An evaluation of deep water navigation systems for autonomous underwater vehicles

Costanzi, Riccardo; Fenucci, Davide; Giagnoni, Simone; Munafo, Andrea; Caiti, Andrea. 2017 An evaluation of deep water navigation systems for autonomous underwater vehicles. IFAC-PapersOnLine, 50 (1). 13680-13685. https://doi.org/10.1016/j.ifacol.2017.08.2532

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Official URL: http://dx.doi.org/10.1016/j.ifacol.2017.08.2532

Abstract/Summary

The navigation system is a crucial element of the control chain of an Autonomous Underwater Vehicle (AUV) because of the unavailability of a reliable positioning system such as the Global Positioning System (GPS). High performance navigation capabilities are ensured by equipping vehicles with high grade INS (Inertial Navigation System) aided by a Doppler Velocity Log (DVL) among other sensors. For its nature, a DVL can work only within a limited range from the bottom precluding its use for deep water applications. This work analyses two different approaches to address the problem of deep water navigation. The first one is based on measurements of relative distance between different nodes (cooperating vehicles and a static gateway buoy) that constitute an acoustic underwater network. The second one is based on the data from a positioning system (the HiPAP system by Kongsberg) that is mounted on the support ship and that has a limited operational range. Results from the two approaches are evaluated based on the data collected during the COLLAB NGAS14 experimental campaign and processed off-line. The results have to be intended as a preliminary work towards the integration of several complementary methods within a unique navigation system capable of exploiting the different technologies towards robust and reliable deep water navigation capabilities.

Item Type:	Publication - Article
Digital Object Identifier (DOI):	https://doi.org/10.1016/j.ifacol.2017.08.2532
ISSN:	24058963
Date made live:	06 Mar 2018 16:34 +0 (UTC)
URI:	https://nora.nerc.ac.uk/id/eprint/519484

Item Type:

Publication - Article

Digital Object Identifier (DOI):

https://doi.org/10.1016/j.ifacol.2017.08.2532

ISSN:

24058963

Date made live:

06 Mar 2018 16:34 +0 (UTC)

URI:

https://nora.nerc.ac.uk/id/eprint/519484