Application of improved particle swarm optimization algorithm in TDOA

被引:4
|
作者
Liang, Zhen-dong [1 ]
Yi, Wen-jun [1 ]
机构
[1] Nanjing Univ Sci & Technol, Natl Key Lab Transient Phys, Nanjing 210094, Peoples R China
关键词
Classical particle - Complex environments - Improved particle swarm optimization algorithms - Location accuracy - Location algorithms - Location technology - Nonlinear optimization problems - Sound source location - Time-differences;
D O I
10.1063/5.0082778
中图分类号
TB3 [工程材料学];
学科分类号
0805 ; 080502 ;
摘要
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. (c) 2022 Author(s). All article content, except where otherwise noted, is licensed under a Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/).
引用
收藏
页数:4
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