Extension of Differentiable SAR Renderer for Ground Target Reconstruction From Multiview Images and Shadows

Three-dimensional (3-D) reconstruction of complex targets on the ground from multiview synthetic aperture radar (SAR) images is of great interests. The inherently integrated forward-inverse architecture of the differentiable SAR renderer (DSR) provides a promising solution to the general inverse pro...

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Bibliographic Details
Published in:IEEE transactions on geoscience and remote sensing 2023, Vol.61, p.1-13
Main Authors: Fu, Shilei, Jia, Hecheng, Pu, Xinyang, Xu, Feng
Format: Article
Language:English
Subjects:
Algorithms
Differentiable SAR renderer (DSR)
Finite element method
Geometry
image and shadow
Image reconstruction
Inverse problems
Radar
Radar imaging
Radar polarimetry
Renderers
SAR (radar)
Scattering
Shadows
Synthetic aperture radar
synthetic aperture radar (SAR)
target reconstruction
Three-dimensional displays
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Summary:Three-dimensional (3-D) reconstruction of complex targets on the ground from multiview synthetic aperture radar (SAR) images is of great interests. The inherently integrated forward-inverse architecture of the differentiable SAR renderer (DSR) provides a promising solution to the general inverse problem of SAR target reconstruction. In this context, the target's shadow provides complementary information to its scattering image. Hence, this article proposes a novel DSR-based target reconstruction approach using both the target image and its shadows. The capabilities of DSR are extended to generate not only target scattering images but also shadows. Furthermore, the gradients of the outputs, specifically illumination map and shadow map, with respect to the inputs, i.e., target geometry represented as a mesh, are derived. This enables us to develop a gradient-descent inverse approach for solving the general reconstruction problem. Extensive simulations and quantitative evaluations demonstrate that incorporating both the target scattering image and its shadows significantly improves the reconstruction performance. Moreover, our analyses indicate that achieving optimal reconstruction effects requires a minimum of nine views with a relatively even distribution. Finally, the proposed algorithm is validated using real SAR images of vehicle targets.
ISSN:0196-2892
1558-0644
DOI:10.1109/TGRS.2023.3320515