An improved method for mission risk analysis of the satellite ACS

The attitude control system (ACS) is crucial for the satellite operation in the space, and it is a typical phased-mission system (PMS). Some features caused by the system designs bring difficulties in the ACS mission risk analysis, and the traditional risk analysis method probabilistic risk assessment (PRA) must be modified to model and analyze the redundant and dynamic features in the system. This paper proposes an improved method for mission risk analysis based on the traditional PRA framework, and combines the dynamic fault tree (DFT) and Bayesian networks (BN) methods with the traditional framework to solve the redundancy features, operation sequence dependencies, and relevant failure properties of some components in the ACS. This method can give a more accurate description of the ACS mission, and the analysis results show that this proposed method can provide more useful information for system design improvements.