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Sensor fusion-based dynamic positioning of ships using Extended Kalman and Particle Filtering

Published online by Cambridge University Press:  01 August 2012

Gerasimos G. Rigatos
Gerasimos G. Rigatos*
Affiliation:
Department of Engineering, Harper-Adams University College, TF10 8NB, Shropshire, UK Unit of Industrial Automation, Industrial Systems Institute, 26504 Rion Patras, Greece
*
*Corresponding author. E-mail: grigat@ieee.org
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Summary

The paper examines the problem of dynamic ship positioning with the use of Kalman Filter- and Particle Filter-based sensor fusion algorithms. The proposed approach enables to estimate accurately the ship's state vector by fusing the vessel's position and heading measurements coming from on-board sensors together with distance measurements coming from sensors located at the coast (e.g. radar). The estimated state vector is used in turn, in a control loop, to regulate the horizontal position and heading of the vessel. The performance of dynamic positioning of the ship based on Kalman and Particle Filtering is evaluated through simulation experiments.

Keywords

Kalman FilteringParticle FilteringSensor fusionDynamic ship positioningDisturbance rejection
Type
Articles
Information
Robotica , Volume 31 , Issue 3 , May 2013 , pp. 389 - 403
Copyright
Copyright © Cambridge University Press 2012

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