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《中国物理文摘》
《中国天文学文摘》

Chinese Journal of Space Science ›› 2015, Vol. 35 ›› Issue (6): 715-720.

### A New Method of Orbit Prediction for LEO Satellites Using Empirical Accelerations

WANG Wenbin1, LIU Rongfang2

1. 1 Technology and Engineering Center for Space Utilization, Chinese Academy of Sciences, Beijing 100094;
2 Academy of Opto-Electronics, Chinese Academy of Sciences, Beijing 100094
• Received:2014-12-29 Revised:2015-06-11 Online:2015-10-15 Published:2015-12-07

Abstract:

A new method of orbit prediction for LEO satellites is proposed by using empirical accelerations to compensate for mismodelling of deterministic force models. The position, velocity and dynamical parameters such as CD, CR, and empirical accelerations are calculated in the orbit determination using reduced dynamic batch Least-Squares technique and GPS pseudorange observations. Therefore the position, velocity, CD, and CR can be used for prediction directly. Furthermore, the empirical accelerations are showed quasi-periodic and cosine characteristics with respect to time variable, in terms of which Fourier series were used to interpolate empirical accelerations. In this way, the fitted tangential empirical accelerations curve, which is added into deterministic force models to compensate for mismodelling of atmospheric drag model, forms enhanced-accuracy dynamic models that are used for orbit prediction. The GRACE-A real flight GPS pseudorange data and IGS Ultra-rapid products have been used to orbit determination and then the proposed method has been used to orbit prediction. The orbit determination results show that initial positioning accuracy is about 0.2m and velocity accuracy is about 1.0×10-4m·s-1. For a 72-hour orbit pass, the prediction accuracy is better than 60m, which is averagely improved about 2.3 times when compared to conventional dynamic models without considering empirical acceleration series fitting models. The proposed orbit determination and prediction scheme are beneficial to establish advanced, even onboard, satellite autonomous navigation system.

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