• Journal of Advanced Navigation Technology
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• v.20 no.1
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• pp.23-28
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• 2016

In this paper, we verified accuracy of the satellite based augmentation system (SBAS) tropospheric delay correction model for the Korean region. We employed the precise data of the tropospheric zenith path delay (ZPD) which is provided by the international GNSS service (IGS). In addition, we compared the verification results with that of the Saastamoinen model and the Hopfield model. Consequently, the bias residual error of the SBAS tropospheric delay correction model is about 50 mm, whereas the Saastamoinen model and the Hopfield model are more accurate. This residual error by the tropospheric delay model can affect the SBAS user position accuracy, but there is no problem in SBAS accuracy requirement. If we modified the meteorological parameters for SBAS tropospheric model to appropriate in Korean weather environment, we can provide better SBAS service to the Korean user.

• Journal of Positioning, Navigation, and Timing
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• v.7 no.3
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• pp.183-188
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• 2018

The Global Navigation Satellite System (GNSS) signal gets delayed as it goes through the troposphere before reaching the GNSS antenna. Various tropospheric models are being used to correct the tropospheric delay. In this study, we compared effectiveness of two popular troposphere correction models: Global Pressure and Temperature (GPT) and Satellite-Based Augmentation System (SBAS). One-year data from a particular site was chosen as the test case. Tropospheric delays were computed using the GPT and SBAS models and compared with the International GNSS Service tropospheric product. The bias of SBAS model computations was 3.4 cm, which is four times lower than that of the GPT model. The cause of higher biases observed in the GPT model is the fact that one cannot get wet delays from the model. If SBAS-based wet delays are added to the hydrostatic delays computed using the GPT model, then the accuracy is similar to that of the full SBAS model. From this study, one can conclude that it is better to use the SBAS model than to use the GPT model in the standard code-pseudorange data processing.