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Error analysis of spaceborne high spectral resolution lidar
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Paper Abstract

The high spectral resolution lidar (HSRL) technique employs a narrow spectral filter to separate the aerosol and molecular scattering components from the echo signals and therefore can retrieve the aerosol optical properties and lidar ratio (i.e., the extinction-to-backscatter ratio) profiles directly, which is different from the traditional Mie lidar with assumed lidar ratio. Accurate aerosol profiles measurement are useful for air quality monitoring. In this paper, a spaceborne HSRL lidar system simulation model based iodine vapor cell filter was presented. According to three different atmosphere aerosol distribution models and the uncertainties of atmosphere temperature and pressure, the signal to noise ratio (SNR) and the relative errors profiles of the backscattering coefficients of this lidar was simulated theoretically in daytime and nighttime. The result shows that the errors of aerosol backscattering coefficients are smaller in the aerosols dense area than in the sparse area. As altitude increases, the relative error of backscattering coefficient is increased. The relative backscattering coefficient error is within 16.5% below 5 km with 30 m range resolution and 10 km horizontal resolution.

Paper Details

Date Published: 28 February 2019
PDF: 8 pages
Proc. SPIE 10846, Optical Sensing and Imaging Technologies and Applications, 108461N (28 February 2019); doi: 10.1117/12.2505030
Show Author Affiliations
Junfa Dong, Shanghai Institute of Optics and Fine Mechanics, Chinese Academy of Sciences (China)
Univ. of Chinese Academy of Sciences (China)
Jiqiao Liu, Univ. of Chinese Academy of Sciences (China)
Xiaolei Zhu, Univ. of Chinese Academy of Sciences (China)
Decang Bi, Univ. of Chinese Academy of Sciences (China)
Weibiao Chen, Univ. of Chinese Academy of Sciences (China)
Xiaopeng Zhu, Univ. of Chinese Academy of Sciences (China)


Published in SPIE Proceedings Vol. 10846:
Optical Sensing and Imaging Technologies and Applications
Mircea Guina; Haimei Gong; Jin Lu; Dong Liu, Editor(s)

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