All-fiber interferometer sensor system is a new type of system, which could be used in long-distance, strong-EMI condition for monitoring and inspection. 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, the universal steps in triggering pattern recognition is introduced, which includes signal characteristics extracting by accurate endpoint detecting, templates establishing by training, and pattern matching. By training the samples acquired in the laboratory, this paper uses the wavelet transformation to decompose the detection signals of the intrusion activities into sub-signals in different frequency bands with multi-resolution analysis. Then extracts the features of the above mentioned intrusions signals by frequency band energy and wavelet information entropy and 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 such as windy and walk effectively. 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.

Date Published: 8 October 2015
PDF: 5 pages
Proc. SPIE 9679, AOPC 2015: Optical Fiber Sensors and Applications, 96790Y (8 October 2015); doi: 10.1117/12.2199827

Published in SPIE Proceedings Vol. 9679:
AOPC 2015: Optical Fiber Sensors and Applications
Yanbiao Liao; Weixu Zhang; Desheng Jiang; Wei Wang; Gilberto Brambilla, Editor(s)