Real-Time Estimation of SGP4 Orbital Elements from GPS Navigation Data

Kurzfassung

The avaiability of GPS receivers for spaceborne applications has opened new prospects for satellite orbit determination over the past decade. In combination with a Kalman filter, accurate estimates of the spacecraft position and velocity can be obtained in real-time onboard the space vehicle. Traditionally, numerical methods of varying complexity are applied for propagating the state vector between measurements and updates of the state vector are referred to the epoch of the latest measurement. This approach is well- suited for applications requiring instataneous state estimates (e.g. sensor pointing or geocoding of images), but cannot easily be applied for onboard mission planning purposes (resource allocation, eclipse prediction, station contact forecast, etc.) that require orbit predictions. A different concept has therefore been developed, which offers increased onboard autonomy and is particularly promising for smal satellites eith moderate accuracy requirements. Here, an analytical orbit model is used to describe the spacecraft trajectory and mean epoch elements are estimated instead of the instantaneous, osculating state vector. Making use of the SGP4 orbit model that is compatible with NORAD twoline elements, an epoch state Kalman filter has been implemented and tested with GPS flight data of GPS/MET and SAC-A. It is demonstrated that the proposed method provides accuracies compatible with that of the analytical model and is robust enough to handle large data gaps in case of limited onboard resources for GPS operations. By adjusting the ballistic coefficient along with the mean epoch elements, a considerable improvement of mid-term orbit predictions is achieved over methods that are restricted to the estimation of the state vector alone.