Expectation Maximization Time Delay Estimation Algorithm Based on Wavelet Singular Feature Constraint

doi:10.12382/bgxb.2022.1078

Abstract

Abstract:

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.

Key words: low signal-to-noise ratio, non-stationary signal, wavelet singularity, expectation maximization, time delay estimation

CLC Number:

TN911.7

ZHU Xiaoting, ZHANG Jun, WANG Lu, CHEN Zhifei, BAO Ming, WANG Yi. Expectation Maximization Time Delay Estimation Algorithm Based on Wavelet Singular Feature Constraint[J]. Acta Armamentarii, 2024, 45(4): 1108-1116.

Figures/Tables 10

Fig.1 Decomposition results on different scales

Fig.2 Algorithm steps of expectation maximization time delay estimation based on wavelet singular feature constraint

Fig.3 Results from different wavelet scales

Fig.4 Mean square error of algorithms

Fig.5 Absolute error of algorithms

Fig.6 Mean square error of algorithms and CRLB

Fig.7 Algorithmic effective estimation success rate

Fig.8 Distribution map of microphones

Fig.9 Comparison of mean square errors of different algorithms

Fig.10 Comparison of operation time of different algorithms

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