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Practical Metropolitan-Scale Positioning for GSM Phones

  • Conference paper
UbiComp 2006: Ubiquitous Computing (UbiComp 2006)

Abstract

This paper examines the positioning accuracy of a GSM beacon-based location system in a metropolitan environment. We explore five factors effecting positioning accuracy: location algorithm choice, scan set size, simultaneous use of cells from different providers, training and testing on different devices, and calibration data density. We collected a 208-hour, 4350Km driving trace of three different GSM networks covering the Seattle metropolitan area. We show a median error of 94m in downtown and 196m in residential areas using a single GSM network and the best algorithm for each area. Estimating location using multiple providers’ cells reduces median error to 65-134 meters and 95% error to 163m in the downtown area, which meets the accuracy requirements for E911. We also show that a small 60-hour calibration drive is sufficient for enabling a metropolitan area similar to Seattle.

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References

  1. Arulampalam, S., Maskell, S., Gordon, N., Clapp, T.: A Tutorial on Particle Filters for Online Non-Linear/Non-Gaussian Bayesian Tracking. IEEE Transactions on Signal Processing 50(2), 174–188 (2002)

    Article  Google Scholar 

  2. Ashbrook, D., Starner, T.: Using GPS to Learn Significant Locations and Predict Movement across Multiple Users. Personal and Ubiquitous Computing 7, 275–286 (2003)

    Article  Google Scholar 

  3. Bahl, P., Padmanabhan, V.N.: RADAR: An In-Building RF-Based User Location and Tracking System. In: Proceedings of IEEE INFOCOM 2000, vol. 2, pp. 775–784 (2000)

    Google Scholar 

  4. Cheng, Y., Chawathe, Y., LaMarca, A., Krumm, J.: Accuracy Characterization for Metropolitan-scale WiFi Localization. In: Proceedings of Mobisys 2005 (2005)

    Google Scholar 

  5. Fox, D., Burgard, W., Dellaert, F., Thrun, S.: Monte Carlo localization: Efficient Position Estimation for Mobile Robots. In: Proceedings of AAAI (1999)

    Google Scholar 

  6. Haeberlen, A., Flannery, E., Ladd, A.M., Rudys, A., Wallach, D.S., Kavraki, L.E.: Practical Robust Localization over Large-scale 802.11 Wireless Networks. In: Proceedings of Mobicom (2004)

    Google Scholar 

  7. Hightower, J., et al.: Learning and recognizing the places we go. In: Beigl, M., Intille, S.S., Rekimoto, J., Tokuda, H. (eds.) UbiComp 2005. LNCS, vol. 3660, pp. 159–176. Springer, Heidelberg (2005)

    Chapter  Google Scholar 

  8. Laasonen, K., Raento, M., Toivonen, H.: Adaptive On-device Location Recognition. In: Ferscha, A., Mattern, F. (eds.) PERVASIVE 2004. LNCS, vol. 3001, pp. 287–304. Springer, Heidelberg (2004)

    Chapter  Google Scholar 

  9. LaMarca, A., et al.: Place lab: Device positioning using radio beacons in the wild. In: Gellersen, H.-W., Want, R., Schmidt, A. (eds.) PERVASIVE 2005. LNCS, vol. 3468, pp. 116–133. Springer, Heidelberg (2005)

    Chapter  Google Scholar 

  10. Laitinen, H., Lahteenmaki, J., Nordstrom, T.: Database correlation method for GSM location. In: IEEE 53rd Vehicular Technology Conference (2001)

    Google Scholar 

  11. Letchner, J., Fox, D., LaMarca, A.: Large-Scale Localization from Wireless Signal Strength. In: Proceedings of the National Conference on Artificial Intelligence (AAAI 2005) (2005)

    Google Scholar 

  12. Otsason, V., Varshavsky, A., LaMarca, A., de Lara, E.: Accurate GSM indoor localization. In: Beigl, M., Intille, S.S., Rekimoto, J., Tokuda, H. (eds.) UbiComp 2005. LNCS, vol. 3660, pp. 141–158. Springer, Heidelberg (2005)

    Chapter  Google Scholar 

  13. Privacy-Observant Location System, http://pols.sourceforge.net/

  14. Schwaighofer, A., Grigoras, M., Tresp, V., Hoffmann, C.: GPPS: A Gaussian Process Positioning System for Cellular Networks. In: Proceedings of NIPS 2003 (2003)

    Google Scholar 

  15. Trevisani, E., Vitaletti, A.: Cell-ID Location Technique, Limits and Benefits: An Experimental Study. In: Proceedings of WMCSA 2004, pp. 51–60 (2004)

    Google Scholar 

  16. Priyantha, N.B., Chakraborty, A., Balakrishnan, H.: The cricket location-support system. In: Proceedings of Mobicom 2000, pp. 32–43 (2000)

    Google Scholar 

  17. Want, R., Hopper, A., Falco, V., Gibbons, J.: The Active Badge Location System. ACM Transactions on Information Systems 10(1), 91–102 (1992)

    Article  Google Scholar 

  18. Addlesee, M.D., Jones, A., Livesey, F., Samaria, F.: The ORL Active Floor. IEEE Personal Communications 4(5), 35–41 (1997)

    Article  Google Scholar 

  19. Sohn, T., et al.: Place-its: A study of location-based reminders on mobile phones. In: Beigl, M., Intille, S.S., Rekimoto, J., Tokuda, H. (eds.) UbiComp 2005. LNCS, vol. 3660, pp. 232–250. Springer, Heidelberg (2005)

    Chapter  Google Scholar 

  20. Smith, I., et al.: Social disclosure of place: From location technology to communication practices. In: Gellersen, H.-W., Want, R., Schmidt, A. (eds.) PERVASIVE 2005. LNCS, vol. 3468, pp. 134–151. Springer, Heidelberg (2005)

    Chapter  Google Scholar 

  21. Sinnott, R.W.: Virtues of the Haversine. Sky and Telescope 68(2), 159 (1984)

    MathSciNet  Google Scholar 

  22. Computer Industry Almanac Press Release. Mobile PCs In-Use Surpass 200M (June 2005), http://www.c-i-a.com/pr0605.htm

  23. Computer Industry Almanac Press Release. Worldwide Internet Users will Top 1 Billion in 2005 (September 2004), http://www.c-i-a.com/pr0904.htm

  24. GSM Association Press Release. Worldwide cellular connections exceeds 2 billion (September 2005), http://www.gsmworld.com/news/press_2005/press05_21.shtml

  25. Microsoft Virtual Earth, http://virtualearth.msn.com

  26. Series 60 Phone Platform, http://s60.com

  27. Skyhook Wireless, http://www.skyhookwireless.com

  28. US Wireless, http://web.archive.org/web/20031124182802/http://uswcorp.com

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© 2006 Springer-Verlag Berlin Heidelberg

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Chen, M.Y. et al. (2006). Practical Metropolitan-Scale Positioning for GSM Phones. In: Dourish, P., Friday, A. (eds) UbiComp 2006: Ubiquitous Computing. UbiComp 2006. Lecture Notes in Computer Science, vol 4206. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11853565_14

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  • DOI: https://doi.org/10.1007/11853565_14

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-39634-5

  • Online ISBN: 978-3-540-39635-2

  • eBook Packages: Computer ScienceComputer Science (R0)

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