Precision pointing estimator design for minimum absolute, window- and stability-time errors

Future satellite missions have high precision pointing performance requirements. This leads to the necessity of optimizing attitude estimators not only with respect to absolute, but also with respect to window- and stability-time errors. These errors are especially important for achieving unprecedented image quality. The standard attitude estimator is designed to be optimal with respect to its absolute knowledge error. In practice, such an estimator design is either assumed to be almost optimal for window- and stability-time errors or a cumbersome simulation-based optimization is conducted to achieve optimality in this respect. The first assumption is not sufficient for high precision pointing missions and simulation-based design is computationally expensive. In this article frequency-domain metrics are used to develop a continuous-time design approach for a fixed gain attitude estimator that is optimized with respect to window- or stability-time errors. Colored noise is explicitly taken into account in the optimization because its spectrum strongly affects the solution. However, that might lead to instability of the estimator. This issue is addressed and a solution is provided that guarantees stability with the burden of marginal performance losses only. The approach is applied to design a two-state attitude estimator and its results are verified in frequency-domain computations and time-domain simulations for the future ESA mission, Meteosat Third Generation. In this case, the computational time for optimizing the window-time error has been reduced from hours to a few seconds. The fast and high precision estimator design for window- and stability-time errors thus supports time-efficient design trade-offs.