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dc.contributorDepartment of Land Surveying and Geo-Informaticsen_US
dc.creatorXiong, Ying-
dc.identifier.urihttps://theses.lib.polyu.edu.hk/handle/200/6942-
dc.languageEnglishen_US
dc.publisherHong Kong Polytechnic University-
dc.rightsAll rights reserveden_US
dc.titleAn integrated algorithm for dual-frequency GPS data pre-processingen_US
dcterms.abstractGPS data pre-processing involves two main parts: cycle slip correction for carrier phase observables and data smoothing for code pseudorange observables. For the first part, an integrated algorithm is proposed for cycle slip detection and correction. Through this algorithm, various kinds of linear combination of GPS data can be chosen according to the corresponding signal-noise ratio. Besides, the solution of cycle slip correction can be validated through the control of mis-detection and false alarm probability. For the second part, data smoothing is implemented through a standard kalman filter, in which the distance between satellite and receiver, ionosphere refraction and multipath effect are conceived as state variables. The former two variables can be calculated from corrected carrier phase observable while the multipath effect is modeled as a time-correlated Markov process. During the experiment, cycle slips are detected and corrected with the algorithm at first. Then, the corrected carrier phase observable is used to update state variables and thus smooth the code pseudorange observation. Various kinds of test are implemented; which include simulated data, real data, comparison with other algorithm, point positioning and relative positioning. The results prove the overall algorithm in this work to be effective and reliable in cycle slip correction and data smoothing.en_US
dcterms.extentx, 70 leaves : ill. ; 30 cm.en_US
dcterms.isPartOfPolyU Electronic Thesesen_US
dcterms.issued2012en_US
dcterms.educationalLevelAll Masteren_US
dcterms.educationalLevelM.Sc.en_US
dcterms.LCSHGlobal Positioning System -- Mathematical modelsen_US
dcterms.LCSHHong Kong Polytechnic University -- Dissertationsen_US
dcterms.accessRightsrestricted accessen_US

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Please use this identifier to cite or link to this item: https://theses.lib.polyu.edu.hk/handle/200/6942