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Deep space exploration missions are aimed at acquiring information about the solar system and a significant communication capacity has to be planned to transfer data for such very large distances. Terrestrial atmospheric impairments on the space-to-Earth propagating signal are the major responsible for the signal degradation thus reducing the channel temporal availability. In this work weather forecast models, coupled with microphysically-oriented radio-propagation models, are described in order to evaluate atmospheric effects at Ka-band. Estimation data return techniques are summarized and numerical results in a simulated operational scenario are illustrated in terms of received data volume using the BepiColombo mission as a baseline example.

Media propagation noises are amongst the main error sources of radiometric observables for deep space missions, with fluctuations of the tropospheric excess path length representing a relevant contributor to the Doppler noise budget. Microwave radiometers currently represent the most accurate instruments for the estimation of the tropospheric delay and delay rate along a slant direction. A prototype of a tropospheric delay calibration system (TDCS), using a 14 channel Ka/V band microwave radiometer, has been developed under a European Space Agency contract and installed at the deep space ground station in Malargüe, Argentina, in February 2019. After its commissioning, the TDCS has been involved in an extensive testbed campaign by recording a total of 44 tracking passes of the Gaia spacecraft, which were used to perform an orbit determination analysis. This work presents the first statistical characterization of the end-to-end performance of the TDCS prototype in an operational scenario. The results show that using TDCS-based calibrations instead of the standard GNSS-based calibrations leads to a significant reduction of the residual Doppler noise and instability.