• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• 2014.06a
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• pp.107-108
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• 2014

As the demand for precise navigation has increased, more focus is put on the precise positioning, RTK(Real Time Kinematics) which has been used in the surveying field. The Position of Single Reference Station RTK or two-way network RTK such as VRS (Virtual Reference Station) is accurate enough to be used as a main technology in land surveying, however its service area and number of users is limited and the users are assumed static. This characteristic is not suitable to the navigation, whose service target is infinite number of users moving over a wide area. One-way network RTK has recently been suggested as a solution for the precise navigation technique for the mobile user. This paper shows the performance prediction of the one-way network RTK such as MAC(Master-Auxiliary Concept), or FKP (Flachenkorrekturparameter). To show the performance variation by the rover position, we constructed a simulation data of users on the grid with 0.1 degree spacing between 36.5 and 37 degree latitude and between 127 and 127.5 degree longitude.

• Journal of Advanced Navigation Technology
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• v.15 no.5
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• pp.705-713
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• 2011

In this paper, we introduce two techniques for resolving integer ambiguities between reference stations, which is one of the most important processes in Network RTK correction generation process. Each techniques uses Hatch filter and combination of L1/L2 measurements and we used simulation data and real data to evaluate performance of the techniques. For evaluating performance of each technique, we compared corrections generated from user site and Network RTK. As a result, Network RTK with the technique which uses Hatch filter improves user performance much more than single baseline RTK does. Residual of user is smaller than a half size of wavelength so it does not affect user integer ambiguity resolution, however, it contains significant bias error. On the other hand, when we used the technique which uses combination of L1/L2 measurements, residual error of user is largely reduced compared to the technique using Hatch filter.