Estimating Mean Frequency for Narrowband Lowpass Signals by Pisarenko Harmonic Decomposition

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.