Adaptive Robust Extended Kalman Filter
نویسنده
چکیده
The development of Kalman filters designed for state estimation of the position and velocity of a spacecraft is attempted and their performance evaluated. Three Kalman Filters are developed, each with its unique characteristics: the Extended Kalman Filter (EKF), the Robust Extended Kalman Filter (REKF) and the Adaptive Robust Extended Kalman Filter (AREKF). The three filters are implemented assuming the same system model, for a proper comparison analysis. Regarding the simulation, three different scenarios are modeled with different sources of non-modeled accelerations. A Low Earth Orbit with a perturbations model, an orbit with outliers and trajectory correction maneuvers. Results show that it is possible to reduce the error of the estimation when non-modeled accelerations are present. The best performance RMSE based filter is the Adaptive Robust Extended Kalman Filter, being the Extended Kalman Filter the fastest one to compute.
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