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Autonomous underwater vehicles localisation in mobile underwater networks

Authors: Xiaohui Wei 0002; Xingwang Wang 0003; Xin Bai 0004; Sen Bai; Jun Liu 0006;

Autonomous underwater vehicles localisation in mobile underwater networks

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.

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Found an issue? Give us feedback
selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
8
Top 10%
Average
Top 10%
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