A proof of uniform convergence over time for a distributed particle filter Articles uri icon

publication date

  • May 2016

start page

  • 152

end page

  • 163

volume

  • 122

International Standard Serial Number (ISSN)

  • 0165-1684

Electronic International Standard Serial Number (EISSN)

  • 1872-7557

abstract

  • Distributed signal processing algorithms have become a hot topic during the past years. One class of algorithms that have received special attention are particles filters (PFs). However, most distributed PFs involve various heuristic or simplifying approximations and, as a consequence, classical convergence theorems for standard PFs do not hold for their distributed counterparts. In this paper, we analyze a distributed PF based on the non-proportional weight-allocation scheme of Bolic et al (2005) and prove rigorously that, under certain stability assumptions, its asymptotic convergence is guaranteed uniformly over time, in such a way that approximation errors can be kept bounded with a fixed computational budget. To illustrate the theoretical findings, we carry out computer simulations for a target tracking problem. The numerical results show that the distributed PF has a negligible performance loss (compared to a centralized filter) for this problem and enable us to empirically validate the key assumptions of the analysis.

keywords

  • particle filtering; convergence analysis; ireless sensor networks; parallelization; distributed algorithms