Development of an EKF Based Gyro Calibration Method for High-Precision Attitude Estimation

Abstract

In high-resolution remote sensing satellites, achieving stability and meeting stringent pointing requirements are crucial for mission success. Accurate gyroscopes are employed as primary attitude sensors to ensure this stability. However, gyroscope data must be calibrated at appropriate intervals to maintain high attitude estimation accuracy and prevent drift over time. This research investigates an Extended Kalman Filter (EKF)-based approach for gyro calibration, aiming to enhance the precision and reliability of attitude estimation. Initially, a comprehensive model that includes the main gyro parameters—such as biases, scale factors, and misalignments—is proposed. This model is the foundation for developing an EKF-based algorithm designed to estimate and correct these gyro parameters dynamically. Following this, the study implements a Multiplicative Quaternion Extended Kalman Filter (MQEKF), which utilizes star sensor data as inputs to improve the accuracy of attitude estimation further. A quaternion feedback controller is implemented to evaluate the effectiveness of the proposed gyro calibration method within the attitude control loop. The simulation results demonstrate that the satellite's stability and pointing are maintained with accuracies better than 0.005°/s in angular velocity and 0.15° in angular positioning. These results highlight the method's potential to significantly benefit missions with tight control requirements significantly, providing enhanced performance and reliability in high-precision space applications. This approach offers a robust solution for improving satellite mission outcomes where precise attitude control is essential.

Keywords

• gyro calibration
• ekf
• high-precision attitude estimation
• quaternion feedback
• remote sensing satellites