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GPS-less Low-Cost Outdoor Localization for Very Small Devices. Nirupama Bulusu, John Heidemann, and Deborah Estrin. Design Goals. RF-based Receiver-based Ad hoc Responsive Low Energy Adaptive Fidelity. In this paper …. Related Work Algorithm for Coarse-grained Localization - PowerPoint PPT Presentation
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GPS-less Low-Cost Outdoor Localizationfor Very Small Devices
Nirupama Bulusu, John Heidemann, and Deborah Estrin
Design Goals
RF-based Receiver-based Ad hoc Responsive Low Energy Adaptive Fidelity
In this paper …
Related Work Algorithm for Coarse-grained
Localization Implementation Results
Related Work
Fine-Grained Localization
Coarse-Grained Localization
Fine-Grained Localization
Range Finding Timing Signal Strength Signal Pattern Matching
Directionality Based Electrical Phasing Small aperture Direction Finding
Timing
Time of flight of communication signal Signal Pattern
Global Positioning System Local Positioning System Pinpoint’s 3D-iD
Different modalities of communication Active Bat
Signal Strength
Attenuation of radio signal increases with increasing distance
RADAR Wall Attenuation Factor based Signal
Propagation Model RF mapping
Signal Pattern Matching
Multi-path phenomenon Signature unique to given location Data from single point sufficient Robust Substantial effort needed for
generating signature database
Fine-Grained Localization
Range Finding Timing Signal Strength Signal Pattern Matching
Directionality Based Electrical Phasing Small aperture Direction Finding
Small Aperture Direction Finding
Used in cellular networks Requires complex antenna array Disadvantages
Costly Not a receiver based approach
Coarse-Grained Localization
Infrared Active Badge – fixed sensors Fixed transmitters Disadvantages
Scales poorly Incurs significant installation,
configuration and maintenance costs
Localization Algorithm Multiple nodes serve as Reference points
Reference points transmit periodic beacon signals containing their positions
Receiver node finds reference points in its range and localizes to the intersection of connectivity regions of these points
An Idealized Radio Model
Perfect spherical radio propagation
Identical transmission range for all radios
Terms
d : Distance b/w adjacent ref. points
R : Transmission range of reference point
T : Time interval between two successive
beacons
t : Receiver sampling time
Nsent(i,t) : No. of beacons sent by Ri in time t
Nrecv(i,t) : No. of beacons sent by Ri received in t
contd…
CMi : Connectivity metric for Ri
S : Sample size for
connectivity metric
CMthresh : Threshold for CM
(Xest, Yest) : Estimated location of
receiver
(Xa, Ya) : Actual location of receiver
contd… CMi = (Nrecv(i,t) / Nsent(i,t)) * 100
t = (S + 1 + ε) * T , 0 < ε « 1
k = No. of reference points within connectivity range
(Xest, Yest) = (avg(Xi1+…+Xik), avg(Yi1+…+Yik))
LE = Sqrt( (Xest – Xa)2 + (Yest – Ya)2)
Model
Validation of Model
78 points measured
68 correct matches
Mismatches were all at the edge
Error <= 2m
CMthresh = 90
R = 8.94m
Results
T = 2s
S = 20
t = 41.9s
d = 10m
contd…
Average error 1.83m
Standard deviation 1.07m
Max. error 4.12m
contd…
contd…
Simulation to check the effect of increasing the overlap of ref. points
Calculated for 10,201 points
NO MONOTONIC INCREASE
Discussion and Future Work
Collision Avoidance Tuning for Energy Conservation Non-uniform reference point
placement Reference Point Configuration Robustness Adaptation to Noisy Environment
Questions
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