偶极子分离的矢量阵MIMO雷达多维角度估计算法

该文提出了一种基于2维矢量接收阵列的双基地MIMO雷达系统多目标ADOD(Azimuth Direction Of Departure), ADOA(Azimuth Direction Of Arrival)和EDOA(Elevation Direction Of Arrival)联合估计算法。雷达发射端采用均匀标量线阵，接收端将常规矢量阵元的每个电磁偶极子相互分离构成2维接收阵列。算法通过张量因子分解获取各流形矩阵，并利用ESPRIT算法估计目标的ADOD。文中给出了接收阵列的一种特定阵元排列方式，并改进了矢量叉积法用于估计目标的2D-DOA。与传统方法相比，该文所用阵列结构可通过扩展接收阵列孔径提高雷达的角度估计性能，相互分离的偶极子弱化了传统矢量阵的天线互耦效应。相应算法避免了谱峰搜索，能够自动配对，仿真实验证明了算法的有效性。

MIMO Radar Multi-dimension Angle Estimation with Electromagnetic Vector Sensors of Noncollocating Dipoles/Loops

A novel algorithm for estimation of Azimuth Direction Of Departure (ADOD), Azimuth Direction Of Arrival (ADOA) and Elevation Direction Of Arrival (EDOA) based on bistatic MIMO radar with electromagnetic vector sensors is presented. The linear transmit array composes of multiple scalar sensors with uniform distribution, while the 2D receive array consist of several electromagnetic vector sensor subarrays. Each subarray contains six orthogonally oriented but spatially noncollocating dipoles/loops. With the application of tensor decomposition, the transmit/receive array manifolds are estimated. From the former, a group of multi-targets DODs are calculated with an ESPRIT algorithm. An improved vector cross product direction finding algorithm is presented to estimate the targets 2D-DOAs, based on the 2D receive array constructed with a presented arrangement of subarrays. The proposed array configuration has great advantage, in spatial aperture extending to refine the estimation accuracy, and in reducing mutual coupling. Corresponding algorithm avoid peak searching and parameter pairing processes. Simulation results are presented to verify the effectiveness of the proposed method.