Volume XL-3/W2
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XL-3/W2, 149-154, 2015
https://doi.org/10.5194/isprsarchives-XL-3-W2-149-2015
© Author(s) 2015. This work is distributed under
the Creative Commons Attribution 3.0 License.
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XL-3/W2, 149-154, 2015
https://doi.org/10.5194/isprsarchives-XL-3-W2-149-2015
© Author(s) 2015. This work is distributed under
the Creative Commons Attribution 3.0 License.

  10 Mar 2015

10 Mar 2015

CHALLENGES AND POTENTIALS USING MULTI ASPECT COVERAGE OF URBAN SCENES BY AIRBORNE SAR ON CIRCULAR TRAJECTORIES

S. Palm, N. Pohl, and U. Stilla S. Palm et al.
  • Fraunhofer FHR, Institute for High Frequency Physics and Radar Techniques, 53343 Wachtberg, Germany
  • Institute for Photogrammetry, Technische Universitaet Muenchen, Muenchen, Germany

Keywords: Airborne Circular Synthetic Aperture Radar, UAV, Urban Scenario, FMCW SAR, Multi Aspect Microwave Imaging

Abstract. Airborne SAR on small and flexible platforms guarantees the evaluation of local damages after natural disasters and is both weather and daylight independent. The processing of circular flight trajectories can further improve the reconstruction of target scenes especially in complex urban scenarios as shadowing and foreshortening effects can be reduced by multiple views from different aspect angles (hyper- or full- aspect). A dataset collected with the Miranda 35 GHz radar system with 1 GHz bandwidth on a small ultralight aircraft on a circular trajectory over an urban scene was processed using a time domain approach. The SAR processing chain and the effects of the navigational data for such highly nonlinear trajectories and unstable platforms are described. The generated SAR image stack over the entire trajectory consists of 240 individual SAR images, each image visualizing the scene from a slightly different aspect angle. First results for the fusion of multiple aspect views to create one resulting image with reduced shadow areas and the possibility to find hidden targets are demonstrated. Further potentials of such particular datasets like moving target indication are discussed.