Satellite Mission Support Efficiency Evaluation Based on Cascade Decomposition and Bayesian Network

Abstract

Aiming at the complexity of evaluation system construction is high due to the numerous and jumbled nodes of satellite mission support efficiency evaluation system and the difficulty in identifying the system hierarchy and the relationship between nodes, this paper proposes an evaluation method based on Cascade decomposition and Bayesian network. Firstly, establish a satellite mission support efficiency evaluation system based on Cascade decomposition. According to the basic information of satellite health status and environmental risk, the satellite mission is decomposed into multiple dimensions such as task level, attribute level, measure level and input level. Then, a method based on Bayesian network is designed to extract the experience knowledge, which can represent the complex expert experience mathematically. Finally, an example simulation analysis of earth observation mission is carried out, and the results show that this method can effectively and accurately complete the satellite mission support efficiency evaluation, and verify the validity and correctness of this method.

This research was supported by the project: 2019001TJ20172A04097-4, the Key Laboratory Opening Funding of Harbin Institute of Technology of Deep Space Exploration Landing and Return Control Technology (HIT.KLOF.2018.076, HIT.KLOF. 2018.074), and the pre-research projects of equipment development department of China Central Military Commission (JZX7Y20190243001201).