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

3-D building layout sensing is a key capability for internet of things (IoT)-enabled smart city applications, including postdisaster assessment and urban security monitoring. However, acquiring reliable 3-D building layouts from an external perspective remains challenging in complex urban environments due to severe signal attenuation and multipath effects. This article proposes an IoT-enabled unmanned aerial vehicle (UAV)-based through-the-wall radar (TWR) sensing framework for large-scale 3-D building layout reconstruction. In the proposed framework, UAV-mounted radar sensors act as mobile IoT sensing nodes to collect multiview sensing data. A multilayer wall echo propagation model and an angle-weighted 3-D back-projection (BP) imaging algorithm are employed to generate multiview 3-D synthetic aperture radar (SAR) representations. An enhanced U-Net architecture is then developed to fuse the multiview SAR data and reconstruct clearer 3-D 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.