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TitleGLONASS ambiguity resolution of mixed receiver types without external calibration
AuthorBanville, S; Collins, P; Lahaye, F
SourceGPS Solutions 2013 p. 1-8,
Alt SeriesEarth Sciences Sector, Contribution Series 20120426
PublisherSpringer Nature
Mediapaper; on-line; digital
File formatpdf
Subjectsgeophysics; remote sensing; global positioning system
Illustrationstables; plots
ProgramGeodetic Survey, Canadian Spatial Reference System
Released2013 03 15
AbstractGLONASS processing from mixed receiver types is typically subject to unmodeled inter-frequency phase biases which prevent carrier phase ambiguity parameters from converging to integers. Receiver-dependent values have been proposed to mitigate the contribution of these biases, but are still subject to a number of issues, such as firmware updates. Recent studies have demonstrated that the origin of inter-frequency biases is a misalignment between phase and code observations, and could be calibrated to first order by manufacturers. In this contribution, a calibration-free method for GLONASS ambiguity resolution is presented in which ambiguities naturally converge to integers. A mandatory condition is that two GLONASS satellites with adjacent frequency numbers are observed simultaneously, although this condition can be relaxed once a fixed solution has been obtained. This approach then permits the integration of different receiver types and firmware versions into seamless processing.
Summary(Plain Language Summary, not published)
NRCan provides GPS solutions that enable clients to obtain consistent cm-level positioning in the Canadian Spatial Reference System. Clients will benefit from the addition of GLONASS and Galileo constellations through increased reliability and improved accuracy. However, use of different satellite constellations and receiver types presents many signal processing challenges to ensure full consistency and realize the cumulative benefits of these systems. Signal phase biases are a notable concern for the GLONASS constellation and careful treatment is necessary. This investigation reports on a novel method to mitigate the impacts of such biases, resulting in simplified processing of data from mixed receiver types and firmware versions.