Observability of path loss parameters in WLAN-based Simultaneous Localization and Mapping

Indoor positioning by means of received signal strengths has been gathering much interest since the massive presence of wireless local area networks (WLANs) in buildings. Theoretical approaches rely on the perfect knowledge of the APs' positions and propagation conditions; since this is unrealistic in real world, we estimate such knowledge as well as the building map from data by applying Simultaneous Localization and Mapping (SLAM). In this paper we address the joint estimation of the path loss parameters, namely the transmitted power and the path loss exponent, this latter being usually approximated in the literature by the free space value. We provide examples that show the relevance of estimating both parameters and analyze observability issues from the point of view of estimation theory. The integration of the parameter estimation in a WLAN based SLAM algorithm - WiSLAM - has been carried out and the results are discussed.

[1]  Magnus Jobs,et al.  Accurate and reliable soldier and first responder indoor positioning: multisensor systems and cooperative localization , 2011, IEEE Wireless Communications.

[2]  Robert Harle,et al.  Pedestrian localisation for indoor environments , 2008, UbiComp.

[3]  Sebastian Thrun,et al.  FastSLAM: a factored solution to the simultaneous localization and mapping problem , 2002, AAAI/IAAI.

[4]  Xinrong Li,et al.  RSS-Based Location Estimation with Unknown Pathloss Model , 2006, IEEE Transactions on Wireless Communications.

[5]  Qing Zhang,et al.  Variable elasticity spring-relaxation: improving the accuracy of localization for WSNs with unknown path loss exponent , 2011, Personal and Ubiquitous Computing.

[6]  B. Krach,et al.  Cascaded estimation architecture for integration of foot-mounted inertial sensors , 2008, 2008 IEEE/ION Position, Location and Navigation Symposium.

[7]  Hugh F. Durrant-Whyte,et al.  Simultaneous localization and mapping: part I , 2006, IEEE Robotics & Automation Magazine.

[8]  Patrick Robertson,et al.  Simultaneous localization and mapping for pedestrians using only foot-mounted inertial sensors , 2009, UbiComp.

[9]  J. D. Parsons,et al.  The Mobile Radio Propagation Channel , 1991 .

[10]  Patrick Robertson,et al.  WiSLAM: Improving FootSLAM with WiFi , 2011, 2011 International Conference on Indoor Positioning and Indoor Navigation.

[11]  Johan Hjelm,et al.  Local Positioning Systems: LBS Applications and Services , 2006 .

[12]  Steven Kay,et al.  Fundamentals Of Statistical Signal Processing , 2001 .

[13]  Markku Renfors,et al.  Statistical path loss parameter estimation and positioning using RSS measurements in indoor wireless networks , 2012, 2012 International Conference on Indoor Positioning and Indoor Navigation (IPIN).

[14]  S. Beauregard,et al.  Indoor PDR performance enhancement using minimal map information and particle filters , 2008, 2008 IEEE/ION Position, Location and Navigation Symposium.

[15]  Chuan Heng Foh,et al.  A practical path loss model for indoor WiFi positioning enhancement , 2007, 2007 6th International Conference on Information, Communications & Signal Processing.

[16]  Neil J. Gordon,et al.  A tutorial on particle filters for online nonlinear/non-Gaussian Bayesian tracking , 2002, IEEE Trans. Signal Process..

[17]  Patrick Robertson,et al.  FootSLAM: Pedestrian Simultaneous Localization and Mapping Without Exteroceptive Sensors—Hitchhiking on Human Perception and Cognition , 2012, Proceedings of the IEEE.

[18]  Neil D. Lawrence,et al.  WiFi-SLAM Using Gaussian Process Latent Variable Models , 2007, IJCAI.

[19]  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).

[20]  Alok Aggarwal,et al.  Efficient, generalized indoor WiFi GraphSLAM , 2011, 2011 IEEE International Conference on Robotics and Automation.

[21]  Sailes K. Sengijpta Fundamentals of Statistical Signal Processing: Estimation Theory , 1995 .

[22]  Mohammad Ilyas,et al.  Location-Based Services Handbook: Applications, Technologies, and Security , 2010 .