Abstract
The intrusion events in the optical fiber pre-warning system (OFPS) are divided into two types which are harmful intrusion event and harmless interference event. At present, the signal feature extraction methods of these two types of events are usually designed from the view of the time domain. However, the differences of time-domain characteristics for different harmful intrusion events are not obvious, which cannot reflect the diversity of them in detail. We find that the spectrum distribution of different intrusion signals has obvious differences. For this reason, the intrusion signal is transformed into the frequency domain. In this paper, an energy ratio feature extraction method of harmful intrusion event is drawn on. Firstly, the intrusion signals are pre-processed and the power spectral density (PSD) is calculated. Then, the energy ratio of different frequency bands is calculated, and the corresponding feature vector of each type of intrusion event is further formed. The linear discriminant analysis (LDA) classifier is used to identify the harmful intrusion events in the paper. Experimental results show that the algorithm improves the recognition rate of the intrusion signal, and further verifies the feasibility and validity of the algorithm.
Highlights
The optical fiber pre-warning system utilizes the optical fiber sensor technology to realize the external intrusions pre-warning [1, 2], which is widely used in the perimeter security field such as border and military areas
References [7, 8] propose a method of signal acquisition for optical fiber pre-warning system (OFPS) based on Ф-OTDR with single-core optical fiber, which can establish sufficient data samples for the conventional perimeter intrusion events and meet the majority of concurrent intrusions
The parameter w of linear discriminant analysis (LDA) classification model is obtained by training
Summary
The optical fiber pre-warning system utilizes the optical fiber sensor technology to realize the external intrusions pre-warning [1, 2], which is widely used in the perimeter security field such as border and military areas. References [7, 8] propose a method of signal acquisition for OFPS based on Ф-OTDR with single-core optical fiber, which can establish sufficient data samples for the conventional perimeter intrusion events and meet the majority of concurrent intrusions. Zhiyong SHENG et al.: An Energy Ratio Feature Extraction Method for Optical Fiber Vibration Signal the system based on Ф-OTDR and is analyzed. Reference [11] proposes a feature extraction method for optical fiber signal based on time-domain features, which performs well in distinguishing harmful intrusion event and harmless interference. Reference [13] proposes a robust method to identify the optical fiber intrusion, which extracts the time-domain characteristics of the signals as inputs into the neural network for training and recognition.
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