizing a rectangular pulse, on average.

  16. Modified Polar-Format Software for Processing SAR Data

    Science.gov (United States)

    Chen, Curtis

    2003-01-01

    HMPF is a computer program that implements a modified polar-format algorithm for processing data from spaceborne synthetic-aperture radar (SAR) systems. Unlike prior polar-format processing algorithms, this algorithm is based on the assumption that the radar signal wavefronts are spherical rather than planar. The algorithm provides for resampling of SAR pulse data from slant range to radial distance from the center of a reference sphere that is nominally the local Earth surface. Then, invoking the projection-slice theorem, the resampled pulse data are Fourier-transformed over radial distance, arranged in the wavenumber domain according to the acquisition geometry, resampled to a Cartesian grid, and inverse-Fourier-transformed. The result of this process is the focused SAR image. HMPF, and perhaps other programs that implement variants of the algorithm, may give better accuracy than do prior algorithms for processing strip-map SAR data from high altitudes and may give better phase preservation relative to prior polar-format algorithms for processing spotlight-mode SAR data.

  17. Improved Hyperthermia Treatment Control using SAR/Temperature Simulation and PRFS Magnetic Resonance Thermal Imaging

    Science.gov (United States)

    Li, Zhen; Vogel, Martin; Maccarini, Paolo F.; Stakhursky, Vadim; Soher, Brian J.; Craciunescu, Oana I.; Das, Shiva; Arabe, Omar A.; Joines, Williams T.; Stauffer, Paul R.

    2010-01-01

    Purpose This article explores the feasibility of using coupled electromagnetic and thermodynamic simulations to improve planning and control of hyperthermia treatments for cancer. The study investigates the usefulness of preplanning to improve heat localization in tumor targets in treatments monitored with PRFS-based Magnetic Resonance Thermal Imaging (MRTI). . Methods Heating capabilities of a cylindrical radiofrequency (RF) mini-annular phased array (MAPA) applicator were investigated with electromagnetic and thermal simulations of SAR in homogeneous phantom models and two human leg sarcomas. HFSS (Ansoft Corp) was used for electromagnetic simulations and SAR patterns were coupled into EPhysics (Ansoft Corp) for thermal modeling with temperature dependent variable perfusion. Simulations were accelerated by integrating tumor specific anatomy into a pre-gridded whole body tissue model. To validate this treatment planning approach, simulations were compared with MR thermal images in both homogenous phantoms and heterogeneous tumors. Results SAR simulations demonstrated excellent agreement with temperature rise distributions obtained with MR thermal imaging in homogeneous phantoms, and clinical treatments of large soft-tissue sarcomas. The results demonstrate feasibility of preplanning appropriate relative phases of antennas for localizing heat in tumor. Conclusions Advances in the accuracy of computer simulation and non-invasive thermometry via MR thermal imaging have provided powerful new tools for optimization of clinical hyperthermia treatments. Simulations agree well with MR thermal images in both homogeneous tissue models and patients with lower leg tumors. This work demonstrates that better quality hyperthermia treatments should be possible when simplified hybrid model simulations are performed routinely as part of the clinical pretreatment plan. PMID:21070140

  18. An image formation algorithm for missile-borne circular-scanning SAR

    Science.gov (United States)

    Gao, Yesheng; Wang, Kaizhi; Liu, Xingzhao

    2013-12-01

    Circular-scanning SAR is an imaging mode with its antenna beam rotating continuously with respect to the vertical axis. An image formation algorithm for the missile-borne circular-scanning SAR is proposed in this article. Based on the principle of the polar format algorithm, the focus algorithm is generalized to form each subimage when the antenna beam scans at an arbitrary position. By calculating the 2-D position of each calibration point between the scatterers and the subimages, a method is presented to correct the geometric distortion of each subimage. This method is able to correct the geometric distortion even in the case of high maneuvering. These subimages are then mosaicked together to form a circular image. The simulation results under three different maneuvering trajectories are given, the subimages are formed by the focusing algorithm, and then the final circular image can be formed by mosaicking 71 subimages, each of which is after geometric distortion correction. The simulations validate the proposed image formation algorithm, and the results satisfy system design requirements.

  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. Decomposition of Polarimetric SAR Images Based on Second- and Third-order Statics Analysis

    Science.gov (United States)

    Kojima, S.; Hensley, S.

    2012-12-01

    There are many papers concerning the research of the decomposition of polerimetric SAR imagery. Most of them are based on second-order statics analysis that Freeman and Durden [1] suggested for the reflection symmetry condition that implies that the co-polarization and cross-polarization correlations are close to zero. Since then a number of improvements and enhancements have been proposed to better understand the underlying backscattering mechanisms present in polarimetric SAR images. For example, Yamaguchi et al. [2] added the helix component into Freeman's model and developed a 4 component scattering model for the non-reflection symmetry condition. In addition, Arii et al. [3] developed an adaptive model-based decomposition method that could estimate both the mean orientation angle and a degree of randomness for the canopy scattering for each pixel in a SAR image without the reflection symmetry condition. This purpose of this research is to develop a new decomposition method based on second- and third-order statics analysis to estimate the surface, dihedral, volume and helix scattering components from polarimetric SAR images without the specific assumptions concerning the model for the volume scattering. In addition, we evaluate this method by using both simulation and real UAVSAR data and compare this method with other methods. We express the volume scattering component using the wire formula and formulate the relationship equation between backscattering echo and each component such as the surface, dihedral, volume and helix via linearization based on second- and third-order statics. In third-order statics, we calculate the correlation of the correlation coefficients for each polerimetric data and get one new relationship equation to estimate each polarization component such as HH, VV and VH for the volume. As a result, the equation for the helix component in this method is the same formula as one in Yamaguchi's method. However, the equation for the volume

  1. AN EVOLUTIONARY ALGORITHM FOR FAST INTENSITY BASED IMAGE MATCHING BETWEEN OPTICAL AND SAR SATELLITE IMAGERY

    Directory of Open Access Journals (Sweden)

    P. Fischer

    2018-04-01

    Full Text Available This paper presents a hybrid evolutionary algorithm for fast intensity based matching between satellite imagery from SAR and very high-resolution (VHR optical sensor systems. The precise and accurate co-registration of image time series and images of different sensors is a key task in multi-sensor image processing scenarios. The necessary preprocessing step of image matching and tie-point detection is divided into a search problem and a similarity measurement. Within this paper we evaluate the use of an evolutionary search strategy for establishing the spatial correspondence between satellite imagery of optical and radar sensors. The aim of the proposed algorithm is to decrease the computational costs during the search process by formulating the search as an optimization problem. Based upon the canonical evolutionary algorithm, the proposed algorithm is adapted for SAR/optical imagery intensity based matching. Extensions are drawn using techniques like hybridization (e.g. local search and others to lower the number of objective function calls and refine the result. The algorithm significantely decreases the computational costs whilst finding the optimal solution in a reliable way.

  2. Dual-Branch Deep Convolution Neural Network for Polarimetric SAR Image Classification

    Directory of Open Access Journals (Sweden)

    Fei Gao

    2017-04-01

    Full Text Available The deep convolution neural network (CNN, which has prominent advantages in feature learning, can learn and extract features from data automatically. Existing polarimetric synthetic aperture radar (PolSAR image classification methods based on the CNN only consider the polarization information of the image, instead of incorporating the image’s spatial information. In this paper, a novel method based on a dual-branch deep convolution neural network (Dual-CNN is proposed to realize the classification of PolSAR images. The proposed method is built on two deep CNNs: one is used to extract the polarization features from the 6-channel real matrix (6Ch which is derived from the complex coherency matrix. The other is utilized to extract the spatial features of a Pauli RGB (Red Green Blue image. These extracted features are first combined into a fully connected layer sharing the polarization and spatial property. Then, the Softmax classifier is employed to classify these features. The experiments are conducted on the Airborne Synthetic Aperture Radar (AIRSAR data of Flevoland and the results show that the classification accuracy on 14 types of land cover is up to 98.56%. Such results are promising in comparison with other state-of-the-art methods.

  3. A High-precision Motion Compensation Method for SAR Based on Image Intensity Optimization

    Directory of Open Access Journals (Sweden)

    Hu Ke-bin

    2015-02-01

    Full Text Available Owing to the platform instability and precision limitations of motion sensors, motion errors negatively affect the quality of synthetic aperture radar (SAR images. The autofocus Back Projection (BP algorithm based on the optimization of image sharpness compensates for motion errors through phase error estimation. This method can attain relatively good performance, while assuming the same phase error for all pixels, i.e., it ignores the spatial variance of motion errors. To overcome this drawback, a high-precision motion error compensation method is presented in this study. In the proposed method, the Antenna Phase Centers (APC are estimated via optimization using the criterion of maximum image intensity. Then, the estimated APCs are applied for BP imaging. Because the APC estimation equals the range history estimation for each pixel, high-precision phase compensation for every pixel can be achieved. Point-target simulations and processing of experimental data validate the effectiveness of the proposed method.

  4. NEUTRINOS: Moriond spotlight

    International Nuclear Information System (INIS)

    Petcov, S.T.

    1991-01-01

    The regular 'Rencontres de Moriond' meetings in the French Alps, which celebrate their 25th anniversary this year, have a strong tradition of reflecting new trends in physics thinking and January's session on 'Tests of Fundamental Laws in Physics' was no exception. The spotlight this time fell on the neutrino sector, a branch of physics frequently in evolution, if not controversial

  5. Dynamic experiment design regularization approach to adaptive imaging with array radar/SAR sensor systems.

    Science.gov (United States)

    Shkvarko, Yuriy; Tuxpan, José; Santos, Stewart

    2011-01-01

    We consider a problem of high-resolution array radar/SAR imaging formalized in terms of a nonlinear ill-posed inverse problem of nonparametric estimation of the power spatial spectrum pattern (SSP) of the random wavefield scattered from a remotely sensed scene observed through a kernel signal formation operator and contaminated with random Gaussian noise. First, the Sobolev-type solution space is constructed to specify the class of consistent kernel SSP estimators with the reproducing kernel structures adapted to the metrics in such the solution space. Next, the "model-free" variational analysis (VA)-based image enhancement approach and the "model-based" descriptive experiment design (DEED) regularization paradigm are unified into a new dynamic experiment design (DYED) regularization framework. Application of the proposed DYED framework to the adaptive array radar/SAR imaging problem leads to a class of two-level (DEED-VA) regularized SSP reconstruction techniques that aggregate the kernel adaptive anisotropic windowing with the projections onto convex sets to enforce the consistency and robustness of the overall iterative SSP estimators. We also show how the proposed DYED regularization method may be considered as a generalization of the MVDR, APES and other high-resolution nonparametric adaptive radar sensing techniques. A family of the DYED-related algorithms is constructed and their effectiveness is finally illustrated via numerical simulations.

  6. GOTCHA experience report: three-dimensional SAR imaging with complete circular apertures

    Science.gov (United States)

    Ertin, Emre; Austin, Christian D.; Sharma, Samir; Moses, Randolph L.; Potter, Lee C.

    2007-04-01

    We study circular synthetic aperture radar (CSAR) systems collecting radar backscatter measurements over a complete circular aperture of 360 degrees. This study is motivated by the GOTCHA CSAR data collection experiment conducted by the Air Force Research Laboratory (AFRL). Circular SAR provides wide-angle information about the anisotropic reflectivity of the scattering centers in the scene, and also provides three dimensional information about the location of the scattering centers due to a non planar collection geometry. Three dimensional imaging results with single pass circular SAR data reveals that the 3D resolution of the system is poor due to the limited persistence of the reflectors in the scene. We present results on polarimetric processing of CSAR data and illustrate reasoning of three dimensional shape from multi-view layover using prior information about target scattering mechanisms. Next, we discuss processing of multipass (CSAR) data and present volumetric imaging results with IFSAR and three dimensional backprojection techniques on the GOTCHA data set. We observe that the volumetric imaging with GOTCHA data is degraded by aliasing and high sidelobes due to nonlinear flightpaths and sparse and unequal sampling in elevation. We conclude with a model based technique that resolves target features and enhances the volumetric imagery by extrapolating the phase history data using the estimated model.

  7. Observation of pressure ridges in SAR images of sea ice: Scattering theory and comparison with observations

    Science.gov (United States)

    Vesecky, J. F.; Daida, J. M.; Shuchman, R. A.; Onstott, R. H.; Camiso, J. C.

    1993-01-01

    Ridges and keels (hummocks and bummocks) in sea ice flows are important in sea ice research for both scientific and practical reasons. Sea ice movement and deformation is driven by internal and external stresses on the ice. Ridges and keels play important roles in both cases because they determine the external wind and current stresses via drag coefficients. For example, the drag coefficient over sea ice can vary by a factor of several depending on the fluid mechanical roughness length of the surface. This roughness length is thought to be strongly dependent on the ridge structures present. Thus, variations in ridge and keel structure can cause gradients in external stresses which must be balanced by internal stresses and possibly fracture of the ice. Ridging in sea ice is also a sign of fracture. In a practical sense, large ridges form the biggest impediment to surface travel over the ice or penetration through sea ice by ice-strengthened ships. Ridges also play an important role in the damage caused by sea ice to off-shore structures. Hence, observation and measurement of sea ice ridges is an important component of sea ice remote sensing. The research reported here builds on previous work, estimating the characteristics of ridges and leads in sea ice from SAR images. Our objective is to develop methods for quantitative measurement of sea ice ridges from SAR images. To make further progress, in particular, to estimate ridge height, a scattering model for ridges is needed. Our research approach for a ridge scattering model begins with a survey of the geometrical properties of ridges and a comparison with the characteristics of the surrounding ice. For this purpose we have used airborne optical laser (AOL) data collected during the 1987 Greenland Sea Experiment. These data were used to generate a spatial wavenumber spectrum for height variance for a typical ridge - the typical ridge is the average over 10 large ridges. Our first-order model radar scattering includes

  8. MicroCT image-generated tumour geometry and SAR distribution for tumour temperature elevation simulations in magnetic nanoparticle hyperthermia.

    Science.gov (United States)

    Lebrun, Alexander; Manuchehrabadi, Navid; Attaluri, Anilchandra; Wang, Frank; Ma, Ronghui; Zhu, Liang

    2013-12-01

    The objective of this study was to develop and test computer algorithms to export micro computed tomography (microCT) images and to generate tumour geometry and specific absorption rate (SAR) distribution for heat transfer simulation in magnetic nanoparticle hyperthermia. Computer algorithms were written to analyse and export microCT images of 3D tumours containing magnetic nanoparticles. MATLAB(®) and ProE(®) programs were used to generate a prototype of the tumour geometry. The enhancements in the microCT pixel index number due to presence of nanoparticles in the tumours were first converted into corresponding SAR values. The SAR data were then averaged over three-dimensional clusters of pixels using the SAS(®) program. This greatly decreased the size of the SAR file, while in the meantime it ensured that the amount of total energy deposited in the tumour was conserved. Both the tumour geometry and the SAR file were then imported into the COMSOL(®) software package to simulate temperature elevations in the tumour and their surrounding tissue region during magnetic nanoparticle hyperthermia. A linear relationship was obtained to relate individual pixel index numbers in the microCT images to the SAR values under a specific magnetic field. The generated prototype of the tumour geometry based on only 30 slices of microCT images resembled the original tumour shape and size. The tumour geometry and the simplified SAR data set were successfully accepted by the COMSOL software for heat transfer simulation. Up to 20 °C temperature elevations from its baseline temperature were found inside the tumours, implying possible thermal damage to the tumour during magnetic nanoparticle hyperthermia.

  9. Ubiquitous and continuous SAR imaging for natural hazards: present and future of remote sensing

    Science.gov (United States)

    Monti Guarnieri, Andrea; Rocca, Fabio

    2017-04-01

    Constellation of optical and SAR sensors have achieved unprecedented performances: dense constellation of cubesats - like the next constellation of 88 Dove satellites (Planet labs), launched simultaneously this February - reduce the revisit time to nearly daily. This brings great value to many domains, like the assessment of risk and damage in natural hazards, post-earthquake response, real time flood monitoring. The limits to optical imaging due to cloud coverage could then be removed with drones. Alternatively, decades of coherent exploitation of Synthetic Aperture Radars have demonstrated their unique capabilities in precise deformation monitoring, penetration in canopies and subsurfaces (glacier and deserts), 3D imaging of volumes, sensitivity to soil moisture and generation of water vapor maps. Thanks to these capabilities, for one, early warning was possible for a landslide at Bingham Canyon Mine (one of the largest in history), whereas monitoring of infrastructures, natural gas and carbon dioxide storage reservoirs, dams, mines is already an established business. Many of these applications are made possible by the Sentinel-1 SAR constellation, the first to provide systematic coherent acquisitions and free and open data. More than 50000 products are downloaded daily. Nonetheless, the present revisit times of this constellation (1-3 days), or the future 6 hours of Cosmo-SKYmed I and II constellations, will leave a gap that cannot be fruitfully exploited for early warning of landslides, real time mapping of flooding, hydrometeor forecasts, real-time regional alerts of collapse, continuous soil moisture mapping for precision farming. On the other side, the limited penetration capabilities of C-band (Sentinel-1) and X band (Cosmo, TerraSAR constellations) would not allow sufficient penetration to monitor volumes, like ice, sands and forests. In order to fill these gaps, two novel SAR systems are under study and will possibly appear in the next decades

  10. 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.

  11. Classification of Polarimetric SAR Image Based on Support Vector Machine Using Multiple-Component Scattering Model and Texture Features

    Directory of Open Access Journals (Sweden)

    Lamei Zhang

    2010-01-01

    Full Text Available The classification of polarimetric SAR image based on Multiple-Component Scattering Model (MCSM and Support Vector Machine (SVM is presented in this paper. MCSM is a potential decomposition method for a general condition. SVM is a popular tool for machine learning tasks involving classification, recognition, or detection. The scattering powers of single-bounce, double-bounce, volume, helix, and wire scattering components are extracted from fully polarimetric SAR images. Combining with the scattering powers of MCSM and the selected texture features from Gray-level cooccurrence matrix (GCM, SVM is used for the classification of polarimetric SAR image. We generate a validity test for the proposed method using Danish EMISAR L-band fully polarimetric data of Foulum Area (DK, Denmark. The preliminary result indicates that this method can classify most of the areas correctly.

  12. Improved MISO-SAR System Based on BiDirectional Imaging

    Directory of Open Access Journals (Sweden)

    Jiang Hai

    2015-10-01

    Full Text Available In 2012, the German Aerospace Center (DLR. proposed a BiDirectional mode that can achieve several seconds of repeated time lags by single star and single flight. Its basic principle includes the generation of a double-beam antenna pattern by electronic beam steering and simultaneous emission of two pulses that irradiate the front and back imaging area. The two pulses, which are simultaneously received will be separated by band-pass filtering in the Doppler domain and imaged, respectively. This paper presents an improved Multi Input Single Output (MISO-SAR system based on the BiDirectional mode which converts the traditional simultaneous dual beam emitting and receiving into time-division emitting and simultaneous receiving, respectively. This results in an improved emitting antenna pattern owning to the suppression of the Azimuth Ambiguity to Signal Ratio (AASR. The current paper describes the spectrum separation effects, AASR analysis, and the system design process. Therefore, to confirm effectiveness, point target 1-D and 2-D simulation results are compared before and after the improvement. Furthermore, the BiDirectional and other short-term repeated SAR modes are compared.

  13. Ship heading and velocity analysis by wake detection in SAR images

    Science.gov (United States)

    Graziano, Maria Daniela; D'Errico, Marco; Rufino, Giancarlo

    2016-11-01

    With the aim of ship-route estimation, a wake detection method is developed and applied to COSMO/SkyMed and TerraSAR-X Stripmap SAR images over the Gulf of Naples, Italy. In order to mitigate the intrinsic limitations of the threshold logic, the algorithm identifies the wake features according to the hydrodynamic theory. A post-detection validation phase is performed to classify the features as real wake structures by means of merit indexes defined in the intensity domain. After wake reconstruction, ship heading is evaluated on the basis of turbulent wake direction and ship velocity is estimated by both techniques of azimuth shift and Kelvin pattern wavelength. The method is tested over 34 ship wakes identified by visual inspection in both HH and VV images at different incidence angles. For all wakes, no missed detections are reported and at least the turbulent and one narrow-V wakes are correctly identified, with ship heading successfully estimated. Also, the azimuth shift method is applied to estimate velocity for the 10 ships having route with sufficient angular separation from the satellite ground track. In one case ship velocity is successfully estimated with both methods, showing agreement within 14%.

  14. 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.

  15. Two-Stage Multi-Task Representation Learning for Synthetic Aperture Radar (SAR Target Images Classification

    Directory of Open Access Journals (Sweden)

    Xinzheng Zhang

    2017-11-01

    Full Text Available In this paper, we propose a two-stage multi-task learning representation method for the classification of synthetic aperture radar (SAR target images. The first stage of the proposed approach uses multi-features joint sparse representation learning, modeled as a ℓ 2 , 1 -norm regularized multi-task sparse learning problem, to find an effective subset of training samples. Then, a new dictionary is constructed based on the training subset. The second stage of the method is to perform target images classification based on the new dictionary, utilizing multi-task collaborative representation. The proposed algorithm not only exploits the discrimination ability of multiple features but also greatly reduces the interference of atoms that are irrelevant to the test sample, thus effectively improving classification performance. Conducted with the Moving and Stationary Target Acquisition and Recognition (MSTAR public SAR database, experimental results show that the proposed approach is effective and superior to many state-of-the-art methods.

  16. Two-Step Single Slope/SAR ADC with Error Correction for CMOS Image Sensor

    Directory of Open Access Journals (Sweden)

    Fang Tang

    2014-01-01

    Full Text Available Conventional two-step ADC for CMOS image sensor requires full resolution noise performance in the first stage single slope ADC, leading to high power consumption and large chip area. This paper presents an 11-bit two-step single slope/successive approximation register (SAR ADC scheme for CMOS image sensor applications. The first stage single slope ADC generates a 3-bit data and 1 redundant bit. The redundant bit is combined with the following 8-bit SAR ADC output code using a proposed error correction algorithm. Instead of requiring full resolution noise performance, the first stage single slope circuit of the proposed ADC can tolerate up to 3.125% quantization noise. With the proposed error correction mechanism, the power consumption and chip area of the single slope ADC are significantly reduced. The prototype ADC is fabricated using 0.18 μm CMOS technology. The chip area of the proposed ADC is 7 μm × 500 μm. The measurement results show that the energy efficiency figure-of-merit (FOM of the proposed ADC core is only 125 pJ/sample under 1.4 V power supply and the chip area efficiency is 84 k μm2·cycles/sample.

  17. Removal of Optically Thick Clouds from Multi-Spectral Satellite Images Using Multi-Frequency SAR Data

    Directory of Open Access Journals (Sweden)

    Robert Eckardt

    2013-06-01

    Full Text Available This study presents a method for the reconstruction of pixels contaminated by optical thick clouds in multi-spectral Landsat images using multi-frequency SAR data. A number of reconstruction techniques have already been proposed in the scientific literature. However, all of the existing techniques have certain limitations. In order to overcome these limitations, we expose the Closest Spectral Fit (CSF method proposed by Meng et al. to a new, synergistic approach using optical and SAR data. Therefore, the term Closest Feature Vector (CFV is introduced. The technique facilitates an elegant way to avoid radiometric distortions in the course of image reconstruction. Furthermore the cloud cover removal is independent from underlying land cover types and assumptions on seasonality, etc. The methodology is applied to mono-temporal, multi-frequency SAR data from TerraSAR-X (X-Band, ERS (C-Band and ALOS Palsar (L-Band. This represents a way of thinking about Radar data not as foreign, but as additional data source in multi-spectral remote sensing. For the assessment of the image restoration performance, an experimental framework is established and a statistical evaluation protocol is designed. The results show the potential of a synergistic usage of multi-spectral and SAR data to overcome the loss of data due to cloud cover.

  18. A Combined Use of Decomposition and Texture for Terrain Classification of Fully Polarimetric SAR Images

    Science.gov (United States)

    Rodionova, N. V.

    2007-03-01

    This p aper presents two-stag e unsupervised terrain classification of fully polarimetr ic SA R data using Freeman and Durden decomposition based on three simp le scattering mechanisms: surface, volume and double bounce (first step), and textur al features (uncorrelated uniformity , contr ast, inv erse mo men t and entropy) obtained from grey lev el co-occurrence matr ices (GLCM) (second step). Textural f eatures ar e defined in moving w indow 5x5 pixels w ith N=32 (N - number of grey lev els) . This algorith m preserves th e purity of domin ant polarimetric scattering properties and defines textural features in each scatter ing category. It is shown better object discrimin ation after app lying textur e w ith in fix ed scattering category. Speckle r eduction is one of th e main mo ments in imag e interpr etation improvement because of its great influen ce on textur e. Results from unfiltered and Lee filtered polar imetr ic SAR imag es show that the v alues of contrast and en tropy decr ease and th e values of uniformity and inverse moment increase with speckle reduction, that's tru e for all polarizations (HH, VV, HV). Th e d iscr imination b etw een objects increases after speckle f ilter ing. Polar ization influen ce on textur e features is def ined by calculating th e features in SAR images w ith HH , VV and HV polarizations before and after speck le filter ing, and then creating RG B images. It is shown mor e polarization inf luence on textur e features (uniformity , inverse mo ment and entropy) before filtering and less influen ce - after speck le f iltering. I t's not true for contrast wher e polar ization influen ce is not ch anged practically w ith filtering. SIR-C/X-SA R SLC L-band imag es of Moscow r egion are used for illustr ation.

  19. An Integrated Processing Strategy for Mountain Glacier Motion Monitoring Based on SAR Images

    Science.gov (United States)

    Ruan, Z.; Yan, S.; Liu, G.; LV, M.

    2017-12-01

    Mountain glacier dynamic variables are important parameters in studies of environment and climate change in High Mountain Asia. Due to the increasing events of abnormal glacier-related hazards, research of monitoring glacier movements has attracted more interest during these years. Glacier velocities are sensitive and changing fast under complex conditions of high mountain regions, which implies that analysis of glacier dynamic changes requires comprehensive and frequent observations with relatively high accuracy. Synthetic aperture radar (SAR) has been successfully exploited to detect glacier motion in a number of previous studies, usually with pixel-tracking and interferometry methods. However, the traditional algorithms applied to mountain glacier regions are constrained by the complex terrain and diverse glacial motion types. Interferometry techniques are prone to fail in mountain glaciers because of their narrow size and the steep terrain, while pixel-tracking algorithm, which is more robust in high mountain areas, is subject to accuracy loss. In order to derive glacier velocities continually and efficiently, we propose a modified strategy to exploit SAR data information for mountain glaciers. In our approach, we integrate a set of algorithms for compensating non-glacial-motion-related signals which exist in the offset values retrieved by sub-pixel cross-correlation of SAR image pairs. We exploit modified elastic deformation model to remove the offsets associated with orbit and sensor attitude, and for the topographic residual offset we utilize a set of operations including DEM-assisted compensation algorithm and wavelet-based algorithm. At the last step of the flow, an integrated algorithm combining phase and intensity information of SAR images will be used to improve regional motion results failed in cross-correlation related processing. The proposed strategy is applied to the West Kunlun Mountain and Muztagh Ata region in western China using ALOS

  20. (Non-) homomorphic approaches to denoise intensity SAR images with non-local means and stochastic distances

    Science.gov (United States)

    Penna, Pedro A. A.; Mascarenhas, Nelson D. A.

    2018-02-01

    The development of new methods to denoise images still attract researchers, who seek to combat the noise with the minimal loss of resolution and details, like edges and fine structures. Many algorithms have the goal to remove additive white Gaussian noise (AWGN). However, it is not the only type of noise which interferes in the analysis and interpretation of images. Therefore, it is extremely important to expand the filters capacity to different noise models present in li-terature, for example the multiplicative noise called speckle that is present in synthetic aperture radar (SAR) images. The state-of-the-art algorithms in remote sensing area work with similarity between patches. This paper aims to develop two approaches using the non local means (NLM), developed for AWGN. In our research, we expanded its capacity for intensity SAR ima-ges speckle. The first approach is grounded on the use of stochastic distances based on the G0 distribution without transforming the data to the logarithm domain, like homomorphic transformation. It takes into account the speckle and backscatter to estimate the parameters necessary to compute the stochastic distances on NLM. The second method uses a priori NLM denoising with a homomorphic transformation and applies the inverse Gamma distribution to estimate the parameters that were used into NLM with stochastic distances. The latter method also presents a new alternative to compute the parameters for the G0 distribution. Finally, this work compares and analyzes the synthetic and real results of the proposed methods with some recent filters of the literature.

  1. An Efficient SAR Image Segmentation Framework Using Transformed Nonlocal Mean and Multi-Objective Clustering in Kernel Space

    Directory of Open Access Journals (Sweden)

    Dongdong Yang

    2015-02-01

    Full Text Available Synthetic aperture radar (SAR image segmentation usually involves two crucial issues: suitable speckle noise removing technique and effective image segmentation methodology. Here, an efficient SAR image segmentation method considering both of the two aspects is presented. As for the first issue, the famous nonlocal mean (NLM filter is introduced in this study to suppress the multiplicative speckle noise in SAR image. Furthermore, to achieve a higher denoising accuracy, the local neighboring pixels in the searching window are projected into a lower dimensional subspace by principal component analysis (PCA. Thus, the nonlocal mean filter is implemented in the subspace. Afterwards, a multi-objective clustering algorithm is proposed using the principals of artificial immune system (AIS and kernel-induced distance measures. The multi-objective clustering has been shown to discover the data distribution with different characteristics and the kernel methods can improve its robustness to noise and outliers. Experiments demonstrate that the proposed method is able to partition the SAR image robustly and accurately than the conventional approaches.

  2. STUDY ON LANDSLIDE DISASTER EXTRACTION METHOD BASED ON SPACEBORNE SAR REMOTE SENSING IMAGES – TAKE ALOS PALSAR FOR AN EXAMPLE

    Directory of Open Access Journals (Sweden)

    D. Xue

    2018-04-01

    Full Text Available In this paper, sequence ALOS PALSAR data and airborne SAR data of L-band from June 5, 2008 to September 8, 2015 are used. Based on the research of SAR data preprocessing and core algorithms, such as geocode, registration, filtering, unwrapping and baseline estimation, the improved Goldstein filtering algorithm and the branch-cut path tracking algorithm are used to unwrap the phase. The DEM and surface deformation information of the experimental area were extracted. Combining SAR-specific geometry and differential interferometry, on the basis of composite analysis of multi-source images, a method of detecting landslide disaster combining coherence of SAR image is developed, which makes up for the deficiency of single SAR and optical remote sensing acquisition ability. Especially in bad weather and abnormal climate areas, the speed of disaster emergency and the accuracy of extraction are improved. It is found that the deformation in this area is greatly affected by faults, and there is a tendency of uplift in the southeast plain and western mountainous area, while in the southwest part of the mountain area there is a tendency to sink. This research result provides a basis for decision-making for local disaster prevention and control.

  3. Intersubject local SAR variation for 7T prostate MR imaging with an eight-channel single-side adapted dipole antenna array.

    Science.gov (United States)

    Ipek, Ozlem; Raaijmakers, Alexander J; Lagendijk, Jan J; Luijten, Peter R; van den Berg, Cornelis A T

    2014-04-01

    Surface transmit arrays used in ultra-high field body MRI require local specific absorption rate (SAR) assessment. As local SAR cannot be measured directly, local SAR is determined by simulations using dielectric patient models. In this study, the inter-patient local SAR variation is investigated for 7T prostate imaging with the single-side adapted dipole antenna array. Four-dedicated dielectric models were created by segmenting Dixon water-fat separated images that were obtained from four subjects with a 1.5T scanner and the surface array in place. Electromagnetic simulations were performed to calculate the SAR distribution for each model. Radio frequency (RF) exposure variations were determined by analyzing the SAR(10g) distributions (1) with one element active, (2) using a Q-matrix eigenvalue/eigenvector approach, (3) with the maximum potential SAR in each voxel, and (4) for a phase shimmed prostate measurement. Maximum potential local SAR levels for 1 W time-averaged accepted power per transmit channel range from 4.1 to 7.1 W/kg. These variations show that one model is not sufficient to determine safe scan settings. For the operation of the surface array conservative power settings were derived based on a worst-case SAR evaluation and the most SAR-sensitive body model. Copyright © 2013 Wiley Periodicals, Inc.

  4. Bayesian Fusion of Multi-Scale Detectors for Road Extraction from SAR Images

    Directory of Open Access Journals (Sweden)

    Rui Xu

    2017-01-01

    Full Text Available This paper introduces an innovative road network extraction algorithm using synthetic aperture radar (SAR imagery for improving the accuracy of road extraction. The state-of-the-art approaches, such as fraction extraction and road network optimization, failed to obtain continuous road segments in separate successions, since the optimization could not change the parts ignored by the fraction extraction. In this paper, the proposed algorithm integrates the fraction extraction and optimization procedure simultaneously to extract the road network: (1 the Bayesian framework is utilized to transfer the road network extraction to joint reasoning of the likelihood of fraction extraction and the priority of network optimization; (2 the multi-scale linear feature detector (MLFD and the network optimization beamlet are introduced; (3 the conditional random field (CRF is used to reason jointly. The result is the global optimum since the fraction extraction and network optimization are exploited at the same time. The proposed algorithm solves the problem that the fractions are bound to reduce in the process of network optimization and has demonstrated effectiveness in real SAR images applications.

  5. Expressway deformation mapping using high-resolution TerraSAR-X images

    KAUST Repository

    Shi, Xuguo

    2014-01-27

    Monitoring deformation of linear infrastructures such as expressway and railway caused by natural processes or anthropogenic activities is a vital task to ensure the safety of human lives and properties. Interferometric Synthetic Aperture Radar (InSAR) has been widely recognized as an effective technology to carry out large-area surface deformation mapping. However, its application in linear infrastructure deformation monitoring has not been intensively studied till now. In this article, a modified Small BAseline Subset (SBAS) method is proposed to retrieve the deformation patterns of the expressway. In our method, only the point-like targets identified on the expressway were kept in our analysis, and two complementary subsets of interferograms were formed to better separate the signals of height error and deformation from inteferometric phase observations. We successfully applied this method with multitemporal high-resolution TerraSAR-X images to retrieve the spatialoral pattern of surface deformation along the Beian-Heihe expressway that is located in island-permafrost areas and threatened by geohazards. © 2014 Taylor & Francis.

