An statistical filtering models comparison for GNSS LEO satellite navigation

Abstract

In this work the performance of different statistical filtering models used for estimating states of aerospace vehicles, particularly LEO satellites, based on measurements of GNSS systems are compared. This problem is non-linear in nature, since both the state variables model and the output function are non-linear. Thus we resort to the use of the extension of the Kalman filter called EKF. Different models based on several kinematic and dynamic approaches are considered. For the performance assessment we use representative simulation scenarios. Finally, as a real application example, the case of GPS measurements taken on board the Argentine SAC-D satellite is analyzed.