State and bias estimation of spacecraft attitude control system based on l₁-TSXKF

The state and bias estimation problem of spacecraft attitude control system considering non-Gaussian noise characteristics is studied. Firstly, a spacecraft attitude control system model with bias is established, and the expression for the non-Gaussian characteristic noise is given. Then, through l₁-norm Kalman Filtering (l₁-KF) algorithm and mathematical simulation, it is verified that the introduction of l₁-norm into the Kalman filtering algorithm can avoid the influence of non-Gaussian process noise. However, the l₁-KF algorithm cannot achieve simultaneous estimation of state and bias, and is only suitable for estimation of attitude stability control process. Therefore, on the basis of l₁-KF algorithm, considering the complex situation of time-varying moment of inertia and time-varying bias of the system, as well as real-time identification of time-varying moment of inertia, an l₁-norm Two-Stage eXogenous Kalman Filtering (l₁-TSXKF) algorithm is designed to estimate the state and bias of the spacecraft during attitude maneuver. The mathematical simulation results show that the l₁-TSXKF algorithm can reduce the influence of non-Gaussian characteristics of the system and obtain high precision attitude and bias estimation results quickly in the process of spacecraft attitude maneuver, which is conducive to the application of spacecraft in orbit.