A New Algorithm for Ill-Posed Problem of GNSS-Based Ionospheric Tomography
Ill-posedness of GNSS-based ionospheric tomography affects the stability and the accuracy of the inversion results. Truncated singular value decomposition (TSVD) is a common algorithm of ionospheric tomography reconstruction. However, the TSVD method usually has low inversion accuracy and reconstruc...
| Main Authors: | , , , , , |
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| Format: | Article |
| Language: | English |
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MDPI AG
2023-04-01
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| Series: | Remote Sensing |
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| Online Access: | https://www.mdpi.com/2072-4292/15/7/1930 |
| _version_ | 1827746443148918784 |
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| author | Debao Wen Kangyou Xie Yinghao Tang Dengkui Mei Xi Chen Hanqing Chen |
| author_facet | Debao Wen Kangyou Xie Yinghao Tang Dengkui Mei Xi Chen Hanqing Chen |
| author_sort | Debao Wen |
| collection | DOAJ |
| description | Ill-posedness of GNSS-based ionospheric tomography affects the stability and the accuracy of the inversion results. Truncated singular value decomposition (TSVD) is a common algorithm of ionospheric tomography reconstruction. However, the TSVD method usually has low inversion accuracy and reconstruction efficiency. To resolve the above problem, a truncated mapping singular value decomposition (TMSVD) algorithm is presented to improve the reconstructed accuracy and computational efficiency. To authenticate the effectiveness and the advantages of the TMSVD algorithm, a numerical test scheme is devised. Finally, ionospheric temporal–spatial variations of the selected reconstructed region are studied using the GNSS observations under different geomagnetic conditions. The reconstructed results of TMSVD can accurately reflect semiannual anomalies, diurnal variations, and geomagnetic storm effects. In contrast with the ionosonde data, it is found that the reconstructed profiles of the TMSVD method are more consistent with than those of the IRI 2016. The study suggests that TMSVD is an efficient algorithm for the tomographic reconstruction of ionospheric electron density (IED). |
| first_indexed | 2024-03-11T05:25:25Z |
| format | Article |
| id | doaj.art-0795d3686e7d41628a8c0fb935f6c248 |
| institution | Directory Open Access Journal |
| issn | 2072-4292 |
| language | English |
| last_indexed | 2024-03-11T05:25:25Z |
| publishDate | 2023-04-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Remote Sensing |
| spelling | doaj.art-0795d3686e7d41628a8c0fb935f6c2482023-11-17T17:31:03ZengMDPI AGRemote Sensing2072-42922023-04-01157193010.3390/rs15071930A New Algorithm for Ill-Posed Problem of GNSS-Based Ionospheric TomographyDebao Wen0Kangyou Xie1Yinghao Tang2Dengkui Mei3Xi Chen4Hanqing Chen5School of Geography and Remote Sensing, Guangzhou University, Guangzhou 510006, ChinaSchool of Geography and Remote Sensing, Guangzhou University, Guangzhou 510006, ChinaSchool of Geography and Remote Sensing, Guangzhou University, Guangzhou 510006, ChinaSchool of Geodesy and Geomatics, Wuhan University, Wuhan 430072, ChinaSchool of Geography and Remote Sensing, Guangzhou University, Guangzhou 510006, ChinaSchool of Geography and Remote Sensing, Guangzhou University, Guangzhou 510006, ChinaIll-posedness of GNSS-based ionospheric tomography affects the stability and the accuracy of the inversion results. Truncated singular value decomposition (TSVD) is a common algorithm of ionospheric tomography reconstruction. However, the TSVD method usually has low inversion accuracy and reconstruction efficiency. To resolve the above problem, a truncated mapping singular value decomposition (TMSVD) algorithm is presented to improve the reconstructed accuracy and computational efficiency. To authenticate the effectiveness and the advantages of the TMSVD algorithm, a numerical test scheme is devised. Finally, ionospheric temporal–spatial variations of the selected reconstructed region are studied using the GNSS observations under different geomagnetic conditions. The reconstructed results of TMSVD can accurately reflect semiannual anomalies, diurnal variations, and geomagnetic storm effects. In contrast with the ionosonde data, it is found that the reconstructed profiles of the TMSVD method are more consistent with than those of the IRI 2016. The study suggests that TMSVD is an efficient algorithm for the tomographic reconstruction of ionospheric electron density (IED).https://www.mdpi.com/2072-4292/15/7/1930ill-posed problemionospheric electron densityalgorithmcomputerized ionospheric tomography |
| spellingShingle | Debao Wen Kangyou Xie Yinghao Tang Dengkui Mei Xi Chen Hanqing Chen A New Algorithm for Ill-Posed Problem of GNSS-Based Ionospheric Tomography Remote Sensing ill-posed problem ionospheric electron density algorithm computerized ionospheric tomography |
| title | A New Algorithm for Ill-Posed Problem of GNSS-Based Ionospheric Tomography |
| title_full | A New Algorithm for Ill-Posed Problem of GNSS-Based Ionospheric Tomography |
| title_fullStr | A New Algorithm for Ill-Posed Problem of GNSS-Based Ionospheric Tomography |
| title_full_unstemmed | A New Algorithm for Ill-Posed Problem of GNSS-Based Ionospheric Tomography |
| title_short | A New Algorithm for Ill-Posed Problem of GNSS-Based Ionospheric Tomography |
| title_sort | new algorithm for ill posed problem of gnss based ionospheric tomography |
| topic | ill-posed problem ionospheric electron density algorithm computerized ionospheric tomography |
| url | https://www.mdpi.com/2072-4292/15/7/1930 |
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