SAR Tomography of Urban Areas: 3D Regularized Inversion in the Scene Geometry

Starting from a stack of co-registered SAR images in interferometric configuration, SAR tomography performs a reconstruction of the reflectivity of scatterers in 3-D. Scatterers seen within the same resolution cell in each SAR image can be separated by jointly unmixing the SAR complex amplitude observed throughout the stack. In urban areas, Compress Sensing (CS) approaches have been applied to achieve super-resolution in the estimation of the position of the scatterers. However, even if all the local information coming from a stack at a given pixel is used, the structural information that is inherent to the image is not directly used to improve the rendering of the scene. This paper addresses the problem of adding structural constraints to sparse tomographic reconstructions of urban areas. We derive an algorithm allowing the inversion of tomographic data under structural constraints and illustrate its performances on a stack of Spotlight TerraSAR-X images.