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A Robust Particle Filter for State Estimation - with Convergence Results
China Jiliang University, China.
Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, The Institute of Technology.
Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, The Institute of Technology.
2007 (English)Report (Other academic)
Abstract [en]

Particle filters are becoming increasingly important and useful for state estimation in nonlinear systems. Many filter versions have been suggested, and several results on convergence of filter properties have been reported. However, apparently a result on the convergence of the state estimate itself has been lacking. This contribution describes a general framework for particle filters for state estimation, as well as a robustified filter version. For this version a quite general convergence result is established. In particular, it is proved that the particle filter estimate convergences w.p.1 to the optimal estimate, as the number of particles tends to infinity.

Place, publisher, year, edition, pages
Linköping: Linköping University Electronic Press, 2007. , 8 p.
Series
LiTH-ISY-R, ISSN 1400-3902 ; 2822
Keyword [en]
Nonlinear lters, particle lter, convergence, dynamic systems
National Category
Control Engineering
Identifiers
URN: urn:nbn:se:liu:diva-56141ISRN: LiTH-ISY-R-2822OAI: oai:DiVA.org:liu-56141DiVA: diva2:316958
Available from: 2010-04-30 Created: 2010-04-30 Last updated: 2014-10-08Bibliographically approved

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Hu, Xiao-LiSchön, ThomasLjung, Lennart

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CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • harvard1
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • oxford
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf