The Optimal Deployment Strategy of Mega-Constellation Based on Markov Decision Process

Abstract

LEO satellite mega-constellation projects have been proposed by many countries or commercial organizations in recent years. With more than 2000 satellites launched by SpaceX to configure the Starlink system, the orbital resources are more constrained given the existence of spacecrafts and countless orbital debris. Due to this, the operating environment is full of uncertainty and information symmetry is absent for designers and stakeholders during the process of project deployment. The flux model of space debris on orbit has been built for assessing the LEO operation environment. Based on the orbital debris flux model, the collision probability can be calculated, which is an important variable of the state space. Given the condition that tge number of satellites decreases due to collision between satellites and debris, the Markov decision model has been built for optimal deployment strategy and decision-making. In order to assure that the mega-constellation system could provide services when satellites have failed, additional satellites need to be launched. The optimal deployment is the decision to launch a moderate number of satellites to maximize the benefit and minimize the cost. Assuming that at least 30 satellites need to be operated, 4 deployment scenarios are considered and the optimal deployment strategies can be obtained.