双基地稀疏阵列MIMO雷达快速多目标定位方法  

Fast Multi-target Localization with Sparse Array in Bistatic MIMO Radar

作　　者：孙理[1] 朱晓华[1] 贺亚鹏[2] 王克让[1] 顾陈[1] 

机构地区：[1]南京理工大学电子工程与光电技术学院,南京210094 [2]中国空间技术研究院微波遥感与数传技术研究所,西安710000

出　　处：《电子与信息学报》2013年第5期1142-1148,共7页Journal of Electronics & Information Technology

摘　　要：针对双基地稀疏阵列MIMO雷达目标定位问题,该文提出一种基于投影处理与奇异值分解的多测量矢量欠定系统正则化聚焦求解(Projection-SVD-RMFOCUSS,PSVDRMF)算法。该算法首先估计接收角,接着依次将回波信号向目标存在的角度进行投影,最后将投影后的数据重排进行发射角估计,从而得到目标的准确位置。同时借助奇异值分解(SVD)进行信号降维与能量积累,进一步降低运算量,提高了传统压缩感知恢复算法在低信噪比下的估计性能。与现有稀疏重建算法相比,该算法减少了2维场景带来的庞大运算负担,且保持了良好的性能,可以稳健地对相干与非相干目标进行定位。To solve the problem of target localization with sparse array in bistatic MIMO radar,a projection and Singular Value Decomposition（SVD） based Regularized Multi-vectors FOCal Undetermined System Solver（RMFOCUSS） algorithm is proposed.First the target angles with respect to receive array are estimated,and then the echoed signal is projected back to them.After an rearrangement of the projected signal,the target angles with respect to transmit array are estimated,so targets are located.SVD is utilized to reduce signal dimension and accumulate signal power,which makes traditional Compressive Sensing（CS） recovery algorithms perform better under low SNR,and computational complexity is reduced even more.Compared with existing sparse reconstruction approaches,the proposed method costs much less computation time in coping with large two dimensional scene and maintains a good performance whether the targets are relative or not.

关 键 词：双基地MIMO雷达 稀疏阵列 压缩感知 多测量矢量欠定系统正则化聚焦 正交投影 

分 类 号：TN958[电子电信—信号与信息处理]