  6. MAXIMUM LIKELIHOOD CLASSIFICATION OF HIGH-RESOLUTION SAR IMAGES IN URBAN AREA

    Directory of Open Access Journals (Sweden)

    M. Soheili Majd

    2012-09-01

    Full Text Available In this work, we propose a state-of-the-art on statistical analysis of polarimetric synthetic aperture radar (SAR data, through the modeling of several indices. We concentrate on eight ground classes which have been carried out from amplitudes, co-polarisation ratio, depolarization ratios, and other polarimetric descriptors. To study their different statistical behaviours, we consider Gauss, log- normal, Beta I, Weibull, Gamma, and Fisher statistical models and estimate their parameters using three methods: method of moments (MoM, maximum-likelihood (ML methodology, and log-cumulants method (MoML. Then, we study the opportunity of introducing this information in an adapted supervised classification scheme based on Maximum–Likelihood and Fisher pdf. Our work relies on an image of a suburban area, acquired by the airborne RAMSES SAR sensor of ONERA. The results prove the potential of such data to discriminate urban surfaces and show the usefulness of adapting any classical classification algorithm however classification maps present a persistant class confusion between flat gravelled or concrete roofs and trees.

  7. Approximation and bounding of distortion errors in polar format SAR imaging for squinted geometries

    Science.gov (United States)

    Horvath, Matt S.; Rigling, Brian D.

    2012-05-01

    Synthetic aperture radar (SAR) imaging is a powerful tool that can be utilized where other conventional surveillance methods fail. It has a variety of applications including reconnaissance and surveillance for defense purposes, natural resource exploration, and environmental monitoring, among others. SAR systems generally create large datasets that need to be processed to form a final image. Processing this data can be computationally intensive, and applications may demand algorithms that can form images quickly. The goal and motivation of this research is to analyze algorithms that permit a large SAR dataset to be efficiently processed into a high-resolution image of a large scene. The backprojection algorithm (BPA)1 can serve as a baseline for performance relative to other SAR imaging algorithms. It results in accurately formed images for a vast variety of imaging scenarios. The tradeoff comes in its computational complexity which is O(N3) for an N × N pixel image. The polar format algorithm (PFA)2 is a long-standing and popular alternative to the BPA. The PFA allows the use of fast Fourier Transforms (FFTs), leading to a computational complexity of O(N2 logN) for an N × N pixel image. However, the PFA relies on a far-field approximation, wherein the curved wavefront of the transmitted pulses is approximated as a planar wavefront, thereby introducing spatially variant phase errors and hence distortion and defocus in the PFA formed image. The defocus and distortion errors can be corrected, but this is a non-trivial process.3 It can be shown that first-order Taylor expansion of a differential range expression yields the assumed received signal phase used to generate images from SAR phase history data with the PFA.4 This work focuses on error terms introduced by the PFA assumption that introduce geometric distortion in the resulting image. This distortion causes a point scatterer located at a true (x, y) coordinate to appear at some (x, y) in the formed image, i

  8. USING MORPHOLOGICAL DIFFERENTIAL ATTRIBUTE PROFILES FOR CHANGE CATEGORIZATION IN HIGH RESOLUTION SAR IMAGES

    Directory of Open Access Journals (Sweden)

    M. Boldt

    2013-04-01

    Full Text Available Change detection in urban and suburban areas through remote sensing satellite imagery is an important topic. Furthermore, it is of special interest to derive information on the category of detected changes is of special interest. In Boldt et al. (2012, a fullyautomatic change detection method based on a morphological filtered ratio image was presented. This filter step is accomplished by an alternating sequential filter (ASF, which supports the knowledge-driven analysis of the scene. For example, the focus can be set on small-scaled changes caused by vehicles or smaller construction sites. The change detection itself is performed using the automatic threshold method shown in Sahoo et al. (2004 considering the entropies of the fore- and background of the filtered ratio image. In contrast, the presented approach makes use of morphological differential attribute profiles (DAPs to compare changes detected in high resolution (HR TerraSAR-X (TSX amplitude images of Greding (Germany. DAPs are the derivatives of morphological attribute profiles (APs. APs are calculated by applying iteratively attribute openings and/or closings to an input image. Attribute openings (resp. closings themselves are a combination of connected openings (closings and trivial openings (closings. DAPs provide the opportunity to derive typical signatures for each pixel of the entire image (Dalla Mura et al., 2010, and, as a consequence, for each detected change segment. Aiming on the categorization of changes, it is shown in this paper that the DAPs represent a promising method for detecting changes with similar semantics automatically.

  9. 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%.

  10. Novel Polarimetric SAR Interferometry Algorithms, Phase II

    Data.gov (United States)

    National Aeronautics and Space Administration — Polarimetric SAR interferometry (PolInSAR) is a recently developed synthetic aperture radar (SAR) imaging mode that combines the capabilities of radar polarimetry...

  11. Two-dimensional Co-Seismic Surface Displacements Field of the Chi-Chi Earthquake Inferred from SAR Image Matching.

    Science.gov (United States)

    Hu, Jun; Li, Zhi-Wei; Ding, Xiao-Li; Zhu, Jian-Jun

    2008-10-21

    The M w =7.6 Chi-Chi earthquake in Taiwan occurred in 1999 over the Chelungpu fault and caused a great surface rupture and severe damage. Differential Synthetic Aperture Radar Interferometry (DInSAR) has been applied previously to study the co-seismic ground displacements. There have however been significant limitations in the studies. First, only one-dimensional displacements along the Line-of-Sight (LOS) direction have been measured. The large horizontal displacements along the Chelungpu fault are largely missing from the measurements as the fault is nearly perpendicular to the LOS direction. Second, due to severe signal decorrelation on the hangling wall of the fault, the displacements in that area are un-measurable by differential InSAR method. We estimate the co-seismic displacements in both the azimuth and range directions with the method of SAR amplitude image matching. GPS observations at the 10 GPS stations are used to correct for the orbital ramp in the amplitude matching and to create the two-dimensional (2D) co-seismic surface displacements field using the descending ERS-2 SAR image pair. The results show that the co-seismic displacements range from about -2.0 m to 0.7 m in the azimuth direction (with the positive direction pointing to the flight direction), with the footwall side of the fault moving mainly southwards and the hanging wall side northwards. The displacements in the LOS direction range from about -0.5 m to 1.0 m, with the largest displacement occuring in the northeastern part of the hanging wall (the positive direction points to the satellite from ground). Comparing the results from amplitude matching with those from DInSAR, we can see that while only a very small fraction of the LOS displacement has been recovered by the DInSAR mehtod, the azimuth displacements cannot be well detected with the DInSAR measurements as they are almost perpendicular to the LOS. Therefore, the amplitude matching method is obviously more advantageous than the

  12. Optimizing Kernel PCA Using Sparse Representation-Based Classifier for MSTAR SAR Image Target Recognition

    Directory of Open Access Journals (Sweden)

    Chuang Lin

    2013-01-01

    Full Text Available Different kernels cause various class discriminations owing to their different geometrical structures of the data in the feature space. In this paper, a method of kernel optimization by maximizing a measure of class separability in the empirical feature space with sparse representation-based classifier (SRC is proposed to solve the problem of automatically choosing kernel functions and their parameters in kernel learning. The proposed method first adopts a so-called data-dependent kernel to generate an efficient kernel optimization algorithm. Then, a constrained optimization function using general gradient descent method is created to find combination coefficients varied with the input data. After that, optimized kernel PCA (KOPCA is obtained via combination coefficients to extract features. Finally, the sparse representation-based classifier is used to perform pattern classification task. Experimental results on MSTAR SAR images show the effectiveness of the proposed method.

  13. A Novel Fusion-Based Ship Detection Method from Pol-SAR Images.

    Science.gov (United States)

    Wang, Wenguang; Ji, Yu; Lin, Xiaoxia

    2015-09-29

    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.

  14. 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.

  15. Measurement of pressure ridges in SAR images of sea ice - Preliminary results on scattering theory

    Science.gov (United States)

    Vesecky, J. F.; Smith, M. P.; Daida, J. M.; Samadani, R.; Camiso, J. C.

    1992-01-01

    Sea ice ridges and keels (hummocks and bummocks) are important in sea ice research for both scientific and practical reasons. A long-term objective is to make quantitative measurements of sea ice ridges using synthetic aperture radar (SAR) images. The preliminary results of a scattering model for sea ice ridge are reported. The approach is through the ridge height variance spectrum Psi(K), where K is the spatial wavenumber, and the two-scale scattering model. The height spectrum model is constructed to mimic height statistics observed with an airborne optical laser. The spectrum model is used to drive a two-scale scattering model. Model results for ridges observed at C- and X-band yield normalized radar cross sections that are 10 to 15 dB larger than the observed cross sections of multiyear ice over the range of angles of incidence from 10 to 70 deg.

  16. Random Forests as a tool for estimating uncertainty at pixel-level in SAR image classification

    DEFF Research Database (Denmark)

    Loosvelt, Lien; Peters, Jan; Skriver, Henning

    2012-01-01

    , we introduce Random Forests for the probabilistic mapping of vegetation from high-dimensional remote sensing data and present a comprehensive methodology to assess and analyze classification uncertainty based on the local probabilities of class membership. We apply this method to SAR image data......It is widely acknowledged that model inputs can cause considerable errors in the model output. Since land cover maps obtained from the classification of remote sensing data are frequently used as input to spatially explicit environmental models, it is important to provide information regarding...... the classification quality of the produced map. Map quality is generally assessed at the global or class-specific level, using standard methods based on the confusion matrix. Unfortunately, these accuracy measures do not provide information regarding the spatial variability in classification quality. In this paper...

  17. Classification of PolSAR Images Using Multilayer Autoencoders and a Self-Paced Learning Approach

    Directory of Open Access Journals (Sweden)

    Wenshuai Chen

    2018-01-01

    Full Text Available In this paper, a novel polarimetric synthetic aperture radar (PolSAR image classification method based on multilayer autoencoders and self-paced learning (SPL is proposed. The multilayer autoencoders network is used to learn the features, which convert raw data into more abstract expressions. Then, softmax regression is applied to produce the predicted probability distributions over all the classes of each pixel. When we optimize the multilayer autoencoders network, self-paced learning is used to accelerate the learning convergence and achieve a stronger generalization capability. Under this learning paradigm, the network learns the easier samples first and gradually involves more difficult samples in the training process. The proposed method achieves the overall classification accuracies of 94.73%, 94.82% and 78.12% on the Flevoland dataset from AIRSAR, Flevoland dataset from RADARSAT-2 and Yellow River delta dataset, respectively. Such results are comparable with other state-of-the-art methods.

  18. Complex surface deformation monitoring and mechanism inversion over Qingxu-Jiaocheng, China with multi-sensor SAR images

    Science.gov (United States)

    Liu, Yuanyuan; Zhao, Chaoying; Zhang, Qin; Yang, Chengsheng

    2018-02-01

    Qingxu-Jiaocheng, China has been suffering severe land subsidence along with the development of ground fissure, which are controlled by local fault and triggered by groundwater withdrawal. With multi-sensor SAR images, we study the spatiotemporal evolution of ground deformation over Qingxu-Jiaocheng with an IPTA InSAR technique and assess the role of groundwater withdrawal to the observed deformation. Discrete GPS measurements are applied to verify the InSAR results. The RMSE of the differences between InSAR and GPS, i.e. ALOS and GPS and Envisat and GPS, are 5.7 mm and 6.3 mm in the LOS direction, respectively. The east-west and vertical components of the observed deformation from 2007 to 2010 are decomposed by using descending-track Envisat and ascending-track ALOS interferograms, indicating that the east-west component cannot be neglected when the deformation is large or the ground fissure is active. Four phases of land subsidence in the study region are successfully retrieved, and its spatiotemporal evolution is quantitatively analyzed. Lastly, a flat lying sill model with distributed contractions is implemented to model the InSAR deformation over Qingxu-Jiaocheng, which manifests that the ground deformation is mainly caused by groundwater withdrawal. This research provides new insights into the land subsidence monitoring and its mechanism inversion over Qingxu-Jiaocheng region.

  19. Integration of Frequency Domain Wideband Antenna Nulling and Wavenumber Domain Image Formation for Multi-Channel SAR

    Directory of Open Access Journals (Sweden)

    M. Bucciarelli

    2016-01-01

    Full Text Available A Multichannel Synthetic Aperture Radar (M-SAR exploiting an antenna nulling based Electronic Counter-Counter Measures (ECCM technique shall be able to cancel the effects of noise-like interferences over the collected SAR data. Since SAR systems often work with wide bandwidths to provide high resolution images, ECCM technique must account for the presence of wideband interference signal. In this paper we consider a wideband antenna nulling technique based on space-frequency adaptive nulling and we propose an integration of the WB antenna nulling scheme within the focusing algorithm for M-SAR systems, thus allowing a fusion between ECCM and usual SAR processing steps. The computational cost of the integrated algorithm is compared with the cost of more traditional sequence of the wideband extension of the Side-Lobe Canceller and the focusing operation, to show the computational feasibility of the proposed integrated algorithm. The possibility to perform suboptimally the space-frequency adaptive nulling is also considered.

  20. Investigation of Slow-Moving Landslides from ALOS/PALSAR Images with TCPInSAR: A Case Study of Oso, USA

    Directory of Open Access Journals (Sweden)

    Qian Sun

    2014-12-01

    Full Text Available Monitoring slope instability is of great significance for understanding landslide kinematics and, therefore, reducing the related geological hazards. In recent years, interferometric synthetic aperture radar (InSAR has been widely applied to this end, especially thanks to the prompt evolution of multi-temporal InSAR (MTInSAR algorithms. In this paper, temporarily-coherent point InSAR (TCPInSAR, a recently-developed MTInSAR technique, is employed to investigate the slow-moving landslides in Oso, U.S., with 13 ALOS/PALSAR images. Compared to other MTInSAR techniques, TCPInSAR can work well with a small amount of data and is immune to unwrapping errors. Furthermore, the severe orbital ramps emanated from the inaccurate determination of the ALOS satellite’s state vector can be jointly estimated by TCPInSAR, resulting in an exhaustive separation between the orbital errors and displacement signals. The TCPInSAR-derived deformation map indicates that the riverside slopes adjacent to the North Fork of the Stillaguamish River, where the 2014 mudslide occurred, were active during 2007 and 2011. Besides, Coal Mountain has been found to be experiencing slow-moving landslides with clear boundaries and considerable magnitudes. The Deer Creek River is also threatened by a potential landslide dam due to the creeps detected in a nearby slope. The slope instability information revealed in this study is helpful to deal with the landslide hazards in Oso.

  1. 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.

  2. 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.

  3. Ship Detection in Gaofen-3 SAR Images Based on Sea Clutter Distribution Analysis and Deep Convolutional Neural Network

    Directory of Open Access Journals (Sweden)

    Quanzhi An

    2018-01-01

    Full Text Available 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.

  4. Ultra Wide X-Band Microwave Imaging of Concealed Weapons and Explosives Using 3D-SAR Technique

    OpenAIRE

    Millot, P.; Casadebaig, L

    2015-01-01

    International audience; In order to detect and image concealed weapons and explosives, an electromagnetic imaging tool with its related signal processing is presented. The aim is to penetrate clothes and to find personal-born weapons and explosives under clothes. The chosen UWB frequency range covers the whole X-band. The frequency range is justified after transmission measurements of numerous clothes that are dry or slightly wet. The apparatus and the 3D near-field SAR processor are describe...

  5. A study of P-band SAR applicability and performance for Mars exploration: Imaging subsurface geology and detecting shallow moisture

    OpenAIRE

    Paillou, Philippe; Lasne, Y.; Heggy, Essam; Malézieux, J.-M.; Ruffie, G.

    2006-01-01

    Over the past decade, orbital images of the Martian surface revealed key evidences about the history of the planet environment (craters, faults, paleo-lakes and rivers), partially hidden under a widespread layer of aeolian deposits. Furthermore, several recent observations and studies support the hypothesis that water could be found in the shallow sub-surface of Mars. Low frequency SAR – Synthetic Aperture Radar – has demonstrated its subsurface imaging capabilities on Earth, especially in ar...

  6. Coseismic displacements from SAR image offsets between different satellite sensors: Application to the 2001 Bhuj (India) earthquake

    KAUST Repository

    Wang, Teng

    2015-09-05

    Synthetic aperture radar (SAR) image offset tracking is increasingly being used for measuring ground displacements, e.g., due to earthquakes and landslide movement. However, this technique has been applied only to images acquired by the same or identical satellites. Here we propose a novel approach for determining offsets between images acquired by different satellite sensors, extending the usability of existing SAR image archives. The offsets are measured between two multiimage reflectivity maps obtained from different SAR data sets, which provide significantly better results than with single preevent and postevent images. Application to the 2001 Mw7.6 Bhuj earthquake reveals, for the first time, its near-field deformation using multiple preearthquake ERS and postearthquake Envisat images. The rupture model estimated from these cross-sensor offsets and teleseismic waveforms shows a compact fault slip pattern with fairly short rise times (<3 s) and a large stress drop (20 MPa), explaining the intense shaking observed in the earthquake.

  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. A method to calibrate channel friction and bathymetry parameters of a Sub-Grid hydraulic model using SAR flood images

    Science.gov (United States)

    Wood, M.; Neal, J. C.; Hostache, R.; Corato, G.; Chini, M.; Giustarini, L.; Matgen, P.; Wagener, T.; Bates, P. D.

    2015-12-01

    Synthetic Aperture Radar (SAR) satellites are capable of all-weather day and night observations that can discriminate between land and smooth open water surfaces over large scales. Because of this there has been much interest in the use of SAR satellite data to improve our understanding of water processes, in particular for fluvial flood inundation mechanisms. Past studies prove that integrating SAR derived data with hydraulic models can improve simulations of flooding. However while much of this work focusses on improving model channel roughness values or inflows in ungauged catchments, improvement of model bathymetry is often overlooked. The provision of good bathymetric data is critical to the performance of hydraulic models but there are only a small number of ways to obtain bathymetry information where no direct measurements exist. Spatially distributed river depths are also rarely available. We present a methodology for calibration of model average channel depth and roughness parameters concurrently using SAR images of flood extent and a Sub-Grid model utilising hydraulic geometry concepts. The methodology uses real data from the European Space Agency's archive of ENVISAT[1] Wide Swath Mode images of the River Severn between Worcester and Tewkesbury during flood peaks between 2007 and 2010. Historic ENVISAT WSM images are currently free and easy to access from archive but the methodology can be applied with any available SAR data. The approach makes use of the SAR image processing algorithm of Giustarini[2] et al. (2013) to generate binary flood maps. A unique feature of the calibration methodology is to also use parameter 'identifiability' to locate the parameters with higher accuracy from a pre-assigned range (adopting the DYNIA method proposed by Wagener[3] et al., 2003). [1] https://gpod.eo.esa.int/services/ [2] Giustarini. 2013. 'A Change Detection Approach to Flood Mapping in Urban Areas Using TerraSAR-X'. IEEE Transactions on Geoscience and Remote

  9. A Novel 3D Imaging Method for Airborne Downward-Looking Sparse Array SAR Based on Special Squint Model

    Directory of Open Access Journals (Sweden)

    Xiaozhen Ren

    2014-01-01

    Full Text Available Three-dimensional (3D imaging technology based on antenna array is one of the most important 3D synthetic aperture radar (SAR high resolution imaging modes. In this paper, a novel 3D imaging method is proposed for airborne down-looking sparse array SAR based on the imaging geometry and the characteristic of echo signal. The key point of the proposed algorithm is the introduction of a special squint model in cross track processing to obtain accurate focusing. In this special squint model, point targets with different cross track positions have different squint angles at the same range resolution cell, which is different from the conventional squint SAR. However, after theory analysis and formulation deduction, the imaging procedure can be processed with the uniform reference function, and the phase compensation factors and algorithm realization procedure are demonstrated in detail. As the method requires only Fourier transform and multiplications and thus avoids interpolations, it is computationally efficient. Simulations with point scatterers are used to validate the method.

  10. Automated Waterline Detection in the Wadden Sea Using High-Resolution TerraSAR-X Images

    Directory of Open Access Journals (Sweden)

    Stefan Wiehle

    2015-01-01

    Full Text Available We present an algorithm for automatic detection of the land-water-line from TerraSAR-X images acquired over the Wadden Sea. In this coastal region of the southeastern North Sea, a strip of up to 20 km of seabed falls dry during low tide, revealing mudflats and tidal creeks. The tidal currents transport sediments and can change the coastal shape with erosion rates of several meters per month. This rate can be strongly increased by storm surges which also cause flooding of usually dry areas. Due to the high number of ships traveling through the Wadden Sea to the largest ports of Germany, frequent monitoring of the bathymetry is also an important task for maritime security. For such an extended area and the required short intervals of a few months, only remote sensing methods can perform this task efficiently. Automating the waterline detection in weather-independent radar images provides a fast and reliable way to spot changes in the coastal topography. The presented algorithm first performs smoothing, brightness thresholding, and edge detection. In the second step, edge drawing and flood filling are iteratively performed to determine optimal thresholds for the edge drawing. In the last step, small misdetections are removed.

  11. Living in the spotlight

    CERN Multimedia

    2009-01-01

    Just a few weeks ago, we celebrated the 20th anniversary of the World Wide Web. It gave me my first opportunity since taking up my mandate to see first hand what CERN’s newfound public profile means in practice. There were over 60 media from around the world present at CERN for the event, and some 900 reports in the media over the following days. Some weeks before, Sony pictures held a press event for their upcoming movie, Angels and Demons, part of which takes place at CERN. That happened during the same week that we published the new LHC schedule, and it was the LHC that got the most media coverage. So what does this mean for how we carry out our daily work? Particle physics has always operated in a fully open and transparent way. It’s in our DNA to do so. Meetings are open to all comers, and it is important that we continue to foster such a culture of transparency. Nevertheless, we need to be aware that we are much more in the public spotlight than ever before....

  12. A Fast Superpixel Segmentation Algorithm for PolSAR Images Based on Edge Refinement and Revised Wishart Distance.

    Science.gov (United States)

    Zhang, Yue; Zou, Huanxin; Luo, Tiancheng; Qin, Xianxiang; Zhou, Shilin; Ji, Kefeng

    2016-10-13

    The superpixel segmentation algorithm, as a preprocessing technique, should show good performance in fast segmentation speed, accurate boundary adherence and homogeneous regularity. A fast superpixel segmentation algorithm by iterative edge refinement (IER) works well on optical images. However, it may generate poor superpixels for Polarimetric synthetic aperture radar (PolSAR) images due to the influence of strong speckle noise and many small-sized or slim regions. To solve these problems, we utilized a fast revised Wishart distance instead of Euclidean distance in the local relabeling of unstable pixels, and initialized unstable pixels as all the pixels substituted for the initial grid edge pixels in the initialization step. Then, postprocessing with the dissimilarity measure is employed to remove the generated small isolated regions as well as to preserve strong point targets. Finally, the superiority of the proposed algorithm is validated with extensive experiments on four simulated and two real-world PolSAR images from Experimental Synthetic Aperture Radar (ESAR) and Airborne Synthetic Aperture Radar (AirSAR) data sets, which demonstrate that the proposed method shows better performance with respect to several commonly used evaluation measures, even with about nine times higher computational efficiency, as well as fine boundary adherence and strong point targets preservation, compared with three state-of-the-art methods.

  13. A Fast Superpixel Segmentation Algorithm for PolSAR Images Based on Edge Refinement and Revised Wishart Distance

    Directory of Open Access Journals (Sweden)

    Yue Zhang

    2016-10-01

    Full Text Available The superpixel segmentation algorithm, as a preprocessing technique, should show good performance in fast segmentation speed, accurate boundary adherence and homogeneous regularity. A fast superpixel segmentation algorithm by iterative edge refinement (IER works well on optical images. However, it may generate poor superpixels for Polarimetric synthetic aperture radar (PolSAR images due to the influence of strong speckle noise and many small-sized or slim regions. To solve these problems, we utilized a fast revised Wishart distance instead of Euclidean distance in the local relabeling of unstable pixels, and initialized unstable pixels as all the pixels substituted for the initial grid edge pixels in the initialization step. Then, postprocessing with the dissimilarity measure is employed to remove the generated small isolated regions as well as to preserve strong point targets. Finally, the superiority of the proposed algorithm is validated with extensive experiments on four simulated and two real-world PolSAR images from Experimental Synthetic Aperture Radar (ESAR and Airborne Synthetic Aperture Radar (AirSAR data sets, which demonstrate that the proposed method shows better performance with respect to several commonly used evaluation measures, even with about nine times higher computational efficiency, as well as fine boundary adherence and strong point targets preservation, compared with three state-of-the-art methods.

  14. Multilook SAR Image Segmentation with an Unknown Number of Clusters Using a Gamma Mixture Model and Hierarchical Clustering.

    Science.gov (United States)

    Zhao, Quanhua; Li, Xiaoli; Li, Yu

    2017-05-12

    This paper presents a novel multilook SAR image segmentation algorithm with an unknown number of clusters. Firstly, the marginal probability distribution for a given SAR image is defined by a Gamma mixture model (GaMM), in which the number of components corresponds to the number of homogeneous regions needed to segment and the spatial relationship among neighboring pixels is characterized by a Markov Random Field (MRF) defined by the weighting coefficients of components in GaMM. During the algorithm iteration procedure, the number of clusters is gradually reduced by merging two components until they are equal to one. For each fixed number of clusters, the parameters of GaMM are estimated and the optimal segmentation result corresponding to the number is obtained by maximizing the marginal probability. Finally, the number of clusters with minimum global energy defined as the negative logarithm of marginal probability is indicated as the expected number of clusters with the homogeneous regions needed to be segmented, and the corresponding segmentation result is considered as the final optimal one. The experimental results from the proposed and comparing algorithms for simulated and real multilook SAR images show that the proposed algorithm can find the real number of clusters and obtain more accurate segmentation results simultaneously.

  15. The dual-use potential of the TerraSAR-X mission

    Science.gov (United States)

    Suess, Helmut; Buckreuss, Stefan

    2009-05-01

    TerraSAR-X, Germany's first national remote sensing satellite, is implemented in a public-private partnership between the German Aerospace Centre (DLR) and EADS Astrium, Infoterra GmbH. This radar satellite, launched at June 15th 2007 supplies high-quality radar data for purposes of scientific observation of the Earth for a period of at least five years. The first part of the paper describes the key features of the TerraSAR-X mission, the high-resolution X-Band Synthetic Aperture Radar which allows the operation in Spotlight, Stripmap and ScanSAR mode with various polarizations. The second part of this paper deals with the interpretation of TerraSAR-X images under dual-use aspects, especially for security and reconnaissance purposes. Examples for relevant and characteristic target categories are listed and attributes for a precise description are defined. As a measure for resolution and interpretation the public NIIRS-table (National Image Interpretation Rating Scale) is used. As an application example the characteristic scenario of a military airport including railway and route connections are extracted. Finally the applicability of the NIIRS-table is discussed in this particular case.

  16. 2002/2003 IfSAR data for Southern California: Radar Reflectance Image

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This metadata document describes the collection and processing of topographic elevation point data derived from Interferometric Synthetic Aperture Radar (IfSAR)...

  17. Two-dimensional Co-Seismic Surface Displacements Field of the Chi-Chi Earthquake Inferred from SAR Image Matching

    Directory of Open Access Journals (Sweden)

    Jian-Jun Zhu

    2008-10-01

    Full Text Available The Mw=7.6 Chi-Chi earthquake in Taiwan occurred in 1999 over the Chelungpu fault and caused a great surface rupture and severe damage. Differential Synthetic Aperture Radar Interferometry (DInSAR has been applied previously to study the co-seismic ground displacements. There have however been significant limitations in the studies. First, only one-dimensional displacements along the Line-of-Sight (LOS direction have been measured. The large horizontal displacements along the Chelungpu fault are largely missing from the measurements as the fault is nearly perpendicular to the LOS direction. Second, due to severe signal decorrelation on the hangling wall of the fault, the displacements in that area are un-measurable by differential InSAR method. We estimate the co-seismic displacements in both the azimuth and range directions with the method of SAR amplitude image matching. GPS observations at the 10 GPS stations are used to correct for the orbital ramp in the amplitude matching and to create the two-dimensional (2D co-seismic surface displacements field using the descending ERS-2 SAR image pair. The results show that the co-seismic displacements range from about -2.0 m to 0.7 m in the azimuth direction (with the positive direction pointing to the flight direction, with the footwall side of the fault moving mainly southwards and the hanging wall side northwards. The displacements in the LOS direction range from about -0.5 m to 1.0 m, with the largest displacement occuring in the northeastern part of the hanging wall (the positive direction points to the satellite from ground. Comparing the results from amplitude matching with those from DInSAR, we can see that while only a very small fraction of the LOS displacement has been recovered by the DInSAR mehtod, the azimuth displacements cannot be well detected with the DInSAR measurements as they are almost perpendicular to the LOS. Therefore, the amplitude matching method is obviously more

  18. Ultra Wide X-Band Microwave Imaging of Concealed Weapons and Explosives Using 3D-SAR Technique

    Directory of Open Access Journals (Sweden)

    P. Millot

    2015-01-01

    Full Text Available In order to detect and image concealed weapons and explosives, an electromagnetic imaging tool with its related signal processing is presented. The aim is to penetrate clothes and to find personal-born weapons and explosives under clothes. The chosen UWB frequency range covers the whole X-band. The frequency range is justified after transmission measurements of numerous clothes that are dry or slightly wet. The apparatus and the 3D near-field SAR processor are described. A strategy for contour identification is presented with results of some simulants of weapon and explosive. A conclusion is drawn on the possible future of this technique.

  19. A pattern recognition system for locating small volvanoes in Magellan SAR images of Venus

    Science.gov (United States)

    Burl, M. C.; Fayyad, U. M.; Smyth, P.; Aubele, J. C.; Crumpler, L. S.

    1993-01-01

    The Magellan data set constitutes an example of the large volumes of data that today's instruments can collect, providing more detail of Venus than was previously available from Pioneer Venus, Venera 15/16, or ground-based radar observations put together. However, data analysis technology has not kept pace with data collection and storage technology. Due to the sheer size of the data, complete and comprehensive scientific analysis of such large volumes of image data is no longer feasible without the use of computational aids. Our progress towards developing a pattern recognition system for aiding in the detection and cataloging of small-scale natural features in large collections of images is reported. Combining classical image processing, machine learning, and a graphical user interface, the detection of the 'small-shield' volcanoes (less than 15km in diameter) that constitute the most abundant visible geologic feature in the more that 30,000 synthetic aperture radar (SAR) images of the surface of Venus are initially targeted. Our eventual goal is to provide a general, trainable tool for locating small-scale features where scientists specify what to look for simply by providing examples and attributes of interest to measure. This contrasts with the traditional approach of developing problem specific programs for detecting Specific patterns. The approach and initial results in the specific context of locating small volcanoes is reported. It is estimated, based on extrapolating from previous studies and knowledge of the underlying geologic processes, that there should be on the order of 10(exp 5) to 10(exp 6) of these volcanoes visible in the Magellan data. Identifying and studying these volcanoes is fundamental to a proper understanding of the geologic evolution of Venus. However, locating and parameterizing them in a manual manner is forbiddingly time-consuming. Hence, the development of techniques to partially automate this task were undertaken. The primary

  20. 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.

  1. Time Series Analysis OF SAR Image Fractal Maps: The Somma-Vesuvio Volcanic Complex Case Study

    Science.gov (United States)

    Pepe, Antonio; De Luca, Claudio; Di Martino, Gerardo; Iodice, Antonio; Manzo, Mariarosaria; Pepe, Susi; Riccio, Daniele; Ruello, Giuseppe; Sansosti, Eugenio; Zinno, Ivana

    2016-04-01

    The fractal dimension is a significant geophysical parameter describing natural surfaces representing the distribution of the roughness over different spatial scale; in case of volcanic structures, it has been related to the specific nature of materials and to the effects of active geodynamic processes. In this work, we present the analysis of the temporal behavior of the fractal dimension estimates generated from multi-pass SAR images relevant to the Somma-Vesuvio volcanic complex (South Italy). To this aim, we consider a Cosmo-SkyMed data-set of 42 stripmap images acquired from ascending orbits between October 2009 and December 2012. Starting from these images, we generate a three-dimensional stack composed by the corresponding fractal maps (ordered according to the acquisition dates), after a proper co-registration. The time-series of the pixel-by-pixel estimated fractal dimension values show that, over invariant natural areas, the fractal dimension values do not reveal significant changes; on the contrary, over urban areas, it correctly assumes values outside the natural surfaces fractality range and show strong fluctuations. As a final result of our analysis, we generate a fractal map that includes only the areas where the fractal dimension is considered reliable and stable (i.e., whose standard deviation computed over the time series is reasonably small). The so-obtained fractal dimension map is then used to identify areas that are homogeneous from a fractal viewpoint. Indeed, the analysis of this map reveals the presence of two distinctive landscape units corresponding to the Mt. Vesuvio and Gran Cono. The comparison with the (simplified) geological map clearly shows the presence in these two areas of volcanic products of different age. The presented fractal dimension map analysis demonstrates the ability to get a figure about the evolution degree of the monitored volcanic edifice and can be profitably extended in the future to other volcanic systems with

  2. Design and Implementation of a Real-time Processing System of Full Resolution Quick-look Image of HJ-1 Environmental Satellite C SAR Based on High Performance Cluster

    Directory of Open Access Journals (Sweden)

    Li Jing-shan

    2014-06-01

    Full Text Available This study is concerned with the design and implementation of a real-time processing system of full resolution quick-look image of HJ-1 environmental satellite C SAR based on high-performance clusters. The system processes the first quick-look SAR image on December 9, 2012. The results show that the design and implementation of the quick-look processing system satisfies the real-time SAR image processing performance requirements at full resolution. Moreover, this system is the first real-time business system of full-resolution quick-look spaceborne SAR images in China.

