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Airborne circular W-band SAR for multiple aspect urban site monitoring

: Palm, Stephan; Sommer, Rainer; Janssen, Daniel; Tessmann, Axel; Stilla, U.


IEEE transactions on geoscience and remote sensing 57 (2019), Nr.9, S.6996-7016
ISSN: 0196-2892
ISSN: 0018-9413
Fraunhofer IAF ()
Fraunhofer FHR ()
airborne circular synthetic aperture radar (CSAR); full aspect image analysis; millimeter-wave radar; nonplanar targets; radar signal processing; shadow tracking; video SAR

This paper presents a strategy for urban site monitoring by very high-resolution circular synthetic aperture radar (CSAR) imaging of multiple aspects. We analytically derive the limits of coherent azimuth processing for nonplanar objects in CSAR if no digital surface model (DSM) is available. The result indicates the level of maximum achievable resolution of these objects in this geometry. The difficulty of constantly illuminating a specific scene in full aspect mode (360°) for such small wavelengths is solved by a hardware- and software-side integration of the radar in a mechanical tracking mode. This results in the first demonstration of full aspect airborne subaperture CSAR images collected with an active frequency-modulated continuous wave (FMCW) radar at W-band. We describe the geometry and the implementation of the real-time beam-steering mode and evaluate resulting effects in the CSAR processing chain. The physical properties in W-band allow the use of extremely short subapertures in length while generating high azimuthal bandwidths. We use this feature to generate full aspect image stacks for CSAR video monitoring in very high frame rates. This technique offers the capability of detecting and observing moving objects in single channel data by shadow tracking. Due to the relatively strong echo of roads, the shadows of moving cars are rich in contrast. The image stack is further evaluated to present wide angular anisotropic properties of targets and first results on multiple aspect image fusion. Both topics show huge potential for further investigations in terms of image analysis and scene classification.