Abstract
We propose an efficient location algorithm which can mitigate the influence of NLOS error. Based on the geometric relationship between known positions of the base stations, the theorem of “Fermat Point” is utilized to collect the candidate positions (CPs) of the mobile station. Then, a set of weighting parameters are computed using a density-based clustering method. Finally, the location of mobile station is estimated by solving the optimal solution of the weighted objective function. Different distributions of NLOS error models are used to evaluate the performance of this method. Simulation results show that the performance of the least range measure (LRM) algorithm is slightly better than density-based clustering algorithm (DCA), and superior to the range based linear lines of position algorithm (LLOP) and range scaling algorithm (RSA) on location accuracy under different NLOS environments. The simulation results also satisfy the location accuracy demand of Enhanced 911 (E-911).
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
References
Caffery, J., Stuber, G.: Overview of Radiolocation in CDMA Cellular Systems. IEEE Communications Magazine 36, 38–45 (1998)
Caffery, J., Stuber, G.: Subscriber Location in CDMA Cellular Networks. IEEE Transactions on Vehicular Technology 47(2), 406–416 (1998)
Caffery, J.: Wireless Location in CDMA Cellular Radio Systems. Kluwer, Massachusetts (1999)
Caffery, J.: A New Approach to the Geometry of TOA Location. In: Proceedings of the IEEE Vehicular Technology Conference, pp. 1943–1949 (2000)
FCC, Revision of the Commissions Rules to Insure Compatibility with Enhanced 911 Emergency Calling Systems. Technical Report, RM-8143. Washington, DC: U.S. Federal Communications Commission (1996)
Lin, C.-H., Cheng, J.-Y., Wu, C.-N.: Mobile Location Estimation by Density-Based Clustering for NLoS Environments. In: Proceedings of the 20th International Conference on Advanced Information Networking and Applications, vol. 1, pp. 295–300 (2006)
Venkatraman, S., Caffery, J., You, H.-R.: A Novel ToA Location Algorithm Using LoS Range Estimation for NLoS Environments. IEEE Transaction on Vehicular Technology 53, 1515–1524 (2004)
Wylie, M.P., Holtzman, J.: The Non-Line of Sight Problem in Mobile Location Estimation. In: Proceedings of the IEEE International Conference on Universal Personal Communications, vol. 2, pp. 827–831 (1996)
Zhao, Y.: Standardization of Mobile Phone Positioning for 3G Systems. IEEE Communications Magazine 40, 108–116 (2002)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2009 Springer-Verlag Berlin Heidelberg
About this chapter
Cite this chapter
Lin, CH., Wang, CC., Tsai, CH. (2009). A Mobile Location Algorithm with Least Range and Clustering Techniques for NLoS Environments. In: Chien, BC., Hong, TP. (eds) Opportunities and Challenges for Next-Generation Applied Intelligence. Studies in Computational Intelligence, vol 214. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-92814-0_38
Download citation
DOI: https://doi.org/10.1007/978-3-540-92814-0_38
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-92813-3
Online ISBN: 978-3-540-92814-0
eBook Packages: EngineeringEngineering (R0)