Abstract
With the development of space missions and the diversity of satellites, space information networks have become more complex. Space TT&C (Tracking Telemetry and Command) missions are faced with shortage of resources and complex demand characteristics. In view of these challenges, we propose a hierarchical progressive TT&C mission planning algorithm. Firstly, we model the TT&C mission planning problem as a mixed integer linear programming problem with aiming at maximizing the network reward, i.e., the weighted number of completed TT&C missions. Then, we decompose this problem into multiple levels of optimization sub-problems according to the types of constraints and use time buckets and binary conflict trees to reduce the complexity of the algorithm. Finally, we use the binary conflict tree to perform local disturbances Simulation results show that, compared with the existing planning algorithms, the proposed algorithm not only guarantees the efficiency of the algorithm, but also improves the total reward of TT&C mission planning.
This work was supported in part by the Natural Science Foundation of China under Grant U19B2025, and Grant 62001347, in part by the China Postdoctoral Science Foundation under Grant 2019TQ0241 and Grant 2020M673344, and in part by the Fundamental Research Funds for the Central Universities under Grant XJS200117.
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Wang, C., Zhou, D., Sheng, M., Li, J., Xiao, Y. (2021). Regular Space TT&C Mission Planning Based on Hierarchical Progress in Space Information Networks. In: Yu, Q. (eds) Space Information Network. SINC 2020. Communications in Computer and Information Science, vol 1353. Springer, Singapore. https://doi.org/10.1007/978-981-16-1967-0_8
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DOI: https://doi.org/10.1007/978-981-16-1967-0_8
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