Title: Particle filter based device free localisation and tracking for large scale wireless sensor networks

Authors: Jie Wang; Qinghua Gao; Xiaoyun Zhang; Hongyu Wang; Minglu Jin

Addresses: Faculty of Electronic Information and Electrical Engineering, Dalian University of Technology, Dalian 116023, China ' Faculty of Electronic Information and Electrical Engineering, Dalian University of Technology, Dalian 116023, China ' Department of Electrical and Computer Engineering, Iowa State University, Iowa 50011, USA ' Faculty of Electronic Information and Electrical Engineering, Dalian University of Technology, Dalian 116023, China ' Faculty of Electronic Information and Electrical Engineering, Dalian University of Technology, Dalian 116023, China

Abstract: This paper presents a particle filter (PF) based approach to realise the target localisation and tracking task for large scale wireless sensor networks (WSNs) without the need of equipping the target with a wireless device. We utilise the variation of the received signal strength (RSS) measurements between the node pairs and present a statistical model for relating the variation of the RSS measurements to the spatial location of the target. And then, we adopt the PF framework to realise the localisation and tracking task, and the statistical model is utilised to build the observation likelihood function. Meanwhile, to make the above strategies applicable for the computational and power resource limited large scale WSNs, we propose a scheme to select a subset of nodes and links to participate in the location estimation. Experimental results demonstrate the effectiveness of our approach.

Keywords: device free localisation; device free tracking; particle filter; WSNs; wireless sensor networks; RSS measurements; node pairs; received signal strength; statistical modelling; location estimation.

DOI: 10.1504/IJSNET.2015.072860

International Journal of Sensor Networks, 2015 Vol.19 No.3/4, pp.194 - 203

Received: 19 Jan 2012
Accepted: 13 May 2012
Published online: 05 Nov 2015 *

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