RADAR An In Building RF based User Location and Tracking System Venkat Padmanabhan and Victor Bahl Microsoft Research Presented by Yanhua Mao Outline Motivation and related work RADAR Generating a radio map NNSS algorithm Performance Evaluation Summary Motivation Location aware services are key ingredient of mobile computing Determining user location is a prerequisite to building such services Solution designed for the outdoors e g GPS are ineffective indoors Related Work in Indoor Positioning Systems Infrared based systems e g Active Badge Accurate due to short range and line of sight property But scales poorly requires specialized infrastructure Radio Frequency based systems Cell level granularity using point of attachment Duress Alarm Location System PinPoint Alternative technologies magnetic optical acoustic Very accurate mm to cm resolution But requires dedicated infrastructure Targeted at specialized application e g head tracking Our Approach Leverage existing infrastructure Use an off the shelf RF wireless LAN Several advantages WLAN deployed primarily to provide data connectivity Software adds value to wireless hardware Better scalability and lower cost than dedicated technology RADAR Key idea signal strength matching Offline calibration Tabulate map location SS to construct radio Real time location tracking Extract SS from base station beacons Find table entry that best matches the measured SS Constructing a Radio Map Empirical method Measure SS at various locations using BS beacons Record SS along with corresponding coordinates User orientation need to be included too Tuples of the form x y z d s1 sn Mathematical method Compute SS using a simple propagation model Factor in free space loss and wall attenuation Apply Cohen Sutherland line clipping algorithm on building layout More convenient but less accurate Determining Location Find nearest neighbor in signal space NNSS Default metric is Euclidean distance Physical coordinates of NNSS user location Refinement k NNSS Average the coordinates of k nearest neighours N1 T N2 G N3 N1 N2 N3 neighbors T true location of user Guess based on averaging Experimental Setting Digital RoamAbout WaveLAN 2 4 GHz ISM band 2 Mbps data rate 3 base stations 70x4 280 x y d tuples How good an indicator of location is signal strength Base line performance Median error distance is 2 94 meters Performance with averaging Median error distance is 2 13 meters when averaging is done over 3 neighbors How extensive the Radio Map have to be Diminishing as the number of physical points mapped increased Signal Propagation Model d nW WAF P d dbm P d 0 dbm 10n log d 0 C WAF nW C nW C How well done it work Median error distance is 4 94 m compared to 2 94 m with empirically constructed radio map and 8 16 m with nearest base station method Summary Determine user location via signal strength matching Radio map constructed via empirical measurements Median error 2 3 meters with empirical map Leverages existing wireless LAN infrastructure
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