A monte carlo algorithm for state and parameter estimation of extended targets

Authors:
Donka Angelova;Lyudmila Mihaylova
Affiliations:
Institute for Parallel Processing, Bulgarian Academy of Sciences, Sofia, Bulgaria;Department of Communication Systems, Lancaster University, Lancaster, UK
Venue:
ICCS'06 Proceedings of the 6th international conference on Computational Science - Volume Part III
Year:
2006

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Abstract

This paper considers the joint state and parameter estimation of extended targets. Both the target kinematic states, position and speed, are estimated with the target extent parameters. The developed algorithm is applied to a ship, whose shape is modelled by an ellipse. A Bayesian sampling algorithm with finite mixtures is proposed for the evaluation of the extent parameters whereas a suboptimal Bayesian interacting multiple model (IMM) filter estimates the kinematic parameters of the maneuvering ship. The algorithm performance is evaluated by Monte Carlo comparison with a particle filtering approach.