Intrusion detection method based on time-frequency analysis and distributed optical fiber sensing system

The invention discloses an intrusion detection method based on time-frequency analysis and a distributed optical fiber sensing system. The intrusion detection method comprises the following steps: acquiring space-time signal data acquired by the distributed optical fiber sensing system; adopting a time-frequency analysis method to extract space-time signal data collected by the distributed optical fiber sensing system as a time-frequency characteristic matrix; and detecting and classifying intrusion events according to the time-frequency characteristic matrix by adopting a convolutional neural network. According to the method, the position of an intrusion channel can be accurately positioned, and the false alarm rate is remarkably reduced while high detection precision is kept, so that an intrusion event is effectively detected, and false alarm of interference noise is avoided. 本发明公开了一种基于时频分析和分布式光纤传感系统的入侵检测方法，包括获取分布式光纤传感系统采集的时空信号数据；采用时频分析方法将分布式光纤传感系统采集的时空信号数据提取为时频特征矩阵；采用卷积神经网络根据时频特征矩阵对入侵事件进行检测和分类。本发明能够准确定位入侵通