An Improved PSO Algorithm for Direction Finding with Tetrahedral-based USBL System

DOI

10.2991/caai-18.2018.31How to use a DOI?

Keywords

particle swarm optimization; ultra-short baseline; region-division; adaptive

Abstract

Aiming at the problem that the standard particle swarm optimization algorithm has a slow convergence speed and easy to fall into the local optimum, the method of region-division is introduced to dynamically adjust the inertia weight and learning factors of the particle to achieve the balance between optimization ability and convergence speed, and adaptive mutation operation are used to avoid the population falling into the local optimum. The proposed algorithm is applied to the target direction finding by a tetrahedral-based ultra-short baseline positioning system. Simulation experiments show that the proposed algorithm can effectively improve the accuracy of direction finding and achieve the purpose of accelerating the convergence of PSO algorithm.

Copyright

© 2018, the Authors. Published by Atlantis Press.

Open Access

This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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TY  - CONF
AU  - Jian Huang
AU  - Shenggang Yan
PY  - 2018/08
DA  - 2018/08
TI  - An Improved PSO Algorithm for Direction Finding with Tetrahedral-based USBL System
BT  - Proceedings of the 2018 3rd International Conference on Control, Automation and Artificial Intelligence (CAAI 2018)
PB  - Atlantis Press
SP  - 130
EP  - 136
SN  - 2589-4919
UR  - https://doi.org/10.2991/caai-18.2018.31
DO  - 10.2991/caai-18.2018.31
ID  - Huang2018/08
ER  -