Name
Abstract | ||
|---|---|---|
In recent years, due to the rapidly growing capacities of physical layer, device-free passive detection holds great importance for a broad range of application. Most recent works focus on motion detection, intrusion detection, and vital sign with commodity WiFi devices in the indoor environment. Conventional device-free motion detection techniques, which utilize received signal strength (RSS), may suffer from coarse granularity and high variability problems. In resorting to the finer-grained channel state information (CSI), we propose PhaseMode, a novel approach for device-free motion detection leveraging CSI phase difference data between adjacent antenna pairs. We implement our approach on commercial WiFi devices and validate its performance. We conduct experiments in different test periods of three indoor environments; the results show that the proposed scheme achieves an average accuracy over 99.4% of motion detection in different scenarios. |
Year | DOI | Venue |
|---|---|---|
2018 | 10.1155/2018/8243905 | JOURNAL OF SENSORS |
Field | DocType | Volume |
Motion detection,Passive detection,Electronic engineering,Real-time computing,Physical layer,Signal strength,Engineering,Granularity,RSS,Intrusion detection system,Channel state information | Journal | 2018 |
ISSN | Citations | PageRank |
1687-725X | 1 | 0.35 |
References | Authors | |
10 | 5 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Enjie Ding | 1 | 109 | 11.52 |
| Xiansheng Li | 2 | 1 | 0.35 |
| Tong Zhao | 3 | 14 | 7.30 |
| Lei Zhang | 4 | 1 | 0.35 |
| yanjun hu | 5 | 10 | 3.81 |