基于光纤迈克耳孙干涉仪和神经网络模式识别算法，设计并实现了一种新的防区型全光纤周界安防系统。采用偏振不敏感光纤迈克耳孙干涉仪作为周界入侵探测系统(PIDS)的振动传感器，降低了双折射效应导致的信号衰落，分析了传感光纤与物理围栏宿主材料间的应力应变关系对干涉信号相位变化的影响，并使用穿越统计(LC)和模式识别(PR)技术实现噪声抑制、行为分析和报警判决。实验证明，系统可以对入侵和干扰行为的原始干涉信号进行LC分析和特征提取，最小响应时间为0.5 s，通过神经网络训练生成行为模式，并可通过动态均值算法(DMA)有效抑制雨致噪声和其他环境噪声。实现了低成本、高可靠性和高实用性的全光纤周界安防系统。

A new multi-area perimeter security system based on optical fiber Michelson interferometer and pattern recognition technique is proposed and demonstrated. The polarization-insensitive optical fiber Michelson interferometer is used as the vibration sensor for perimeter intrusion detection system (PIDS) which reduces the polarization-induced fading. Strain measurement of fiber bonding on host material is analyzed. Noise suppression, behavior analysis and alarm judgement are realized by using level crossing (LC) method and pattern recognition (PR) technique. The experiment results show that the system is able to analyze the original signal with LC method and extract the feature values with response time less than 0.5 s. Behavior pattern is generated through neural network training. Rain-induced noise and other environmental noise are eliminated by dynamic means algorithm (DMA). So the all-fiber perimeter security system with low lost, high reliability and high praclicability is realized.