The increasing launch rate of spacecraft, particularly due to the deployment of large constellations and miniaturized satellites in Low Earth Orbit (LEO), has led to a significant rise in space traffic and debris. This paper examines emerging technologies and strategies for future Space Traffic Management (STM) to ensure sustainable operations in space. Key focus areas include the use of artificial intelligence (AI) for enhanced Collision Avoidance (CA) systems, the development of advanced Space Surveillance and Tracking (SST) capabilities, and Active Debris Removal (ADR) techniques to mitigate the growing risks associated with space debris. Additionally, the paper explores the potential of in-orbit servicing, re-entry services, and the exploitation of Very Low Earth Orbits (VLEO) and cislunar space. The integration of these technologies and practices is essential to manage the anticipated growth in space activities while minimizing collision risks and ensuring the long-term sustainability of the space environment.

Future activities in the near-earth space in the face of ever-increasing space traffic

Rossi A.
;
2024

Abstract

The increasing launch rate of spacecraft, particularly due to the deployment of large constellations and miniaturized satellites in Low Earth Orbit (LEO), has led to a significant rise in space traffic and debris. This paper examines emerging technologies and strategies for future Space Traffic Management (STM) to ensure sustainable operations in space. Key focus areas include the use of artificial intelligence (AI) for enhanced Collision Avoidance (CA) systems, the development of advanced Space Surveillance and Tracking (SST) capabilities, and Active Debris Removal (ADR) techniques to mitigate the growing risks associated with space debris. Additionally, the paper explores the potential of in-orbit servicing, re-entry services, and the exploitation of Very Low Earth Orbits (VLEO) and cislunar space. The integration of these technologies and practices is essential to manage the anticipated growth in space activities while minimizing collision risks and ensuring the long-term sustainability of the space environment.
2024
Istituto di Fisica Applicata - IFAC
Collision avoidance service
ADR services
Machine learning
Very low Earth orbits
Cislunar space
spaceborne computing
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/20.500.14243/525167
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