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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
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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)
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… 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 ???