Location and processing of optical network disturbance signal based on improved clustering algorithm

Yunjie Xiao; Jiyun Qiu; Weixiang Qiu; Lingqi Yun

doi:10.1117/12.2639363

29 April 2022 Location and processing of optical network disturbance signal based on improved clustering algorithm

Yunjie Xiao, Jiyun Qiu, Weixiang Qiu, Lingqi Yun

Proceedings Volume 12255, 2022 International Conference on Optoelectronic Information and Functional Materials (OIFM 2022); 122550Y (2022) https://doi.org/10.1117/12.2639363
Event: 2022 International Conference on Optoelectronic Information and Functional Materials (OIFM 2022), 2022, Chongqing, China

Abstract

Among the various types of distributed optical fiber sensors, the distributed optical fiber sensor is widely used in the field of perimeter security to monitor the occurrence of external disturbances because of its high sensitivity, high resolution and simple structure, which can determine the location of external intrusion and achieve accurate alarm. However, due to the uncertainty of the external environment and the existence of system noise in the optical fiber sensing system, the collected signal is mixed with a variety of noise, which is easy to produce false alarms. Therefore, it is particularly important to suppress the noise in the sensing signal. Only when the signal-to-noise ratio is improved can the accurate positioning be achieved by choosing the appropriate positioning method. In this paper, the application of distributed optical fiber sensing system in perimeter security is taken as the experimental scenario. The adaptive singular value decomposition based on the improved clustering algorithm is used as the signal denoising method. The improved clustering method is used as the positioning method. The single-point remote disturbance positioning experiment is carried out under disturbance. The positioning accuracy is more than 95% in the single-point remote disturbance experiment. The average positioning accuracy can reach 97%. In the multi-point perturbation experiment, the positioning accuracy is above 90%. The average positioning accuracy can reach 96. 57%, which proves the effectiveness of the proposed method.

Citation Download Citation

Yunjie Xiao, Jiyun Qiu, Weixiang Qiu, and Lingqi Yun "Location and processing of optical network disturbance signal based on improved clustering algorithm", Proc. SPIE 12255, 2022 International Conference on Optoelectronic Information and Functional Materials (OIFM 2022), 122550Y (29 April 2022); https://doi.org/10.1117/12.2639363

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KEYWORDS

Signal to noise ratio

Optical fibers

Denoising

Signal processing

Interference (communication)

Optical networks

Environmental sensing

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