Jie Xiong and Kyle Jamieson, University College London
Abstract:
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.
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BibTeX
@inproceedings {180296,
author = {Jie Xiong and Kyle Jamieson},
title = {{ArrayTrack}: A {Fine-Grained} Indoor Location System},
booktitle = {10th USENIX Symposium on Networked Systems Design and Implementation (NSDI 13)},
year = {2013},
isbn = {978-1-931971-00-3},
address = {Lombard, IL},
pages = {71--84},
url = {https://www.usenix.org/conference/nsdi13/technical-sessions/presentation/xiong},
publisher = {USENIX Association},
month = apr,
}
As mobile applications and services continue to grow in importance, the ability for a mobile device to quickly and accurately locate its own position (and that of its user) has also become increasingly important. The authors explore new techniques for designing efficient indoor localization. The ArrayTrack paper leverages MIMO radios to achieve more accurate localization, through some variations of some popular angle-of-arrival based techniques, in which multiple known Access Points together combine such information.
The paper is quite comprehensive in its design and implementation. The implementation was done on a FPGA-based platform and shows quite promising results. The solution requires that the AP be equipped with more antennas that are usually available in them today—the paper shows increasing accuracy as the antenna count grows from 4 to 8. While Access Points today are not usually equipped with 8 antennas, perhaps this is more likely to be true in the future. Overall, this paper presents some impressive accuracy results in the controlled settings described. A study that evaluates such systems in highly varying and mobile user environments would be worth pursuing next.
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