Conference Proceeding Article
Device-free passive indoor localization is playing a critical role in many applications such as elderly care, intrusion detection, smart home, etc. However, existing device-free localization systems either suffer from labor-intensive offline training or require dedicated special-purpose devices. To address the challenges, we present our system named MaTrack, which is implemented on commodity off-the-shelf Intel 5300 Wi-Fi cards. MaTrack proposes a novel Dynamic-MUSIC method to detect the subtle reflection signals from human body and further differentiate them from those reflected signals from static objects (furniture, walls, etc.) to identify the human target's angle for localization. MaTrack does not require any offline training compared to existing signature-based systems and is insensitive to changes in environment. With just two receivers, MaTrack is able to achieve a median localization accuracy below 0.6 m when the human is walking, outperforming the state-of-the-art schemes.
indoor localization, angle-of-arrival, device-free
Computer Sciences | Software Engineering
Software and Cyber-Physical Systems
UbiComp '16: Proceedings of the 2016 ACM International Joint Conference on Pervasive and Ubiquitous Computing: Heidelberg, Germany, September 12-16, 2016
City or Country
LI, Xiang; LI, Shengjie; ZHANG, Daqing; Jie XIONG; WANG, Yasha; and MEI, Hong.
Dynamic-MUSIC: Accurate device-free indoor localization. (2016). UbiComp '16: Proceedings of the 2016 ACM International Joint Conference on Pervasive and Ubiquitous Computing: Heidelberg, Germany, September 12-16, 2016. 196-207. Research Collection School Of Information Systems.
Available at: http://ink.library.smu.edu.sg/sis_research/3390
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