多径传播
计算机科学
多输入多输出
雷达
人工神经网络
连续波雷达
雷达成像
人工智能
电子工程
实时计算
电信
工程类
频道(广播)
作者
Ruoyu Feng,Eddy De Greef,Maxim Rykunov,Hichem Sahli,Sofie Pollin,André Bourdoux
标识
DOI:10.1109/radarconf2248738.2022.9764274
摘要
Multipath is a significant challenge for indoor multiple-input-multiple-output (MIMO) radar applications. It generates the so-called ‘ghosts' in the radar detection, which represent the objects that do not exist. Targets and ghosts are very similar, which makes them difficult to be recognized without prior knowledge of the environment geometry. In this work, a multi-path model for the indoor scenario is analyzed for a frequency-modulated continuous-wave (FMCW) MIMO radar. Based on the multipath model, spatial signals from the MIMO virtual channels are fed to a deep neural network that is proposed to classify the multipath ghost, combined with a linear pattern recognition algorithm from our previous work. Simulation and experimental results demonstrate the performance of the proposed solution.
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