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Vector ionosphere modeling by vector spherical Slepian base functions

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Abstract

Ionosphere and its spatial and temporal gradients play an important role in positioning and navigation using global navigation satellite systems (GNSS). This study intends to propose a new method for modeling both the spatial gradients and also the total electron content (TEC) in radial direction (vertical TEC or VTEC). The spatio-spectral concentration is applied to optimize vector spherical harmonic functions. The Slepian theory is used for this purpose. Dual-frequency GPS measurements are used to derive the required input data utilizing six IGS (International GNSS Service) stations, located in the northern polar region. Two additional IGS stations are used to analyze the accuracy of the developed model. To employ the method, GPS measurements over three periods, i.e., over high and low solar activity and perturbed ionospheric conditions, have been used. Four vector spherical Slepian models with the maximal degrees of K = 10, 15, 20 and 25 are taken into account. The models are estimated at each epoch in this research. Based on the results, K = 15 is the optimum degree for the vector spherical Slepian (VSS) model. On average, at the degree of 15, the RMSE is about 0.1 TECU and less than 0.05 TECU/degree for the radial and tangential components, respectively. Repeatability of the baseline (precision) components on a long baseline is used as a measure for validation of VSS model. On average, the repeatability improves by 25 and 35 % in the vertical and horizontal components for gradients of ionosphere.

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Authors and Affiliations

  1. Faculty of Geodesy and Geomatics Engineering, K. N. Toosi University of Technology, No. 1346, Vali_Asr Ave., Mirdamad Cr., Tehran, Iran

    Hossein Etemadfard & Masoud Mashhadi Hossainali

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  1. Hossein Etemadfard
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  2. Masoud Mashhadi Hossainali
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Correspondence to Hossein Etemadfard.

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Etemadfard, H., Hossainali, M.M. Vector ionosphere modeling by vector spherical Slepian base functions. GPS Solut 21, 675–684 (2017). https://doi.org/10.1007/s10291-016-0559-4

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