Name
Abstract | ||
|---|---|---|
With the eruptible popularity of wireless sensing, wireless device-free passive human detection has received widespread attention. Indoor fine-grained device-free passive human motion detection based on the PHY layer information is rapidly developed. Since the received signal features can vary under different multipath propagation conditions, in the paper, we propose a lightweight and real-time passive human motion via physical layer phase information, which is independent of the indoor scenarios and needs no re-calibration. We firstly obtain available phase feature by a linear transformation on the raw channel state information(CSI). The real-time human motion detection is implemented based on two developed schemes: short-term averaged variance ratio (SVR) and long-term averaged variance ratio (LVR). We realize the design with commercial WiFi devices and evaluate it in typical multipath-rich indoor scenarios. As demonstrated in the experiments, our approach can achieve high detection rate and low false positive rate. |
Year | DOI | Venue |
|---|---|---|
2015 | 10.1109/UIC-ATC-ScalCom-CBDCom-IoP.2015.65 | 2015 IEEE 12th Intl Conf on Ubiquitous Intelligence and Computing and 2015 IEEE 12th Intl Conf on Autonomic and Trusted Computing and 2015 IEEE 15th Intl Conf on Scalable Computing and Communications and Its Associated Workshops (UIC-ATC-ScalCom) |
Keywords | Field | DocType |
PHY layer,CSI,Phase,Motion Detection | Multipath propagation,False positive rate,Wireless,Motion detection,Simulation,Computer science,Real-time computing,Human motion,Physical layer,Linear map,Channel state information,Distributed computing | Conference |
ISBN | Citations | PageRank |
978-1-4673-7212-1 | 0 | 0.34 |
References | Authors | |
3 | 5 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Liangyi Gong | 1 | 38 | 14.57 |
| Dapeng Man | 2 | 29 | 10.54 |
| Jiguang Lv | 3 | 11 | 4.32 |
| Guowei Shen | 4 | 0 | 0.68 |
| Yang Wu | 5 | 69 | 22.62 |