针对合成孔径雷达(SAR)目标识别,提出一种联合非线性相关信息熵(NCIE)和多分辨表示的方法。采用NCIE对原始SAR图像的多分辨率表示进行选择,获得内在相关较强的若干分辨率。然后,采用联合稀疏表示对选取的多分辨率样本进行联合表征和分类。实验中,以MSTAR数据集为基础设计多种操作条件对不同方法进行测试,结果表明了所提方法的有效性。

A method to combine nonlinear correlation information entropy (NCIE) and multi-resolution representation is proposed for synthetic aperture radar (SAR) target recognition. NCIE is employed to select the multi-resolution representation of an original SAR image, and several resolutions with strong intrinsic correlation are obtained. Then, the joint sparse representation is used to characterize and classify the selected multi-resolution samples simultaneously. Experiments are conducted in which various operating conditions are employed to test the different methods based on the MSTAR dataset. The experimental results demonstrate the validity of the proposed method.