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Robust auxiliary particle filters using multiple importance sampling
Linköping University, Department of Science and Technology, Media and Information Technology. Linköping University, The Institute of Technology. (Datorgrafik och bildbehandling)
Uppsala Universitet, Sweden. (Information Technology)
2014 (English)In: Proceedings of the 2014 IEEE Statistical Signal Processing Workshop, IEEE , 2014, 268-271 p.Conference paper, Published paper (Refereed)
Abstract [en]

A poor choice of importance density can have detrimental effect on the efficiency of a particle filter. While a specific choice of proposal distribution might be close to optimal for certain models, it might fail miserably for other models, possibly even leading to infinite variance. In this paper we show how mixture sampling techniques can be used to derive robust and efficient particle filters, that in general performs on par with, or better than, the best of the standard importance densities. We derive several variants of the auxiliary particle filter using both random and deterministic mixture sampling via multiple importance sampling. The resulting robust particle filters are easy to implement and require little parameter tuning.

Place, publisher, year, edition, pages
IEEE , 2014. 268-271 p.
National Category
Signal Processing
Identifiers
URN: urn:nbn:se:liu:diva-107134DOI: 10.1109/SSP.2014.6884627ISI: 000361019700068ISBN: 978-1-4799-4975-5 (print)OAI: oai:DiVA.org:liu-107134DiVA: diva2:722010
Conference
2014 IEEE Statistical Signal Processing Workshop (SSP), 29 June - 02 July 2014, Gold Coast, Australia
Projects
VPSCADICS
Available from: 2014-06-05 Created: 2014-06-05 Last updated: 2015-10-20Bibliographically approved

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Kronander, Joel

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CiteExportLink to record
Permanent link

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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