A robust SAR target recognition method based on multi-scale feature and sparse representation

doi:10.7523/j.issn.2095-6134.2017.01.013

Abstract

Abstract:

A robust synthetic aperture radar (SAR) target recognition method based on multi-scale Gabor feature extraction and sparse representation is proposed. Firstly, SAR images are segmented and filtered in different directions by using multi-scale Gabor filter to enhance the local features. Then, based on sparse representation model, the sparse dictionary is constructed by using the training samples as atoms. By using the sparse solving algorithms, the testing samples are represented by selecting the optimal atom set. Finally, the testing samples are recognized according to the l₁ norm of non-negative sparse representation coefficient. Experimental results show the effectiveness and robustness of the proposed method.

Key words: SAR, target recognition, sparse representation, multi-scale

CLC Number:

TP391

XIANG Weili, LI Xiaohui, ZHOU Yongsheng, LI Chuanrong, TANG Lingli. A robust SAR target recognition method based on multi-scale feature and sparse representation[J]. , 2017, 34(1): 99-105.

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