Inversion of atmospheric turbulence intensity profile based on neural network algorithm

Analysis and study of bright-temperature weights with different integrated height

“…Brightness temperature forward modeling uses the MonoRTM model, an atmospheric radiative transfer model suitable for the microwave segment, developed by the Institute of Atmospheric Environment of the United States [6]. The MonoRTM model uses the Voigt line shape, and the relevant parameters are from the HITRAN database.…”

Research on inversion method of atmospheric temperature and humidity profile based on microwave radiometer

“…In order to obtain better quality primary data, a set of quality control schemes applicable to primary data is developed by combining the observation mode of ground-based microwave radiometer and its characteristics, and the schemes include rain/non-rain test, and radiation transmission mode test [5]. The specific quality control methods are as follows.…”

A Computational Model of Cn2 Profile Inversion for Atmospheric Laser Communication in the Vertical Path

“…Wang Yao [12] et al took five conventional meteorological parameters as input and used an artificial neural network to predict the profile of the sea surface near Mauna Loa, Hawaii, for one month. Zhang et al [13] based their study on the artificial neural network algorithm and established an artificial neural network model based on the data to predict the upper atmospheric turbulence profile. The predicted value simulated using the neural network algorithm is in good agreement with the actual turbulence profile in the Maoming area, which proves the feasibility and reliability of using a neural network to simulate the atmospheric turbulence profile.…”