Design of the ASSUT-FF Algorithm for GTO Satellite CNS/BDS Integrated Navigation

The velocity and acceleration of geostationary transfer orbit (GTO) satellites change dramatically and periodically, and the operating area extends from hundreds of kilometers to 36,000 km above the Earth’s surface. This leads to the limitation of navigation methods of GTO satellites, the complexity of perturbation components and the increase of sensor measurement noise. Therefore, in this paper, a celestial navigation system/Beidou navigation system (CNS/BDS) integrated navigation method based on the adaptive spherical simplex unscented transformation federated Kalman filter (ASSUT-FF) algorithm is designed for GTO satellite high-precision autonomous navigation, considering the integrated navigation method and filtering algorithm. A Beidou observation model based on the relative pseudorange/pseudorange rate is established. Even when the GTO satellite moves to the high orbit region, it can still use BDS navigation information to determine the orbit. In addition, the designed adaptive algorithm can still ensure the filter stability in a complex space environment. The CNS/BDS integrated navigation method based on the ASSUT-FF algorithm proposed in this paper can realize continuous and high-precision autonomous navigation of GTO satellites. The simulation results show that the orbit determination accuracy of the proposed navigation method is 96.23% and 84.06% higher than that of the single celestial navigation method and the traditional Beidou geometric positioning correction celestial navigation method, respectively. The performance test results of the adaptive algorithm also show that the ASUT-FF algorithm has good robustness.