A High Accuracy Spatial Reconstruction Method Based on Surface Theory for Regional Ionospheric TEC Prediction
Abstract In order to achieve more accurate spatial reconstruction of ionospheric total electron content (TEC) and promote improved satellite positioning and ranging applications, a high accuracy spatial reconstruction (HASR) method for TEC is proposed based on the surface theory. The core theory of...
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| Format: | Article |
| Language: | English |
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Wiley
2023-12-01
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| Series: | Space Weather |
| Online Access: | https://doi.org/10.1029/2023SW003663 |
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| author | Jian Wang Yi‐ran Liu Ya‐fei Shi |
| author_facet | Jian Wang Yi‐ran Liu Ya‐fei Shi |
| author_sort | Jian Wang |
| collection | DOAJ |
| description | Abstract In order to achieve more accurate spatial reconstruction of ionospheric total electron content (TEC) and promote improved satellite positioning and ranging applications, a high accuracy spatial reconstruction (HASR) method for TEC is proposed based on the surface theory. The core theory of this method is as follows: (a) Any surface can be uniquely determined by its first and second fundamental quantities; (b) By direct difference approximation, differential equations are transformed into algebraic equations to solve Gauss equations faster. At the same time, taking parts of Europe as an example, the proposed HASR method is used to determine the correlation coefficients and the number of iterations of the model by using the relative root mean square error (RRMSE) as the evaluation criterion. The statistical results show that the TEC predicted by the HASR method is highly consistent with the actual observed values of ionospheric observation stations, and the prediction RRMSE is 9.75%. Compared with the Kriging interpolation with scale factor, the prediction accuracy of the HASR method is improved by 8.5%. We hope this method can provide ideas for the spatial reconstruction of other ionospheric parameters and further promote the realization of complete and accurate space weather forecast. |
| format | Article |
| id | doaj-art-991e9e41584e4f678e2eeab2c96efdba |
| institution | Kabale University |
| issn | 1542-7390 |
| language | English |
| publishDate | 2023-12-01 |
| publisher | Wiley |
| record_format | Article |
| series | Space Weather |
| spelling | doaj-art-991e9e41584e4f678e2eeab2c96efdba2025-01-14T16:30:45ZengWileySpace Weather1542-73902023-12-012112n/an/a10.1029/2023SW003663A High Accuracy Spatial Reconstruction Method Based on Surface Theory for Regional Ionospheric TEC PredictionJian Wang0Yi‐ran Liu1Ya‐fei Shi2School of Microelectronics Tianjin University Tianjin ChinaSchool of Microelectronics Tianjin University Tianjin ChinaSchool of Microelectronics Tianjin University Tianjin ChinaAbstract In order to achieve more accurate spatial reconstruction of ionospheric total electron content (TEC) and promote improved satellite positioning and ranging applications, a high accuracy spatial reconstruction (HASR) method for TEC is proposed based on the surface theory. The core theory of this method is as follows: (a) Any surface can be uniquely determined by its first and second fundamental quantities; (b) By direct difference approximation, differential equations are transformed into algebraic equations to solve Gauss equations faster. At the same time, taking parts of Europe as an example, the proposed HASR method is used to determine the correlation coefficients and the number of iterations of the model by using the relative root mean square error (RRMSE) as the evaluation criterion. The statistical results show that the TEC predicted by the HASR method is highly consistent with the actual observed values of ionospheric observation stations, and the prediction RRMSE is 9.75%. Compared with the Kriging interpolation with scale factor, the prediction accuracy of the HASR method is improved by 8.5%. We hope this method can provide ideas for the spatial reconstruction of other ionospheric parameters and further promote the realization of complete and accurate space weather forecast.https://doi.org/10.1029/2023SW003663 |
| spellingShingle | Jian Wang Yi‐ran Liu Ya‐fei Shi A High Accuracy Spatial Reconstruction Method Based on Surface Theory for Regional Ionospheric TEC Prediction Space Weather |
| title | A High Accuracy Spatial Reconstruction Method Based on Surface Theory for Regional Ionospheric TEC Prediction |
| title_full | A High Accuracy Spatial Reconstruction Method Based on Surface Theory for Regional Ionospheric TEC Prediction |
| title_fullStr | A High Accuracy Spatial Reconstruction Method Based on Surface Theory for Regional Ionospheric TEC Prediction |
| title_full_unstemmed | A High Accuracy Spatial Reconstruction Method Based on Surface Theory for Regional Ionospheric TEC Prediction |
| title_short | A High Accuracy Spatial Reconstruction Method Based on Surface Theory for Regional Ionospheric TEC Prediction |
| title_sort | high accuracy spatial reconstruction method based on surface theory for regional ionospheric tec prediction |
| url | https://doi.org/10.1029/2023SW003663 |
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