Node Selection Algorithm for Underwater Acoustic Sensor Network Based on Particle Swarm Optimization

Abstract

Underwater target positioning technology is the most important part of UnderWater Acoustic Sensor Network(called UWASN), and it is one of the most important research directions in this field with broad application prospects in commercial and military fields. Due to the complex and variability of underwater acoustic environment, the underwater acoustic sensor network has the characteristics of fluidity, sparse deployment and energy limitation, which brings certain challenges to underwater positioning technology. Aiming at the scenario that the node redundancy in the underwater acoustic sensor network leads to low positioning efficiency, this paper considers the sound velocity correction factor based on the traditional anchor node selection algorithm in this paper. Under the premise of ensuring certain positioning accuracy, considering the communication overhead, node residual energy, position suspiciousness, sound ray propagation bending characteristics and other factors, the anchor node optimization mechanism which uses the particle swarm algorithm to iterate out the optimal sensor combination for improving the accuracy of positioning is designed. The simulation results show that the proposed algorithm shows small calculation, fast convergence and high positioning accuracy. It can effectively improve the energy utilization of nodes, balance positioning performance as well as energy use efficiency, and optimize the positioning result of UWASN, which is well suited for underwater acoustic positioning scenarios.