ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences
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Articles | Volume IV-2/W7
https://doi.org/10.5194/isprs-annals-IV-2-W7-129-2019
https://doi.org/10.5194/isprs-annals-IV-2-W7-129-2019
16 Sep 2019
 | 16 Sep 2019

ULTRA-HIGH RESOLUTION IMAGING OF FACADES AND VERTICAL INFRASTRUCTURE BY CARBORNE SAR AND AIRBORNE CSAR

S. Palm, R. Sommer, A. Tessmann, and U. Stilla

Keywords: Ultra-high Resolution SAR, Carborne SAR, Airborne CSAR, Facade Mapping, Vertical Infrastructure Mapping, Mobile Radar Mapping

Abstract. In this paper we propose a strategy to focus ultra-high resolution single channel carborne SAR and airborne circular SAR (CSAR) data to image facades and vertical infrastructure. We illustrate the related theoretical background and the design of an optimal focusing geometry for carborne SAR applications while using backprojection focusing techniques. Of particular interest is thereby the determination of the minimum distance and orientation of the facade to the radar sensor. Potential image distortions due to a wrong choice of these parameters are illustrated. Effects on the final resolution of the data due to the rotation of the focusing geometry compared to typical airborne SAR are discussed. We validated the strategy by driving on conventional roads illuminating facades with an experimental mobile radar mapping (MRM) sensor operating at 300 GHz. We further present an adapted version of the proposed strategy to focus vertical infrastructure in CSAR data sets. By extracting the center coordinate and the principal orientation of an object from GiS data, the focusing plane is designed arbitrarily in the 3D space. For the CSAR data set, a radar sensor particularly designed for circular flight trajectories operating at 94 GHz was evaluated. An electrical pylon was chosen as potential target. In both applications, the final images show a high level of detail. The combination of proposed strategy and radar sensor with very high bandwidth is capable of subcentimeter imaging of facades. The height, shape and dimensions of objects can be extracted directly from the image geometry at very high accuracy.