  3. 3D SAR approach to IF SAR processing

    Science.gov (United States)

    Doerry, Armin W.; Bickel, Doug

    2000-08-01

    Interferometric SAR (IFSAR) can be shown to be a special case of 3-D SAR image formation. In fact, traditional IFSAR processing results in the equivalent of merely a super- resolved, under-sampled, 3-D SAR image. However, when approached as a 3-D SAR problem, a number of IFSAR properties and anomalies are easily explained. For example, IFSAR decorrelation with height is merely ordinary migration in 3-D SAR. Consequently, treating IFSAR as a 3-D SAR problem allows insight and development of proper motion compensation techniques and image formation operations to facilitate optimal height estimation. Furthermore, multiple antenna phase centers and baselines are easily incorporated into this formulation, providing essentially a sparse array in the elevation dimension. This paper shows the Polar Format image formation algorithm extended to 3 dimensions, and then proceeds to apply it to the IFSAR collection geometry. This suggests a more optimal reordering of the traditional IFSAR processing steps.

  4. An improvement in SAR image interpretability provided by post-correlation signal processing

    Science.gov (United States)

    Matthews, N. D.; Kaupp, V. H.; Waite, W. P.; Macdonald, H. C.

    1983-01-01

    A presentation on the basis of subjective analysis of computer-generated SAR imagery depicts the improvement in interpretability obtained by post-correlation signal processing. A parametric study was conducted to determine the improvement in interpretability obtained by the application of signal weighting functions on the post-processed returns. The results suggest that a marked improvement in interpretability results from symmetrizing the exponential distribution of the fading signal. Preliminary analysis indicates that signal weighting improves the contrast ratio between the mean value of adjacent homogeneous regions in a SAR scene.

  5. Adventures in SAR processing

    Science.gov (United States)

    Fiedler, Ralph; Jansen, Robert

    2000-04-01

    The image formation process associated with coherent imaging sensor is particularly sensitive to and is often corrupted by non-stationary processes. In the case of SAR, non- stationary processes result from motion within the scene, variable radar cross section, multi-path, topographic variations, sensor anomalies, and deficiencies in the image formation processing chain. Conversely, stationary processes result in image signatures that appear literal to the eye, e.g., urban infrastructure, vegetation, and natural terrain. In analyzing SAR signal history two objectives unfold. One is to obtain a well-focused image devoid of distortions and non-literal artifacts. The second objective is the detection and value-added exploitation of the non-stationary signatures. Note that the roles of signal and clutter are reversed for these two objectives. The notion that joint time-frequency (JTF) techniques may prove useful in accomplishing these objectives has spurred limited investigations into the field of coherent radar imaging systems. This paper addresses SAR image formation processing, the complex response function for a point source, and SAR JTF image formation implementations. Each of these topics is described within the context of applying JTF processing to all aspects of SAR image formation and analysis.

  6. An easy to use ArcMap based texture analysis program for extraction of flooded areas from TerraSAR-X satellite image

    Science.gov (United States)

    Pradhan, Biswajeet; Hagemann, Ulrike; Shafapour Tehrany, Mahyat; Prechtel, Nikolas

    2014-02-01

    Extraction of the flooded areas from synthetic aperture radar (SAR) and especially TerraSAR-X data is one of the most challenging tasks in the flood management and planning. SAR data due to its high spatial resolution and its capability of all weather conditions makes a proper choice for tropical countries. Texture is considered as an effective factor in distinguishing the classes especially in SAR imagery which records the backscatters that carry information of kind, direction, heterogeneity and relationship of the features. This paper put forward a computer program for texture analysis for high resolution radar data. Texture analysis program is introduced and discussed using the gray-level co-occurrence matrix (GLCM). To demonstrate the ability and correctness of this program, a test subset of TerraSAR-X imagery from Terengganu area, Malaysia was analyzed and pixel-based and object-based classification were attempted. The thematic maps derived by pixel-based method could not achieve acceptable visual interpretation and for that reason no accuracy assessment was performed on them. The overall accuracy achieved by object-based method was 83.63% with kappa coefficient of 0.8. Results on image texture classification showed that the proposed program is capable for texture analysis in TerraSAR-X image and the obtained textural analysis resulted in high classification accuracy. The proposed texture analysis program can be used in many applications such as land use/cover (LULC) mapping, hazard studies and many other applications.

  7. Progress on the calibration of channel geometry and friction parameters of the LISFLOOD-FP hydraulic model using time series of SAR flood images

    Science.gov (United States)

    Wood, M.; Neal, J. C.; Hostache, R.; Corato, G.; Bates, P. D.; Chini, M.; Giustarini, L.; Matgen, P.; Wagener, T.

    2014-12-01

    The objective of this work is to calibrate channel depth and roughness parameters of the LISFLOOD-FP Sub-Grid 2D hydraulic model using SAR image-derived flood extent maps. The aim is to reduce uncertainty in flood model predictions for those rivers where channel geometry is unknown and/or cannot be easily measured. In particular we consider the effectiveness of using real SAR data for calibration and whether the number and timings of SAR acquisitions is of benefit to the final result. Terrain data are processed from 2m LiDAR images and inflows to the model are taken from gauged data. As a test case we applied the method to the River Severn between Worcester and Tewkesbury. We firstly applied the automatic flood mapping algorithm of Giustarini[1] et al. (2013) to ENVISAT ASAR (wide swath mode) flood images; generating a series of flood maps. We then created an ensemble of flood extent maps with the hydraulic model (each model representing a unique parameter set). Where there is a favourable comparison between the modelled flood map and the SAR obtained flood map we may suggest an optimal parameter set. Applying the method to a sequence of SAR acquisitions provides insight into the advantages, disadvantages and limitations of using series of acquired images. To complete the investigation we simultaneously explore parameter 'identifiabilty' within a sequence of available satellite observations by adopting the DYNIA method proposed by Wagener[2] et al. (2003). We show where we might most easily detect the depth and roughness parameters within the SAR acquisition sequence. [1] Giustarini. 2013. 'A Change Detection Approach to Flood Mapping in Urban Areas Using TerraSAR-X'. IEEE Transactions on Geoscience and Remote Sensing, vol. 51, no. 4. [2] Wagener. 2003. 'Towards reduced uncertainty in conceptual rainfall-runoff modelling: Dynamic identifiability analysis'. Hydrol. Process. 17, 455-476.

  8. Snow Water Equivalent Retrieval Using Multitemporal COSMO Skymed X-Band SAR Images To Inform Water Systems Operation

    Science.gov (United States)

    Denaro, S.; Del Gobbo, U.; Castelletti, A.; Tebaldini, S.; Monti Guarnieri, A.

    2015-12-01

    In this work, we explore the use of exogenous snow-related information for enhancing the operation of water facilities in snow dominated watersheds. Traditionally, such information is assimilated into short-to-medium term streamflow forecasts, which are then used to inform water systems operation. Here, we adopt an alternative model-free approach, where the policy is directly conditioned upon a small set of selected observational data able to surrogate the snow-pack dynamics. In snow-fed water systems, the Snow Water Equivalent (SWE) stored in the basin often represents the largest contribution to the future season streamflow. The SWE estimation process is challenged by the high temporal and spatial variability of snow-pack and snow properties. Traditional retrieval methods, based on few ground sensors and optical satellites, often fail at representing the spatial diversity of snow conditions over large basins and at producing continuous (gap-free) data at the high sample frequency (e.g. daily) required to optimally control water systems. Against this background, SWE estimates from remote sensed radar products stand out, being able to acquire spatial information with no dependence on cloud coverage. In this work, we propose a technique for retrieving SWE estimates from Synthetic Aperture Radar (SAR) Cosmo SkyMed X-band images: a regression model, calibrated on ground SWE measurements, is implemented on dry snow maps obtained through a multi-temporal approach. The unprecedented spatial scale of this application is novel w.r.t. state of the art radar analysis conducted on limited spatial domains. The operational value of the SAR retrieved SWE estimates is evaluated based on ISA, a recently developed information selection and assessment framework. The method is demonstrated on a snow-rain fed river basin in the Italian Alps. Preliminary results show SAR images have a good potential for monitoring snow conditions and for improving water management operations.

  9. 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.

  10. 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.

  11. Analysis of wind and wave events at the MIZ based on TerraSAR-X satellite images

    Science.gov (United States)

    Gebhardt, Claus; Bidlot, Jean-Raymond; Jacobsen, Sven; Lehner, Susanne; Pleskachevsky, Andrey; Singha, Suman

    2017-04-01

    The seasonal opening-up of large expanses of open water in the Beaufort/Chukchi Sea is a phenomenon observed in recent years. The diameter of the open-water area is on the order of 1000 km around the sea ice minimum in summer. Thus, wind events in the area are accompanied by the build-up of sea waves. Significant wave heights of few to several meters may be reached. Under low to moderate winds, the morphology of the MIZ is governed by oceanic forcing. As a result, the MIZ resembles ocean circulation features such as eddies, meanders, etc.. In the case of strong wind events, however, the wind forcing may gain control. We analyse effects related to wind and wave events at the MIZ using TerraSAR-X satellite imagery. Methods such as the retrieval of sea state and wind data by empirical algorithms and automatic sea ice classification are applied. This is facilitated by a series of TerraSAR-X images acquired in support of a cruise of the research vessel R/V Sikuliaq in the Beaufort/Chukchi Sea in autumn 2015. For selected images, the results are presented and compared to numerical model forecasts which were as well part of the cruise support.

  12. Road Extraction from High-Resolution SAR Images via Automatic Local Detecting and Human-Guided Global Tracking

    Directory of Open Access Journals (Sweden)

    Jianghua Cheng

    2012-01-01

    Full Text Available Because of existence of various kinds of disturbances, layover effects, and shadowing, it is difficult to extract road from high-resolution SAR images. A new road center-point searching method is proposed by two alternant steps: local detection and global tracking. In local detection step, double window model is set, which consists of the outer fixed square window and the inner rotary rectangular one. The outer window is used to obtain the local road direction by using orientation histogram, based on the fact that the surrounding objects always range along with roads. The inner window rotates its orientation in accordance with the result of local road direction calculation and searches the center points of a road segment. In global tracking step, particle filter of variable-step is used to deal with the problem of tracking frequently broken by shelters along the roadside and obstacles on the road. Finally, the center-points are linked by quadratic curve fitting. In 1 m high-resolution airborne SAR image experiment, the results show that this method is effective.

  13. 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.

  14. 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.

  15. Lagrangian-based Backtracking of Oil Spill Dynamics from SAR Images: Application to Montara Case

    Science.gov (United States)

    Gautama, Budhi Gunadharma; Mercier, Gregoire; Fablet, Ronan; Longepe, Nicolas

    2016-08-01

    Within the framework of INDESO project (Infrastructure Development Space Oceanography), we address the issue of oilspill and aim at developing an operational SAR- based system for monitoring this issue in Indonesian waters from space. In this work, we focus on the backtrack- ing of an oilspill detected from SAR observations. As a case-study, we consider one large oil spill event that happened in Indonesian waters in 2009, referred to as the Montara oilspill. On 21 August 2009, the Montara Wellhead Platform had an uncontrolled release of hydrocarbons from one of the platform wells. It was estimated that 400 barrels (or approximately 64 tonnes) of crude oil were being lost per day. The uncontrolled release continued until 3 November 2009 and response operations continued until 3 December 2009. In this work, we develop a Langragian analysis and associated numerical inversion tools with a view to further analyzing the oil spread due to the Montara Wellhead Platform. Our model relies on a 2D Lagrangian transport model developed by CLS (Collecte Localisation Satellite). Our model involves four main parameters : the weights of wind- related and current-related advection, the origin and the duration of the oil leakage. Given SAR oilspill detections, we propose a numerical inversion of the parameters of the Lagrangian model, so that the simulated drift match the SAR observations of the oil spill. We demonstrate the relevance of the proposed model and numerical scheme for the Montara oilspill and further discuss their operational interest for the space-based oilspill backtracking and forecasting.

  16. A new scheme for urban impervious surface classification from SAR images

    Science.gov (United States)

    Zhang, Hongsheng; Lin, Hui; Wang, Yunpeng

    2018-05-01

    Urban impervious surfaces have been recognized as a significant indicator for various environmental and socio-economic studies. There is an increasingly urgent demand for timely and accurate monitoring of the impervious surfaces with satellite technology from local to global scales. In the past decades, optical remote sensing has been widely employed for this task with various techniques. However, there are still a range of challenges, e.g. handling cloud contamination on optical data. Therefore, the Synthetic Aperture Radar (SAR) was introduced for the challenging task because it is uniquely all-time- and all-weather-capable. Nevertheless, with an increasing number of SAR data applied, the methodology used for impervious surfaces classification remains unchanged from the methods used for optical datasets. This shortcoming has prevented the community from fully exploring the potential of using SAR data for impervious surfaces classification. We proposed a new scheme that is comparable to the well-known and fundamental Vegetation-Impervious surface-Soil (V-I-S) model for mapping urban impervious surfaces. Three scenes of fully polarimetric Radsarsat-2 data for the cities of Shenzhen, Hong Kong and Macau were employed to test and validate the proposed methodology. Experimental results indicated that the overall accuracy and Kappa coefficient were 96.00% and 0.8808 in Shenzhen, 93.87% and 0.8307 in Hong Kong and 97.48% and 0.9354 in Macau, indicating the applicability and great potential of the new scheme for impervious surfaces classification using polarimetric SAR data. Comparison with the traditional scheme indicated that this new scheme was able to improve the overall accuracy by up to 4.6% and Kappa coefficient by up to 0.18.

  17. SAR Systems and Related Signal Processing

    NARCIS (Netherlands)

    Hoogeboom, P.; Dekker, R.J.; Otten, M.P.G.

    1996-01-01

    Synthetic Aperture Radar (SAR) is today a valuable source of remote sensing information. SAR is a side-looking imaging radar and operates from airborne and spacebome platforms. Coverage, resolution and image quality are strongly influenced by the platform. SAR processing can be performed on standard

  18. 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...

  19. Classification of very high resolution SAR images of urban areas by dictionary-based mixture models, copulas, and Markov random fields using textural features

    Science.gov (United States)

    Voisin, Aurélie; Moser, Gabriele; Krylov, Vladimir A.; Serpico, Sebastiano B.; Zerubia, Josiane

    2010-10-01

    This paper addresses the problem of the classification of very high resolution (VHR) SAR amplitude images of urban areas. The proposed supervised method combines a finite mixture technique to estimate class-conditional probability density functions, Bayesian classification, and Markov random fields (MRFs). Textural features, such as those extracted by the greylevel co-occurrency method, are also integrated in the technique, as they allow to improve the discrimination of urban areas. Copulas are applied to estimate bivariate joint class-conditional statistics, merging the marginal distributions of both textural and SAR amplitude features. The resulting joint distribution estimates are plugged into a hidden MRF model, endowed with a modified Metropolis dynamics scheme for energy minimization. Experimental results with COSMO-SkyMed and TerraSAR-X images point out the accuracy of the proposed method, also as compared with previous contextual classifiers.

  20. Which Fault Segments Ruptured in the 2008 Wenchuan Earthquake and Which Did Not? New Evidence from Near‐Fault 3D Surface Displacements Derived from SAR Image Offsets

    KAUST Repository

    Feng, Guangcai

    2017-03-15

    The 2008 Mw 7.9 Wenchuan earthquake ruptured a complex thrust‐faulting system at the eastern edge of the Tibetan plateau and west of Sichuan basin. Though the earthquake has been extensively studied, several details about the earthquake, such as which fault segments were activated in the earthquake, are still not clear. This is in part due to difficult field access to the fault zone and in part due to limited near‐fault observations in Interferometric Synthetic Aperture Radar (InSAR) observations because of decorrelation. In this study, we address this problem by estimating SAR image offsets that provide near‐fault ground displacement information and exhibit clear displacement discontinuities across activated fault segments. We begin by reanalyzing the coseismic InSAR observations of the earthquake and then mostly eliminate the strong ionospheric signals that were plaguing previous studies by using additional postevent images. We also estimate the SAR image offsets and use their results to retrieve the full 3D coseismic surface displacement field. The coseismic deformation from the InSAR and image‐offset measurements are compared with both Global Positioning System and field observations. The results indicate that our observations provide significantly better information than previous InSAR studies that were affected by ionospheric disturbances. We use the results to present details of the surface‐faulting offsets along the Beichuan fault from the southwest to the northeast and find that there is an obvious right‐lateral strike‐slip component (as well as thrust faulting) along the southern Beichuan fault (in Yingxiu County), which was strongly underestimated in earlier studies. Based on the results, we provide new evidence to show that the Qingchuan fault was not ruptured in the 2008 Wenchuan earthquake, a topic debated in field observation studies, but show instead that surface faulting occurred on a northward extension of the Beichuan fault during

  1. Assessment of Off-shore Wind Energy Resource in China using QuikSCAT Satellite data and SAR Satellite Images

    DEFF Research Database (Denmark)

    Xiuzhi, Zhang; Yanbo, Shen; Jingwei, Xu

    2010-01-01

    From August 2008 to August 2009, the project ‘Off-Shore Wind Energy Resource Assessment and Feasibility Study of Off-Shore Wind Farm Development in China’ was carried out by China Meteorological Administration (CMA), which was funded by the EU-China Energy and Environment Programme (EEP). As one ...... part of the project, off-shore wind energy resource in China was assessed with QuikSCAT Satellite data and SAR Satellite Images. In this paper, the results from these two ways were introduced.......From August 2008 to August 2009, the project ‘Off-Shore Wind Energy Resource Assessment and Feasibility Study of Off-Shore Wind Farm Development in China’ was carried out by China Meteorological Administration (CMA), which was funded by the EU-China Energy and Environment Programme (EEP). As one...

  2. 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.

  3. The Advanced Rapid Imaging and Analysis (ARIA) Project: Providing Standard and On-Demand SAR products for Hazard Science and Hazard Response

    Science.gov (United States)

    Owen, S. E.; Hua, H.; Rosen, P. A.; Agram, P. S.; Webb, F.; Simons, M.; Yun, S. H.; Sacco, G. F.; Liu, Z.; Fielding, E. J.; Lundgren, P.; Moore, A. W.

    2017-12-01

    A new era of geodetic imaging arrived with the launch of the ESA Sentinel-1A/B satellites in 2014 and 2016, and with the 2016 confirmation of the NISAR mission, planned for launch in 2021. These missions assure high quality, freely and openly distributed regularly sampled SAR data into the indefinite future. These unprecedented data sets are a watershed for solid earth sciences as we progress towards the goal of ubiquitous InSAR measurements. We now face the challenge of how to best address the massive volumes of data and intensive processing requirements. Should scientists individually process the same data independently themselves? Should a centralized service provider create standard products that all can use? Are there other approaches to accelerate science that are cost effective and efficient? The Advanced Rapid Imaging and Analysis (ARIA) project, a joint venture co-sponsored by California Institute of Technology (Caltech) and by NASA through the Jet Propulsion Laboratory (JPL), is focused on rapidly generating higher level geodetic imaging products and placing them in the hands of the solid earth science and local, national, and international natural hazard communities by providing science product generation, exploration, and delivery capabilities at an operational level. However, there are challenges in defining the optimal InSAR data products for the solid earth science community. In this presentation, we will present our experience with InSAR users, our lessons learned the advantages of on demand and standard products, and our proposal for the most effective path forward.

  4. Physics in the Spotlight

    Science.gov (United States)

    2000-10-01

    journalists to take part in this both politically and visually interesting event. We expect many useful results from this exchange of experience, there will a large choice of potential interview partners and of course uncountable images and impressions. Please fill in the form below and fax it back to CERN under +41 22 7850247. Go to the Webpage http://www.cern.ch/pos to find out all about Physics on Stage Festival at CERN. The main "Physics on Stage" web address is: http://www.estec.esa.nl/outreach/pos There is also a Physics On Stage webpage at ESO Notes [1] This is a joint Press Release by the European Organization for Nuclear Research (CERN) , the European Space Agency (ESA) and the European Southern Observatory (ESO). [2] The 22 countries are the member countries of at least one of the participating organisations or the European Union: Austria, Belgium, Bulgaria, the Czech Republic, Denmark, Finland, France, Germany, Greece, Hungary, Ireland, Italy, Luxembourg, the Netherlands, Norway, Poland, Portugal, the Slovak Republic, Spain, Sweden, Switzerland, United Kingdom.

  5. Large scale rock slope release planes imaged by differential ground based InSAR at Randa, Switzerland

    Science.gov (United States)

    Gischig, V.; Loew, S.; Kos, A.; Raetzo, H.

    2009-04-01

    In April and May of 1991 a steep rock slope above the village of Randa (Valais, Switzerland) failed in two events, releasing a total rock volume of 30 million m3. The rock mass behind the back scarp contains several million cubic meters of unstable gneisses and schists which are moving with a maximum rate of about 2 cm/yr. Different geodetic, geotechnical and geophysical techniques were applied to monitor this new instability and to determine its spatial extent. However, the boundaries of the instability could only be roughly estimated so far. For this reason five ground based differential InSAR surveys (GB-DInSAR) were carried out between 2005 and 2007 from the opposite valley flank at a distance to target of 1.3 to 1.9 km. These surveys provide displacements maps of four different time intervals with a spatial resolution of 2 to 6 m and an accuracy of less than 1 mm. These datasets reveal interesting new insights into the spatial distribution of displacements and significantly contribute to the kinematic interpretation of the ongoing movements. We found that the lower boundary of the instability is a narrow rupture plane which coincides with a primary lithological boundary on the slope. The intersection line between this basal rupture plane and the steep rock cliff extents over at least 200 m meters. It is possible to identify this structure on helicopter-based high resolution images and a LiDAR DTM of the failure surface. The eastern boundary of the instability also presents itself as a sharp line separating stable bedrock from a strongly fractured rock mass moving about 1 cm/yr along the line of sight. This lateral release plane is formed by a steeply east dipping tectonic fault plane, with subhorizontal striations and an exposed surface area of about 10'000 square meters. In the north-east of the instability the lateral boundaries crop out on surfaces that have an acute angle to the line of sight or lie in the shadow of the radar. Here the boundaries of the

  6. DARK SPOT DETECTION USING INTENSITY AND THE DEGREE OF POLARIZATION IN FULLY POLARIMETRIC SAR IMAGES FOR OIL POLUTION MONITORING

    Directory of Open Access Journals (Sweden)

    F. Zakeri

    2015-12-01

    Full Text Available Oil spill surveillance is of great environmental and economical interest, directly contributing to improve environmental protection. Monitoring of oil spills using synthetic aperture radar (SAR has received a considerable attention over the past few years, notably because of SAR data abilities like all-weather and day-and-night capturing. The degree of polarization (DoP is a less computationally complex quantity characterizing a partially polarized electromagnetic field. The key to the proposed approach is making use of DoP as polarimetric information besides intensity ones to improve dark patches detection as the first step of oil spill monitoring. In the proposed approach first simple intensity threshold segmentation like Otsu method is applied to the image. Pixels with intensities below the threshold are regarded as potential dark spot pixels while the others are potential background pixels. Second, the DoP of potential dark spot pixels is estimated. Pixels with DoP below a certain threshold are the real dark-spot pixels. Choosing the threshold is a critical and challenging step. In order to solve choosing the appropriate threshold, we introduce a novel but simple method based on DoP of potential dark spot pixels. Finally, an area threshold is used to eliminate any remaining false targets. The proposed approach is tested on L band NASA/JPL UAVSAR data, covering the Deepwater Horizon oil spill in the Gulf of Mexico. Comparing the obtained results from the new method with conventional approaches like Otsu, K-means and GrowCut shows better achievement of the proposed algorithm. For instance, mean square error (MSE 65%, Overall Accuracy 20% and correlation 40% are improved.

  7. Dark SPOT Detection Using Intensity and the Degree of Polarization in Fully Polarimetric SAR Images for Oil Polution Monitoring

    Science.gov (United States)

    Zakeri, F.; Amini, J.

    2015-12-01

    Oil spill surveillance is of great environmental and economical interest, directly contributing to improve environmental protection. Monitoring of oil spills using synthetic aperture radar (SAR) has received a considerable attention over the past few years, notably because of SAR data abilities like all-weather and day-and-night capturing. The degree of polarization (DoP) is a less computationally complex quantity characterizing a partially polarized electromagnetic field. The key to the proposed approach is making use of DoP as polarimetric information besides intensity ones to improve dark patches detection as the first step of oil spill monitoring. In the proposed approach first simple intensity threshold segmentation like Otsu method is applied to the image. Pixels with intensities below the threshold are regarded as potential dark spot pixels while the others are potential background pixels. Second, the DoP of potential dark spot pixels is estimated. Pixels with DoP below a certain threshold are the real dark-spot pixels. Choosing the threshold is a critical and challenging step. In order to solve choosing the appropriate threshold, we introduce a novel but simple method based on DoP of potential dark spot pixels. Finally, an area threshold is used to eliminate any remaining false targets. The proposed approach is tested on L band NASA/JPL UAVSAR data, covering the Deepwater Horizon oil spill in the Gulf of Mexico. Comparing the obtained results from the new method with conventional approaches like Otsu, K-means and GrowCut shows better achievement of the proposed algorithm. For instance, mean square error (MSE) 65%, Overall Accuracy 20% and correlation 40% are improved.

  8. Improved techniques to utilize remotely sensed data from multi-frequency imaging radar polarimeter; Tashuha tahenha SAR data no riyoho no kenkyu

    Energy Technology Data Exchange (ETDEWEB)

    Okada, K. [Sumitomo Metal Mining Co. Ltd., Osaka (Japan); Maruyama, Y. [Earth Remote Sensing Data Analysis Center, Tokyo (Japan); Tapley, I.

    1997-05-27

    It was intended to serve for establishing specifications for a next generation SAR such as PALSAR through studying methods for evaluating and utilizing the multi-frequency, multi-polarized wave SAR data. Placing an emphasis on utilization of the NASA`s AIRSAR, identification was made on backscatter amount recorded on the SAR data, terrestrial constitutional substances, patterns of the ground surface, micro-topography and such terrestrial conditions as vegetation and land utilization. Their mutual relationships were also analyzed. A noise reduction method usable on multi-band data can be applied to the AIRSAR data, and can reduce noise effectively. Images with more volume of information can be acquired from multi-band images with the same polarization wave than from multi-polarization wave images with the same band. As a result of estimating terrestrial permitivity by using the method invented by Dubois and van Zyl, most of the subject area is judged to have terrestrial substances dried at the time of having acquired the images. A colluvium rich with exposed rock regions and gravels was identified as an area having higher permitivity than the former area. Images of terrestrial roughness were divided largely into smooth flat lands, sand and gravel distributed regions, exposed rock regions, and plant distributed regions along river basins. 3 refs., 2 figs., 1 tab.

  9. The Advanced Rapid Imaging and Analysis (ARIA) Project: Status of SAR products for Earthquakes, Floods, Volcanoes and Groundwater-related Subsidence

    Science.gov (United States)

    Owen, S. E.; Yun, S. H.; Hua, H.; Agram, P. S.; Liu, Z.; Sacco, G. F.; Manipon, G.; Linick, J. P.; Fielding, E. J.; Lundgren, P.; Farr, T. G.; Webb, F.; Rosen, P. A.; Simons, M.

    2017-12-01

    The Advanced Rapid Imaging and Analysis (ARIA) project for Natural Hazards is focused on rapidly generating high-level geodetic imaging products and placing them in the hands of the solid earth science and local, national, and international natural hazard communities by providing science product generation, exploration, and delivery capabilities at an operational level. Space-based geodetic measurement techniques including Interferometric Synthetic Aperture Radar (InSAR), differential Global Positioning System, and SAR-based change detection have become critical additions to our toolset for understanding and mapping the damage and deformation caused by earthquakes, volcanic eruptions, floods, landslides, and groundwater extraction. Up until recently, processing of these data sets has been handcrafted for each study or event and has not generated products rapidly and reliably enough for response to natural disasters or for timely analysis of large data sets. The ARIA project, a joint venture co-sponsored by the California Institute of Technology and by NASA through the Jet Propulsion Laboratory, has been capturing the knowledge applied to these responses and building it into an automated infrastructure to generate imaging products in near real-time that can improve situational awareness for disaster response. In addition to supporting the growing science and hazard response communities, the ARIA project has developed the capabilities to provide automated imaging and analysis capabilities necessary to keep up with the influx of raw SAR data from geodetic imaging missions such as ESA's Sentinel-1A/B, now operating with repeat intervals as short as 6 days, and the upcoming NASA NISAR mission. We will present the progress and results we have made on automating the analysis of Sentinel-1A/B SAR data for hazard monitoring and response, with emphasis on recent developments and end user engagement in flood extent mapping and deformation time series for both volcano

  10. Subsurface and through-wall SAR imaging techniques for ground penetrating radar

    Directory of Open Access Journals (Sweden)

    Unal M.

    2013-12-01

    Full Text Available This paper presents some useful signal processing and synthetic aperture radar imaging techniques for ultra-wide band (UWB ground penetrating radar. Novel UWB antenna structures are experimentally designed in this work. Raw and processed data collected in the course of experimental studies of subsurface sensing and through-wall imaging scenarios are demonstrated in B-scan and C-scan target images.

  11. Fusion of optical and SAR remote sensing images for tropical forests monitoring

    Science.gov (United States)

    Wang, C.; Yu, M.; Gao, Q.; Wang, X.

    2016-12-01

    Although tropical deforestation prevails in South America and Southeast Asia, reforestation appeared in some tropical regions due to economic changes. After the economic shift from agriculture to industry, the tropical island of Puerto Rico has experienced rapid reforestation as well as urban expansion since the late 1940s. Continued urban growth without the guide of sustainable planning might prevent further forest regrowth. Accurate and timely mapping of LULC is of great importance for evaluating the consequences of reforestation and urban expansion on the coupled human and nature systems. However, owning to persistent cloud cover in tropics, it remains a challenge to produce reliable LULC maps in fine spatial resolution. Here, we retrieved cloud-free Landsat surface reflectance composite data by removing clouds and shades from the USGS Landsat Surface Reflectance (SR) product for each scene using the CFmask and Fmask algorithms in Google Earth Engine. We then produced high accuracy land cover classification maps using SR optical data for the year of 2000 and fused optical and ALOS SAR data for 2010 and 2015, with an overall accuracy of 92.0%, 92.5%, and 91.6%, respectively. The classification result indicated that a successive forest gain of 6.52% and 1.03% occurred between the first (2000-2010) and second (2010-2015) study periods, respectively. We also conducted a comparative spatial analysis of patterns of deforestation and reforestation based on a series of forest cover zones (50 × 50 pixels, 150 ha). The annual rates of deforestation and reforestation against forest cover presented the similar trends during two periods: decreasing with the forest cover increasing. However, the annual net forest change rate was different in the zones with forest cover less than 30%, presenting significant gain (2.2-8.4% yr-1) for the first period and significant loss (2.3-6.4% yr-1) for the second period. It indicated that both deforestation and reforestation mostly

  12. Oil spill detection from TerraSAR-X dual-polarized images using artificial neural network

    Science.gov (United States)

    Kim, D.; Jung, H.-S.

    2017-10-01

    Marine pollution from oil spills destroys ecosystems. In order to minimize the damage, it is important to fast cleanup it after predicting how the oil will spread. In order to predict the spread of oil spill, remote sensing technique, especially radar satellite image is widely used. In previous studies, only the back-scattering value is generally used for the detection of oil spill. However, in this study, oil spill was detected by applying ANN (Artificial Neural Network) as input data from the back-scattering value of the radar image as well as the phase information extracted from the dual polarization. In order to maximize the efficiency of oil spill detection using a back-scattering value, the speckle noise acting as an error factor should be removed first. NL-means filter was applied to multi-look image to remove it without smoothing of spatial resolution. In the coherence image, the sea has a high value and the oil spill area has a low value due to the scattering characteristics of the pulse. In order to using the characteristics of radar image, training sample was set up from NL-means filtered images(HH, VV) and coherence image, and ANN was applied to produce probability map of oil spill. In general, the value was 0.4 or less in the case of the sea, and the value was mainly in the range of 0.7 to 0.9 in the oil spill area. Using coherence images generated from different polarizations showed better detection results for relatively thin oil spill areas such as oil slick or oil sheen than using back-scattering information alone. It is expected that if the information about the look-alike of oil spill such as algae, internal wave and rainfall area is provided, the probability map can be produced with higher accuracy.

  13. Dual Super-Systolic Core for Real-Time Reconstructive Algorithms of High-Resolution Radar/SAR Imaging Systems

    Science.gov (United States)

    Atoche, Alejandro Castillo; Castillo, Javier Vázquez

    2012-01-01

    A high-speed dual super-systolic core for reconstructive signal processing (SP) operations consists of a double parallel systolic array (SA) machine in which each processing element of the array is also conceptualized as another SA in a bit-level fashion. In this study, we addressed the design of a high-speed dual super-systolic array (SSA) core for the enhancement/reconstruction of remote sensing (RS) imaging of radar/synthetic aperture radar (SAR) sensor systems. The selected reconstructive SP algorithms are efficiently transformed in their parallel representation and then, they are mapped into an efficient high performance embedded computing (HPEC) architecture in reconfigurable Xilinx field programmable gate array (FPGA) platforms. As an implementation test case, the proposed approach was aggregated in a HW/SW co-design scheme in order to solve the nonlinear ill-posed inverse problem of nonparametric estimation of the power spatial spectrum pattern (SSP) from a remotely sensed scene. We show how such dual SSA core, drastically reduces the computational load of complex RS regularization techniques achieving the required real-time operational mode. PMID:22736964

  14. Cognitive Vision and Perceptual Grouping by Production Systems with Blackboard Control - An Example for High-Resolution SAR-Images

    Science.gov (United States)

    Michaelsen, Eckart; Middelmann, Wolfgang; Sörgel, Uwe

    The laws of gestalt-perception play an important role in human vision. Psychological studies identified similarity, good continuation, proximity and symmetry as important inter-object relations that distinguish perceptive gestalts from arbitrary sets of clutter objects. Particularly, symmetry and continuation possess a high potential in detection, identification, and reconstruction of man-made objects. This contribution focuses on coding this principle in an automatic production system. Such systems capture declarative knowledge. Procedural details are defined as control strategy for an interpreter. Often an exact solution is not feasible while approximately correct interpretations of the data with the production system are sufficient. Given input data and a production system the control acts accumulatively instead of reducing. The approach is assessment driven features any-time capability and fits well into the recently discussed paradigms of cognitive vision. An example from automatic extraction of groupings and symmetry in man-made structure from high resolution SAR-image data is given. The contribution also discusses the relations of such approach to the "mid-level" of what is today proposed as "cognitive vision".

