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Spatio-Temporal Prediction of Ionospheric Total Electron Content Using an Adaptive Data Fusion Technique

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Abstract

The ionosphere, a part of upper atmosphere, plays an important role on the propagation of radio waves. Hence, understanding, remote sensing and monitoring of the ionospheric phenomena can provide a compressive description to the physical process that are affected by the behavior of ionosphere. One of descriptive quantity of ionosphere is Total Electron Content (TEC). TEC is the total number of electrons integrated between two points and characterized by observing carrier phase delays of received radio signals transmitted from satellites located above the ionosphere, often using Global Positioning System (GPS) satellites. In this study, TEC is predicted from TEC estimates obtained from GPS network located in Turkey in space and time using an Adaptive Data Fusion Technique (ADF). It is observed that characteristic distributions of the predict TEC and original TEC values are similar with each other. Mean Square Errors are less than 4 TECU. ADF has a high performance for the spatio-temporal prediction when the results are compared with the techniques used in the related studies in the literature.

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ACKNOWLEDGMENTS

The GIM-TEC, Satellite DCB and ephemeris data that are used in computation of IONOLAB-TEC are obtained from IGS Analysis Center of Jet Propulsion Laboratory (JPL) at (ftp://cddis.gsfc.nasa.gov/pub/gps/products/ionex). TNPGN-Active RINEX data set is made available to IONOLAB group for TUBITAK 109E055 project. This data set can be accessed by the permission from TUBITAK and General Command of Mapping of Turkish Army (http://www.hgk.msb.gov.tr/). The authors are grateful to anonymous Reviewers for their comments and contributions, which have been very helpful and constructive in improving the paper. Finally, the authors wish to thank IONOLAB group and Prof. Dr. Feza Arikan for personal communication on IONOLAB-TEC.

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  1. Department of Electrical and Electronics Engineering, Kastamonu University, Kastamonu, Turkey

    Faruk Erken, Secil Karatay & Ali Cinar

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  1. Faruk Erken
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Correspondence to Faruk Erken, Secil Karatay or Ali Cinar.

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Faruk Erken, Karatay, S. & Cinar, A. Spatio-Temporal Prediction of Ionospheric Total Electron Content Using an Adaptive Data Fusion Technique. Geomagn. Aeron. 59, 971–979 (2019). https://doi.org/10.1134/S001679321908005X

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