Research on denoising method based on temperature and humidity profile lidar
Author:
Funder
the National Key R&D Program of China
the National Natural Science Foundation of China
Publisher
Springer Science and Business Media LLC
Link
https://www.nature.com/articles/s41598-024-71876-4.pdf
Reference23 articles.
1. Lange, D., Behrendt, A. & Wulfmeyer, V. Compact operational tropospheric water vapor and temperature raman lidar with turbulence resolution. Geophys. Res. Lett. 46(24), 14844–14853 (2019).
2. Chang, J. et al. Noise reduction in Lidar signal using correlation-based EMD combined with soft thresholding and roughness penalty. Opt. Commun. 407, 290–295 (2018).
3. Qin, X. & Mao, J. Noise reduction for lidar returns using self-adaptive wavelet neural network. Opt. Rev. 24(3), 416–427 (2017).
4. Zhang, B. et al. An optimal denoising method for spaceborne photon-counting LiDAR based on a multiscale quadtree. Remote Sens. 16(13), 2475 (2024).
5. Merjora, A. & Maran, P. Optimized shuffle attention based Lidar signal denoising and temperature retrievals in the middle atmosphere. Opt. Quant. Electron. 56, 1178 (2024).
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