ESA GNC Conference Papers Repository

The flourishing of the new space economy, characterized by new mission types, capabilities, space-based services, and players, is increasing congestion in space, particularly in low Earth orbit. To deal with the growing amount of data and potentially dangerous close approaches, as well as to enable new autonomous capabilities, lightweight and accurate algorithms are required. This work presents the latest advancements in a suite of algorithms for the modelling and design of collision avoidance manoeuvres (CAMs). First, a fully analytical approximation for low-thrust CAMs is developed, achieving significant improvements in both accuracy and computational time with respect to the previous semi analytical model. Then, a procedure to numerically propagate state transition matrices including the effects of drag and solar radiation pressure is presented. Several numerical test cases are studied to assess the performance of these solutions. Finally, the potential use of these algorithms in combination with machine learning models for autonomous on-board operations is discussed, and a proposed demonstration mission is presented.