The purpose of the project COLA (Coincident Lasersheet Particle Monitor) was to perform a feasibility study for an in-situ lasersheet particles/debris detection system enabling the detection and identification of small sized space debris/meteoroids currently not detectable from ground and that can nonetheless present important hazards for space missions. The detection system must be able to determine and reconstruct particle shapes and trajectories for sizes and velocities ranging from 1 mm to 10 mm and 2 km/s to 20 km/s, respectively.

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During this Phase 0 maturation study, ASUK, with the support of Thales Alenia Space (TAS), Nammo, MDA and GMV, performed a programmatic, business and technical assessment of a future low-Earth orbit (LEO) refuelling mission. The mission concept proposes developing and demonstrating core technologies in a preliminary service offering to enable a commercial in-orbit refuelling service. Such a service will swiftly redefine how satellites are designed and operated, launching a dynamic and sustainable in-orbit ecosystem with significant potential.

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.

In this project the authors looked at event-based sensing and processing for space situational awareness (SSA). Many advantages exist with the new paradigm of neuromorphic engineering, the authors investigate whether event-based optical data is suitable for the task and if processing with Spiking Neural Networks (SNN) provides advantages in terms of efficiency and efficacy. With the implementation of a novel heterogeneous LIF SNN, authors claim to surpass the state of the art in event-based SSA with a 15% increase in accuracy.

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.

With the 'democratisation of space', and the proliferation of large non-geostationary orbit constellations, the pace at which human-made objects are being deployed into orbit demands urgent action in defining and supporting a global space traffic management plan.

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