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.

中文翻译：

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使用粒子群优化优化有效声速的长基线系统的改进

摘要 在长基线（LBL）定位系统中，声速不确定导致的误差是影响其定位精度的主要因素。本研究通过设置声波信号在目标与不同声速的不同水听器之间传播，利用粒子群优化算法求解多参数优化问题，得到声速来解决该问题。仿真结果表明，与现有算法相比，所提算法能够有效提高LBL系统的定位精度，并且计算效率足够高。