1. Enhancing Positioning Accuracy Through RSS Based Ranging and Weighted Least Square Approximation How to enhance RSS based ranging and localization by learning the channel ? Mohamed Laaraiedh Stéphane Avrillon Bernard Uguen POCA 09 - Antwerpen May 28, 2009 IETR Labs http://www.ietr.org University of Rennes 1

2. Mohamed Laaraiedh, POCA 2009 – Antwerpen – May 28, 2009 Context and Motivations RSS measurements are less accurate then time based observables (ToA,TDoA) RSS is usually available for free RSS can be modelled as a function of distance: Path Loss models Path loss models can be updated using RSS measurements How can the knowledge of channel enhance RSS based localization and ranging accuracies? 1/12

3. Mohamed Laaraiedh, POCA 2009 – Antwerpen – May 28, 2009 Outline Learning of radio propagation channelRSS based ranging estimatorsRSS based LocalizationSimulations and ResultsConclusions and Perspectives 2/12

4. Mohamed Laaraiedh, POCA 2009 – Antwerpen – May 28, 2009 Ranging and Localization 3/12 Ranging Step RSS 1 RSS 2 RSS n … r1r1 r2r2 rnrn … Range Based Estimator Position x WLS LS Localization Step

5. Mohamed Laaraiedh, POCA 2009 – Antwerpen – May 28, 2009 Indirect estimators: RSS ranging 4/12 To get more sophisticated estimators of position, variances must be considered.

6. Mohamed Laaraiedh, POCA 2009 – Antwerpen – May 28, 2009 Learning of Radio Channel 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 numbers 5/12

7. Mohamed Laaraiedh, POCA 2009 – Antwerpen – May 28, 2009 LS and WLS Approximations 6/12 evaluated from K anchor nodes positions evaluated from estimated ranges and anchor nodes coordinates LS estimator WLS estimator

8. Mohamed Laaraiedh, POCA 2009 – Antwerpen – May 28, 2009 Simulations and Results 7/12 Path loss Parameters IndoorOutdoor npnp 1.6 to 1.82 to 4 l(m)0.120.33 σ sh 2 to 5 Square Length (m) 151000

9. Mohamed Laaraiedh, POCA 2009 – Antwerpen – May 28, 2009 Simulations and Results 8/12 Performances in outdoor scenario

10. Mohamed Laaraiedh, POCA 2009 – Antwerpen – May 28, 2009 Simulations and Results 9/12 Performances in indoor scenario

11. Mohamed Laaraiedh, POCA 2009 – Antwerpen – May 28, 2009 Conclusions & Perspectives A new ML estimator of Ranges from RSS observables is proposed. Localization and Ranging accuracies depend on PL parameters. Evaluate these estimators on Real Measurements and Ray tracing simulations. 10/12 How interesting is the learning of channel for localization and ranging. Localization accuracy depends on the used technique for RSS ranging. Pipe these estimators in Tracking processes using Klaman and Particle Filters. A direct approach for RSS based localization is already published in VTC Spring

12. Mohamed Laaraiedh, POCA 2009 – Antwerpen – May 28, 2009 Bibliography 11/12 [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.