|Title:||Extraction of Temperature Distributions in Brillouin Optical Time Domain Analysis Sensors Using 2D Wiener Filter Based Matched Filter Detection|
|Keywords:||Distributed fiber-optic sensors, Wiener filter, Matched filter detection, Least-squares curve fitting, Data interpolation, Lorentzian function|
In this paper, the use of 2D Wiener filter based matched filter detection (WMFD) is proposed and demonstrated for the extraction of temperature distributions in Brillouin optical time domain analysis (BOTDA) sensors. The experimental Brillouin gain spectra (BGSs) are obtained along a 38.2 km sensing fiber by adopting ten different numbers of BOTDA-trace averaging (NTA). These BGSs are first denoised by applying Wiener filter (WF) to enhance the signal-to-noise ratio (SNR) of the BOTDA-traces. The improvement of trace-SNR for using WF is quantified and analyzed experimentally. The matched filter detection (MFD) which is free from time-consuming iterative optimization procedure is then applied to the denoised BGSs for the ultrafast extraction of temperature distributions along the fiber. The measurement uncertainty, spatial resolution and temperature extraction speed provided by WMFD are also analyzed in detail and compared with that provided by widely-used curve fitting method (CFM). The results show that WF can improve the trace-SNR within the range from ~6.78 dB to ~8.28 dB depending on NTA. Consequently, WMFD can improve the measurement uncertainty within the range from ~48.70% to ~59.41% without sacrificing the spatial resolution as compared to CFM. Moreover, the speed in extracting temperature distributions from the experimental BGSs acquired with different NTA for using WMFD can be improved within the range from ~47.36 times to ~50.69 times as compared to that for using CFM. Thus, the proposed WMFD can be an effective approach for highly accurate and ultrafast extraction of temperature distributions along the sensing fiber.