Abstract
The objective of this work is to evaluate GPS static relative positioning (Hofmann-Wellenhof et al, GNSS-Global Navigation Satellite Systems GPS, GLONASS, Galileo, and more. Springer Verlag-Wien, New York, 2008; Kaplan and Hegarty, Understanding GPS: Principles and Applications. Artech House, Norwood, 2006; Leick, GPS Satellite Surveying. John Wiley & Sons, New Jersey, 2004), regarding accuracy, as the equivalent of a Real Time Kinematic (RTK) network and to address the practicality of using either a continuously operating reference stations (CORS) or a passive control point for providing accurate positioning control. The precision of an observed 3D relative position between two global navigation satellite systems (GNSS) antennas, and how it depends on the distance between these antennas and on the duration of the observing session, was studied. We analyze the performance of the software for each of the six chosen ranges of length in each of the four scenarios created, considering different intervals of observation time. The relation between observing time and baseline length is established. In this work are applied different statistical techniques, such as data analysis and elementary/intermediate inference level techniques (Tamhane and Dunlop, Statistics and Data Analysis: From Elementary to Intermediate. Prentice Hall, New Jersey, 2000) or multivariate analysis (Turkman and Silva, Modelos Lineares Generalizados da teoria a prática. Sociedade Portuguesa de Estatística, Lisboa, 2000; Anderson, An Introduction to Multivariate Analysis. Jonh Wiley & Sons, New York, 2003).
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References
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Acknowledgements
This work was supported by Portuguese funds through the Center for Computational and Stochastic Mathematics (CEMAT), The Portuguese Foundation for Science and Technology (FCT), University of Lisbon, Portugal, project UID/Multi/04621/2013, and Center of Naval Research (CINAV), Naval Academy, Portuguese Navy, Portugal.
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Teodoro, M.F., Gonçalves, F.M. (2017). A Preliminary Statistical Evaluation of GPS Static Relative Positioning. In: Quintela, P., et al. Progress in Industrial Mathematics at ECMI 2016. ECMI 2016. Mathematics in Industry(), vol 26. Springer, Cham. https://doi.org/10.1007/978-3-319-63082-3_110
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DOI: https://doi.org/10.1007/978-3-319-63082-3_110
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