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Annales Geophysicae An interactive open-access journal of the European Geosciences Union
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Volume 35, issue 2 | Copyright
Ann. Geophys., 35, 263-277, 2017
© Author(s) 2017. This work is distributed under
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

Eren Erdogan1, Michael Schmidt1, Florian Seitz1, and Murat Durmaz2 Eren Erdogan et al.
  • 1Deutsches Geodätisches Forschungsinstitut der Technischen Universität München (DGFI-TUM), Arcisstraße 21, 80333 München, Germany
  • 2Geomatics Engineering Division, Civil Engineering Department, Middle East Technical University (METU), 06800 Ankara, Turkey

Abstract. Although the number of terrestrial global navigation satellite system (GNSS) receivers supported by the International GNSS Service (IGS) is rapidly growing, the worldwide rather inhomogeneously distributed observation sites do not allow the generation of high-resolution global ionosphere products. Conversely, with the regionally enormous increase in highly precise GNSS data, the demands on (near) real-time ionosphere products, necessary in many applications such as navigation, are growing very fast. Consequently, many analysis centers accepted the responsibility of generating such products. In this regard, the primary objective of our work is to develop a near real-time processing framework for the estimation of the vertical total electron content (VTEC) of the ionosphere using proper models that are capable of a global representation adapted to the real data distribution.

The global VTEC representation developed in this work is based on a series expansion in terms of compactly supported B-spline functions, which allow for an appropriate handling of the heterogeneous data distribution, including data gaps. The corresponding series coefficients and additional parameters such as differential code biases of the GNSS satellites and receivers constitute the set of unknown parameters. The Kalman filter (KF), as a popular recursive estimator, allows processing of the data immediately after acquisition and paves the way of sequential (near) real-time estimation of the unknown parameters. To exploit the advantages of the chosen data representation and the estimation procedure, the B-spline model is incorporated into the KF under the consideration of necessary constraints. Based on a preprocessing strategy, the developed approach utilizes hourly batches of GPS and GLONASS observations provided by the IGS data centers with a latency of 1h in its current realization.

Two methods for validation of the results are performed, namely the self consistency analysis and a comparison with Jason-2 altimetry data. The highly promising validation results allow the conclusion that under the investigated conditions our derived near real-time product is of the same accuracy level as the so-called final post-processed products provided by the IGS with a latency of several days or even weeks.

Publications Copernicus
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...