Cheng Shuyan, Wang Shujun, Guan Wenbai, Xu He, Li Peng
School of Computer Science, Nanjing University of Posts and Telecommunications, Nanjing 210023, China.
Jiangsu High Technology Research Key Laboratory for Wireless Sensor Networks, Nanjing 210003, China.
Sensors (Basel). 2020 May 11;20(9):2731. doi: 10.3390/s20092731.
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.
作为物联网的核心支撑技术，射频识别（RFID）技术在智能交通、物流管理、工业自动化等领域迅速普及，因其具备快速高效的数据采集能力而具有巨大的发展潜力。RFID技术在室内定位领域有着广泛应用，其中三维定位能够获取更为真实、具体的目标位置信息。针对现有的基于RFID的三维定位方案，本文提出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场景。实验结果表明，该方法具有更高的定位精度和更好的系统稳定性。
