Feasibility Study of Using Mobile Laser Scanning Point Cloud Data for GNSS Line of Sight Analysis

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dc.contributor Aalto-yliopisto fi
dc.contributor Aalto University en
dc.contributor.author Chen, Yuwei
dc.contributor.author Zhu, Lingli
dc.contributor.author Tang, Jian
dc.contributor.author Pei, Ling
dc.contributor.author Kukko, Antero
dc.contributor.author Wang, Yiwu
dc.contributor.author Hyyppä, Juha
dc.contributor.author Hyyppä, Hannu
dc.date.accessioned 2017-10-15T20:40:37Z
dc.date.available 2017-10-15T20:40:37Z
dc.date.issued 2017
dc.identifier.citation Chen , Y , Zhu , L , Tang , J , Pei , L , Kukko , A , Wang , Y , Hyyppä , J & Hyyppä , H 2017 , ' Feasibility Study of Using Mobile Laser Scanning Point Cloud Data for GNSS Line of Sight Analysis ' MOBILE INFORMATION SYSTEMS , vol 2017 , 5407605 . DOI: 10.1155/2017/5407605 en
dc.identifier.issn 1574-017X
dc.identifier.other PURE UUID: 8c5a593b-1d2b-483f-972a-992c6643dc7c
dc.identifier.other PURE ITEMURL: https://research.aalto.fi/en/publications/feasibility-study-of-using-mobile-laser-scanning-point-cloud-data-for-gnss-line-of-sight-analysis(8c5a593b-1d2b-483f-972a-992c6643dc7c).html
dc.identifier.other PURE LINK: http://www.scopus.com/inward/record.url?scp=85015860742&partnerID=8YFLogxK
dc.identifier.other PURE FILEURL: https://research.aalto.fi/files/15024734/5407605.pdf
dc.identifier.uri https://aaltodoc.aalto.fi/handle/123456789/28240
dc.description.abstract The positioning accuracy with good GNSS observation can easily reach centimetre level, supported by advanced GNSS technologies. However, it is still a challenge to offer a robust GNSS based positioning solution in a GNSS degraded area. The concept of GNSS shadow matching has been proposed to enhance the GNSS based position accuracy in city canyons, where the nearby high buildings block parts of the GNSS radio frequency (RF) signals. However, the results rely on the accuracy of the utilized ready-made 3D city model. In this paper, we investigate a solution to generate a GNSS shadow mask with mobile laser scanning (MLS) cloud data. The solution includes removal of noise points, determining the object which only attenuated the RF signal and extraction of the highest obstruction point, and eventually angle calculation for the GNSS shadow mask generation. By analysing the data with the proposed methodology, it is concluded that the MLS point cloud data can be used to extract the GNSS shadow mask after several steps of processing to filter out the hanging objects and the plantings without generating the accurate 3D model, which depicts the boundary of GNSS signal coverage more precisely in city canyon environments compared to traditional 3D models. en
dc.format.extent 11
dc.format.mimetype application/pdf
dc.language.iso en en
dc.relation.ispartofseries MOBILE INFORMATION SYSTEMS en
dc.relation.ispartofseries Volume 2017 en
dc.rights openAccess en
dc.subject.other Computer Science Applications en
dc.subject.other Computer Networks and Communications en
dc.subject.other 113 Computer and information sciences en
dc.subject.other 1171 Geosciences en
dc.title Feasibility Study of Using Mobile Laser Scanning Point Cloud Data for GNSS Line of Sight Analysis en
dc.type A1 Alkuperäisartikkeli tieteellisessä aikakauslehdessä fi
dc.description.version Peer reviewed en
dc.contributor.department Finnish Geospatial Research Institute
dc.contributor.department Wuhan University
dc.contributor.department Shanghai Jiao Tong University
dc.contributor.department MeMo
dc.contributor.department Department of Real Estate, Planning and Geoinformatics
dc.contributor.department Department of Built Environment en
dc.subject.keyword Computer Science Applications
dc.subject.keyword Computer Networks and Communications
dc.subject.keyword 113 Computer and information sciences
dc.subject.keyword 1171 Geosciences
dc.identifier.urn URN:NBN:fi:aalto-201710157100
dc.identifier.doi 10.1155/2017/5407605
dc.type.version publishedVersion

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