Enhanced Velocity Extraction of Moving Subject Using Through-Wall-Imaging Radar

Detecting human movement through walls is vital for disaster response and security, where obstacles obscure visibility and endanger rescue operations, necessitating advanced through-wall radar (TWR) solutions. This study introduces a novel method to enhance velocity estimation accuracy in TWR systems despite signal attenuation caused by walls. Our proposed method dynamically adjusts the beamforming range based on radar-target distance, improving point cloud reconstruction and enabling precise velocity measurements. We conducted experiments in 1D and 2D indoor environments, with and without a brick wall, to validate the proposed method’s effectiveness. In both 1D and 2D experiments, the proposed method successfully restored the velocity information of five subjects located behind a brick wall, achieving root mean square error (RMSE) values of approximately 0.1–0.2 m/s in most cases. Furthermore, statistical comparisons before and after applying the proposed method in the brick wall environment revealed significant reductions in RMSE (p < 0.05) and significant increases in the number of detected point clouds (p < 0.05), confirming the method’s effectiveness in enhancing both velocity extraction accuracy and detection capability.