Title: An End-to-End Approach for Near Real Time Ionosphere Monitoring Over Mid-Latitudes from GPS Data Using Kriging Interpolation and IGS Products
Author(s): Elhadi Takka, Aichouch Belhadj-Aissa, Hocine Kimouche
Published in: Proceedings of IEEE/ION PLANS 2018
April 23 - 26, 2018
Hyatt Regency Hotel
Monterey, CA
Pages: 1173 - 1180
Cite this article: Takka, Elhadi, Belhadj-Aissa, Aichouch, Kimouche, Hocine, "An End-to-End Approach for Near Real Time Ionosphere Monitoring Over Mid-Latitudes from GPS Data Using Kriging Interpolation and IGS Products," Proceedings of IEEE/ION PLANS 2018, Monterey, CA, April 2018, pp. 1173-1180.
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Abstract: Ionosphere variability and disturbances affect the performance of Global Navigation Satellite Systems (GNSS). Knowledge of Total Electron Content (TEC) distribution in realtime is important to the study of solar activity. GPS networks are a valuable tool to provide TEC maps at a regional scale. This study presents a complete algorithm for near-real-time ionosphere regional mapping that emphasizes its implementation. The algorithm uses an ordinary kriging along with planar detrending to spatially predict TEC values. The differential code biases of satellites and receivers are retrieved separately from ionosphere parameters. The theoretical semivariogram function is chosen automatically from five parametric covariance functions, that is, spherical, exponential, Gaussian, Matern family and Matern Stein’s parameterization. A software package is developed and applied to 6 stations from Algerian Permanent GPS Network (RGPA) and 25 stations from IGS (International GNSS Service) network scattered over mid-latitudes of Algeria, Morocco and Western Europe. Hourly-data collected during January and February, 2014 are processed and 1°x1° TEC maps are obtained with 1-hour temporal resolution. The results show the efficiency of Matern family functions and, at lower level, Gaussian function, in fitting the TEC experimental semivarigram. To investigate performance of the spatial TEC prediction with kriging model, 10-fold cross-validation is assessed during quiet and disturbed conditions.