Mahtab Hossain
580 California St., Suite 400
San Francisco, CA, 94104
Indoor Localization Using Multiple Wireless Technologies
2007, 2007 IEEE Internatonal Conference on Mobile Adhoc and Sensor Systems
https://doi.org/10.1109/MOBHOC.2007.4428622
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Abstract
Indoor localization techniques using location fingerprints are gaining popularity because of their cost-effectiveness compared to other infrastructure-based location systems. However, their reported accuracy fall short of their counterparts. In this paper, we investigate many aspects of fingerprint-based location systems in order to enhance their accuracy. First, we derive analytically a robust location fingerprint definition, and then verify it experimentally as well. We also devise a way to facilitate under-trained location systems through simple linear regression technique. This technique reduces the training time and effort, and can be particularly useful when the surrounding or setup of the localization area changes. We further show experimentally that because of the positions of some access points or the environmental factors around them, their signal strength correlates nicely with distance. We argue that it would be more beneficial to give special consideration to these access points for location computation, owing to their ability to distinguish locations distinctly in signal space. The probability of encountering such access points will be even higher when we denote a location's signature using the signals of multiple wireless technologies collectively. We present the results of two well-known localization algorithms (K-Nearest Neighbor and Bayesian Probabilistic Model) when the above factors are exploited, using Bluetooth and Wi-Fi signals. We have observed significant improvement in their accuracy when our ideas are implemented.
References (23)
- P. Bahl and V. N. Padmanabhan. RADAR: An in-building RF-based user location and tracking system. In Proceedings of the 19 th Annual Joint Conference of the IEEE Computer and Communications Societies (INFOCOM), pages 775-784, Tel Aviv, Israel, Mar. 2000.
- R. Battiti, M. Brunato, and A. Villani. Statistical learning theory for location fingerprinting in wireless LANs. Technical Report DIT-02-0086, Universita di Trento, Dipartimento di Informatica e Telecomunicazioni, Oct. 2002.
- R. Battiti, T. Le Nhat, and A. Villani. Location-aware comput- ing: a neural network model for determining location in wireless LANs. Technical Report DIT-02-0083, Universita di Trento, Dipartimento di Informatica e Telecomunicazioni, Feb. 2002.
- Bluetooth SIG. Bluetooth Core Specification v1.2. https://www.bluetooth.org/spec/.
- P. Castro, P. Chiu, T. Kremenek, and R. R. Muntz. A probabilis- tic room location service for wireless networked environments. In Proceedings of the 3 rd International Conference on Ubiq- uitous Computing (UbiComp '01), pages 18-34, Atlanta, GA, Sept. 2001.
- Ekahau. http://www.ekahau.com/.
- Y. Gwon, R. Jain, and T. Kawahara. Robust indoor location estimation of stationary and mobile users. In Proc. of the 23 rd Annual Joint Conference of the IEEE Computer and Communication Societies (INFOCOM'04), pages 1032-1043, Mar. 2004.
- A. Haeberlen, E. Flannery, A. M. Ladd, A. Rudys, D. S. Wallach, and L. E. Kavraki. Practical robust localization over large-scale 802.11 wireless networks. In Proceedings of the 10th annual international conference on Mobile computing and networking (MobiCom '04), pages 70-84, Philadelphia, PA, 2004.
- J. Hightower and G. Borriella. Location systems for ubiquitous computing. IEEE Computer, 34(8):57-66, 2001.
- K. Kaemarungsi and P. Krishnamurth. Properties of indoor received signal strength for WLAN location fingerprinting. In 1st Annual International Conference on Mobile and Ubiquitous Systems: Networking and Services (MobiQuitous'04), pages 14- 23, San Diego, CA, 2004.
- K. Kaemarungsi and P. Krishnamurthy. Modeling of indoor positioning systems based on location fingerprinting. In Proc. of the 23 rd Annual Joint Conference of the IEEE Computer and Communication Societies (INFOCOM'04), pages 1012-1022, Mar. 2004.
- B. Li, J. Salter, A. G. Dempster, and C. Rizos. Indoor position- ing techniques based on wireless LAN. In 1st IEEE Int. Conf. on Wireless Broadband & Ultra Wideband Communications, Sydney, AUS, Mar. 2006.
- The libpcap Project. http://sourceforge.net/projects/libpcap/.
- BlueZ: Official Linux Bluetooth protocol stack. http://www.bluez.org.
- K. Pahlavan, X. Li, and J. Maleka. Indoor geolocation science and technology. IEEE Communications Mag., 40(2):112-118, 2002.
- D. Pandya, R. Jain, and E. Lupu. Indoor location using multiple wireless technologies. In Proc. IEEE PIMRC, pages 2208-2212, Beijing, China, Sept. 2003.
- N. Priyantha, A. Chakraborty, and H. Balakrishnan. The cricket location-support system. In Proc. of the 6 th Annual International Conference on Mobile Computing and Networking (MobiCom '00), pages 32-43, Boston, MA, Aug. 2000.
- N. Priyantha, A. Miu, H. Balakrishnan, and S. Teller. The cricket compass for context-aware mobile applications. In Proceedings of the 7 th Annual International Conference on Mobile Computing and Networking, pages 1-14, Rome, Italy, July 2001.
- T. S. Rappaport. Wireless Communications -Principles and Practice. Prentice Hall, 1996.
- P. Tao, A. Rudys, A. M. Ladd, and D. S. Wallach. Wireless LAN location-sensing for security applications. In Proceedings of the second ACM Workshop on Wireless Security (WiSe '03), pages 11-20, San Diego, CA, Sept. 2003.
- R. Want, A. Hopper, V. Falcão, and J. Gibbons. The active badge location system. ACM Trans. on Information Systems, 10(1):91-102, Jan. 1992.
- A. Ward, A. Jones, and A. Hopper. A new location technique for the active office. IEEE Personal Communications, 4(5):42- 47, Oct. 1997.
- M. A. Youssef, A. Agrawala, and A. U. Shankar. WLAN location determination via clustering and probability distribu- tions. In Proceedings of the 1 st IEEE International Conference on Pervasive Computing and Communications (PERCOM '03), Mar. 2003.