Name
Abstract | ||
|---|---|---|
Optical fiber has been widely used for security monitoring due to its sensitive phase and amplitude reacting from external vibration. However, it is difficult to extract the intrusion characteristics of optical fiber and identify intrusion in windy conditions. To solve this problem, we introduce a state space model for the optical fiber detection system and propose two intrusion detection methods, e.g., estimating noise variance based on system identification and calculating cross output reconstruction error. The accuracy and effectiveness of the two methods are demonstrated by field data collected in windy environment. The results show that the proposed methods outperform compared existing methods in both performance and robustness. |
Year | DOI | Venue |
|---|---|---|
2022 | 10.1587/elex.19.20220098 | IEICE ELECTRONICS EXPRESS |
Keywords | DocType | Volume |
intrusion detection, system identification, Kalman filter, reconstruction error | Journal | 19 |
Issue | ISSN | Citations |
8 | 1349-2543 | 0 |
PageRank | References | Authors |
0.34 | 0 | 6 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Yuting Zhu | 1 | 0 | 0.34 |
| Jianghui Li | 2 | 0 | 0.34 |
| Qiong Wang | 3 | 0 | 0.34 |
| Chunhua Yu | 4 | 0 | 0.34 |
| Lan Tang | 5 | 39 | 7.39 |
| Yechao Bai | 6 | 0 | 0.68 |