相位敏感光时域反射仪的信号处理方法综述

Signal processing methods of phase sensitive optical time domain reflectometer:a review

相位敏感光时域反射仪由于具备监测范围广、灵敏度高等优点被广泛应用于周界安防等领域。近年来,研究者对其光学系统的改进使得传感距离更长、空间分辨率更高。但需要处理的数据量大大增加,且环境噪声以及扰动类型多样给分布式扰动传感系统的实际应用带来了挑战。本文总结了提高该系统信号信噪比、扰动识别率等性能指标的信号处理方法,包括降噪算法、特征提取算法、机器学习以及深度学习算法,尽可能地对比各种算法的优劣,并展望了未来该领域信号处理方法可能的发展方向。

Phase-sensitive optical time domain reflectometry is widely used in perimeter security and other fields because of its advantages of wide monitoring range and high sensitivity.In recent years,researchers have improved optical systems to increase sensing distance and spatial resolution,thus greatly increasing the amount of data that needs to be processed.In addition,strong environmental noise and diverse types of vibrations bring challenges to the practical application of distributed vibration sensing systems.This study summarizes the signal processing methods used to improve the signal-to-noise ratio and vibration recogni⁃tion rate of the system,including noise reduction algorithms,feature extraction algorithms,machine learn⁃ing,and deep learning algorithms;compares the advantages and disadvantages of different algorithms;and finally outlines the possible direction of signal processing methods in this field in the future.