该文研究了一种基于多输入多输出(MIMO)电磁矢量传感器阵列雷达目标波离角(DOD)，波达角(DOA)和极化联合估计问题。提出一种新型矢量阵MIMO雷达系统模型，发射阵列采用常规阵元，而接收阵列采用电磁矢量传感器。在此基础上，该文提出4维MUSIC, ESPRIT和迭代1维MUSIC 3种联合参数估计算法。其中迭代1维MUSIC算法首先利用矢量传感器的内在结构特点获得目标DOA预估计，随后采用MUSIC算法对DOD和DOA分别进行1维搜索获得目标角度的高精度估计，最后给出一种基于ESPRIT的目标极化估计算法。迭代1维MUSIC算法可用于不规则阵列，对接收阵列约束较少，无需2维搜索及多维搜索，还可以利用矢量阵特点扩展阵列孔径提高DOA估计精度。此外，论文还推导了DOD, DOA和极化联合估计的CRB。仿真实验表明，与前两种算法相比，迭代1维MUSIC算法具有与CRB更接近的估计精度。
The issue of joint estimation of Direction Of Departure (DOD), Direction Of Arrive (DOA) and polarization for MIMO radar with electromagnetic vector sensors is investigated. A novel bistatic MIMO radar system with multiple transmit sensors and multiple receive electromagnetic vector sensors is proposed. Three joint parameter estimation algorithms, which are, respectively, termed as four-dimensional MUSIC, ESPRIT and iterative one-dimensional (1D) MUSIC, are presented. The iterative 1D-MUSIC algorithm first uses the internal structure of the vector sensors to obtain a set of initialize DOA estimates, and then two 1D-MUSIC searches are employed to get the DOD and DOA estimates in succession, finally a polarization ESPRIT algorithm is proposed for polarization estimation. The iterative 1D-MUSIC algorithm is suitable for irregular array geometry, imposes less constraints on the receive array geometries, and requires no two-dimensional or high-dimensional searching. Moreover, this algorithm can improve the DOA estimation performance by extending the array aperture. The CRB for the issue under consideration is also derived. Simulations show that the estimation accuracy of the iterative 1D-MUSIC algorithm is closest to the CRB, compared with those of the previous two algorithms.