We consider the problem of state and parameter estimation for geostationary spacecraft in an accurate and efficient way. For this purpose we implement a Jet Transport Taylor technique in two coordinate representations, analyzing the impact of using different orders in the computations. Then, under the assumption of a Gaussian distribution, we evaluate the mean vectors and covariance matrices corresponding to estimated states and parameters. These are incorporated into a high order Kalman filter where the estimates are updated sequentially. The performances on the orbit determination and parameter estimation are discussed by a series of numerical simulations which are compared with a classical implementation of the filter.

Peer Reviewed