基于二阶统计量的分布式信源二维波达方向估计

Two-dimensional direction of arrival estimation for distributed source based on second-order statistics

对于由本地散射导致的分布式信源二维波达方向估计,根据空间角度信号密度的共轭对称特性,首先将相干分布式信源方向向量化简为传统点信源方向向量与实向量的Schur-Hadamard积,进而提出了一种基于Schur-Hadamard积的相干分布式信源二维波达方向估计算法。该算法通过构造基于Schur-Hadamard积的二阶统计量,可直接给出仰角和方位角的估计值。与传统谱峰搜索类算法和经典子空间类算法相比,无须谱峰搜索和任何特征值或奇异值分解,有效地降低了计算量;所利用的二阶统计量对噪声不敏感,具有较好的信噪比性能。仿真实验表明,该算法具有较好的参数估计精度,可有效解决复杂通信环境下相干分布式信源的二维波达方向估计问题。

For estimating the two-dimensional direction of arrival（DOA） of local scattering distributed source,according to the symmetry assumption of spatial angular signal intensity,the steering vector is deduced to be a Schur-Hadamard product comprising the steering vector of the point source and a real vector for coherently distributed source.And then second-order statistics based on Schur-Hadamard product is proposed for estimating elevation and azimuth angles.An advantage of this method over the classical algorithms is that it does not apply any peak-finding searching and eigenvalue decomposition or singular value decomposition,which significantly reduces the computational complexity.The proposed algorithm is not sensitive to white noise,so it can improve signal to noise ratio performance.Simulations clearly demonstrate that the algorithm enjoys improved precision and is more suitable for complicated environment.