Real-time inter-vehicle distance estimation and multi-vehicle detection using FMCW radar with corner reflectors and reflective metal sheets

In this study, we propose a method for estimating inter-vehicle distances to multiple preceding vehicles in blind-spot environments by combining a 24 GHz FMCW radar with passive metal sheets and triangular corner reflectors. The method uses the radiation directivity of the radar, the boundary reflection characteristics of passive metal sheets, and the high radar cross section gain of corner reflectors. Reflected signal characteristics obtained from the transmission angle and discrete Fourier transform are used to detect vehicles that conventional sensors, such as cameras, LiDAR, and millimeter-wave radars, may fail to detect under non-line-of-sight conditions. Experiments were conducted using three vehicles, including the radar-equipped vehicle, while varying the distances of two preceding vehicles and the radar transmission angle. The results showed that the proposed method successfully estimated the distances to multiple preceding vehicles in blind-spot conditions with an error of approximately 0.36 m. These findings indicate that the method can enhance environmental perception for next-generation mobility robots and may contribute to traffic safety by helping prevent chain-reaction collisions caused by operational errors or delayed judgment.