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Indoor Localization Based on CFR Environment Awareness

机译:基于CFR环境认识的室内定位

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摘要

Accurate amplitude information provides the possibility for indoor localization, it is easy to acquire and does not require complex corrections like phase. However, the amplitude information is sensitive to the environment, which reduces the localization accuracy. This paper proposes an indoor localization method based on environment awareness. First, using the variance of phase difference to judge whether there is anyone walking in the environment. Second, we create amplitude images as the input to Convolution Neural Network without the person walking to train localization model in the offline. Third, online localization using localization model.
机译:精确的幅度信息提供了室内定位的可能性,易于获取,并且不需要类似相位的复杂校正。然而,幅度信息对环境敏感,这降低了本地化精度。本文提出了一种基于环境意识的室内定位方法。首先,使用相位差的方差来判断是否有人在环境中行走。其次,我们创建幅度图像作为卷积神经网络的输入,如果没有人在离线中培训到培训本地化模型的人。第三,使用本地化模型的在线本地化。

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