Target shape reconstruction from multi-perspective shadows in drone-borne SAR systems

This paper explores the potentials of multi-perspective shadow features in drone-borne SAR images for the reconstruction of targets' shapes. By exploiting target shadows from multiple viewing angles, a comprehensive understanding of targets' morphology can be obtained. This holds substantial promise in potentially deriving three-dimensional measurements encompassing length, width, and height of the targeted objects. The proposed methodology adopts a decentralized approach, involving the extraction and subsequent combination of information from shadowed areas within individual images. This approach is validated through application to experimental data acquired by means of a 24 GHz INRAS radar-equipped drone-borne SAR system. The outcomes show the capability of diverse illumination angles in capturing distinct characteristics of targets, thereby enabling the extraction of the 3D shapes of man-made objects spanning varying dimensional classes.