TY - GEN
T1 - Dynamic-MUSIC
T2 - 2016 ACM International Joint Conference on Pervasive and Ubiquitous Computing, UbiComp 2016
AU - Li, Xiang
AU - Li, Shengjie
AU - Zhang, Daqing
AU - Xiong, Jie
AU - Wang, Yasha
AU - Mei, Hong
N1 - Publisher Copyright:
© ACM.
PY - 2016/9/12
Y1 - 2016/9/12
N2 - 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.
AB - 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.
KW - Angle-of-arrival
KW - Device-free
KW - Indoor localization
UR - https://www.scopus.com/pages/publications/84991512010
U2 - 10.1145/2971648.2971665
DO - 10.1145/2971648.2971665
M3 - Conference contribution
AN - SCOPUS:84991512010
T3 - UbiComp 2016 - Proceedings of the 2016 ACM International Joint Conference on Pervasive and Ubiquitous Computing
SP - 196
EP - 207
BT - UbiComp 2016 - Proceedings of the 2016 ACM International Joint Conference on Pervasive and Ubiquitous Computing
PB - Association for Computing Machinery
Y2 - 12 September 2016 through 16 September 2016
ER -