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.
Research supported in part by the Bulgarian Foundation for Scientific Investigations: I-1202/02,I-1205/02,MI-1506/05 and by Center of Excellence BIS21++, 016639.
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Angelova, D., Mihaylova, L. (2006). A Monte Carlo Algorithm for State and Parameter Estimation of Extended Targets. In: Alexandrov, V.N., van Albada, G.D., Sloot, P.M.A., Dongarra, J. (eds) Computational Science – ICCS 2006. ICCS 2006. Lecture Notes in Computer Science, vol 3993. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11758532_82
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DOI: https://doi.org/10.1007/11758532_82
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