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Fusion of Data from Different Sources
Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, The Institute of Technology.
2009 (English)Report (Other academic)
Abstract [en]

The use of data from different, often complementary sources in order to obtain a better estimate of the state of the system under consideration has recently become very popular within many scientific areas. We will in this talk provide a framework, including the popular Kalman and particle filters for fusing data from different, complementary sources. The theory will be illustrated using several application examples from the automotive and the aerospace industry. Possible applications for 3D analysis of human motion will be discussed.

Place, publisher, year, edition, pages
Linköping: Linköping University Electronic Press, 2009. , 3 p.
Series
LiTH-ISY-R, ISSN 1400-3902 ; 2874
Keyword [en]
Sensor fusion, Nonlinear estimation, Kalman filter, Particle filter
National Category
Control Engineering
Identifiers
URN: urn:nbn:se:liu:diva-56190ISRN: LiTH-ISY-R-2874OAI: oai:DiVA.org:liu-56190DiVA: diva2:316981
Available from: 2010-04-30 Created: 2010-04-30 Last updated: 2014-10-01Bibliographically approved

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Schön, Thomas

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Automatic ControlThe Institute of Technology
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CiteExportLink to record
Permanent link

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Citation style
  • apa
  • harvard1
  • ieee
  • modern-language-association-8th-edition
  • vancouver
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  • 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