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‰ Cluster: Set of locations sharing a common set of Access points ‰ Cluster key: This set of Access points i

The Horus WLAN location determination system

MobiSys, pp.205-218, (2005)

Cited by: 1372|Views164
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Abstract

We present the design and implementation of the Horus WLAN location determination system. The design of the Horus system aims at satisfying two goals: high accuracy and low computational requirements. The Horus system identifies different causes for the wireless channel variations and addresses them to achieve its high accuracy. It uses l...More

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Introduction
  • † WLAN Location Determination System † Wireless Channel Characteristics † The Horus System † Experimental Evaluation † Conclusions.
  • The Horus WLAN Location Determination System
  • WLAN Location Determination System
  • Location Determination System
  • † Online location determination
  • „ Using SS samples „ search the radio map „ estimate the user location
Highlights
  • † WLAN Location Determination System † Wireless Channel Characteristics † The Horus System † Experimental Evaluation † Conclusions
  • ‰ Cluster: Set of locations sharing a common set of Access points ‰ Cluster key: This set of Access points i
  • „ If one sample includes signal strength (s1,s2,...sk), the system will try all combinations of si, si(1+d), si(1-d) and chose the nearest location to the previous location as the final location estimate
  • We suppose after 5 seconds, the estimates are {(3, 6), (3, 2), (3, 6), (1, 6), (3, 6)} The technique estimates the current location as X = (3+3+3+1+3)/5 = 2.6 Y = (6+2+6+6+6)/5 = 5.2
Results
  • † Variations occur when the receiver position is changed.
  • Cluster radio map locations
  • † Distribution of correlated samples Gaussian mean μ and variance 1+α σ 2 1−α
  • To estimate the distribution parameters (μ, σ and α) .
  • These distribution parameters (μ, σ and α) are stored in the radio map.
  • Estimate user location
  • Discrete Space Estimator
  • † Offline phrase, estimation of SS distribution for ∀ AP at ∀ location.
  • † Given Æ SS distribution for ∀ AP , Compute Æ Probability ∀ location
  • Small-Scale Compensator
  • † Detection small-scale variations
  • 1. User’s location cannot change faster than their moving rate.
  • 2. If distance between estimated location and previous location, there are small-scale variations
  • † Compensating for small-scale variations(Perturbation technique)
  • „ If one sample includes signal strength (s1,s2,...sk), the system will try all combinations of si, si(1+d), si(1-d) and chose the nearest location to the previous location as the final location estimate.
  • Continuous Space Estimator
  • † To increase the accuracy, the Horus System uses two techniques to obtain a location estimation in the continuous space:
  • „ Time-Averaging in the Physical Space
  • The authors suppose after 5 seconds, the estimates are {(3, 6), (3, 2), (3, 6), (1, 6), (3, 6)} The technique estimates the current location as X = (3+3+3+1+3)/5 = 2.6 Y = (6+2+6+6+6)/5 = 5.2
  • The radio map has 110 locations along the corridors and 62 locations inside the room The training data was placed 1.52 meters apart
Conclusion
  • Effect of changing the perturbation fraction on average distance error(Small-Scale Compensator)
  • As the threshold value increases, the number of access points consulted increases, and so does the accuracy.
  • More than 90% estimates have error distance less than 1 meter
  • † This system approaches the WLAN-based location determination system by identifying the various causes of variations in a wireless system.
  • † By using correlation handling and perturbation technique, the accuracy is enhanced.
  • † The Horus system has achieved high accuracy and low computational
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