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O. Hlinka, O. Sluciak, F. Hlawatsch, P. Djuric, M. Rupp:
"Distributed Gaussian particle filtering using likelihood consensus";
in: "Proc. IEEE ICASSP-11", herausgegeben von: IEEE; IEEE Xplore, Prague, Czech Republic, 2011, S. 3756 - 3759.

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.

Gaussian particle filter, distributed particle filter, likelihood consensus, target tracking, wireless sensor network

http://publik.tuwien.ac.at/files/PubDat_200987.pdf

Projektleitung Franz Hlawatsch:
Signal and Information Processing in Science and Engineering - Statistische Inferenz

Projektleitung Markus Rupp:
Signal and Information Processing in Science and Engineering - Entwicklungsmethodik