Study on Application of Compressive Sensing in Radar Signal Processing

当前各种雷达体制如相控阵雷达、宽带/超宽带雷达、合成孔径与逆合成孔 径雷达等，都采用数字化处理技术从回波中提取目标参数信息。压缩感知理论能 够用远低于奈奎斯特（Nyquist）理论的采样速率采集信号、获取离散数据，然 后通过非线性重构算法重建信号，是信号处理领域的一个革命性突破。本文对压 缩感知在雷达信号处理中的应用展开研究，拟解决目前雷达信号处理中存在的若 干问题，主要内容有： (1)远程雷达及多目标跟踪的相控阵雷达对目标跟踪数据率较低，多普勒频 率的估计存在模糊问题。本文采用了一种基于压缩感知的随机稀疏脉冲多普勒解 模糊新方法。雷达系统只需随机发射稀疏的探测脉冲，通过设计相...Digital Radar Signal Processing is used for parameters extraction in most radar system such as Phased Array Radar, Broadband/Ultra Wideband Radar, Synthetic Aperture and Inverse Synthetic Aperture Radar. Compressive Sensing (CS) Theory with its advantage of sampling signal at a lower sampling frequency in comparison with the Nyquist theory, is getting the favor of signal processing field since put...学位：工学硕士院系专业：信息科学与技术学院_通信与信息系统学号：2332011115315

Radar Super-Resolution Imaging Based on Compressive Sensing

研究压缩感知理论在逆合成孔径雷达(InVErSE SynTHETIC APErTurE rAdAr,ISAr)成像中的应用.雷达发射方位稀疏的探测脉冲,对满足nyQuIST采样定理的雷达去斜回波数据进行稀疏采样,再利用压缩感知重构算法分别重构距离向和方位向的完整的目标特性回波信号.为了得到高分辨的雷达ISAr像,对重构的数据在距离向和方位向分别进行超分辨率处理.实际雷达数据和仿真数据表明ISAr像的分辨率有较大提高,所给出的综合方法可以降低数据量,节省雷达的时间资源,具有良好的应用价值.Application of compressed sensing(CS) in inverse synthetic aperture radar is investigated in this paper.The radar transmits sparse probing pulses and dechirped radar echo samples that satisfy the Nyquist sampling theorem are resampled sparsely.Reconstruction is performed to these sparse samples both in range and cross-range directions to recover the whole radar echo signals containing the target characteristics.To obtain high resolution ISAR images, super-resolution processing on both range and cross-range directions is conducted on the reconstructed data.Results of processing on real radar data and simulated data show that the resolution of ISAR image can be enhanced significantly.The proposed algorithm can reduce data size and time consumption, and is valuable for super-resolution radar image applications.国家自然科学基金(No.61102135); 中央高校基本科研业务费专项基金(No.2010121063)资