Enhancement of vital signals for UWB through-wall radar using nonconvex regularization

In this paper, an advanced signal processing algorithm based on low-rank sparse representation is proposed to enhance the vital signal in life detection radar applications. The pre-processed echo signal can be decomposed into low-rank, sparse, and noisy parts, where the sparse part is the vital signal. A non-convex regularization method is adopted to obtain the required components, and the approximate solution method is used to accelerate the calculation to meet real-time requirements. Simulated and experimental results show that the proposed algorithm outperforms existing methods in terms of output signal-to-noise ratio (SNR).