  15. Landslide Deformation Analysis by Coupling Deformation Time Series from SAR Data with Hydrological Factors through Data Assimilation

    Directory of Open Access Journals (Sweden)

    Yanan Jiang

    2016-02-01

    Full Text Available Time-series SAR/InSAR techniques have proven to be effective tools for measuring landslide movements over large regions. Prior studies of these techniques, however, have focused primarily on technical innovation and applications, leaving coupling analysis of slope displacements and trigging factors as an unexplored area of research. Linking potential landslide inducing factors such as hydrology to SAR/InSAR derived displacements is of crucial importance for understanding landslide deformation mechanisms and could support the development of early-warning systems for disaster mitigation and management. In this study, a sequential data assimilation method named the Ensemble Kalman filter (EnKF, is adopted to explore the response mechanisms of the Shuping landslide movement in relation to hydrological factors. Previous research on the Shuping landslide area shows that the reservoir water level and rainfall are the two main triggering factors in slope failures. To extract the time-series deformations for the Shuping landslide area, Pixel Offset Tracking (POT technique with corner reflectors was adopted to process the TerraSAR-X StripMap (SM and High-resolution Spotlight (HS images. Considering that these triggering factors are the primary causes of displacement fluctuations in periodic displacement, time-series decomposition was carried out to extract the periodic displacement from the POT measurements. The correlations between the periodic displacement and the inducing factors were qualitatively estimated through a grey relational analysis. Based on this analysis, the EnKF method was adopted to explore the response relationships between the displacements and triggering factors. Preliminary results demonstrate the effectiveness of EnKF in studying deformation response mechanisms and understanding landslide development processes.

  16. Best Accuracy Land Use/Land Cover (LULC Classification to Derive Crop Types Using Multitemporal, Multisensor, and Multi-Polarization SAR Satellite Images

    Directory of Open Access Journals (Sweden)

    Christoph Hütt

    2016-08-01

    Full Text Available When using microwave remote sensing for land use/land cover (LULC classifications, there are a wide variety of imaging parameters to choose from, such as wavelength, imaging mode, incidence angle, spatial resolution, and coverage. There is still a need for further study of the combination, comparison, and quantification of the potential of multiple diverse radar images for LULC classifications. Our study site, the Qixing farm in Heilongjiang province, China, is especially suitable to demonstrate this. As in most rice growing regions, there is a high cloud cover during the growing season, making LULC from optical images unreliable. From the study year 2009, we obtained nine TerraSAR-X, two Radarsat-2, one Envisat-ASAR, and an optical FORMOSAT-2 image, which is mainly used for comparison, but also for a combination. To evaluate the potential of the input images and derive LULC with the highest possible precision, two classifiers were used: the well-established Maximum Likelihood classifier, which was optimized to find those input bands, yielding the highest precision, and the random forest classifier. The resulting highly accurate LULC-maps for the whole farm with a spatial resolution as high as 8 m demonstrate the beneficial use of a combination of x- and c-band microwave data, the potential of multitemporal very high resolution multi-polarization TerraSAR-X data, and the profitable integration and comparison of microwave and optical remote sensing images for LULC classifications.

  17. Study on monitoring ecological restoration in Jiuli mining area by SAR image

    Science.gov (United States)

    Wei, Na; Chen, Fu; Tang, Qian

    2011-10-01

    The ecological restoration in mining area is one of the study hot spots in the field of resources and environment at present. The vegetation biomass is used as the ecological restoration evaluation index in mining area in the paper. The synthetic aperture radar image after ecological restoration in mining area is used to classify different kinds of vegetation covers. Integrating the field data and the data of L band, the average total backward scattering coefficient which corresponds to the synthetic aperture radar image is calculated and the relation model between the average total backward scattering coefficient and vegetation biomass is established. At last the vegetation biomass is assessed in Jiuli mining area. The results show that the vegetation biomass characteristics which are assessed by using synthetic aperture radar image data and the field data of vegetation biomass characteristics have better consistency in Jiuli mining area. The effects of ecological restoration can be evaluated by using this relation model effectively and accurately.

  18. On the classification of mixed floating pollutants on the Yellow Sea of China by using a quad-polarized SAR image

    Science.gov (United States)

    Wang, Xiaochen; Shao, Yun; Tian, Wei; Li, Kun

    2017-09-01

    This study explored different methodologies using a C-band RADARSAT-2 quad-polarized Synthetic Aperture Radar (SAR) image located over China's Yellow Sea to investigate polarization decomposition parameters for identifying mixed floating pollutants from a complex ocean background. It was found that solitary polarization decomposition did not meet the demand for detecting and classifying multiple floating pollutants, even after applying a polarized SAR image. Furthermore, considering that Yamaguchi decomposition is sensitive to vegetation and the algal variety Enteromorpha prolifera, while H/A/alpha decomposition is sensitive to oil spills, a combination of parameters which was deduced from these two decompositions was proposed for marine environmental monitoring of mixed floating sea surface pollutants. A combination of volume scattering, surface scattering, and scattering entropy was the best indicator for classifying mixed floating pollutants from a complex ocean background. The Kappa coefficients for Enteromorpha prolifera and oil spills were 0.7514 and 0.8470, respectively, evidence that the composite polarized parameters based on quad-polarized SAR imagery proposed in this research is an effective monitoring method for complex marine pollution.

  19. A METHOD FOR THE EXTRACTION OF LONG-TERM DEFORMATION CHARACTERISTICS OF LONG-SPAN HIGH-SPEED RAILWAY BRIDGES USING HIGH-RESOLUTION SAR IMAGES

    Directory of Open Access Journals (Sweden)

    H. G. Jia

    2016-06-01

    Full Text Available Natural causes and high-speed train load will result in the structural deformation of long-span bridges, which greatly influence the safety operation of high-speed railway. Hence it is necessary to conduct the deformation monitoring and regular status assessment for long-span bridges. However for some traditional surveying technique, e.g. control-point-based surveying techniques, a lot of human and material resources are needed to perform the long-term monitoring for the whole bridge. In this study we detected the long-term bridge deformation time-series by persistent scatterer interferometric synthetic aperture radar (PSInSAR technique using the high-resolution SAR images and external digital elevation model. A test area in Nanjing city in China is chosen and TerraSAR-X images and Tandem-X for this area have been used. There is the Dashengguan bridge in high speed railway in this area as study object to evaluate this method. Experiment results indicate that the proposed method can effectively extract the long-term deformation of long-span high-speed railway bridge with higher accuracy.

  20. An improved MIMO-SAR simulator strategy with ray tracing

    Science.gov (United States)

    Xiang, Xingyu; Mo, Zijian; Wang, Zhonghai; Chen, Genshe; Pham, Khanh; Blasch, Erik

    2016-05-01

    High resolution and wide-swath imaging can be obtained by Multiple-Input Multiple-Output (MIMO) synthetic aperture radar (SAR) with the state of the art technologies. The time division multiple access (TDMA) MIMO SAR mimics the motion of the antenna of SAR systems by switching the array channels to transmit the radar signals at different time slots. In this paper, we develop a simulation tool with ray tracing techniques to retrieve high resolution and accurate SAR images for development of MIMO SAR imaging methods. Without loss of generality, in the proposed simulator, we apply a TDMA MIMO SAR system with 13 transmitting antennas and 8 receiving antennas, where all transmitting antennas share a single transmitter and the receiving antennas share a single receiver. By comparing with the normal simulation MIMO SAR strategies, the simulation image using ray tracing results validate that the proposed method provides more accurate and higher resolution SAR images.

  1. SARS virus

    Indian Academy of Sciences (India)

    First page Back Continue Last page Overview Graphics. SARS virus. Novel corona virus emerges in the new millenia. Genome sequences invariant- global isolates do not show differences of consequence.Protein spike similar. HE gene absent. 2787 nucleotides. Largest genome. Jumps species by genetic deletion.

  2. Bistatic SAR/ISAR/FSR geometry, signal models and imaging algorithms

    CERN Document Server

    Lazarov, Andon Dimitrov

    2013-01-01

    Bistatic radar consists of a radar system which comprises a transmitter and receiver which are separated by a distance comparable to the expected target distance. This book provides a general theoretical description of such bistatic technology in the context of synthetic aperture, inverse synthetic aperture and forward scattering radars from the point of view of analytical geometrical and signal formation as well as processing theory. Signal formation and image reconstruction algorithms are developed with the application of high informative linear frequency and phase code modulating techniques

  3. Prostate Magnetic Resonance Imaging and Magnetic Resonance Imaging Targeted Biopsy in Patients with a Prior Negative Biopsy: A Consensus Statement by AUA and SAR.

    Science.gov (United States)

    Rosenkrantz, Andrew B; Verma, Sadhna; Choyke, Peter; Eberhardt, Steven C; Eggener, Scott E; Gaitonde, Krishnanath; Haider, Masoom A; Margolis, Daniel J; Marks, Leonard S; Pinto, Peter; Sonn, Geoffrey A; Taneja, Samir S

    2016-12-01

    After an initial negative biopsy there is an ongoing need for strategies to improve patient selection for repeat biopsy as well as the diagnostic yield from repeat biopsies. As a collaborative initiative of the AUA (American Urological Association) and SAR (Society of Abdominal Radiology) Prostate Cancer Disease Focused Panel, an expert panel of urologists and radiologists conducted a literature review and formed consensus statements regarding the role of prostate magnetic resonance imaging and magnetic resonance imaging targeted biopsy in patients with a negative biopsy, which are summarized in this review. The panel recognizes that many options exist for men with a previously negative biopsy. If a biopsy is recommended, prostate magnetic resonance imaging and subsequent magnetic resonance imaging targeted cores appear to facilitate the detection of clinically significant disease over standardized repeat biopsy. Thus, when high quality prostate magnetic resonance imaging is available, it should be strongly considered for any patient with a prior negative biopsy who has persistent clinical suspicion for prostate cancer and who is under evaluation for a possible repeat biopsy. The decision of whether to perform magnetic resonance imaging in this setting must also take into account the results of any other biomarkers and the cost of the examination, as well as the availability of high quality prostate magnetic resonance imaging interpretation. If magnetic resonance imaging is done, it should be performed, interpreted and reported in accordance with PI-RADS version 2 (v2) guidelines. Experience of the reporting radiologist and biopsy operator are required to achieve optimal results and practices integrating prostate magnetic resonance imaging into patient care are advised to implement quality assurance programs to monitor targeted biopsy results. Patients receiving a PI-RADS assessment category of 3 to 5 warrant repeat biopsy with image guided targeting. While

  4. Interaction between magma intrusion and flank dynamics at Mt. Etna in 2008, imaged by integrated dense GPS and DInSAR data

    Science.gov (United States)

    Bonforte, Alessandro; Guglielmino, Francesco; Puglisi, Giuseppe

    2013-08-01

    Global positioning system (GPS) and differential interferometric synthetic aperture radar (DInSAR) data, collected from July 2007 to July 2008 on Mt. Etna, are analyzed to define the dynamics preceding and accompanying the onset of the eruption on 13 May 2008. Short- and long-term comparisons have been made on both GPS and radar data, covering similar time windows. Thanks to the availability of three GPS surveys the year before the eruption onset, an increase in the seaward movement of the NE flank of the volcano has been detected in the few months before the dike intrusion. The GPS ground deformation pattern also shows a slight inflation centered on the western side of the volcano in the preeruptive long-term comparison (from July 2007 to May 2008). The GPS has been integrated with DInSAR data by the SISTEM approach, to take advantage of the different methodologies and provide high spatial sampling of the 3-D ground displacement pattern. We inverted the SISTEM results to model the pressure source causing the observed preeruptive inflation. The subsequent emplacement of the eruptive dike was imaged by two GPS surveys carried out on a dense network over the uppermost part of the volcano on 6 and 13 May, i.e., a few days before and a few hours after the beginning of the eruption. We inverted this comparison to define the position, geometry, and kinematics of the dike. The dike intrusion was also imaged by DInSAR data with temporal baselines of 2-3 months, which confirm strong displacements localized on the summit area, rapidly decreasing toward the middle flanks of the volcano, as detected by very short-term GPS data; furthermore, the comparison between DInSAR and GPS data highlighted the presence of a depressurizing source localized beneath the upper southwestern area, acting just after the dike intrusion. Finally, the long-period (1 year) GPS and DInSAR data were integrated by SISTEM to finely depict the 3-D ground deformation pattern with the highest spatial

  5. Holding a spotlight to an ageing society.

    Science.gov (United States)

    Cann, Paul

    2008-07-01

    In May 2008 Help the Aged published its 3rd annual Spotlight Report. The report highlights the stark realities facing older people in the UK today and gives detailed statistical data on how the lives of some have improved but many are still being left behind.

  6. Design and characterization of a 12-bit 10MS/s 10mW pipelined SAR ADC for CZT-based hard X-ray imager

    Science.gov (United States)

    Xue, F.; Gao, W.; Duan, Y.; Zheng, R.; Hu, Y.

    2018-02-01

    This paper presents a 12-bit pipelined successive approximation register (SAR) ADC for CZT-based hard X-ray Imager. The proposed ADC is comprised of a first-stage 6-bit SAR-based Multiplying Digital Analog Converter (MDAC) and a second-stage 8-bit SAR ADC. A novel MDAC architecture using Vcm-based Switching method is employed to maximize the energy efficiency and improve the linearity of the ADC. Moreover, the unit-capacitor array instead of the binary-weighted capacitor array is adopted to improve the conversion speed and linearity of the ADC in the first-stage MDAC. In addition, a new layout design method for the binary-weighted capacitor array is proposed to reduce the capacitor mismatches and make the routing become easier and less-time-consuming. Finally, several radiation-hardened-by-design technologies are adopted in the layout design against space radiation effects. The prototype chip was fabricated in 0.18 μm mixed-signal 1.8V/3.3V process and operated at 1.8 V supply. The chip occupies a core area of only 0.58 mm2. The proposed pipelined SAR ADC achieves a peak signal-to-noise-and-distortion ratio (SNDR) of 66.7 dB and a peak spurious-free dynamic range (SFDR) of 78.6 dB at 10 MS/s sampling rate and consumes 10 mW. The figure of merit (FOM) of the proposed ADC is 0.56 pJ/conversion-step.

  7. Change analysis at Stuttgart airport using TerraSAR-X imagery

    Science.gov (United States)

    Boldt, Markus; Thiele, Antje; Cadario, Erich; Schulz, Karsten; Hinz, Stefan

    2014-10-01

    Change detection based on remote sensing imagery is a topic highly on demand with various fields of application. Probably, disaster management is the best known, where it is crucial to get fast and reliable results to enable a suitable supply of the affected region. Another important issue, for example in city or land-use planning, is the regular monitoring of specific regions of interest. For both scenarios, it would be significant to have information about the type or category of the detected changes. Since High-Resolution (HR) Synthetic Aperture Radar (SAR) is in opposite to optical sensors an active technique, it is well-capable for all change detection topics where a regular monitoring is intended. SAR sensors illuminate the investigated scene by their own microwave radiation and most applied microwave wavelengths make SAR nearly independent from atmospheric effects like dust, fog, and clouds. Moreover, the time of day makes no difference using SAR sensors. Acquired in HR SpotLight mode 300 (HS300) by the German satellite TerraSAR-X (TSX), images have a resolution of better than one meter, which allows to separate small objects placed close together. In this paper, a concept of change analysis focusing on small-sized areas is presented. Those change areas can be caused by man-made objects (e.g. vehicles, small construction sites) or natural events like phenologically based changes of the vegetation. Since the presented change analysis concept deals with the analysis of time series imagery, other seasonal also man-made caused changes (e.g. agriculture) can be detected. Furthermore, the concept comprises the categorization of the detected changes, which separates it from many of the existing change detection approaches. It includes five central components given by the change detection itself, the pre-categorization of change pixels, the feature extraction for change blobs, the analysis of their spatial context, and the final decision making forming a

  8. SAR processing using SHARC signal processing systems

    Science.gov (United States)

    Huxtable, Barton D.; Jackson, Christopher R.; Skaron, Steve A.

    1998-09-01

    Synthetic aperture radar (SAR) is uniquely suited to help solve the Search and Rescue problem since it can be utilized either day or night and through both dense fog or thick cloud cover. Other papers in this session, and in this session in 1997, describe the various SAR image processing algorithms that are being developed and evaluated within the Search and Rescue Program. All of these approaches to using SAR data require substantial amounts of digital signal processing: for the SAR image formation, and possibly for the subsequent image processing. In recognition of the demanding processing that will be required for an operational Search and Rescue Data Processing System (SARDPS), NASA/Goddard Space Flight Center and NASA/Stennis Space Center are conducting a technology demonstration utilizing SHARC multi-chip modules from Boeing to perform SAR image formation processing.

  9. Simultaneous Navigation and SAR Auto-Focusing

    OpenAIRE

    Sjanic, Zoran; Gustafsson, Fredrik

    2010-01-01

    Synthetic Aperture Radar (SAR) equipment is an all-weather radar imaging system that can create high resolution images by means of utilising the movement of the flying platform. Accurate knowledge of the flown trajectory is essential in order to get focused images. Recently SAR systems are becoming more used on smaller and cheaper flying platforms like Unmanned Aerial Vehicles (UAV). Since UAVs in general have navigation systems with poorer performance than manned aircraft, the resulting images ...

  10. Analysis of summer subsidence in Barrow, Alaska, using InSAR and hyperspectral remote sensing

    OpenAIRE

    Mahmud Haghshenas Haghighi; M. Motagh; B. Heim; S. Chabrillat; D. Streletskiy; G. Grosse; T. Sachs; Katrin Kohnert

    2016-01-01

    In this study, gradual elevation change due to summer thawing of active layer in tundra permafrost landscape of Barrow, Alaska is investigated using SAR interferometry (InSAR) technique. We used a variety of SAR sensors including TerraSAR-X, ALOS, and Sentinel-1 images to assess elevation changes in summer season. Preliminary result, obtained by TerraSAR-X InSAR analysis, clearly delineates subsidence during the summer by identifying thousands of coherent pixels on ...

  11. SAR change detection techniques and applications

    NARCIS (Netherlands)

    Dekker, R.J.

    2005-01-01

    ABSTRACT: Change detection, the comparison of remote sensing images from different moments in time, is an important technique in environmental earth observation and security. SAR change detection is useful when weather and light conditions are unfavourable. Five methods of SAR change detection are

  12. SAR/MTI on small airborne platforms

    NARCIS (Netherlands)

    Rossum, W.L. van; Vermeulen, B.C.B.

    2006-01-01

    A small SAR-MTI system is being developed at TNO, aimed at deployment on tactical UAV. The system makes use of modern front-end technology, to provide flexible SAR imaging and MTI modes. Major design goals are 50 kg weight, 500 W power consumption and 50 cm resolution in order to comply with typical

  13. Imaging the complex geometry of a magma reservoir using FEM-based linear inverse modeling of InSAR data: application to Rabaul Caldera, Papua New Guinea

    Science.gov (United States)

    Ronchin, Erika; Masterlark, Timothy; Dawson, John; Saunders, Steve; Martì Molist, Joan

    2017-06-01

    We test an innovative inversion scheme using Green's functions from an array of pressure sources embedded in finite-element method (FEM) models to image, without assuming an a-priori geometry, the composite and complex shape of a volcano deformation source. We invert interferometric synthetic aperture radar (InSAR) data to estimate the pressurization and shape of the magma reservoir of Rabaul caldera, Papua New Guinea. The results image the extended shallow magmatic system responsible for a broad and long-term subsidence of the caldera between 2007 February and 2010 December. Elastic FEM solutions are integrated into the regularized linear inversion of InSAR data of volcano surface displacements in order to obtain a 3-D image of the source of deformation. The Green's function matrix is constructed from a library of forward line-of-sight displacement solutions for a grid of cubic elementary deformation sources. Each source is sequentially generated by removing the corresponding cubic elements from a common meshed domain and simulating the injection of a fluid mass flux into the cavity, which results in a pressurization and volumetric change of the fluid-filled cavity. The use of a single mesh for the generation of all FEM models avoids the computationally expensive process of non-linear inversion and remeshing a variable geometry domain. Without assuming an a-priori source geometry other than the configuration of the 3-D grid that generates the library of Green's functions, the geodetic data dictate the geometry of the magma reservoir as a 3-D distribution of pressure (or flux of magma) within the source array. The inversion of InSAR data of Rabaul caldera shows a distribution of interconnected sources forming an amorphous, shallow magmatic system elongated under two opposite sides of the caldera. The marginal areas at the sides of the imaged magmatic system are the possible feeding reservoirs of the ongoing Tavurvur volcano eruption of andesitic products on the

  14. Imaging irregular magma reservoirs with InSAR and GPS observations: Application to Kilauea and Copahue volcanoes

    Science.gov (United States)

    Lundgren, P.; Camacho, A.; Poland, M. P.; Miklius, A.; Samsonov, S. V.; Milillo, P.

    2013-12-01

    The availability of synthetic aperture radar (SAR) interferometry (InSAR) data has increased our awareness of the complexity of volcano deformation sources. InSAR's spatial completeness helps identify or clarify source process mechanisms at volcanoes (i.e. Mt. Etna east flank motion; Lazufre crustal magma body; Kilauea dike complexity) and also improves potential model realism. In recent years, Bayesian inference methods have gained widespread use because of their ability to constrain not only source model parameters, but also their uncertainties. They are computationally intensive, however, which tends to limit them to a few geometrically rather simple source representations (for example, spheres). An alternative approach involves solving for irregular pressure and/or density sources from a three-dimensional (3-D) grid of source/density cells. This method has the ability to solve for arbitrarily shaped bodies of constant absolute pressure/density difference. We compare results for both Bayesian (a Markov chain Monte Carlo algorithm) and the irregular source methods for two volcanoes: Kilauea, Hawaii, and Copahue, Argentina-Chile border. Kilauea has extensive InSAR and GPS databases from which to explore the results for the irregular method with respect to the Bayesian approach, prior models, and an extensive set of ancillary data. One caveat, however, is the current restriction in the irregular model inversion to volume-pressure sources (and at a single excess pressure change), which limits its application in cases where sources such as faults or dikes are present. Preliminary results for Kilauea summit deflation during the March 2011 Kamoamoa eruption suggests a northeast-elongated magma body lying roughly 1-1.5 km below the surface. Copahue is a southern Andes volcano that has been inflating since early 2012, with intermittent summit eruptive activity since late 2012. We have an extensive InSAR time series from RADARSAT-2 and COSMO-SkyMed data, although both are

  15. A novel flood detection mapping using multi-temporal RADARSAT-2 and TerraSAR-X images through an optimized Taguchi based classification technique

    Science.gov (United States)

    Pradhan, Biswajeet

    2016-07-01

    Floods are considered as one of the most common natural disasters in Malaysia. Preparation of an actuate flood inventory map is the basic step in flood risk management. Flood detection is yet significantly complex process due to the presence of cloud coverage in the tropical areas especially in Malaysia. Moreover, the most available techniques are expensive and time-consuming. Therefore, in the present study an efficient approach is presented to identify the flooded areas by means of multi-temporal RADARSAT-2 and single Terra-SAR-X images. The proposed framework was tested at two tropical areas in Malaysia: Kelantan (2014 flood); and Kuala Terengganu (2009 flood) to map the flooded areas. Multi-temporal RADARSAT-2 and single TerrSAR-X and Landsat images were classified based on a rule-based object-oriented technique. Then, different levels of image segmentation was performed to distinguish the boundaries of various dimensions and scales of objects. Finally, a novel Taguchi based method was employed to optimize the segmentation parameters. After the completion of segmentation, the rules were defined and the images were classified to produce an accurate flood inventory map for both 2014 Kelantan flood event as well as 2009 flood event in Kuala Terengganu. Finally, the results of classification were measured through the confusion matrix. In this research, the combination of techniques and the optimization approach were applied as a pioneering approach for flood detection. The flood inventory map which was obtained by using the proposed approach is showing the efficiency of the methodology which can be applied by other researchers and decision makers to construct the flood inventory maps. Keywords: Radarsat 2; Multispectral imagery; flood detection; Taguchi; rule-based classification

  16. The SUMO Ship Detector Algorithm for Satellite Radar Images

    Directory of Open Access Journals (Sweden)

    Harm Greidanus

    2017-03-01

    Full Text Available Search for Unidentified Maritime Objects (SUMO is an algorithm for ship detection in satellite Synthetic Aperture Radar (SAR images. It has been developed over the course of more than 15 years, using a large amount of SAR images from almost all available SAR satellites operating in L-, C- and X-band. As validated by benchmark tests, it performs very well on a wide range of SAR image modes (from Spotlight to ScanSAR and resolutions (from 1–100 m and for all types and sizes of ships, within the physical limits imposed by the radar imaging. This paper describes, in detail, the algorithmic approach in all of the steps of the ship detection: land masking, clutter estimation, detection thresholding, target clustering, ship attribute estimation and false alarm suppression. SUMO is a pixel-based CFAR (Constant False Alarm Rate detector for multi-look radar images. It assumes a K distribution for the sea clutter, corrected however for deviations of the actual sea clutter from this distribution, implementing a fast and robust method for the clutter background estimation. The clustering of detected pixels into targets (ships uses several thresholds to deal with the typically irregular distribution of the radar backscatter over a ship. In a multi-polarization image, the different channels are fused. Azimuth ambiguities, a common source of false alarms in ship detection, are removed. A reliability indicator is computed for each target. In post-processing, using the results of a series of images, additional false alarms from recurrent (fixed targets including range ambiguities are also removed. SUMO can run in semi-automatic mode, where an operator can verify each detected target. It can also run in fully automatic mode, where batches of over 10,000 images have successfully been processed in less than two hours. The number of satellite SAR systems keeps increasing, as does their application to maritime surveillance. The open data policy of the EU

  17. Seismic imaging beneath an InSAR anomaly in eastern Washington State: Shallow faulting associated with an earthquake swarm in a low-hazard area

    Science.gov (United States)

    Stephenson, William J.; Odum, Jackson K.; Wicks, Chuck; Pratt, Thomas L.; Blakely, Richard J.

    2016-01-01

    In 2001, a rare swarm of small, shallow earthquakes beneath the city of Spokane, Washington, caused ground shaking as well as audible booms over a five‐month period. Subsequent Interferometric Synthetic Aperture Radar (InSAR) data analysis revealed an area of surface uplift in the vicinity of the earthquake swarm. To investigate the potential faults that may have caused both the earthquakes and the topographic uplift, we collected ∼3  km of high‐resolution seismic‐reflection profiles to image the upper‐source region of the swarm. The two profiles reveal a complex deformational pattern within Quaternary alluvial, fluvial, and flood deposits, underlain by Tertiary basalts and basin sediments. At least 100 m of arching on a basalt surface in the upper 500 m is interpreted from both the seismic profiles and magnetic modeling. Two west‐dipping faults deform Quaternary sediments and project to the surface near the location of the Spokane fault defined from modeling of the InSAR data.

  18. 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...

  19. 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...

  20. AUTOMATED WETLAND DELINEATION FROM MULTI-FREQUENCY AND MULTI-POLARIZED SAR IMAGES IN HIGH TEMPORAL AND SPATIAL RESOLUTION

    Directory of Open Access Journals (Sweden)

    L. Moser

    2016-06-01

    Full Text Available Water scarcity is one of the main challenges posed by the changing climate. Especially in semi-arid regions where water reservoirs are filled during the very short rainy season, but have to store enough water for the extremely long dry season, the intelligent handling of water resources is vital. This study focusses on Lac Bam in Burkina Faso, which is the largest natural lake of the country and of high importance for the local inhabitants for irrigated farming, animal watering, and extraction of water for drinking and sanitation. With respect to the competition for water resources an independent area-wide monitoring system is essential for the acceptance of any decision maker. The following contribution introduces a weather and illumination independent monitoring system for the automated wetland delineation with a high temporal (about two weeks and a high spatial sampling (about five meters. The similarities of the multispectral and multi-polarized SAR acquisitions by RADARSAT-2 and TerraSAR-X are studied as well as the differences. The results indicate that even basic approaches without pre-classification time series analysis or post-classification filtering are already enough to establish a monitoring system of prime importance for a whole region.

  1. Spotlight on GME/GHSE Supported Research

    Science.gov (United States)

    2017-12-07

    REPORT TYPE 3. DATES COVERED (From- To) 12/07/2017 Poster 4. TITLE AND SUBTITLE Sa. CONTRACT NUMBER Spotlight on GME/GHSE-Supported Research Sb...ORGANIZATION NAME(S) AND ADDRESS(ES) 8. PERFORMING ORGANIZATION 59th Clinical Research Division REPORT NUMBER 1100 Willford Hall Loop, Bldg 4430 JBSA... Research Division 1100 Willford Hall Loop, Bldg 4430 JBSA-Lack:land, TX 78236-9908 11. SPONSOR/MONITOR’S REPORT 210-292-7141 NUMBER(S) 12

  2. Alteration zone Mapping in the Meiduk and Sar Cheshmeh Porphyry Copper Mining Districts of Iran using Advanced Land Imager (ALI Satellite Data

    Directory of Open Access Journals (Sweden)

    A. Beiranvand Pour

    2015-10-01

    Full Text Available This study evaluates the capability of Earth Observing-1 (EO1 Advanced Land Imager (ALI data for hydrothermal alteration mapping in the Meiduk and Sar Cheshmeh porphyry copper mining districts, SE Iran. Feature-oriented principal components selection, 4/2, 8/9, 5/4 band ratioing were applied to ALI data for enhancing the hydrothermally altered rocks associated with porphyry copper mineralization, lithological units and vegetation. Mixture-tuned matched-filtering (MTMF was tested to discriminate the hydrothermal alteration areas of porphyry copper mineralization from surrounding environment using the shortwave infrared bands of ALI. Results indicate that the tested methods are able to yield spectral information for identifying vegetation, iron oxide/hydroxide and clay minerals, lithological units and the discrimination of hydrothermally altered rocks from unaltered rocks using ALI data.

  3. 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.

  4. Nuclear Fuels & Materials Spotlight Volume 4

    Energy Technology Data Exchange (ETDEWEB)

    I. J. van Rooyen,; T. M. Lillo; Y. Q. WU; P.A. Demkowicz; L. Scott; D.M. Scates; E. L. Reber; J. H. Jackson; J. A. Smith; D.L. Cottle; B.H. Rabin; M.R. Tonks; S.B. Biner; Y. Zhang; R.L. Williamson; S.R. Novascone; B.W. Spencer; J.D. Hales; D.R. Gaston; C.J. Permann; D. Anders; S.L. Hayes; P.C. Millett; D. Andersson; C. Stanek; R. Ali; S.L. Garrett; J.E. Daw; J.L. Rempe; J. Palmer; B. Tittmann; B. Reinhardt; G. Kohse; P. Ramuhali; H.T. Chien; T. Unruh; B.M. Chase; D.W. Nigg; G. Imel; J. T. Harris

    2014-04-01

    As the nation's nuclear energy laboratory, Idaho National Laboratory brings together talented people and specialized nuclear research capability to accomplish our mission. This edition of the Nuclear Fuels and Materials Division Spotlight provides an overview of some of our recent accomplishments in research and capability development. These accomplishments include: • The first identification of silver and palladium migrating through the SiC layer in TRISO fuel • A description of irradiation assisted stress corrosion testing capabilities that support commercial light water reactor life extension • Results of high-temperature safety testing on coated particle fuels irradiated in the ATR • New methods for testing the integrity of irradiated plate-type reactor fuel • Description of a 'Smart Fuel' concept that wirelessly provides real time information about changes in nuclear fuel properties and operating conditions • Development and testing of ultrasonic transducers and real-time flux sensors for use inside reactor cores, and • An example of a capsule irradiation test. Throughout Spotlight, you'll find examples of productive partnerships with academia, industry, and government agencies that deliver high-impact outcomes. The work conducted at Idaho National Laboratory helps to spur innovation in nuclear energy applications that drive economic growth and energy security. We appreciate your interest in our work here at INL, and hope that you find this issue informative.

  5. Experiment of Azimuth-invariant Bistatic UHF UWB SAR

    Science.gov (United States)

    Xie, Hongtu; Shi, Shaoying; Mao, Junfa; Li, Fuhai; An, Daoxiang; Zhou, Zhimin; Wang, Guoqian

    2018-01-01

    Bistatic ultrahigh frequency ultrawideband synthetic aperture radar (UHF UWB SAR) has the well ability of the penetrating the foliage, high-resolution imaging and providing the increased information. In the paper, an imaging experiment of the azimuth-invariant bistatic UHF UWB SAR is described and the result is proposed. In August 2015, an along-track bistatic UHF UWB SAR experiment was conducted in China, and the raw data was collected. In this bistatic SAR system, the transmitter and receiver are both carried by a vehicle and separated by an invariable distance. The aim was to investigate the imaging property of the bistatic UHF UWB SAR system. Bistatic image was obtained using the subaperture spectrum-equilibrium method integrated with the fast factorized back projection algorithm (FFBPA). Experiment results prove the validity of the bistatic UHF UWB SAR experiment.

  6. 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....

  7. A new detection method of oil rigs in SAR imagery

    Science.gov (United States)

    Chen, Peng; Yang, Jingsong; Ren, Lin

    2013-10-01

    It's difficult for simple space-borne SAR to identify oil rigs effectively in single pass SAR image. One method of oil rig detection is using multi-temporal SAR images. Some papers had do some research on it. In this paper, we use interferometry SAR image to detect the oil rigs. We get the correlation coefficient image from the In-SAR data, and using the histogram of correlation coefficient image, A Constant False Alarm Rate (CFAR) algorithm is imported to detect the oil rigs. The Probabilistic Neural Network (PNN) is used to get the threshold of detection. The test result shows that sea coherent target detection in the coherent coefficient image is efficacious.

