基于维度特性的二维到达角及极化参量联合估计算法

针对利用极化敏感阵列进行多维参数联合估计运算复杂度大的问题，提出一种基于噪声子空间维度特性的极化敏感阵列DOA及极化参数联合估计算法。算法利用阵列接收数据协方差矩阵噪声子空间的维度特性构造谱函数，有效降低了极化敏感阵列信号参数联合估计的计算复杂度，同时保证了算法的估计性能。对算法与现有基于长矢量的MUSIC算法的运算复杂度进行了理论分析对比。最后，仿真对比实验验证了算法的有效性。

Dimension Feature-based Two-dimensional DOA and Polarization Estimation with a Polarization Sensitive Array

Joint estimation of DOA and polarization with a polarization sensitive array has the shortcoming of high computational complexity . In order to solve this problem , a direction of arrival ( DOA) and polarization joint estimation algorithm based on dimension feature of the noise-subspace using polarization sensitive array was proposed .Approximation of projection matrix was obtained for construction of spectrum function by dimension feature of noise subspace , which reduces computational complexity of DOA and polarization joint estimation algorithm but also guarantees estimation performance .Ccomputational complexity of the algorithm was compared with that of long vector -based MUSIC algorithm.Finally, efficiency of the proposed algorithm was verified based on the simulation results .