Stochastic Modeling of Residual Tropospheric Delay

Hassan E. Ibrahim and Ahmed El-Rabbany

Abstract:	Generally, as a result of the limitations in current tropospheric correction models, a residual tropospheric error component remains unmodelled. The analysis of many data series representing different seasons and geographical locations showed that residual tropospheric delays are positively correlated over a time period that varies from one hour to more than two hours. Unless accounted for, such a residual tropospheric error component is expected to slow down the GPS solution convergence. In addition, an overestimation of the accuracy of both the observations and the resulting position estimates would be expected. To overcome the limitations of the current models, a new approach to tropospheric modelling is proposed in this paper. Our approach accounts for the bulk of the tropospheric delay using either of the standard tropospheric models (e.g., Saastamoinen and Hopfield models) or numerical weather prediction-based models (e.g., NOAA tropospheric correction model). The remaining residual tropospheric error component is accounted for stochastically. To do this, data series of the residual tropospheric errors are obtained by comparing the output of the above models with the new final tropospheric product of the International GNSS Service (IGS). To ensure that spatial and seasonal variations are properly taken into account, data series at well-distributed reference stations spanning a full year are generated. The various data sets are then used to develop a set of empirical covariance functions, which reflect the spatiotemporal variability of the residual tropospheric error.
Published in:	Proceedings of the 2007 National Technical Meeting of The Institute of Navigation January 22 - 24, 2007 The Catamaran Resort Hotel San Diego, CA
Pages:	1044 - 1049
Cite this article:	Ibrahim, Hassan E., El-Rabbany, Ahmed, "Stochastic Modeling of Residual Tropospheric Delay," Proceedings of the 2007 National Technical Meeting of The Institute of Navigation, San Diego, CA, January 2007, pp. 1044-1049.
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