Enhancing Positioning Accuracy through Direct Position Estimators based on Hybrid RSS Data Fusion

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

2. 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 anew estimator able to estimate position from RSS observables without dealing with ranges. TOOLS:Monte Carlosimulations. RESULTS:A newMaximum Likelihood Estimatorof position from RSS. BS Femtocell AP 1/12 1/12

3. Direct vs Indirect RSS based location estimation Review of Indirect RSS based location estimation Proposed Direct Maximum Likelihood Estimator Simulations and Results Conclusions and Perspectives Outline 2/12

4. Direct vs Indirect estimators Indirect Estimation Direct Estimation … … RSS1 RSS2 RSSn RSS1 RSS2 RSSn … r1 r2 rn Direct RSS Based Estimator Range Based Estimator WLS LS others ML estimator Position x Position x 3/12

5. To get more sophisticated estimators of position, variances must be considered. Indirect estimators: RSS ranging 5/12

6. Indirect estimators: LS and WLS evaluated from K anchor nodes positions evaluated from estimated ranges and anchor nodes coordinates LS estimator WLS estimator 7/12

7. Proposed ML Direct Estimator Path Loss : Log-Normal Shadowing Distance : Log Normal Distribution 8/12

8. How to improve Path Loss Model relevance ? For each fixed AP or BS Continuously update and keep track of 3 parameters Estimation of Path loss parameters It is necessary to learn the Path Loss Model Parameters from the channel. 6/12

9. Simulations and Results 8/12

10. Simulations and Results 8/12

11. Simulations and Results 8/12

12. Simulations and Results 8/12

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

14. Bibliography [1] P. Bellavista, A. Kupper, and S. Helal, “Location-based services: Back to the future,” IEEE, Pervasive Computing, 2008. [2] “http://www.kn-s.dlr.de/where/.” [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. 2007. [4] A. Goldsmith, Wireless communications. 2005. [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. 2007. [6] K. Cheung, H. So, W. Ma, and Y. Chan, “A constrained least squares approach to mobile positioning: Algorithms and optimality,” 2006. [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, 2007. [8] M. Sugano and T. Kawazoe, “Indoor localization system using rssi measurement of wireless sensor network based on zigbee standard,” WSN 06, July 2006. [9] S. Frattasi, M. Monti, and P. Ramjee, “A cooperative localization scheme for 4g wireless communications,” IEEE Radio and Wireless Symposium, 2006. [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, 2005. [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, 2007. [12] M. P.McLaughlin, A Compendium of Common Probability Distributions, vol. Regress+ Documentation. 1999. [13] M.Laaraiedh, S.Avrillon, B.Uguen. Hybrid Data Fusion Techniques for Localization in UWB Networks. In Proceedings WPNC Hanover, Germany, March 2009.[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 2009.[15] M.Laaraiedh, S.Avrillon, B.Uguen. Enhancing positioning accuracy through RSS based ranging and weighted least square approximation. POCA, Antwerp, Belgium, May, 2009. 12/12

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