Wavelet Decomposition Layer Selection for the φ-OTDR Signal

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Wavelet Decomposition Layer Selection for the φ-OTDR Signal
Title:
Wavelet Decomposition Layer Selection for the φ-OTDR Signal
Journal Title:
Photonics
Publication Date:
31 January 2024
Citation:
Chen, Y., Yu, K., Wu, M., Feng, L., Zhang, Y., Zhu, P., Chen, W., & Hao, J. (2024). Wavelet Decomposition Layer Selection for the φ-OTDR Signal. Photonics, 11(2), 137. https://doi.org/10.3390/photonics11020137
Abstract:
The choice of wavelet decomposition layer (DL) not only affects the denoising quality of wavelet denoising (WD), but also limits the denoising efficiency, especially when dealing with real phase-sensitive optical time-domain reflectometry (φ-OTDR) signals with complex signal characteristics and different noise distributions. In this paper, a straightforward adaptive DL selection method is introduced, which dose not require known noise and clean signals, but relies on the similarity between the probability density function (PDF) of method noise (MN) and the PDF of Gaussian white noise. Validation is carried out using hypothetical noise signals and measured φ-OTDR vibration signals by comparison with conventional metrics, such as peak signal-to-noise ratio (PSNR) and structural similarity (SSIM). The proposed wavelet DL selection method contributes to the fast processing of distributed fiber optic sensing signals and further improves the system performance.
License type:
Attribution 4.0 International (CC BY 4.0)
Funding Info:
This work was supported in part by the Educational and Scientific Research Projects for Young and Middle-aged Teachers of Fujian under Grants [JAT200236, JAT200289] and the Natural Science Foundation of Fujian Science and Technology Plan under Grants [2022J01824, 2021J01866].
Description:
ISSN:
2304-6732
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