Height Modernization from Static GPS Networks in Oregon: Evaluating NGS Guidelines and OPUS-Projects Public Deposited

http://ir.library.oregonstate.edu/concern/graduate_thesis_or_dissertations/d791sk39n

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  • Determining accurate elevations is important for many engineering and scientific applications, and finding these heights via GNSS increases efficiency and significantly reduces the costs as compared to precise geodetic leveling. The National Geodetic Survey (NGS) has published guidelines for determining both ellipsoidal and orthometric heights with GPS to within 2 cm at 95% confidence. However, these guidelines, known as NOS-NGS 58 and 59, were developed based on technologies and experiences in the 1990s. Since then, GNSS-related technologies continue to improve, including increases in accuracy and availability of orbits, the completion of additional Global Navigation Satellite Systems, and the construction of more robust GNSS receivers and antennas. By closely following NGS 58 and 59 guidelines, a ten day static GPS survey campaign was conducted in Oregon during the summer of 2014. The resulting GPS baselines were processed in commercial software, Leica Geo Office (LGO©), and the final static network was adjusted by least squares in MicroSurvey STAR*NET©. From the network adjustment, the estimated error in elevation at each station ranged from plus or minus 0.8 to 1.8 cm at 95% confidence, with an average error in elevation equal to plus or minus 1.3 cm at 95% confidence. For comparison, the data was also post-processed in OPUS-Projects, a web-based program recently released by NGS for surveys involving multiple sites and multiple occupations. This comparison showed that a user-defined network in OPUS-Projects with a central hub tightly constrained to International GNSS Service (IGS) active stations yielded results most similar to those found in the commercial software. The average difference in elevations when comparing the commercial software solution with the final network in OPUS-Projects was only 5 mm. Lastly, this paper makes recommendations on how NGS 58 and 59 could be optimized by changing network configurations and changing the 1.5 cm RMS and 2.0 cm Up screening requirement to a statistical outlier identification approach. Areas of future research are also identified such as incorporating GLONASS, analyzing solutions based on fewer observations, and including trivial vectors.
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