基于迭代重加权的子阵级MIMO雷达角度超分辨算法  

Angle Super-resolution Algorithm for Subarray MIMO Radar Based on Iterative Reweighted Approach

作　　者：王行舒 张劲东[1] 张亚男 董乔龙 WANG Xingshu;ZHANG Jindong;ZHANG Yanan;DONG Qiaolong(College of Electronic and Information Engineering,Nanjing University of Aeronautics and Astronautics,Nanjing Jiangsu 211106,China)

机构地区：[1]南京航空航天大学电子信息工程学院,江苏南京211106

出　　处：《现代雷达》2024年第6期85-91,共7页Modern Radar

基　　金：国家自然科学基金资助项目(62171220)。

摘　　要：针对子阵级多输入多输出(MIMO)雷达阵列孔径数量有限带来的高方向图旁瓣问题,构建了子阵级MIMO雷达收发信号和多子阵角度测量模型,提出了基于自适应迭代重加权(AIR)和p-范数约束下迭代重加权最小二乘(p-IRLS)的角度超分辨算法,分析了两种算法的计算复杂度。在仿真实验中验证了两种算法的性能,并对其在单目标和双目标、以及干扰环境检测中的效果进行了比较分析。仿真结果表明,AIR和p-IRLS算法能够有效降低子阵级MIMO雷达的方向图旁瓣电平,同时实现对目标的角度超分辨。和AIR算法相比,p-IRLS算法在低信噪比和邻近目标分辨性能更突出。A subarray-level MIMO radar transceiver signal and multi-subarray angular measurement model is constructed in this paper to address the problem of high directional map sidelobes caused by the limited number of apertures of subarray-level multiple-input multiple-output(MIMO)radar arrays.Angular super-resolution algorithms based on adaptive iterative reweighted(AIR)and iterative reweighted least squares with p-norm constraint(p-IRLS)are proposed and the computational complexity of the two algorithms is analyzed.The performance of the two algorithms is verified in simulation experiments,and their effects in single and dual-target,and interference environment detection are comparatively analyzed.The simulation results show that the AIR and p-IRLS algorithms are able to effectively reduce the level of directional map sidelobes in subarray-level MIMO radars,while realizing angular super-resolution of targets.Compared with the AIR algorithm,the p-IRLS algorithm is more prominent in low signal-to-noise ratio and neighboring target resolution performance.

关 键 词：子阵级多输入多输出雷达 自适应迭代重加权 迭代重加权最小二乘 超分辨 

分 类 号：TN972[电子电信—信号与信息处理]