A Robust Multi-Channel Moving Target Detection Algorithm for Complex Scenes
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
万方数据
维普
