Spacecraft attitude determination using a decoupling filter

In this paper, an algorithm for real-time attitude estimation of spacecraft motion is investigated. For efficient computation, the decoupling filter presented in this paper is accomplished by a derived pseudo-measurement from the given measurement and the decoupled state in the original system. However, the proposed decoupling filter contains model errors due to coupling terms in the system. Therefore, we develope an attitude determination algorithm in which coupling terms are compensated through an error analysis. The attitude estimation algorithm using the state decoupling technique for real-time processing provides accurate attitude determination capability under a highly maneuvering dynamic environment, because the algorithm does not have any bias errors from a truncation, and the covariance of the estimator is compensated by nonlinear terms in the system. To verify the performance of the proposed algorithm vis-a-vis the EKF (extended Kalman filter), and the nonlinear filter, simulations have been performed by varying the initial values of the state and covariance, and measurement covariance. Results show that the proposed algorithm has consistently better performance than the EKF in all of the ranges of initial state values and covariance values of measurement, and it is as accurate as the nonlinear filter. However, the convergence speed of the nonlinear filter is faster than the proposed algorithm because of the pseudo-measurement model errors in the proposed algorithm. We show that the computational time of the proposed algorithm is improved by about 23% over the nonlinear filter.