To improve the accuracy of time delay estimation for non-stationary signals under low signal-to-noise ratio ( SNR ),an expectation maximization time delay estimation algorithm based on wavelet singular feature constraint is presented. A generalized cross-correlation matrix of the wavelet singularity feature scale is designed,and an expectation maximization model under the constraints of multiscale wavelet singularity feature is constructed. The parameter update formula is deduced,and the expectation maximization algorithm is used to iterate in parallel to obtain the adaptive scale of the signal and the optimal time delay estimate of the sound source signal at the maximum singularity significance. The simulated and experimental results show that the proposed algorithm has higher accuracy of time delay estimation than the traditional generalized cross-correlation time delay estimation algorithm and the improved algorithm under low signal-to-noise ratio,and effectively improves the estimation success rate within the error constraints.
维普
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