Sciweavers

Share
ICASSP
2011
IEEE

Distributed Gaussian particle filtering using likelihood consensus

8 years 2 days ago
Distributed Gaussian particle filtering using likelihood consensus
We propose a distributed implementation of the Gaussian particle filter (GPF) for use in a wireless sensor network. Each sensor runs a local GPF that computes a global state estimate. The updating of the particle weights at each sensor uses the joint likelihood function, which is calculated in a distributed way, using only local communications, via the recently proposed likelihood consensus scheme. A significant reduction of the number of particles can be achieved by means of another consensus algorithm. The performance of the proposed distributed GPF is demonstrated for a target tracking problem.
Ondrej Hlinka, Ondrej Sluciak, Franz Hlawatsch, Pe
Added 20 Aug 2011
Updated 20 Aug 2011
Type Journal
Year 2011
Where ICASSP
Authors Ondrej Hlinka, Ondrej Sluciak, Franz Hlawatsch, Petar M. Djuric, Markus Rupp
Comments (0)
books