UAV-Based Through-the-Wall Radar Sensing for 3-D Urban Building Layout Reconstruction Using an Enhanced U-Net

Three-dimensional (3D) building layout sensing is a key capability for Internet of Things (IoT)–enabled smart city applications, including post-disaster assessment and urban security monitoring. However, acquiring reliable 3D building layouts from an external perspective remains challenging in complex urban environments due to severe signal attenuation and multipath effects. This paper proposes an IoT-enabled unmanned aerial vehicle (UAV)–based through-the-wall radar (TWR) sensing framework for large-scale 3D building layout reconstruction. In the proposed framework, UAV-mounted radar sensors act as mobile IoT sensing nodes to collect multi-view sensing data. A multi-layer wall echo propagation model and an angle-weighted three-dimensional back-projection (BP) imaging algorithm are employed to generate multi-view 3D synthetic aperture radar (SAR) representations. An enhanced U-Net architecture is then developed to fuse the multi-view SAR data and reconstruct clearer 3D building layout representations. The simulation and real-world experimental results show that the proposed framework achieves improved reconstruction performance over representative existing methods under the tested conditions, indicating its potential for IoT-oriented smart city sensing.