Ground replenishment strategy optimization of LEO satellite constellations considering performance degradation

This paper optimizes a ground replenishment strategy for large-scale LEO satellite constellations, aiming for ensuring high economic efficiency and performance requirements. Firstly, the uncertainties of influential elements are analyzed and satellite lifetime distributions are estimated to determine satellite operating statuses. Secondly, satellite statuses are used for obtaining real-time constellation status and simulating data package transmission paths. Performance degradation function is then derived by selecting time delay as the key performance. To confront with the performance degradation, an optimization model of ground replenishment strategy is established with the objective of minimizing the overall replenishment cost under the time delay and loading capacity constraints. The model is solved by a Dichotomous-domain algorithm. Finally, a case study of a large-scale STARLINK constellation is adopted to validate the effectiveness of the model and sensitivity analyses are conducted to verify its robustness. © 2024 Informa UK Limited, trading as Taylor & Francis Group.