Radar Forward-looking Imaging Method for Complex Targets Based on L1-Regularized Least Squares

Abstract

Based on the wavefront modulation technique, we introduced the principle and imaging model of forward-looking imaging. Considering the scattering coefficient distribution of the complex target is no longer sparse, L1-regularized least squares method based on sparse representation is proposed for reconstructing radar images of complex targets. The transformation matrix is generated by the dictionary learning method which provides a sparser representation of the scattering coefficient distribution of the complex target. By inversing the solved sparse vector under the transformation matrix, the reconstruction of complex targets can be realized. Simulation results show the effectiveness of the proposed method.