The Combined Effect of Periodic Signals and Noise on the Dilution of Precision of GNSS Station Velocity Uncertainties

Klos, Anna; Olivares Pulido, German; Teferle, Felix Norman; Hunegnaw, Addisu; Bogusz, Janusz

Reference : The Combined Effect of Periodic Signals and Noise on the Dilution of Precision of GNS...


	Document type :	Scientific congresses, symposiums and conference proceedings : Poster
	Discipline(s) :	Physical, chemical, mathematical & earth Sciences : Earth sciences & physical geography
	To cite this reference:	http://hdl.handle.net/10993/30095

Title :	The Combined Effect of Periodic Signals and Noise on the Dilution of Precision of GNSS Station Velocity Uncertainties
Language :	English
Author, co-author :	Klos, Anna [Warsaw Military University of Technology]
	Olivares Pulido, German [University of Luxembourg > Faculty of Science, Technology and Communication (FSTC) > Engineering Research Unit >]
	Teferle, Felix Norman [University of Luxembourg > Faculty of Science, Technology and Communication (FSTC) > Engineering Research Unit >]
	Hunegnaw, Addisu [University of Luxembourg > Faculty of Science, Technology and Communication (FSTC) > Engineering Research Unit >]
	Bogusz, Janusz [Warsaw Military University of Technology]
Publication date :	5-Apr-2016
Peer reviewed :	No
On invitation :	No
Audience :	International
Event name :	EGU General Assembly 2015, Vienna, Austria, 17-22 April 2016
Event date :	17-04-2016 to 22-04-2016
Event organizer :	European Geosciences Union
Event place (city) :	Vienna
Event country :	Austria
Keywords :	[en] Dilution of Precision ; Periodic Signals ; Noise
Abstract :	[en] Station velocity uncertainties determined from a series of Global Navigation Satellite System (GNSS) position estimates depend on both the deterministic and stochastic models applied to the time series. While the deterministic model generally includes parameters for a linear and several periodic terms, the stochastic model is a representation of the noise character of the time series in form of a power-law process. For both of these models the optimal model may vary from one time series to another while the models also depend, to some degree, on each other. In the past various power-law processes have been shown to fit the time series and the sources for the apparent temporally-correlated noise were attributed to, for example, mismodelling of satellites orbits, antenna phase centre variations, troposphere, Earth Orientation Parameters, mass loading effects and monument instabilities.
Target :	Researchers ; Professionals
Permalink :	http://hdl.handle.net/10993/30095

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