基于四阶累积量的最小模DOA估计方法

高阶累积量由于对高斯噪声不敏感,在高分辨阵列信号处理中可用来提高参数估计的分辨性能。本文从一个统一的角度来研究基于高阶累积量的高分辨阵列信号处理方法,用四阶累积量构造了一个较通用的累积量矩阵,该矩阵符合最小模(M in-Norm)算法的结构,从而可进行DOA(D irection of Arrival)估计。由于四阶累积量对高斯噪声干扰不敏感,从而可提高估计的分辨性能。本文就这种方法在阵列信号处理中的应用,通过计算机仿真与基于二阶矩的M in-Norm算法进行了较全面的比较。仿真结果表明,该方法在高斯噪声中具有良好的统计性能,是实现高分辨方位估计的有效方法。

Min-Norm DOA estimation method based on fourth-order cumulants

High-order cumulants can be used to improve the parameters estimation due to its insensitivity to Gaussian noise.This paper studies the high-resolution array processing based on high order cumulants with a uniform manner,and a method based on fourth-order cumulants is proposed.The fourth-order cumulants has the structure of Min-Norm algorithm,therefore we can estimate the DOA(Direction of Arrival).Because the fourth-order cumulants is insensitive to gaussian noise or inference,the performance of the estimates can be increased.This paper compared the method with the method based on convariance through computer simulations.The simulation results show that the method has good statistical performance in Gaussian noise and it is an effective method in implementing high-resolution DOA estimation.