Surface models to constrain three-dimensional sparse SAR reconstruction

Sparse data collection geometries represent a significant challenge to high-resolution three-dimensional SAR imaging. In particular, sparse sampling can lead to significant sidelobe structure in high-resolution reconstructions. To help constrain volumetric SAR reconstructions, we have introduced a surface model. We justify this based on physical phenomenology: higher frequency SAR systems exhibit only limited surface penetration. In our method, we jointly estimate the surface models and reconstructions, significantly reducing sidelobing artifacts in comparison with traditional reconstructions. Our paper and presentation illustrate reconstructions both with and without surface models to demonstrate the potential improvement.