Gyroless satellite attitude estimation for square root unscented kalman filter

The algorithm based on the square root Unscented Kalman filter (UKF) is presented to solve the attitude and rate estimation problem for gyroless satellite. To avoid the singular problem from Euler angle, quaternion parameterization is implemented to describe the attitude. Considering the satellite nonlinear model, the orthogonalization and Cholesky decomposition are used as computational tools in square root UKF, rendering the state covariance with positive semi-definiteness and exceptional estimation accuracy. The attitude estimation algorithm is simple in computation, and no Jacobian matrix is required to be calculated in the proposed algorithm. The efficiency of the square root UKF estimator is tested through numerical simulation of a fully actuated rigid body with only three-axis-magnetometers (TAM). The simulation results show that the algorithm is feasible and efficient.