XNAV/SRNS integrated navigation based on Augmented EKF

XNAV (X-ray pulsar-based navigation) is one of the effective means to realize autonomous navigation for deep space probe, which is characterized by reliability, stability and autonomy. However, the performance of XNAV is not only affected by systematic errors such as pulsar direction error and probe-borne clock error, but also facing the challenges of weak signals and prolonged observation time. In response to the above-mentioned issues, this paper proposes an XNAV/SRNS (Spectral Redshift Navigation System) integrated navigation method based on augmented EKF. Firstly, the systematic errors are augmented into the state variable for real-time estimation by EKF. Secondly, the FKF (Federated Kalman Filter) is employed to fuse the local state estimations from XNAV and SRNS subsystems, aiming to achieve the globally optimal estimation. Finally, the proposed method is validated by comprehensive simulations and comparison analysis. The simulation results show that the proposed method can overcome the defects of XNAV effectively and improve the navigation accuracy of deep space probe significantly.