A Robust Particle Filter for State Estimation - with Convergence Results
2007 (English)Report (Other academic)
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
Linköping: Linköping University Electronic Press, 2007. , 8 p.
LiTH-ISY-R, ISSN 1400-3902 ; 2822
Nonlinear lters, particle lter, convergence, dynamic systems
IdentifiersURN: urn:nbn:se:liu:diva-56141ISRN: LiTH-ISY-R-2822OAI: oai:DiVA.org:liu-56141DiVA: diva2:316958