Handling samples correlation in the Horus system

We present an autoregressive model for modelling samples autocorrelation from the same access point in WLAN location determination systems. Our work is in the context of the Horus system, which is a probabilistic WLAN location determination system. We show that the autocorrelation between consecutive samples from the same access point can be as high as 0.9. Using our model, we describe a technique to use multiple signal strength samples from each access point, taking the high autocorrelation into account, to achieve better accuracy. Implementation of the technique in the Horus system shows that the average system accuracy is increased by more than 50%. Our results show that assuming independence of samples from the same access point can lead to degraded performance as the number of samples used in the estimation algorithm is increased, due to the wrong independence assumption. We also discuss how to incorporate the new technique with other algorithms for enhancing the performance of WLAN location determination systems.

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

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

[3]  Moustafa Youssef,et al.  Small-scale compensation for WLAN location determination systems , 2003, 2003 IEEE Wireless Communications and Networking, 2003. WCNC 2003..

[4]  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)..

[5]  Guanling Chen,et al.  A Survey of Context-Aware Mobile Computing Research , 2000 .

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

[7]  Henry Tirri,et al.  A Statistical Modeling Approach to Location Estimation , 2002, IEEE Trans. Mob. Comput..

[8]  Kostas E. Bekris,et al.  Robotics-Based Location Sensing Using Wireless Ethernet , 2002, MobiCom '02.

[9]  Kostas E. Bekris,et al.  Robotics-Based Location Sensing Using Wireless Ethernet , 2005, Wirel. Networks.

[10]  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).

[11]  A. M. Abdullah,et al.  Wireless lan medium access control (mac) and physical layer (phy) specifications , 1997 .

[12]  Richard R. Muntz,et al.  Managing context data for smart spaces , 2000, IEEE Wirel. Commun..

[13]  Asim Smailagic,et al.  Location sensing and privacy in a context-aware computing environment , 2002, IEEE Wirel. Commun..

[14]  Henry Tirri,et al.  A Probabilistic Approach to WLAN User Location Estimation , 2002, Int. J. Wirel. Inf. Networks.

[15]  Theodore S. Rappaport,et al.  Wireless communications - principles and practice , 1996 .

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