Principal component reconstruction: With application to target recognition in SAR image

Abstract

This paper proposes a classification method based on principal component reconstruction (PCR) for target recognition in synthetic aperture radar (SAR) image. To characterize the SAR image and alleviate the influence of different intensity of the same targets on target recognition, the SAR image is mapped into the principal component space by the principal component analysis with zero mean. In the principal component space, the query sample is reconstructed by a combination of the nearest training samples from the specific class, respectively. Then, the identity is decided by evaluating the minimum reconstruction error with respect to each class. Specifically, the reconstruction coefficients are constrained to be positive, which is more reasonable to the certain application. Extensive experiments carried out on the moving and stationary target acquisition and recognition (MSTAR) dataset illustrate the effective performance of the proposed method on ten-class targets recognition and configuration variation.