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Issue No.02 - February (2012 vol.11)
pp: 254-263
Kegen Yu , Macquarie University, North Ryde
Eryk Dutkiewicz , Macquarie University, North Ryde
This paper presents positioning algorithms for cellular network-based vehicle tracking in severe non-line-of-sight (NLOS) propagation scenarios. The aim of the algorithms is to enhance positional accuracy of network-based positioning systems when the GPS receiver does not perform well due to the complex propagation environment. A one-step position estimation method and another two-step method are proposed and developed. Constrained optimization is utilized to minimize the cost function which takes account of the NLOS error so that the NLOS effect is significantly reduced. Vehicle velocity and heading direction measurements are exploited in the algorithm development, which may be obtained using a speedometer and a heading sensor, respectively. The developed algorithms are practical so that they are suitable for implementation in practice for vehicle applications. It is observed through simulation that in severe NLOS propagation scenarios, the proposed positioning methods outperform the existing cellular network-based positioning algorithms significantly. Further, when the distance measurement error is modeled as the sum of an exponential bias variable and a Gaussian noise variable, the exact expressions of the CRLB are derived to benchmark the performance of the positioning algorithms.
NLOS mitigation, heading angle, constrained optimization, Cramer-Rao lower bound, mobile tracking.
Kegen Yu, Eryk Dutkiewicz, "Geometry and Motion-Based Positioning Algorithms for Mobile Tracking in NLOS Environments", IEEE Transactions on Mobile Computing, vol.11, no. 2, pp. 254-263, February 2012, doi:10.1109/TMC.2011.24
[1] K. Yu, I. Sharp, and Y.J. Guo, Ground-Based Wireless Positioning. Wiley-IEEE, 2009.
[2] S. Al-Jazzar and J. CafferyJr., “NLOS Mitigation Method for Urban Environments,” Proc. IEEE Vehicular Technology Conf. (VTC '04), pp. 5112-5115, Sept. 2004.
[3] W. Kim, J.G. Lee, and G.-I. Jee, “The Interior-Point Method for an Optimal Treatment of Bias in Trilateration Location,” IEEE Trans. Vehicular Technology, vol. 55, no. 4, pp. 1291-1301, July 2006.
[4] K. Yu and Y.J. Guo, “Improved Positioning Algorithms for Nonline-of-Sight Environments,” IEEE Trans. Vehicular Technology, vol. 57, no. 4, pp. 2342-2353, July 2008.
[5] M. Najar and J. Vidal, “Kalman Tracking for Mobile Location in NLOS Situations,” Proc. IEEE Personal, Indoor and Mobile Comm., pp. 2203-2207, 2003.
[6] P. Bahl and V. Padmanabhan, “RADAR: An In-Building RF-Based User Location and Tracking System,” Proc. IEEE INFOCOM, pp. 775-784, 2000.
[7] L. Cong and W. Zhuang, “Nonline-of-Sight Error Mitigation in Mobile Location,” IEEE Trans. Wireless Comm., vol. 4, no. 2, pp. 560-573, Mar. 2005.
[8] N.J. Thomas, D.G.M. Cruickshank, and D.I. Laurenson, “Calculation of Mobile Location Using Scatterer Information,” Electronics Letters, vol. 37, no. 19, pp. 1193-1194, Sept. 2001.
[9] H. Miao, K. Yu, and M. Juntti, “Positioning for NLOS Propagation: Algorithm Derivations and Cramer-Rao Bounds,” IEEE Trans. Vehicular Technology, vol. 56, no. 5, pp. 2568-2580, Sept. 2007.
[10] W.-S. Ku, R. Zimmermann, and H. Wang, “Non-Line-of-Sight Localization in Multipath Environments,” IEEE Trans. Mobile Computing, vol. 7, no. 5, pp. 647-660, May 2008.
[11] C.-H. Lin, J.-Y. Cheng, and C.-N. Wu, “Mobile Location Estimation by Density-Based Clustering for NLoS Environments,” Proc. Int'l Conf. Advanced Information Networking and Applications, pp. 1-6, Apr. 2006.
[12] B. Li, A.G. Dempster, C. Rizos, and H.K. Lee, “A Database Method to Mitigate the NLOS Error in Mobile Phone Positioning,” Proc. IEEE/ION Position, Location, and Navigation Symp., pp. 173-179, 2006.
[13] B.L. Le, K. Ahmed, and H. Tsuji, “Mobile Location Estimator with NLOS Mitigation Using Kalman Filtering,” Proc. IEEE Wireless Comm. and Networking, pp. 1969-1973, 2003.
[14] J.-F. Liao and B.-S. Chen, “Robust Mobile Location Estimator with NLOS Mitigation Using Interacting Multiple Model Algorithm,” IEEE Trans. Wireless Comm., vol. 5, no. 11, pp. 3002-3006, Nov. 2006.
[15] K. Pahlavan, X. Li, and J.-P. Makela, “Indoor Geolocation Science and Technology,” IEEE Comm. Magazine, vol. 40, no. 2, pp. 112-118, Feb. 2002.
[16] N. Patwari, A.O. HeroIII, M. Perkins, N.S. Correal, and R.J. O'dea, “Relative Location Estimation in Wireless Sensor Networks,” IEEE Trans. Signal Processing, vol. 51, no. 8, pp. 2137-2148, Aug. 2003.
[17] C. Nerguizian, C. Despins, and S. Affes, “Geolocation in Mines with an Impulse Response Fingerprinting and Neural Networks,” IEEE Trans. Wireless Comm., vol. 5, no. 3, pp. 603-611, Mar. 2006.
[18] P.E. Gill, W. Murray, and M.H. Wright, Practical Optimization. Academic, 1981.
[19] K. Yu, “3-D Localization Error Analysis in Wireless Networks,” IEEE Trans. Wireless Comm., vol. 6, no. 10, pp. 3473-3481, Oct. 2007.
[20] K. Yu, Y.J. Guo, and M. Hedley, “TOA-Based Distributed Localisation with Unknown Internal Delays and Clock Frequency Offsets in Wireless Sensor Networks,” IET Signal Processing, vol. 3, no. 2, pp. 106-118, 2009.
[21] S.M. Kay, Fundamentals of Statistical Signal Processing: Estimation Theory. Prentice Hall, 1993.
[22] W.C.Y. Lee, Mobile Communication Engineering. McGraw-Hill, 1993.
[23] S.-S. Woo, H.-R. You, and J.-S. Koh, “The NLOS Mitigation Technique for Position Location Using IS-95 CDMA Networks,” Proc. IEEE Vehicular Technology Conf. (VTC '00), pp. 2556-2560, Sept. 2000.
[24] B. Alavi and K. Pahlavan, “Modeling of the Distance Error for Indoor Geolocation,” Proc. IEEE Wireless Comm. and Networking, pp. 668-672, Mar. 2003.
[25] W.H. Beyer, CRC Standard Mathematical Tables and Formulae. CRC, 2000.
[26] W. Wang, Z. Wang, and B. O'Dea, “A TOA-Based Location Algorithm Reducing the Errors Due to Nonline-of-Sight (NLOS) Propagation,” IEEE Trans. Vehicular Technology, vol. 52, pp. 112-116, Jan. 2003.
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