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首页> 外文期刊>Applied Computational Electromagnetics Society journal >Source Enumeration Method Combining Gerschgorin Circle Transform and Generalized Bayesian Information Criterion in Large-scale Antenna Array
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Source Enumeration Method Combining Gerschgorin Circle Transform and Generalized Bayesian Information Criterion in Large-scale Antenna Array

机译：源枚举方法组合Gerschgorin Circle变换和大规模天线阵列中的广义贝叶斯信息标准

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摘要

A new source enumeration method based on gerschgorin circle transform and generalized Bayesian information criterion is devised, for the case that the antenna array observed signals are overlapped with spatial colored noise, and the number of antennas compared with that of snapshots meet the requirement of general asymptotic regime. Firstly, the sample covariance matrix of the observed signals is calculated, and then gerschgorin circle transformation is carried out on the sample covariance matrix. With the help of the more obvious distinction between the transformed signal gerschgorin circle radius and the noise gerschgorin circle radius, the observation statistic used to establish the likelihood function of the information theoretic criterion is constructed, by using the estimated values of the transformed sample covariance matrix's eigenvalues, and according to the idea of corrected Rao's score test, the observed statistics used to establish the likelihood function of the ITC are constructed. Based on the statistics, the source number is estimated by employing the generalized Bayesian information criterion (GBIC). The effectiveness of the proposed method is validated by experiments. Compared with the information theoretic criterion (ITC) methods and gerschgorin circle method (GDE), in Gaussian white noise, at the time M/N = 1, that is the relationship between the number of antennas and that of snapshots meets the requirement of the general asymptotic regime, the proposed method can accurately estimate the source number with 100% probability, the other methods failed. Compared with the ITC methods based on eigenvalue diagonal loading and GDE, in colored noise, at the time M/N = 1, the proposed method can accurately estimate the source number with 100% probability, the other methods failed. Compared with the methods based on random matrix theory, in colored noise, the proposed method can estimate the source number with 100% probability, but the estimation of other methods failed. The proposed method has wide applicability, in terms of the relationship between the numbers of antennas and snapshots, it is suitable for both general asymptotic regime and classical asymptotic system, and in terms of noise characteristics, it is suitable for both Gaussian white noise environment and colored noise environment.
机译：设计了一种基于GERSchgorin圆变换和广义贝叶斯信息标准的新的源枚举方法，对于天线阵列观察信号与空间彩色噪声重叠，与快照相比的天线数量满足一般渐近的要求政权。首先，计算观察信号的样本协方差矩阵，然后在样本协方差矩阵上进行Gerschgorin圆形变换。借助于转换信号Gerschgorin圆半径和噪声Gerschgorin圆半径的更明显的区别，通过使用变换样本协方差矩阵的估计值来构造用于建立信息理论标准的似然函数的观察统计特征值，并根据纠正RAO的得分测试的想法，构建了用于建立ITC的似然函数的观察到的统计数据。基于统计数据，通过采用广义贝叶斯信息标准（GBIC）来估算源号码。通过实验验证了所提出的方法的有效性。与信息理论标准（ITC）方法和Gerschgorin圈法（GDE）相比，在高斯白噪声中，在时间m / n> = 1，即天线数与快照的关系符合要求一般渐近制度，所提出的方法可以准确估计100％概率的源数字，其他方法失败。与基于特征值对角线加载和GDE的ITC方法相比，在彩色噪声中，在时间m / n> = 1时，所提出的方法可以准确地估计100％概率的源数字，其他方法失败。与基于随机矩阵理论的方法相比，在彩色噪声中，所提出的方法可以估计100％概率的源数字，但其他方法的估计失败。所提出的方法具有广泛的适用性，就天线和快照之间的关系而言，它适用于一般渐近政权和经典渐近系统，以及在噪声特性方面，它适用于高斯白噪声环境和彩色噪声环境。

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