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dc.contributor.authorAckermann
dc.contributor.authorAngrisano
dc.contributor.authorDel Pizzo
dc.contributor.authorGaglione
dc.contributor.authorGioia
dc.contributor.authorTroisi
dc.date.accessioned2017-05-08T22:01:27Z
dc.date.available2017-05-08T22:01:27Z
dc.date.copyrightMay 2014
dc.date.issued2014
dc.identifier.other%28asce%29te%2E1943-5436%2E0000050.pdf
dc.identifier.urihttp://yetl.yabesh.ir/yetl/handle/yetl/68999
dc.description.abstractGlobal Navigation Satellite System (GNSS) surveys performed in critical environments (e.g., urban canyons, mountainous areas, or areas of dense vegetation) usually suffer from a lack of satellite coverage as a result of obstacles such as buildings and vegetation. GNSS mission-planning software provides an estimate of satellite visibility and dilution-of-precision (DOP) values along a planned trajectory to establish the best time frame over which to perform the survey. However, such an estimate is not reliable in a complex scenario because the surrounding environmental morphology is not considered. This paper introduces a new method to improve the prediction of GNSS satellite visibility. This method involves computing GNSS satellites position by means of the orbital parameters, as well as using three-dimensional digital surface models (DSMs) to develop a more reliable mission plan. The time evolution of key parameters describing the GNSS constellation is computed by means of a visibility georeferenced map for both dynamic and static surveys.
dc.publisherAmerican Society of Civil Engineers
dc.titleDigital Surface Models for GNSS Mission Planning in Critical Environments
dc.typeJournal Paper
dc.journal.volume140
dc.journal.issue2
dc.journal.titleJournal of Surveying Engineering
dc.identifier.doi10.1061/(ASCE)SU.1943-5428.0000119
dc.treeJournal of Surveying Engineering:;2014:;Volume ( 140 ):;issue: 002
dc.contenttypeFulltext


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