A Robust Particle Filter for State Estimation - with Convergence Results
2007 (English)In: Proceedings of the 46th IEEE Conference on Decision and Control, 2007, 312-317 p.Conference paper (Refereed)
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
2007. 312-317 p.
Nonlinear estimation, Nonlinear systems, Particle filtering, State estimation
National CategoryEngineering and Technology Control Engineering
IdentifiersURN: urn:nbn:se:liu:diva-38861DOI: 10.1109/CDC.2007.4434208Local ID: 45909ISBN: 978-1-4244-1498-7ISBN: 978-1-4244-1497-0OAI: oai:DiVA.org:liu-38861DiVA: diva2:259710
46th IEEE Conference on Decision and Control, New Orleans, LA, USA, December, 2007