In the frame of an In Orbit Servicing Maturation Phase (IOSMP) contract, this maturation study has been realised on the START-€ solution which is proposed to extend the lifetime of geostationary orbit (GEO) communication satellites. The START-€ servicer spacecraft will first demonstrate on a GEO communication satellite its ability to perform the critical operations related to its mission, before proceeding with several commercial life extension missions by capturing and taking the AOCS control of aged client spacecraft.

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In this activity, Mission Control Space Services deployed a low-level implementation of the OPS-SAT SmartCam model using a Field Programmable Gate Array (FPGA), comparing against a high-level CPU model using Tensorflow Lite. Experiments showed that the FPGA implementation reproduced the precision and accuracy of the high-level model, while running at a slower speed. Further optimisations of the FPGA are expected to close the gap in timing and unlock new methods for deploying deep learning on spacecraft.

In applications such as space traffic and disaster response management, there are growing public and private capabilities. Multiple different stakeholders can detect and identify events (space collision predictions, natural disaster definitions). Augmentation of events definitions lead to confusion for local authorities, operators or any users of these information for costly decisions. This project, Space DAO, sets the base infrastructure to agree on consensus mechanisms to reduce confusion and augment trust in key decision making information.

The LEO-GEO4GHG project studied the feasibility of new frontiers of cloud computing in space and artificial intelligence (AI) combining multiple sources of data such as the SATLANTIS GEI-SAT constellation and other external meteorological and atmospheric data with the final aim of providing near real-time methane detection and quantification.

The ESA Deep Space Network consists of three 35m beam waveguide antennas located around the globe. The 35m beam waveguide antennas employ an X-Band feed covering the Deep Space uplink band near 7.2 GHz and down-link band near 8.45 GHz. Simultaneous uplink commanding at 20 kW and low noise reception (Generation #2) is supported. In order to increase the transmit power capability of ESA Deep Space antennas it is currently considered to add a new high power feed and associated 80 kW High Power Amplifier.

The driver behind the MoBaTe activity was to propose ways to improve the current software development and validation lifecycle using MBSE techniques to shift some of the system validation activities to the early stages of development. The roadmap to achieve this included identifying strategies, required model properties, modelling tools and languages needed to move from a requirements-based approach to a model-based approach. All this considering existing and established workflows and tools currently used by ESA.

The results of the IOSPR maturation phase study done by D-Orbit (UK) are presented.