@article{fdi:010086649,
  title = {{D}etermination of {H}elmert transformation parameters for continuous {GNSS} networks : a case study of the {G}eoazur {GNSS} network},
  author = {{T}ran, {D}. {T}. and {N}ocquet, {J}ean-{M}athieu and {L}uong, {N}. {D}. and {N}guyen, {D}. {H}.},
  editor = {},
  language = {{ENG}},
  abstract = {{I}n this paper, we propose an approach to determine seven parameters of the {H}elmert transformation by transforming the coordinates of a continuous {GNSS} network from the {W}orld {G}eodetic {S}ystem 1984 ({WGS}84) to the {I}nternational {T}errestrial {R}eference {F}rame. {T}his includes (1) converting the coordinates of common points from the global coordinate system to the local coordinate system, (2) identifying and eliminating outliers by the {D}ikin estimator, and (3) estimating seven parameters of the {H}elmert transformation by least squares ({LS}) estimation with the "clean" data (i.e. outliers removed). {H}erein, the local coordinate system provides a platform to separate points' horizontal and vertical components. {T}hen, the {D}ikin estimator identifies and eliminates outliers in the horizontal or vertical component separately. {I}t is significant because common points in a continuous {GNSS} network may contain outliers. {T}he proposed approach is tested with the {G}eoazur {GNSS} network with the results showing that the {D}ikin estimator detects outliers at 6 out of 18 common points, among which three points are found with outliers in the vertical component only. {T}hus, instead of eliminating all coordinate components of these six common points, we only eliminate all coordinate components of three common points and only the vertical component of another three common points. {F}inally, the classical {LS} estimation is applied to "clean" data to estimate seven parameters of the {H}elmert transformation with a significant accuracy improvement. {T}he {D}ikin estimator's results are compared to those of other robust estimators of {H}uber and {T}heil-{S}en, which shows that the {D}ikin estimator performs better. {F}urthermore, the weighted total least-squares estimation is implemented to assess the accuracy of the {LS} estimation with the same data. {T}he inter-comparison of the seven estimated parameters and their standard deviations shows a small difference at a few per million levels ({E}-6).},
  keywords = {{C}ontinuous {GNSS} ; tectonic geodesy ; {D}ikin estimation ; {H}elmert transformation},
  booktitle = {},
  journal = {{G}eo-{S}patial {I}nformation {S}cience},
  volume = {[{E}arly access]},
  numero = {},
  pages = {[14 p.]},
  ISSN = {1009-5020},
  year = {2022},
  DOI = {10.1080/10095020.2022.2138569},
  URL = {https://www.documentation.ird.fr/hor/fdi:010086649},
}