Paper
18 December 2023 Intrusion signal recognition method based on Φ-OTDR fiber distributed sensing research progress
Author Affiliations +
Proceedings Volume 12968, AOPC 2023: Optic Fiber Gyro ; 129680D (2023) https://doi.org/10.1117/12.3000044
Event: Applied Optics and Photonics China 2023 (AOPC2023), 2023, Beijing, China
Abstract
The optical fiber distributed vibration/acoustic wave sensing system (DVS/DAS) based on phase-sensitive optical time-domain reflection (Φ-OTDR) technology detects vibration/acoustic wave signals along optical fibers by detecting backward Rayleigh scattered light, which has the advantages of long detection distance, high spatial resolution, and wide detection frequency range compared with traditional electronic monitoring systems. In recent years, the pattern recognition technology of DVS/DAS for the purpose of identifying intrusion signals has received wide attention and has been widely used in national defense technology, aerospace, perimeter security, oil and gas pipeline security monitoring and other fields. This paper analyzes and summarizes the feature extraction methods in intrusion signal recognition from four aspects: time domain, frequency domain, time-frequency domain, and space-time domain, and then summarizes the relevant progress of pattern recognition algorithms in the field of intrusion detection of DVS/DAS in recent years from two aspects: machine learning and deep learning.
(2023) Published by SPIE. Downloading of the abstract is permitted for personal use only.
Xiaodong Wang, Chang Wang, Faxiang Zhang, Shaodong Jiang, Zhihui Sun, Zhenguo Yang, Hongyu Zhang, Zhaoying Liu, and Zhenhui Duan "Intrusion signal recognition method based on Φ-OTDR fiber distributed sensing research progress", Proc. SPIE 12968, AOPC 2023: Optic Fiber Gyro , 129680D (18 December 2023); https://doi.org/10.1117/12.3000044
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KEYWORDS
Feature extraction

Signal processing

Vibration

Detection and tracking algorithms

Pattern recognition

Signal detection

Education and training

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