Multiple Targets Localization Behind L-Shaped Corner via UWB Radar
Multiple Targets Localization Behind L-Shaped Corner via UWB Radar
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DOI：
10.1109/tvt.2021.3068266
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发表时间：
2021-03
影响因子：
6.8
通讯作者：
Songlin Li;Shisheng Guo;Jiahui Chen;X. Yang;Shihao Fan;Chao Jia;G. Cui;Haining Yang
中科院分区：
文献类型：
--
作者：
Songlin Li;Shisheng Guo;Jiahui Chen;X. Yang;Shihao Fan;Chao Jia;G. Cui;Haining Yang
研究了多通道超宽带（UWB）成像雷达非视距（NLOS）信号处理的多目标定位问题。针对复杂多径鬼信号下L形拐角场景下多目标位置估计问题，提出了一种基于匹配的雷达成像新算法。首先建立了多目标环境下的多径传播模型。然后从雷达图像中提取实际多径鬼点的位置，并得到与这些多径鬼点相对应的候选目标。其次，椭圆交叉定位的方法来获得候选多径鬼的位置，其次是两个定义的匹配因子来衡量实际和候选多径鬼之间的相似性。根据相似度设计决策规则，确定实际目标。与基于一维距离像的定位算法相比，该算法能有效地处理多目标情况，即使在粗糙壁和噪声的情况下也能有效地处理多目标情况。最后，通过仿真和实验数据验证了该算法的有效性.
This paper deals with the multiple targets localization problem via multi-channel ultra-wideband (UWB) imaging radar non-line-of-sight (NLOS) signal processing. A novel matching-based radar imaging algorithm is proposed to obtain the positions of multiple targets in the L-shaped corner scenario with complex multipath ghost signals. Firstly, a multipath propagation model for the multiple targets scenario is established. Then the positions of the actual multipath ghosts are extracted from the radar image, and the candidate targets corresponding to these multipath ghosts are derived. Secondly, the ellipse-cross-localization method is proposed to obtain the positions of the candidate multipath ghosts, followed by two defined matching factors to measure the similarity between actual and candidate multipath ghosts. According to the similarity, decision rules are designed to determine the actual targets. Compared with the localization algorithm based on one-dimensional range profile, the proposed algorithm can effectively cope with the cases of multiple targets, even in the cases of rough walls and noise. Finally, simulations and experimental data are used to validate the effectiveness of the proposed algorithm.