The increasing number of satellites and space debris poses significant challenges to the sustainable use of the Earth orbital environment. The proliferation of satellite constellations intensifies the risks of overexploitation and collisions, and underscores the need for effective Space Traffic Management (STM) strategies. Central to STM is Space Situational Awareness (SSA), which relies on accurate tracking and trajectory estimation of space objects using observable measurements and orbital mechanics. This paper explores the role of Global Navigation Satellite Systems (GNSS) to enable the operation of cooperative SSA services, which aim to exploit collaboration among various space actors to enhance space safety and sustainability. GNSS offers continuous, global coverage for Precise Orbit Determination (POD) and enables real-time orbit tracking for cooperative satellites. However, GNSS-based methods are constrained to active satellites equipped with receivers, and small satellites often face limitations in size, power, and processing capabilities. To address these challenges, the European Commission’s Joint Research Centre has proposed a novel and compact solution called SARGASSIA (Search & Rescue and GNSS for Space Situational Awareness), which integrates low SWaP-C (Size, Weight, Power, Cost) snapshot GNSS receivers with Search and Rescue (SAR) technology. This system activates the GNSS receiver under specific conditions, such as satellite failure or end-of-life, and transmits data on ground via SAR communication links. It allows for intermittent but power-efficient position updates, making even inactive satellites temporarily cooperative for STM purposes. The study includes a trade-off analysis between the sparse, energy-saving data from SARGASSIA and the accuracy of Reduced-Dynamic POD. It evaluates performance under degraded conditions (e.g., poor satellite visibility due to loss of attitude control capability) and compares it with traditional, noncooperative SSA methods. A comprehensive POD pipeline is developed to support the analysis, emphasizing accuracy and responsiveness for effective collision avoidance and STM.
RUSSO Pietro;
ISOLETTA Giorgio;
OPROMOLLA Roberto;
FASANO Giancarmine;
MENZIONE Francesco;
PICCOLO Andrea;
2025-10-23
Institute of Navigation
JRC144193
978-0-936406-42-8 (online),
2331-5954 (online),
https://www.ion.org/publications/browse.cfm?proceedingsID=171,
https://www.ion.org/publications/abstract.cfm?articleID=20350,
https://publications.jrc.ec.europa.eu/repository/handle/JRC144193,
10.33012/2025.20350 (online),