  8. Spotlight on Psoriasis: Preventing Patches of Itchy, Sore Skin

    Science.gov (United States)

    ... Subscribe August 2016 Print this issue Spotlight on Psoriasis Preventing Patches of Itchy, Sore Skin En español ... Sun Damage Sun and Skin Wise Choices Avoid Psoriasis Triggers Factors that may trigger psoriasis or make ...

  9. Nuclear Fuels & Materials Spotlight Volume 5

    Energy Technology Data Exchange (ETDEWEB)

    Petti, David Andrew [Idaho National Lab. (INL), Idaho Falls, ID (United States)

    2016-10-01

    As the nation's nuclear energy laboratory, Idaho National Laboratory brings together talented people and specialized nuclear research capability to accomplish our mission. This edition of the Nuclear Fuels and Materials Division Spotlight provides an overview of some of our recent accomplishments in research and capability development. These accomplishments include: • Evaluation and modeling of light water reactor accident tolerant fuel concepts • Status and results of recent TRISO-coated particle fuel irradiations, post-irradiation examinations, high-temperature safety testing to demonstrate the accident performance of this fuel system, and advanced microscopy to improve the understanding of fission product transport in this fuel system. • Improvements in and applications of meso and engineering scale modeling of light water reactor fuel behavior under a range of operating conditions and postulated accidents (e.g., power ramping, loss of coolant accident, and reactivity initiated accidents) using the MARMOT and BISON codes. • Novel measurements of the properties of nuclear (actinide) materials under extreme conditions, (e.g. high pressure, low/high temperatures, high magnetic field) to improve the scientific understanding of these materials. • Modeling reactor pressure vessel behavior using the GRIZZLY code. • New methods using sound to sense temperature inside a reactor core. • Improved experimental capabilities to study the response of fusion reactor materials to a tritium plasma. Throughout Spotlight, you'll find examples of productive partnerships with academia, industry, and government agencies that deliver high-impact outcomes. The work conducted at Idaho National Laboratory helps spur innovation in nuclear energy applications that drive economic growth and energy security. We appreciate your interest in our work here at Idaho National Laboratory, and hope that you find this issue informative.

  10. 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.

    with radar imagery. 1. SAR Measurements Digital ERS-1 image mode SAR scenes off Goa, Paradeep and Visakhapatnam were acquired from the National Remote Sensing Agency (NRSA), Hyderabad, India, with the intention of studying the spatial evolution... density and wave direction separately as a function of frequency using the digital band, pass filtering method, the buoy observation at 1050 IST showed (Table 1) that there were two main spectral peaks, both due to "swell" ( waves generated by distant...

  11. Ship surveillance with Radarsat-2 ScanSAR

    Science.gov (United States)

    Wang, Ziwei; Zhang, Hong; Wang, Chao; Wu, Fan

    2014-10-01

    Ship detection is a significant application of maritime monitoring and security. To fully explore the potential of wide coverage of synthetic aperture radar (SAR) image, the ScanSAR Wide image for ship detection is investigated in this paper. The Radarsat-2 ScanSAR Wide mode image is used as the image source due to its huge coverage and constant false alarm rate (CFAR) with Gamma distribution is selected as the core detector. Two problems of ScanSAR ship detection, the unbalanced phenomenon and false alarms of islands, are investigated and solved by a compensation step and Hessian matrix respectively. For more aspects, the detector also concerns the polarization channel selection and distribution fitting. Finally, a whole flow chart of ScanSAR ship detection is presented. As test cases, the experimental image is used to show the efficiency of our method.

  12. 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.)

  13. Digital SAR Mosaic and Elevation Map of the Greenland Ice Sheet

    Data.gov (United States)

    National Aeronautics and Space Administration — The Digital SAR Mosaic and Elevation Map of the Greenland Ice Sheet CD-ROM combines the most detailed synthetic aperture radar (SAR) image mosaic available with the...

  14. Digital SAR Mosaic and Elevation Map of the Greenland Ice Sheet, Version 1

    Data.gov (United States)

    National Aeronautics and Space Administration — The Digital SAR Mosaic and Elevation Map of the Greenland Ice Sheet CD-ROM combines the most detailed synthetic aperture radar (SAR) image mosaic available with the...

  15. SAR Polarimetry

    Science.gov (United States)

    vanZyl, Jakob J.

    2012-01-01

    Radar Scattering includes: Surface Characteristics, Geometric Properties, Dielectric Properties, Rough Surface Scattering, Geometrical Optics and Small Perturbation Method Solutions, Integral Equation Method, Magellan Image of Pancake Domes on Venus, Dickinson Impact Crater on Venus (Magellan), Lakes on Titan (Cassini Radar, Longitudinal Dunes on Titan (Cassini Radar), Rough Surface Scattering: Effect of Dielectric Constant, Vegetation Scattering, Effect of Soil Moisture. Polarimetric Radar includes: Principles of Polarimetry: Field Descriptions, Wave Polarizations: Geometrical Representations, Definition of Ellipse Orientation Angles, Scatter as Polarization Transformer, Scattering Matrix, Coordinate Systems, Scattering Matrix, Covariance Matrix, Pauli Basis and Coherency Matrix, Polarization Synthesis, Polarimeter Implementation.

  16. 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.

  17. 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....... There is a good agreement between the SAR-estimated HE center location and the best track data from the National Hurricane Center. The wind speeds at 10 m above the ocean surface are also retrieved from the SAR data using the geophysical model function (GMF), CMOD5, and compared with in situ wind speed...... 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)....

  18. 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

  19. Near-source high-rate GPS, strong motion and InSAR observations to image the 2015 Lefkada (Greece) Earthquake rupture history.

    Science.gov (United States)

    Avallone, Antonio; Cirella, Antonella; Cheloni, Daniele; Tolomei, Cristiano; Theodoulidis, Nikos; Piatanesi, Alessio; Briole, Pierre; Ganas, Athanassios

    2017-09-04

    The 2015/11/17 Lefkada (Greece) earthquake ruptured a segment of the Cephalonia Transform Fault (CTF) where probably the penultimate major event was in 1948. Using near-source strong motion and high sampling rate GPS data and Sentinel-1A SAR images on two tracks, we performed the inversion for the geometry, slip distribution and rupture history of the causative fault with a three-step self-consistent procedure, in which every step provided input parameters for the next one. Our preferred model results in a ~70° ESE-dipping and ~13° N-striking fault plane, with a strike-slip mechanism (rake ~169°) in agreement with the CTF tectonic regime. This model shows a bilateral propagation spanning ~9 s with the activation of three main slip patches, characterized by rise time and peak slip velocity in the ranges 2.5-3.5 s and 1.4-2.4 m/s, respectively, corresponding to 1.2-1.8 m of slip which is mainly concentrated in the shallower ( 6) earthquakes to the northern and to the southern boundaries of the 2015 causative fault cannot be excluded.

  20. MULTI-TEMPORAL SAR CHANGE DETECTION AND MONITORING

    Directory of Open Access Journals (Sweden)

    S. Hachicha

    2012-08-01

    Full Text Available Multitemporal SAR images are a very useful source of information for a large amount of applications, especially for change detection and monitoring. In this paper, a new SAR change detection and monitoring approach is proposed through the analysis of a time series of SAR images covering the same region. The first step of the method is the SAR filtering preprocessing step using an extension of the spatial NL-means filter to the temporal domain. Then, the Rayleigh Kullback Leibler and the Rayleigh Distribution Ratio measures are combined to detect the changes between a reference image and each SAR image of the time series at both local and global scale. These measures are combined using the Dezert-Smarandache theory which takes into account conflicts between sources and thus enhances the dual change detection results. Finally, a pixel based temporal classification is applied starting from the obtained change maps in order to describe the temporal behaviour of the covered regions.

  1. Flood extent and water level estimation from SAR using data-model integration

    Science.gov (United States)

    Ajadi, O. A.; Meyer, F. J.

    2017-12-01

    Synthetic Aperture Radar (SAR) images have long been recognized as a valuable data source for flood mapping. Compared to other sources, SAR's weather and illumination independence and large area coverage at high spatial resolution supports reliable, frequent, and detailed observations of developing flood events. Accordingly, SAR has the potential to greatly aid in the near real-time monitoring of natural hazards, such as flood detection, if combined with automated image processing. This research works towards increasing the reliability and temporal sampling of SAR-derived flood hazard information by integrating information from multiple SAR sensors and SAR modalities (images and Interferometric SAR (InSAR) coherence) and by combining SAR-derived change detection information with hydrologic and hydraulic flood forecast models. First, the combination of multi-temporal SAR intensity images and coherence information for generating flood extent maps is introduced. The application of least-squares estimation integrates flood information from multiple SAR sensors, thus increasing the temporal sampling. SAR-based flood extent information will be combined with a Digital Elevation Model (DEM) to reduce false alarms and to estimate water depth and flood volume. The SAR-based flood extent map is assimilated into the Hydrologic Engineering Center River Analysis System (Hec-RAS) model to aid in hydraulic model calibration. The developed technology is improving the accuracy of flood information by exploiting information from data and models. It also provides enhanced flood information to decision-makers supporting the response to flood extent and improving emergency relief efforts.

  2. Building Detection in SAR Imagery

    Energy Technology Data Exchange (ETDEWEB)

    Steinbach, Ryan Matthew [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Koch, Mark William [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Moya, Mary M [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Goold, Jeremy [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States)

    2014-08-01

    Current techniques for building detection in Synthetic Aperture Radar (SAR) imagery can be computationally expensive and/or enforce stringent requirements for data acquisition. The desire is to present a technique that is effective and efficient at determining an approximate building location. This approximate location can be used to extract a portion of the SAR image to then perform a more robust detection. The proposed technique assumes that for the desired image, bright lines and shadows, SAR artifact effects, are approximately labeled. These labels are enhanced and utilized to locate buildings, only if the related bright lines and shadows can be grouped. In order to find which of the bright lines and shadows are related, all of the bright lines are connected to all of the shadows. This allows the problem to be solved from a connected graph viewpoint. Where the nodes are the bright lines and shadows and the arcs are the connections between bright lines and shadows. Constraints based on angle of depression and the relationship between connected bright lines and shadows are applied to remove unrelated arcs. Once the related bright lines and shadows are grouped, their locations are combined to provide an approximate building location. Experimental results are provided showing the outcome of the technique.

  3. 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.

  4. Mapping of oil spill environmental sensitivity index (ESI) in western Amazonia, Brazil, using USTC classification of dual season GRFM SAR image mosaics

    Energy Technology Data Exchange (ETDEWEB)

    Miranda, Fernando P. de [PETROBRAS S.A., Rio de Janeiro, RJ (Brazil). Centro de Pesquisas; Beisl, Carlos H.; Pedroso, Enrico C. [Universidade Federal, Rio de Janeiro, RJ (Brazil). Coordenacao dos Programas de Pos-graduacao de Engenharia. Centro Brasileiro de Recursos - RADARSAT

    2003-07-01

    This study focuses on improving information about oil spill environmental sensitivity in Western Amazonia, Brazil, using a pair of multi seasonal (1995 - low flood to 1996 - high flood) GRFM JERS-1 SAR mosaics. Fuzzy analysis is carried out to extract information about landscape modifications within half hydrological cycle. The oil spill hazard information derived from JERS-1 SAR data is straightforward to interpret and constitutes a representation of the original Environmental Sensitivity Index (ESI) product conceived by PETROBRAS. (author)

  5. 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.

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

    Science.gov (United States)

    Krieger, Gerhard; Papathanassiou, Konstantinos Panagiotis; Cloude, Shane R.

    2005-12-01

    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.

  7. Bistatic SAR: State of the Art and Development Trend

    Directory of Open Access Journals (Sweden)

    Zeng Tao

    2012-12-01

    Full Text Available Bistatic SAR (BiSAR systems have attracted the interests from global researchers and become a hotspot in the international radar community due to the progress of radar technology and rapidly increased applications nowadays. Based on the BiSAR experiments and breakthrough of the key technology, the paper summarized the general progresses of BiSAR systems, especially in European radar community, from different aspects such as system design, processing idea and topology etc. Different bistatic image formation algorithms have been analyzed and reviewed. Finally, the development trend is discussed in the paper.

  8. Ocean Surface Wind Speed of Hurricane Helene Observed by SAR

    DEFF Research Database (Denmark)

    Xu, Qing; Cheng, Yongcun; Li, Xiaofeng

    2011-01-01

    The hurricanes can be detected by many remote sensors, but synthetic aperture radar (SAR) can yield high-resolution (sub-kilometer) and low-level wind information that cannot be seen below the cloud by other sensors. In this paper, an assessment of SAR capability of monitoring high......-resolution hurricane was conducted. A case study was carried out to retrieve ocean surface wind field from C-band RADARSAT-1 SAR image which captured the structure of hurricane Helene over the Atlantic Ocean on 20 September, 2006. With wind direction from the outputs of U.S. Navy Operational Global Atmospheric...... CIWRAP models have been tested to extract wind speed from SAR data. The SAR retrieved ocean surface winds were compared to the aircraft wind speed observations from stepped frequency microwave radiometer (SFMR). The results show the capability of hurricane wind monitoring by SAR....

  9. Investigation of Polarimetric SAR Data Acquired at Multiple Incidence Angles

    DEFF Research Database (Denmark)

    Svendsen, Morten Thougaard; Skriver, Henning; Thomsen, A.

    1998-01-01

    The dependence of different polarimetric parameters on the incidence angles in the range of 30° to 60° is investigated for a number of different crops using airborne SAR data. The purpose of the investigation is to determine the effect of the variation of incidence angle within a SAR image when...

  10. 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.

  11. 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.

  12. Integrating interferometric SAR data with levelling measurements of land subsidence using geostatistics

    NARCIS (Netherlands)

    Zhou, Y.; Stein, A.; Molenaar, M.

    2003-01-01

    Differential Synthetic Aperture Radar (SAR) interferometric (D-InSAR) data of ground surface deformation are affected by several error sources associated with image acquisitions and data processing. In this paper, we study the use of D-InSAR for quantifying land subsidence due to groundwater

  13. Feature learning and change feature classification based on deep learning for ternary change detection in SAR images

    Science.gov (United States)

    Gong, Maoguo; Yang, Hailun; Zhang, Puzhao

    2017-07-01

    Ternary change detection aims to detect changes and group the changes into positive change and negative change. It is of great significance in the joint interpretation of spatial-temporal synthetic aperture radar images. In this study, sparse autoencoder, convolutional neural networks (CNN) and unsupervised clustering are combined to solve ternary change detection problem without any supervison. Firstly, sparse autoencoder is used to transform log-ratio difference image into a suitable feature space for extracting key changes and suppressing outliers and noise. And then the learned features are clustered into three classes, which are taken as the pseudo labels for training a CNN model as change feature classifier. The reliable training samples for CNN are selected from the feature maps learned by sparse autoencoder with certain selection rules. Having training samples and the corresponding pseudo labels, the CNN model can be trained by using back propagation with stochastic gradient descent. During its training procedure, CNN is driven to learn the concept of change, and more powerful model is established to distinguish different types of changes. Unlike the traditional methods, the proposed framework integrates the merits of sparse autoencoder and CNN to learn more robust difference representations and the concept of change for ternary change detection. Experimental results on real datasets validate the effectiveness and superiority of the proposed framework.

  14. Knowledge-aided Two-dimensional Autofocus for Spotlight SAR Polar Format Imagery

    OpenAIRE

    Mao, Xinhua

    2015-01-01

    Conventional two-dimensional (2-D) autofocus algorithms blindly estimate the phase error in the sense that they do not exploit any a priori information on the structure of the 2-D phase error. As such, they often suffer from low computational efficiency and lack of data redundancy to accurately estimate the 2-D phase error. In this paper, a knowledge-aided (KA) 2-D autofocus algorithm which is based on exploiting a priori knowledge about the 2-D phase error structure, is presented. First, as ...

  15. Use of time series of optical and SAR images in the estimation of snow cover for the optimization of water use in the Andes of Argentina and Chile

    Science.gov (United States)

    Salinas de Salmuni, Graciela; Cabezas Cartes, Ricardo; Menicocci, Felix

    2014-05-01

    operational application because it is simple and easy to implement. From the analysis of multitemporal study in the region using COSMO SkyMed images, it is observed that the values of wet snow coverage, obtained along the 2012 hydrological cycle, are consistent with the dynamics of the same: The study area has a high rise and steep relief (up to 6400m), therefore the shadows loom large, processing optical and SAR images improve the results. The behavior of the accumulation process (winter) and snowmelt (summer), is influenced by the elevation of the different study areas. A high percentage (49%) of surface snow at higher elevations to 3000 m. This is due to the accumulation of snow increases with elevation, by the combined effect of low temperatures and increased precipitation snowy orographic effect. In studies of wet meadows with optical images, a high correspondence between the spectral classes and vigor of vegetation and soil moisture (seen in the field) so are considered as indicators of degradation of these ecosystems was observed

  16. Derivation of soil moisture and snow wetness from satellite SAR images over a permafrost region in interior Alaska

    Science.gov (United States)

    Adewuyi, Adeniyi Abiodun

    The empirically adopted integral equation model (EA-IEM) was implemented for soil moisture and snow wetness derivations from active microwave data under bare soil or pure snow cover and sparsely vegetated conditions in the permafrost region. Since the permafrost region consists of land mixed with snow cover, MODIS image was used as a reference to separate the original backscattering coefficient radar image into soil and snow backscattering coefficient subimages. The EA-IEM provides simplified mathematical expressions to calculate the soil and snow dielectric constants. A sensitivity analysis was performed and then the range of model parameters for snow wetness retrieval was determined. The Newton-Rhapson iteration was used to generate the calibrated surface root-mean-square (rms) height and calibrated correlation length by using the absolute difference between the retrieved volumetric soil moisture from the backscattering coefficient of RADARSAT-1 (a Canadian satellite radar sensor) and the measured volumetric soil moisture. The absolute difference is less than the threshold value set to be 106. In this study, two empirical roughness models were developed that allow for the parameterization of the soil surface roughness. The first empirical roughness model was established between the calibrated correlation length values and the backscattering coefficient observations, while the second model was implemented between the calibrated surface RMS height values and the backscattering coefficient values. Further incorporating these two empirical roughness models into the EA-IEM provides a robust way of retrieving volumetric liquid water content (LWC) over a large area. Liquid water content is then calculated from the radar backscattering coefficient without iteration. Four strategies were adopted to calibrate and validate the derived volumetric liquid water content data at two NCRS-SCAN sites: Nenana and Ward Farm in Alaska, USA. The first strategy combined the two data

  17. NOAA high resolution sea surface winds data from Synthetic Aperture Radar (SAR) on the RADARSAT-2 satellite

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — Synthetic Aperture Radar (SAR)-derived high resolution wind products are calculated from high resolution SAR images of normalized radar cross section (NRCS) of the...

  18. SARS – clinical features

    Indian Academy of Sciences (India)

    SARS – clinical features. Fever - > 38C; Respiratory symptoms, eg cough, difficulty in breathing; OR; Unexplained respiratory distress leading to death; AND; Close contact or travel to Asia within 10 days of onset of illness.

  19. 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...

  20. 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)....

  1. 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.)

  2. Stop outbreak of SARS with infrared cameras

    Science.gov (United States)

    Wu, Yigang M.

    2004-04-01

    SARS (Severe Acute Respiratory Syndrome, commonly known as Atypical Pneumonia in mainland China) caused 8422 people affected and resulting in 918 deaths worldwide in half year. This disease can be transmitted by respiratory droplets or by contact with a patient's respiratory secretions. This means it can be spread out very rapidly through the public transportations by the travelers with the syndrome. The challenge was to stop the SARS carriers traveling around by trains, airplanes, coaches and etc. It is impractical with traditional oral thermometers or spot infrared thermometers to screen the tens of travelers with elevated body temperature from thousands of normal travelers in hours. The thermal imager with temperature measurement function is a logical choice for this special application although there are some limitations and drawbacks. This paper discusses the real SARS applications of industrial infrared cameras in China from April to July 2003.

  3. 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

  4. Monitoring of Oil Exploitation Infrastructure by Combining Unsupervised Pixel-Based Classification of Polarimetric SAR and Object-Based Image Analysis

    Directory of Open Access Journals (Sweden)

    Simon Plank

    2014-12-01

    Full Text Available In developing countries, there is a high correlation between the dependence of oil exports and violent conflicts. Furthermore, even in countries which experienced a peaceful development of their oil industry, land use and environmental issues occur. Therefore, independent monitoring of oil field infrastructure may support problem solving. Earth observation data enables fast monitoring of large areas which allows comparing the real amount of land used by the oil exploitation and the companies’ contractual obligations. The target feature of this monitoring is the infrastructure of the oil exploitation, oil well pads—rectangular features of bare land covering an area of approximately 50–60 m × 100 m. This article presents an automated feature extraction procedure based on the combination of a pixel-based unsupervised classification of polarimetric synthetic aperture radar data (PolSAR and an object-based post-classification. The method is developed and tested using dual-polarimetric TerraSAR-X imagery acquired over the Doba basin in south Chad. The advantages of PolSAR are independence of the cloud coverage (vs. optical imagery and the possibility of detailed land use classification (vs. single-pol SAR. The PolSAR classification uses the polarimetric Wishart probability density function based on the anisotropy/entropy/alpha decomposition. The object-based post-classification refinement, based on properties of the feature targets such as shape and area, increases the user’s accuracy of the methodology by an order of a magnitude. The final achieved user’s and producer’s accuracy is 59%–71% in each case (area based accuracy assessment. Considering only the numbers of correctly/falsely detected oil well pads, the user’s and producer’s accuracies increase to even 74%–89%. In an iterative training procedure the best suited polarimetric speckle filter and processing parameters of the developed feature extraction procedure are

  5. Reconstruction of interrupted SAR imagery for persistent surveillance change detection

    Science.gov (United States)

    Stojanovic, Ivana; Karl, W. C.; Novak, Les

    2012-05-01

    In this paper we apply a sparse signal recovery technique for synthetic aperture radar (SAR) image formation from interrupted phase history data. Timeline constraints imposed on multi-function modern radars result in interrupted SAR data collection, which in turn leads to corrupted imagery that degrades reliable change detection. In this paper we extrapolate the missing data by applying the basis pursuit denoising algorithm (BPDN) in the image formation step, effectively, modeling the SAR scene as sparse. We investigate the effects of regular and random interruptions on the SAR point spread function (PSF), as well as on the quality of both coherent (CCD) and non-coherent (NCCD) change detection. We contrast the sparse reconstruction to the matched filter (MF) method, implemented via Fourier processing with missing data set to zero. To illustrate the capabilities of the gap-filling sparse reconstruction algorithm, we evaluate change detection performance using a pair of images from the GOTCHA data set.

  6. 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.

  7. Severe acute respiratory syndrome (SARS)

    Science.gov (United States)

    ... their fever and other symptoms are gone. Hand hygiene is the most important part of SARS prevention. ... Coronaviruses, including severe acute respiratory syndrome (SARS) and Middle East respiratory syndrome (MERS). In: Bennett JE, Dolin ...

  8. Sentinel-3 SAR Altimetry Toolbox

    Science.gov (United States)

    Benveniste, Jerome; Lucas, Bruno; DInardo, Salvatore

    2015-04-01

    ) and raster images (JPEG, PNG, etc.). Several kinds of computations can be done within BRAT involving combinations of data fields that the user can save for posterior reuse or using the already embedded formulas that include the standard oceanographic altimetry formulas. The Radar Altimeter Tutorial, that contains a strong introduction to altimetry, showing its applications in different fields such as Oceanography, Cryosphere, Geodesy, Hydrology among others. Included are also "use cases", with step-by-step examples, on how to use the toolbox in the different contexts. The Sentinel-3 SAR Altimetry Toolbox shall benefit from the current BRAT version. While developing the Sentinel-3 SAR Altimetry Toolbox we will revamp of the Graphical User Interface and provide, among other enhancements, support for reading the upcoming S3 datasets and specific "use-cases" for SAR altimetry in order to train the users and make them aware of the great potential of SAR altimetry for coastal and inland applications. As for any open source framework, contributions from users having developed their own functions are welcome. The Kick Off is expected to be happen in Q1 2015 and have the 1st version available before the launch of Sentinel-3.

  9. 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.

  10. 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.

  11. DInSAR/PSInSAR Observations of Kirishima, Shinmoe-dake Volcano, Japan

    Science.gov (United States)

    Miyagi, Yousuke; Ozawa, Taku; Kozono, Tomofumi; Shimada, Masanobu

    2013-04-01

    Shinmoe-dake in the Kirishima volcano group is located in southwestern part of Japan. In January 2011, eruptive activities started from the Shinmoe-dake crater and resulted in sub-Plinian and Vulcanian eruptions and a rapid accumulation of lava within the crater. GPS and DInSAR data acquired before and after the eruption revealed pre-eruptive inflation, co-eruptive deflation, and post-eruptive inflation centered on 5km west of the crater. The eruption phase ceased by the beginning of September, and the post-eruptive inflation also ceased by November 2011. After the 2011 eruption, monitoring by TerraSAR-X have continued. Surface change and surface deformation on the lava within the crater were detected by high-resolution amplitude images and DInSAR data. Especially, the surface deformation after September 2011 revealed a continual shortening of satellite-ground distance even after the end of the main activity. This LOS shortening means uplifts of the lava surface. We estimated the volume increase of the lava after November 2011, using DInSAR processing of TerraSAR-X data, and concluded that the volume increase still continued in December 2012. The volume change rate has decreased with a small fluctuation as an overall trend. PSInSAR and long-term DInSAR results helped us to know deformation around the crater. They show LOS elongation including a subsidence in the northeast flank of the crater. It is interpreted that the subsidence is caused by a deflation of shallow deformation source located just beneath the crater.

  12. 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.

  13. Multichannel FMCW SAR

    NARCIS (Netherlands)

    Rossum, W.L. van; Otten, M.P.G.; Dorp, Ph. van

    2012-01-01

    A light weight SAR, suitable for use on short range tactical UAV, has been designed and built. The system consists of a fully digital receive array, and a very compact active transmit antenna. The approximate weight of the complete system is 6 kg, with power consumption below 75 W, depending on the

  14. 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.

  15. 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.

  16. Statistical SAR studies of windfields near Unimak Island

    Energy Technology Data Exchange (ETDEWEB)

    Smith, R.B.; Pan, F. [Yale Univ., New Haven, CT (United States)

    1997-06-01

    The modification of wind patterns by coastlines and islands is outlined. The paper focuses on methods for observing the sheltering effect, in which windspeed downwind of high terrain is reduced. Three observational methods are described: in situ observation, sunglint imagery using specular reflection, and synthetic-aperture radar (SAR). A data archive of SAR images of Unimak Island in the Aleutian Islands chain which was analyzed for sheltering effects is described.

  17. Sustainable prevention of obesity through integrated strategies: The SPOTLIGHT project’s conceptual framework and design

    Directory of Open Access Journals (Sweden)

    Lakerveld Jeroen

    2012-09-01

    Full Text Available Abstract Background The prevalence of overweight and obesity in Europe is high. It is a major cause of the overall rates of many of the main chronic (or non communicable diseases in this region and is characterized by an unequal socio-economic distribution within the population. Obesity is largely determined by modifiable lifestyle behaviours such as low physical activity levels, sedentary behaviour and consumption of energy dense diets. It is increasingly being recognised that effective responses must go beyond interventions that only focus on a specific individual, social or environmental level and instead embrace system-based multi-level intervention approaches that address both the individual and environment. The EU-funded project “sustainable prevention of obesity through integrated strategies” (SPOTLIGHT aims to increase and combine knowledge on the wide range of determinants of obesity in a systematic way, and to identify multi-level intervention approaches that are strong in terms of Reach, Efficacy, Adoption, Implementation and Maintenance (RE-AIM. Methods/Design SPOTLIGHT comprises a series of systematic reviews on: individual-level predictors of success in behaviour change obesity interventions; social and physical environmental determinants of obesity; and on the RE-AIM of multi-level interventions. An interactive web-atlas of currently running multi-level interventions will be developed, and enhancing and impeding factors for implementation will be described. At the neighbourhood level, these elements will inform the development of methods to assess obesogenicity of diverse environments, using remote imaging techniques linked to geographic information systems. The validity of these methods will be evaluated using data from surveys of health and lifestyles of adults residing in the neighbourhoods surveyed. At both the micro- and macro-levels (national and international the different physical, economical, political and socio

  18. 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.

  19. Using SAR satellite data time series for regional glacier mapping

    Directory of Open Access Journals (Sweden)

    S. H. Winsvold

    2018-03-01

    Full Text Available With dense SAR satellite data time series it is possible to map surface and subsurface glacier properties that vary in time. On Sentinel-1A and RADARSAT-2 backscatter time series images over mainland Norway and Svalbard, we outline how to map glaciers using descriptive methods. We present five application scenarios. The first shows potential for tracking transient snow lines with SAR backscatter time series and correlates with both optical satellite images (Sentinel-2A and Landsat 8 and equilibrium line altitudes derived from in situ surface mass balance data. In the second application scenario, time series representation of glacier facies corresponding to SAR glacier zones shows potential for a more accurate delineation of the zones and how they change in time. The third application scenario investigates the firn evolution using dense SAR backscatter time series together with a coupled energy balance and multilayer firn model. We find strong correlation between backscatter signals with both the modeled firn air content and modeled wetness in the firn. In the fourth application scenario, we highlight how winter rain events can be detected in SAR time series, revealing important information about the area extent of internal accumulation. In the last application scenario, averaged summer SAR images were found to have potential in assisting the process of mapping glaciers outlines, especially in the presence of seasonal snow. Altogether we present examples of how to map glaciers and to further understand glaciological processes using the existing and future massive amount of multi-sensor time series data.

  20. Using SAR satellite data time series for regional glacier mapping

    Science.gov (United States)

    Winsvold, Solveig H.; Kääb, Andreas; Nuth, Christopher; Andreassen, Liss M.; van Pelt, Ward J. J.; Schellenberger, Thomas

    2018-03-01

    With dense SAR satellite data time series it is possible to map surface and subsurface glacier properties that vary in time. On Sentinel-1A and RADARSAT-2 backscatter time series images over mainland Norway and Svalbard, we outline how to map glaciers using descriptive methods. We present five application scenarios. The first shows potential for tracking transient snow lines with SAR backscatter time series and correlates with both optical satellite images (Sentinel-2A and Landsat 8) and equilibrium line altitudes derived from in situ surface mass balance data. In the second application scenario, time series representation of glacier facies corresponding to SAR glacier zones shows potential for a more accurate delineation of the zones and how they change in time. The third application scenario investigates the firn evolution using dense SAR backscatter time series together with a coupled energy balance and multilayer firn model. We find strong correlation between backscatter signals with both the modeled firn air content and modeled wetness in the firn. In the fourth application scenario, we highlight how winter rain events can be detected in SAR time series, revealing important information about the area extent of internal accumulation. In the last application scenario, averaged summer SAR images were found to have potential in assisting the process of mapping glaciers outlines, especially in the presence of seasonal snow. Altogether we present examples of how to map glaciers and to further understand glaciological processes using the existing and future massive amount of multi-sensor time series data.

  1. The Financial Management System: A Pivotal Tool for Fiscal Viability. CDS Spotlight. ECAR Research Bulletin

    Science.gov (United States)

    Lang, Leah; Pirani, Judith A.

    2014-01-01

    This spotlight focuses on data from the 2013 CDS to better understand how higher education institutions approach financial management systems. Information provided for this spotlight was derived from Module 8 of Core Data Service (CDS), which asked several questions regarding information systems and applications. Responses from 525 institutions…

  2. BI Reporting, Data Warehouse Systems, and Beyond. CDS Spotlight Report. Research Bulletin

    Science.gov (United States)

    Lang, Leah; Pirani, Judith A.

    2014-01-01

    This Spotlight focuses on data from the 2013 Core Data Service [CDS] to better understand how higher education institutions approach business intelligence (BI) reporting and data warehouse systems (see the Sidebar for definitions). Information provided for this Spotlight was derived from Module 8 of CDS, which contains several questions regarding…

  3. Maximize Institutional Relationships with CRMs. CDS Spotlight Report. ECAR Research Bulletin

    Science.gov (United States)

    Lang, Leah; Pirani, Judith A.

    2014-01-01

    This Spotlight focuses on data from the 2013 Core Data Service (CDS) to better understand how higher education institutions approach customer relationship management (CRM) systems. Information provided for this Spotlight was derived from Module 8 of the Core Data survey, which asked several questions regarding information systems and applications.…

  4. Polarimetric and Interferometric Synthetic Aperture Radar (Pol-InSAR); a new way to quantify three-dimensional structure of Earth and planetary surfaces Project

    Data.gov (United States)

    National Aeronautics and Space Administration — This study will employ a three phased approach: SAR image formation and calibration. DBSAR polarimetric and interferometric data analysis. PolInSAR algorithm...

  5. Signal subspace change detection in averaged multi-look SAR imagery

    Science.gov (United States)

    Ranney, Kenneth; Soumekh, Mehrdad

    2005-05-01

    Modern Synthetic Aperture Radar (SAR) signal processing algorithms could retrieve accurate and subtle information regarding a scene that is being interrogated by an airborne radar system. An important reconnaissance problem that is being studied via the use of SAR systems and their sophisticated signal processing methods involves detecting changes in an imaged scene. In these problems, the user interrogates a scene with a SAR system at two different time points (e.g. different days); the resultant two SAR databases that we refer to as reference and test data, are used to determine where targets have entered or left the imaged scene between the two data acquisitions. For instance, X band SAR systems have the potential to become a potent tool to determine whether mines have been recently placed in an area. This paper describes an algorithm for detecting changes in averaged multi-look SAR imagery. Averaged multi-look SAR images are preferable to full aperture SAR reconstructions when the imaging algorithm is approximation based (e.g. polar format processing), or motion data are not accurate over a long full aperture. We study the application of a SAR detection method, known as Signal Subspace Processing, that is based on the principles of 2D adaptive filtering. We identify the change detection problem as a binary hypothesis-testing problem, and identify an error signal and its normalized version to determine whether i) there is no change in the imaged scene; or ii) a target has been added to the imaged scene. A statistical analysis of the error signal is provided to show its properties and merits. Results are provided for data collected by an X band SAR platform and processed to form non-coherently look-averaged SAR images.

