Journal
PHOTOGRAMMETRIE FERNERKUNDUNG GEOINFORMATION
Volume -, Issue 1, Pages 17-30Publisher
E SCHWEIZERBARTSCHE VERLAGSBUCHHANDLUNG
DOI: 10.1127/pfg/2016/0284
Keywords
self-calibration; (in)direct sensor orientation; block deformation; UAV-based RTK; cross flight pattern; sensor synchronisation
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Unmanned aerial vehicles (UAV) are increasingly used for topographic mapping. Despite the flexibility gained when using those devices, one has to invest more effort for ground control measurements compared to conventional photo-grammetric airborne data acquisition, because positioning devices on UAVs are generally less accurate. Additionally, the limited quality of employed end-user cameras asks for self-calibration, which might cause some problems as well. A good distribution of ground control points (GCPs) is not only needed to solve for the absolute orientation of the image block in the desired coordinate frame, but also to mitigate block deformation effects which are resulting mainly from remaining systematic errors in the camera calibration. In this paper recent developments in the UAV-hardware market are picked up: some providers equip fixed-wing UAVs with RTK-GNSS-enabled 2-frequency receivers and set up a processing pipeline which allows them to promise an absolute block orientation in a similar accuracy range as through traditional indirect sensor orientation. Besides the analysis of the actually obtainable accuracy, when one of those systems is used, we examine the effect different flight directions and altitudes (cross flight) have onto the bundle adjustment. For this purpose two test areas have been prepared and flown with a fixed-wing UAV. Results are promising: not only the absolute image orientation gets significantly enhanced when the RTK-option is used, also block deformation is reduced. However, remaining offsets originating from time synchronization or camera event triggering should be considered during flight planning. In flat terrains a cross flight pattern helps to enhance results because of better and more reliable self-calibration.
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