A Robust Multi-Channel Moving Target Detection Algorithm for Complex Scenes

LIU Kun; HE Xiongpeng; LIAO Guisheng; YU Yue; WANG Qikai

doi:10.11999/JEIT230958

Volume 46 Issue 5

May 2024

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Article Navigation > Journal of Electronics & Information Technology > 2024 > 46(5): 2018-2027

LIU Kun, HE Xiongpeng, LIAO Guisheng, YU Yue, WANG Qikai. A Robust Multi-Channel Moving Target Detection Algorithm for Complex Scenes[J]. Journal of Electronics & Information Technology, 2024, 46(5): 2018-2027. doi: 10.11999/JEIT230958

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LIU Kun, HE Xiongpeng, LIAO Guisheng, YU Yue, WANG Qikai. A Robust Multi-Channel Moving Target Detection Algorithm for Complex Scenes[J]. Journal of Electronics & Information Technology, 2024, 46(5): 2018-2027. doi: 10.11999/JEIT230958

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A Robust Multi-Channel Moving Target Detection Algorithm for Complex Scenes

doi: 10.11999/JEIT230958

National Key Laboratory of Radar Signal Processing, Xidian University, Xi’an, 710071, China

Funds: The National Natural Science Foundation of China (62201408, 61931016), The National Radar Signal Processing Laboratory (JKW202108)

Received Date: 2023-09-04
Rev Recd Date: 2024-05-06

Available Online: 2024-05-12

Publish Date: 2024-05-30

Abstract

Abstract

Aiming at the problems of high false alarm and sensitivity to channel error of Robust Principal Component Analysis (RPCA) algorithm in multi-channel Ground Moving Target Indication (GMTI), this paper proposes a data reconstruction and Velocity Synthetic Aperture Radar (VSAR)-RPCA joint processing method. Firstly, the sample selection and joint pixel method are used to complete the accurate reconstruction of inter-channel data; then a new RPCA optimization model is proposed by combining the VSAR detection mode, and the sparse matrix in the spatial frequency domain is obtained by solving the new RPCA optimization model with the alternating projection multiplier method, and then the differences in the distribution characteristics of the moving target and the strong clutter residuals in the spatial frequency domain channel are used to realize the strong clutter residuals rejection and the detection of the moving target; finally, the radial velocity of the target is estimated by the Along-Track Interferometry algorithm to complete the moving target relocation. Compared with the traditional RPCA algorithm, the proposed algorithm significantly reduces the false alarm rate under the background of non-ideal strong clutter. Theoretical analyses and experiments verify the effectiveness of the proposed algorithm.
- Synthetic Aperture Radar (SAR),
- Ground Moving Target Indication (GMTI),
- Robust Principal Component Analysis (RPCA),
- Data reconstruction

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References(31)

References

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