Abstract
Abstract. Highly precise ground control points, which are globally available, can be derived from the SAR satellite TerraSAR-X. This opens up many new applications like for example the precise aerial image orientation. In this paper, we propose a method for precise aerial image orientation using spaceborne geodetic Synthetic Aperture Radar Ground Control Points (SAR-GCPs). The precisely oriented aerial imagery can then be used e.g. for mapping of urban landmarks, which support the ego-positioning of autonomous cars. The method for precise image orientation was validated based on two aerial image data sets. SAR-GCPs were measured in images, then the image orientation has been improved by a bundle-adjustment. Results based on check points show, that the accuracy of the image orientation is better than 5 cm in X and Y coordinates.
Highlights
Ground Control Points from the SAR Satellite TerraSAR-X data have an absolute coordinate accuracy which is comparable to GNSS in-situ measurements
We propose a method for precise aerial image orientation using spaceborne geodetic Synthetic Aperture Radar Ground Control Points (SAR-GCPs)
Base of the validation are the image orientations, which have been improved by a self-calibrating bundle adjustment using SAR-GCPs
Summary
Ground Control Points from the SAR Satellite TerraSAR-X data have an absolute coordinate accuracy which is comparable to GNSS in-situ measurements. With this new technology, it is no longer necessary to be on-site to obtain high precision ground information. The assignment in the airborne imagery allows the absolute geo-referencing of the airborne imagery up to the accuracy of one pixel Using such precisely georeferenced images landmarks suitable for the relative orientation and location of a car may be detected and provided to the autonomous cars in the context of a so called “HD-Map” (Runge et al, 2016, Runge et al, 2018, Richter et al, 2016). Useful landmarks for autonomous driving are for example poles of traffic lights or traffic signs, road markings, trunks of trees or corners of buildings
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