收稿日期: 2016-04-22
修回日期: 2016-05-11
网络出版日期: 2017-01-15
基金资助
国家自然科学基金（61331020，61571422）和国家863计划项目（2013AA122903，2013AA122904）资助
A robust SAR target recognition method based on multi-scale feature and sparse representation
Received date: 2016-04-22
Revised date: 2016-05-11
Online published: 2017-01-15
向卫力 , 李晓辉 , 周勇胜 , 李传荣 , 唐伶俐 . 一种鲁棒的多尺度稀疏表示SAR目标识别方法[J]. 中国科学院大学学报, 2017 , 34(1) : 99 -105 . DOI: 10.7523/j.issn.2095-6134.2017.01.013
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
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