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.

Highlights

  • State-of-the-art radio frequency identification (RFID)-based indoor autonomous vehicles localization methods are mostly based on received signal strength indicator (RSSI) measurements

  • Since the phase difference of arrival (PDOA) ranging method is affected by multipath propagation, this paper proposed an algorithm to mitigate this effect

  • The UHF RFID tags were placed in this area with a square grid layout

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Summary

Introduction

A considerable amount of robots have been used in the industrial field. The backscatter signal has three dimensions, which are the signal strength, signal phase, and signal frequency Using these three features of the backscatter signal, the position of RFID tags or reader antennas is obtained by localization algorithms. Ranging-based UHF RFID localization algorithms are made up of the received signal strength indicator (RSSI) [3], the phase difference of arrival (PDOA) [4], and the angle of arrival (AOA) [5]. A novel RFID-based indoor mobile robots localization and navigation system is presented. The RFID reader is mounted on the mobile robot and obtains the position of the robot by dual-frequency PDOA ranging. This system needs a much lower tag deployment density, which can reduce the tag reading collision.

Related Works
Autonomous Vehicle Movement Model
Autonomous Vehicle Localization Problem
UHF RFID Channel Model
G 2 λ4 X 2 M
Localization and Tracking Algorithm
Simulation Configuration
Performance of Tracking with Different Trajectories
Performance of Tracking with Different Numbers of Tags
Comparison With an RSSI Ranging Method
Conclusions
Full Text
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