A New Method to Improve the Measurement Accuracy of Autonomous Astronomical Navigation

Abstract

Based on the theory of atmospheric refraction, combined with the atmospheric parameter data of NCEP (National Centers for environmental prediction), the Fourier interpolation fitting algorithm is used to model and analyze the parameters affecting atmospheric refraction on a global scale. The atmospheric temperature and density model with space-time variation is constructed. The spacecraft state equation and the measurement equation with the starlight apparent height as the observation quantity are established. Moreover, the Unscented Kalman filter is applied to the indirect sensitive horizon autonomous astronomical navigation of starlight refraction. The relative error of fitting the measured data with the spatiotemporal atmospheric temperature model established in this paper is less than 2%. The position estimation error of the navigation system is 94 m, and the velocity estimation error is 0.16 m/s. Compared with the traditional model, the navigation and positioning considering complex atmospheric changes are more accurate.