Satellite accurate orbit prediction method

Abstract

The invention relates to a satellite accurate orbit prediction method. Deep neural network automatic learning training is carried out according to comparison results of a prediction ephemeris calculated through a satellite ephemeris and kinetic models and a real ephemeris to obtain a deep neural network compensator, and then the prediction of satellite accurate obits is obtained by adding the error compensation obtained through the deep neural network compensator and prediction orbit results obtained through the kinetic models. According to the satellite accurate orbit prediction method, the kinetic prediction models and deep neural networks are two independent parts, the structure is simple, the method is easy to achieve, compared with pure kinetic models or other neural network algorithms, prediction accuracy and control over prediction errors in long-term prediction are improved.

Description

technical field [0001] The invention belongs to the technical field of aerospace orbit dynamics, and relates to a satellite precise orbit prediction method. Background technique [0002] Satellite orbit prediction is the basis of satellite application research, and it is of great significance to theoretical research and actual measurement work. The accuracy of orbit prediction, especially high-precision orbit prediction, mainly depends on the accuracy of dynamic force model. The accuracy of the dynamic model directly affects the prediction accuracy. However, the space dynamic environment is highly complex, and the nonlinearity of the satellite motion perturbation force leads to the nonlinearity of the satellite’s in-orbit motion. Coupled with the uncertainty of various parameters of the satellite itself, the simple The accuracy of the dynamic model is limited, and it is difficult to improve the prediction accuracy. [0003] In order to make up for the lack of accuracy of t...

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Problems solved by technology

[0004] In order to solve the problems existing in the prior art that there are large errors in satellite precise orbit prediction or short prediction time, the present invention aims to propose a prediction method that reduces errors, improves accuracy, and has a long application period

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