近年来发展起来的压缩感知理论挑战了SHANNON的NYQUIST采样定理的理论极限，对信号处理领域产生了极其重要的影响。本文对压缩感知成像雷达的研究进展进行了综述,首先从压缩感知理论的基本原理出发，探讨了压缩感知应用于雷达成像领域的基本思想；重点阐述了压缩感知成像雷达的研究现状，包括合成孔径雷达、逆合成孔径雷达、多发多收雷达、探地雷达、穿墙雷达、认知雷达等多个方面;最后探讨了压缩感知成像雷达走向实用化所面临的若干挑战，并提出后续发展的相关建议。

Compressed Sensing (CS) theory has challenged the limitation of Nyquist-Shannon sampling theorem and has a very important impact on signal processing field in recent years. In this paper, the research progresses of CS imaging radar are reviewed. Firstly, based on the basic principle of CS theory, the idea of its application in radar imaging is discussed. Then, the current research development of CS imaging radar is demonstrated, including Synthetic Aperture Radar (SAR), Inverse Synthetic Aperture Radar (ISAR), Multiple-Input Multiple-Output (MIMO) radar, Ground Penetrating Radar (GPR), Through-the-Wall Radar (TWR), Cognitive Radar (CR) and so on. Finally, some challenges faced by the CS imaging radar in its practical applications are discussed, and several suggestions are given on its future development.