Contributions to Proceedings:
O. Hlinka, F. Hlawatsch, P. Djuric:
"Likelihood Consensus-Based Distributed Particle Filtering with Distributed Proposal Density Adaptation";
in: "Proc. IEEE ICASSP 2012",
issued by: IEEE;
We present a consensus-based distributed particle filter (PF) for
wireless sensor networks. Each sensor runs a local PF to compute a
global state estimate that takes into account the measurements of all
sensors. The local PFs use the joint (all-sensors) likelihood function, which is calculated in a distributed way by a novel generalization of the likelihood consensus scheme. A performance improvement (or a reduction of the required number of particles) is achieved by a novel distributed, consensus-based method for adapting the proposal densities of the local PFs. The performance of the proposed distributed PF is demonstrated for a target tracking problem.
distributed particle filter, likelihood consensus, distributed proposal density adaptation, target tracking, wireless sensor network
Electronic version of the publication:
Created from the Publication Database of the Vienna University of Technology.