Adaptive data processing of a ground-based radiometric complex for remote sensing of tropospheric parameters

The paper presents algorithm development results for adaptive data processing of the troposphere parameters remote sensing. The algorithm is implemented in the LabVIEW graphical programming environment and processes data of the ground-based water vapor radiometer (WVR) in a quasi-real time scale. To identify trends and forecast changes in the time series of WVR data during intense precipitation, it is proposed to use the method of Singular Spectrum Analysis - “Caterpillar” - SSA". To determine the anomalous values of the initial time series data, the fuzzy method is used. The results of the comparison of the troposphere integral water vapor content obtained with the help of WVR and global navigation satellite systems are given.