An Improved SAR Image Target Recognition Algorithm

Target recognition is a key step in the interpretation of SAR images. For existing SAR image recognition methods based on sparse representation, the recognition rate is still not high enough. Based on the analysis of the impact recognition rate, the target region and shadow region characteristics in SAR images are combined. In this paper, a SAR image target recognition method based on sparse representation and stretching is proposed. In this method, a new training sample image is generated by stretching the training sample image, a sparse dictionary is constructed by using the existing training sample image and a new training sample image, and the joint sparse representation of the target region and the shadow region is solved by the reconstruction. The minimum error criterion completes the SAR image target recognition. The target recognition method of this paper is tested by using MSTAR real-measured SAR image. The results show that the recognition rate of this method is higher than that of existing methods, which verifies the effectiveness of the proposed method.