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International Journal of Distributed Sensor Networks
Volume 2013 (2013), Article ID 208904, 9 pages
http://dx.doi.org/10.1155/2013/208904
Research Article

Indoor Mobile Localization in Wireless Sensor Network under Unknown NLOS Errors

1College of Information Science and Engineering, Northeastern University, Shenyang 110819, China
2Faculty of Engineering & Information Technologies, University of Sydney, NSW 2006, Australia

Received 17 November 2012; Accepted 12 December 2012

Academic Editor: Shuai Li

Copyright © 2013 Long Cheng 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.

Abstract

Localization is one of the key techniques in wireless sensor network. One of the main problems in indoor mobile localization is non-line-of-sight (NLOS) propagation. And the NLOS effects will lead to a large localization error. So the NLOS problem is the biggest challenge for accurate mobile location estimation in WSN. In this paper, we propose a likelihood matrix correction based mixed Kalman and -infinity filter (LC-MKHF) method. A likelihood matrix based correction method is firstly proposed to correct the LOS and NLOS measurements. This method does not need the prior information about the statistical properties of the NLOS errors. So it is independent of the physical measurement ways. And then a mixed Kalman and -infinity filter method is proposed to improve the range measurement. Simulation results show that the LC-MKHF algorithm has higher estimate accuracy in comparison with no-filter, Kalman filter, and -infinity filter methods. And it is robust to the NLOS errors.