REBAR CLUTTER SUPPRESSION METHOD BASED ON WEIGHTED NUCLEAR NORM MINIMIZATION WITH RANDOM SVD

Through-the-wall radar (TWR) greatly suffers from the wall and rebar clutter, which whelms the targets' echoes heavily. Since the rebars inside the wall often has the same shape as that of targets, many clutter suppression methods do not work effectively. To solve this problem, this paper utilizes a method based on weighted nuclear norm minimization with random singular value decomposition ͧSVDͨ and entry-wise hard-thresholding. For each iteration of the method, different weights are assigned to the singular values, which is used to accurately approximate the rebar clutter. And random SVD is employed to reduce the size of the decomposed data and improve the efficiency. Besides, according to the prior sparsity, entry-wise hard-thresholding is applied to extract the target waves and suppress the remained clutter as well as noise. The effectiveness of proposed method has been verified by the numerical simulation and experimental results.