4.5 Article

Calibration by Air in Polarization Sensing

期刊

ATMOSPHERE
卷 13, 期 8, 页码 -

出版社

MDPI
DOI: 10.3390/atmos13081225

关键词

polarization lidar; backscattering; Mueller matrix; wave plate

资金

  1. IAO SB RAS State Assignment [121031500341-3]
  2. Russian Science Foundation [21-72-10089]
  3. National Research Foundation of Korea (NRF) - Korean government (MSIT) [2020R1F1A1048293]
  4. National Research Foundation of Korea [2020R1F1A1048293] Funding Source: Korea Institute of Science & Technology Information (KISTI), National Science & Technology Information Service (NTIS)

向作者/读者索取更多资源

Scattered light polarization plays a significant role as an indicator and characteristic in various atmospheric processes. By measuring the polarization of all scattering matrix elements, the optical and morphological parameters as well as the orientation of particles in clouds can be adequately described. This article focuses on the calibration of matrix polarization lidar (MPL) parameters, specifically through the calibration by air technique to correct optical element parameters.
Scattered light polarization serves as an indicator and a characteristic of various processes in the atmosphere. The polarization measurements of all scattering matrix elements provide an adequate description of the optical and morphological parameters and orientation of particles in clouds. In this article, we consider the problem of the calibration of matrix polarization lidar (MPL) parameters. Calibration by air is an effective alternative to the technique for correcting optical element parameters and among the calibration parameters of the MPL optical path are the relative transmission coefficient of a two-channel receiver, the angular positions of the transmission axes of the optical elements of the transmitter and receiver units, including the polarizers and wave plates, and the retardance of wave plates. For the first time, the method of calibration by air was partially implemented in the MPL to study Asian dust in the atmosphere. We considered the calibration problem more generally and this was due to the need to calibrate different MPL modifications from stationary to mobile ones. The calibration equations have been derived in terms of instrumental vectors, and the method of their solution by the generalized least squares method has been proposed. The method has been verified on a numerical MPL model and validated using MPL measurements in Daejeon, Republic of Korea.

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