Paper Info
Title
An Indoor Localization Method Based on AOA and PDOA Using Virtual Stations in Multipath and NLOS Environments for Passive UHF RFID.
Abstract
Ultra-high frequency radio frequency identification (UHF RFID) localization technique has been considered increasingly promising in indoor positioning systems. However, conventional localization algorithms are vulnerable in multipath and non-line of sight (NLOS) environments. To solve this problem, this paper presents an indoor localization method based on angle of arrival and phase difference of arrival (PDOA) using virtual stations for passive UHF RFID. We use the array antenna to distinguish multipath signals and choose the two strongest paths according to the received signal strength to perform localization. The angles of the two paths are obtained through the phase difference of the received signals at different array elements, and the distances of the two paths are estimated through PDOA measurement. After obtaining the angles and distances, we establish virtual stations to convert NLOS paths into LOS paths. The possible positions of the tag are calculated through virtual stations, angle, and distance information, which are derived from the two signal paths. Then, the weighted least squares combined with residual weighted algorithm are proposed to calculate real position of the tag. Simulation results demonstrate that our method achieves decimeter level accuracy and has higher precision than traditional algorithms.
Year
DOI
Venue
2018
10.1109/ACCESS.2018.2838590
IEEE ACCESS
Keywords
Field
DocType
AOA,PDOA,multipath,NLOS,UHF RFID,virtual stations
Multipath propagation,Non-line-of-sight propagation,Least squares,Residual,Computer science,Angle of arrival,Real-time computing,Signal strength,Radio-frequency identification,Ultra high frequency,Distributed computing
Journal
Volume
ISSN
Citations 
6
2169-3536
1
PageRank 
References 
Authors
0.35
0
6
Name
Order
Citations
PageRank
Yongtao Ma1334.96
Bobo Wang2101.96
Shuyang Pei310.35
Yunlei Zhang441.80
Shuai Zhang56323.35
Jiexiao Yu610.35