加权空间平滑TLS-ESPRIT算法性能分析

Performance Analysis of Weighted Spatial Smoothing TLS-ESPRIT Algorithm

针对常规TLS-ESPRIT算法不能处理相干信源测向的问题,在空间平滑TLS-ESPRIT算法的基础上,提出了加权空间平滑TLS-ESPRIT算法。通过对原始阵列进行特殊结构的子阵划分,直接利用子阵输出的自相关和互相关信息求得加权矩阵,充分利用阵列输出的自相关和互相关信息,提高了信号子空间与噪声子空间的正交性,从而实现相干信源的解相干。仿真结果表明,新算法在不同信噪比和快拍数下,都优于空间平滑TLS-ESPRIT算法,对相干信号的DOA估计具有更好的处理效果。

Aiming at the problem that the conventional TLS-ESPRIT algorithm can’t deal with the coherent source direction-finding,and on the basis of spatial smoothing TLS-ESPRIT algorithm,a weighted spatial smoothing TLS-ESPRIT algorithm is proposed in this paper.By dividing the original array into subarrays with special structure,the weighted matrix is obtained by direct use of the autocorrelation and cross-correlation information output by subarrays.In this algorithm,the weighted covariance matrix makes full use of the autocorrelation and cross-correlation information output by subarrays to improve the orthogonality of the signal subspace and the noise subspace,to realize the decorrelation of coherent source.The simulation results show that the new algorithm is superior to the spatial smoothing TLS-ESPRIT algorithm under different SNR and snapshot,especially in the scenarios of multiple coherent sources.