  6. SAR++: A Multi-Channel Scalable and Reconfigurable SAR System

    DEFF Research Database (Denmark)

    Høeg, Flemming; Christensen, Erik Lintz

    2002-01-01

    SAR++ is a technology program aiming at developing know-how and technology needed to design the next generation civilian SAR systems. Technology has reached a state, which allows major parts of the digital subsystem to be built using custom-off-the-shelf (COTS) components. A design goal is to des......SAR++ is a technology program aiming at developing know-how and technology needed to design the next generation civilian SAR systems. Technology has reached a state, which allows major parts of the digital subsystem to be built using custom-off-the-shelf (COTS) components. A design goal...... is to design a modular, scalable and reconfigurable SAR system using such components, in order to ensure maximum flexibility for the users of the actual system and for future system updates. Having these aspects in mind the SAR++ system is presented with focus on the digital subsystem architecture...... and the analog to digital interface....

  7. 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.

  8. Segment-based change detection for polarimetric SAR data

    DEFF Research Database (Denmark)

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

    2006-01-01

    single-channel SAR images but multi-channel algorithms have also been described. Different approaches have been used for image segmentation. Edge detection combined with region growing is one approach, where segments are created by growing regions from a previously edge detected and edge thinned image....... This method relies primarily on a robust edge detector, which preferably provides a constant false alarm rate. For single-channel SAR images this is fulfilled by the ratio edge detector, and for polarimetric SAR data, an edge detector based on the above mentioned test statistic fulfils this. Another approach......, wetlands, lakes, and urban areas. Also, other test sites over for instance urban areas have been used to assess the improvement by the segment-based change detection method. In the paper, results from pixel-based change detection, i.e. without segmentation, and from segment-based change detection, where...

  9. Airborne Downward Looking Sparse Linear Array 3-D SAR Heterogeneous Parallel Simulation

    OpenAIRE

    Yirong Wu; Weixian Tan; Xueming Peng; Wen Hong; Yanping Wang

    2013-01-01

    The airborne downward looking sparse linear array three dimensional synthetic aperture radar (DLSLA 3-D SAR) operates nadir observation with the along-track synthetic aperture formulated by platform movement and the cross-track synthetic aperture formulated by physical sparse linear array. Considering the lack of DLSLA 3-D SAR data in the current preliminary study stage, it is very important and essential to develop DLSLA 3-D SAR simulation (echo generation simulation and image reconstruction...

  10. Research Skills for the Future: Research Workforce Under the Spotlight

    Directory of Open Access Journals (Sweden)

    Eva Dobozy

    2013-01-01

    Full Text Available The value and training needs of the future research workforce is under the spotlight. In this article, I take up Ulrich and Dash's (2013 somewhat provocative invitation to engage in discussion and debate about current and future research. In my three-tiered response, I first discuss Ulrich and Dash's article, followed by my own observations about the APEC/Deloitte (2010 research report: "Skills and Competencies Needed in the Research Field: Objectives 2020," and finally, I explore, in some detail, challenges of building a twentyfirst-century research workforce.

  11. New military uses for synthetic aperture radar (SAR)

    Science.gov (United States)

    Reamer, Richard E.; Stockton, Wayne; Stromfors, Richard D.

    1993-02-01

    Loral Defense Systems-Arizona, holder of the original patent for the invention of Synthetic Aperture Radar (SAR), developed SAR to meet the military's need for an all-weather, day/night sensor that could produce high quality reconnaissance imagery in adverse weather and restricted visibility conditions. These features, and the ability to image large areas with fine resolution in a relatively short period of time make this sensor useful for many military applications. To date, however, SARs for military use have been hampered by the fact that they've been large, complex, and expensive. Additionally, they have been mounted on special purpose, single mission aircraft which are costly to operate. That situation has changed. A small, modular SAR, called Miniature Synthetic Aperture Radar (MSAR) developed by Loral can be mounted with relative ease on Unmanned Aerial Vehicles (UAV) or on multi-mission aircraft such as the F-16, F/A-18, or on the F-14.

  12. Mining Land Subsidence Monitoring Using SENTINEL-1 SAR Data

    Science.gov (United States)

    Yuan, W.; Wang, Q.; Fan, J.; Li, H.

    2017-09-01

    In this paper, DInSAR technique was used to monitor land subsidence in mining area. The study area was selected in the coal mine area located in Yuanbaoshan District, Chifeng City, and Sentinel-1 data were used to carry out DInSAR techniqu. We analyzed the interferometric results by Sentinel-1 data from December 2015 to May 2016. Through the comparison of the results of DInSAR technique and the location of the mine on the optical images, it is shown that DInSAR technique can be used to effectively monitor the land subsidence caused by underground mining, and it is an effective tool for law enforcement of over-mining.

  13. Wetland InSAR

    Science.gov (United States)

    Wdowinski, S.; Kim, S.; Amelung, F.; Dixon, T.

    2006-12-01

    Wetlands are transition zones where the flow of water, the nutrient cycling, and the sun energy meet to produce a unique and very productive ecosystem. They provide critical habitat for a wide variety of plant and animal species, including the larval stages of many ocean fish. Wetlands also have a valuable economical importance, as they filter nutrients and pollutants from fresh water used by human and provide aquatic habitats for outdoor recreation, tourism, and fishing. Globally, many such regions are under severe environmental stress, mainly from urban development, pollution, and rising sea level. However, there is increasing recognition of the importance of these habitats, and mitigation and restoration activities have begun in a few regions. A key element in wetlands conservation, management, and restoration involves monitoring its hydrologic system, as the entire ecosystem depends on its water supply. Heretofore, hydrologic monitoring of wetlands are conducted by stage (water level) stations, which provide good temporal resolution, but suffer from poor spatial resolution, as stage station are typically distributed several, or even tens of kilometers, from one another. Wetland application of InSAR provides the needed high spatial resolution hydrological observations, complementing the high temporal resolution terrestrial observations. Although conventional wisdom suggests that interferometry does not work in vegetated areas, several studies have shown that both L- and C-band interferograms with short acquisition intervals (1-105 days) can maintain excellent coherence over wetlands. In this study we explore the usage of InSAR for detecting water level changes in various wetland environments around the world, including the Everglades (south Florida), Louisiana Coast (southern US), Chesapeake Bay (eastern US), Pantanal (Brazil), Okavango Delta (Botswana), and Lena Delta (Siberia). Our main study area is the Everglades wetland (south Florida), which is covered by

  14. Detecting and monitoring UCG subsidence with InSAR

    Energy Technology Data Exchange (ETDEWEB)

    Mellors, R J; Foxall, W; Yang, X

    2012-03-23

    The use of interferometric synthetic aperture radar (InSAR) to measure surface subsidence caused by Underground Coal Gasification (UCG) is tested. InSAR is a remote sensing technique that uses Synthetic Aperture Radar images to make spatial images of surface deformation and may be deployed from satellite or an airplane. With current commercial satellite data, the technique works best in areas with little vegetation or farming activity. UCG subsidence is generally caused by roof collapse, which adversely affects UCG operations due to gas loss and is therefore important to monitor. Previous studies have demonstrated the usefulness of InSAR in measuring surface subsidence related to coal mining and surface deformation caused by a coal mining roof collapse in Crandall Canyon, Utah is imaged as a proof-of-concept. InSAR data is collected and processed over three known UCG operations including two pilot plants (Majuba, South Africa and Wulanchabu, China) and an operational plant (Angren, Uzbekistan). A clear f eature showing approximately 7 cm of subsidence is observed in the UCG field in Angren. Subsidence is not observed in the other two areas, which produce from deeper coal seams and processed a smaller volume. The results show that in some cases, InSAR is a useful tool to image UCG related subsidence. Data from newer satellites and improved algorithms will improve effectiveness.

  15. SAR polar format implementation with MATLAB.

    Energy Technology Data Exchange (ETDEWEB)

    Martin, Grant D.; Doerry, Armin Walter

    2005-11-01

    Traditional polar format image formation for Synthetic Aperture Radar (SAR) requires a large amount of processing power and memory in order to accomplish in real-time. These requirements can thus eliminate the possible usage of interpreted language environments such as MATLAB. However, with trapezoidal aperture phase history collection and changes to the traditional polar format algorithm, certain optimizations make MATLAB a possible tool for image formation. Thus, this document's purpose is two-fold. The first outlines a change to the existing Polar Format MATLAB implementation utilizing the Chirp Z-Transform that improves performance and memory usage achieving near realtime results for smaller apertures. The second is the addition of two new possible image formation options that perform a more traditional interpolation style image formation. These options allow the continued exploration of possible interpolation methods for image formation and some preliminary results comparing image quality are given.

  16. Voicing Others’ Voices: Spotlighting the Researcher as Narrator

    Directory of Open Access Journals (Sweden)

    Dan O’SULLIVAN

    2015-12-01

    Full Text Available As qualitative research undertakings are not independent of the researcher, the “indissoluble interrelationship between interpreter and interpretation” (Thomas & James, 2006, p. 782 renders it necessary for researchers to understand that their text is a representation, a version of the truth that is the product of writerly choices, and that it is discursive. Endlessly creative, artistic and political, as there is no single interpretative truth, the interpretative process facilitates the refashioning of representations, the remaking of choices and the probing of discourses. As a consequence of the particularity of any researcher’s account, issues pertaining to researcher identity and authorial stance always remain central to research endeavours (Kamler & Thomson, 2006, p. 68; Denzin & Lincoln 2011, pp. 14-15. Therefore, researchers are encouraged to be reflexive about their analyses and research accounts (Elliott, 2005, p. 152, as reflexivity helps spotlight the role of the researcher as narrator. In turn, spotlighting the researcher as narrator foregrounds a range of complex issues about voice, representation and interpretive authority (Chase, 2005, p. 657; Genishi & Glupczynski, 2006, p. 671; Eisenhart, 2006. In essence, therefore, this paper is reflective of the challenges of “doing” qualitative research in educational settings. Its particular focus-the shaping of beginning primary teachers’ identities, in Ireland, throughout the course of their initial year of occupational experience, post-graduation- endeavours to highlight issues pertaining to the researcher as narrator (O’Sullivan, 2014.

  17. Spotlighting quantum critical points via quantum correlations at finite temperatures

    International Nuclear Information System (INIS)

    Werlang, T.; Ribeiro, G. A. P.; Rigolin, Gustavo

    2011-01-01

    We extend the program initiated by T. Werlang et al. [Phys. Rev. Lett. 105, 095702 (2010)] in several directions. Firstly, we investigate how useful quantum correlations, such as entanglement and quantum discord, are in the detection of critical points of quantum phase transitions when the system is at finite temperatures. For that purpose we study several thermalized spin models in the thermodynamic limit, namely, the XXZ model, the XY model, and the Ising model, all of which with an external magnetic field. We compare the ability of quantum discord, entanglement, and some thermodynamic quantities to spotlight the quantum critical points for several different temperatures. Secondly, for some models we go beyond nearest neighbors and also study the behavior of entanglement and quantum discord for second nearest neighbors around the critical point at finite temperature. Finally, we furnish a more quantitative description of how good all these quantities are in spotlighting critical points of quantum phase transitions at finite T, bridging the gap between experimental data and those theoretical descriptions solely based on the unattainable absolute zero assumption.

  18. Seasonal Inundation Monitoring of Northern Pantanal Wetland, Brazil Using ALOS SAR/InSAR and Envisat Altimetry

    Science.gov (United States)

    Kim, J.; Calmant, S.; Lee, H.; Lu, Z.; Shum, C.

    2011-12-01

    The Pantanal is one of the most biologically diverse ecosystems and largest wetland in the world. It has been threatened by massive economic development, and anthropogenic climate change. At the current rate, the Brazilian Pantanal will disappear within 45 years, according to 2006 report by Conservation International. Here, we illustrate that the evolutions of the Pantanal can be characterized by using ALOS PALSAR Fine-Beam and ScanSAR mode images, and Envisat radar altimetry. Multi-mode of high resolution and large-scale SAR images were used to unveil temporal and spatial inundation patterns. The backscattering coefficient of multi-mode SAR images shows regular change pattern in response to periodic inundation. InSAR analysis allows us to recognize that the temporal variation is not spatially constant, which is distinct among other wetlands, e.g., Louisiana wetlands. In addition to SAR/InSAR data, radar Altimetry (Envisat) is critical for providing vertical datum and fine temporal resolution, towards characterization of the Pantanal wetland condition during inundation. The observed close correlation between inundation area from SAR images and hydraulic change from a river gauge implies that the Pantanal is vulnerable to external effects presumably by human activities, and abnormal hydraulic change can threaten the ecosystems and biological diversity. We conclude that radar remote sensing data can provide timely and high-resolution monitoring of hydraulic characteristics of the Pantanal, one of the least-known and most fragile wetlands, and they can potentially be used as an efficient tool for remote wetland monitoring and ecological studies.

  19. Coseismic Deformation Detection of the 1997 Mani Earthquake Using ERS SAR Data

    Science.gov (United States)

    Wang, Xinhong; Tang, Lingli; Li, Chuanrong; Ouyang, Guangzhou; Zhang, Jingfa

    2010-12-01

    D-InSAR has been proven a powerful technique to measure coseismic deformation. This paper will describe an application of D-InSAR on earthquake deformation detecting. On the basis of analysis of fundamentals of D-InSAR, coseismic displacement fields corresponding to Mani earthquake which took place in November 1997, has been successfully extracted. Through the coseismic displacement information, the largest surface displacement value on LOS direction can then be estimated. Four ERS SAR images were used for the D-InSAR processing, in which three images were acquired prior to the earthquake event, and the other one were acquired after the earthquake. The resultant coseismic displacement field image clearly shows the spatial distribution pattern of the deformation magnitude and the location of the earthquake epicentre. From the number of deformation fringes, the most large displacement can be estimated to be at least 92.4 cm in the line of sight direction of the radar.

  20. 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

  1. 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

  2. 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

  3. Airborne FM-CW SAR and Integrated Navigation System Data Fusion

    NARCIS (Netherlands)

    Lorga, J.F.M.; Meta, A.; Wit, J.J.M. de; Mulder, J.A.

    2005-01-01

    The combination of compact FM-CW radar technology and high resolution SAR pro- cessing techniques should pave the way for the development of a small and cost e®ective imaging radar with high resolution. However, airborne SAR is a very novel application for FM-CW radars. In order to investigate the

  4. Development of a High Resolution Airborne Millimeter Wave FM-CW SAR

    NARCIS (Netherlands)

    Meta, A.; Wit, J.J.M. de; Hoogeboom, P.

    2004-01-01

    The combination of compact FM-CW radar technology and high resolution SAR processing techniques should pave the way for the development of a small, lightweight and cost effective imaging radar. In the field of airborne earth observation, SAR is however a novel application for FM-CW radars. At IRCTR

  5. PS-InSAR Monitoring of Landslide Activity in the Black Sea Coast of the Caucasus

    NARCIS (Netherlands)

    Kiseleva, E.; Mikhailov, V.; Smolyaninova, E.; Dmitriev, P.; Golubev, V.; Timoshkina, E.; Hooper, A.; Samiei-Esfahany, S.; Hanssen, R.F.

    2014-01-01

    The landslide activity in the area of Bolshoy Sochi (Big Sochi) situated at the Black Sea coast of the Great Caucasus has been studied using the StaMPS PS-InSAR method. We incorporated three sets of radar images from the satellites with different wavelengths ALOS, Envisat and Terra-SAR-X from both

  6. Development of a Small Phased Array SAR-MTI System for Tactical UAV

    NARCIS (Netherlands)

    Rossum, W.L. van; Grooters, R.; Halsema, D. van; Lorga, J.F.M.; Otten, M.P.G.; Vermeulen, B.C.B.; Vlothuizen, W.J.

    2005-01-01

    A small SAR-MTI system is being developed at TNO, aimed at deployment on tactical UAV, such as the SPERWER, in use with the Royal Netherlands Army. The system makes use of modern front-end technology, to provide flexible SAR imaging and MTI modes. Major design goals are 40 kg weight, 500 W power

  7. InSAR datum connection using GNSS-augmented radar transponders

    NARCIS (Netherlands)

    Mahapatra, P.S.; van der Marel, H.; van Leijen, F.J.; Samiei Esfahany, S.; Klees, R.; Hanssen, R.F.

    2017-01-01

    Deformation estimates from Interferometric Synthetic
    Aperture Radar (InSAR) are relative: they form a ‘free’
    network referred to an arbitrary datum, e.g. by assuming a reference
    point in the image to be stable. However, some applications
    require ‘absolute’ InSAR estimates, i.e.

  8. Demonstration MTI/SAR capability

    NARCIS (Netherlands)

    Vries, F.P.P. de; Broek, A.C. van den; Otten, M.P.G.; Groot, J.S.; Steeghs, T.P.H.; Dekker, R.J.; Rossum, W.L. van

    2001-01-01

    The aim of this project is to demonstrate to the Dutch armed forces the capability of MTI (Moving Target Indicator) and SAR (Synthetic Aperture Radar). This is done with the Dutch PHARUS sensor. The sensor is used to demonstrate how a phased array antenna can be used as an MTI/SAR sensor

  9. 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 ?

  10. 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

  11. Marine Targets Classification in PolInSAR Data

    Science.gov (United States)

    Chen, Peng; Yang, Jingsong; Ren, Lin

    2014-11-01

    In this paper, marine stationary targets and moving targets are studied by Pol-In-SAR data of Radarsat-2. A new method of stationary targets detection is proposed. The method get the correlation coefficient image of the In-SAR data, and using the histogram of correlation coefficient image. Then, A Constant False Alarm Rate (CFAR) algorithm and The Probabilistic Neural Network model are imported to detect stationary targets. To find the moving targets, Azimuth Ambiguity is show as an important feature. We use the length of azimuth ambiguity to get the target's moving direction and speed. Make further efforts, Targets classification is studied by rebuild the surface elevation of marine targets.

  12. The Danish real-time SAR processor: first results

    DEFF Research Database (Denmark)

    Dall, Jørgen; Jørgensen, Jørn Hjelm; Netterstrøm, Anders

    1993-01-01

    . The processor is capable of focusing the entire swath of the raw SAR data into full resolution, and depending on the choice made by the on-board operator, either a high resolution one-look zoom image or a spatially multilooked overview image is displayed. After a brief design review, the paper addresses various......A real-time processor (RTP) for the Danish airborne Synthetic Aperture Radar (SAR) has been designed and constructed at the Electromagnetics Institute. The implementation was completed in mid 1992, and since then the RTP has been operated successfully on several test and demonstration flights...

  13. Scattering property based contextual PolSAR speckle filter

    Science.gov (United States)

    Mullissa, Adugna G.; Tolpekin, Valentyn; Stein, Alfred

    2017-12-01

    Reliability of the scattering model based polarimetric SAR (PolSAR) speckle filter depends upon the accurate decomposition and classification of the scattering mechanisms. This paper presents an improved scattering property based contextual speckle filter based upon an iterative classification of the scattering mechanisms. It applies a Cloude-Pottier eigenvalue-eigenvector decomposition and a fuzzy H/α classification to determine the scattering mechanisms on a pre-estimate of the coherency matrix. The H/α classification identifies pixels with homogeneous scattering properties. A coarse pixel selection rule groups pixels that are either single bounce, double bounce or volume scatterers. A fine pixel selection rule is applied to pixels within each canonical scattering mechanism. We filter the PolSAR data and depending on the type of image scene (urban or rural) use either the coarse or fine pixel selection rule. Iterative refinement of the Wishart H/α classification reduces the speckle in the PolSAR data. Effectiveness of this new filter is demonstrated by using both simulated and real PolSAR data. It is compared with the refined Lee filter, the scattering model based filter and the non-local means filter. The study concludes that the proposed filter compares favorably with other polarimetric speckle filters in preserving polarimetric information, point scatterers and subtle features in PolSAR data.

  14. First Spaceborne SAR-GMTI Experimental Results for the Chinese Gaofen-3 Dual-Channel SAR Sensor.

    Science.gov (United States)

    Wang, Chenghao; Liao, Guisheng; Zhang, Qingjun

    2017-11-21

    In spaceborne synthetic aperture radar (SAR) sensors, it is a challenging task to detect ground slow-moving targets against strong clutter background with limited spatial channels and restricted pulse repetition frequency (PRF). In this paper, we evaluate the image-based dual-channel SAR-ground moving target indication (SAR-GMTI) workflow for the Gaofen-3 SAR sensor and analyze the impact of strong azimuth ambiguities on GMTI when the displaced phase center antenna (DPCA) condition is not fully satisfied, which has not been demonstrated yet. An effective sliding window design technique based on system parameters analysis is proposed to deal with azimuth ambiguities and reduce false alarm. In the SAR-GMTI experiments, co-registration, clutter suppression, constant false alarm rate (CFAR) detector, vector velocity estimation and moving target relocation are analyzed and discussed thoroughly. With the real measured data of the Gaofen-3 dual-channel SAR sensor, the GMTI capability of this sensor is demonstrated and the effectiveness of the proposed method is verified.

  15. First Spaceborne SAR-GMTI Experimental Results for the Chinese Gaofen-3 Dual-Channel SAR Sensor

    Directory of Open Access Journals (Sweden)

    Chenghao Wang

    2017-11-01

    Full Text Available In spaceborne synthetic aperture radar (SAR sensors, it is a challenging task to detect ground slow-moving targets against strong clutter background with limited spatial channels and restricted pulse repetition frequency (PRF. In this paper, we evaluate the image-based dual-channel SAR-ground moving target indication (SAR-GMTI workflow for the Gaofen-3 SAR sensor and analyze the impact of strong azimuth ambiguities on GMTI when the displaced phase center antenna (DPCA condition is not fully satisfied, which has not been demonstrated yet. An effective sliding window design technique based on system parameters analysis is proposed to deal with azimuth ambiguities and reduce false alarm. In the SAR-GMTI experiments, co-registration, clutter suppression, constant false alarm rate (CFAR detector, vector velocity estimation and moving target relocation are analyzed and discussed thoroughly. With the real measured data of the Gaofen-3 dual-channel SAR sensor, the GMTI capability of this sensor is demonstrated and the effectiveness of the proposed method is verified.

  16. Performance Analysis for Airborne Interferometric SAR Affected by Flexible Baseline Oscillation

    Directory of Open Access Journals (Sweden)

    Liu Zhong-sheng

    2014-04-01

    Full Text Available The airborne interferometric SAR platform suffers from instability factors, such as air turbulence and mechanical vibrations during flight. Such factors cause the oscillation of the flexible baseline, which leads to significant degradation of the performance of the interferometric SAR system. This study is concerned with the baseline oscillation. First, the error of the slant range model under baseline oscillation conditions is formulated. Then, the SAR complex image signal and dual-channel correlation coefficient are modeled based on the first-order, second-order, and generic slant range error. Subsequently, the impact of the baseline oscillation on the imaging and interferometric performance of the SAR system is analyzed. Finally, simulations of the echo data are used to validate the theoretical analysis of the baseline oscillation in the airborne interferometric SAR.

  17. Spotlight on topographical pressure pain sensitivity maps: a review

    Directory of Open Access Journals (Sweden)

    Alburquerque-Sendín F

    2018-01-01

    Full Text Available Francisco Alburquerque-Sendín,1 Pascal Madeleine,2 César Fernández-de-las-Peñas,3 Paula Rezende Camargo,4 Tania Fátima Salvini4 1Department of Socio-Sanitary Sciences, Radiology and Physical Medicine, Universidad de Córdoba, Córdoba, Spain; 2Physical Activity and Human Performance Group, SMI, Department of Health Science and Technology, Faculty of Medicine, Aalborg University, Aalborg, Denmark; 3Department of Physical Therapy, Occupational Therapy, Physical Medicine and Rehabilitation, Universidad Rey Juan Carlos, Madrid, Spain; 4Department of Physical Therapy, Federal University of São Carlos, São Carlos, SP, Brazil Abstract: Mechanical hyperalgesia defined as decreased pressure pain thresholds (PPTs is commonly associated with pain. In this narrative review, we report the current state of the art within topographical pressure sensitivity maps. Such maps are based on multiple PPT assessments. The PPTs are assessed by an a priori defined grid with special focus on both spatial and temporal summation issues. The grid covers the muscle or the body region of interest using absolute or relative values determined from anatomical landmarks or anthropometric values. The collected PPTs are interpolated by Shepard or Franke and Nielson interpolation methods to create topographical pressure sensitivity maps. This new imaging technique has proven to be valuable in various disciplines including exercise physiology, neurology, physical therapy, occupational medicine, oncology, orthopedics, and sport sciences. The reviewed papers have targeted different body regions like the scalp, low back, neck–shoulder, and upper and lower extremities. The maps have delineated spatial heterogeneity in the pressure pain sensitivity underlining the different extents of pressure pain hyperalgesia in both experimentally induced and disease-associated pain conditions. Furthermore, various intervention studies have proven the utility of topographical pressure pain

  18. Airborne Multi-Band SAR in the Arctic

    Science.gov (United States)

    Gardner, J. M.; Brozena, J. M.; Liang, R.; Ball, D.; Holt, B.; Thomson, J.

    2016-12-01

    As one component of the Office of Naval Research supported Sea State Departmental Research Initiative during October of 2015 the Naval Research Laboratory flew an ultrawide-band, low-frequency, polarimetric SAR over the southward advancing sea ice in Beaufort Sea. The flights were coordinated with the research team aboard the R/V Sikuliaq working near and in the advancing pack ice. The majority of the SAR data were collected with the L-Band sensor (1000-1500 MHz) from an altitude of 10,000', providing a useful swath 6 km wide with 75o and 25 o angles of incidence at the inner and outer edge of the swath respectively. Some data were also collected with the P-Band SAR (215-915 MHz). The extremely large bandwidths allowed for formation of image pixels as small as 30 cm, however, we selected 60 cm pixel size to reduce image speckle. The separate polarimetric images are calibrated to one pixel to allow for calculations such as polarimetric decompositions that require the images to be well aligned. Both frequencies are useful particularly for the detection of ridges and areas of deformed ice. There are advantages and disadvantages to airborne SAR imagery compared to satellites. The chief advantages being the enormous allowable bandwidth leading to very fine range resolution, and the ability to fly arbitrary trajectories on demand. The latter permits specific areas to be imaged at a given time with a specified illumination direction. An area can even be illuminated from all directions by flying a circular trajectory around the target area. This captures ice features that are sensitive to illumination direction such as cracks, sastrugi orientation, and ridges. The disadvantages include variation of intensity across the swath with range and incidence angle. In addition to the SAR data, we collected photogrammetric imagery from a DSS-439, scanning lidar from a Riegl Q560 and surface brightness temperatures from a KT-19. However, since all of these sensors are nadir pointing

  19. Validation and Sensitivity Analysis of 3D Synthetic Aperture Radar (SAR) Imaging of the Interior of Primitive Solar System Bodies: Comets and Asteroids

    Data.gov (United States)

    National Aeronautics and Space Administration — This task will demonstrate that using Radar Reflection Imager Instrument in an orbing platform , we can perform 3D mapping of the Cometary Nucleus. To probe the...

  20. Validation and Sensitivity Analysis of 3D Synthetic Aperture Radar (SAR) Imaging of the Interior of Primitive Solar System Bodies: Comets and Asteroids Project

    Data.gov (United States)

    National Aeronautics and Space Administration — To probe the interior of a comet, we are going to employ Radar Reflection Imager (RRI) Instrument on an orbiting platform. While orbiting around the comet at a safe...

  1. SAR: A novel application for FM-CW radars

    NARCIS (Netherlands)

    Wit, J.J.M. de; Hoogeboom, P.

    2001-01-01

    For small-scale earth observation applications, there ia a special interest in low-cost, high-resolution imaging radars small, enough to be operated from small, possibly unmanned aircraft. The combination of FM-CW technology and the high resolution of SAR systems should result in such a small,

  2. Siyah Sarımsak

    Directory of Open Access Journals (Sweden)

    Selen Akan

    2015-02-01

    Full Text Available Sarımsağın insan sağlığına yararları yüzyıllardır yaygın olarak bilinmektedir. Besin içeriği nedeniyle uzmanların şiddetle tavsiye etmelerine ve beslenme programlarına mutlaka eklenilmesine rağmen keskin kokusu nedeniyle birçok kişi tüketmekten kaçınmaktadır. Sarımsağın bu dezavantajı için alternatif olarak siyah sarımsak gündeme getirilmiştir. Siyah sarımsak, taze sarımsağın fermente edilip, tamamen siyah rengini alana kadar koyu renge dönüşümü ile oluşmakta ve bu süreçte besin içeriği de değişim göstermektedir. Fermantasyon işlemi ile sarımsak başlarının karakteristik kokusunu veren öncül maddeleri alliin ve allicin azalmakta böylelikle hem istenmeyen kokusunu kaybetmekte hem de tadındaki acılık kaybolmaktadır. Siyah sarımsak, taze sarımsağa oranla yüksek oranda antioksidan aktiviteye sahiptir. Bu özelliği, sadece koku ve lezzet olarak değil, besin içeriğiyle de beslenme takviyesinde kullanımını daha çekici hale getirmiştir. Siyah sarımsak Asya ve Avrupa ülkelerinde henüz yeni beğeni toplamaya başlamıştır. Japonya ve Kore’de siyah sarımsak, anti kanserojen özellikleri ve aroması ile yemeklerde aparatif olarak kullanılmaktadır. Amerika Birleşik Devletleri, Kanada ve İngiltere’de de yoğun şekilde ticareti başlamıştır. Bu çalışmada, siyah sarımsak konusunda yapılan araştırmaların sonuçları derlenmiştir.

  3. Semi-physical Simulation of the Airborne InSAR based on Rigorous Geometric Model and Real Navigation Data

    Science.gov (United States)

    Changyong, Dou; Huadong, Guo; Chunming, Han; yuquan, Liu; Xijuan, Yue; Yinghui, Zhao

    2014-03-01

    Raw signal simulation is a useful tool for the system design, mission planning, processing algorithm testing, and inversion algorithm design of Synthetic Aperture Radar (SAR). Due to the wide and high frequent variation of aircraft's trajectory and attitude, and the low accuracy of the Position and Orientation System (POS)'s recording data, it's difficult to quantitatively study the sensitivity of the key parameters, i.e., the baseline length and inclination, absolute phase and the orientation of the antennas etc., of the airborne Interferometric SAR (InSAR) system, resulting in challenges for its applications. Furthermore, the imprecise estimation of the installation offset between the Global Positioning System (GPS), Inertial Measurement Unit (IMU) and the InSAR antennas compounds the issue. An airborne interferometric SAR (InSAR) simulation based on the rigorous geometric model and real navigation data is proposed in this paper, providing a way for quantitatively studying the key parameters and for evaluating the effect from the parameters on the applications of airborne InSAR, as photogrammetric mapping, high-resolution Digital Elevation Model (DEM) generation, and surface deformation by Differential InSAR technology, etc. The simulation can also provide reference for the optimal design of the InSAR system and the improvement of InSAR data processing technologies such as motion compensation, imaging, image co-registration, and application parameter retrieval, etc.

  4. Semi-physical Simulation of the Airborne InSAR based on Rigorous Geometric Model and Real Navigation Data

    International Nuclear Information System (INIS)

    Changyong, Dou; Huadong, Guo; Chunming, Han; Yuquan, Liu; Xijuan, Yue; Yinghui, Zhao

    2014-01-01

    Raw signal simulation is a useful tool for the system design, mission planning, processing algorithm testing, and inversion algorithm design of Synthetic Aperture Radar (SAR). Due to the wide and high frequent variation of aircraft's trajectory and attitude, and the low accuracy of the Position and Orientation System (POS)'s recording data, it's difficult to quantitatively study the sensitivity of the key parameters, i.e., the baseline length and inclination, absolute phase and the orientation of the antennas etc., of the airborne Interferometric SAR (InSAR) system, resulting in challenges for its applications. Furthermore, the imprecise estimation of the installation offset between the Global Positioning System (GPS), Inertial Measurement Unit (IMU) and the InSAR antennas compounds the issue. An airborne interferometric SAR (InSAR) simulation based on the rigorous geometric model and real navigation data is proposed in this paper, providing a way for quantitatively studying the key parameters and for evaluating the effect from the parameters on the applications of airborne InSAR, as photogrammetric mapping, high-resolution Digital Elevation Model (DEM) generation, and surface deformation by Differential InSAR technology, etc. The simulation can also provide reference for the optimal design of the InSAR system and the improvement of InSAR data processing technologies such as motion compensation, imaging, image co-registration, and application parameter retrieval, etc

  5. JERS-1 SAR Global Rain Forest Mapping Project: South America, 1995-1996, Vol. AM-1

    Data.gov (United States)

    National Aeronautics and Space Administration — This data set contains four ISO images of a CD-ROM set from the Japanese Earth Resources Satellite 1 (JERS-1)Synthetic Aperture Radar (SAR) of the National Space...

  6. An image-segmentation-based framework to detect oil slicks from moving vessels in the Southern African oceans using SAR imagery

    CSIR Research Space (South Africa)

    Mdakane, Lizwe W

    2017-06-01

    Full Text Available Oil slick events caused due to bilge leakage/dumps from ships and from other anthropogenic sources pose a threat to the aquatic ecosystem and need to be monitored on a regular basis. An automatic image-segmentation-based framework to detect oil...

