High-precision orbit prediction and error control techniques for COMPASS navigation satellite

A new satellite orbit prediction method based on artificial neural network (ANN) model is proposed to improve the precision of orbit prediction. In order to avoid the difficulty of amending the dynamical model, it is attempted to use ANN model to learn the variation of orbit prediction error, and then the prediction result of ANN model is used to compensate the predicted orbit based on dynamic model to form a final predicted orbit. The experiment results showed that the orbit prediction error based on ANN model was less than that based on dynamical model, and the improvement effects for different satellites and different time were different. The maximum rates of improvement of predicting 8, 15, 30 d were respectively 80 %, 77.77 %, 85 %. The orbit prediction error control technique based on the method of back overlap arc compare was brought forward to avoid the risk that the precision of predicted orbit is even worse after it is compensated by ANN model. The phenomena of failure were basically eliminated based on this technique, and the rate of failure was reduced from 30 % to 5 %. This technique could ensure that the engineering application of ANN model could come true.