Intrusion signal recognition method based on φ-OTDR fiber distributed sensing research progress

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, timefrequency 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.