  7. UTILIZING SAR AND MULTISPECTRAL INTEGRATED DATA FOR EMERGENCY RESPONSE

    Directory of Open Access Journals (Sweden)

    S. Havivi

    2016-06-01

    Full Text Available Satellite images are used widely in the risk cycle to understand the exposure, refine hazard maps and quickly provide an assessment after a natural or man-made disaster. Though there are different types of satellite images (e.g. optical, radar these have not been combined for risk assessments. The characteristics of different remote sensing data type may be extremely valuable for monitoring and evaluating the impacts of disaster events, to extract additional information thus making it available for emergency situations. To base this approach, two different change detection methods, for two different sensor's data were used: Coherence Change Detection (CCD for SAR data and Covariance Equalization (CE for multispectral imagery. The CCD provides an identification of the stability of an area, and shows where changes have occurred. CCD shows subtle changes with an accuracy of several millimetres to centimetres. The CE method overcomes the atmospheric effects differences between two multispectral images, taken at different times. Therefore, areas that had undergone a major change can be detected. To achieve our goals, we focused on the urban areas affected by the tsunami event in Sendai, Japan that occurred on March 11, 2011 which affected the surrounding area, coastline and inland. High resolution TerraSAR-X (TSX and Landsat 7 images, covering the research area, were acquired for the period before and after the event. All pre-processed and processed according to each sensor. Both results, of the optical and SAR algorithms, were combined by resampling the spatial resolution of the Multispectral data to the SAR resolution. This was applied by spatial linear interpolation. A score representing the damage level in both products was assigned. The results of both algorithms, high level of damage is shown in the areas closer to the sea and shoreline. Our approach, combining SAR and multispectral images, leads to more reliable information and provides a

  8. Interpreting sea surface slicks on the basis of the normalized radar cross-section model using RADARSAT-2 copolarization dual-channel SAR images

    Science.gov (United States)

    Ivonin, D. V.; Skrunes, S.; Brekke, C.; Ivanov, A. Yu.

    2016-03-01

    A simple automatic multipolarization technique for discrimination of main types of thin oil films (of thickness less than the radio wave skin depth) from natural ones is proposed. It is based on a new multipolarization parameter related to the ratio between the damping in the slick of specially normalized resonant and nonresonant signals calculated using the normalized radar cross-section model proposed by Kudryavtsev et al. (2003a). The technique is tested on RADARSAT-2 copolarization (VV/HH) synthetic aperture radar images of slicks of a priori known provenance (mineral oils, e.g., emulsion and crude oil, and plant oil served to model a natural slick) released during annual oil-on-water exercises in the North Sea in 2011 and 2012. It has been shown that the suggested multipolarization parameter gives new capabilities in interpreting slicks visible on synthetic aperture radar images while allowing discrimination between mineral oil and plant oil slicks.

  9. 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.

  10. 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 of sufficient size, simulated data play a big role in SAR ATR development, but the transferability of knowledge learned on simulated data to real data remains to be studied further. In this letter, we show the first study of Transfer Learning between a simulated data set and a set of real....... These results encourage SAR ATR development to continue the improvement of simulated data sets of greater size and complex scenarios in order to build robust algorithms for real life SAR ATR applications.......Data-driven classification algorithms have proved to do well for automatic target recognition (ATR) in synthetic aperture radar (SAR) data. Collecting data sets suitable for these algorithms is a challenge in itself as it is difficult and expensive. Due to the lack of labeled data sets with real...

  11. 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.

  12. Sensitivity of Multi-Source SAR Backscatter to Changes in Forest Aboveground Biomass

    Directory of Open Access Journals (Sweden)

    Wenli Huang

    2015-07-01

    Full Text Available Accurate estimates of forest aboveground biomass (AGB after anthropogenic disturbance could reduce uncertainties in the carbon budget of terrestrial ecosystems and provide critical information to policy makers. Yet, the loss of carbon due to forest disturbance and the gain from post-disturbance recovery have not been sufficiently assessed. In this study, a sensitivity analysis was first conducted to investigate: (1 the influence of incidence angle and soil moisture on Synthetic Aperture Radar (SAR backscatter; (2 the feasibility of cross-image normalization between multi-temporal and multi-sensor SAR data; and (3 the possibility of applying normalized backscatter data to detect forest biomass changes. An empirical model was used to reduce incidence angle effects, followed by cross-image normalization procedure to lessen soil moisture effect. Changes in forest biomass at medium spatial resolution (100 m were mapped using both spaceborne and airborne SAR data. Results indicate that (1 the effect of incidence angle on SAR backscatter could be reduced to less than 1 dB by the correction model for airborne SAR data; (2 over 50% of the changes in SAR backscatter due to soil moisture could be eliminated by the cross-image normalization procedure; and (3 forest biomass changes greater than 100 Mg·ha−1 or above 50% of 150 Mg·ha−1 are detectable using cross-normalized SAR data.

  13. Satellite SAR interferometric techniques applied to emergency mapping

    Science.gov (United States)

    Stefanova Vassileva, Magdalena; Riccardi, Paolo; Lecci, Daniele; Giulio Tonolo, Fabio; Boccardo Boccardo, Piero; Chiesa, Giuliana; Angeluccetti, Irene

    2017-04-01

    monitoring maps for risk prevention and mitigation purposes. Nevertheless, multi-temporal techniques require large SAR temporal datasets, i.e. 20 and more images. Being the Sentinel-1 missions operational only since April 2014, multi-mission SAR datasets should be therefore exploited to carry out historical analysis.

  14. Seasat SAR identification of dry climate urban land cover

    Science.gov (United States)

    Henderson, F. M.; Wharton, S. W.

    1980-01-01

    Digitally processed Seasat synthetic aperture radar (SAR) imagery of the Denver, Colorado area was examined to assess its potential for mapping urban land cover and the compatibility of SAR derived classes with those described in the U.S. Geological Survey classification system. The entire scene was interpreted to generate a small-scale land cover map. In addition, six subscene enlargements representative of urban land cover categories extant in the area were used as test sites for detailed analysis of land cover types. Two distinct approaches were employed and compared in examining the imagery - a visual interpretation of black-and-white positive transparencies and an automated-machine/visual interpretation. The latter used the Image 100 interactive image analysis system to generate land cover classes by density level slicing of the image frequency histogram.

  15. The Danish SAR system - Design and initial tests

    Science.gov (United States)

    Madsen, Soren N.; Christensen, Erik L.; Skou, Niels; Dall, Jorgen

    1991-01-01

    In January 1986, the design of a high-resolution airborne C-band SAR started at the Electromagnetics Institute of the Technical University of Denmark. The initial system test flights took place in November and December 1989. The authors describe the design of the system, its implementation, and its performance. They show how digital technology has been utilized to realize a very flexible radar with variable resolution, swath-width, and imaging geometry. The motion-compensation algorithms implemented to obtain the high resolution and the special features built into the system to ensure proper internal calibration are outlined. The data processing system, developed for image generation and quality assurance, is sketched, with special emphasis on the flexibility of the system. Sample images and a preliminary performance evaluation are presented, demonstrating that the design goals have been met. The ongoing system upgrades and the planned scientific utilization of the C-band SAR are described.

  16. Parametric estimation of time varying baselines in airborne interferometric SAR

    DEFF Research Database (Denmark)

    Mohr, Johan Jacob; Madsen, Søren Nørvang

    1996-01-01

    A method for estimation of time varying spatial baselines in airborne interferometric synthetic aperture radar (SAR) is described. The range and azimuth distortions between two images acquired with a non-linear baseline are derived. A parametric model of the baseline is then, in a least square...... sense, estimated from image shifts obtained by cross correlation of numerous small patches throughout the image. The method has been applied to airborne EMISAR imagery from the 1995 campaign over the Storstrommen Glacier in North East Greenland conducted by the Danish Center for Remote Sensing. This has...... reduced the baseline uncertainties from several meters to the centimeter level in a 36 km scene. Though developed for airborne SAR the method can easily be adopted to satellite data...

  17. Capability of geometric features to classify ships in SAR imagery

    Science.gov (United States)

    Lang, Haitao; Wu, Siwen; Lai, Quan; Ma, Li

    2016-10-01

    Ship classification in synthetic aperture radar (SAR) imagery has become a new hotspot in remote sensing community for its valuable potential in many maritime applications. Several kinds of ship features, such as geometric features, polarimetric features, and scattering features have been widely applied on ship classification tasks. Compared with polarimetric features and scattering features, which are subject to SAR parameters (e.g., sensor type, incidence angle, polarization, etc.) and environment factors (e.g., sea state, wind, wave, current, etc.), geometric features are relatively independent of SAR and environment factors, and easy to be extracted stably from SAR imagery. In this paper, the capability of geometric features to classify ships in SAR imagery with various resolution has been investigated. Firstly, the relationship between the geometric feature extraction accuracy and the SAR imagery resolution is analyzed. It shows that the minimum bounding rectangle (MBR) of ship can be extracted exactly in terms of absolute precision by the proposed automatic ship-sea segmentation method. Next, six simple but effective geometric features are extracted to build a ship representation for the subsequent classification task. These six geometric features are composed of length (f1), width (f2), area (f3), perimeter (f4), elongatedness (f5) and compactness (f6). Among them, two basic features, length (f1) and width (f2), are directly extracted based on the MBR of ship, the other four are derived from those two basic features. The capability of the utilized geometric features to classify ships are validated on two data set with different image resolutions. The results show that the performance of ship classification solely by geometric features is close to that obtained by the state-of-the-art methods, which obtained by a combination of multiple kinds of features, including scattering features and geometric features after a complex feature selection process.

  18. Surface deformation of Taipei basin detected by Differential SAR Interferometry

    Science.gov (United States)

    Chen, Y.; Chang, C.; Yen, J.; Lin, M.

    2006-12-01

    Taiwan island is located between the southeastern periphery of the Eurasian plate and the Philippine Sea plate. The two converging plates produced very active tectonics, and can be seen by the high seismicity and deformation rate. Taipei, the highest populated area, center of politics, and economics in Taiwan, is in Taipei basin at the northern part of the island. There are several faults in and surrounding the basin, and the city is threatened with a high geological hazard potential that we should keep monitoring the crustal deformation to prevent and mitigate the disaster effect. The aims of our study is to apply the DInSAR technique to determine the surface deformation of Taipei basin area, and discussing the relation between the manifestation of deformation and the tectonically active region, Shanjiao fault. In the past few years, Differential SAR Interferometry (DInSAR) has been proved to be a powerful technique for monitoring the neotectonic activities and natural hazards. High spatial sampling rate of DInSAR technique allows studies of surface deformations with centimeter accuracy. In this area, we used ERS-1/2 SAR images acquired from 1993 to 2005 to generate 10 differential interferograms and processed the data using DIAPASON developed by CNES and SRTM global DEM.From our results, the deformation rate in Taipei is generally high in the western end of the basin along the Shanjiao fault and decrease eastward, while the subsidence center often appeared in the center of the Taipei basin. The neotectonic activity of the Shanjiao fault appeared to be insignificant by itself but it seemed to separate the subsiding basin from the surrounding areas. Further comparison between our DInSAR results and isopach of the Taipei basin revealed that the subsidence centers appeared in the interferograms did not coincide with the location where the sediments are thickest. Our results from differential interferometry will be compared to other geodetic measurements such as the

  19. FEM-based linear inverse modeling using a 3D source array to image magma chambers with free geometry. Application to InSAR data from Rabaul Caldera (PNG).

    Science.gov (United States)

    Ronchin, Erika; Masterlark, Timothy; Dawson, John; Saunders, Steve; Martí Molist, Joan

    2015-04-01

    In this study, we present a method to fully integrate a family of finite element models (FEMs) into the regularized linear inversion of InSAR data collected at Rabaul caldera (PNG) between February 2007 and December 2010. During this period the caldera experienced a long-term steady subsidence that characterized surface movement both inside the caldera and outside, on its western side. The inversion is based on an array of FEM sources in the sense that the Green's function matrix is a library of forward numerical displacement solutions generated by the sources of an array common to all FEMs. Each entry of the library is the LOS surface displacement generated by injecting a unity mass of fluid, of known density and bulk modulus, into a different source cavity of the array for each FEM. By using FEMs, we are taking advantage of their capability of including topography and heterogeneous distribution of elastic material properties. All FEMs of the family share the same mesh in which only one source is activated at the time by removing the corresponding elements and applying the unity fluid flux. The domain therefore only needs to be discretized once. This precludes remeshing for each activated source, thus reducing computational requirements, often a downside of FEM-based inversions. Without imposing an a-priori source, the method allows us to identify, from a least-squares standpoint, a complex distribution of fluid flux (or change in pressure) with a 3D free geometry within the source array, as dictated by the data. The results of applying the proposed inversion to Rabaul InSAR data show a shallow magmatic system under the caldera made of two interconnected lobes located at the two opposite sides of the caldera. These lobes could be consistent with feeding reservoirs of the ongoing Tavuvur volcano eruption of andesitic products, on the eastern side, and of the past Vulcan volcano eruptions of more evolved materials, on the western side. The interconnection and

  20. Dynamic changes of serum SARS-Coronavirus IgG, pulmonary function and radiography in patients recovering from SARS after hospital discharge

    Directory of Open Access Journals (Sweden)

    Chen Liangan

    2005-01-01

    Full Text Available Abstract Objective The intent of this study was to examine the recovery of individuals who had been hospitalized for severe acute respiratory syndrome (SARS in the year following their discharge from the hospital. Parameters studied included serum levels of SARS coronavirus (SARS-CoV IgG antibody, tests of lung function, and imaging data to evaluate changes in lung fibrosis. In addition, we explored the incidence of femoral head necrosis in some of the individuals recovering from SARS. Methods The subjects of this study were 383 clinically diagnosed SARS patients in Beijing, China. They were tested regularly for serum levels of SARS-CoV IgG antibody and lung function and were given chest X-rays and/or high resolution computerized tomography (HRCT examinations at the Chinese PLA General Hospital during the 12 months that followed their release from the hospital. Those individuals who were found to have lung diffusion abnormities (transfer coefficient for carbon monoxide [DLCO] Findings Of all the subjects, 81.2% (311 of 383 patients tested positive for serum SARS-CoV IgG. Of those testing positive, 27.3% (85 of 311 patients were suffering from lung diffusion abnormities (DLCO Interpretation The lack of sero-positive SARS-CoV in some individuals suggests that there may have been some misdiagnosed cases among the subjects included in this study. Of those testing positive, the serum levels of SARS-CoV IgG antibody decreased significantly during the 12 months after hospital discharge. Additionally, we found that the individuals who had lung fibrosis showed some spontaneous recovery. Finally, some of the subjects developed femoral head necrosis.

  1. Using TerraSAR-X satellite data to detect road age and degradation

    Science.gov (United States)

    Necsoiu, Marius; Longepe, Nicolas; Parra, Jorge O.; Walter, Gary R.

    2017-05-01

    Analysis of satellite-acquired synthetic aperture radar (SAR) data provides a way to rapidly survey road conditions over large areas. This capability could be useful for identifying road segments that potentially require repair or at least onsite inspection of their condition due to changes in vehicular traffic associated with change in land use. We conducted a feasibility study focused on urban roads near the Southwest Research Institute (SwRI) campus in San Antonio, Texas. The roads near SwRI were affected by heavy truck traffic, they were easily inspected, and the age and construction of the pavement was known. TerraSAR-X (TSX) SpotLight (ST) satellite data were used to correlate radar backscattering response to pavement age and condition. Our preliminary results indicate that TSX radar imagery can be useful for detecting changes in pavement type, damage to pavement, such as cracking and scaling, and, occasionally, severe rutting. In addition, multitemporal interferometric analysis showed patches of settlement along two roads south of the SwRI campus. Further development of an automated approach to detect degradation of roads could allow transportation departments to prioritize inspection and repair efforts. The techniques also could be used to detect surreptitious heavy truck traffic in areas where direct inspection is not possible.

  2. 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

  3. 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.

  4. 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.

  5. Light weight digital array SAR

    NARCIS (Netherlands)

    Otten, M.; Maas, N.; Bolt, R.; Anitori, L.

    2010-01-01

    A light weight SAR has been designed, suitable for short range tactical UAVs, consisting of a fully digital receive array, and a very compact active transmit antenna. The weight of the complete RF front is expected to be below 3 kg, with a power consumption below 30 W. This X-band system can provide

  6. Three-dimensional subsurface imaging synthetic aperture radar

    International Nuclear Information System (INIS)

    Moussally, G.J.

    1995-01-01

    The objective of this applied research and development project is to develop a system known as '3-D SISAR'. This system consists of a ground penetrating radar with software algorithms designed for the detection, location, and identification of buried objects in the underground hazardous waste environments found at DOE storage sites. Three-dimensional maps of the object locations will be produced which can assist the development of remediation strategies and the characterization of the digface during remediation operations. It is expected that the 3-D SISAR will also prove useful for monitoring hydrocarbon based contaminant migration after remediation. The underground imaging technique being developed under this contract utilizes a spotlight mode Synthetic Aperture Radar (SAR) approach which, due to its inherent stand-off capability, will permit the rapid survey of a site and achieve a high degree of productivity over large areas. When deployed from an airborne platform, the stand-off techniques is also seen as a way to overcome practical survey limitations encountered at vegetated sites

  7. 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.

  8. SAR Target Recognition with Feature Fusion Based on Stacked Autoencoder

    Directory of Open Access Journals (Sweden)

    Kang Miao

    2017-04-01

    Full Text Available A feature fusion algorithm based on a Stacked AutoEncoder (SAE for Synthetic Aperture Rader (SAR imagery is proposed in this paper. Firstly, 25 baseline features and Three-Patch Local Binary Patterns (TPLBP features are extracted. Then, the features are combined in series and fed into the SAE network, which is trained by a greedy layer-wise method. Finally, the softmax classifier is employed to fine tune the SAE network for better fusion performance. Additionally, the Gabor texture features of SAR images are extracted, and the fusion experiments between different features are carried out. The results show that the baseline features and TPLBP features have low redundancy and high complementarity, which makes the fused feature more discriminative. Compared with the SAR target recognition algorithm based on SAE or CNN (Convolutional Neural Network, the proposed method simplifies the network structure and increases the recognition accuracy and efficiency. 10-classes SAR targets based on an MSTAR dataset got a classification accuracy up to 95.88%, which verifies the effectiveness of the presented algorithm.

  9. Forest mapping using bi-aspect polarimetric SAR data in southwest China

    Science.gov (United States)

    Zhang, Fengli; Xu, Maosong; Xia, Zhongsheng; Wan, Zi; Li, Kun; Li, Xiaofang

    2009-10-01

    Synthetic aperture radar (SAR) provides a powerful tool for forestry inventory because of its all-weather and all-day capabilities. In this paper forest mapping method using bi-aspect polarimetric SAR data acquired from ascending and descending path has been studied. Zhazuo forest farm in Guizhou province was selected as test site and an 8-temporal field experiment was designed to obtain bio-physical parameters and spatial structure parameters of the 12 sample plots. Then the Michigan Microwave Canopy Scattering model (MIMICS) was employed to analyze the seasonal variation of these 4 types of managed forests. Using polarimetric Radarsat 2 data, scattering mechanisms of each forest type were determined and polarimetric variables were extracted and analyzed for forest discrimination. Considering the inherent geometric distortion of SAR imaging in hilly areas, a geometric correction strategy using bi-aspect SAR images and high resolution DEM was proposed. Then support vector machines method was adopted for classification of the whole test area. Experiments show that the bi-aspect geometric strategy is useful for hilly areas especially for shadow elimination in SAR image, and polarimetric SAR data is helpful to forest mapping.

  10. Rapid Flood Map Generation from Spaceborne SAR Observations

    Science.gov (United States)

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

    2016-12-01

    The Advanced Rapid Imaging and Analysis (ARIA) team has responded to the January 2016 US Midwest Floods along the Mississippi River. Daily teleconferences with FEMA, NOAA, NGA, and USGS, provided information on precipitation and flood crest migration, based on which we coordinated with the Japanese Aerospace Exploration Agency (JAXA) through NASA headquarters for JAXA's ALOS-2 timely tasking over two paths. We produced flood extent maps using ALOS-2 SM3 mode Level 1.5 data that were provided through the International Charter and stored at the US Geological Survey's Hazards Data Distribution System (HDDS) archive. On January 6, the first four frames (70 km x 240 km) were acquired, which included the City of Memphis. We registered post-event SAR images to pre-event images, applied radiometric calibration, took a logarithm of the ratio of the two images. Two thresholds were applied to represent flooded areas that became open water (colored in blue) and flooded areas with tall vegetation (colored in red). The second path was acquired on January 11 further down along the Mississippi River. Seven frames (70 km x 420 km) were acquired and flood maps were created in the similar fashion. The maps were delivered to the FEMA as well as posted on ARIA's public website. The FEMA stated that SAR provides inspection priority for optical imagery and ground response. The ALOS-2 data and the products have been a very important source of information during this response as the flood crest has moved down stream. The SAR data continue to be an important resource during times when optical observations are often not useful. In close collaboration with FEMA and USGS, we also work on other flood events including June 2016 China Floods using European Space Agency's (ESA's) Sentienl-1 data, to produce flood extent maps and identify algorithmic needs and ARIA system's requirements to automate and rapidly produce and deliver flood maps for future events. With the addition of Sentinel-1B

  11. Diarrhea & Child Care: Controlling Diarrhea in Out-of-Home Child Care. NCEDL Spotlights, No. 4.

    Science.gov (United States)

    Churchill, Robin B.; Pickering, Larry K.

    This report, the fourth in the National Center for Early Development and Learning's (NCEDL) "Spotlights" series, is based on excerpts from a paper presented during a "Research into Practice in Infant/Toddler Care" synthesis conference in fall 1997. The report addresses controlling diarrhea in out-of-home child care. The report…

  12. InSAR data for monitoring land subsidence: time to think big

    Directory of Open Access Journals (Sweden)

    A. Ferretti

    2015-11-01

    Full Text Available Satellite interferometric synthetic aperture radar (InSAR data have proven effective and valuable in the analysis of urban subsidence phenomena based on multi-temporal radar images. Results obtained by processing data acquired by different radar sensors, have shown the potential of InSAR and highlighted the key points for an operational use of this technology, namely: (1 regular acquisition over large areas of interferometric data stacks; (2 use of advanced processing algorithms, capable of estimating and removing atmospheric disturbances; (3 access to significant processing power for a regular update of the information over large areas. In this paper, we show how the operational potential of InSAR has been realized thanks to the recent advances in InSAR processing algorithms, the advent of cloud computing and the launch of new satellite platforms, specifically designed for InSAR analyses (e.g. Sentinel-1a operated by the ESA and ALOS2 operated by JAXA. The processing of thousands of SAR scenes to cover an entire nation has been performed successfully in Italy in a project financed by the Italian Ministry of the Environment. The challenge for the future is to pass from the historical analysis of SAR scenes already acquired in digital archives to a near real-time monitoring program where up to date deformation data are routinely provided to final users and decision makers.

  13. Multi-Frequency Polarimetric SAR Classification Based on Riemannian Manifold and Simultaneous Sparse Representation

    Directory of Open Access Journals (Sweden)

    Fan Yang

    2015-07-01

    Full Text Available Normally, polarimetric SAR classification is a high-dimensional nonlinear mapping problem. In the realm of pattern recognition, sparse representation is a very efficacious and powerful approach. As classical descriptors of polarimetric SAR, covariance and coherency matrices are Hermitian semidefinite and form a Riemannian manifold. Conventional Euclidean metrics are not suitable for a Riemannian manifold, and hence, normal sparse representation classification cannot be applied to polarimetric SAR directly. This paper proposes a new land cover classification approach for polarimetric SAR. There are two principal novelties in this paper. First, a Stein kernel on a Riemannian manifold instead of Euclidean metrics, combined with sparse representation, is employed for polarimetric SAR land cover classification. This approach is named Stein-sparse representation-based classification (SRC. Second, using simultaneous sparse representation and reasonable assumptions of the correlation of representation among different frequency bands, Stein-SRC is generalized to simultaneous Stein-SRC for multi-frequency polarimetric SAR classification. These classifiers are assessed using polarimetric SAR images from the Airborne Synthetic Aperture Radar (AIRSAR sensor of the Jet Propulsion Laboratory (JPL and the Electromagnetics Institute Synthetic Aperture Radar (EMISAR sensor of the Technical University of Denmark (DTU. Experiments on single-band and multi-band data both show that these approaches acquire more accurate classification results in comparison to many conventional and advanced classifiers.

  14. Six years of land subsidence in shanghai revealed by JERS-1 SAR data

    Science.gov (United States)

    Damoah-Afari, P.; Ding, X.-L.; Li, Z.; Lu, Z.; Omura, M.

    2008-01-01

    Differential interferometric synthetic aperture radar (SAR) (DInSAR) has proven to be very useful in mapping and monitoring land subsidence in many regions of the world. Shanghai, China's largest city, is one of such areas suffering from land subsidence as a result of severe withdrawal of groundwater for different usages. DInSAR application in Shanghai with the C-band European Remote Sensing 1 & 2 (ERS-1/2) SAR data has been difficult mainly due to the problem of decorrelation of InSAR pairs with temporal baselines larger than 10 months. To overcome the coherence loss of C-band InSAR data, we used eight L-band Japanese Earth Resource Satellite (JERS-1) SAR data acquired during 2 October 1992 to 15 July 1998 to study land subsidence phenomenon in Shanghai. Three of the images were used to produce two separate digital elevation models (DEMs) of the study area to remove topographic fringes from the interferograms used for subsidence mapping. Six interferograms were used to generate 2 different time series of deformation maps over Shanghai. The cumulative subsidence map generated from each of the time series is in agreement with the land subsidence measurements of Shanghai city from 1990-1998, produced from other survey methods. ?? 2007 IEEE.

  15. It counts who counts: an experimental evaluation of the importance of observer effects on spotlight count estimates

    DEFF Research Database (Denmark)

    Sunde, Peter; Jessen, Lonnie

    2013-01-01

    Spotlight surveys conducted by volunteers is a promising method to assess the abundance of nocturnally active mammals, but estimates are subject to bias if different observer groups differ in their ability to detect animals in the dark. We quantified the variation amongst volunteer spotlight...... observers with respect to their ability to detect and estimate distance to realistic animal silhouettes at different distances. Detection probabilities were higher for observers experienced in spotlighting mammals than for inexperienced observers, higher for observers with a hunting background compared...

  16. LAND COVER MAPPING USING SENTINEL-1 SAR DATA

    Directory of Open Access Journals (Sweden)

    S. Abdikan

    2016-06-01

    Full Text Available In this paper, the potential of using free-of-charge Sentinel-1 Synthetic Aperture Radar (SAR imagery for land cover mapping in urban areas is investigated. To this aim, we use dual-pol (VV+VH Interferometric Wide swath mode (IW data collected on September 16th 2015 along descending orbit over Istanbul megacity, Turkey. Data have been calibrated, terrain corrected, and filtered by a 5x5 kernel using gamma map approach. During terrain correction by using a 25m resolution SRTM DEM, SAR data has been resampled resulting into a pixel spacing of 20m. Support Vector Machines (SVM method has been implemented as a supervised pixel based image classification to classify the dataset. During the classification, different scenarios have been applied to find out the performance of Sentinel-1 data. The training and test data have been collected from high resolution image of Google Earth. Different combinations of VV and VH polarizations have been analysed and the resulting classified images have been assessed using overall classification accuracy and Kappa coefficient. Results demonstrate that, combining opportunely dual polarization data, the overall accuracy increases up to 93.28% against 73.85% and 70.74% of using individual polarization VV and VH, respectively. Our preliminary analysis points out that dual polarimetric Sentinel-1SAR data can be effectively exploited for producing accurate land cover maps, with relevant advantages for urban planning and management of large cities.

  17. SAR wind retrieval: from Singlecore to Multicore and GPU computing

    Science.gov (United States)

    Myasoedov, Alexander; Monzikova, Anna

    The large spatial coverage and high resolution of spaceborne synthetic aperture radars (SAR) offers a unique opportunity to derive mesoscale wind fields over the ocean surface, providing high resolution wind fields near the shore. On the other hand, due to the large size of SAR images their processing might be a headache when dealing with operational tasks or doing long-period statistical analysis. Algorithms for satellite image processing often offer many possibilities for parallelism (e.g., pixel-by-pixel processing) which makes them good candidates for execution on high-performance parallel computing hardware such as Multicore CPUs and modern graphic processing units (GPUs). In this study we implement different SAR wind speed retrieval algorithms (e.g. CMOD4, CMOD5) for Singlecore and Multicore systems, including GPUs. For this purpose both serial and parallelized versions of CMOD algorithms were written in Matlab, Python, CPython and PyOpenCL. We apply these algorithms to an Envisat ASAR image, compare the results received with different versions of the algorithms executed on both Intel CPU and a Tesla GPU. As a result of our experiments we not only show the up to 400 times speedup of GPU comparing to CPU but also try to give some advises on how much time we have spent and efforts were made for writing the same algorithm using different programming languages. We hope that our experience will help other scientist to achieve all the goodness from the GPU/Multicore computing.

  18. An integrated hyperspectral and SAR satellite constellation for environment monitoring

    Science.gov (United States)

    Wang, Jinnian; Ren, Fuhu; Xie, Chou; An, Jun; Tong, Zhanbo

    2017-09-01

    A fully-integrated, Hyperspectral optical and SAR (Synthetic Aperture Radar) constellation of small earth observation satellites will be deployed over multiple launches from last December to next five years. The Constellation is expected to comprise a minimum of 16 satellites (8 SAR and 8 optical ) flying in two orbital planes, with each plane consisting of four satellite pairs, equally-spaced around the orbit plane. Each pair of satellites will consist of a hyperspectral/mutispectral optical satellite and a high-resolution SAR satellite (X-band) flying in tandem. The constellation is expected to offer a number of innovative capabilities for environment monitoring. As a pre-launch experiment, two hyperspectral earth observation minisatellites, Spark 01 and 02 were launched as secondary payloads together with Tansat in December 2016 on a CZ-2D rocket. The satellites feature a wide-range hyperspectral imager. The ground resolution is 50 m, covering spectral range from visible to near infrared (420 nm - 1000 nm) and a swath width of 100km. The imager has an average spectral resolution of 5 nm with 148 channels, and a single satellite could obtain hyperspectral imagery with 2.5 million km2 per day, for global coverage every 16 days. This paper describes the potential applications of constellation image in environment monitoring.

  19. Airborne Downward Looking Sparse Linear Array 3-D SAR Heterogeneous Parallel Simulation

    Directory of Open Access Journals (Sweden)

    Yirong Wu

    2013-10-01

    Full Text Available The airborne downward looking sparse linear array three dimensional synthetic aperture radar (DLSLA 3-D SAR operates nadir observation with the along-track synthetic aperture formulated by platform movement and the cross-track synthetic aperture formulated by physical sparse linear array. Considering the lack of DLSLA 3-D SAR data in the current preliminary study stage, it is very important and essential to develop DLSLA 3-D SAR simulation (echo generation simulation and image reconstruction simulation, including point targets simulation and 3-D distributed scene simulation. In this paper, DLSLA 3-D SAR imaging geometry, the echo signal model and the heterogeneous parallel technique are discussed first. Then, heterogeneous parallel echo generation simulation with time domain correlation and the frequency domain correlation method is described. In the following, heterogeneous parallel image reconstruction simulation with two imaging algorithms, e.g., 3-D polar format algorithm, polar formatting and L1 regularization algorithm is discussed. Finally, the point targets and the 3-D distributed scene simulation are demonstrated to validate the effectiveness and performance of our proposed heterogeneous parallel simulation technique. The 3-D distributed scene employs airborne X-band DEM and P-band Circular SAR image of the same area as simulation scene input.

  20. Operational SAR-based sea ice drift monitoring over the Baltic Sea

    Directory of Open Access Journals (Sweden)

    J. Karvonen

    2012-07-01

    Full Text Available An algorithm for computing ice drift from pairs of synthetic aperture radar (SAR images covering a common area has been developed at FMI. The algorithm has been developed based on the C-band SAR data over the Baltic Sea. It is based on phase correlation in two scales (coarse and fine with some additional constraints. The algorithm has been running operationally in the Baltic Sea from the beginning of 2011, using Radarsat-1 ScanSAR wide mode and Envisat ASAR wide swath mode data. The resulting ice drift fields are publicly available as part of the MyOcean EC project. The SAR-based ice drift vectors have been compared to the drift vectors from drifter buoys in the Baltic Sea during the first operational season, and also these validation results are shown in this paper. Also some navigationally useful sea ice quantities, which can be derived from ice drift vector fields, are presented.

  1. InSAR datum connection using GNSS-augmented radar transponders

    Science.gov (United States)

    Mahapatra, Pooja; der Marel, Hans van; van Leijen, Freek; Samiei-Esfahany, Sami; Klees, Roland; Hanssen, Ramon

    2018-01-01

    Deformation estimates from Interferometric Synthetic Aperture Radar (InSAR) are relative: they form a `free' network referred to an arbitrary datum, e.g. by assuming a reference point in the image to be stable. However, some applications require `absolute' InSAR estimates, i.e. expressed in a well-defined terrestrial reference frame, e.g. to compare InSAR results with those of other techniques. We propose a methodology based on collocated InSAR and Global Navigation Satellite System (GNSS) measurements, achieved by rigidly attaching phase-stable millimetre-precision compact active radar transponders to GNSS antennas. We demonstrate this concept through a simulated example and practical case studies in the Netherlands.

  2. Forest biomass estimation from polarimetric SAR interferometry

    Energy Technology Data Exchange (ETDEWEB)

    Mette, T.

    2007-07-01

    Polarimetric SAR interferometry (Pol-InSAR) is a radar remote sensing technique that allows extracting forest heights by means of model-based inversions. Forest biomass is closely related to forest height, and can be derived from it with allometric relations. This work investigates the combination of the two methods to estimate forest biomass from Pol-InSAR. It develops a concept for the use of height-biomass allometry, and outlines the Pol-InSAR height inversion. The methodology is validated against a set of forest inventory data and Pol-InSAR data at L-band of the test site Traunstein. The results allow drawing conclusions on the potential of Pol-InSAR forest biomass missions. (orig.)

  3. Sample Extraction Bsaed on Helix Scattering for Polarimetric SAR Calibratio

    Science.gov (United States)

    Chang, Y.; Yang, J.; Li, P.; Zhao, L.; Shi, L.

    2017-09-01

    Polarimetric calibration (PolCAL) of Synthetic Aperture Radar (SAR) images is a significant preprocessing for further applications. Since the reflection symmetry property of distributed objects can provide stable constraints for PolCAL. It is reasonable to extract these reference samples before calibration. The helix scattering generally appears in complex urban area and disappears for a natural scatterer, making it a good measure to extract distributed objects. In this paper, a novel technique that extracts reflecting symmetry samples is proposed by using helix scattering. The helix scattering information is calculated by Yamaguchi four-component decomposition algorithm. An adaptive threshold selection algorithm based on generalized Gaussian distribution is also utilized to scale the helix scattering components automatically, getting rid of the problem of various numerical range. The extracting results will be taken as PolCAL reference samples and the Quegan method are utilized to calibrate these PolSAR images. A C-band airborne PolSAR data was taken as examples to evaluate its ability in improving calibration precision. Traditional method i.e. extracting samples with span power was also evaluated as contrast experiment. The results showed that the samples extracting method based on helix scattering can improve the Polcal precision preferably.

