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Online Variational Bayesian Filtering-Based Mobile Target Tracking in Wireless Sensor Networks

Zhou, B, Chen, Q, Li, J and Xiao, P (2014) Online Variational Bayesian Filtering-Based Mobile Target Tracking in Wireless Sensor Networks Sensors, 14. pp. 21281-21315.

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Abstract

Online variational bayesian filtering-based mobile target tracking in wireless sensor networks. Abstract: The received signal strength (RSS)-based online tracking for a mobile node in wireless sensor networks (WSNs) is investigated in this paper. Firstly, a multi-layer dynamic Bayesian network (MDBN) is introduced to characterize the target mobility with either directional or undirected movement. In particular, it is proposed to employ the Wishart distribution to approximate the time-varying RSS measurement precision's randomness due to the target movement. It is shown that the proposed MDBN offers a more general analysis model via incorporating the underlying statistical information of both the target movement and observations, which can be utilized to improve the online tracking capability by exploiting the Bayesian statistics. Secondly, based on the MDBN model, a mean-field variational Bayesian filtering (VBF) algorithm is developed to realize the online tracking of a mobile target in the presence of nonlinear observations and time-varying RSS precision, wherein the traditional Bayesian filtering scheme cannot be directly employed. Thirdly, a joint optimization between the real-time velocity and its prior expectation is proposed to enable online velocity tracking in the proposed online tacking scheme. Finally, the associated Bayesian Cramer-Rao Lower Bound (BCRLB) analysis and numerical simulations are conducted. Our analysis unveils that, by exploiting the potential state information via the general MDBN model, the proposed VBF algorithm provides a promising solution to the online tracking of a mobile node in WSNs. In addition, it is shown that the final tracking accuracy linearly scales with its expectation when the RSS measurement precision is time-varying.

Item Type: Article
Divisions : Faculty of Engineering and Physical Sciences > Electronic Engineering
Authors :
AuthorsEmailORCID
Zhou, BUNSPECIFIEDUNSPECIFIED
Chen, QUNSPECIFIEDUNSPECIFIED
Li, JUNSPECIFIEDUNSPECIFIED
Xiao, PUNSPECIFIEDUNSPECIFIED
Date : 11 November 2014
Identification Number : 10.3390/s141121281
Additional Information : 2014 by the authors; licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution license (http://creativecommons.org/licenses/by/4.0/).
Depositing User : Symplectic Elements
Date Deposited : 26 Nov 2014 16:35
Last Modified : 27 Nov 2014 02:33
URI: http://epubs.surrey.ac.uk/id/eprint/806631

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