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基于压缩感知理论的雷达成像技术与应用研究进展

李少东 杨军 陈文峰 马晓岩

李少东, 杨军, 陈文峰, 马晓岩. 基于压缩感知理论的雷达成像技术与应用研究进展[J]. 电子与信息学报, 2016, 38(2): 495-508. doi: 10.11999/JEIT150874
引用本文: 李少东, 杨军, 陈文峰, 马晓岩. 基于压缩感知理论的雷达成像技术与应用研究进展[J]. 电子与信息学报, 2016, 38(2): 495-508. doi: 10.11999/JEIT150874
LI Shaodong, YANG Jun, CHEN Wenfeng, MA Xiaoyan. Overview of Radar Imaging Technique and Application Based on Compressive Sensing Theory[J]. Journal of Electronics and Information Technology, 2016, 38(2): 495-508. doi: 10.11999/JEIT150874
Citation: LI Shaodong, YANG Jun, CHEN Wenfeng, MA Xiaoyan. Overview of Radar Imaging Technique and Application Based on Compressive Sensing Theory[J]. Journal of Electronics and Information Technology, 2016, 38(2): 495-508. doi: 10.11999/JEIT150874

基于压缩感知理论的雷达成像技术与应用研究进展

doi: 10.11999/JEIT150874

Overview of Radar Imaging Technique and Application Based on Compressive Sensing Theory

  • 摘要: 压缩感知理论基于信号稀疏性,将对信号采样转换为对信息自由度的采样,可大大降低采样率。而将压缩感知理论应用于雷达成像时有望在以下几个方面得到改善:增强成像性能,简化雷达硬件设计,缩短数据获取时间,减少数据量和传输量等。该文从压缩感知的稀疏性,压缩采样,无模糊重建3个关键步骤与成像雷达有机结合的角度,对近年来基于压缩感知理论的雷达成像技术研究现状进行系统综述,重点论述场景稀疏性与成像关系, 压缩采样方法(包括硬件)设计,场景图像快速高精度重建以及成像系统体制应用等方面,最后探讨了压缩感知理论应用尚需解决的问题和进一步发展方向。
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    • 收稿日期:  2015-07-21
    • 修回日期:  2015-12-08
    • 刊出日期:  2016-02-19

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