Download - Enhancing Positioning Accuracy through Direct Position Estimators based on Hybrid RSS Data Fusion
Enhancing Positioning Accuracy through Direct Position Estimators based on Hybrid RSS Data
Fusion
How to estimate position using RSS without dealing with ranges ?
Mohamed LaaraiedhStéphane Avrillon
Bernard Uguen
VTC Spring 09 - BarcelonaRAS Cluster Workshop
April 28, 2009
IETR Labshttp://www.ietr.org
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.
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BS
APFemtocell
Mohamed Laaraiedh, VTC Spring 2009 – Barcelona – April 29, 2009
Outline
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
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Mohamed Laaraiedh, VTC Spring 2009 – Barcelona – April 29, 2009
Direct vs Indirect estimators
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Indirect Estimation Direct Estimation
RSS1 RSS2 RSSn…
r1 r2 rn…
Range Based Estimator
Position x
RSS1 RSS2 RSSn…
Direct RSS Based Estimator
Position x
WLSLSothers
MLestimator
Mohamed Laaraiedh, VTC Spring 2009 – Barcelona – April 29, 2009
Indirect estimators: RSS ranging
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To get more sophisticated estimators of position, variances must be considered.
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Mohamed Laaraiedh, VTC Spring 2009 – Barcelona – April 29, 2009
Indirect estimators: LS and WLS
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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
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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.
10log d
( )L dBHow to improve Path Loss Modelrelevance ?
For each fixed AP or BS
Continuously update and keep track of 3 parameters
0 0 1, , ( , , , , , )ksh k shk kn L LR k L d n L
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Mohamed Laaraiedh, VTC Spring 2009 – Barcelona – April 29, 2009
Simulations and Results
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Path loss Parameters
Indoor Outdoor
np1.6 to 1.82 to 4
l(m)0.12 0.33σsh2 to 52 to 5
Square Length (m)
151000
Mohamed Laaraiedh, VTC Spring 2009 – Barcelona – April 29, 2009
Simulations and Results
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Mohamed Laaraiedh, VTC Spring 2009 – Barcelona – April 29, 2009
Simulations and Results
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Mohamed Laaraiedh, VTC Spring 2009 – Barcelona – April 29, 2009
Simulations and Results
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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.
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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
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[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.
Enhancing Positioning Accuracy through Direct Position Estimators based on Hybrid RSS Data
Fusion
How to estimate position using RSS without dealing with ranges ?
Mohamed LaaraiedhStéphane Avrillon
Bernard Uguen
VTC Spring 09 - BarcelonaRAS Cluster Workshop
April 29, 2009
IETR Labshttp://www.ietr.org
University of Rennes 1