SAR ATR based on Bayesian compressive sensing

被引：6
|
作者：
Zhang, Xin-Zheng [1 ]
Huang, Pei-Kang [2 ]
机构：
[1] College of Communication Engineering, Chongqing University
[2] The Science and Technology Committee, China Aerospace Science and Industry Corporation
来源：
Xi Tong Gong Cheng Yu Dian Zi Ji Shu/Systems Engineering and Electronics | 2013年 / 35卷 / 01期
关键词：
Automatic target recognition (ATR); Compressive sensing (CS); Sparse; Synthetic aperture radar (SAR);
D O I：
10.3969/j.issn.1001-506X.2013.01.07
中图分类号：
学科分类号：
摘要：
A new approach is developed for synthetic aperture radar (SAR) automatic target recognition based on Bayesian compressive sensing (BCS). Firstly SAR images are segmented into image data of target zones by constant false alarm rate. Then based on the BCS model, the sensing matrix is constructed by all training sets. The sparse coefficient vectors corresponding to the test samples are solved. Recognition is performed according to the L2 norm corresponding to each of training types of samples in the sensing matrix. Experimental results with the moving and stationary target acquisition and recognition public dataset show that the proposed approach has good recognition effects.
引用
收藏
页码：40 / 44
页数：4
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