<div class="csl-bib-body">
<div class="csl-entry">Pöppl, F., Neuner, H., Mandlburger, G., & Pfeifer, N. (2023). Integrated trajectory estimation for 3D kinematic mapping with GNSS, INS and imaging sensors: A framework and review. <i>ISPRS Journal of Photogrammetry and Remote Sensing</i>, <i>196</i>, 287–305. https://doi.org/10.1016/j.isprsjprs.2022.12.022</div>
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dc.identifier.issn
0924-2716
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dc.identifier.uri
http://hdl.handle.net/20.500.12708/142475
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dc.description.abstract
Trajectory estimation refers to the task of obtaining position and orientation estimates by fusing various sensor inputs. In kinematic mapping, global navigation satellite systems (GNSS) and inertial navigation systems (INS) are traditionally used to compute a trajectory which then serves as basis for direct or integrated orientation of the imaging sensors. As an inherently interdisciplinary problem, literature on trajectory estimation is broad. Apart from remote sensing itself, many recent advances come from autonomous navigation and robotics. This paper aims to provide a unified view of trajectory estimation with a focus on its role in kinematic mapping, specifically on the integration of GNSS, INS, laser scanners and cameras, as well as a survey of the related literature. Recent trends and challenges in trajectory estimation are identified and discussed.
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dc.description.sponsorship
Riegl Research Forschungsgesellschaft; FFG - Österr. Forschungsförderungs- gesellschaft mbH
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dc.language.iso
en
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dc.publisher
Elsevier
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dc.relation.ispartof
ISPRS Journal of Photogrammetry and Remote Sensing
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dc.rights.uri
http://creativecommons.org/licenses/by/4.0/
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dc.subject
Sensor orientation
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dc.subject
Sensor fusion
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dc.subject
Georeferencing
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dc.subject
LiDAR
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dc.subject
Camera
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dc.title
Integrated trajectory estimation for 3D kinematic mapping with GNSS, INS and imaging sensors: A framework and review