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Differentiable SAR Renderer and Image-Based Target Reconstruction.

Authors :
Fu, Shilei
Xu, Feng
Source :
IEEE Transactions on Image Processing; 2022, Vol. 31, p6679-6693, 15p
Publication Year :
2022

Abstract

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 the 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 at inverse graphics for SAR imagery. A differentiable SAR renderer (DSR) is developed, which reformulates the mapping and projection algorithm of the 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 synthesized data or real measured inverse SAR (ISAR) data by ground radar. Results demonstrate the efficacy of the proposed DSR and its inverse approach. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
10577149
Volume :
31
Database :
Complementary Index
Journal :
IEEE Transactions on Image Processing
Publication Type :
Academic Journal
Accession number :
170077398
Full Text :
https://doi.org/10.1109/TIP.2022.3215069