Robust Adaptation to Background Noise in Multichannel C-OTDR Monitoring Systems

A robust sequential nonparametric method is proposed for adaptation to background noise parameters for real-time. The distribution of background noise was modelled like to Huber contamination mixture. The method is designed to operate as an adaptation-unit, which is included inside a detection subsystem of an integrated multichannel monitoring system. The proposed method guarantees the given size of a nonasymptotic confidence set for noise parameters. Properties of the suggested method are rigorously proved. The proposed algorithm has been successfully tested in real conditions of a functioning C-OTDR monitoring system, which was designed to monitor railways.

Authors:

• Andrey V. Timofeev
• Viktor M. Denisov

Keywords:

• Guaranteed estimation
• multichannel monitoring systems
• non-asymptotic confidence set
• contamination mixture.

References:

[1] K. N. Choi, J. C. Juarez, H. F. Taylor, “Distributed fiber optic
pressure/seismic sensor for low-cost monitoring of long perimeters”,
Proc. SPIE 5090, Unattended Ground Sensor Technologies and
Applications, 2003, pp. 134-141.
[2] J. C. Juarez, E. W. Maier, K. N. Choi, and H. F. Taylor, “Distributed
Fiber-Optic Intrusion Sensor System”, Journal of Lightwave
Technology, Vol. 23, Issue 6, 2005, pp. 2081-2087.
[3] S. S. Mahmoud, Y. Visagathilagar, J. Katsifolis., “Real-time distributed
fiber optic sensor for security systems: Performance, event classification
and nuisance mitigation". Photonic Sensors, Vol.2, Issue 3, 2012, pp.
225-236.
[4] V. Korotaev, V. M. Denisov, A. V. Timofeev, and M. G. Serikova,
"Analysis of seismoacoustic activity based on using optical fiber
classifier," in Latin America Optics and Photonics Conference, OSA
Technical Digest (online) (Optical Society of America, 2014), paper
LM4A.22.
[5] Timofeev A.V. The guaranteed detection of the seismoacoustic emission
source in the C- OTDR systems, International Journal of Mathematical,
Computational, Physical and Quantum Engineering, Vol.8, Issue 10,
2014, pp. 1213-1216.
[6] Timofeev A.V., Egorov D.V., Multichannel classification of target
signals by means of an SVM ensemble in C-OTDR systems for remote
monitoring of extended objects, MVML-2014 Conference Proceedings
Prague, 2014, V.1.
[7] S. Karlin, V. Studden, "Tchebycheff systems: with applications in
analysis and statistics", Interscience, 1966 .