【摘要】 现有的波达方向(Direction Of Arrival,DOA)和极化参数估计方法大多基于子空间理论.本文从稀疏信号重构角度出发,提出了一种新的DOA和极化角度估计算法.该算法首先构建一个只包含DOA信息的累积量矩阵模型,然后基于加权l1范数最小化获得DOA估计.在DOA估计的基础上,进一步通过求和平均运算构建三个包含不同极化信息的累积量向量模型,利用Zhang惩罚进行稀疏性约束,获得近似无偏的极化角度估计.阐述了如何利用极化信息来区分两个入射角度一样的信源信号.计算机仿真结果验证了所提算法的有效性.更多还原

【Abstract】 Existing direction-of-arrival and polarization estimation methods mostly rely on subspace technique. This paper proposes a novel DOA and polarization angle estimation algorithm from sparse signal reconstruction perspective. The algorithm first constructs a cumulant matrix model which is only related to DOA parameter,and then obtains DOA estimation using the weighted l1-norm minimization. Further,this paper constructs another three cumulant vector models by sum-average arithmetic,and enforces sparsity by Zhang penalty,which leads to almost unbiased polarization angle estimation.M eanwhile,this paper also demonstrates howto identify two sources with same DOA using their polarization characteristics.Computer simulation results validate the effectiveness of the proposed algorithm.更多还原