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ArrayTrack: A Fine-Grained Indoor Location System

Xiong, J; Jamieson, KAS; (2013) ArrayTrack: A Fine-Grained Indoor Location System. In: Proceedings of the 10th USENIX Symposium on Networked Systems Design and Implementation. Usenix: Lombard, Illinois, USA. Green open access

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Type: Proceedings paper
Title: ArrayTrack: A Fine-Grained Indoor Location System
Event: USENIX Symposium on Networked Systems Design and Implementation (NSDI 2013)
Dates: 2013-04-02 - 2013-04-05
Open access status: An open access version is available from UCL Discovery
Publisher version: https://www.usenix.org/conference/nsdi13/technical...
Language: English
Additional information: Copyright © The Authors 2013. USENIX is committed to Open Access to the research presented at our events. Papers and proceedings are freely available to everyone once the event begins. Any video, audio, and/or slides that are posted after the event are also free and open to everyone.
Keywords: With myriad augmented reality, social networking, and retail shopping applications all on the horizon for the mobile handheld, a fast and accurate location technology will become key to a rich user experience. When roaming outdoors, users can usually count on a clear GPS signal for accurate location, but indoors, GPS often fades, and so up until recently, mobiles have had to rely mainly on rather coarse-grained signal strength readings. What has changed this status quo is the recent trend of dramatically increasing numbers of antennas at the indoor access point, mainly to bolster capacity and coverage with multiple-input, multiple-output (MIMO) techniques. We thus observe an opportunity to revisit the important problem of localization with a fresh perspective. This paper presents the design and experimental evaluation of ArrayTrack, an indoor location system that uses MIMO-based techniques to track wireless clients at a very fine granularity in real time, as they roam about a building. With a combination of FPGA and general purpose computing, we have built a prototype of the ArrayTrack system. Our results show that the techniques we propose can pinpoint 41 clients spread out over an indoor office environment to within 23 centimeters median accuracy, with the system incurring just 100 milliseconds latency, making for the first time ubiquitous real-time, fine-grained location available on the mobile handset.
UCL classification: UCL
UCL > Provost and Vice Provost Offices > UCL BEAMS
UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science
UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science > Dept of Computer Science
URI: https://discovery.ucl.ac.uk/id/eprint/1389786
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