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基于滤波器结构的压缩感知雷达感知矩阵优化

张劲东, 张弓, 潘汇, 贲德   

  1. 南京航空航天大学 电子信息工程学院, 江苏 南京 210016
  • 收稿日期:2012-03-15 修回日期:2012-12-10 出版日期:2013-04-25 发布日期:2013-04-23
  • 通讯作者: 张劲东,Tel.: 025-84892410 E-mail: zhangjd@nuaa.edu.cn E-mail:zhangjd@nuaa.edu.cn
  • 作者简介:张劲东 男, 博士, 讲师。主要研究方向: 雷达信号处理, 压缩感知理论。 Tel: 025-84892410 E-mail: zhangjd@nuaa.edu.cn;张弓 男, 博士, 教授, 博士生导师。主要研究方向: 新体制雷达, 雷达信号处理。 Tel: 025-84892410 E-mail: gzhang@nuaa.edu.cn;潘汇 男, 硕士研究生。主要研究方向: 压缩感知雷达。 Tel: 025-84892410 E-mail: panhui.com@gmail.com;贲德 男, 中国工程院院士, 南京航空航天大学电子信息工程学院院长, 教授, 博士生导师。主要研究方向: 雷达信号处理。
  • 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

ZHANG Jindong, ZHANG Gong, PAN Hui, BEN De   

  1. College of Electronic and Information Engineering, Nanjing University of Aeronautics and Astronautics, Nanjing 210016, China
  • Received:2012-03-15 Revised:2012-12-10 Online:2013-04-25 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

摘要:

压缩感知雷达的目标场景恢复性能要求不同目标的反射回波在压缩空间上的互相关性尽可能小。基于该思想,提出了压缩感知雷达感知矩阵优化模型,根据系统参数和任务信息,以降低感知矩阵互相关性为目标,自适应地构造发射波形和测量矩阵,提升系统性能。分别给出了基于滤波器结构的压缩感知雷达发射波形优化、测量矩阵优化以及波形-测量矩阵联合优化算法。仿真结果表明:本文提出的压缩感知雷达感知矩阵优化模型和算法能够有效地提高场景恢复精度。

关键词: 压缩感知雷达, 感知矩阵优化, 发射波形优化, 测量矩阵优化, 滤波器结构

Abstract:

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.

Key words: compressed sensing radar, sensing matrix optimization, waveform optimization, measurement matrix optimization, filter structure

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