High accuracy state and parameter estimation of GEO-stationary satellites using jet transport based nonlinear filtering algorithm

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.