In this project, a feasibility study for the PULSARS geostationary CubeSat system has been carried out. This involves the definition of a public protection and disaster relief use case using the satellite C-band, evaluation of a 16U CubeSat platform, and investigation into the spacecraft and ground segment technology required for coherent beamforming using a swarm of 20 independent spacecrafts. PULSARS mission design and system architecture are proposed, as well as a programme of technology development, enabling the spacecraft to operate for a minimum of three years.

Robots are the most important assistants for astronauts during extra-terrestrial missions. All successful exploration missions in the past have proven the importance and the durability that robots have in extreme environments. For our next step on the lunar surface, it’s essential to redesign a more complete and multifunctional robotic system that can provide support for astronauts during the construction, exploration, research and everyday life tasks. This research study aims to create a new framework for reconfigurable robotics, going beyond the “traditional” intransigent robot.

The interest of having in the near future an available Position, Navigation and Timing (PNT) service supporting future missions to and at the Moon is currently supported by both institutional and commercial initiatives. On the commercial side, multiple companies are developing business solutions targeting the Moon and several major European companies are proposing to team up to build a communications network on the Moon compatible to terrestrial standards. In parallel, NASA has recently announced its plans to a ?Return to the moon?

This Auroral Oval Monitoring (AOM) Phase A study was a reorientation after the previous Phase AB1, with a simplified payload prioritizing auroral observation and a complete redesign of the mission. The first part of the study was to update the mission architecture with an affordable, sustainable, and scalable solution resulting in a Mission Definition Review (MDR).

FITAI is a Machine Learning based technique that improves GNSS positioning engine accuracy by mapping signal strength and residuals into position errors. These inputs are fed into a neural network to learn and correct errors, offering a non-invasive solution that provides better location precision without relying on external sources like reference stations.

FMCW radar technology in the automotive industry radar market covers 24 GHz and 77 GHz bands with modulated bandwidths of up to 4 GHz, allowing simultaneously ultra-precise determination of target range and its relative velocity. Fine angular resolution with 0.1 deg steps at distance of 300 m and beam-steering capability has been recently demonstrated. FMCW systems have also proved their efficiency for detection of fast-moving objects with small cross-section such as drones.

In December 2019, the 3GPP standardization group approved a dedicated work-item for the implementation of a new set of 5G New Radio (NR) specifications allowing the integration with mobile broadband satellite networks. This is the first time ever that the space industry has this challenging opportunity of a full integration with terrestrial cellular systems, and to benefit from very large economies of scale.

During its science phase EnVision will use ESTRACK antennas located at the three ESA deep space sites in New Norcia (Western Australia), Cebreros (Spain) and Malarg?e (Argentina), and optionally the DSN antennas located at the NASA sites of Canberra (Australia), Robledo (Spain) and Goldstone (United States of America). In order to increase the flexibility in the selection of the ground stations, or alternatively to increase the data volume, offline arraying between distant antennas is proposed during overlapping visibility slots.