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International Journal of Distributed Sensor Networks
Volume 2013 (2013), Article ID 758749, 8 pages
Research Article

An Indoor Mobile Localization Strategy for Robot in NLOS Environment

The School of Information Science and Engineering, Northeastern University, Shenyang 110819, China

Received 4 October 2012; Accepted 17 December 2012

Academic Editor: Long Cheng

Copyright © 2013 Yan 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.


This paper deals with the problem of localization of mobile robot in indoor environment with mixed line-of-sight/nonline-of-sight (LOS/NLOS) conditions. To reduce the NLOS errors, a prior knowledge-based correction strategy (PKCS) is proposed to locate the robot. This strategy consists of two steps: NLOS identification and mitigation. We propose an NLOS identification method by applying the statistical theory. Then we correct the NLOS errors by subtracting the expected NLOS errors. Finally, the residual weighting algorithm is employed to estimate the location of the robot. Simulation results show that the proposed strategy significantly improves the accuracy of localization in mixed LOS/NLOS indoor environment.