Improvement of Klobuchar Model for Refinement in the Chinese Region

In GPS navigation and positioning, single-frequency receivers use the Klobuchar ionospheric correction model for navigation message dissemination to correct ionospheric errors, but the correction effect is less than ideal, in order to improve its correction accuracy and use it for real time ionospheric forecasting, we refine it to meet the requirements by means of the measured data of ionospheric electron content. Firstly, the high precision ionospheric grid data released by the International GNSS Monitoring and Assessment System (IGMAS) is used as a comparison, and then in order to further improve the accuracy of the klobuchar ionospheric model, the klobuchar ionospheric error prediction model with neural network of the gated recurrent unit GRU model is established, and the sampling data of May and December 2022 are used as an example for the error prediction and then compared. In this paper, on the basis of the original Klobuchar ionospheric model, the neural network is introduced for error prediction, and a comparative study of the original method as well as the improved method is carried out, and the results show that the improved method has a better overall effect.