Earth Planets Space, Vol. 57 (No. 4), pp. 253-259, 2005
Shuanggen Jin1,2,3, J.Wang2, and Pil-Ho Park1
1Space Geodesy Research Group, Korea Astronomy and Space Science Institute, Daejeon 305-348, South Korea
2School of Surveying and Spatial Information Systems, University of New South Wales, Sydney, NSW 2052, Australia
3Shanghai Astronomical Observatory, Chinese Academy of Sciences, Shanghai 200030, China
(Received November 12, 2004; Revised March 11, 2005; Accepted March 14, 2005)
The results of GPS positioning depend on both functional and stochastic models. In most of the current GPS processing programs, however, the stochastic model that describes the statistical properties of GPS observations is usually assumed that all GPS measurements have the same accuracy and are statistically independent. Such assumptions are unrealistic. Although there were only a few studies modeling the effects on the GPS relative positioning, they are restricted to short baselines and short session lengths. In this paper, the stochastic modeling for IGS long-baseline positioning (with 24-hour session) is analyzed in the GAMIT software by modified stochastic models. Results show that any mis-specifications of stochastic model result in unreliable GPS baseline results, and the deviation of baseline estimations reaches as much as 2 cm in the height component. Using the stochastic model of satellite elevation angle-based cosine function, the precision of GPS baseline estimations can be improved, and the GPS baseline component is closest to the reference values, especially GPS height.
Key words: ochastic modeling, GPS, IGS, height.