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Journal of Sensors
Volume 2018, Article ID 5387142, 10 pages
Research Article

Distributed Particle Flow Filter for Target Tracking in Wireless Sensor Networks

School of Computer, Science and Technology, Harbin Institute of Technology, Harbin, China

Correspondence should be addressed to Lingling Zhao; nc.ude.tih@lloahz

Received 28 July 2017; Revised 12 December 2017; Accepted 8 January 2018; Published 11 April 2018

Academic Editor: Hana Vaisocherova - Lisalova

Copyright © 2018 Junjie Wang et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.


We propose, in this paper, a fully distributed tracking algorithm based on particle flow filter over sensor networks based on the max-consensus. The presented distributed particle flow filter is particularly suitable for the sensor network with limited sensing range and consists of two phases: the estimation phase and consensus phase. The local estimation results are obtained via particle flow filter in the estimation phase; then the sensor nodes agree on the best estimation based on max-consensus protocol in the consensus phase. Numerical simulations and comparisons with other distributed target tracking algorithms are carried out to show the effectiveness and feasibility of our approach.