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Sensors 2014, 14(11), 21195-21212; doi:10.3390/s141121195

Constrained State Estimation for Individual Localization in Wireless Body Sensor Networks

1
School of Automation, Northwestern Polytechnical University, Xi'an 710072, China
2
Institute of Charles Delaunay, University of Technology of Troyes, Troyes 10000, France
*
Author to whom correspondence should be addressed.
Received: 11 June 2014 / Revised: 25 July 2014 / Accepted: 1 August 2014 / Published: 10 November 2014
(This article belongs to the Section Sensor Networks)
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Abstract

Wireless body sensor networks based on ultra-wideband radio have recently received much research attention due to its wide applications in health-care, security, sports and entertainment. Accurate localization is a fundamental problem to realize the development of effective location-aware applications above. In this paper the problem of constrained state estimation for individual localization in wireless body sensor networks is addressed. Priori knowledge about geometry among the on-body nodes as additional constraint is incorporated into the traditional filtering system. The analytical expression of state estimation with linear constraint to exploit the additional information is derived. Furthermore, for nonlinear constraint, first-order and second-order linearizations via Taylor series expansion are proposed to transform the nonlinear constraint to the linear case. Examples between the first-order and second-order nonlinear constrained filters based on interacting multiple model extended kalman filter (IMM-EKF) show that the second-order solution for higher order nonlinearity as present in this paper outperforms the first-order solution, and constrained IMM-EKF obtains superior estimation than IMM-EKF without constraint. Another brownian motion individual localization example also illustrates the effectiveness of constrained nonlinear iterative least square (NILS), which gets better filtering performance than NILS without constraint. View Full-Text
Keywords: constrained state estimation; ultra-wideband radio; individual localization; wireless body sensor networks constrained state estimation; ultra-wideband radio; individual localization; wireless body sensor networks
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. (CC BY 4.0).

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MDPI and ACS Style

Feng, X.; Snoussi, H.; Liang, Y.; Jiao, L. Constrained State Estimation for Individual Localization in Wireless Body Sensor Networks. Sensors 2014, 14, 21195-21212.

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