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Proceedings Paper

Denoising processing of MIE-polarization lidar signal using wavelet
Author(s): Hui Yang; Xuesong Zhao; Jiesong Ye; Yanfei Sun; Tiedong Wang
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Paper Abstract

The echo signal of MIE scattering and polarization lidar is contanminated by the noises including background noises and detector noises, there exist obvious difference in fourier spectrums of original signals and denoised signals at high frequency parts. In this paper, a new method of lidar signal denoised by scattering wavelets was proposed, and original PRR signals of lidar were denoised by different wavelet basis. The experimental results showed that:1) Daubechies 4 wavelet basis (db4) met the requirements of denoising; 2)wavelet denoising could better preserve peak features of lidar echo signal than moving average method; 3) the original and detailed characteristics of atmospheric aerosol extinction profile was maintained, and the accuracy of atmospheric aerosol extinction coefficient inversion was improved. For lidar echo signals with low SNR, this method improved data processing method of Mie-scattering and polarization lidar and improved the accuracy of the retrieval of atmospheric aerosol extinction coefficient, the signal contamination from electric noise and the background light noise can be reduced by the proposed wavelet method.

Paper Details

Date Published: 24 October 2017
PDF: 13 pages
Proc. SPIE 10462, AOPC 2017: Optical Sensing and Imaging Technology and Applications, 104620F (24 October 2017); doi: 10.1117/12.2282267
Show Author Affiliations
Hui Yang, New Star Research Institute of Applied Technology (China)
Xuesong Zhao, Anhui Institute of Optics and Fine Mechanics (China)
Jiesong Ye, New Star Research Institute of Applied Technology (China)
Yanfei Sun, New Star Research Institute of Applied Technology (China)
Tiedong Wang, New Star Research Institute of Applied Technology (China)


Published in SPIE Proceedings Vol. 10462:
AOPC 2017: Optical Sensing and Imaging Technology and Applications
Yadong Jiang; Haimei Gong; Weibiao Chen; Jin Li, Editor(s)

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