Optimum SAR/GMTI Processing and Its Application to the Radar Satellite RADARSAT-2 for Traffic Monitoring

Cerutti-Maori, Delphine; Sikaneta, Ishuwa; Gierull, Christoph H.

doi:10.1109/tgrs.2012.2186637

Cited by 158 publications

(87 citation statements)

References 15 publications

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“…Since the scope of the paper is to demonstrate the improved capabilities of the proposed configuration against current state-of-the-art SAR-GMTI missions, the clutter is assumed to have a stationary zero-mean complex Gaussian distribution c (ϑ c ) ∈ C ∼ N (0, R c ), as it is extendedly considered in the literature [16], [18], [19]. This hypothesis breaks down when considering realistic scenarios that may contain highly heterogeneous terrains, such as urban or industrial areas [13].…”

Section: B Interferencementioning

confidence: 99%

“…Therefore, for the main non-ambiguous clutter patch, a grid of N surrounding ambiguous clutter responses should be also considered when modeling the clutter [14], [18], [25]. Assuming a homogeneous (stationary) complex Gaussian sea clutter surface and uncorrelated ambiguities, the interference covariance matrix can be expressed as:…”

Section: B Interferencementioning

confidence: 99%

“…The objective is to provide subclutter visibility for maritime surveillance of small slowly moving boats. This optimized multichannel configuration, in combination with the new optimum GMTI processing techniques as imaging STAP (ISTAP) and extended DPCA (EDPCA), is expected to provide a substantial improvement in SAR-GMTI performance, [18]- [19].…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

A Performance Evaluation of SAR-GMTI Missions for Maritime Applications

Makhoul

Broquetas

Rodon

et al. 2015

IEEE Trans. Geosci. Remote Sensing

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Abstract-This paper proposes a new optimized multichannel synthetic aperture radar (SAR) configuration, based on receiving antennas with non-uniformly displaced phase centers, intended for ground moving target indication (GMTI) applications over maritime scenarios. This system is compared with current SAR missions, such as TerraSAR-X (TSX) or TanDEM-X (TDX). The GMTI capabilities of the different configurations are analyzed in a two-level performance approach. First, an intensive numerical simulation evaluation, based on Monte Carlo (MC) trials, is carried out in order to characterize the probabilities of detection under different system parameters as well as scenario conditions. Different GMTI techniques, displaced phase center antenna (DPCA), along-track interferometry (ATI) and extended displaced phase center antenna (EDPCA), are assessed. In a second step, synthetic simulated SAR data, obtained in a study case scenario, is used to demonstrate the potential improvement of the proposed multichannel configuration compared to current SAR missions, providing subclutter visibility for maritime surveillance of small and slowly moving boats.Index Terms-Synthetic aperture radar (SAR), ground moving target indication (GMTI), displaced phase center antenna (DPCA), along-track interferometry (ATI), extended DPCA (ED-PCA), constant false alarm rate (CFAR) detector, Monte Carlo (MC) simulations, SAR raw data simulation.

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Section: B Interferencementioning

confidence: 99%

Section: B Interferencementioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

A Performance Evaluation of SAR-GMTI Missions for Maritime Applications

Makhoul

Broquetas

Rodon

et al. 2015

IEEE Trans. Geosci. Remote Sensing

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“…현재 민수와 방위사업의 다양한 분야에서 지상이동표 적을 관측하고자 하는 수요가 늘어나면서 SAR 시스템에 ground moving target indication (GMTI) 기능을 접목시킨 SAR-GMTI 시스템이 주목을 받고 있다 [1], [2] . SAR-GMTI 시스템에서는 정지된 지형 이미징 외에 지 상이동 표적의 속도로 인한 SAR 영상의 왜곡을 보상하기 위해 표적의 속도를 정확히 추정하는 것이 중요한 과제 로 여겨지고 있다.…”

Section: ⅰ 서 론unclassified

Ground Moving Target’s Velocity Estimation in SAR-GMTI

Bae¹,

Jeon²,

Yang³

et al. 2017

J. Korean Inst. Electromagn. Eng. Sci.

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A ground moving target's velocity estimation algorithm applicable for a SAR-GMTI system using 2 channel displaced phase center antenna(DPCA) is proposed. In this algorithm, we assume target's across-track velocity can be estimated by along-track interferometry (ATI) and present a method to estimate target's along-track velocity. To accomplish this method, we first transform a radar-target geometry in which a moving target has zero velocity via altering a radar velocity such that target's velocity is reflected into it and next manipulate the spectral centers of the subapertures within the synthetic aperture. The validity of the proposed algorithm is demonstrated through simulation results showing the performance of the target's velocity estimation and the enhancement of reconstructed target image quality in terms of resolution and SINR.

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“…[1], [2]). Compared to other GMTI systems, SAR sensors have the great advantage of detecting moving objects while simultaneously imaging the area of interest.…”

Section: Introductionmentioning

confidence: 99%

Tracking and refocussing of moving targets in multichannel SAR data

Henke

Meier

2015

2015 IEEE International Geoscience and Remote Sensing Symposium (IGARSS)

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Moving targets in Synthetic Aperture Radar (SAR) data impose several challenges for SAR processing. In full-aperture SAR images, moving objects appear smeared and/or displaced. In previous studies, we showed that a combination of sub-aperture processing, feature extraction, unscented Kalman filtering and multi-target hypotheses can reliably detect and track moving objects. In this paper, we present some extensions to the tracking algorithm itself, show results on a newly acquired data set and demonstrate how the estimated trajectories of the moving objects can be utilized to refocus the originally smeared objects. TRACKING AND REFOCUSSING OF MOVING TARGETS IN MULTICHANNEL SAR DATA Daniel Henke, Erich MeierRemote Sensing Laboratories (RSL), University of Zurich ABSTRACTMoving targets in Synthetic Aperture Radar (SAR) data impose several challenges for SAR processing. In fullaperture SAR images, moving objects appear smeared and/or displaced. In previous studies, we showed that a combination of sub-aperture processing, feature extraction, unscented Kalman filtering and multi-target hypotheses can reliably detect and track moving objects. In this paper, we present some extensions to the tracking algorithm itself, show results on a newly acquired data set and demonstrate how the estimated trajectories of the moving objects can be utilized to refocus the originally smeared objects.

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Optimum SAR/GMTI Processing and Its Application to the Radar Satellite RADARSAT-2 for Traffic Monitoring

Cited by 158 publications

References 15 publications

A Performance Evaluation of SAR-GMTI Missions for Maritime Applications

A Performance Evaluation of SAR-GMTI Missions for Maritime Applications

Ground Moving Target’s Velocity Estimation in SAR-GMTI

Tracking and refocussing of moving targets in multichannel SAR data

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