Optimizing satellite ground station facilities scheduling for RSGS: a novel model and algorithm

Abstract

ABSTRACT As the rapid increasing of the number of the satellites, the number of facilities of the satellite ground stations is becoming insufficient and the conflicts of serving satellite data missions exist. To make full use of the facilities of the China Remote Sensing Satellite Ground Station (RSGS), scheduling optimization of these facilities was studied in this paper, which was not well-solved by the original method in the operation system of RSGS. The problem is formulated as a continuous time-based mixed integer linear programming (MILP) model. A decomposition optimization algorithm is proposed to solve the large-scale problem, which is difficult to solve using traditional methods. In the first step, the particle swarm optimization (PSO) algorithm is used to optimize the multi-ground station relay tasks, and the multi-ground station optimization problem is transformed into several single ground station optimization problems. Next, in two additional steps, optimization of the facilities at a single ground station is performed to further reduce the size of the model. The proposed method has been applied to operations systems of RSGS, and the approach presented in this article has demonstrated stable performance and sufficient efficiency online, resulting in the automation of facility scheduling.