  4. 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.

  5. SAMPLE EXTRACTION BSAED ON HELIX SCATTERING FOR POLARIMETRIC SAR CALIBRATIO

    Directory of Open Access Journals (Sweden)

    Y. Chang

    2017-09-01

    Full Text Available Polarimetric calibration (PolCAL of Synthetic Aperture Radar (SAR images is a significant preprocessing for further applications. Since the reflection symmetry property of distributed objects can provide stable constraints for PolCAL. It is reasonable to extract these reference samples before calibration. The helix scattering generally appears in complex urban area and disappears for a natural scatterer, making it a good measure to extract distributed objects. In this paper, a novel technique that extracts reflecting symmetry samples is proposed by using helix scattering. The helix scattering information is calculated by Yamaguchi four-component decomposition algorithm. An adaptive threshold selection algorithm based on generalized Gaussian distribution is also utilized to scale the helix scattering components automatically, getting rid of the problem of various numerical range. The extracting results will be taken as PolCAL reference samples and the Quegan method are utilized to calibrate these PolSAR images. A C-band airborne PolSAR data was taken as examples to evaluate its ability in improving calibration precision. Traditional method i.e. extracting samples with span power was also evaluated as contrast experiment. The results showed that the samples extracting method based on helix scattering can improve the Polcal precision preferably.

  6. Tandem-L: Monitoring the Earth's Dynamics with InSAR and Pol-InSAR

    Science.gov (United States)

    Moriera, A.; Hajnsek, I.; Krieger, G.; Papathanassiou, K.; Eineder, M.; De Zan, F.; Younis, M.; Werner, M.

    2009-04-01

    Tandem-L is a German mission proposal for an innovative interferometric L-band radar mission that enables the systematic monitoring of dynamic Earth processes using advanced techniques and technologies. The mission is science driven aiming to provide a unique data set for climate and environmental research, geodynamics, hydrology and oceanography. Important application examples are global forest height and biomass inventories, measurements of Earth deformation due to tectonic processes and/or anthropogenic factors, observations of ice/glacier velocity field and 3-D structure changes, and the monitoring of ocean surface currents. The Tandem-L mission concept consists of two cooperating satellites flying in close formation. The Pol-InSAR and repeat-pass acquisition modes provide a unique data source to observe, analyse and quantify a wide range of mutually interacting processes in the bio-, litho-, hydro- and cryosphere. The systematic observation of these processes benefits from the high data acquisition capacity and the novel high-resolution wide-swath SAR imaging modes that combine digital beamforming with a large reflector antenna. This paper provides an overview of the Tandem-L mission concept and its main application areas.

  7. Deep Learning as Applied in SAR Target Recognition and Terrain Classification

    Directory of Open Access Journals (Sweden)

    Xu Feng

    2017-04-01

    Full Text Available Deep learning such as deep neural networks has revolutionized the computer vision area. Deep learning-based algorithms have surpassed conventional algorithms in terms of performance by a significant margin. This paper reviews our works in the application of deep convolutional neural networks to target recognition and terrain classification using the SAR image. A convolutional neural network is employed to automatically extract a hierarchic feature representation from the data, based on which the target recognition and terrain classification can be conducted. Experimental results on the MSTAR benchmark dataset reveal that deep convolutional network could achieve a state-of-the-art classification accuracy of 99% for the 10-class task. For a polarimetric SAR image classification, we propose complex-valued convolutional neural networks for complex SAR images. This algorithm achieved a state-of-the-art accuracy of 95% for the 15-class task on the Flevoland benchmark dataset.

  8. Channel Phase Error Compensation for MIMO-SAR

    Directory of Open Access Journals (Sweden)

    Lei Zhang

    2014-01-01

    Full Text Available Multi-input multioutput (MIMO is a novel technique to achieve high-resolution as well as wide swath in synthetic aperture radar (SAR systems. Channel imbalance is inevitable in multichannel systems that it declines the imaging quality. Generally, the imbalance cannot be fully compensated by simple internal calibration in a MIMO-SAR system. In this paper, a new algorithm based on raw data is presented to remove the channel phase error. Based on the error source, this approach models the phase error as two parts: the transmit phase error and the receive phase error. The receive phase error is removed using cost function at the azimuth processing stage, whereas the transmit phase error is estimated with correlation. Point target simulations confirm the influence of channel phase error and the validation of the proposed approach. Besides, the performance is also investigated.

  9. Estimating soil moisture using the Danish polarimetric SAR

    DEFF Research Database (Denmark)

    Jiankang, Ji; Thomsen, A.; Skriver, Henning

    1995-01-01

    The results of applying data from the Danish polarimetric SAR (EMISAR) to estimate soil moisture for bare fields are presented. Fully calibrated C-band SAR images for hh, vv and cross polarizations have been used in this study. The measured surface roughness data showed that classical roughness...... autocorrelation functions (Gaussian and Exponential) were not able to fit natural surfaces well. A Gauss-Exp hybrid model which agreed better with the measured data has been proposed. Theoretical surface scattering models (POM, IEM), as well as an empirical model for retrieval of soil moisture and surface rms...... height from coand cross-polarized ratio, have been examined, but the results are less satisfactory. As soil moisture response to backscattering coefficient σo is mainly coupled to surface roughness effect for bare fields, a bilinear model coupling volumetric soil moisture mv and surface rms height σ...

  10. Feature Fusion Based on Convolutional Neural Network for SAR ATR

    Directory of Open Access Journals (Sweden)

    Chen Shi-Qi

    2017-01-01

    Full Text Available Recent breakthroughs in algorithms related to deep convolutional neural networks (DCNN have stimulated the development of various of signal processing approaches, where the specific application of Automatic Target Recognition (ATR using Synthetic Aperture Radar (SAR data has spurred widely attention. Inspired by the more efficient distributed training such as inception architecture and residual network, a new feature fusion structure which jointly exploits all the merits of each version is proposed to reduce the data dimensions and the complexity of computation. The detailed procedure presented in this paper consists of the fused features, which make the representation of SAR images more distinguishable after the extraction of a set of features from DCNN, followed by a trainable classifier. In particular, the obtained results on the 10-class benchmark data set demonstrate that the presented architecture can achieve remarkable classification performance to the current state-of-the-art methods.

  11. EMISAR: A Dual-frequency, Polarimetric Airborne SAR

    DEFF Research Database (Denmark)

    Dall, Jørgen; Christensen, Erik Lintz

    2002-01-01

    . The SAR is operated at high altitudes on a Gulfstream G-3 jet aircraft. The system is very well calibrated and has low sidelobes and low cross-polar contamination. Digital technology has been utilized to realize a flexible and highly stable radar with variable resolution, swath width, and imaging geometry....... Thermal control and several calibration loops have been built into the system to ensure system stability and absolute calibration. Accurately measured antenna gains and radiation patterns are included in the calibration. The processing system is developed to support data calibration, which is the key......EMISAR is a fully polarimetric, dual frequency (L- and C-band) SAR system designed for remote sensing applications. The data are usually processed to 2×2 m resolution. The system has the capability of C-band cross-track single-pass interferometry and fully polarimetric repeat-pass interferometry...

  12. Robustness of Spann-Wilson segmentation on SAR imagery

    Science.gov (United States)

    Daida, Jason M.; Vesecky, John F.

    1992-01-01

    The performances of the Spann-Wilson algorithm on simulated synthetic aperture radar (SAR) images with varying degrees of speckle (one to four looks and varying amounts of white noise) is described. One hundred forty-eight test images are considered, of which the algorithm segmented most without any adjustment to the algorithm's parameters. The effect of speckle on fractal boundaries is studied. The effect of varying multiplicative and additive noise distributions for a fixed set of segmentation parameters is examined. The modified Spann-Wilson algorithm on four-look imagery is evaluated.

  13. Phase History Decomposition for efficient Scatterer Classification in SAR Imagery

    Science.gov (United States)

    2011-09-15

    96] Liu, Qi, Yun Lin , Weixian Tan, Yanping Wang, Wen Hong, and Yirong Wu. “Study on SAR image formation for aspect-dependent scatterers”. Asian Pacific...Antennas and Prop., 55(9):2610–2617, 2007. [28] Chen, V.C. and H. Ling . Time-frequency transforms for radar imaging and signal analysis. Artech House...Sens., 45(12):4043 –4058, Dec. 2007. [118] Perlovsky, L., R. Ilin, R. Deming, R. Linnehan, and F. Lin . “Moving target detection and characterization with

  14. Mars Mission Concepts: SAR and Solar Electric Propulsion

    Science.gov (United States)

    Elsperman, M.; Klaus, K.; Smith, D. B.; Clifford, S. M.; Lawrence, S. J.

    2012-12-01

    Introduction: The time has come to leverage technology advances (including advances in autonomous operation and propulsion technology) to reduce the cost and increase the flight rate of planetary missions, while actively developing a scientific and engineering workforce to achieve national space objectives. Mission Science at Mars: A SAR imaging radar offers an ability to conduct high resolution investigations of the shallow (system would enable the generation of false color images, resulting in useful science results, and the stereo data could be reduced into high-resolution Digital Elevation Models uniquely useful for exploration planning and science purposes. Since the SAR and the notional high-resolution stereo imaging system would be huge data volume producers - to maximize the science return we are currently considering the usage of laser communications systems; this notional spacecraft represents one pathway to evaluate the utility of laser communications in planetary exploration while providing useful science return.. Mission Concept: Using a common space craft for multiple missions reduces costs. Solar electric propulsion (SEP) provides the flexibility required for multiple mission objectives. SEP provides the greatest payload advantage albeit at the sacrifice of mission time. Our concept involves using a SEP enabled space craft (Boeing 702SP) with a highly capable SAR imager that also conducts autonomous rendezvous and docking experiments accomplished from Mars orbit. Our concept of operations is to launch on May 5, 2018 using a launch vehicle with 2000kg launch capacity with a C3 of 7.4. After reaching Mars it takes 145 days to spiral down to a 250 km orbit above the surface of Mars when Mars SAR operations begin. Summary/Conclusions: A robust and compelling Mars mission can be designed to meet the 2018 Mars launch window opportunity. Using advanced in-space power and propulsion technologies like High Power Solar Electric Propulsion provides enormous

  15. InfoTerra/TerraSAR initiative

    Science.gov (United States)

    Wahl, Manfred W.

    2004-01-01

    The overarching goal of the InfoTerra/TerraSAR Initiative is to establish a self-sustaining operational/commercial business built on Europe"s know-how and experience in space-borne Synthetic Aperture Radar (SAR) technology, in SAR data processing as well as in SAR applications. InfoTerra stands for a new business concept based on supplying innovative geo-information products and services. TerraSAR is a space and ground system conceived to consist of an initial deployment and operation of 2 Radar satellites (one in X- and one in L-band) flying in a tandem configuration in the same orbit. The design of TerraSAR is driven by the market and is user-oriented. TerraSAR is key to capturing a significant proportion of the existing market and to opening new market opportunities, when it becomes operational. The InfoTerra/TerraSAR Initiative has evolved gradually. It started in 1997 as a joint venture between German (DSS) and British (MMS-UK) space industry, strongly supported by both space agencies, DLR and BNSC. In early 2001, DLR and BNSC submitted to ESA the Formal Programme Proposal for InfoTerra/TerraSAR to become an essential element of ESA"s Earth Watch Programme. In summer 2001, when it became evident that there was not yet sufficient support from the ESA Member States to allow immediate start entering into TerraSAR Phase C/D, it has been decided to implement first a TerraSAR consolidation phase. In early 2002, in order to avoid further delays, a contract was signed between DLR and Astrium GmbH on the development of one component of TerraSAR, the TerraSAR-X, in the frame of a national programme, governed by a Public Private Partnership Agreement. Even if now the different launch dates for TerraSAR-X and TerraSAR-L are narrowing down the window of common data acquisition, it is a reasonable starting point, but it should always be kept in mind that the utmost goal for the longterm is to achieve self sustainability by supplying geo-information products and services

  16. Basic to Advanced InSAR Processing: GMTSAR

    Science.gov (United States)

    Sandwell, D. T.; Xu, X.; Baker, S.; Hogrelius, A.; Mellors, R. J.; Tong, X.; Wei, M.; Wessel, P.

    2017-12-01

    Monitoring crustal deformation using InSAR is becoming a standard technique for the science and application communities. Optimal use of the new data streams from Sentinel-1 and NISAR will require open software tools as well as education on the strengths and limitations of the InSAR methods. Over the past decade we have developed freely available, open-source software for processing InSAR data. The software relies on the Generic Mapping Tools (GMT) for the back-end data analysis and display and is thus called GMTSAR. With startup funding from NSF, we accelerated the development of GMTSAR to include more satellite data sources and provide better integration and distribution with GMT. In addition, with support from UNAVCO we have offered 6 GMTSAR short courses to educate mostly novice InSAR users. Currently, the software is used by hundreds of scientists and engineers around the world to study deformation at more than 4300 different sites. The most challenging aspect of the recent software development was the transition from image alignment using the cross-correlation method to a completely new alignment algorithm that uses only the precise orbital information to geometrically align images to an accuracy of better than 7 cm. This development was needed to process a new data type that is being acquired by the Sentinel-1A/B satellites. This combination of software and open data is transforming radar interferometry from a research tool into a fully operational time series analysis tool. Over the next 5 years we are planning to continue to broaden the user base through: improved software delivery methods; code hardening; better integration with data archives; support for high level products being developed for NISAR; and continued education and outreach.

  17. 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.

  18. 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

  19. Real-time brute force SAR processing

    NARCIS (Netherlands)

    Vlothuizen, W.J.; Ditzel, M.

    2009-01-01

    This paper presents a brute force method to perform real-time SAR processing. The method has several advantages over traditional so-called fast SAR implementations, as it does not make any approximations to alleviate the processing burden. However, the method does allow efficient implementation on

  20. Application of spaceborne SAR data to uranium metallogenetic environment, condition and prognosis

    International Nuclear Information System (INIS)

    Huang Xianfang; Huang Shutao; Dong Wenming; Pan Wei; Fang Maolong; Xuan Yanxiu

    2001-01-01

    JERS-1 SAR data processing and data fusion with TM, airborne radioactive and magnetic survey data have been elaborated and image effects have been described in the paper. By means of the analysis of the processed images, the stratigraphy, structures (including faults and folds) and ore-controlling factors in the study area have successfully been interpreted; the underground water mobile characteristics have been discussed; and the metallogenetic environment and condition have been summarized. Based on above research results, the prospecting criteria have been provided and favorable sections have been suggested. The practice has indicated that the application of spaceborne SAR data to uranium reconnaissance and exploration has potential prospects

  1. Building Damage Estimation by Integration of Seismic Intensity Information and Satellite L-band SAR Imagery

    Directory of Open Access Journals (Sweden)

    Nobuoto Nojima

    2010-09-01

    Full Text Available For a quick and stable estimation of earthquake damaged buildings worldwide, using Phased Array type L-band Synthetic Aperture Radar (PALSAR loaded on the Advanced Land Observing Satellite (ALOS satellite, a model combining the usage of satellite synthetic aperture radar (SAR imagery and Japan Meteorological Agency (JMA-scale seismic intensity is proposed. In order to expand the existing C-band SAR based damage estimation model into L-band SAR, this paper rebuilds a likelihood function for severe damage ratio, on the basis of dataset from Japanese Earth Resource Satellite-1 (JERS-1/SAR (L-band SAR images observed during the 1995 Kobe earthquake and its detailed ground truth data. The model which integrates the fragility functions of building damage in terms of seismic intensity and the proposed likelihood function is then applied to PALSAR images taken over the areas affected by the 2007 earthquake in Pisco, Peru. The accuracy of the proposed damage estimation model is examined by comparing the results of the analyses with field investigations and/or interpretation of high-resolution satellite images.

  2. Mixture Statistical Distribution Based Multiple Component Model for Target Detection in High Resolution SAR Imagery

    Directory of Open Access Journals (Sweden)

    Chu He

    2017-11-01

    Full Text Available This paper proposes an innovative Mixture Statistical Distribution Based Multiple Component (MSDMC model for target detection in high spatial resolution Synthetic Aperture Radar (SAR images. Traditional detection algorithms usually ignore the spatial relationship among the target’s components. In the presented method, however, both the structural information and the statistical distribution are considered to better recognize the target. Firstly, the method based on compressed sensing reconstruction is used to recover the SAR image. Then, the multiple component model composed of a root filter and some corresponding part filters is applied to describe the structural information of the target. In the following step, mixture statistical distributions are utilised to discriminate the target from the background, and the Method of Logarithmic Cumulants (MoLC based Expectation Maximization (EM approach is adopted to estimate the parameters of the mixture statistical distribution model, which will be finally merged into the proposed MSDMC framework together with the multiple component model. In the experiment, the aeroplanes and the electrical power towers in TerraSAR-X SAR images are detected at three spatial resolutions. The results indicate that the presented MSDMC Model has potential for improving the detection performance compared with the state-of-the-art SAR target detection methods.

  3. Detecting Landscape Disturbance at the Nasca Lines Using SAR Data Collected from Airborne and Satellite Platforms

    Directory of Open Access Journals (Sweden)

    Douglas C. Comer

    2017-10-01

    Full Text Available We used synthetic aperture radar (SAR data collected over Peru’s Lines and Geoglyphs of the Nasca and Palpa World Heritage Site to detect and measure landscape disturbance threatening world-renowned archaeological features and ecosystems. We employed algorithms to calculate correlations between pairs of SAR returns, collected at different times, and generate correlation images. Landscape disturbances even on the scale of pedestrian travel are discernible in correlation images generated from airborne, L-band SAR. Correlation images derived from C-band SAR data collected by the European Space Agency’s Sentinel-1 satellites also provide detailed landscape change information. Because the two Sentinel-1 satellites together have a repeat pass interval that can be as short as six days, products derived from their data can not only provide information on the location and degree of ground disturbance, but also identify a time window of about one to three weeks during which disturbance must have occurred. For Sentinel-1, this does not depend on collecting data in fine-beam modes, which generally sacrifice the size of the area covered for a higher spatial resolution. We also report on pixel value stretching for a visual analysis of SAR data, quantitative assessment of landscape disturbance, and statistical testing for significant landscape change.

  4. Assessment of GF-3 Polarimetric SAR Data for Physical Scattering Mechanism Analysis and Terrain Classification.

    Science.gov (United States)

    Yin, Junjun; Yang, Jian; Zhang, Qingjun

    2017-12-01

    On 10 August 2016 China launched the GF-3, its first C-band polarimetric synthetic aperture radar (SAR) satellite, which was put into operation at the end of January, 2017. GF-3 polarimetric SAR has many advantages such as high resolution and multi-polarization imaging capabilities. Polarimetric SAR can fully characterize the backscatter property of targets, and thus it is of great interest to explore the physical scattering mechanisms of terrain types, which is very important in interpreting polarimetric SAR imagery and for its further usages in Earth observations. In this paper, focusing on target scattering characterization and feature extraction, we generalize the Δ α B / α B method, which was proposed under the reflection symmetric assumption, for the general backscatter process to account for both the reflection symmetry and asymmetry cases. Then, we evaluate the performances of physical scattering mechanism analysis methods for GF-3 polarimetric SAR imagery. Radarsat-2 data acquired over the same area is used for cross validation. Results show that GF-3 polarimetric SAR data has great potential for target characterization, especially for ocean area observation.

  5. Mapping Forest Height in Gabon Using UAVSAR Multi-Baseline Polarimetric SAR Interferometry and Lidar Fusion

    Science.gov (United States)

    Simard, M.; Denbina, M. W.

    2017-12-01

    Using data collected by NASA's Uninhabited Aerial Vehicle Synthetic Aperture Radar (UAVSAR) and Land, Vegetation, and Ice Sensor (LVIS) lidar, we have estimated forest canopy height for a number of study areas in the country of Gabon using a new machine learning data fusion approach. Using multi-baseline polarimetric synthetic aperture radar interferometry (PolInSAR) data collected by UAVSAR, forest heights can be estimated using the random volume over ground model. In the case of multi-baseline UAVSAR data consisting of many repeat passes with spatially separated flight tracks, we can estimate different forest height values for each different image pair, or baseline. In order to choose the best forest height estimate for each pixel, the baselines must be selected or ranked, taking care to avoid baselines with unsuitable spatial separation, or severe temporal decorrelation effects. The current baseline selection algorithms in the literature use basic quality metrics derived from the PolInSAR data which are not necessarily indicative of the true height accuracy in all cases. We have developed a new data fusion technique which treats PolInSAR baseline selection as a supervised classification problem, where the classifier is trained using a sparse sampling of lidar data within the PolInSAR coverage area. The classifier uses a large variety of PolInSAR-derived features as input, including radar backscatter as well as features based on the PolInSAR coherence region shape and the PolInSAR complex coherences. The resulting data fusion method produces forest height estimates which are more accurate than a purely radar-based approach, while having a larger coverage area than the input lidar training data, combining some of the strengths of each sensor. The technique demonstrates the strong potential for forest canopy height and above-ground biomass mapping using fusion of PolInSAR with data from future spaceborne lidar missions such as the upcoming Global Ecosystems

  6. Comparison of four moderate-size earthquakes in southern California using seismology and InSAR

    Science.gov (United States)

    Mellors, R.J.; Magistrale, H.; Earle, P.; Cogbill, A.H.

    2004-01-01

    Source parameters determined from interferometric synthetic aperture radar (InSAR) measurements and from seismic data are compared from four moderate-size (less than M 6) earthquakes in southern California. The goal is to verify approximate detection capabilities of InSAR, assess differences in the results, and test how the two results can be reconciled. First, we calculated the expected surface deformation from all earthquakes greater than magnitude 4 in areas with available InSAR data (347 events). A search for deformation from the events in the interferograms yielded four possible events with magnitudes less than 6. The search for deformation was based on a visual inspection as well as cross-correlation in two dimensions between the measured signal and the expected signal. A grid-search algorithm was then used to estimate focal mechanism and depth from the InSAR data. The results were compared with locations and focal mechanisms from published catalogs. An independent relocation using seismic data was also performed. The seismic locations fell within the area of the expected rupture zone for the three events that show clear surface deformation. Therefore, the technique shows the capability to resolve locations with high accuracy and is applicable worldwide. The depths determined by InSAR agree with well-constrained seismic locations determined in a 3D velocity model. Depth control for well-imaged shallow events using InSAR data is good, and better than the seismic constraints in some cases. A major difficulty for InSAR analysis is the poor temporal coverage of InSAR data, which may make it impossible to distinguish deformation due to different earthquakes at the same location.

  7. 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

  8. Cameras instead of sieves for aggregate characterization : research spotlight

    Science.gov (United States)

    2012-01-01

    Michigan researchers explored the use of cameras and software that may eventually replace the use of screen sieves in sizing and assessing crushed aggregate for pavement construction. This research explored approaches to imaging aggregate as a way to...

  9. Constraints on the geomorphological evolution of the nested summit craters of Láscar volcano from high spatio-temporal resolution TerraSAR-X interferometry

    Science.gov (United States)

    Richter, Nicole; Salzer, Jacqueline Tema; de Zeeuw-van Dalfsen, Elske; Perissin, Daniele; Walter, Thomas R.

    2018-03-01

    Small-scale geomorphological changes that are associated with the formation, development, and activity of volcanic craters and eruptive vents are often challenging to characterize, as they may occur slowly over time, can be spatially localized, and difficult, or dangerous, to access. Using high-spatial and high-temporal resolution synthetic aperture radar (SAR) imagery collected by the German TerraSAR-X (TSX) satellite in SpotLight mode in combination with precise topographic data as derived from Pléiades-1A satellite data, we investigate the surface deformation within the nested summit crater system of Láscar volcano, Chile, the most active volcano of the central Andes. Our aim is to better understand the structural evolution of the three craters that comprise this system, to assess their physical state and dynamic behavior, and to link this to eruptive activity and associated hazards. Using multi-temporal SAR interferometry (MT-InSAR) from ascending and descending orbital geometries, we retrieve the vertical and east-west components of the displacement field. This time series indicates constant rates of subsidence and asymmetric horizontal displacements of all summit craters between June 2012 and July 2014, as well as between January 2015 and March 2017. The vertical and horizontal movements that we observe in the central crater are particularly complex and cannot be explained by any single crater formation mechanism; rather, we suggest that short-term activities superimposed on a combination of ongoing crater evolution processes, including gravitational slumping, cooling and compaction of eruption products, as well as possible piston-like subsidence, are responsible for the small-scale geomorphological changes apparent in our data. Our results demonstrate how high-temporal resolution synthetic aperture radar interferometry (InSAR) time series can add constraints on the geomorphological evolution and structural dynamics of active crater and vent systems at

  10. Ocean Wave Parameters Retrieval from Sentinel-1 SAR Imagery

    Directory of Open Access Journals (Sweden)

    Weizeng Shao

    2016-08-01

    Full Text Available In this paper, a semi-empirical algorithm for significant wave height (Hs and mean wave period (Tmw retrieval from C-band VV-polarization Sentinel-1 synthetic aperture radar (SAR imagery is presented. We develop a semi-empirical function for Hs retrieval, which describes the relation between Hs and cutoff wavelength, radar incidence angle, and wave propagation direction relative to radar look direction. Additionally, Tmw can be also calculated through Hs and cutoff wavelength by using another empirical function. We collected 106 C-band stripmap mode Sentinel-1 SAR images in VV-polarization and wave measurements from in situ buoys. There are a total of 150 matchup points. We used 93 matchups to tune the coefficients of the semi-empirical algorithm and the rest 57 matchups for validation. The comparison shows a 0.69 m root mean square error (RMSE of Hs with a 18.6% of scatter index (SI and 1.98 s RMSE of Tmw with a 24.8% of SI. Results indicate that the algorithm is suitable for wave parameters retrieval from Sentinel-1 SAR data.

  11. Snowpack permittivity profile retrieval from tomographic SAR data

    Science.gov (United States)

    Rekioua, Badreddine; Davy, Matthieu; Ferro-Famil, Laurent; Tebaldini, Stefano

    2017-01-01

    This work deals with 3D structure characterization and permittivity profile retrieval of snowpacks by tomographic SAR data processing. The acquisition system is a very high resolution ground based SAR system, developed and operated by the SAPHIR team, of IETR, University of Rennes-1 (France). It consists mainly of a vector network analyser and a multi-static antenna system, moving along two orthogonal directions, so as to obtain a two-dimensional synthetic array. Data were acquired during the AlpSAR campaign carried by the European Space Agency and led by ENVEO. In this study, tomographic imaging is performed using Time Domain Back Projection and consists in coherently combining the different recorded backscatter contributions. The assumption of free-space propagation during the focusing process is discussed and illustrated by focusing experimental data. An iterative method for estimating true refractive indices of the snow layers is presented. The antenna pattern is also compensated for. The obtained tomograms after refractive index correction are compared to the stratigraphy of the observed snowpack.

  12. MRI investigation on steroid induced osteo-ischemia of SARS

    International Nuclear Information System (INIS)

    Wang Wu; Zhang Xuezhe; Lu Yan; Li Zirong; Lin Peng; Huang Zhenguo; Hong Wen; Ren An; Shang Yanning

    2004-01-01

    Objective: To investigate the steroid induced osteo-ischemia of recovered SARS with MRI. Methods: 38 studies of MRI were performed on hips, lower limbs, shoulders, and lumbar vertebrae in 23 SARS patients treated with steroid. Hip X-ray was conducted in 7 of the 23 cases. Results: MRI: (1) Avascular osteonecrosis was found in 31 places, including 28 femoral heads (stage I 16, stage II 8, stage III 4 ), 1 tibial plateau, and 2 humerus capita; (2) Osteo-infarction was detected in multiple sites (bilateral femora, tibiae, calcaneus, and tali) in a severe case (also had osteonecrosis of bilateral femoral heads and left humerus capita). (3) Bone marrow edema was seen in 48 places, including 43 hips, 3 tibial plateaus, and 2 humerus capita. (4) Joint fluid was found in 16 hips and 9 knees. No positive finding was detected in X-ray. Conclusion: The steroid induced osteo-ischemia is frequent in SARS. The image follow-up is needed

  13. SAR wavefront reconstruction using motion-compensated phase history (polar format) data and DPCA-based GMTI

    Science.gov (United States)

    Soumekh, Mehrdad; Worrell, Steven W.; Zelnio, Edmund G.; Keaffaber, Brett L.

    2000-08-01

    This paper address the problem of processing an X-band SAR database that was originally intended for processing via a polar format imaging algorithm. In our approach, we use the approximation-free SAR wavefront reconstruction. For this, the measured and motion compensated phase history (polar format) data are processed in a multi-dimensional digital signal processing algorithm that yields alias-free slow-time samples. The resultant database is used for wavefront image formation. The X-band SAR system also provides a two channel along-track monopulse database. The alias-free monopulse SAR data are used in a coherent signal subspace algorithm for Ground Moving Target Indication (GMTI). Results are provided.

  14. A Method of SAR Target Recognition Based on Gabor Filter and Local Texture Feature Extraction

    Directory of Open Access Journals (Sweden)

    Wang Lu

    2015-12-01

    Full Text Available This paper presents a novel texture feature extraction method based on a Gabor filter and Three-Patch Local Binary Patterns (TPLBP for Synthetic Aperture Rader (SAR target recognition. First, SAR images are processed by a Gabor filter in different directions to enhance the significant features of the targets and their shadows. Then, the effective local texture features based on the Gabor filtered images are extracted by TPLBP. This not only overcomes the shortcoming of Local Binary Patterns (LBP, which cannot describe texture features for large scale neighborhoods, but also maintains the rotation invariant characteristic which alleviates the impact of the direction variations of SAR targets on recognition performance. Finally, we use an Extreme Learning Machine (ELM classifier and extract the texture features. The experimental results of MSTAR database demonstrate the effectiveness of the proposed method.

  15. What is missing? An operational inundation mapping framework by SAR data

    Science.gov (United States)

    Shen, X.; Anagnostou, E. N.; Zeng, Z.; Kettner, A.; Hong, Y.

    2017-12-01

    Compared to optical sensors, synthetic aperture radar (SAR) works all-day all-weather. In addition, its spatial resolution does not decrease with the height of the platform and is thus applicable to a range of important studies. However, existing studies did not address the operational demands of real-time inundation mapping. The direct proof is that no water body product exists for any SAR-based satellites. Then what is missing between science and products? Automation and quality. What makes it so difficult to develop an operational inundation mapping technique based on SAR data? Spectrum-wise, unlike optical water indices such as MNDWI, AWEI etc., where a relative constant threshold may apply across acquisition of images, regions and sensors, the threshold to separate water from non-water pixels in each SAR images has to be individually chosen. The optimization of the threshold is the first obstacle to the automation of the SAR data algorithm. Morphologically, the quality and reliability of the results have been compromised by over-detection caused by smooth surface and shadowing area, the noise-like speckle and under-detection caused by strong-scatter disturbance. In this study, we propose a three-step framework that addresses all aforementioned issues of operational inundation mapping by SAR data. The framework consists of 1) optimization of Wishart distribution parameters of single/dual/fully-polarized SAR data, 2) morphological removal of over-detection, and 3) machine-learning based removal of under-detection. The framework utilizes not only the SAR data, but also the synergy of digital elevation model (DEM), and optical sensor-based products of fine resolution, including the water probability map, land cover classification map (optional), and river width. The framework has been validated throughout multiple areas in different parts of the world using different satellite SAR data and globally available ancillary data products. Therefore, it has the potential

  16. 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.

  17. Integrating polarimetric synthetic aperture radar and imaging spectrometry for wildland fuel mapping in southern California

    Science.gov (United States)

    P.E. Dennison; D.A. Roberts; J. Regelbrugge; S.L. Ustin

    2000-01-01

    Polarimetric synthetic aperture radar (SAR) and imaging spectrometry exemplify advanced technologies for mapping wildland fuels in chaparral ecosystems. In this study, we explore the potential of integrating polarimetric SAR and imaging spectrometry for mapping wildland fuels. P-band SAR and ratios containing P-band polarizations are sensitive to variations in stand...

  18. Processing PHARUS Data with the Generic SAR Processor

    NARCIS (Netherlands)

    Otten, M.P.G.

    1996-01-01

    The Generic SAR Processor (GSP) is a SAR processing environment created to process airborne and spaceborne SAR data with a maximum amount of flexibility, while at the same time providing a user friendly and powerful environment for handling and analyzing SAR, including polarimetric calibiation.

  19. 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

  20. Sensor-Oriented Path Planning for Multiregion Surveillance with a Single Lightweight UAV SAR

    Science.gov (United States)

    Li, Jincheng; Chen, Jie; Wang, Pengbo; Li, Chunsheng

    2018-01-01

    In the surveillance of interested regions by unmanned aerial vehicle (UAV), system performance relies greatly on the motion control strategy of the UAV and the operation characteristics of the onboard sensors. This paper investigates the 2D path planning problem for the lightweight UAV synthetic aperture radar (SAR) system in an environment of multiple regions of interest (ROIs), the sizes of which are comparable to the radar swath width. Taking into account the special requirements of the SAR system on the motion of the platform, we model path planning for UAV SAR as a constrained multiobjective optimization problem (MOP). Based on the fact that the UAV route can be designed in the map image, an image-based path planner is proposed in this paper. First, the neighboring ROIs are merged by the morphological operation. Then, the parts of routes for data collection of the ROIs can be located according to the geometric features of the ROIs and the observation geometry of UAV SAR. Lastly, the route segments for ROIs surveillance are connected by a path planning algorithm named the sampling-based sparse A* search (SSAS) algorithm. Simulation experiments in real scenarios demonstrate that the proposed sensor-oriented path planner can improve the reconnaissance performance of lightweight UAV SAR greatly compared with the conventional zigzag path planner. PMID:29439447