基于滤波器结构的压缩感知雷达感知矩阵优化
收稿日期: 2012-03-15
修回日期: 2012-12-10
网络出版日期: 2013-04-23
基金资助
国家自然科学基金(61071163,61201367,61071164,61271327);江苏省自然科学基金(BK2012382);中国博士后科学基金(20100481143);江苏省博士后科研资助计划(1109093C);中央高校基本科研业务费(NS2012020);江苏高校优势学科建设工程资助项目
Optimized Sensing Matrix Design of Filter Structure Based Compressed Sensing Radar
Received date: 2012-03-15
Revised date: 2012-12-10
Online published: 2013-04-23
Supported by
National Natural Science Foundation of China (61071163, 61201367, 61071164, 61271327); Natural Science Foundation of Jiangsu Province (BK2012382); China Postdoctoral Science Foundation (20100481143); Jiangsu Planned Projects for Postdoctoral Research Funds (1109093C); Fundamental Research Funds for the Central Universities (NS2012020); A Project Funded by the Priority Academic Program Development of Jiangsu Higher Education Institutions *Corresponding author. Tel.: 025-84892410 E-mail: zhangjd@nuaa.edu.cn
张劲东 , 张弓 , 潘汇 , 贲德 . 基于滤波器结构的压缩感知雷达感知矩阵优化[J]. 航空学报, 2013 , 34(4) : 864 -872 . DOI: 10.7527/S1000-6893.2013.0147
The sparse scene recovery performance of a compressed sensing radar (CSR) requires that the cross correlations between the atoms of the sensing matrix be as small as possible. Based on this thought, a CSR optimal sensing matrix design system is proposed. According to the information of the radar system task and target scene, it can optimize the transmitted waveform and measurement matrix adaptively for the purpose of reducing the coherence of the sensing matrix to improve the system performance. The algorithms for optimizing the transmitted waveform and measurement matrix separately and jointly are presented. Simulation results demonstrate that the proposed methods can effectively improve scene recovery accuracy.
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