AIP Advances (Feb 2022)

Application of improved particle swarm optimization algorithm in TDOA

  • Zhen-dong Liang,
  • Wen-jun Yi

DOI
https://doi.org/10.1063/5.0082778
Journal volume & issue
Vol. 12, no. 2
pp. 025304 – 025304-4

Abstract

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In order to improve the location accuracy of passive sound source location technology in a complex environment, an improved particle swarm optimization algorithm is proposed. Aiming at the nonlinear optimization problem in the time difference of the arrival location algorithm, based on the classical particle swarm optimization algorithm, combined with the fitness function and the method of adaptive changing parameters, the improved particle swarm optimization algorithm can not only effectively solve the problem that particle swarm optimization is sour and easy to fall into local optimization but also accurately locate the position of the passive sound source. The feasibility and stability of the algorithm are verified by actual simulation.