Abstract
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.
Highlights
In recent years, with the development and maturity of satellite navigation systems, it is no longer difficult to achieve high-precision outdoor positioning
We propose an Radio Frequency Identification (RFID) three-dimensional indoor positioning scheme based on deep learning
The research status of the RFID positioning technology is descripted in Section 2; the whole system architecture and model is built in Section 3; the whole experiment is described and analyzed in Section 4; our system is compared with other typical RFID positioning methods in Section 5; and the summary of this paper is given in the last section
Summary
With the development and maturity of satellite navigation systems, it is no longer difficult to achieve high-precision outdoor positioning. Radio Frequency Identification (RFID) technology has the advantages of no contact, permanent storage, strong readability, etc Using the unique identification characteristic of the tag to the object, the RFID positioning system obtains the position information of the electronic tag according to the signal sent by the electronic tag received by the reader. While saving costs, it can obtain more authentic and effective target location information. Deep learning is used to mine the characteristics and laws of the data, further obtaining the Z-axis position information of the tag with higher accuracy. The research status of the RFID positioning technology is descripted in Section 2; the whole system architecture and model is built in Section 3; the whole experiment is described and analyzed in Section 4; our system is compared with other typical RFID positioning methods in Section 5; and the summary of this paper is given in the last section
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