An Improvement of Long Baseline System Using Particle Swarm Optimization to Optimize Effective Sound Speed

Abstract

In long baseline (LBL) positioning system, errors due to uncertain sound speed are the major facts to its positioning accuracy. In this study, the problem is solved by setting acoustic signal travels between the target and different hydrophones with different sound speed and using particle swarm optimization algorithm to solve the multi-parameter optimization problem to obtain the sound speeds. Presented simulation results show that the proposed algorithm can effectively improve the positioning accuracy of the LBL system compared to existing algorithms and its computational efficiency is high enough.

Keywords:

• Effective sound speed
• long baseline positioning system
• particle swarm optimization
• sound speed correction

Additional information

Funding

This work was supported by the National Natural Science Foundation of China (grant number 61371151).