Outline Reconstruction for Radar Forward-Looking Imaging Based on Total Variation Functional Deconvloution Methodxs

Abstract

It is great significant to achieve clear outline reconstruction for radar forward-looking imaging. In this paper, we apply the total variation (TV) function as the regularization term operator to obtain the forward-looking imaging with clear outline. Firstly, we establish the deconvolution model, by which the forward-looking super-resolution imaging problem is converted into inverse problem. Then, taking the TV function as regularization constraint term, we construct the objective function to solve the inverse problem. Finally, we obtain the minimum of the objective function, by which we can achieve radar forward-looking super-resolution imaging with clear outline. Simulations verify effectiveness of the proposed method in reconstructing the outline of targets.