Multi-person localization via RF body reflections
Name
Katabi_Multi-person localization.pdf
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2.05 MB
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Adobe PDF
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Author(s)
Adib, Fadel
Kabelac, Zachary E.
Katabi, Dina
Date Issued
May 2015
Journal
12th USENIX Symposium on Networked Systems Design and Implementation
Publisher
USENIX Association
Citation
Adib, Fadel, Zachary Kabelac, and Dina Katabi. "Multi-Person Localization via RF Body Reflections." 12th USENIX Symposium on Networked Systems Design and Implementation." 4-6 May, 2015, Oakland, California, USENIX, 2015.
Version
Author's final manuscript
Abstract
We have recently witnessed the emergence of RF-based indoor localization systems that can track user motion without requiring the user to hold or wear any device. These systems can localize a user and track his gestures by relying solely on the reflections of wireless signals off his body, and work even if the user is behind a wall or obstruction. However, in order for these systems to become practical, they need to address two main challenges: 1) They need to be able to operate in the presence of more than one user in the environment, and 2) they must be able to localize a user without requiring him to move or change his position.
This paper presents WiTrack2.0, a multi-person localization system that operates in multipath-rich indoor environments and pinpoints users’ locations based purely on the reflections of wireless signals off their bodies. WiTrack2.0 can even localize static users, and does so by sensing the minute movements due to their breathing.We built a prototype of WiTrack2.0 and evaluated it in a standard office building. Our results show that it can localize up to five people simultaneously with a median accuracy of 11.7 cm in each of the x=y dimensions. Furthermore, WiTrack2.0 provides coarse tracking of body parts, identifying the direction of a pointing hand with a median error of 12.5º, for multiple users in the environment.
MIT Department
Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science
Program in Media Arts and Sciences (Massachusetts Institute of Technology)
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Creative Commons Attribution-Noncommercial-Share Alike
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DOI of Published Version
https://www.usenix.org/node/188986
