Estimation of Multi-Constellation GNSS Observation Stochastic Properties Using a Single-Receiver Single-Satellite Data Validation Method
dc.contributor.author | El-Mowafy, Ahmed | |
dc.date.accessioned | 2017-01-30T12:50:36Z | |
dc.date.available | 2017-01-30T12:50:36Z | |
dc.date.created | 2014-08-06T20:00:18Z | |
dc.date.issued | 2015 | |
dc.identifier.citation | El-Mowafy, A. 2015. Estimation of Multi-Constellation GNSS Observation Stochastic Properties Using a Single-Receiver Single-Satellite Data Validation Method. Survey Review. 47 (341): pp. 99-108. | |
dc.identifier.uri | http://hdl.handle.net/20.500.11937/25861 | |
dc.identifier.doi | 10.1179/1752270614Y.0000000100 | |
dc.description.abstract |
The single receiver single satellite validation method is a technique that screens data from each satellite independently to detect and identify faulty observations. A new method for estimation of the stochastic properties of multi-constellation GNSS observation is presented utilising parameters of this validation method. Agreement of the characteristics of the validation statistics with theory is used as the criterion to select the best precision of the observations, spectral density and correlation time of the unknowns. A curve fitting approach in an iterative scheme is employed. The method is applicable to any GNSS with any arbitrary number of frequencies. Demonstration of the method results and performance is given using multiple-frequency data from GPS, GLONASS and Galileo in static and kinematic modes. | |
dc.publisher | Maney Publishing | |
dc.subject | GNSS | |
dc.subject | Observation precision | |
dc.subject | Data validation | |
dc.subject | Stochastic properties | |
dc.title | Estimation of Multi-Constellation GNSS Observation Stochastic Properties Using a Single-Receiver Single-Satellite Data Validation Method | |
dc.type | Journal Article | |
dcterms.source.startPage | 1 | |
dcterms.source.endPage | 11 | |
dcterms.source.issn | 0039-6265 | |
dcterms.source.title | Survey Review | |
curtin.note |
This is an Author's Original Manuscript of an article published by Taylor & Francis in The Service Industries Journal on 27/04/2014 available online at http://www.tandfonline.com/ 10.1179/1752270614Y.0000000100 | |
curtin.department | Department of Spatial Sciences | |
curtin.accessStatus | Open access |