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Intrusion recognition method based on echo state network for optical fiber perimeter security systems

机译:基于回波状态网络的光纤外围安全系统的入侵识别方法

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摘要

In order to accurately and efficiently identify different types of intrusion signals of optical fiber perimeter security systems, this paper proposes a novel intrusion signal recognition method based on an echo state network (ESN). A perimeter security system based on an in-line Sagnac interferometer is employed to simulate in lab two laying situations of the sensing fiber: attached to a physical fence or buried under ground and acquire various event signals. The preprocessed signals are input into a trained well ESN to identify different types of events. The final recognition result of an event signal segment is determined according to the most dominant classification label corresponding to the signal segment. As a result, the average identification rates are 98.75% and 100% for the two laying situations, respectively. The proposed method has no need of extracting signal features and a large number of samples to train the classifier model. Therefore, more accurate and more effective intrusion identification can be achieved by the method than by others. The method is expected to satisfy the requirements of the practical application in the security field.
机译:为了准确和有效地识别光纤周边安全系统的不同类型的入侵信号,本文提出了一种基于回波状态网络(ESN)的新型入侵信号识别方法。基于在线SAGNAC干涉仪的周边安全系统用于模拟感测光纤的实验室两个铺设情况:附接到物理围栏或在地面下埋下并获取各种事件信号。预处理的信号被输入到训练井ESN以识别不同类型的事件。事件信号段的最终识别结果是根据与信号段对应的最主导分类标签确定的。结果,对于两个铺设情况,平均识别率分别为98.75%和100%。所提出的方法不需要提取信号特征和大量样本来训练分类器模型。因此,可以通过该方法实现更准确和更有效的入侵识别。预计该方法将满足安全领域实际应用的要求。

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