Joint classification of multiresolution representations with discrimination analysis for SAR ATR

Abstract

This paper proposes an automatic target recognition of synthetic aperture radar image by joint classification of multiresolution representations with discrimination analysis. The multiresolution representations are generated to better convey the inner discriminability of the original image. Considering the extended operating conditions (EOCs) in practical applications, it is preferred that those resolutions, which make little contributions to correct target recognition, are not used. Accordingly, the discrimination analysis is performed to select the resolutions with notably high discriminability for the present operating conditions based on their reliability levels calculated from sparse representation-based classification. Afterward, the selected resolutions are jointly classified based on joint sparse representation for target recognition. Finally, extensive experiments are conducted on the moving and stationary target acquisition and recognition dataset under both the standard operating condition and various EOCs. The results validate the effectiveness and robustness of the proposed method.