An Acoustic Signal Delay Estimation Method Based on Phase Difference and Maximum Likelihood Estimation

Abstract

The invention belongs to the technical field of wireless monitoring, and discloses a sound signal time delay estimation method based on a phase difference and maximum likelihood estimation. The methodcomprises the steps that in a noise background, signals are acquired by a sound sensor array and preprocessed through a cross-correlation function and short-time Fourier transform to obtain frequencydomain signals; the relative phase ratios of two sound signals are calculated, and the probabilities of all possible time delay estimation values are obtained by combining the principle of a maximumlikelihood estimation algorithm; and on the condition of not relying on signal and noise prior knowledge, the time delay value corresponding to a maximum probability peak value is taken as the final time delay estimation value. According to the sound signal time delay estimation method, the time difference of arrival (TDOA) of a sound source can be precisely estimated; 10 groups of data with the length of 1,024 sampling points are acquired, the mean square errors of the delay time are calculated when 0.0029 s, 0.0059 s, 0.0088 s and 0.0118 s are delayed respectively, and it can be seen that the method has the high accuracy through the diagram 1 and the diagram 2.

Description

technical field [0001] The invention belongs to the technical field of wireless monitoring, in particular to an acoustic signal delay estimation method based on phase difference and maximum likelihood estimation. Background technique [0002] Target passive positioning technology has been a hot issue in the field of wireless monitoring and has been widely used in military monitoring, environmental monitoring, emergency rescue and disaster relief. The passive target itself does not emit electromagnetic waves and has high concealment. Therefore, it is very necessary to study the accurate passive target positioning scheme. At present, the positioning technology based on geometric parameter optimization has been studied at home and abroad, which can be mainly divided into four categories based on time of arrival TOA, time difference of arrival TDOA, angle of arrival AOA, and received signal strength RSS. Time of Arrival TOA positioning technology estimates the target position b...

AI Technical Summary

Problems solved by technology

[0003] To sum up, the problems existing in the existing technology are: the current target passive positioning method has high computational complexity, and it is impossible to estimate the position of the target in real time and realize the target tracking for the moving target.

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