The outer space is commonly perceived as one of the most hazardous environments for human beings. Nowadays, the training of astronauts relies on a wide range of courses and facilities to prepare them for any situation they may encounter in space. The combination of these training technologies has successfully prepared multiple generations of astronauts. However, these assets lack flexibility to customise the training process, and are limited in scalability to accommodate an increasing number of trainees.

ESA missions with downlink in X-band are limited to 10 MHz of bandwidth and 8.75 Mbps of data, using the current GAIA modulation. GAIA-NIR is requiring higher data rates and it is pushing the limits at X-band.The CCSDS-131.2-B standard defines 27 Adaptive Coding and Modulation (ACM) modes that are intended to allow fine control of information rate in a given bandwidth to optimise data throughput by minimising the required link margin.

Currently EO missions are operated in S/X-Band with payload data in X-Band. New EO missions will have payload data in K-Band and TTC still in S-Band. In the long term TTC will be moved to X-Band still keeping payload data in K-Band. Presently only US suppliers are able to provide antenna radomes operating over different frequency bands. It is intended to develop an European alternative to US suppliers in the domain of high/multi-frequency application like the one needed for future Earth Observation missions.

SIDLOC (Spacecraft Identification and Localization) is a new transmission scheme proposed by Libre Space Foundation to enable LEO satellite identification and tracking. The SIDLOC system relies on a reduced size autonomous transmitter that requires minimal integration and area on the carrier spacecraft. The ground segment of the SIDLOC system utilizes the existing SatNOGS network and the UHF band to perform the signal demodulation and identification. The SIDLOC system uses DSSS (Direct Sequence Spread Spectrum) PSK modulated signals with an effective bitrate of ~50 bits/s.

An Operations Ground Segment consists of a complex system of systems, each of which is a source of high-throughput events e.g. telemetry, Out-Of-Limits, operating/data/network system logs. Today the majority of MC systems support a particular subsystem, have limited processing / analysis capabilities (e.g. limit checking, synthetic parameters, filters) and support only stateless operations.

The main objective of this activity was to design and develop an innovative virtual lab for Mars experiments, where AI methods are used to improve orbital imagery resolution, as well to obtain terrain features based on local images from rovers. Two different methods were used to recreate the virtual environment. The first one was dedicated to process low resolution images from orbital information. The main contribution in this sense was the use of AI to increase the resolution of these images.

Present ESA Deep Space Stations are equipped with a 20 kW X-Band High Power Amplifier (HPA).