Target recognition of SAR images based on multi-resolution representation

ABSTRACT

This letter presents a target recognition method for synthetic aperture radar (SAR) images by exploiting the multi-resolution information. For the training samples, images with lower resolutions are generated to construct a multi-resolution dictionary for the sparse representation-based classification (SRC). Then the test sample will be classified based on the augmented dictionary. The multi-resolution representation of the training samples can not only promote the representation capability of the dictionary but also enhance the robustness to the resolution variance of the test sample due to the sensor variation. Experiments are conducted on the moving and stationary target acquisition and recognition (MSTAR) dataset to demonstrate the validity of the proposed method.