Research On Assimilation Modeling Of Ionospheric TEC Based On GNSS

As an important component of the near-Earth space environment,an in-depth study of the morphological structure and variability of the ionosphere is of great significance to promote the research and development of ionospheric physics theory and practical applications.Among them,Total Electron Content(TEC),as a key parameter to characterize the ionospheric delay,is of great value for space weather monitoring and satellite navigation and communication applications.In this paper,we focus on the establishment and performance analysis of ionospheric TEC data assimilation models using various data assimilation methods.The main contents and results of this paper are as follows.(1)The Local Ensemble Kalman Filter(LEn KF)assimilation method is introduced to develop a global ionospheric TEC assimilation model using multi-source observations from the Global Navigation Satellite System(GNSS),COSMIC-2occultation,and JASON-3 satellites.By changing the observation structure,we study the effects of different types of observations on the assimilation of the present and forecast effects.The results show that the assimilation model is better than the background model in showing the subtle changes of ionospheric TEC.The assimilation effect is significantly improved by adding COSMIC-2 occultation data compared to MIT TEC,while the assimilation effect becomes worse by adding COSMIC-2occultation data and JASON-3 altimetry data compared to the Center for Orbit Determination in Europe(CODE)TEC data.The forecast accuracy gradually decreases with the increase of the forecast duration.(2)The assimilation model of the ionospheric TEC data in China and the surrounding region was completed and analyzed by using the LEn KF assimilation method.By comparing with CODE TEC and Bei Dou Navigation Satellite System(BDS)Geostationary Earth Orbit(GEO)TEC data,we found that the data assimilation can improve the ionospheric TEC accuracy in both the geomagnetic calm and geomagnetic disturbance periods.The correlation coefficient increased by about 17%and the Root Mean Squared Error(RMSE)decreased by 42% after assimilation compared with that before assimilation.The PPP/Assimilated ionospheric constraint can effectively improve the accuracy of single-frequency precision point positioning(PPP).(3)The Local Ensemble Transform Kalman Filter(LETKF)assimilation algorithm is introduced to develop and analyze the assimilation model of ionospheric TEC data in Yunnan and surrounding areas.The experimental results show that the assimilation model improves the background model more significantly in the geomagnetic calm period than in the geomagnetic disturbance period at low latitudes.The LETKF assimilation method can be used effectively in ionospheric data assimilation.