Attributed Scattering Center Extraction Algorithm Based on Sparse Representation With Dictionary Refinement

Compared with the point-scattering model, the attributed scattering center model (ASCM) is able to describe the frequency and aspect dependence of canonical scattering objects using solutions from both physical optics and the geometric theory of diffraction. As the ASCM is complicated, it may increase the dimension of the parameterized dictionary, which will increase the cost of computation and storage significantly. Aiming at this problem, a novel sparse representation-based algorithm, combined with an alternative optimization and dictionary refinement, is proposed. Utilizing the orthogonal matching pursuit algorithm combined with relaxation algorithm, the solution to the sparse signal recovery problem can be obtained. Numerical results on both electromagnetic computation data and measured SAR data verify the validity of the proposed algorithm.