Graph Laplacian Distributed Particle Filtering

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Authors
  1. Rabbat, M.
  2. Coates, M.
  3. Blouin, S.
Corporate Authors
Defence Research and Development Canada, Atlantic Research Centre, Halifax NS (CAN);McGill Univ, Montreal Que (CAN) Dept of Electrical and Computer Engineering
Abstract
We address the problem of designing a distributed particle filter for tracking one or more targets using a sensor network. We propose a novel approach for reducing the communication overhead involved in the data fusion step. The approach uses graph-based signal processing to construct a transform of the joint log likelihood values of the particles. This transform is adaptive to particle locations and in many cases leads to a parsimonious representation, so that the joint likelihood values of all particles can be accurately approximated using only a few transform coefficients. The proposed particle filter uses gossip to perform distributed, approximate computation of the transform coefficients. Numerical experiments highlight the potential of the proposed approach to provide accurate tracks with reduced communication overhead.
Keywords
particle filtering;data compression
Report Number
DRDC-RDDC-2016-P127 — External Literature
Date of publication
13 Dec 2016
Number of Pages
5
DSTKIM No
CA042862
CANDIS No
804757
Format(s):
Electronic Document(PDF)

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