The application of radial basis function neural network in the GPS satellite clock bias prediction

Satellite atomic clocks can be easily influenced by various factors in space, so the clock behaviour is not sufficiently described and cannot achieved a reliable high-precision prediction by the existed model, such as a linear model, a quadratic polynomial model, grey model and so on. Radial basis function neural network was used in the continuous prediction of four GPS satellite clock bias with five minutes, one hour and one day in this paper, the root mean square error was better than 0.8 ns, 0.6 ns and 1 ns, respectively, these prove the reliability of the radial basis network structure on the clock error forecasting.