Abstract:The satellite attitude control system is critical in ensuring the stability and precision of satellite operations in orbit. Currently, most fault detection methods for satellite attitude control systems rely on precise modeling, making it difficult for them to adapt to diverse faults in complex dynamic environments. To address this challenge, this paper analyzes the dynamic characteristics of the satellite attitude control system, directly leveraging system input-output data and studying the mapping relationships between different signal subspaces. A subspace-aided fault detection method is proposed to enhance monitoring capabilities during satellite operations in orbit. This approach aims to improve the reliability and safety of satellite systems in complex space environments. The proposed method's effectiveness is validated through simulations of the satellite attitude control system. Results demonstrate that the method accurately detects various types of faults, exhibits strong adaptability and robustness across different fault scenarios, and provides reliable technical support for fault diagnosis during satellite operations in orbit.