Differentiable SAR Renderer and SAR Target Reconstruction
This work addresses the challenge of advanced information retrieval and target reconstruction in SAR imagery for remote sensing applications, representing a novel approach but with incremental integration of differentiable rendering techniques.
The paper tackles the problem of reconstructing 3D targets from synthetic aperture radar (SAR) images by developing a differentiable SAR renderer (DSR) that models wave scattering and imaging mechanisms, enabling gradient-based optimization for inverse reconstruction, with experiments on simulated and real ISAR data showing its efficacy.
Forward modeling of wave scattering and radar imaging mechanisms is the key to information extraction from synthetic aperture radar (SAR) images. Like inverse graphics in optical domain, an inherently-integrated forward-inverse approach would be promising for SAR advanced information retrieval and target reconstruction. This paper presents such an attempt to the inverse graphics for SAR imagery. A differentiable SAR renderer (DSR) is developed which reformulates the mapping and projection algorithm of SAR imaging mechanism in the differentiable form of probability maps. First-order gradients of the proposed DSR are then analytically derived which can be back-propagated from rendered image/silhouette to the target geometry and scattering attributes. A 3D inverse target reconstruction algorithm from SAR images is devised. Several simulation and reconstruction experiments are conducted, including targets with and without background, using both synthesized data or real measured inverse SAR (ISAR) data by ground radar. Results demonstrate the efficacy of the proposed DSR and its inverse approach.