Research On Ionospheric Data Assimilation Based On GNSS System

The ionosphere is an important part of the near-earth space environment.It locates between the outer space and middle atmosphere.Various thermodynamic,chemical and dynamic processes affect human production and life.The research on the ionosphere can enrich our knowledge of the sun-earth system and serve the human's space activities.Therefore,it is significantly to study the ionospheric.In the recent years,with the increasingly frequent of human's communication system and space activity,our demand for understanding the ionospheric fundamental state and forecast the ionospheric climate and disturbances is increasing.On the basis,data assimilation method used in meteorological were introduced.By combining observation data and theoretical model,the method can more accurately describe the state of ionospheric,eventually achieves the Ionospheric nowcast and forecast.The main contents are as follows:Firstly,the work about the study of the inversion technique,inverting the ionospheric electron density profile by GNSS(Global Navigation Satellite System).In the recent years,ionospheric TEC(Total election content)from the GNSS measurements is widely used.However,compared with altimeter and other equipment,GNSS can only measure TEC,and cannot obtain the electron density of vertical.It is also one of its main shortage.So,how to further obtain the electron density of vertical and meet the demand of more applications,became an important direction of GNSS data applications in recent years.A classical ionospheric inversion method is proposed in this paper.It used Chapman function of ionospheric electron density profile.Then the feasibility of the method is studied.Compared with other methods,this method has the advantages of high computational efficiency and high timeliness.Then the inversion results were compared with the observation data,we believed the method has a high inversion precision.It can be described the characteristic of ionospheric electron density in the vertical structure effectively.Secondly,the work about the study of ionospheric data assimilation model.According to study of several commonly data assimilation method,we found that the background error covariance matrix is very important in the process of assimilation.However,in the actual application process of data assimilation algorithm,the back error covariance matrix has data large and calculation process complex.Hence,in order to reduce the computation of the assimilation algorithm and improve the computational efficiency,we need to make a reasonable estimate of the background error covariance matrix and make a model.The paper is based on this.Studying the global TECMAP data,the error covariance matrix of each grid is obtained,which is helpful for us to further understand the correlation scale characteristics of ionosphere in various changes.The covariance matrix of the ionospheric background error is better constructed,which provides a reference for the analysis and modeling of specific background error,and finally improves the ionospheric data assimilation system.