Enhancing Positioning Accuracy through Direct Position Estimators based on Hybrid RSS Data Fusion How to estimate position using RSS without dealing with ranges ? Mohamed Laaraiedh Stéphane Avrillon Bernard Uguen VTC Spring 09 - Barcelona RAS Cluster Workshop April 28, 2009 IETR Labs University of Rennes 1

Mohamed Laaraiedh, VTC Spring 2009 – Barcelona – April 29, 2009 Context and Motivations RSS is usually available for free RSS measurements are less accurate then time based observables (ToA,TDoA) Historically the RSS based positioning estimators involve a step of ranging. Why not estimating position from RSS observables DIRECTLY ? MOTIVATION: to propose a new estimator able to estimate position from RSS observables without dealing with ranges. TOOLS: Monte Carlo simulations. RESULTS: A new Maximum Likelihood Estimator of position from RSS. 1/12 BS AP Femtocell

Mohamed Laaraiedh, VTC Spring 2009 – Barcelona – April 29, 2009 Outline Direct vs Indirect RSS based location estimationReview of Indirect RSS based location estimationProposed Direct Maximum Likelihood EstimatorSimulations and ResultsConclusions and Perspectives 2/12

Mohamed Laaraiedh, VTC Spring 2009 – Barcelona – April 29, 2009 Direct vs Indirect estimators 3/12 Indirect EstimationDirect Estimation RSS1RSS2RSSn … r1r2rn … Range Based Estimator Position x RSS1RSS2RSSn … Direct RSS Based Estimator Position x WLS LS others ML estimator

Mohamed Laaraiedh, VTC Spring 2009 – Barcelona – April 29, 2009 Indirect estimators: RSS ranging 5/12 To get more sophisticated estimators of position, variances must be considered.

Mohamed Laaraiedh, VTC Spring 2009 – Barcelona – April 29, 2009 Indirect estimators: LS and WLS 7/12 evaluated from K anchor nodes positions evaluated from estimated ranges and anchor nodes coordinates LS estimator WLS estimator

Mohamed Laaraiedh, VTC Spring 2009 – Barcelona – April 29, 2009 Proposed ML Direct Estimator 8/12 Path Loss : Log-Normal Shadowing Distance : Log Normal Distribution

Mohamed Laaraiedh, VTC Spring 2009 – Barcelona – April 29, 2009 Estimation of Path loss parameters It is necessary to learn the Path Loss Model Parameters from the channel. How to improve Path Loss Model relevance ? For each fixed AP or BS Continuously update and keep track of 3 parameters 6/12

Mohamed Laaraiedh, VTC Spring 2009 – Barcelona – April 29, 2009 Simulations and Results 8/12 Path loss Parameters IndoorOutdoor npnp 1.6 to 1.82 to 4 l(m) σ sh 2 to 5 Square Length (m)

Mohamed Laaraiedh, VTC Spring 2009 – Barcelona – April 29, 2009 Simulations and Results 8/12

Mohamed Laaraiedh, VTC Spring 2009 – Barcelona – April 29, 2009 Simulations and Results 8/12

Mohamed Laaraiedh, VTC Spring 2009 – Barcelona – April 29, 2009 Simulations and Results 8/12

Mohamed Laaraiedh, VTC Spring 2009 – Barcelona – April 29, 2009 Conclusions & Perspectives A new ML estimator of position from RSS observables. This ML estimator performs better than Indirect estimators. Evaluate these estimators on Real Measurements and Ray tracing simulations. 11/12 Differences between Direct and Indirect approaches in RSS based Localization. Indirect estimators performances depend on the technique of RSS ranging. Pipe these estimators in Tracking processes using Klaman and Particle Filters. On-line estimation of path loss parameters.

Mohamed Laaraiedh, VTC Spring 2009 – Barcelona – April 29, 2009 Bibliography 12/12 [1] P. Bellavista, A. Kupper, and S. Helal, “Location-based services: Back to the future,” IEEE, Pervasive Computing, [2] “ [3] H. Laitinen, S. Juurakko, T. Lahti, R. Korhonen, and J. Lahteenmaki, “Experimental evaluation of location methods based on signal-strength measurements,” IEEE transactions on vehicular technology, vol. 56, Jan [4] A. Goldsmith, Wireless communications [5] H. Liu, H. Darabi, P. Banerjee, and J. Liu, “Survey of wireless indoor positioning techniques and systems,” IEEE Transactions on systems, man, and cybernetics, vol. 37, Nov [6] K. Cheung, H. So, W. Ma, and Y. Chan, “A constrained least squares approach to mobile positioning: Algorithms and optimality,” [7] T. Gigl, G. J. M. Janssen, V. Dizdarevic, K. Witrisal, and Z. Irahhauten, “Analysis of a uwb indoor positioning system based on received signal strength,” WPNC 07, [8] M. Sugano and T. Kawazoe, “Indoor localization system using rssi measurement of wireless sensor network based on zigbee standard,” WSN 06, July [9] S. Frattasi, M. Monti, and P. Ramjee, “A cooperative localization scheme for 4g wireless communications,” IEEE Radio and Wireless Symposium, [10] V. Abhayawardhana, W. Crosby, M. Sellars, and M. Brown, “Comparison of empirical propagation path loss models for fixed wireless access systems,” IEEE VTC spring, [11] K. Whitehouse, C. Karlof, and D. Culler, “A practical evaluation of radio signal strength for ranging-based localization,” Mobile Computing and Communications Review, vol. 11, no. 1, [12] M. P.McLaughlin, A Compendium of Common Probability Distributions, vol. Regress+ Documentation [13] M.Laaraiedh, S.Avrillon, B.Uguen. Hybrid Data Fusion Techniques for Localization in UWB Networks. In Proceedings WPNC Hanover, Germany, March [14] S. Sand, C. Mensing, M. Laaraiedh, B. Uguen, B. Denis, S. Mayrargue, M. García, J. Casajús, D. Slock, T. Pedersen, X. Yin, G. Steinboeck, and B. H. Fleury. Performance Assessment of Hybrid Data Fusion and Tracking Algorithms. In Accepted for publication in Proceedings ICT Mobile Summit (ICT Summit 2009), Santander, Spain, June [15] M.Laaraiedh, S.Avrillon, B.Uguen. Enhancing positioning accuracy through RSS based ranging and weighted least square approximation. POCA, Antwerp, Belgium, May, 2009.

Enhancing Positioning Accuracy through Direct Position Estimators based on Hybrid RSS Data Fusion How to estimate position using RSS without dealing with ranges ? Mohamed Laaraiedh Stéphane Avrillon Bernard Uguen VTC Spring 09 - Barcelona RAS Cluster Workshop April 29, 2009 IETR Labs University of Rennes 1