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The Rao-Blackwellized Particle Filter: A Filter Bank Implementation
German Research Centre for Artificial Intelligence, Germany.ORCID iD: 0000-0002-1971-4295
Swedish Defence Research Agency, Sweden.
Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, The Institute of Technology.
2010 (English)In: EURASIP Journal on Advances in Signal Processing, ISSN 1687-6172, E-ISSN 1687-6180, Vol. 2010, no 724087Article in journal (Refereed) Published
Abstract [en]

For computational efficiency, it is important to utilize model structure in particle filtering. One of the most important cases occurs when there exists a linear Gaussian substructure, which can be efficiently handled by Kalman filters. This is the standard formulation of the Rao-Blackwellized particle filter (RBPF). This contribution suggests an alternative formulation of this well-known result that facilitates reuse of standard filtering components and which is also suitable for object-oriented programming. Our RBPF formulation can be seen as a Kalman filter bank with stochastic branching and pruning.

Place, publisher, year, edition, pages
Hindawi Publishing Corporation, 2010. Vol. 2010, no 724087
Keyword [en]
Particle filtering, Kalman filtre, Rao-Blackwellized particle filter, Gaussian
National Category
Control Engineering
URN: urn:nbn:se:liu:diva-67731DOI: 10.1155/2010/724087ISI: 000289090900001OAI: diva2:412640
Available from: 2011-04-26 Created: 2011-04-26 Last updated: 2015-09-22

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