Multipath Imaging for NLOS Targets Behind an L-Shaped Corner With Single-Channel UWB Radar
Quan Tang, Jun Li, Lingyu Wang, Yong Jia, Guolong Cui
Abstract
Non-line-of-sight (NLOS) detection is widely encountered in military and civilian fields, such as urban battles and disaster rescues. In this study, a novel multipath imaging approach is proposed to solve the problem of multi-target localization behind an L-shaped corner for a single-channel ultra-wide-band (UWB) radar. Specifically, a multipath propagation model based on an L-shaped corner is established, and the positions of virtual radars are analyzed by the specular reflection feature of electromagnetic wave, which forms a virtual array aperture to achieve enough image resolution. Then, the radar echo is mapped based on each propagation path to form multiple images. Finally, according to the trajectory distribution in each image, the incoherent addition is exploited to fuse the multiple images to focus on the target locations. Simulation and experimental results demonstrate that the estimated target positions are consistent with the actual target locations, and the proposed multipath imaging algorithm is applicable in the case of partial path loss.