Electronic Science and Technology ›› 2023, Vol. 36 ›› Issue (9): 21-28.doi: 10.16180/j.cnki.issn1007-7820.2023.09.004

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TDOA Sound Source Localization Method Based on Particle Swarm Optimization Algorithm

ZHANG Dagui1,ZHOU Zhifeng1,ZHANG Yi2,WANG Liduan3   

  1. 1. School of Mechanical and Automotive Engineering,Shanghai University of Engineering Science,Shanghai 201620,China
    2. Shanghai Songjiang Xinqiao Vocational and Technical School,Shanghai 201612,China
    3. Shanghai Compass Satellite Navigation Technology Co.,Ltd., Shanghai 201801,China
  • Received:2022-04-19 Online:2023-09-15 Published:2023-09-18
  • Supported by:
    Scientific Research Fund of Science and Technology Commission of Shanghai Municipality(17511106700)

Abstract:

In order to solve the problem of 3D coordinate estimation of sound source based on planar microphone array, this study introduces particle swarm optimization algorithm in TDOA(Time Difference of Arrival) sound source localization algorithm. The true value of the delay difference is calculated using the generalized cross-correlation method of the PHAT(Phase Transform) weighting function. Combined with the coordinate position of the microphone, the estimated value of the delay difference between the hypothetical sound source arriving at the microphone is calculated through the geometric relationship. The sum of the squares of the error between the actual value and the estimated value of the design delay is the particle fitness function. The particle swarm optimization algorithm is used to search for the sound source points in the space that conform to the fitness function, so as to realize the sound source position estimation. The simulation results show that the proposed algorithm has better robustness and noise resistance than the spherical interpolation method when the calculation speed is similar to that of the spherical interpolation method.

Key words: microphone array, particle swarm optimization algorithm, TDOA, sound source localization, delay estimation, location estimation, generalized cross correlation, spherical interpolation method

CLC Number: 

  • TP912