Fault diagnosis for satellite's attitude determination system based on model error prediction and EMD

As one of the main parts for a satellite's attitude measure and control system, star trackers and gyros tend to be damaged in the actual on-orbit operation. That often makes the satellite fail to finish the given task. In this paper, an approach is proposed to detect, identify and diagnose the fault for gyro and star tracker in a satellite's attitude determination system. The model errors, including the model uncertainty and the fault factors, are estimated by predictive filter based on a satellite's attitude kinematics equation firstly. And then the estimated model error is decomposed into some intrinsic mode functions (IMF) and one trend component by the empirical mode decomposition (EMD). Furthermore, the fault model for the trend component is established by the time series analysis. And the time series model's parameters and residual variance are extracted as the feature vector, which is used to construct the discriminant function for the fault diagnosis of gyro and star tracker. Finally, promising simulated experimental results demonstrate the validity and effectiveness of the proposed method. Compared with the traditional fault diagnosis method, the detection and identification precision of the approach are improved significantly.