Adaptive Wall Clutter Suppression Based on DPSS Basis and Channel Correlation for Through-the-Wall Radar

Through-the-wall radar can detect and localize hidden targets behind obstacles, which has been widely applied in varieties of civil and military applications. However, wall reflections are usually stronger than that of the targets, making it very challenge to extract the target information. In this paper, an adaptive wall clutter mitigation method is proposed. The discrete prolate spheroidal sequence basis is first used to model the wall clutter due to its superiority in modeling the spatially extended property of the walls. Then, by incorporating the compressed sensing technique, we propose a block adaptive subspace pursuit algorithm to estimate the support of the wall, which is further sifted by leveraging the correlation of the wall clutter over different antenna positions. In an adaptive manner, the proposed algorithm can realize the mitigation of wall clutter and separate the target echo data without wall parameters or other prior information, which greatly improves the robustness in practice. Extensive simulations and real-world experiments commendably validate the effectiveness and superiority of the proposed method.