Three-dimensional data assimilation for ionospheric reference scenarios

The reliable estimation of ionospheric refraction effects is an important topic in the GNSS (Global Navigation Satellite Systems) positioning and navigation domain, especially in safety-of-life applications. This paper describes a three-dimensional ionosphere reconstruction approach that combines th...

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Bibliographic Details
Published in:Annales geophysicae (1988) 2017-02, Vol.35 (2), p.203-215
Main Authors: Gerzen, Tatjana, Wilken, Volker, Minkwitz, David, Hoque, Mainul M, Schlüter, Stefan
Format: Article
Language:English
Subjects:
Analysis
Computer centers
Data
Data assimilation
Data collection
Density distribution
Electron density
F 2 region
Global navigation satellite system
Ground stations
Ionosondes
Ionosphere
Ionospheric models
Navigation
Navigation satellites
Navigation systems
Navigational satellites
Profiles
Radio occultation
Receivers & amplifiers
Reconstruction
Satellite observation
Satellites
Total Electron Content
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Summary:The reliable estimation of ionospheric refraction effects is an important topic in the GNSS (Global Navigation Satellite Systems) positioning and navigation domain, especially in safety-of-life applications. This paper describes a three-dimensional ionosphere reconstruction approach that combines three data sources with an ionospheric background model: space- and ground-based total electron content (TEC) measurements and ionosonde observations. First the background model is adjusted by F2 layer characteristics, obtained from space-based ionospheric radio occultation (IRO) profiles and ionosonde data, and secondly the final electron density distribution is estimated by an algebraic reconstruction technique.The method described is validated by TEC measurements of independent ground-based GNSS stations, space-based TEC from the Jason 1 and 2 satellites, and ionosonde observations. A significant improvement is achieved by the data assimilation, with a decrease in the residual errors by up to 98 % compared to the initial guess of the background. Furthermore, the results underpin the capability of space-based measurements to overcome data gaps in reconstruction areas where less GNSS ground-station infrastructure exists.
ISSN:1432-0576
0992-7689
1432-0576
DOI:10.5194/angeo-35-203-2017