Fast information acquisition using spectra subtraction for Brillouin distributed fiber sensors

Abstract

The traditional methods of extracting sensing information of a Brillouin distributed sensor is by curve fitting the Brillouin gain profiles along the fiber, we propose two concise and time-saving methods to process signals from only the frequency shifted section(s) of the fiber by subtracting the original spectrum from the sensing Brillouin spectrum. Experimental results validate that our methods can provide up to over 9 times faster information acquisition for a 10 km sensing fiber with 800 m frequency shifted section comparing with the traditional way. The proposed methods could be potentially attractive in getting information for the Brillouin distributed sensors as well as the Raman and Rayleigh distributed sensors especially when the processing speed is concerned.

Extraction of Temperature Distributions in Brillouin Optical Time Domain Analysis Sensors Using 2D Wiener Filter Based Matched Filter Detection

“…However, the uncertainty in temperature extraction provided by CFM is quite large, especially for low SNR at the end of a long fiber [9,10]. Moreover, the CFM utilizes iterative optimization procedure that takes long time to estimate BFSs, especially for large number of BGSs along a long fiber [8,11]. Consequently, the use of CFM to process BGSs acquired from BOTDA sensor is limited in practical applications where fast and accurate extraction of temperature distribution is not utterly essential.…”