SNR improvement for Φ-OTDR with sparse representation denoising method

Abstract

A Rayleigh backscattering (RBS) signal denoising method based on sparse representation is proposed in this paper. The method can effectively reduce the noise of the RBS signal and improve the signal-to-noise ratio (SNR) of vibration location results for the phase-sensitive optical time-domain reflectometry (Φ-OTDR) system. In the experiments, the initial dictionary is constructed by discrete cosine transform, the dictionary matrix and sparse matrix are updated by the k-singular value decomposition method, and then RBS signal reconstruction is executed. In this process of reconstruction, the effective signals can be sparsely represented by the linear combination of dictionary atoms, while the noise signals are discarded as the residual between the original RBS signals and the reconstructed target signals, which makes the noise separated and improves the SNR of the system. To validate the feasibility and effectiveness of the proposed approach for the SNR enhancement, we have carried out experiments on the actual signals obtained from the Φ-OTDR system. The experimental result indicates that the average increment of SNR is 3.44 dB at 10 km, 20 km, 30 km, and 40 km of the optical fiber after using the sparse representation denoising method. Moreover, the vibration detection range is enhanced to 80 km and the SNR reaches 3.27 dB. This method provides a novel scheme to improve the SNR for the Φ-OTDR system.