Aimed at the problems of severe layover, interferometric phase aliasing and phase jumps caused by dense urban features, which lead to difficulties in phase unwrapping and insufficient automation and intelligence in building areas under complex scenes, this paper proposes a phase reconstruction and unwrapping method for interferometric synthetic aperture radar (InSAR) building layover areas in complex scenarios integrated with YOLOv11. Based on a self-constructed dedicated dataset, the YOLOv11 object detection network is trained to identify and locate building layover areas in synthetic aperture radar (SAR) images and extract their original interferometric phases. On this basis, by integrating the building facade interferometry model and the interferometric phase gradient model, regions dominated by facade scattering are effectively identified, and their interferometric phases are reconstructed to reduce scattering interference from non-relevant areas. Finally, the reconstructed phase is unwrapped using a quality-guided phase unwrapping method. Experimental results demonstrate that the proposed method can automatically and intelligently achieve phase unwrapping in building areas under complex scenes, providing reliable technical support for urban deformation monitoring and 3D reconstruction.