Attitude Dynamics Model-Based Gyroless Attitude Estimation for Agile Spacecraft

With increasing demand for high-agility spacecraft, the importance of accurate attitude estimation in high-agility condition is gradually increasing. In previous high-cost spacecraft missions, high-quality gyroscopes were able to be employed and the conventional gyro-based Kalman filter has provided accurate attitude estimates. However, in low-cost missions such as CubeSat missions, high-quality gyroscopes usually cannot be adopted due to its expensive price and large size/power/mass, and this leads to performance degradation in high-agility condition. This proceeding presents a simple example that illustrates how high-agility condition induces performance degradation in a classical gyro-based Kalman filter framework. Then, an alternative attitude estimation method that is based on a model-based gyroless Kalman filter framework is proposed. Numerical results demonstrate that the proposed gyroless filter could exhibit comparable attitude estimation performance, compared to the gyro-based filter, when gyro performance belongs to an industrial grade (such as MEMS gyros). The proposed gyroless filter could be implemented as a main attitude estimation method or as a backup estimation method, depending on available gyros' performance.