基于稀疏表示的双基地MIMO雷达多目标定位及幅相误差估计

Localization and Estimation of Gain-phase Error for Bistatic MIMO Radar Based on Sparse Representation

基于稀疏表示理论,提出一种新的双基地多输入多输出(MIMO)雷达收发角度及幅相误差估计算法。利用接收数据,分别构造发射和接收协方差矩阵,并以列向量化后的发射和接收协方差矩阵为量测信号建立2个一维稀疏线性模型,构造模型求解的L2-L1混合范数优化目标函数,通过交替迭代寻优获得目标角度估计和幅相误差估计,最后给出了本文算法的收敛性分析。与现有算法相比,该算法充分利用了目标发射和接收空域的稀疏特性,且能够通过对噪声功率的预估计来抑制噪声。仿真结果表明:在低信噪比(SNR)条件下,本文算法仍能够得到较好的估计精度,且对幅相误差具有一定的稳健性。

A new algorithm is presented for the joint estimation of angle and gain-phase error of a bistatic multiple-input mul- tiple-output （MIMO） radar based on sparse representation. The transmitting and receiving covariance matrices are construc- ted by using the received data. Two one-dimensional sparse linear models are obtained by performing the vectorization oper- ation on the transmitting and receiving covariance matrices. Then the mixed L2-1-~ norm cost functions are constructed, in which the solution is derived by utilizing the alternating minimization technique. Furthermore, the coverage analysis of the it- erative algorithm is provided. Compared with the existing algorithms, the proposed method fully utilizes the sparse charac- teristic of the spatial field of a target, and the noise can be suppressed by pre-estimating the noise power. The simulation re- sults show that the proposed method can achieve good estimation performance even under low signal to noise ratio （SNR） and is robust against the variation of gain-phase errors.