基于虚拟阵列扩展的改进加权空间平滑算法

针对相干信源的波达方向(direction of arrival, DOA)估计问题, 传统的空间平滑算法通过减小阵列孔径来解相干, 导致估计精度降低。本文以相干分布源为研究对象, 首先通过扩展共轭虚拟阵列增大阵列孔径, 使用Toeplitz算法进行预估计, 根据预估计值构建加权矩阵, 通过二次加权空间平滑恢复协方差矩阵的秩, 消除信号的相干性, 结合传播因子算法估计得到目标信源的入射角度。该算法充分利用子阵输出的自相关和互相关信息, 改善了阵列孔径带来的精度影响。仿真结果表明, 所提算法对相干信源具有良好的分辨能力和估计精度, 在低信噪比时鲁棒性较好。

Improved weighted spatial smoothing algorithm based on virtual array expansion

Aiming at the direction of arrival (DOA) estimation problem of coherent sources, the traditional spatial smoothing algorithm reduces the aperture of the array to resolve the coherence, resulting in lower estimation accuracy. This paper takes the coherent distribution source as the research object. First, the conjugate virtual array is expanded to increase the array aperture, and the Toeplitz algorithm is used for pre-estimation, a weighting matrix is constructed according to the pre-estimated value, and the rank of the covariance matrix is restored through the secondary weighted space smoothing, so the coherence of the signal is eliminated, the incident angle of the target source is estimated combined with the propagation factor algorithm. This algorithm makes full use of the auto-correlation and cross-correlation information by the sub-array, improving the accuracy impact brought by the array aperture. Simulation results show that the proposed algorithm has good resolution and estimation accuracy for coherent sources. It has better robustness at low signal to noise ratio.