Intelligent collision avoidance strategy for all-electric propulsion GEO satellite orbit transfer control

Abstract

Abstract The all-electric propulsion Geostationary Earth Orbit (GEO) satellite, characterized by its low launch cost, high precision control, and long operational lifespan, has become a focal point in aerospace research worldwide. During its orbital transfer control, this satellite continuously performs weak maneuvers across various orbits including LEO, MEO, and GEO, creating a potential “weavin” effect with other space objects, thereby dramatically increasing the risk of collisions. To effectively mitigate collision risks, this article proposes a collision warning analysis strategy based on deviation orbits. Through the categorization of warning space domain interval level, deviation orbit coverage calculation, and dynamic analysis of control parameters, a collision warning success rate of 100% is ensured. In addition, a collision avoidance algorithm based on deviation orbit control strategy is established, ensuring a 100% success rate in collision avoidance through precision calibration of electric thrust, optimization of deviation orbit control strategy, and autonomous generation of control strategy. Furthermore, a dynamic intelligent collision avoidance model based on orbit prediction error compensation is designed. By constructing an orbit prediction error analysis model, error learning model, and error compensation model, perturbation error in the orbit model are corrected, leading to an accuracy improvement of over 25% in prediction. The experimental results validate the correctness and effectiveness of the proposed methods, ensuring the safety requirements for collision warning and avoidance during the orbital transfer control process of all-electric propulsion GEO satellites.