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

2SmedianMLd d e

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2

2mean

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2 22 2 3 ( 1)M S Smean e e

2 22 2 ( 1)M S SMedian e e

2 22 2 2 (1 )M S SML e e

2 2 2mML edian mean

To get more sophisticated estimators of position, variances must be considered.

0 100

log (10 )dL L n Xd

),0(~ 2shNX

Mohamed Laaraiedh, VTC Spring 2009 – Barcelona – April 29, 2009

Indirect estimators: LS and WLS

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11 ( )2

T Tx A A A h 1 1 11 ( )2

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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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2

1 2

(ln )

21,..., 1 1

1

,..., .. 1( , )2

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Path Loss : Log-Normal Shadowing

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0 lnL LMn

d

Distance : Log Normal Distribution

),0(~ 2shNX

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

8/12

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