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RF-Based Indoor Moving Direction Estimation Using a Single Access Point

delete2022-01-01
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PRE
AI
Y
Yusen Fan
F
Feng Zhang
C
Chenshu Wu
B
Beibei Wang *
K
K. J. Ray Liu
DOI:10.1109/JIOT.2021.3083669delete
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Abstract

Abstract

En 中文
Indoor moving direction and rotation angle measurements are crucial to many ubiquitous mobile computing applications. Most of the state-of-the-art approaches rely on inertial sensors, e.g., accelerometers, gyroscopes, and magnetometers, which suffer from severe accumulative errors or accuracy degradation indoors. This article presents an RF-based direction estimation method, which utilizes the off-the-shelf commodity WiFi devices for accurate moving direction and in-place rotation angle estimation. The proposed approach employs a novel 2-D antenna array and leverages the spatial decay property of the time-reversal resonating strength. First, the moving speeds along different directions, specified by the 2-D array, are derived using virtual antenna alignment. The precise estimation of the device's moving direction is then achieved by combining the obtained velocity information and the a prior knowledge of the array's geometry layout. Experiments in a multipath-rich indoor environment have shown that the median error for moving direction estimation is 6.9 degrees, which outperforms the accelerometer counterpart. The results also verify the good accuracy of in-place rotation angle estimation without any accumulative error, which beats the gyroscope in long-term tests. Because the proposed approach can achieve high accuracy without accumulative drifts, it is a promising candidate solution to applications that require accurate direction information.
Keywords:
Antenna arrays
Estimation
Antenna measurements
Gyroscopes
Directive antennas
Rotation measurement
Accelerometers
2-D antenna array
direction finding
time reversal
virtual antenna alignment (VAA)
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Journal

IEEE Internet of Things Journal cover
IEEE Internet of Things Journal
IF:
8.9
Papers:
1.4W
Citations:
7.8W

Organization

University System of Maryland cover
University System of Maryland
Scholars:
6.4W
Papers: 5.6W
Citations: 113