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3DLRA: An RFID 3D Indoor Localization Method Based on Deep Learning

机译:3DLRA:一种基于深度学习的RFID 3D室内定位方法

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摘要

As the core supporting technology of the Internet of Things, Radio Frequency Identification (RFID) technology is rapidly popularized in the fields of intelligent transportation, logistics management, industrial automation, and the like, and has great development potential due to its fast and efficient data collection ability. RFID technology is widely used in the field of indoor localization, in which three-dimensional location can obtain more real and specific target location information. Aiming at the existing three-dimensional location scheme based on RFID, this paper proposes a new three-dimensional localization method based on deep learning: combining RFID absolute location with relative location, analyzing the variation characteristics of the received signal strength (RSSI) and Phase, further mining data characteristics by deep learning, and applying the method to the smart library scene. The experimental results show that the method has a higher location accuracy and better system stability.
机译:射频识别(RFID)技术作为物联网的核心支持技术,在智能交通,物流管理,工业自动化等领域迅速普及,其数据快速高效的发展潜力巨大。收集能力。 RFID技术被广泛应用于室内定位领域,其中三维定位可以获取更多真实和特定的目标定位信息。针对现有的基于RFID的三维定位方案,提出了一种基于深度学习的新型三维定位方法:将RFID绝对定位与相对定位相结合,分析接收信号强度(RSSI)和相位的变化特征。 ,通过深度学习进一步挖掘数据特征,并将该方法应用于智能图书馆。实验结果表明,该方法具有较高的定位精度和较好的系统稳定性。

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