An Automatic Navigation Method Based on Factor Graph Optimization by Observing Resident Space Objects

In response to the growing population of resident space object (RSO) in the low Earth orbit (LEO), a novel celestial navigation approach that is based on RSO observations is proposed in this paper. This study first analyzes the feasibility of navigation through RSO observations. Subsequently, an autonomous position and attitude determination algorithm is derived on the basis of RSO observations, and an inertial navigation system and RSO integrated navigation model is established. By employing factor graph optimization, the method effectively combines RSO-based navigation with inertial navigation. Finally, the navigation algorithm is verified through simulations using ephemeris data combined with star catalogs of different scales. The simulation results demonstrate that the INS/RSO integrated navigation system can achieve autonomous navigation. (c) 2025 COSPAR. Published by Elsevier B.V. All rights are reserved, including those for text and data mining, AI training, and similar technologies.