Bo Cheng
ABSTRACT
This paper proposed a Synthetic Aperture Radar (SAR) target recognition method based on joint sparse representation of three complementary features. The Elliptical Fourier descriptors (EFDs) of the target outline and PCA features were extracted to depict the geometrical shape and intensity distribution of original SAR image. The azimuthal sensitivity image was constructed to describe the electromagnetic scattering characteristics of the target. The joint sparse representation was used to jointly classify the three features to exploit their complementary advantages. Finally, the target label of the test sample was decided based on the reconstruction errors. To validate the effeteness of the proposed method, experiments were conducted on the Moving and Stationary Target Acquisition and Recognition (MSTAR) dataset under various operating conditions.
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Index Terms
- SAR Target Recognition Based on Joint Sparse Representation of Complementary Features
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