Robust Radial Velocity Estimation of Moving Targets Based on Adaptive Data Reconstruction and Subspace Projection Algorithm

Shu, Yuxiang; Liao, Guisheng; Yang, Zhiwei

doi:10.1109/lgrs.2013.2287285

Cited by 28 publications

(12 citation statements)

References 16 publications

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“…The conventional imaging methods consider a model that assumes the scattering field can be considered as a combination of point targets. Examples of such methods include Fourier transform‐based polar format [1, 2], subspace projection [3, 4], and spectral estimation [5, 6]. However, these scattering centres actually arise from the real‐world objects rather than the ideal points.…”

Section: Introductionmentioning

confidence: 99%

Object‐level SAR imaging method with canonical scattering characterisation and inter‐subdictionary interferences mitigation

Cong

Gui

Xiao

et al. 2016

IET Radar, Sonar & Navigation

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Section: Introductionmentioning

confidence: 99%

Object‐level SAR imaging method with canonical scattering characterisation and inter‐subdictionary interferences mitigation

Cong

Gui

Xiao

et al. 2016

IET Radar, Sonar & Navigation

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“…Multifunctional SAR with large-area static scene imaging and ground moving target indication (SAR/GMTI) has drawn much more attentions in recent past decades [1,2,3,4,5,6,7,8,9,10,11,12,13,14,15,16,17,18,19,20,21,22,23,24,25,26,27,28,29,30,31,32]. In the most of applications, not only the point moving targets but also the distributed moving targets are interested.…”

Section: Introductionmentioning

confidence: 99%

“…However, it requires a high pulse repetition frequency (PRF), which may be contradict to the large-swath applications. Therefore, many multichannel SAR methods have been proposed, such as displaced phase center antenna (DPCA) [1,9,10], along track interferometry (ATI) [11,12,13,14], space-time adaptive processing (STAP) [15,16,17,18] and velocity synthetic aperture radar (VSAR) [19,20,21,22]. Furthermore, a method combining SDAP and ISAR technique is proposed in [23] to improve the detection performance.…”

Section: Introductionmentioning

confidence: 99%

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

Huang

Liang

et al. 2016

Sensors

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

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“…The challenge of GMTI includes both the detection of targets and the estimation of their velocity components. Recently, the topic of moving target detection has been extensively studied [1,2,3,4,5]. In conventional SAR images, the target will be displaced and defocused because of the target’s radial (cross-track) and along-track velocities, respectively [6].…”

Section: Introductionmentioning

confidence: 99%

Parameter Estimation of a Ground Moving Target Using Image Sharpness Optimization

2016

Sensors

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Motion parameter estimation of a ground moving target is an important issue in synthetic aperture radar ground moving target indication (SAR-GMTI) which has significant applications for civilian and military. The SAR image of a moving target may be displaced and defocused due to the radial and along-track velocity components, respectively. The sharpness cost function presents a measure of the degree of focus of the image. In this work, a new ground moving target parameter estimation algorithm based on the sharpness optimization criterion is proposed. The relationships between the quadratic phase errors and the target's velocity components are derived. Using two-dimensional searching of the sharpness cost function, we can obtain the velocity components of the target and the focused target image simultaneously. The proposed moving target parameter estimation method and image sharpness metrics are analyzed in detail. Finally, numerical results illustrate the effective and superior velocity estimation performance of the proposed method when compared to existing algorithms.

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Robust Radial Velocity Estimation of Moving Targets Based on Adaptive Data Reconstruction and Subspace Projection Algorithm

Cited by 28 publications

References 16 publications

Object‐level SAR imaging method with canonical scattering characterisation and inter‐subdictionary interferences mitigation

Object‐level SAR imaging method with canonical scattering characterisation and inter‐subdictionary interferences mitigation

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

Parameter Estimation of a Ground Moving Target Using Image Sharpness Optimization

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