Kolloquium Geoinformatik From TomoSAR Point Clouds To Objects

Synthetic aperture radar (SAR) projects a 3-D scene onto two naive coordinates i.e., range and azimuth. In order to fully localize a point in 3-D, advanced interferometric SAR (InSAR) techniques are required that process stack(s) of complex-valued SAR images to retrieve the lost third dimension (i.e., the elevation coordinate). Among other InSAR methods, SAR tomography (TomoSAR) is the most advanced 3-D imaging technique. By exploiting stack(s) of SAR images taken from slightly different positions, it builds up a synthetic aperture in the elevation direction that enables retrieval of precise 3-D position of dominant scatterers within one azimuth-range SAR image pixel. Geocoding these 3-D scatterer positions from SAR geometry to world (UTM) coordinates provide 3-D/4-D point clouds of the illuminated area with point density of around 1 million points/km2. Taking into consideration special characteristics associated to these point clouds e.g., low positioning accuracy, high number of outliers, gaps in the data and rich façade information due to side looking geometry, this presentation will demonstrate the object reconstruction potential of these point clouds using data acquired from both spaceborne and airborne platforms. Experimental results highlighting 3-D reconstruction of two object categories i.e., buildings and individual trees will be presented.
We demonstrate the capabilities of the proposed algorithms on a wide variety of data sets, including a backpack mounted mobile mapping system and a sensor skid for digitizing production lines.