Research paper
Published 29 August 2019
Updated 17 December 2020
ISBN: ISBN 978 1 78413 359 7
As more space activities develop, there is an increasing requirement for comprehensive space situational awareness (SSA). This paper provides an overview of the current landscape in SSA and space traffic management as well as possible scenarios for EU–US cooperation in this area.
The information received from space assets is essential for the operation of so much of the everyday functioning of modern societies including critical national infrastructure, communication, emergency services, positioning and navigation, air traffic control, maritime control, environmental monitoring, weather prediction, and humanitarian and disaster relief. Space is also vital for military and peacekeeping operations, accurate weapons targeting and intelligence gathering. SSA is fundamental to the safe and secure operations of space-based assets and in preventing scenarios that may cause loss of access to space assets.
It is no coincidence that SSA, and more specifically STM, is increasingly seen as important and more STM data providers are recognizing the value of becoming involved in these activities. It is not just the current reliance on space that is driving the need for increased STM. Recent years have seen a dramatic rise in the number of space actors, both state and commercial. This new reality has increased congestion, particularly in low Earth orbit (LEO).8 With plans for several mega-constellations of small satellites to be launched into LEO within the next five years, it is imperative their operators have access to STM data. Similarly, states that possess sovereign space assets or that host satellite operators have a responsibility to invest in STM capabilities. As not all states will have the financial or logistical resources to create fully operational and independent STM systems, scenarios need to be identified that will allow such states to contribute to existing capabilities through partnerships, such as hosting telescopes, financing specific aspects or providing personnel. It is therefore equally important for those states with existing capabilities to engage with these new actors and look at how to provide opportunities for cooperation.
One of the most significant aspects of space security is the avoidance of collisions with other satellites and space debris. The gradual accumulation of space debris – particularly in medium Earth and geostationary orbits, which are important for navigational satellites (such as GPS and Galileo) and communication satellites, respectively – will continue unless removed deliberately. There are different categories of space debris.9 The first is natural debris, consisting of small pieces of material from comets and asteroids. The second, artificial debris, is any man-made object in space that is not functioning. This artificial debris can be further sub-categorized, usually by size, to differentiate between defunct satellites, rocket boosters and smaller pieces, which are generally the result of collisions or the break-up of other satellites. Much STM activity is focused on the detection and tracking of debris to warn satellite operators of possible collisions.
It is important to note that information from STM is complicated and there are often several possible and conflicting interpretations of data. For example, in the event of the break-up of a satellite, one set of data may not provide a complete explanation for the cause. This often results in ambiguity and decision-making can take time and be highly uncertain. Additional data sets may provide the necessary missing information and potentially suggest a different reason for its break-up. To provide another example, in the event of a collision warning between two active satellites, one will need to take evasive action to avoid impact. Conflicting data could lead to a disagreement about which satellite should move, particularly when considering the satellite’s fuel resources and the potential impact on its function. Global STM data cooperation and analysis can reduce these uncertainties. The more cooperation in STM, in terms of quantity, quality and diversity of data, the better the STM as a consequence.
