基于W检验统计量的稳健波达方向估计方法

Robust Direction-of-Arrival Estimation Algorithm Based on W Test Statistics

针对实际环境中广泛存在的脉冲性非高斯噪声会降低基于传统二阶循环统计量的各类算法性能的问题,将混有脉冲噪声的信号样值看作粗差,以稳健估计理论为基础,应用进行高斯检验的W统计量,以自适应方式剔除脉冲样值,得到新的循环互相关函数估计表达式,从而实现了DOA(direction of arrival)的稳健估计.该方法无需噪声统计特性的先验知识,适用于各种非高斯噪声环境,且计算机仿真表明其在不同非高斯噪声条件下的估计性能均优于现有的稳健方法.

Considering the problem that the performance of algorithms based on conventional second order cyclic statistics degrades in the impulsive non-Gaussian noise which exists widely in practical environments, the signal samples contaminated by impulsive noise are taken as outliers and W statistics for Gauss test based on robust statistics theory is adopted to adaptively trim the impulsive samples, and then a new estimated cyclic correlation expression is formulated. Consequently, a novel robust DOA （direction of arrival） estimation is obtained. The proposed algorithm needs no any prior knowledge of the noise probability density function and can be applied to all types of non-Gaussian noise model situations. Computer simulations are presented to illustrate the superior efficiency of the novel approach to the existed robust algorithms under different nonGaussian noise environments.