1 ENHANCED RSSI-BASED HIGH ACCURACY REAL-TIME USER LOCATION TRACKING SYSTEM FOR INDOOR AND OUTDOOR...
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Transcript of 1 ENHANCED RSSI-BASED HIGH ACCURACY REAL-TIME USER LOCATION TRACKING SYSTEM FOR INDOOR AND OUTDOOR...
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ENHANCED RSSI-BASED HIGH ACCURACY REAL-TIME USER LOCATION TRACKING
SYSTEM FOR INDOOR AND OUTDOOR ENVIRONMENTS
Department of Computer Science and Information Engineering National Cheng Kung University, Taiwan R.O.C.
Authors: Erin-Ee-Lin Lau, Boon-Giin Lee, Seung-Chul Lee, and Wan-Young Chung
Publisher: INTERNATIONAL JOURNAL ON SMART SENSING AND INTELLIGENT SYSTEMS
Present: Yu-Tso Chen
Date: Feb, 10, 2009
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Outline
1. Introduction 2. System Design 3. Experiment Setup and Results 4. Conclusions and Future Works
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Introduction
Track a user position in both indoor and outdoor environments by using a single wireless device with minimal tracking error
By incorporating a radiolocation device (CC2431, Chipcon, Norway) which uses Zigbee
The device possesses a location estimation capability via RSSI
Computes distances based on the transmitted and RSS between blind node and reference nodes
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System Design
Blind node broadcasts request to the reference nodes
Reference nodes reply by sending their coordinates and RSSI values
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Original CC2431 Location Estimation Algo.
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Proposed Location Estimation Algo.
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Deterministic Phase
Calibrating RSSI values for each reference node
The feature of non-isotropic path loss due to the various transmission medium and direction in different environments
RSSI = - (10n log10d + A) (1)• n : signal propagation constant
• d : distance from sender
• A : received signal strength at 1 meter distance
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Relation Curve
A=40, n=3
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Deterministic Phase (cont.)
If only a single n (propagation constant) is used for all reference nodes, miscalculation of the distance occurs
Propagation constant is calculated by reversing the linear RSSI equation as shown in (1)
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Probabilistic Phase – Distance Estimation
Main challenge in RSSI-based location tracking is its high sensitivity to the environmental changes
The mobile target does not move and yet, signal strength varies over time
Smoothing algo. is proposed to minimize the dynamic fluctuation of radio signal received
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Probabilistic Phase – Distance Estimation(cont.)
There is a correlation between current positions with previous location
The basic assumption for this smoothing algorithm is that the constant velocity motion
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Estimation Stages
Prediction Stages
Converted to distances
• RSSI = - (10n log10d + A) (1)
Probabilistic Phase – Distance Estimation(cont.)
est – estimation prev – measured
Smoothed RangeRange
rate
pred – predicted
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Probabilistic Phase – Position Estimation
2 2 2
2 2 2
2 2 2
( ) ( ) ( )
( ) ( ) ( )
( ) ( ) ( )
AP A p A p
BP B p B p
CP C p C p
d x x y y
d x x y y
d x x y y
AB
C
P
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Probabilistic Phase – Position Estimation(cont.)
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Experiment Setup
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Experiment Results
Time (sec)
Time (sec)
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Comparison of Distances Between Filtered RSSI and Unfiltered data
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Comparison of Location Coordinates ( X, Y) Comp�uted by Iterative Trilateration Algo. & CC2431
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Conclusions & Future Works
Smoothing algorithm is not proposed in other systems
Apply the smoothing algorithm on distances instead of RSSI
More complicated experiment will be designed to verify the effectiveness of the proposed algorithm