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本文研究了自相关矩阵、协方差矩阵和修正协方差矩阵的正弦信号高分辨频率估计的特征分解法,文章首先研究了这三种相关矩阵的特征分解结构及高分辨特征分解法的原理;接着给出了几种典型的高分辨特征分解法;最后通过大量计算机仿真实验研究了基于这三种相关矩阵的各特征分解法的均方误差特性和分辨概率特性,结果表明,各方法的统计性能不尽相同,各有优势,是实现高分辨参数估计的一类很有希望的方法.
In this paper, the eigen decomposition method of high resolution frequency estimation of sinusoidal signal of autocorrelation matrix, covariance matrix and modified covariance matrix is studied. Firstly, the eigen decomposition structure of the three correlation matrices and the principle of high resolution eigen decomposition are studied. Several typical high resolution eigendecomposition methods are given. Finally, a large number of computer simulation experiments are conducted to investigate the mean square error characteristics and resolution probability characteristics of each eigendecomposition method based on these three correlation matrices. The results show that the statistical performance of each method Not the same, each with its own advantages, is a promising method for achieving high-resolution parameter estimation.