Abstract
More than half a century of space activities has resulted in the placement of thousands of space objects in the Earth’s orbit. Understanding the questions of how, where, and who is moving in orbit is essential for the management of space infrastructure. Since the beginning of space missions, this task as been carried out by Space Situational Awareness (SSA) systems. SSA systems are made up of several subsystems, such as optical recognition instruments, radar and radio. In recent years, these terrestrial systems have also been joined by satellites with similar capabilities. Historically, these systems were maintained by the military. It was only recently that the private sector became a major actor in the field. Consultation, Command and Control (C3) allows for a strong collaboration of civil and military bodies that focus on information sharing and interoperability of the systems. SSA systems have proved critical in collisions between satellites and in preserving the structural stability of the International Space Station several times. The security of these systems hence has a strong impact on space and international security. The growing importance of the space sector and its progressive recognition as a critical infrastructure shows that a model and simulation of the scenario are essential for a centric defence. This paper will identify the areas that pose external threats focussing on the European and Arctic region. Following the threats’ evaluation, their level of disruption will be considered, whether partial or total, permanent or temporary. This approach will enable the development of a European and Arctic scenario analysis of SSA disruption and evaluate the SSA security in the coming years. The scenario will take into consideration environmental, kinetic, electronic, and cyber sources of disruption.
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Carlo, A., Boschetti, N. (2023). Modelling the Impact of Space Situational Awareness Disruption on the European and Arctic Security Landscape. In: Mazal, J., et al. Modelling and Simulation for Autonomous Systems. MESAS 2022. Lecture Notes in Computer Science, vol 13866. Springer, Cham. https://doi.org/10.1007/978-3-031-31268-7_18
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