基于波形选择的MIMO雷达三维稀疏成像与角度误差校正方法  

Three Dimensional MIMO Radar Imaging Using Sparse Model Based on Waveform Selection and Calibration Method in the Presence of Angle Imperfections

作　　者：杨杰[1] 廖桂生[1] 李军[1] 党博[1] 刘长赞[1] 

机构地区：[1]西安电子科技大学雷达信号处理国家重点实验室,西安710071

出　　处：《电子与信息学报》2014年第2期428-434,共7页Journal of Electronics & Information Technology

基　　金：国家自然科学基金(61271292);国家973计划项目(2010CB731903);西安电子科技大学基本科研业务费(k50511020003)资助课题

摘　　要：该文研究稀疏目标场景下,波形选择对基于压缩感知理论的MIMO雷达成像效果的影响并提出一种改进的成像角度误差校正方法。首先分析了模糊函数和压缩感知匹配字典的相关系数之间的关系;然后,在空间小角度域情况下,针对成像场景中的角度误差,提出一种改进的基于迭代最小化的稀疏学习(SLIM)算法进行校正。仿真结果表明,选择具有较低旁瓣模糊函数的发射波形可以提高成像质量,改进的SLIM算法可以有效补偿角度误差。The effect of waveform selection on compressive sensing MIMO radar imaging using sparse model and an improved calibration method in the presence of angle imperfections are researched in this paper. Firstly the relationship between ambiguity function and Compressive Sensing （CS） “dictionary coherence coefficient” is analyzed. Then, in the presence of small spatial angle, an improved method based on“Sparse Learning via Iterative Minimization”（SLIM） algorithm is proposed to calibrate angle errors. Simulation results illustrate that the imaging quality can be enhanced when selected waveforms have low sidelobes and prove that the modifed method can calibrate angle errors effectively.

关 键 词：MIMO雷达 稀疏成像 波形选择 角度误差校正 基于迭代最小化的稀疏学习(SLIM) 

分 类 号：TN958[电子电信—信号与信息处理]