Construction of Space Environmental Warning Model for ESD Anomalies in High Orbit Spacecraft

The electrostatic discharge (ESD) caused by space weather disturbances is one of the major causes of anomalies in high-orbit spacecraft. The warning information about spacecraft failures and the risk of anomalies caused by ESD is necessary to improve the stability and safety of spacecraft. This paper makes a correlation analysis between space environments and in-orbit ESD anomalies and puts forward a new space environmental warning model associated with high-orbit spacecraft ESD anomalies to evaluate the probability of anomalies occurring in high-orbit spacecraft using existing space environmental information based on a series of machine learning (ML) methods. The daily flux of logarithmic high-energy electrons and AE index are selected as the environmental principal components. The model results match well with the on-orbit failure rate. Compared with SWPC flux alert criteria and 2MeV alert criteria, the model achieves a high prediction accuracy rate of 86.1% for anomalies and a very low false alarm rate of 5.3%. The new space environmental warning model, which uses principal component analysis, generalized linear regression (GLM), and decision tree, will be an effective way to provide diagnostic methods for customized in-orbit spacecraft in the future.