Title: Autonomous underwater vehicles localisation in mobile underwater networks

Authors: Xiaohui Wei; Xingwang Wang; Xin Bai; Sen Bai; Jun Liu

Addresses: College of Computer Science and Technology, Jilin University, No. 2699, Qianjin Street, Changchun, 130012, China ' College of Computer Science and Technology, Jilin University, No. 2699, Qianjin Street, Changchun, 130012, China ' College of Computer Science and Technology, Jilin University, No. 2699, Qianjin Street, Changchun, 130012, China ' College of Computer Science and Technology, Jilin University, No. 2699, Qianjin Street, Changchun, 130012, China ' College of Computer Science and Technology, Jilin University, No. 2699, Qianjin Street, Changchun, 130012, China

Abstract: Autonomous underwater vehicles (AUVs) form mobile underwater networks to conduct underwater surveying missions cooperatively. Due to the severe turbulence caused by water currents, individual AUV has to adjust its heading constantly to ensure reaching destination. The coordinated AUV network increases the size of the surveying area, but leads to bigger challenges on maintaining AUV network locations. In this paper, we consider the localisation problem for AUVs in a mobile multi-hop underwater network. In our approach, to avoid the accumulating errors caused by the inertial measurement units, we periodically re-localise the AUV network through surfacing a set of AUVs as beacons. A beacon AUV surfaces to obtain its accurate location information from external sources, such as satellites, and then submerges to adjust the locations for remaining AUVs through acoustic communication. Simulation result shows that our approach greatly improves the localisation accuracy and energy efficiency of the AUV network.

Keywords: AUVs; autonomous underwater vehicles; mobile underwater networks; AUV localisation; mobile networks; acoustic communication; simulation; localisation accuracy; energy efficiency; energy consumption; relocalisation; beacons.

DOI: 10.1504/IJSNET.2017.080664

International Journal of Sensor Networks, 2017 Vol.23 No.1, pp.61 - 71

Received: 08 Jul 2016
Accepted: 20 Jul 2016

Published online: 25 Nov 2016 *

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