压缩感知雷达成像技术综述

压缩感知理论突破了传统Nyquist采样定理的限制，它基于信号的稀疏性、测量矩阵的随机性和非线性优化算法完成对信号的压缩采样和重构。这种全新的信号处理理论为克服传统雷达固有缺陷，解决传统高分辨雷达面临的高采样率、大数据量和实时处理困难等问题提供了可能。本文概述了压缩感知基本理论，详细讨论了基于压缩感知的雷达成像技术，对压缩感知在高分辨雷达成像领域中的研究现状进行了归纳和分析，应用对象包括SAR/ISAR、穿墙雷达、MIMO雷达、探地雷达等，充分体现了压缩感知在简化雷达硬件设计、弥补雷达数据缺陷、改善雷达成像质量等方面的巨大潜力，明确了研究中存在的问题，阐述了有待进一步研究的方向，并总结了压缩感知用于雷达成像的优势和缺陷。 

A Review of Radar Imaging Technique based on Compressed Sensing

Compressed Sensing(CS) theory is a great breakthrough of traditional Nyquist sampling theory,it accomplishes compressive sampling and recovery of signal based on the sparsity of interested signal,the randomicity of measurement matrix and nonlinearized optimization method.Thus,as a fire-new signal processing theory,CS provides great possibilities for overcoming inherent limitations of traditional radar,and has potential to resolve many problems associated with high resolution radar,such as high sampling rate...