Intrusion recognition for optic fiber vibration sensor based on the selective attention mechanism

Haiyan Xu; Yingjuan Xie; Min Li; Zhuo Zhang; Xuewu Zhang

doi:10.1117/12.2291723

15 November 2017 Intrusion recognition for optic fiber vibration sensor based on the selective attention mechanism

Haiyan Xu, Yingjuan Xie, Min Li, Zhuo Zhang, Xuewu Zhang

Proceedings Volume 10605, LIDAR Imaging Detection and Target Recognition 2017; 106051P (2017) https://doi.org/10.1117/12.2291723
Event: LIDAR Imaging Detection and Target Recognition 2017, 2017, Changchun, China

Abstract

Distributed fiber-optic vibration sensors receive extensive investigation and play a significant role in the sensor panorama. A fiber optic perimeter detection system based on all-fiber interferometric sensor is proposed, through the back-end analysis, processing and intelligent identification, which can distinguish effects of different intrusion activities. In this paper, an intrusion recognition based on the auditory selective attention mechanism is proposed. Firstly, considering the time-frequency of vibration, the spectrogram is calculated. Secondly, imitating the selective attention mechanism, the color, direction and brightness map of the spectrogram is computed. Based on these maps, the feature matrix is formed after normalization. The system could recognize the intrusion activities occurred along the perimeter sensors. Experiment results show that the proposed method for the perimeter is able to differentiate intrusion signals from ambient noises. What’s more, the recognition rate of the system is improved while deduced the false alarm rate, the approach is proved by large practical experiment and project.

Citation Download Citation

Haiyan Xu, Yingjuan Xie, Min Li, Zhuo Zhang, and Xuewu Zhang "Intrusion recognition for optic fiber vibration sensor based on the selective attention mechanism", Proc. SPIE 10605, LIDAR Imaging Detection and Target Recognition 2017, 106051P (15 November 2017); https://doi.org/10.1117/12.2291723

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