Indoor positioning using WLAN coverage area estimates

This paper introduces a novel method for positioning using coverage area estimates of wireless communication nodes. The coverage areas are estimated in a Bayesian inference framework using location fingerprints that are collected in an offline calibration phase, and the estimated coverage areas are stored in a database. In the online positioning phase the coverage areas of the heard communication nodes are used to infer the position of the mobile terminal. Floor plan information is used to enhance the positioning accuracy. In a field study comparing Kalman Filter, Box Filter and Particle Filter using real WLAN measurement data, it is found that Kalman Filter achieves almost the same accuracy as Box Filter and Particle Filter but with smaller computational load.

[1]  Harold W. Sorenson,et al.  Recursive Bayesian estimation using piece-wise constant approximations , 1988, Autom..

[2]  François Marx,et al.  Map-aided indoor mobile positioning system using particle filter , 2005, IEEE Wireless Communications and Networking Conference, 2005.

[3]  S. J. Press,et al.  Applied multivariate analysis : using Bayesian and frequentist methods of inference , 1984 .

[4]  Niilo Sirola,et al.  Moving Grid Filter in Hybrid Local Positioning , 2006 .

[5]  Andrei Szabo,et al.  Enhancing the Map Usage for Indoor Location-Aware Systems , 2007, HCI.

[6]  Lauri Wirola.  Studies on Location Technology Standards Evolution in Wireless Networks , 2010 .

[7]  G. C. Tiao,et al.  Bayesian inference in statistical analysis , 1973 .

[8]  Niilo Sirola,et al.  Local Positioning with Parallelepiped Moving Grid , 2006 .

[9]  Ville Kaseva,et al.  Positioning with coverage area estimates generated from location fingerprints , 2010, 2010 7th Workshop on Positioning, Navigation and Communication.

[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]  Laura Koski,et al.  Positioning with Bayesian coverage area estimates and location fingerprints , 2010 .

[12]  Christoforos Panayiotou,et al.  On the RBF-based positioning using WLAN signal strength fingerprints , 2010, 2010 7th Workshop on Positioning, Navigation and Communication.

[13]  Ville Honkavirta.  Location fingerprinting methods in wireless local area networks , 2008 .

[14]  Bayesian Filtering,et al.  Efficient Gaussian Mixture Filter for Hybrid Positioning , 2008 .

[15]  Martin Klepal,et al.  A novel backtracking particle filter for pattern matching indoor localization , 2008, MELT '08.

[16]  Simo Ali-Löytty,et al.  Kalman-type positioning filters with floor plan information , 2008, MoMM.