Ultra Wideband Indoor Positioning Using Kalman Filters

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Abstract:

A time-difference-of-arrival (TDOA) positioning technique for indoor ultra wideband (UWB) systems is presented. Non-line-of-sight (NLOS) propagation error is a major source of error in positioning systems. Therefore an NLOS mitigation technique employing a Kalman filter is utilized to reduce the NLOS errors in indoor UWB environments. An extended Kalman filter (EKF) is used to process the TDOA data for mobile positioning and tracking. Performance results are presented which show that the proposed scheme can significantly improve the positioning accuracy in a UWB environment.

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Periodical:

Advanced Materials Research (Volumes 433-440)

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4207-4213

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January 2012

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© 2012 Trans Tech Publications Ltd. All Rights Reserved

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[1] J. Oppermann, M. Hamalainen, and N. Linatti, UWB: Theory and Applications, Wiley, (2004).

Google Scholar

[2] C. -D. Wann, Y. -J. Yeh, and C. -S. Hsueh. Hybrid TDOA/AOA indoor positioning and tracking using extended Kalman filters, Proc. IEEE Vehic. Tech. Conf., pp.1058-1062, (2006).

DOI: 10.1109/vetecs.2006.1682996

Google Scholar

[3] M. P. Wylie, and J. Holtzman, The non-line of sight problem in mobile location estimation, IEEE Int. Conf. on Universal Personal Commun., pp.827-831, Sept. (1996).

DOI: 10.1109/icupc.1996.562692

Google Scholar

[4] N. J. Thomas, D. G. M. Cruickshank and D. I. Laurenson, A robust location estimator architecture with biased Kalman filtering of TOA data for wireless systems, IEEE Int. Symp. on Spread Spectrum Tech. & Applications, pp.296-300, Sept. (2000).

DOI: 10.1109/isssta.2000.878132

Google Scholar

[5] B. L. Le, K. Ahmed, and H. Tsuji, Mobile location estimator with NLOS mitigation using Kalman filtering, IEEE Wireless Commun. and Networking Conf., pp.16-20, Mar. (2003).

DOI: 10.1109/wcnc.2003.1200689

Google Scholar

[6] M. Najar and J. Vidal, Kalman tracking for mobile location in NLOS situations, Proc. IEEE Int. Symp. on Personal, Indoor and Mobile Radio Communication (PIM1RC), pp.2203-2207, Sept. (2003).

DOI: 10.1109/pimrc.2003.1259107

Google Scholar

[7] M. S. Grewal and A. P. Andrews, Kalman Filtering: Theory and Practice (2nd Ed. ) , Wiley, (2001).

Google Scholar

[8] J. Foerster, et al., Channel Modeling Sub-committee Final Report, IEEE802. 15-02/490rl, Feb. (2003).

Google Scholar

[9] S. M. Kay, Fundamentals of Statistical Signal Processing: Estimation Theory, vol. 1, Prentice Hall, (1993).

Google Scholar

[10] A. F. Molisch, et al., Channel models for ultrawideband personal area networks, IEEE Wireless Communications, vol. 10, no. 6, pp.14-21, Dec. (2003).

DOI: 10.1109/mwc.2003.1265848

Google Scholar

[11] A. F. Molisch, K. Balakrishnan, C. -C. Chong, et al. IEEE 802. 15. 4a Channel Model-Final Report[Z/OL]. IEEE Wireless World Document, 15-04-0662-00-004a.

Google Scholar