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Dictionary construction is a key factor for the sparse representation- (SR-) based algorithms. It has been verified that the learned dictionaries are more effective than the predefined ones. In this paper, we propose a product dictionary learning (PDL) algorithm to achieve synthetic aperture radar (SAR) target configuration recognition. The proposed algorithm obtains the dictionaries from a statistical standpoint to enhance the robustness of the proposed algorithm to noise. And, taking thedoi:10.1155/2020/9704829 fatcat:ribzp2iza5h7te6bxwqnrcyltq