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Development of error reduction model using Bayesian filter for AUV navigating under moving ice

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Hwang, J, Fan, S ORCID: 0000-0002-1865-9730, King, P ORCID: 0000-0001-9436-0936 and Forrest, A 2018 , 'Development of error reduction model using Bayesian filter for AUV navigating under moving ice', in Proceedings of the 2018 IEEE OES Autonomous Underwater Vehicle Symposium , IEEE, United States, pp. 1-6 .

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Abstract

Doppler Velocity Logs (DVL) can provide a simpleunder water navigation aid for Autonomous UnderwaterVehicles (AUV) by measuring relative velocities with respect tothe speed over ground. A valid reference velocity is difficult tocalculate when this approach is applied under a moving frame ofreference such as drifting ice. The primary challenge of under-icelocalization is to accurately estimate the AUV location and itstrajectory in the global coordinate system when DVLmeasurements are being made relative to a constantly drifting icesurface. In this paper, the author introduces and compares twotypes of error sources, scale factor error of DVL and navigationerror due to ice drift. An error reduction model using a Bayesianfilter algorithm is developed for improved estimations, inconjunction with a novel correction method for accurate AUVnavigation under ice. The concept of shift factor is introduced inthis paper as the key to solve both error sources. Having theknowledge of the true beacon location, shift factors in vectorquantity are extracted based on the collected relative velocityprofiles by DVL. The shift factors are directly applied to updatethe final AUV location. The result presents approximately 70.8%of maximum error reduction. The impact of survey pattern,bearing angle to the beacon, pinging frequency on the accuracyof the vehicle localisation are discussed.

Item Type: Conference Publication
Authors/Creators:Hwang, J and Fan, S and King, P and Forrest, A
Keywords: autonomous underwater vehicle, control and estimation, path planning and navigation, under-ice AUV navigation, Doppler Velocity Logs (DVLs), acoustic positioning system, single beacon, moving frame of reference, Bayesian filter algorithm, shift fact
Journal or Publication Title: Proceedings of the 2018 IEEE OES Autonomous Underwater Vehicle Symposium
Publisher: IEEE
Copyright Information:

Copyright 2018 IEEE

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