An Enhanced Wireless LAN Positioning Algorithm based on the Fingerprint Approach

As ubiquitous computing gained much attention in recent years, location estimation in wireless LAN becomes a hot topic. Previous research work suggests the use of the averaged received signal strength (RSS) as fingerprint can achieve high accuracy for location estimation. In a library environment, however, the accuracy of such traditional approach is barely acceptable. It is because library contains considerably large number of metal bookshelves, and limited number of access points. Worse yet, the layout of these access points in the library is fixed for connection to the Internet, and therefore it is hard to change the environment to adapt for location estimation system. In this paper, we introduce an enhanced fingerprint (EFP) algorithm, and tested it in a library environment. The experiment result showed that the proposed EFP algorithm can have more than 30% of improvement in accuracy over traditional approaches without changing anything in the library environment

[1]  Moustafa Youssef,et al.  WLAN location determination via clustering and probability distributions , 2003, Proceedings of the First IEEE International Conference on Pervasive Computing and Communications, 2003. (PerCom 2003)..

[2]  Prashant Krishnamurthy,et al.  Modeling of indoor positioning systems based on location fingerprinting , 2004, IEEE INFOCOM 2004.

[3]  Paramvir Bahl,et al.  RADAR: an in-building RF-based user location and tracking system , 2000, Proceedings IEEE INFOCOM 2000. Conference on Computer Communications. Nineteenth Annual Joint Conference of the IEEE Computer and Communications Societies (Cat. No.00CH37064).

[4]  Ted Kremenek,et al.  A Probabilistic Room Location Service for Wireless Networked Environments , 2001, UbiComp.

[5]  Joseph Kee-Yin Ng,et al.  A dual-channel location estimation system for providing location services based on the GPS and GSM networks , 2003, 17th International Conference on Advanced Information Networking and Applications, 2003. AINA 2003..

[6]  Panos K. Chrysanthis,et al.  On indoor position location with wireless LANs , 2002, The 13th IEEE International Symposium on Personal, Indoor and Mobile Radio Communications.

[7]  Joseph Kee-Yin Ng,et al.  A New Approach for Locating Mobile Stations under the Statistical Directional Propagation Model , 2006, 20th International Conference on Advanced Information Networking and Applications - Volume 1 (AINA'06).

[8]  A. Agrawala,et al.  On the Optimality of WLAN Location Determination Systems , 2003 .

[9]  Moustafa Youssef,et al.  A Probabilistic Clustering-Based Indoor Location Determination System , 2002 .

[10]  V. Padmanabhan,et al.  Enhancements to the RADAR User Location and Tracking System , 2000 .

[11]  Joseph Kee-Yin Ng,et al.  Wireless LAN positioning with mobile devices in a library environment , 2005, 25th IEEE International Conference on Distributed Computing Systems Workshops.