Navin Kumar Sharma
ABSTRACT
This paper presents a weighted center of mass based trilateration approach for locating a wireless device based on the signal strength received from the access points at known locations. This approach mainly consists of two phases: (1) The calculation of distance from RSSI values of various access points as received by the mobile device, (2) Determination of the most probable location of wireless device using coordinates of various known or fixed access points and calculated distances of the device from those access points. Kalman filter is also used in both phases in order to remove the measurement noise component and to increase the accuracy of estimation. The proposed algorithm provides a solution for location tracking of mobile devices in indoor environment where the configuration of access points like transmit power etc., is not fixed and the movements in environment affecting attenuation of signal is so unpredictable that any mathematical modeling of indoor RF signal propagation is infeasible.
- Chong Liu, Kui Wu, and Tian He, "Sensor Localization with Ring Overlapping based on Comparison of Received Signal Strength Indicator," In Proceedings of IEEE International Conference on Mobile Ad-hoc and Sensor Systems (MASS), Florida, USA, October 2004.Google Scholar
- I. Guvenc, C. T. Abdallah, R. Jordan, and O. Dedeoglu, "Enhancements to RSS Based Indoor Tracking Systems Using Kalman Filters", Proceedings of GSPx and International Signal Processing Conference (ISPC), Dallas, TX, (March 31 - April 3, 2003).Google Scholar
- Kevin Murphy, "Kalman Filter Toolbox - Tutorial", http://www.cs.berkeley.edu/~murphyk/Bayes/kalman.htmlGoogle Scholar
- Marc de Jonge, "Benchmarking Various Untrained Localization Algorithms," 3rd Twente Student Conference on IT, Enschede, June, 2005.Google Scholar
- Moustafa Youssef and Ashok Agrawala, "The Horus WLAN Location Determination System," Proceedings of the Third International Conference on Mobile Systems, Applications, and Services (MobiSys 2005), Seattle, WA, USA, June 2005. Google ScholarDigital Library
- Moustafa Youssef and Ashok Agrawala, "Continuous Space Estimation for WLAN Location Determination Systems," IEEE Thirteenth International Conference on Computer Communications and Networks, Chicago, IL, USA, October 2004.Google Scholar
- P. Bahl and V. N. Padmanabhan, "RADAR: An In-Building RF based User Location and Tracking System," Proceedings of IEEE INFOCOM 2000, Tel-Aviv, Israel (March 2000).Google Scholar
- P. Prasithsangaree, P. Krishnamurthy and P. Chrysanthis, "On Indoor Position Location with Wireless LANs", The 13th IEEE International Symposium on Personal, Indoor and Mobile Radio Communications - PIMRC 2002, September 2002.Google ScholarCross Ref
- Raman Kumar K, Varsha Apte, and Yogesh A Power, "Improving the Accuracy of Wireless LAN based Location Determination Systems using Kalman Filter and Multiple Observers," In Wireless Communications and Networking Conference (WCNC), Las Vegas, April 2006.Google Scholar
- Saeed S. Ghassemzadeh, Larry J. Greenstein, Aleksandar Kavcic, Thorvardur Sveinsson, and Vahid Tarokh, "An Empirical Indoor Path Loss Model For Ultra-Wideband Channels," Journal of Communication and Networks, 2003, Volume 5, no. 4, pp 303--308.Google ScholarCross Ref
- Youngjune Gwon, Ravi Jain, and Toshiro Kawahara, "Robust Indoor Location Estimation of Stationary and Mobile Users," Proceedings of IEEE INFOCOM 2004, Hong Kong, China, March 2004.Google Scholar
Index Terms
- A weighted center of mass based trilateration approach for locating wireless devices in indoor environment
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