Space has taken on a leading strategic role today, particularly in a world of increasing geopolitical tensions. Satellites—both civilian and military—represent key resources in fields ranging from telecommunications to military intelligence. They are therefore prime targets in espionage or direct conflict, making their surveillance and protection of paramount importance. Numerous incidents of Rendezvous and Proximity Operations (RPOs) in both geostationary and low Earth orbit have been recorded in recent years, primarily for espionage and jamming purposes. The most well-known case today is that of the Russian satellite Luch-Olymp. This, coupled with increasingly easy access to space, ever more efficient propulsion systems, relatively low-cost satellites, and rising tensions between nations, suggests a significant increase in the number of such events in the future.

Therefore, enhanced space surveillance must be implemented to detect, as early and reliably as possible, any potential close approach between a so-called chaser satellite and a target satellite requiring protection. Given that a chaser satellite will not necessarily be identified as such in advance, and that the approach strategy employed will not always be the most obvious, comprehensive and continuous surveillance must be established to ensure the early detection of any potential risk. The metrics used and the report generated on the current space situation must also be carefully designed and selected to make their analysis as simple and efficient as possible.

With this in mind, we propose here a RPO detection algorithm that classifies, for a given {target; chaser} pair, the risk to which the target satellite is exposed. The classification depends on the chaser mode of action (known or presumed): a kinetic satellite whose action only requires an interception of the target satellite (equalization of positions) does not represent the same level of risk as a jamming satellite whose action requires an orbital rendezvous with the target (equalization of positions and velocities). Furthermore, this classification is based on various metrics specific to the orbital regime under study:

• Geostationnary regime : relative longitude between the two objects (ΔL), relative drift between the two objects (δΔL) and difference in inclination (Δi).
• Medium / Low Earth Orbit regime :
  • Step 1: Difference in right ascension of the ascending node (ΔΩ), relative drift in right ascension (δΔΩ) and difference in inclination (Δi) when the two satellites are not close coplanar.
  • Step 2: In-depth study of the possible maneuver windows open to the fighter in order to carry out either an interception or an orbital rendezvous with the target in the case where the satellites are close coplanar by modeling via Lambert problem.

The proposed algorithm calculates – in conjunction with risk classification – the time to interception or rendezvous, as well as the ΔV required for the operation, allowing an operator to accurately predict the time window available to act and take measures to avoid RPO. The algorithm's lightweight workflow allows it to be executed with each update of the position velocity of a chasing or target object, enabling real-time monitoring of the spatial situation. The paper will detail the developed algorithms as well as the classification used to class the different levels of risk. Some illustration of its application to some recent events detected from the data publicly available will also be presented.