Propagation Modeling for Accurate Indoor WLAN RSS-Based Localization

WLAN RSS-based localization has been a hot research topic for the last years. To obtain high accuracy in the noisy wireless channel, WLAN location determination systems usually use a calibration phase, where a radio map, capturing the signal strength signatures at different locations in the area of interest, is built. The radio map construction process takes a lot of time and effort, reducing the value of WLAN localization systems. In this paper, we propose 3D ray tracing as a way for automatically generating a highly accurate radiomap. We compare this method to previously used propagation modeling-based methods like the Wall Attenuation Factor and 2D ray tracing models. We evaluate the performance of each method and its computational cost in a typical residential environment. We also examine the sensitivity of the localization accuracy to inaccurate material parameters. Our results quantify the accuracy- complexity trade-off of the different proposed techniques with 3D ray tracing giving the best localization accuracy compared to measurements with acceptable computational requirements on a typical PC.

[1]  Robert Wilson,et al.  Propagation Losses Through Common Building Materials 2 . 4 GHz vs 5 GHz Reflection and Transmission Losses Through Common Building Materials , 2003 .

[2]  Reinaldo A. Valenzuela.  A ray tracing approach to predicting indoor wireless transmission , 1993, IEEE 43rd Vehicular Technology Conference.

[3]  Theodore S. Rappaport,et al.  Site-specific propagation prediction for wireless in-building personal communication system design , 1994 .

[4]  Prathima Agrawal,et al.  ARIADNE: a dynamic indoor signal map construction and localization system , 2006, MobiSys '06.

[5]  William G. Scanlon,et al.  Simulation or Measurement: The Effect of Radio Map Creation on Indoor WLAN-Based Localisation Accuracy , 2007, Wirel. Pers. Commun..

[6]  K. Pahlavan,et al.  Comparative statistical analysis of indoor positioning using empirical data and indoor radio channel models , 2006, CCNC 2006. 2006 3rd IEEE Consumer Communications and Networking Conference, 2006..

[7]  Moustafa Youssef,et al.  The Horus location determination system , 2008 .

[8]  Frédéric Lassabe,et al.  Open Wireless Positioning System: A Wi-Fi-Based Indoor Positioning System , 2009, 2009 IEEE 70th Vehicular Technology Conference Fall.

[9]  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).

[10]  Ignas Niemegeers,et al.  A survey of indoor positioning systems for wireless personal networks , 2009, IEEE Communications Surveys & Tutorials.

[11]  W. Marsden.  I and J , 2012 .

[12]  Joe Wiart,et al.  Electromagnetic propagation into reinforced-concrete walls , 1998, IMS 1998.

[13]  Stavros Stavrou,et al.  Review of constitutive parameters of building materials , 2003 .

[14]  C. Balanis.  Advanced Engineering Electromagnetics , 1989 .

[15]  Georgia E. Athanasiadou,et al.  Investigation into the sensitivity of the power predictions of a microcellular ray tracing propagation model , 2000, IEEE Trans. Veh. Technol..

[16]  Yi Huang,et al.  Indoor channel characteristics comparisons for the same building with different dielectric parameters , 2002, 2002 IEEE International Conference on Communications. Conference Proceedings. ICC 2002 (Cat. No.02CH37333).

[17]  Georgia E. Athanasiadou,et al.  A novel 3-D indoor ray-tracing propagation model: the path generator and evaluation of narrow-band and wide-band predictions , 2000, IEEE Trans. Veh. Technol..