A Self-Localization Algorithm with Adaptive and Dynamic Observation Period for Mobile Underwater Acoustic Networks

doi:10.16183/j.cnki.jsjtu.2021.193

Abstract

Abstract:

In order to resolve the conflicts between the communication traffic and the localization accuracy, a self-localization algorithm with adaptive and dynamic observation period for mobile underwater acoustic networks (MUANs) was proposed to improve the localization performance. First, an adaptive and dynamic observation period selection scheme was designed, which could generate a non-uniform observation period vector according to the residual change. Then, based on the non-uniform observation period vector, a self-localization algorithm was proposed, which could precisely predict the trajectory of each mobile node in the network. The simulation results show that the proposed algorithm, which could balance the tradeoff between the localization accuracy and the communication cost, is more suitable for the underwater environment.

Key words: mobile underwater acoustic networks (MUANs), self-localization, adaptive and dynamic observation period

CLC Number:

TN929.3

GAO Jingjie, WANG Wei, SHEN Xiaohong. A Self-Localization Algorithm with Adaptive and Dynamic Observation Period for Mobile Underwater Acoustic Networks[J]. Journal of Shanghai Jiao Tong University, 2022, 56(12): 1658-1665.

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