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Journal of Geodesy

, Volume 92, Issue 6, pp 637–658 | Cite as

On the impact of GNSS ambiguity resolution: geometry, ionosphere, time and biases

  • A. Khodabandeh
  • P. J. G. Teunissen
Original Article
  • 893 Downloads

Abstract

Integer ambiguity resolution (IAR) is the key to fast and precise GNSS positioning and navigation. Next to the positioning parameters, however, there are several other types of GNSS parameters that are of importance for a range of different applications like atmospheric sounding, instrumental calibrations or time transfer. As some of these parameters may still require pseudo-range data for their estimation, their response to IAR may differ significantly. To infer the impact of ambiguity resolution on the parameters, we show how the ambiguity-resolved double-differenced phase data propagate into the GNSS parameter solutions. For that purpose, we introduce a canonical decomposition of the GNSS network model that, through its decoupled and decorrelated nature, provides direct insight into which parameters, or functions thereof, gain from IAR and which do not. Next to this qualitative analysis, we present for the GNSS estimable parameters of geometry, ionosphere, timing and instrumental biases closed-form expressions of their IAR precision gains together with supporting numerical examples.

Keywords

Global navigation satellite system (GNSS) Integer ambiguity resolution (IAR) Canonical differencing (CD) transformation UD-SD-DD decomposition Estimable parameters Precision gain numbers 

Notes

Acknowledgements

The network processing results in Figs. 46 and 7 were obtained by Curtin PPP-RTK Software, developed at the Curtin GNSS Research Centre. The second author is the recipient of an Australian Research Council (ARC) Federation Fellowship (project number FF0883188). All this support is gratefully acknowledged.

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Copyright information

© Springer-Verlag GmbH Germany, part of Springer Nature 2017

Authors and Affiliations

  1. 1.GNSS Research CentreCurtin University of TechnologyPerthAustralia
  2. 2.Department of Geoscience and Remote SensingDelft University of TechnologyDelftThe Netherlands

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