相位敏感光时域反射计(φ-OTDR)在光纤围栏等动态传感领域具有重要的应用，快速、有效地对入侵信号分类识别有着十分重要的意义。基于频谱分析提出了一种称为频谱欧氏距离法(EDFS)的快速模式识别方法。该方法通过短时平移差分和短时能量法对f-OTDR 的解调信号进行提取，确定待分析数据段；对数据段进行归一化和快速傅里叶变换，获得信号的频谱特征；计算信号频谱与预先生成的模板之间的欧氏距离对入侵信号进行分类、识别。采用三种入侵信号对该方法的有效性和实时性进行了实验验证。结果表明，该模式识别方法可以有效识别扰动信号，识别时间小于传统的动态时域规划模式识别方法耗时的1/10。同时，该方法所需训练样本较少，对环境噪声有一定程度的抑制作用。

Phase sensitive optical time domain reflectometer (φ-OTDR) becomes more and more important in intrusion alarming and other dynamic sensing fields. Meanwhile, it makes much sense to classify the intrusion fast and effectively. Therefore, a fast pattern recognition method based on frequency spectrum is presented and experimentally verified. The proposed method is named EDFS, short for Euclidean distance of fast Fourier transform (FFT) frequency spectrum of the detected signals. The signal is abstracted by short-time shifted delta(SSD)and short- time energy, and the features are obtained from the abstracted signal after normalization and FFT transformation. The euclidean distance of the spectra between features and models is used to classify the intrusion. The effectivity and instantaneity are verified by three typical intrusion disturbances. It is shown experimentally that intrusions can be recognized clearly in a period less than one tenth of that by conventional dynamic time warping (DTW). The method needs fewer training models than other recognition methods, such as the neural network, and has a merit of mitigating influence of environmental noises.