Non-Line-of-Sight Targets Localization Algorithm via Joint Estimation of DoD and DoA
Zhihao Zhu, Shisheng Guo, Jiahui Chen, Shucheng Xue, Zihan Xu, Peilun Wu, Guolong Cui, Lingjiang Kong
Abstract
Non-line-of-sight (NLOS) radar has the feature of detecting the targets which are in the blind area, while the existing time-of-arrival (ToA)-based methods limit its further development in multi-target environments. To deal with it, we investigate the problem of multiple targets localization behind L-shaped corner for multiple-input-multiple-output (MIMO) millimeter wave (MMW) radar. Specifically, the multipath signal model that accounts for range, Doppler, direction of departure (DoD) and direction of arrival (DoA) is established first. After echo preprocessing, the position of the reflector wall is estimated using static point clouds. To achieve multiple NLOS targets localization with low false alarm, a multipath recognition method, by fully considering the DoD and DoA relationships of multipaths, is proposed. Furthermore, the real target positions are derived by mirror symmetry. Finally, the performance of the method is tested by the experiments, which reveal that the proposed method can work in the presence of multiple NLOS targets with high accuracy and low false alarm.