Near-range Strong Coupled Signal Suppression Algorithm Based on RPCA for GBSAR

Ground-Based Synthetic Aperture Radar (GBSAR) is an all-day all-weather, non-contact, high precision instrument for wide-area deformation monitoring, which has been widely used to monitormining areas, slops, and dams. When monitoring the outside scene with the radar placed in the inner space, the radar echo would be interfered with by strong scattering signals reflected from the inner space. The strong scattering signal at near range would severely affect the image quality. Therefore, this paper proposes a Robust Principal Component Analysis(RPCA) based algorithm to decompose the range-doppler domain signal into low-rank and sparse parts,as, in the range-doppler domain, the near-range coupled signal has low-rank characteristics, whereas the scene signal has sparse characteristics. Unlike the existing Principal Component Analysis(PCA) based algorithm, the proposed RPCA algorithm does not assume a Gaussian-distributed scene signal, which usually could not be satisfied in reality. Additionally, this paper proposes a correlation-based regularization parameter optimization method for RPCA. Thus, low rank and sparse matrices can be better separated. Furthermore, the proposed method is verified with real GBSAR data. The result shows that the proposed RPCA based method can better suppress the coupled signal while retaining the scene signal than the existing PCA-based algorithm.