Real-Time Resident Space Object Surveillance Using Distributed Satellite Systems

Large constellations of Low Earth Orbit (LEO) satellites are expected to play a key role in a wide spectrum of applications, ranging from communication and Internet of Things (IoT) to Earth Observation (EO) and navigation augmentation services. One important application area is that of cooperative and non-cooperative surveillance for Resident Space Object (RSO) tracking and Collision Avoidance (CA). Currently, various commercial entities have plans to deploy groups of compact to moderate-sized satellites, reaching a cumulative count of more than 20,000 satellites. This poses an unprecedented challenge to satellite operators, emphasizing the need for advanced sensing and tracking techniques that provides real-time information about RSO. In this context, the use of Distributed Satellite Systems (DSS) for Space-Based Space Surveillance (SBSS) has recently received much attention, thanks to their flexibility, responsiveness and adaptability to structural and functional changes. This paper proposes a novel method for non-cooperative surveillance of RSOs using connected and intelligent DSS (iDSS). This will assist in mitigating the risk of collisions, thereby contributing to enhanced Space Domain Awareness (SDA) and to safer, more sustainable near-Earth space operations. The integration of our proposed SBSS with ground-based SDA techniques is very promising, laying foundations for a future Space Traffic Management (STM) framework, whose primary task would be ensuring Separation Assurance (SA) and Collision Avoidance (CA), largely without a direct intervention of human ground-station operators. The validity of the proposed SBSS techniques is verified through simulation case studies performed in representative conditions.