Multi-Satellite, Multi-Station TT&C Scheduling Using Multi-Objective Evolutionary Algorithms
- Paper number
IAC-11,B4,3,5,x10416
- Author
Mr. Huijiao Bu, National University of Defense Technology of the Chinese People's Liberation Army, China
- Coauthor
Mr. Jin Zhang, National University of Defense Technology, China
- Coauthor
Dr. Ya-Zhong Luo, National University of Defense Technology, China
- Year
2011
- Abstract
As the small satellites technologies development rapidly, more and more small satellites are running in orbit to complete various tasks, which even compose satellites constellations to finish more complex missions. In order to running successfully, TT&C (telemetry tracking and command) of small satellites need be considered. TT&C (telemetry tracking and command) workloads are too much for ground stations to afford. The satellite TT&C scheduling technology is an effective method to settle this problem, which is able to improve the operation efficiency of ground stations. Many studies have been made on TT&C scheduling problem, while few of them focus on multi-satellite multi -station TT&C scheduling using multi-objective optimization technique. The purpose of this paper is to propose a new scheduling method using multi-objective evolutionary algorithms for multi-satellite and multi-station TT&C problem. The multi-satellite multi-station TT&C scheduling problem is formulated as a multi-objective optimization model, where the variable that determines whether a ground station connects a satellite when the satellite appears in the ground station’s field of view is chosen as the design variables, the objective functions include the sum of the satellite TT&C priority, the ground station use priority, ground station efficiency and the maximal sum of the longest TT&C arcs. The constraints including the time windows of ground station seeing the satellite and the requirement of minimum transition duration between two neighboring satellites of a ground station are considered in the model. Two popular and well-applied multi-objective evolutionary algorithms, NSGA-II and SPEA-II are employed to solve this multi-objective problem and their performances are compared. The proposed method is applied to several TT&C scheduling problems with different number of stations and satellites. The results show that the proposed TT&C scheduling model is effective, and the proposed method can obtain the Pareto solutions which can quickly demonstrate the tradeoffs between different TT&C schemes.
- Abstract document
- Manuscript document
(absent)