Research on Satellite Orbit Prediction Based on Neural Network Algorithm

Abstract

Satellite orbits predictions is a significant research problem for collision avoidance in space area. However, current prediction methods for satellite orbits are not accurate enough because of the lack of information such as space environment condition. The traditional methods tend to construct a perturbation model. Because of the intrinsic low accuracy of the perturbation model, the prediction accuracy of the low-order analytical solution is relatively low. While the high-order analytical solution is extremely complex, it results in low computational efficiency and even no solution. This paper presents a satellite orbit prediction method based on neural network algorithm, which discovers the orbital variation law by training historical TLE data to predict satellite orbit. The experiment results show that the proposed algorithm is feasible.