[KSCI] Korea Science Citation Index Service

http://dx.doi.org/10.11003/JPNT.2018.7.3.183

Accuracy Comparison of GPT and SBAS Troposphere Models for GNSS Data Processing

Park, Kwan-Dong (Department of Geoinformatic Engineering, Inha University)
Lee, Hae-Chang (Department of Geoinformatic Engineering, Inha University)
Kim, Mi-So (PP-Solution Inc.)
Kim, Yeong-Guk (Department of Geoinformatic Engineering, Inha University)
Seo, Seung Woo (Agency for Defense Development)
Park, Junpyo (Agency for Defense Development)

Publication Information

Journal of Positioning, Navigation, and Timing / v.7, no.3, 2018 , pp. 183-188 More about this Journal

Abstract

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.

Keywords

GPS; GNSS; GPT; SBAS; tropospheric delay;

Citations & Related Records

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