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On Resampling Algorithms for Particle Filters
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.
Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, The Institute of Technology.
2006 (English)In: Proceedings of the 2006 IEEE Nonlinear Statistical Signal Processing Workshop, 2006, 79-82 p.Conference paper, Published paper (Refereed)
Abstract [en]

In this paper a comparison is made between four frequently encountered resampling algorithms for particle filters. A theoretical framework is introduced to be able to understand and explain the differences between the resampling algorithms. This facilitates a comparison of the algorithms with respect to their resampling quality and computational complexity. Using extensive Monte Carlo simulations the theoretical results are verified. It is found that systematic resampling is favourable, both in terms of resampling quality and computational complexity.

Place, publisher, year, edition, pages
2006. 79-82 p.
Keyword [en]
Resampling, Particle filter
National Category
Engineering and Technology Control Engineering
Identifiers
URN: urn:nbn:se:liu:diva-74546DOI: 10.1109/NSSPW.2006.4378824ISBN: 978-1-4244-0581-7 (print)OAI: oai:DiVA.org:liu-74546DiVA: diva2:487845
Conference
2006 IEEE Nonlinear Statistical Signal Processing Workshop, Cambridge, UK, September, 2006
Available from: 2012-02-01 Created: 2012-02-01 Last updated: 2013-02-26

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Hol, JeroenSchön, ThomasGustafsson, Fredrik

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