基于伪协方差矩阵 Otsu 方法的信源数估计

为提高高斯色噪声背景下信源数估计的成功概率, 提出了一种基于伪协方差矩阵的 Otsu 类间方差法。 伪协方差矩阵对一定条件下的高斯白噪声和高斯色噪声具有免疫特性, 而且利用阵元间的时间相关性增加了 阵列的有效孔径, 进而提高了伪协方差矩阵奇异值分解后信号奇异值与噪声奇异值的差异程度。 在此基础上, 利用 Otsu 类间方差法对信号奇异值与噪声奇异值进行分类。 仿真结果表明, 该方法可进一步提高信源数的估 计成功概率。

Number Estimation of Signals Based on Otsu Class Variance with Pseudocovariance Matrix

In order to improve the success probability of number estimation of signals in the presence of color noise, an Otsu method based on pseudocovariance matrix is proposed. The pseudocovariance matrix composed of delay correlation of array output signals is immune to white Gaussian noise and colored Gaussian noise under certain conditions. The array's effective aperture is improved by using the time correlation between arrays, and then the differences between signal singular values and noise singular values, which are obtained from the singular value decomposition of pseudocovariance matrix, are also improved. And by utilizing Otsu method to classify the signal singular values and noise singular values, the probability of successful estimation of source number is further improved.