Super-Resolution 3D Imaging in GB-ArcSAR via OMP

Ground-based arc synthetic aperture radar (GB-ArcSAR) imaging represents a cutting-edge three-dimensional (3D) imaging technology capable of effectively addressing the layover problems inherent in two-dimensional (2D) imaging and achieving panoramic stereoscopic imaging of observed areas. To overcome the limitation of insufficient elevation resolution in existing GB-ArcSAR 3D imaging methods, this paper proposes a superresolution 3D imaging algorithm based on orthogonal matching pursuit (OMP). The proposed method acquires multi-arrayelement 2D SAR images through circular scanning and employs the OMP algorithm to achieve sparse optimization reconstruction and super-resolution imaging of elevation-direction signals. Furthermore, by incorporating density-based spatial clustering of applications with noise (DBSCAN) for denoising and structural clustering of point cloud results, it effectively realizes 3D reconstruction of scene scattering information. Experimental results with real data demonstrate that the proposed method can provide more accurate 3D imaging outcomes.