The architecture of an SPS system requires that the SPS maintain constant visibility to both the Sun and the ground station. This immediately implies a so-called Geosynchronous Equatorial Orbit (GEO), which is also called a Geostationary Orbit; or a near-GEO Geosynchronous Orbit (GSO). These are substantially the same orbits that are used for existing communications satellites.

The increasing interest for Deep-Space cubesat is leading in the near future to the need of adequate deployment systems (``Cubesat Dispensers``) suitable for deep space applications, taking into account all the environmental (e.g. radiation) and mission constraints (e.g. need for power supply to the cubesat, possibility to upload SW updates, need for accurate release conditions).

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.

Early space missions consisted of bespoke components communicating with facilities on Earth. Today this model has been updated with off-the-shelf components and reusable launch systems that lower mission cost into low-Earth orbit. Extending this model to develop a sustainable off-Earth economy requires bringing the concept of reconfigurable computing agents to deep space.

Successfully mitigating the damage caused by marine litter requires large-scale, accurate mapping of oceanborne plastics across the globe. Quantifying where and how much plastic debris enters the marine environment in a global spatio-temporal sense is critical in formulating solutions to the plastic pollution problem. Satellite-based measurements can help to survey remote, isolated locations in which direct observations are sparse, costly, and difficult.

The spatial distribution and quantity of in-situ lunar resources, such as water, ice and ilmenite, is currently highly uncertain. The VMMO (Volatile and Mineralogy Mapping Orbiter) is a low-cost 12U Cubesat that includes both the Lunar Volatile and Mineralogy Mapper (LVMM) science payload, a GNSS technology demonstrator, and the supporting 12U Cubesat platform. This GSTP activity addresses the need for mapping these lunar volatiles at relatively high spatial resolution in permanently-shadowed regions by using active single-mode fiber-lasers.

The main objectives of this study were:
- To carry out thorough analysis and modeling of the anomalous gravity fields expected from lunar lava tubes and other types of void spaces, of various sizes and depths. This work was carried out by geoscientists from Queen’s University.
- To define the mission and system-level requirements for this exploration mission, derived from the scientific analysis of those expected gravity signals, and specifying feasible mission and system-level designs, for a mission to scout the Marius Hills pit crater.

The main goal of this Ariadna study was to determine the radiation hardness of potential future space processors. The AR0 test-chip was used to study the impact of SEUs and SETs on different versions of a hardened processor on UTBB-FDSOI 28nm technology, including DICE flip-flops, and three different hardening level of combinational logic.

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