State Prediction Model Using Starlight Doppler for Orbital Maneuver and Its Application in XNAV

Abstract

During maneuvering flight, a spacecraft is subject to the engine thrust besides the gravitational force fields of celestial bodies. Moreover, the engine thrust model can hardly be built accurately due to its imbalance. Accordingly, the traditional orbit dynamic mode cannot predict the state accurately, which results in a great decline of navigation filter performance. In order to solve this problem, a state prediction model based on starlight Doppler is proposed for orbital maneuver. In this model, the velocity of the spacecraft is obtained from the starlight Doppler measurement instead of the orbit dynamic model. According to the measured velocities and the constant acceleration model, the state in the navigation filter can be predicted precisely. By this means, the state prediction is not influenced by engine thrust. The proposed state prediction model is applied in the XNAV (X-ray pulsar navigation) system for orbital maneuver. In this navigation system, the starlight Doppler velocity and the pulse time-of-arrival from the X-ray pulsar are utilized to predict and update the state, respectively. The simulation results demonstrate that the state provided by the starlight Doppler-based state prediction model is immune to the engine thrust. The starlight Doppler prediction-based XNAV can provide highly-accurate navigation information for spacecraft orbital maneuvers.