基于子空间投影的加权DOA算法

DOA Algorithm Based on Weighted Subspace Projection

针对MUSIC算法在低信噪比条件下性能恶化的问题,提出一种信号子空间和噪声子空间投影加权的联合DOA(Direction of Arrival)估计算法。首先该方法利用信号子空间的抗噪性,构建一个信号子空间投影加权的空间谱,然后引入高分辨MUSIC算法,获得一种新的基于信号子空间投影加权的MUSIC算法。虽然此算法提高了传统MUSIC算法的稳健性,但是分辨率却没有提升,为此对噪声子空间投影进行加权,提出一种基于信号子空间和噪声子空间投影的加权MUSIC算法,此算法既保留了MUSIC算法的噪声子空间投影,又利用了信号子空间的抗噪性,使得所提算法较于MUSIC算法有更好的稳健性以及空间分辨率。

Aiming at the poor performance of MUSIC algorithm with low SNR, a novel DOA estimation algorithm based on weighted signal subspace and noise subspace projection is proposed.This method made use of signal subspace＇s noise resistante to constructed a Space spectrum based on weighted signal subspace.Then utilized the advantages of high resolution MUSIC algorithm to reconstructed a novel Space spectrum. Considering this algorithm improved the robustness of the traditional MUSIC algorithm but don＇t improved resolution, we proposed a weighted signal subspace projection method, So we can had a new Space spectrum based on weighted signal subspace and noise subspace projection.This algorithm keeps the noise subspace projection d MUSIC algorithm, and using the noise of the signal subspace.So the method we proposed had a higher resolution and robustness than MUSIC algorithm.