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Multiple Targets Localization Behind L-Shaped Corner via UWB Radar

机译:通过UWB雷达将L形角落的多个目标定位

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摘要

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.
机译:本文通过多通道超宽带(UWB)成像雷达非视线(NLOS)信号处理来处理多个目标定位问题。提出了一种基于匹配的基于匹配的雷达成像算法,以获得具有复杂多径鬼信号的L形角场景中的多个目标的位置。首先,建立了多目标场景的多径传播模型。然后从雷达图像中提取实际多径鬼的位置,并导出对应于这些多径鬼的候选目标。其次,提出了椭圆形交叉定位方法以获得候选多径鬼的位置,然后是两个定义的匹配因子来测量实际和候选多径鬼之间的相似性。根据相似性,旨在确定实际目标的决策规则。与基于一维范围分布的定位算法相比,即使在粗糙墙壁和噪声的情况下,所提出的算法也可以有效地应对多个目标的情况。最后,使用模拟和实验数据来验证所提出的算法的有效性。

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