| The ionospheric space weather effect caused by solar or geomagnetic activity has always been a research focus in space physics and space geodesy.Through systematic observation,theoretical research and modeling of the ionospheric space environment,it is of great scientific significance for research on ionospheric physics,and it has important application value for the protection of human living environment,the guarantee of radio communication,and the improvement of GNSS performance.In recent years,GNSS has become an important technical means for dynamic monitoring of ionospheric height because of its various advantages.In this thesis,GNSS-based two-and three-dimensional modelings of the ionosphere are studied in the following aspects:(1)Differential code bias(DCB)is the systematic error that needs to be eliminated when accurately extracting the ionospheric delay.Firstly,the stability variations of BDS satellite DCB products under different solar activity levels are studied.Secondly,the BDS satellite DCB products released by IGS MGEX may have some shortcomings,such as data missing and release delay.For these reasons,the short-term prediction of BDS satellite DCB products is realized by using auto-regressive moving average time series prediction model.The prediction results are in good agreement with the MGEX-released values,which meets the user's timely demand for DCB products,avoids the abnormal lack of DCB products and ensures data integrity.(2)The Global Ionospheric Maps released by IGS are used to monitor the horizontal disturbance characteristics of the ionospheric TEC in the middle-low-latitude regions of China during a strong magnetic storm,and the possible physical mechanisms that trigger the ionospheric disturbances are preliminarily discussed.Generally,the IGS GIM product has low spatial-temporal resolution and limited accuracy in China due to the small number of IGS stations.Based on the GNSS data from HNCORS,the regional ionospheric TEC grid model(RIM)with a higher spatial-temporal resolution in Hunan Province is established.The RIM improves the monitoring ability of ionospheric disturbance changes under the condition of magnetic storms.In addition,the ionospheric irregularities and their differences at different latitudes during the geomagnetic storms are analyzed.(3)The ionospheric tomographic system is a typical ill-posed problem,the ionospheric electron density tomographic solution is not unique or stable.To resolve this problem,a three-step improved algorithm for ionospheric tomographic reconstruction is proposed.Firstly,improving the iterative formula of the traditional multiplicative algebraic reconstruction algorithm to speed up the convergence of the tomographic iteration.Secondly,reasonable horizontal and vertical constraints are imposed on to effectively improve the ill-posed problem of the ionospheric tomographic system.Finally,the unequal interval grid division method is used in the vertical height direction.The three-step improved algorithm effectively improves the quality of ionospheric tomographic inversion.(4)Without considering the change of electron density value after each iteration,the coefficients of constraint equations remain unchanged in the whole process of tomographic iteration,which is unreasonable.A new algorithm of adaptive constrained ionospheric tomographic reconstruction is further proposed.The new method recalculates the weight coefficients of the Gaussian distance weighting function in the horizontal direction and the electronic density ratio of the adjacent voxels in the vertical section,which achieves the adaptive adjustment of the horizontal and vertical constraint equation coefficients,effectively improving the iteration speed and inversion precision.Based on the GNSS data from HNCORS,the three-dimensional distribution of ionospheric electron density in Hunan Province is reconstructed by the new algorithm,and the longitudinal,latitudinal and vertical variation characteristics of ionospheric disturbances are analyzed. |
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