Towards fine-grained radio-based indoor location
Location systems are key to a rich experience for mobile users. When they roam outdoors, mobiles can usually count on a clear GPS signal for an accurate location, but indoors, GPS usually fades, and so up until recently, mobiles have had to rely mainly on rather coarse-grained signal strength readin...
Saved in:
| Main Authors: | , |
|---|---|
| Format: | text |
| Language: | English |
| Published: |
Institutional Knowledge at Singapore Management University
2012
|
| Subjects: | |
| Online Access: | https://ink.library.smu.edu.sg/sis_research/2706 https://ink.library.smu.edu.sg/context/sis_research/article/3706/viewcontent/a13_xiong.pdf |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| Institution: | Singapore Management University |
| Language: | English |
| Summary: | Location systems are key to a rich experience for mobile users. When they roam outdoors, mobiles can usually count on a clear GPS signal for an accurate location, but indoors, GPS usually fades, and so up until recently, mobiles have had to rely mainly on rather coarse-grained signal strength readings for location. What has changed this status quo is the recent trend of dramatically increasing numbers of antennas at the indoor AP, mainly to bolster capacity and coverage with multiple-input, multiple-output (MIMO) techniques. In the near future, the number of antennas at the access point will increase several-fold, to meet increasing demands for wireless capacity with MIMO links, spatial division multiplexing, and interference management. 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 in real time as they roam about a building. We prototype ArrayTrack on a WARP platform, emulating the capabilities of an inexpensive 802.11 wireless access point. Our results show that ArrayTrack can pinpoint 33 clients spread out over an indoor office environment to within a 36 cm location accuracy. |
|---|