High Spatial Resolution Investigation of OFDR Based on Image Denoising Methods

Abstract

Measurement accuracy of the optical frequency domain reflectometry (OFDR) will be deteriorated severely when the spatial resolution is improved due to the influence of the random noise, especially in long range distributed fiber optical sensing system. In order to eliminate the random noise, we have experimentally compared and analyzed the performance of OFDR system with and without the image processing methods in term of spatial resolution. The data arrays of the cross-correlation results are obtained after processing the collected distributed Rayleigh scattering signals along the sensing fiber, which can be used to construct a two-dimension (2D) image with the spectrum shift information induced by the strain. Thus, the image denoising methods can be applied to remove the random noise and improve the measurement accuracy. Based on this principle, two image denoising methods including the total variation method and the 2D Gaussian filter arithmetic are introduced to realize distributed sensing with high spatial resolution in long distance OFDR system. Experimental results show that the random noise can be suppressed and the outliers can be removed by the proposed methods. The strain gradients with high spatial resolution are identified effectively when the image denoising methods are used. Furthermore, spatial resolution with 1.3mm is achieved by the proposed methods with a wavelength sweeping rate of 20nm/s in 52m sensing fiber. The proposed methods provide a potential solution for OFDR system in long distance sensing with high spatial resolution, which is a significant step toward a high-performance OFDR system for practical applications.