Paper Info
Title
Localization And Tracking Of An Indoor Autonomous Vehicle Based On The Phase Difference Of Passive Uhf Rfid Signals
Abstract
State-of-the-art radio frequency identification (RFID)-based indoor autonomous vehicles localization methods are mostly based on received signal strength indicator (RSSI) measurements. However, the accuracy of these methods is not high enough for real-world scenarios. To overcome this problem, a novel dual-frequency phase difference of arrival (PDOA) ranging-based indoor autonomous vehicle localization and tracking scheme was developed. Firstly, the method gets the distance between the RFID reader and the tag by dual-frequency PDOA ranging. Then, a maximum likelihood estimation and semi-definite programming (SDP)-based localization algorithm is utilized to calculate the position of the autonomous vehicles, which can mitigate the multipath ranging error and obtain a more accurate positioning result. Finally, vehicle traveling information and the position achieved by RFID localization are fused with a Kalman filter (KF). The proposed method can work in a low-density tag deployment environment. Simulation experiment results showed that the proposed vehicle localization and tracking method achieves centimeter-level mean tracking accuracy.
Year
DOI
Venue
2021
10.3390/s21093286
SENSORS
Keywords
DocType
Volume
indoor localization, radio frequency identification (RFID), Kalman filter (KF), semi-definite programming (SDP)
Journal
21
Issue
ISSN
Citations 
9
1424-8220
0
PageRank 
References 
Authors
0.34
0
4
Name
Order
Citations
PageRank
Yunlei Zhang141.80
Xiaolin Gong200.68
Kaihua Liu311.71
Shuai Zhang43711.44