Ionospheric Assimilation of GNSS TEC into IRI Model Using a Local Ensemble Kalman Filter
Ionospheric total electron content (TEC) is important data for ionospheric morphology, and also an important parameter for ionospheric correction in Global Navigation Satellite System (GNSS) precise positioning, navigation, and radio science. In this study, we present a data assimilation model for r...
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| Format: | Article |
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MDPI AG
2022-07-01
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| Series: | Remote Sensing |
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| Online Access: | https://www.mdpi.com/2072-4292/14/14/3267 |
| _version_ | 1797444029711908864 |
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| author | Jun Tang Shimeng Zhang Xingliang Huo Xuequn Wu |
| author_facet | Jun Tang Shimeng Zhang Xingliang Huo Xuequn Wu |
| author_sort | Jun Tang |
| collection | DOAJ |
| description | Ionospheric total electron content (TEC) is important data for ionospheric morphology, and also an important parameter for ionospheric correction in Global Navigation Satellite System (GNSS) precise positioning, navigation, and radio science. In this study, we present a data assimilation model for regional ionosphere based on a local ensemble Kalman filter (LEnKF) with the International Reference Ionosphere 2016 (IRI-2016) model as the background, to assimilate ionospheric TEC observations from GNSS. To demonstrate the results, the TEC estimates from the Crustal Movement Observation Network of China (CMONOC), which is about 260 stations in China, are applied as observation. The assessments are performed against the TEC estimates from BeiDou Navigation Satellite System (BDS) geostationary earth orbit (GEO) and against the final products from the Center for Orbit Determination in Europe (CODE). The assimilation results are in good agreement with BDS GEO TEC and the CODE TEC on a quiet or disturbed day. The correlation coefficient after assimilation is increased by about 17% compared with that before assimilation, and the RMSE after assimilation is decreased by about 42% compared with that before assimilation. Furthermore, the assimilated method is also evaluated in the single-frequency precise point positioning (PPP). The experimental results indicate that the PPP/Assimilated method can improve the GNSS positioning accuracy more effectively in comparison to the PPP/CODE. These results reveal that the LEnKF method can be considered as a useful tool for ionospheric assimilation. |
| first_indexed | 2024-03-09T13:05:41Z |
| format | Article |
| id | doaj.art-650fa4ebe76d41d89696e8eb479ce211 |
| institution | Directory Open Access Journal |
| issn | 2072-4292 |
| language | English |
| last_indexed | 2024-03-09T13:05:41Z |
| publishDate | 2022-07-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Remote Sensing |
| spelling | doaj.art-650fa4ebe76d41d89696e8eb479ce2112023-11-30T21:48:20ZengMDPI AGRemote Sensing2072-42922022-07-011414326710.3390/rs14143267Ionospheric Assimilation of GNSS TEC into IRI Model Using a Local Ensemble Kalman FilterJun Tang0Shimeng Zhang1Xingliang Huo2Xuequn Wu3Faculty of Land Resources Engineering, Kunming University of Science and Technology, Kunming 650093, ChinaSchool of Information Engineering, Nanchang University, Nanchang 330031, ChinaState Laboratory of Geodesy and Earth’s Dynamics, Innovation Academy for Precision Measurement Science and Technology, Chinese Academy of Sciences, Wuhan 430077, ChinaFaculty of Land Resources Engineering, Kunming University of Science and Technology, Kunming 650093, ChinaIonospheric total electron content (TEC) is important data for ionospheric morphology, and also an important parameter for ionospheric correction in Global Navigation Satellite System (GNSS) precise positioning, navigation, and radio science. In this study, we present a data assimilation model for regional ionosphere based on a local ensemble Kalman filter (LEnKF) with the International Reference Ionosphere 2016 (IRI-2016) model as the background, to assimilate ionospheric TEC observations from GNSS. To demonstrate the results, the TEC estimates from the Crustal Movement Observation Network of China (CMONOC), which is about 260 stations in China, are applied as observation. The assessments are performed against the TEC estimates from BeiDou Navigation Satellite System (BDS) geostationary earth orbit (GEO) and against the final products from the Center for Orbit Determination in Europe (CODE). The assimilation results are in good agreement with BDS GEO TEC and the CODE TEC on a quiet or disturbed day. The correlation coefficient after assimilation is increased by about 17% compared with that before assimilation, and the RMSE after assimilation is decreased by about 42% compared with that before assimilation. Furthermore, the assimilated method is also evaluated in the single-frequency precise point positioning (PPP). The experimental results indicate that the PPP/Assimilated method can improve the GNSS positioning accuracy more effectively in comparison to the PPP/CODE. These results reveal that the LEnKF method can be considered as a useful tool for ionospheric assimilation.https://www.mdpi.com/2072-4292/14/14/3267ionosphereensemble Kalman filterTECIRIGNSSCODE |
| spellingShingle | Jun Tang Shimeng Zhang Xingliang Huo Xuequn Wu Ionospheric Assimilation of GNSS TEC into IRI Model Using a Local Ensemble Kalman Filter Remote Sensing ionosphere ensemble Kalman filter TEC IRI GNSS CODE |
| title | Ionospheric Assimilation of GNSS TEC into IRI Model Using a Local Ensemble Kalman Filter |
| title_full | Ionospheric Assimilation of GNSS TEC into IRI Model Using a Local Ensemble Kalman Filter |
| title_fullStr | Ionospheric Assimilation of GNSS TEC into IRI Model Using a Local Ensemble Kalman Filter |
| title_full_unstemmed | Ionospheric Assimilation of GNSS TEC into IRI Model Using a Local Ensemble Kalman Filter |
| title_short | Ionospheric Assimilation of GNSS TEC into IRI Model Using a Local Ensemble Kalman Filter |
| title_sort | ionospheric assimilation of gnss tec into iri model using a local ensemble kalman filter |
| topic | ionosphere ensemble Kalman filter TEC IRI GNSS CODE |
| url | https://www.mdpi.com/2072-4292/14/14/3267 |
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