Articles | Volume 35, issue 2
https://doi.org/10.5194/angeo-35-263-2017
© Author(s) 2017. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
https://doi.org/10.5194/angeo-35-263-2017
© Author(s) 2017. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
Regular paper
| 
27 Feb 2017
Regular paper |
| 27 Feb 2017
Near real-time estimation of ionosphere vertical total electron content from GNSS satellites using B-splines in a Kalman filter
Deutsches Geodätisches Forschungsinstitut der Technischen Universität München (DGFI-TUM), Arcisstraße 21, 80333 München, Germany
Michael Schmidt
Deutsches Geodätisches Forschungsinstitut der Technischen Universität München (DGFI-TUM), Arcisstraße 21, 80333 München, Germany
Florian Seitz
Deutsches Geodätisches Forschungsinstitut der Technischen Universität München (DGFI-TUM), Arcisstraße 21, 80333 München, Germany
Murat Durmaz
Geomatics Engineering Division, Civil Engineering Department, Middle East Technical University (METU), 06800 Ankara, Turkey
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Cited
28 citations as recorded by crossref.
- Fast determination of geometric matrix in ionosphere tomographic inversion with unevenly spaced curvilinear voxels J. Yu et al. 10.1007/s10291-021-01211-1
- Adaptive Modeling of the Global Ionosphere Vertical Total Electron Content E. Erdogan et al. 10.3390/rs12111822
- High-Resolution Ionosphere Corrections for Single-Frequency Positioning A. Goss et al. 10.3390/rs13010012
- Near Real-Time Global Ionospheric Modeling Based on an Adaptive Kalman Filter State Error Covariance Matrix Determination Method P. Chen et al. 10.1109/TGRS.2021.3091705
- A Least Squares Solution to Regionalize VTEC Estimates for Positioning Applications S. Farzaneh & E. Forootan 10.3390/rs12213545
- Reconstructing Regional Ionospheric Electron Density: A Combined Spherical Slepian Function and Empirical Orthogonal Function Approach S. Farzaneh & E. Forootan 10.1007/s10712-017-9446-y
- High-resolution vertical total electron content maps based on multi-scale B-spline representations A. Goss et al. 10.5194/angeo-37-699-2019
- Accuracy evaluation of XUST’s global ionospheric products P. Chen et al. 10.1016/j.asr.2021.02.041
- Real‐Time Monitoring of Ionosphere VTEC Using Multi‐GNSS Carrier‐Phase Observations and B‐Splines E. Erdogan et al. 10.1029/2021SW002858
- Comparison of quiet-time ionospheric total electron content from the IRI-2016 model and from gridded and station-level GPS observations G. Mengistu Tsidu & M. Melaku Zegeye 10.5194/angeo-38-725-2020
- An investigation of a new artificial neural network-based TEC model using ground-based GPS and COSMIC-2 measurements over low latitudes S. Shi et al. 10.1016/j.asr.2022.07.027
- The Improvement of IRI2016 global maps by the integration of Swarm and GPS observations S. Karimi et al. 10.52547/jgit.9.4.87
- Comparison of adaptive neuro-fuzzy inference system and recurrent neural network in vertical total electron content forecasting D. Pérez Bello et al. 10.1007/s00521-019-04528-8
- Rapid local ionosphere modeling based on Precise Point Positioning over Iran: A case study under 2014 solar maximum N. Abdi et al. 10.1016/j.asr.2018.09.032
- Estimation of Ionospheric Total Electron Content From a Multi-GNSS Station in China C. She et al. 10.1109/TGRS.2019.2941049
- Gauss process regression for real-time ionospheric delay estimation from GNSS observations B. Lupsic & B. Takacs 10.1007/s40328-021-00368-y
- Toward real-time construction of global ionosphere map from ground and space-borne observations Y. Han et al. 10.1007/s10291-022-01337-w
- Ionospheric electron density modelling using B-splines and constraint optimization G. Lalgudi Gopalakrishnan & M. Schmidt 10.1186/s40623-022-01693-4
- A novel approach to enhancing the Klobuchar algorithm to mitigate the effect of ionospheric delay errors on static single-frequency receivers H. Elshambaky 10.1515/jag-2023-0031
- On the drawback of local detrending in universal kriging in conditions of heterogeneously spaced regional TEC data, low-order trends and outlier occurrences W. Jarmołowski et al. 10.1007/s00190-020-01447-8
- Using Support Vector Machine (SVM) with GPS Ionospheric TEC Estimations to Potentially Predict Earthquake Events S. Asaly et al. 10.3390/rs14122822
- Global and Regional High-Resolution VTEC Modelling Using a Two-Step B-Spline Approach A. Goss et al. 10.3390/rs12071198
- Comparative analysis of the GNSS-TEC methods for determining effective height of the ionosphere O. Phillip et al. 10.1016/j.asr.2024.07.022
- Status of CAS global ionospheric maps after the maximum of solar cycle 24 Z. Li et al. 10.1186/s43020-021-00050-2
- Near real-time global ionospheric total electron content modeling and nowcasting based on GNSS observations X. Jin & S. Song 10.1007/s00190-023-01715-3
- Two‐Way Assessment of Ionospheric Maps Performance Over the Brazilian Region: Global Versus Regional Products G. Jerez et al. 10.1029/2022SW003252
- On the advantage of stochastic methods in the modeling of ionospheric total electron content: Southeast Asia case study W. Jarmołowski et al. 10.1088/1361-6501/ab0268
- Using Support Vector Machine (SVM) and Ionospheric Total Electron Content (TEC) Data for Solar Flare Predictions S. Asaly et al. 10.1109/JSTARS.2020.3044470
Latest update: 23 Nov 2024
Short summary
Although the number of terrestrial GNSS receivers is rapidly growing, the rather unevenly distributed observations do not allow the generation of high-resolution global ionosphere products. With the regionally enormous increase in GNSS data, the demands on near real-time products are growing very fast. Thus, a procedure for estimating the vertical total electron content based on B-spline representations and Kalman filtering was developed and validated by self-consistency check and altimetry.
Although the number of terrestrial GNSS receivers is rapidly growing, the rather unevenly...
