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B-spline function-based approach for GPS tropospheric tomography

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Abstract

Tropospheric tomography is one of the most important techniques to reconstruct three-dimensional (3D) images of the tropospheric water vapor fields using a local GNSS network. In the conventional tropospheric tomography method, called voxel-based tropospheric tomography, the 3D space is divided into many voxels and the amount of water vapor is estimated for each voxel. This method suffers from three disadvantages. First, it needs empirical constraints in order to fix the rank deficiency of the coefficient matrix. Second, the amount of water vapor is assumed to be constant in the 3D space of a voxel despite the large spatial variations of this parameter. Third, the number of unknown parameters is high compared to the number of observations. Therefore, an approach based on mathematical functions, called function-based tropospheric tomography, is presented to overcome these problems. The tropospheric tomography using the voxel-based and function-based approaches is performed using 17 GPS stations. Radiosonde observations and precise point positioning results are used to validate the obtained results. A comparison of the results with the radiosonde data indicates that using the function-based method reduces the mean RMSE by about 0.3 gr/m3. Validation using positioning under different wet conditions shows that in wet weather conditions the difference between the RMSE of the two tropospheric tomography approaches is significant. All the validations show the ability and applicability of the function-based tropospheric tomography approach.

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Data availability

The data sets generated during and/or analyzed during the current study are not publicly available but are available from the corresponding author on reasonable request.

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Acknowledgments

The authors would like to appreciate the UNAVCO for the GPS observations and for providing high‐accuracy station position time series. We are also grateful to the ECMWF for publishing ERA-Interim data.

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Authors and Affiliations

  1. Faculty of Geodesy and Geomatics Engineering, K. N. Toosi University of Technology, Tehran, Iran

    Saeid Haji-Aghajany & Yazdan Amerian

  2. Faculty of Civil Engineering and Geosciences, Delft University of Technology, Stevinweg 1, 2628 CN, Delft, The Netherlands

    Saeid Haji-Aghajany & Sandra Verhagen

Authors
  1. Saeid Haji-Aghajany
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  2. Yazdan Amerian
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  3. Sandra Verhagen
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Correspondence to Yazdan Amerian.

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Haji-Aghajany, S., Amerian, Y. & Verhagen, S. B-spline function-based approach for GPS tropospheric tomography. GPS Solut 24, 88 (2020). https://doi.org/10.1007/s10291-020-01005-x

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