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Physically Consistent SAR Image Generation for Unseen Aspect Angles via Attributed Scattering Center Evolution

Submitted:

19 May 2026

Posted:

21 May 2026

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Abstract
Synthetic aperture radar (SAR) target images are highly sensitive to aspect angle, while practical data acquisition usually provides only sparse observations over limited viewpoints. This leads to severe data scarcity at unseen aspect angles and makes cross-angle generation prone to scattering-structure distortion and background-statistics mismatch. Existing SAR image generation methods either focus on distribution matching without explicitly modeling target scattering mechanisms, or emphasize angle conditioning while failing to jointly preserve physically plausible scattering-structure evolution and realistic background speckle statistics at unseen views. To address this issue, we propose a physically consistent framework for SAR image generation at unseen aspect angles. The proposed method employs attributed scattering centers as an intermediate physical representation to explicitly model scattering-structure evolution across aspect angles, and uses this evolving representation to guide the generator toward synthesizing SAR images with structurally plausible scattering layouts. In addition, a dual-consistency scheme is introduced to jointly enforce target-region scattering consistency and background-region statistical consistency, thereby improving the physical realism of the generated results from both target and background perspectives. Extensive experiments under strict unseen-angle interpolation and hold-out protocols demonstrate that the proposed method consistently outperforms representative baselines in image fidelity, target-region scattering consistency, background statistical consistency, and angle-condition consistency. Further visualization and ablation studies verify the critical role of attributed scattering-center evolution modeling in physically consistent SAR view completion.
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Copyright: This open access article is published under a Creative Commons CC BY 4.0 license, which permit the free download, distribution, and reuse, provided that the author and preprint are cited in any reuse.
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