Fault diagnosis for space-borne fiber-optic gyroscopes using a hybrid method

Timely detection and isolation of the failures in attitude sensor is a critical task to ensure the normal operation of the satellite. This article proposes a fault detection and isolation scheme for the four-axis fiber-optic gyroscopes using a hybrid method. Based on the attitude kinematics and gyro model, a sensor fault detector is developed using an adaptive Kalman filter. The process noise covariance can be autonomously tuned by the proposed adaptive mechanism, which makes the filter more robust to the uncertain covariance parameters. The constant drift estimations obtained by the adaptive Kalman filter are applied to detect sensor faults. At the same time, the value of parity equation is computed in real-time using the signals of the four-axis gyroscopes. Then fault diagnosis rules are presented to isolate the faulty sensor. Using the proposed hybrid fault detection and isolation method, fault in gyroscopes can be detected and isolated reliably, and the fault in angle sensor can be detected as well. Thus the results of fault detection and isolation provide the criterions for fiber-optic gyroscopes reconstruction. Finally, the effectiveness of the developed scheme is demonstrated by numerical simulations of four-axis gyroscopes and star sensor with some typical faults.