Laser & Optoelectronics Progress, Volume. 62, Issue 17, 1728001(2025)
Rayleigh Lidar Signal Denoising Method and Applicable Condition Analysis
Fig. 1. Simulation results of lidar echo signals. (a) Ideal echo signal and signal with noise at the altitude range of 30‒70 km; (b) variation in SNR of echo signal with altitude
Fig. 2. Measured data by Rayleigh lidar. (a) Echo signal of lidar; (b) variation in SNR of echo signal with altitude
Fig. 3. Comparison of denoise results by different methods on the measured echo signal, illustrations are enlarged for selected parts. (a) MA; (b) Hann; (c) WTs; (d) EEMD; (e) WT-EEMD-LOWESS; (f) EEMD-VMD-IMWOA
Fig. 4. Characteristic analysis of denoising results by different methods in the high-frequency range of the frequency-domain. (a) Comparison among six methods; (b) fine comparison of MA, Hann, EEMD, and EEMD-VMD-IMWOA
Fig. 5. Effects comparison of different methods on atmospheric fluctuation information. (a) MA; (b) Hann; (c) WTs; (d) EEMD; (e) WT-EEMD-LOWESS; (f) EEMD-VMD-IMWOA
Fig. 6. Atmospheric temperature retrieval results and uncertainties of lidar measured data by different methods. (a) Atmospheric temperature retrieval result and (b) uncertainty of profile 1; (c) atmospheric temperature retrieval result and (d) uncertainty of profile 2; (e) atmospheric temperature retrieval result and (e) uncertainty of profile 3
Fig. 8. Deviation between the temperature retrieval results obtained by different denoising methods and the SABER temperature data, the two ends of red line segment are the maximum and minimum deviations. (a) Profile 1; (b) profile 2; (c) profile 3
|
|
|
Get Citation
Copy Citation Text
Tong Wu, Kai Zhong, Xianzhong Zhang, Fangjie Li, Xinqi Li, Xiaojian Zhang, Degang Xu, Jianquan Yao. Rayleigh Lidar Signal Denoising Method and Applicable Condition Analysis[J]. Laser & Optoelectronics Progress, 2025, 62(17): 1728001
Category: Remote Sensing and Sensors
Received: Jan. 21, 2025
Accepted: Feb. 14, 2025
Published Online: Aug. 11, 2025
The Author Email: Kai Zhong (zhongkai@tju.edu.cn)
CSTR:32186.14.LOP250555