School of Information and Communication Engineering, Dalian University of Technology, Dalian 116024, China.
Sensors (Basel). 2012;12(3):3394-417. doi: 10.3390/s120303394. Epub 2012 Mar 8.
Joint estimation of direction-of-arrival (DOA) and polarization with electromagnetic vector-sensors (EMVS) is considered in the framework of complex-valued non-orthogonal joint diagonalization (CNJD). Two new CNJD algorithms are presented, which propose to tackle the high dimensional optimization problem in CNJD via a sequence of simple sub-optimization problems, by using LU or LQ decompositions of the target matrices as well as the Jacobi-type scheme. Furthermore, based on the above CNJD algorithms we present a novel strategy to exploit the multi-dimensional structure present in the second-order statistics of EMVS outputs for simultaneous DOA and polarization estimation. Simulations are provided to compare the proposed strategy with existing tensorial or joint diagonalization based methods.
在复值非正交联合对角化（CNJD）的框架内，研究了利用电磁矢量传感器（EMVS）联合估计波达方向（DOA）和极化。提出了两种新的 CNJD 算法，通过使用目标矩阵的 LU 或 LQ 分解以及 Jacobi 型方案，提出了通过一系列简单的子优化问题来解决 CNJD 中的高维优化问题。此外，基于上述 CNJD 算法，我们提出了一种新策略，利用 EMVS 输出的二阶统计中的多维结构来进行同时 DOA 和极化估计。仿真结果表明，与现有的张量或联合对角化方法相比，该方法具有优越性。
