Decentralization of Particle Filters Using Arbitrary State Decomposition
2010 (English)In: Proceedings of the 49th IEEE Conference on Decision and Control, 2010, 7383-7388 p.Conference paper (Refereed)
In this paper, a new particle filter (PF) which we refer to as the decentralized PF (DPF) is proposed. By first decomposing the state into two parts, the DPF splits the filtering problem into two nested sub-problems and then handles the two nested sub-problems using PFs. The DPF has an advantage over the regular PF that the DPF can increase the level of parallelism of the PF. In particular, part of the resampling in the DPF bears a parallel structure and thus can be implemented in parallel. The parallel structure of the DPF is created by decomposing the state space, differing from the parallel structure of the distributed PFs which is created by dividing the sample space. This difference results in a couple of unique features of the DPF in contrast with the existing distributed PFs. Simulation results from a numerical example indicates that the DPF has a potential to achieve the same level of performance as the regular PF, in a shorter execution time.
Place, publisher, year, edition, pages
2010. 7383-7388 p.
Particle ﬁltering, Parallel algorithms, Nonlinear system, State estimation
IdentifiersURN: urn:nbn:se:liu:diva-63596DOI: 10.1109/CDC.2010.5717025ISBN: 978-1-4244-7745-6OAI: oai:DiVA.org:liu-63596DiVA: diva2:380831
49th IEEE Conference on Decision and Control, Atlanta, GA, USA, 15-17 December, 2010
FunderSwedish Research CouncilSwedish Foundation for Strategic Research