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Estimating Mean Frequency for Narrowband Lowpass Signals by Pisarenko Harmonic Decomposition

机译:Pisarenko谐波分解估计窄带低通信号的平均频率

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This paper presents a mean frequency estimation method for narrowband lowpass signals. The fundamental idea of this method is that the single frequency approximation for a narrowband lowpass signal embedded in white noise using Pisarenko harmonic decomposition (PHD) algorithm is approximately the power-weighted mean frequency of the signal. In this method, Fourier transform as an indispensable processing link in the conventional power spectrum estimation is given up as well as the convolution effects between the real frequency spectrum and the frequency spectrum of data intercepting window function caused by limited data length are excluded. Experimental results show that the PHD method outperforms the commonly used mean frequency estimation method based on Fourier transform.
机译:本文介绍了窄带低通信号的平均频率估计方法。该方法的基本思想是使用Pisarenko谐波分解(PHD)算法嵌入白噪声中的窄带低通信号的单频近似值大约是信号的功率加权平均频率。在该方法中,作为传统功率谱估计中的不可或缺的处理链路,给出傅里叶变换以及由有限数据长度引起的数据拦截窗口函数的实际频谱和频谱之间的卷积效果。实验结果表明,PHD方法优于基于傅里叶变换的常用均值估计方法。

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