Intelligent Scheduling Method for Satellite Ground Station Resources

China Remote Sensing Satellite Ground Station (RSGS), whose satellite-ground communication missions include telemetry, tracking and command(TT&C) and data transmission (DT ) missions, has a ground station network of 5 ground stations and serves more than 30 satellites. In recent years, the number of satellite-ground communication missions has increased sharply and this fact results in that resources of ground stations became relatively insufficient, which makes the resource scheduling significant. In this paper an intelligent ground station resource scheduling strategy is provided to solve the large-scale mix integer problem with individual needs of operators and resource usage considered. The common individual needs and resource usage are operating habits, preferences of operators, resource availability for data of different types, reliability and load balancing of multiple resources, etc. A hybrid decomposition algorithm is proposed in this paper: firstly, the overall problem is decomposed into multiple small sub-problems after a pre-process by a discrete particle swarm optimization (DPSO) algorithm; secondly, sub-problems are grouped by their solving complexity and the heuristic method or the mixed-integer linear programming (MILP) method is chosen adaptively to solve sub-problems. The method is applied to the actual operation system of RSGS and the rationality of the model and the effectiveness of the algorithm are proved in real cases.