Application of simulated annealing particle swarm optimization in underwater acoustic positioning optimization

Abstract

In the calculation of underwater acoustic positioning, the errors of element position measurement, time delay measurement, attitude accuracy and sound velocity measurement will lead to the calculation errors of final positioning solution. The optimization method of solution is also one of the key technologies of location solution. The traditional statistical methods of solution mostly use arithmetic average optimization method and Newton iteration method. In this paper, the particle swarm optimization method based on simulated annealing is used to improve the estimation accuracy of location solution. The effectiveness of this method is verified by computer simulation and comparative analysis. First, the spherical intersection method of synchronous positioning and the hyperbolic intersection method of asynchronous positioning are introduced in this paper. Then, the method of measuring time delay and filtering signal is introduced. Finally, another factor affecting positioning accuracy is discussed. The method of solving non-linear equation is discussed. By comparing the root mean square error of three methods under different signal-to-noise ratios, the signal-to-noise ratio is obtained. The accuracy of the three algorithms is almost the same when compared with each other, but at low SNR, the simulated annealing particle swarm optimization (SA-PSO) algorithm can calculate more accurate positioning solutions.