Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 31108
Instant Location Detection of Objects Moving at High-Speedin C-OTDR Monitoring Systems

Authors: Andrey V. Timofeev


The practical efficient approach is suggested to estimate the high-speed objects instant bounds in C-OTDR monitoring systems. In case of super-dynamic objects (trains, cars) is difficult to obtain the adequate estimate of the instantaneous object localization because of estimation lag. In other words, reliable estimation coordinates of monitored object requires taking some time for data observation collection by means of C-OTDR system, and only if the required sample volume will be collected the final decision could be issued. But it is contrary to requirements of many real applications. For example, in rail traffic management systems we need to get data of the dynamic objects localization in real time. The way to solve this problem is to use the set of statistical independent parameters of C-OTDR signals for obtaining the most reliable solution in real time. The parameters of this type we can call as «signaling parameters» (SP). There are several the SP’s which carry information about dynamic objects instant localization for each of COTDR channels. The problem is that some of these parameters are very sensitive to dynamics of seismoacoustic emission sources, but are non-stable. On the other hand, in case the SP is very stable it becomes insensitive as rule. This report contains describing of the method for SP’s co-processing which is designed to get the most effective dynamic objects localization estimates in the C-OTDR monitoring system framework.

Keywords: multichannel monitoring systems, C-OTDR-system, co-processing of signaling parameters, high-speed objects localization

Digital Object Identifier (DOI):

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1566


[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] Y. Mei, “Sequential change-point detection when unknown parameters are present in the pre-change distribution”, The Annals of Statistics, Vol. 34, 2006, pp. 92-122.
[6] T.L. Lai, “Sequential Change point Detection in Quality Control and Dynamical Systems”, Journal of Royal Statistical Society, Series B, Vol. 57, 1995, pp. 613-658.
[7] A.V. Timofeev, "Monitoring the Railways by Means of C-OTDR Technology", International Journal of Mechanical, Aerospace, Industrial and Mechatronics Engineering, 9(5), 2015, 620-623.