Sparse based attributed scattering center extraction algorithm with dictionary refinement

Compared with the point scatter model, the attributed scattering center model with several parameters provides a concise, physically relevant description of a complex object. Hence, attributed scattering center parameters in the model are very important feature in automatic target recognition, and it is meaningful to extract attributed scattering center, known as inverse scattering problem. Considering the sparsity of radar measurements in model parameter domain, a novel attributed scattering center extraction algorithm is proposed based on sparse representation with dictionary refinement. Numerical results on measured SAR data show that the proposed algorithm is able to extract scattering centers and estimate the geometrical dimensions of the target and its major structural components accurately.