Indoor Positioning Algorithm Based on ZigBee and Improved Radio Frequency Identification

Authors

Dahu Yan, Engineering Research Center of Internet of Things Technology Applications Ministry of Education, Wuxi 214122, China;
Yangjie Xu, Engineering Research Center of Internet of Things Technology Applications Ministry of Education, Wuxi 214122, China;

Abstract

Abstract: Since the traditional RFID positioning technology relies on the Internet and is especially constrained by the positioning distance in the process of positioning the tags with poor positioning accuracy, a novel positioning algorithm is proposed based on the ZigBee and improved VIRE algorithm. By using the proposed algorithm, ZigBee nodes are adopted to achieve the formation of network information transmission to replace the traditional wired communication. Gaussian-Kalman filter is used to deal with the sampling data of the limited preselected reference node signal strength. The algorithm adopts signal propagation loss model to calculate the RSSI values of virtual reference tags, so as to be more close to the values of real tags. The Dynamic threshold is employed to predict the positioned tags. Simulation results show that compared with the traditional RFID method, the proposed algorithm performs better in terms of positioning accuracy, which improves working efficiency of the indoor positioning method.

Recommended Citation

Yan, Dahu and Xu, Yangjie (2019) "Indoor Positioning Algorithm Based on ZigBee and Improved Radio Frequency Identification," Journal of System Simulation: Vol. 30: Iss. 11, Article 52.
DOI: 10.16182/j.issn1004731x.joss.201811052
Available at: https://dc-china-simulation.researchcommons.org/journal/vol30/iss11/52

First Page

4484

Revised Date

2018-07-05

DOI Link

https://doi.org/10.16182/j.issn1004731x.joss.201811052

Last Page

4491

CLC

TP391.9

Recommended Citation

Yan Dahu, Xu Yangjie. Indoor Positioning Algorithm Based on ZigBee and Improved Radio Frequency Identification[J]. Journal of System Simulation, 2018, 30(11): 4484-4491.

DOI

10.16182/j.issn1004731x.joss.201811052