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. ISPRS Journal of Photogrammetry and Remote Sensing, 196, 287–305. https://doi.org/10.1016/j.isprsjprs.2022.12.022
ISPRS Journal of Photogrammetry and Remote Sensing
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ISSN:
0924-2716
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Datum (veröffentlicht):
Feb-2023
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Umfang:
19
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Verlag:
Elsevier
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Peer Reviewed:
Ja
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Keywords:
Sensor orientation; Sensor fusion; Georeferencing; LiDAR; Camera
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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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Projekttitel:
Zuverlässiger, Automatischer und Präziser: integrierte Schätzung von Trajektorien und Punktwolken aus GNSS, INS und ALS: 883660 (Riegl Research Forschungsgesellschaft; FFG - Österr. Forschungsförderungs- gesellschaft mbH)
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Forschungsschwerpunkte:
Environmental Monitoring and Climate Adaptation: 50% Sensor Systems: 50%