Improved Ground Moving Target Detection Method Combining GSCFT and RPCA for Multi-channel SAR-GMTI System

As a class of Synthetic Aperture Radar Ground Moving Target Indication (SAR-GMTI) methods, Robust Principal Component Analysis (RPCA)-based techniques consistently face the challenge of high correlation coefficients among channels, which will degrade the detection performance. Furthermore, the traditional RPCA-based methods always overlook the impact of azimuth velocity of moving targets, which has certain limitations for practical applications. To address these issues, this paper proposes a novel method, combining the generalized scale fourier transform with RPCA. First, it derives the signal model with introducing the azimuth velocity and proposes a generalized scale kernel function to achieve the decouple the envelope delay from the phase difference. It not only reduces the correlation coefficient effectively, but also achieves the precise estimation of the azimuth velocity through two-dimensional focusing associated with Doppler parameter in transform domain, while improving the method’s detection performance under low signal-to-noise ratio. Second, it derives the compensation processing of inter-channel signals to ensure compatibility with RPCA method and develops the correspond optimized criterion to achieve the detection of moving targets from the separate clutter. Finally, the simulated and measured data are provided to validate the effectiveness and correctness of the proposed method.