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dc.contributor.authorLo, Johnny
dc.contributor.authorEl-Mowafy, Ahmed
dc.contributor.editorNew Zealand Institute of Surveyors and the Surveying and Spatial Sciences Institute.
dc.date.accessioned2017-01-30T13:04:21Z
dc.date.available2017-01-30T13:04:21Z
dc.date.created2012-02-02T20:00:45Z
dc.date.issued2011
dc.identifier.citationLo, Johnny and El-Mowafy, Ahmed. 2011. Interpolation of the GNSS Wet Troposphere Delay, in Proceedings of the Surveying and Spatial Sciences Biennial Conference, Nov 21-25 2011, pp. 425-438. Wellington, NZ: New Zealand Institute of Surveyors and the Surveying and Spatial Sciences Institute.
dc.identifier.urihttp://hdl.handle.net/20.500.11937/28323
dc.description.abstract

Troposphere delay is one of the main distance-dependent errors in Global Navigation Satellite Systems (GNSS) observations. Precise estimation of the troposphere wet delay is necessary to aid ambiguity resolution and for positioning in network Real-Time Kinematic (RTK) and Precise Point Positioning. Wet tropospheric estimates can also serve as a source of atmospheric information to facilitate weather forecasting. Interpolation of the troposphere wet delay is thus required when its estimation is interrupted for short periods or when data are processed at higher intervals from that of available data. The objective of this research is to compare the performance of several interpolation methods that can be used in order to suggest the most appropriate technique. Six interpolation models were considered. The models ranged from the easy-to-implement linear model, to the more sophisticated Kriging model. Other models considered are the cubic spline interpolation, cubic Hermite polynomial interpolation, Lagrange polynomial interpolation, and Fast Fourier transform interpolation. The performance of these methods was assessed by comparing their results with actual troposphere wet delay data collected at the station Onsala (ONSA) in Sweden. As the number of observations used to generate the interpolation process affects the determination of the model coefficients; the use of different lengths of observations was investigated. The number of missing wet delay values considered for interpolation during testing ranged from one to four in a row.Test results showed that the linear interpolation, the cubic Hermite polynomial and fast Fourier transform models produce better estimates than splines and ordinary Kriging. The Lagrange polynomials method was the poorest performer. The paper provides explanation of the interpolation results achieved by linking them with autocorrelation of the troposphere wet delays.

dc.publisherNew Zealand Institute of Surveyors and the Surveying and Spatial Sciences Institute. ONLINE publication
dc.subjectGNSS
dc.subjectPrecise Positioning
dc.subjectTroposphere wet Delay
dc.subjectInterpolation
dc.titleInterpolation of the GNSS Wet Troposphere Delay
dc.typeConference Paper
dcterms.source.startPage425
dcterms.source.endPage438
dcterms.source.serieshttp://www.sssc2011.com/assets/Papers/Reviewed/ElMowafyAhmedInterpolation-of-the-GNSS-Wet-Tropospheric-Delay..pdf
dcterms.source.conferenceSurveying and Spatial Sciences Conference, 2011
dcterms.source.conference-start-dateNov 21 2011
dcterms.source.conferencelocationWellington, New Zealand
dcterms.source.placeNew Zealand
curtin.note

Copyright © 2011 Surveying & Spatial Sciences Institute (SSSI)

curtin.departmentDepartment of Spatial Sciences
curtin.accessStatusOpen access


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