A new study of describing the reliability of GNSS Network RTK positioning with the use of quality indicators

Abstract

The method of precise GNSS positioning using corrections from a network of reference stations, the so-called Network RTK, is currently the most accurate real time kinematic positioning method. The reliability of this method is largely dependent on the accuracy of determination of network ionospheric and geometric corrections (taking into account the tropospheric refraction and orbit errors). There are many indexes describing the reliability of Network RTK positioning in the aspect of the accuracy of modelling these errors. The so-called solution quality indicators are used for this purpose. They are parameters determined in the central network pre-processing which provide quantitative information regarding the predicted reliability of the positioning in an area encompassed by a network of reference stations. Unfortunately, their interpretation is hindered due to the lack of connection with basic parameters describing precise positioning quality, i.e. the correctness of the carrier phase ambiguity resolution and the accuracy of the rover position. This study presents a new approach to the design of quality indicators for the Network RTK method, based on a quantitative description of two parameters—solution accuracy and availability. The presented method is based on the existing parameters describing the probability of the correct fixing of ambiguities and the estimation of the fixed baseline solution accuracy. However, a stochastic model of observation, taking into account the accuracy of network corrections is used for these calculations. The proposed method enables a full account of all parameters affecting the reliability of positioning, which is not possible with the currently applied methods. Numerical tests of the new indicators carried out for a part of the regional reference stations network confirmed the effectiveness of this approach. The proposed indicators provide much more clear identification of the time periods for which the reliability of the solution was lower compared to the existing quality indexes which indications were unclear and inaccurate.

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