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Estimating number of sub-Gaussian emitters in a narrowband DOA estimation problem by using independent component analysis

机译:使用独立分量分析估计窄带DOA估计问题中的次高斯发射器数量

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Accurate determination of the number of emitters is an important and nontrivial problem in direction of arrival (DOA) estimation. The energy criterion based on singular values of the sampled data covariance matrix requires either a-priori knowledge of the signal-to-noise ratio (SNR) or the noise energy itself. More refined approaches, such as the Akaike information criterion (AIC) and the minimum description length (MDL) criterion fail when the signals are non-Gaussian. Thus, they are inapplicable to DOA estimation of communication signals, which generally tend to be non-Gaussian. The presented approach is based on independent component analysis (ICA). The information bearing source signals, obtained by blind source separation (BSS), are identified through measuring their distance from Gaussianity. A fixed threshold parameter in the kurtosis domain is used which can be set to accommodate a wide range of SNRs and data sample sizes.
机译:在到达方向(DOA)估计中,准确确定发射器的数量是一个重要且重要的问题。基于采样数据协方差矩阵奇异值的能量标准要求先验了解信噪比(SNR)或噪声能量本身。当信号为非高斯信号时,诸如Akaike信息标准(AIC)和最小描述长度(MDL)标准之类的更精细的方法将失败。因此,它们不适用于通常倾向于非高斯的通信信号的DOA估计。提出的方法基于独立成分分析(ICA)。通过测量盲源分离(BSS)获得的信息承载源信号,可以测量它们与高斯的距离。使用峰度域中的固定阈值参数,可以将其设置为适应宽范围的SNR和数据样本大小。

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