Impacts of Stochastic Modeling on GPS-Derived ZTD Estimations

Shuanggen Jin, Jinling Wang

Abstract:	GPS-derived ZTD (Zenith Tropospheric Delay) plays a key role in near real-time weather forecasting, especially in improving the precision of Numerical Weather Prediction (NWP) models. The ZTD is usually estimated using the first-order Gauss-Markov process with a fairly large correlation, and under the assumption that all the GPS measurements, carrier phases or pseudo-ranges, have the same accuracy. However, these assumptions are unrealistic. This paper aims to investigate the impact of several stochastic modeling methods on GPS-derived ZTD estimations using Australian IGS data. The results show that the accuracy of GPS-derived ZTD can be improved using a suitable stochastic model for the GPS measurements. The stochastic model using satellite elevation angle-based cosine function is better than other investigated stochastic models. It is noted that, when different stochastic modeling strategies are used, the variations in estimated ZTD can reach as much as 1cm. This improvement of ZTD estimation is certainly critical for reliable NWP and other tropospheric delay corrections. Keywords: Stochastic Modeling, GPS, ZTD, Gauss- Markov.
Published in:	Proceedings of the 17th International Technical Meeting of the Satellite Division of The Institute of Navigation (ION GNSS 2004) September 21 - 24, 2004 Long Beach Convention Center Long Beach, CA
Pages:	941 - 946
Cite this article:	Jin, Shuanggen, Wang, Jinling, "Impacts of Stochastic Modeling on GPS-Derived ZTD Estimations," Proceedings of the 17th International Technical Meeting of the Satellite Division of The Institute of Navigation (ION GNSS 2004), Long Beach, CA, September 2004, pp. 941-946.
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