Cooperative Environment Recognition Utilizing UWB Waveforms and CNNs

M. Mäkelä, Jesperi Rantanen, Julian Ilinea, M. Kirkko-Jaakkola, S. Kaasalainen, L. Ruotsalainen
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引用次数: 3

Abstract

Cooperative navigation enhances localization performance and situational awareness in challenging conditions, such as in tactical and first responder operations. In this work we demonstrate how the waveform of the Ultra Wideband (UWB) signal used for ranging in cooperative navigation can also be used to detect the environment surrounding the user of the navigation system. Different environments affect the wave-form in different ways, and thus the received waveform contains features characteristic to the environment around the receiver. We show how the received UWB signal waveform can be used in a Convolutional Neural Network (CNN) in order to determine whether the user is outdoors, indoors or in a forest. The environment is recognized correctly more than 90% of the time.
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基于超宽带波形和cnn的协同环境识别
协同导航增强了具有挑战性条件下的定位性能和态势感知能力,例如战术和第一响应者操作。在这项工作中,我们演示了用于协作导航测距的超宽带(UWB)信号波形如何也可用于检测导航系统用户周围的环境。不同的环境以不同的方式影响波形,因此接收到的波形包含接收器周围环境的特征。我们展示了如何在卷积神经网络(CNN)中使用接收到的超宽带信号波形,以确定用户是在户外、室内还是在森林中。环境识别的正确率超过90%。
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