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Particle Filtering for Quantized Sensor Information
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.
2005 (English)Report (Other academic)
Abstract [en]

The implication of quantized sensor information on filtering problems is studied. The Cramer-Rao lower bound (CRLB) is derived for estimation and filtering on quantized data. A particle filter (PF) algorithm that approximates the optimal nonlinear filter is provided, and numerical experiments show that the PF attains the CRLB, while second-order optimal Kalman filter (KF) approaches can perform quite bad.

Place, publisher, year, edition, pages
Linköping: Linköping University Electronic Press, 2005. , 6 p.
Series
LiTH-ISY-R, ISSN 1400-3902 ; 2700
Keyword [en]
Cramér-Rao lower bound, Particle filter, Kalman filter
National Category
Control Engineering
Identifiers
URN: urn:nbn:se:liu:diva-56037ISRN: LiTH-ISY-R-2700OAI: oai:DiVA.org:liu-56037DiVA: diva2:316909
Available from: 2010-04-30 Created: 2010-04-30 Last updated: 2014-08-12Bibliographically approved

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Karlsson, RickardGustafsson, Fredrik

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CiteExportLink to record
Permanent link

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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