Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/116100
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dc.contributorDepartment of Land Surveying and Geo-Informatics-
dc.creatorLi, X-
dc.creatorShu, B-
dc.creatorQu, X-
dc.creatorZhang, Q-
dc.creatorTian, Y-
dc.creatorHuang, G-
dc.creatorWang, L-
dc.date.accessioned2025-11-18T06:49:51Z-
dc.date.available2025-11-18T06:49:51Z-
dc.identifier.issn1009-5020-
dc.identifier.urihttp://hdl.handle.net/10397/116100-
dc.publisherTaylor & Francis Asia Pacific (Singapore)en_US
dc.rights© 2025 Wuhan University. Published by Informa UK Limited, trading as Taylor & Francis Group.en_US
dc.rightsThis is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. The terms on which this article has been published allow the posting of the Accepted Manuscript in a repository by the author(s) or with their consent.en_US
dc.rightsThe following publication Li, X., Shu, B., Qu, X., Zhang, Q., Tian, Y., Huang, G., & Wang, L. (2025). Improving multipath extraction in PPP-RTK for high-precision dynamic deformation monitoring. Geo-Spatial Information Science, 1–14 is available at https://doi.org/10.1080/10095020.2025.2543971.en_US
dc.subjectDeformation monitoringen_US
dc.subjectLandslideen_US
dc.subjectMultipath mitigationen_US
dc.subjectPPP-RTKen_US
dc.subjectUndifferenced residualsen_US
dc.titleImproving multipath extraction in PPP-RTK for high-precision dynamic deformation monitoringen_US
dc.typeJournal/Magazine Articleen_US
dc.identifier.doi10.1080/10095020.2025.2543971-
dcterms.abstractMultipath error is one of the most critical error sources in GNSS precise-positioning applications. Extracting accurate observational residuals is a fundamental and challenging task for constructing multipath corrections in a Precision Point Positioning Real-Time Kinematics (PPP-RTK) model. We proposed a novel multipath extraction method in UnDifferenced and UnCombined (UDUC) PPP-RTK framework. Instead of extracting multipath directly from UD residuals, our method first extracts inter-satellite Single-Difference (SD) residuals and then converts them to UD residuals. Additionally, we replace the fixed average position parameters used in traditional multipath modeling with trends that reflect the true deformation at the station, accommodating both stable and dynamic motion scenarios. Experimental results in real landslide scenarios demonstrate that the proposed method reduces the impact of receiver clock offset and other satellite ambiguity parameters on residual extraction and is suitable for both stable and dynamic motion conditions. Results from two reference networks with average spacings of 105 km and 214 km demonstrate that the proposed method achieved positioning accuracies of 1.1 cm, 1.2 cm, 3.2 cm in the east, north, up directions, and 1.0 cm, 1.3 cm, 3.3 cm, respectively. Compared to the traditional multipath extraction method that uses averaged position parameters, these results represent improvements of 15%, 14%, 20%, and 37%, 28%, 23%, respectively.-
dcterms.accessRightsopen accessen_US
dcterms.bibliographicCitationGeo-spatial information science (地球空间信息科学学报), Published online: 20 Aug 2025, Latest Articles, https://doi.org/10.1080/10095020.2025.2543971-
dcterms.isPartOfGeo-spatial information science (地球空间信息科学学报)-
dcterms.issued2025-
dc.identifier.eissn1993-5153-
dc.description.validate202511 bcch-
dc.description.oaVersion of Recorden_US
dc.description.fundingSourceOthersen_US
dc.description.fundingTextThis work is funded by the National Natural Science Foundation of China [Grant number 42127802], the National Key Research and Development Program of China [Grant number 2024YFC3012603], the Natural Science Basic Research Program of Shanxi Province [Grant number 2025JC-YBMS-251], the Innovation Team of ShaanXi Provincial Tri-Qin Scholars with Geoscience Big Data and Geohazard Prevention (2022), and the Fundamental Research Funds for the Central Universities, CHD [Grant number 300102263202].en_US
dc.description.pubStatusEarly releaseen_US
dc.description.oaCategoryCCen_US
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