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Estimation of Markovian Jump Systems with Unknown Transition Probabilities through Bayesian Sampling

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Numerical Methods and Applications (NMA 2002)

Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 2542))

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Abstract

Addressed is the problem of state estimation for dynamic Markovian jump systems (MJS) with unknown transitional probability matrix (TPM) of the embedded Markov chain governing the system jumps. Based on recent authors’ results, proposed is a new TPMestimation algorithm that utilizes stochastic simulation methods (viz. Bayesian sampling) for finite mixtures’ estimation. Monte Carlo simulation results of TMP-adaptive interacting multiple model algorithms for a system with failures and maneuvering target tracking are presented.

Research Supported in part by ONR grant N00014-00-1-0677, NSF grant ECS- 9734285, NASA/LEQSF grant (2001-4)-01, Center of Excellence BIS21 grant ICA1- 2000-70016, and Bulgarian NSF grant I-1202/02

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Author information

Authors and Affiliations

  1. Department of Electrical Engineering, University of New Orleans, 70148, New Orleans, LA, USA

    Vesselin P. Jilkov & X. Rong Li

  2. Central Laboratory for Parallel Processing, Bulgarian Academy Of Sciences, 25A Acad. G. Bonchev St, 1113, Sofia, Bulgaria

    Donka S. Angelova

Authors
  1. Vesselin P. Jilkov
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  2. X. Rong Li
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  3. Donka S. Angelova
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Editor information

Editors and Affiliations

  1. Central Laboratory for Parallel Processing, Bulgarian Academy of Sciences, Acad. G. Bonchev, bl. 25A, 1113, Sofia, Bulgaria

    Ivan Dimov , Ivan Lirkov  & Svetozar Margenov ,  & 

  2. National Environmental Research Institute, Frederiksborgvej 399, P.O. Box 358, 4000, Roskilde, Denmark

    Zahari Zlatev

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© 2003 Springer-Verlag Berlin Heidelberg

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Jilkov, V.P., Li, X.R., Angelova, D.S. (2003). Estimation of Markovian Jump Systems with Unknown Transition Probabilities through Bayesian Sampling. In: Dimov, I., Lirkov, I., Margenov, S., Zlatev, Z. (eds) Numerical Methods and Applications. NMA 2002. Lecture Notes in Computer Science, vol 2542. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-36487-0_34

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  • DOI: https://doi.org/10.1007/3-540-36487-0_34

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  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-00608-4

  • Online ISBN: 978-3-540-36487-0

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