Collision Avoidance Algorithms for Space Traffic Management Applications

Establishing cost-effective Space Traffic Management (STM) systems presents diverse challenges, from technical and operational aspects, to regulatory, policy and legislation. On the technical part, new types of missions and more objects in orbit will increase collisional activities and require advances in Space Situational Awareness. To deal with the growing amount of data, fast and efficient algorithms are a must. Furthermore, autonomous on-orbit collision avoidance capabilities would reduce the workload on satellite operators and improve safety. Also, the analysis of an avoidance manoeuvre should not be limited to the two objects involved but the general effect on the environment. To tackle some of these issues, this work reviews recent advances in collision avoidance manoeuvre modelling, analysis, and optimisation. The focus is put on computational efficiency and suitability for autonomous on-board applications. To achieve these goals analytical and semi-analytical models are used. Both impulsive and low-thrust propulsion systems are considered, as well as maximum deviation and minimum collision probability manoeuvres. The models can also be applied to uncertainties propagation. The algorithms are tested in different practical scenarios and traded-off for computational performance, accuracy, and reliability. Based on the results, their applicability for future STM systems is discussed.