An optional algorithm for ionosphere TEC region reconstruction

Ionospheric total electron content (TEC) region reconstruction often adopts Kriging spatial interpolation method, which is based on the position relationship and correlation of TEC, satisfying the unbiasedness and optimality of weighted space estimation. However, the traditional theoretical variogram function model faces the problems of fixed function curve, unreflectable spatial detail change and chosen with subjectivity when Kriging spatial interpolation method is used to fit the variation function. To solve the above problems, this paper proposes an optional algorithm for ionosphere TEC region reconstruction. Starting from the spatial variation trend of TEC data, least squares support vector machine (LS-SVM) is used to fit the experimental variogram function, which can describe the variogram function more accurately and reflect the spatial variation trend of ionospheric TEC. To verify the accuracy of this algorithm, the vertical TEC (VTEC) values of three groups of puncture points at different times at GNSS stations in Crustal Movement Observation Network of China are selected as the measured data. The theoretical variogram function model of exponential and spherical in ordinary Kriging spatial interpolation method and the model in this paper are selected for experiments. Three sets of experimental results show that the root mean squared error (RMSE) results calculated by the ionospheric TEC region reconstruction algorithm provided in this paper are 1.54, 1.76 and 2.45 TECU, and the mean absolute error (MAE) results are 1.21, 1.23 and 1.62 TECU, respectively. The errors are smaller than those of the other two theoretical variogram function models, and the interpolation accuracy is the best. This paper provides an optional algorithm for ionosphere TEC region reconstruction.