Enhancing spatial resolution of BOTDR sensors using image deconvolution

Abstract

We propose to employ the image deconvolution technique for Brillouin optical time domain reflectometry (BOTDR) systems to achieve a flexible and enhanced spatial resolution with pump pulses longer than phonon lifetime. By taking the measured Brillouin gain spectrum (BGS) distribution as an image blurred by a point spread function (PSF), the image deconvolution algorithm based on the two-dimensional Wiener filtering can mitigate the ambiguity effect on the Brillouin response. The deconvoluted BGS distribution reveals detailed sensing information within shorter fiber segments, improving the inferior spatial resolution and simultaneously maintaining other sensing performance parameters. Thanks to the proposed technique, a typical BOTDR sensor with 40 ns pump pulses reaches a submetric spatial resolution as high as 10 cm. Compared to the differential-spectrum-based BOTDR retrieving the same spatial resolution, the image deconvolution technique shows advantages in system complexity and measurement uncertainty. Moreover, the proposed technique is promising to improve the spatial resolution of other distributed optical fiber sensing (DOFS) techniques such as BOTDR systems with complex pump modulation methods.

Performance comparison of various deconvolution algorithms realizing high spatial resolution Brillouin optical time domain reflectometer

“…Shen 6 has proposed the use of deconvolution techniques to process the measured Brillouin signal traces of the BOTDA system to accomplish sub-meter measurement spatial resolution. Subsequently, image deconvolution techniques have been proposed 7 for BOTDR systems to achieve flexible and enhanced spatial resolution with pump pulses longer than the phonon lifetime. By using the measured Brillouin gain spectrum (BGS) distribution as an image blurred by the point spread function (PSF), a typical BOTDR sensor with a 40 ns pump pulse achieves a sub-meter measurement spatial resolution of up to 10 cm by utilizing an image deconvolution algorithm based on a two-dimensional Wiener filter.…”

Improving the spatial resolution and signal-to-noise ratio of BOTDR using double-pulse coding

“…As a result, the maximal allowable pulse width is 10 ns, corresponding to a 1 m spatial resolution. To break through this intrinsic limitation, several techniques have been demonstrated, such as the double-pulse method 4 , differential pulse pair method 5 , pre-pump pulse method 6 , and image deconvolution method 7 . Even though these methods can realize the submeter-level spatial resolution, the relatively narrow pulse is still in use.…”

Fast Feature Extraction Method for Brillouin Scattering Spectrum of OPGW Optical Cable Based on BOTDR

“…In 2020, Chang, Y. et al presented a distributed BFS-extracted convolutional neural network (BFSCNN) [22]. In 2022, Wu, H. et al proposed a different image de-convolution technique based on 2D Wiener filtering to reduce the BGS blurring effect [23]. While deep learning algorithms have demonstrated superior performance in numerous tasks, the performance of models also needs to improve when data are insufficient or of poor quality and training duration and generalization are problematic [24].…”