Impacts of Stochastic Modeling on GPS-derived ZTD Estimations

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.

[1]  Peter Bona,et al.  Precision, Cross Correlation, and Time Correlation of GPS Phase and Code Observations , 2000, GPS Solutions.

[2]  Chris Rizos,et al.  Stochastic assessment of GPS carrier phase measurements for precise static relative positioning , 2002 .

[3]  Jan M. Johansson,et al.  Three months of continuous monitoring of atmospheric water vapor with a network of Global Positioning System receivers , 1998 .

[4]  Chris Rizos,et al.  Modelling residual systematic errors in GPS positioning: methodologies and comparative studies , 2002 .

[5]  F. Brunner,et al.  GPS signal diffraction modelling: the stochastic SIGMA-δ model , 1999 .

[6]  Jinling Wang,et al.  Stochastic Modeling for Static GPS Baseline Data Processing , 1998 .

[7]  Jaume Sanz,et al.  A new strategy for real‐time integrated water vapor determination in WADGPS Networks , 2001 .

[8]  Steven Businger,et al.  GPS Meteorology: Mapping Zenith Wet Delays onto Precipitable Water , 1994 .

[9]  C. Alber,et al.  Atmospheric Water Vapor as Noise and Signal for Global Positioning System Applications , 1993 .

[10]  Michael Bevis,et al.  GPS meteorology: Reducing systematic errors in geodetic estimates for zenith delay , 1998 .

[11]  J. Saastamoinen.  Contributions to the theory of atmospheric refraction , 1972 .

[12]  Steven Businger,et al.  GPS Meteorology: Direct Estimation of the Absolute Value of Precipitable Water , 1996 .

[13]  Paul Tregoning,et al.  Accuracy of absolute precipitable water vapor estimates from GPS observations , 1998 .

[14]  Richard A. Brown,et al.  Introduction to random signals and applied kalman filtering (3rd ed , 2012 .

[15]  Kristian Mogensen,et al.  Calculation of zenith delays from meteorological data comparison of NWP model, radiosonde and GPS delays , 2001 .

[16]  Jinling Wang,et al.  Stochastic Assessment of the GPS Measurements for Precise Positioning , 1998 .

[17]  A. Niell.  Global mapping functions for the atmosphere delay at radio wavelengths , 1996 .

[18]  H. S. Hopfield.  Two- quartic tropospheric refractivity profile for correcting satellite data , 1969 .