Denoising algorithm of 0-OTDR signal based on curvelet transform with adaptive threshold

In this paper, a denoising scheme based on curvelet transform is proposed to improve the signal-to-noise ratio (SNR) for vibration sensing in phase-sensitive optical time-domain reflectometry (0-OTDR) systems. The noise level can be estimated based on non-vibration images, which can be used to set the threshold for curvelet coefficients. We further optimize the threshold according to the amplitude distribution of the curvelet coefficients. In the experimental demonstration, when the optical pulse width is 100 ns, the SNR of location information of the 100 Hz vibration events can be increased by 6.93 dB, which proves the effectiveness of the proposed method.

Automated summary

A denoising scheme based on curvelet transform is proposed in this paper to improve the signal-to-noise ratio (SNR) for vibration sensing in phase-sensitive optical time-domain reflectometry (0-OTDR) systems. The noise level is estimated based on non-vibration images, which helps to set the threshold for curvelet coefficients. We further optimize the threshold according to the amplitude distribution of the curvelet coefficients. In the experimental demonstration, the SNR of location information for 100 Hz vibration events can be increased by 6.93 dB when the optical pulse width is 100 ns, proving the effectiveness of the proposed method.