Ground Moving Targets Imaging Algorithm for Synthetic Aperture Radar

Zhu, Shengqi; Liao, Guisheng; Qu, Yi; Zhou, Ziheng; Liu, Xiangyang

doi:10.1109/tgrs.2010.2053848

Cited by 174 publications

(109 citation statements)

References 44 publications

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“…In particular, a number of researchers [1][2][3][4] investigate the general features of mover smears. Other researchers [5][6][7][8][9][10][11][12][13][14][15][16][17] examine the detection and focusing of moving target signatures. Additional researchers [18][19][20][21][22][23] analyze techniques for improving the detection and estimation of moving targets in SAR imagery.…”

Section: Introductionmentioning

confidence: 99%

Insights into the complicated SAR signature shapes induced by braking targets

Garren

2018

Algorithms for Synthetic Aperture Radar Imagery XXV

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This investigation considers the shapes of synthetic aperture radar (SAR) imagery signature smears that are caused by surface targets that perform braking maneuvers during the SAR collection time. It is known that such maneuvering target signatures can have a wide variety of two-dimensional (2D) shapes, as opposed to the simpler parabolic signatures that are induced by constant velocity targets. The current paper examines the theoretical properties of these 2D signature shapes for cases in which the specific parameters of the target braking maneuver temporal profile are varied, including the rate at which the target decreases speed, the total amount of speed change, and the speed transition time within the SAR collection interval. Furthermore, the current investigation yields new insights regarding the complicated SAR signature shapes that are indicative of targets undergoing such braking maneuvers. This analysis reveals that the SAR signature for a given braking target is effectively a composite of three curved smear portions. One portion is a part of a parabola that is obtained from the constant-velocity target motion at the initial SAR collection time. Next, the second portion is that of a part of a different parabola that is generated from the final constant target velocity segment during the SAR collection interval. The third curved portion of the full moving target signature forms a connection between the parts of the two parabolas that are due to the initial and final constant velocity segments of the full target motion during the SAR measurement interval.

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Section: Introductionmentioning

confidence: 99%

Insights into the complicated SAR signature shapes induced by braking targets

Garren

2018

Algorithms for Synthetic Aperture Radar Imagery XXV

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“…(1) Methods based on the raw radar data [8][9][10][11][12]. These methods deal with the entire echo data reflected from both stationary background and moving targets.…”

Section: Introductionmentioning

confidence: 99%

Refocusing of Moving Targets in SAR Images via Parametric Sparse Representation

Chen

Zhang

et al. 2017

Remote Sensing

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Abstract:In this paper, a parametric sparse representation (PSR) method is proposed for refocusing of moving targets in synthetic aperture radar (SAR) images. In regular SAR images, moving targets are defocused due to unknown motion parameters. Refocusing of moving targets requires accurate phase compensation of echo data. In the proposed method, the region of interest (ROI) data containing the moving targets are extracted from the complex SAR image and represented in a sparse fashion through a parametric transform, which is related to the phase compensation parameter. By updating the reflectivities of moving target scatterers and the parametric transform in an iterative fashion, the phase compensation parameter can be accurately estimated and the SAR images of moving targets can be refocused well. The proposed method directly operates on small-size defocused ROI data, which helps to reduce the computational burden and suppress the clutter. Compared to other existing ROI-based methods, the proposed method can suppress asymmetric side-lobes and improve the image quality. Both simulated data and real SAR data collected by GF-3 satellite are used to validate the effectiveness of the proposed method.

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“…Many methods have been presented in the literature to address the problem of SAR imaging of ground moving targets (SAR/GMTI). [1][2][3][4][5][6][7][8][9][10] The advantages of SAR and GMTI radar complement each other well: the image formation process can be used to help detect moving targets, and the target detection process can be used to help focus the image.…”

Section: Introductionmentioning

confidence: 99%

Passive synthetic aperture radar imaging of ground moving targets

Wacks

Yazıcı

2012

SPIE Proceedings

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In this paper we present a method for imaging ground moving targets using passive synthetic aperture radar. A passive radar imaging system uses small, mobile receivers that do not radiate any energy. For these reasons, passive imaging systems result in significant cost, manufacturing, and stealth advantages. The received signals are obtained by multiple airborne receivers collecting scattered waves due to illuminating sources of opportunity such as commercial television, radio, and cell phone towers. We describe a novel forward model and a corresponding filtered-backprojection type image reconstruction method combined with entropy optimization. Our method determines the location and velocity of multiple targets moving at different velocities. Furthermore, it can accommodate arbitrary imaging geometries. we present numerical simulations to verify the imaging method.

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Ground Moving Targets Imaging Algorithm for Synthetic Aperture Radar

Cited by 174 publications

References 44 publications

Insights into the complicated SAR signature shapes induced by braking targets

Insights into the complicated SAR signature shapes induced by braking targets

Refocusing of Moving Targets in SAR Images via Parametric Sparse Representation

Passive synthetic aperture radar imaging of ground moving targets

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