Indoor Heading Direction Estimation Using Rf Signals
Yusen Fan, Feng Zhang, Chenshu Wu, Beibei Wang, K. J. Ray Liu
Abstract
Heading direction information is crucial to many ubiquitous computing applications. The main stream has been resorting to inertial sensors, such as accelerometer, gyroscope and magnetometer, which suffer from severe accumulative errors or large degradations indoors. In this paper, we utilize the radio frequency (RF) signals, received from the commercial off-the-shelf (COTS) WiFi devices, to accurately estimate the heading direction in indoor environments. Based on the time- reversal (TR) technique, we make use of the channel state information (CSI) and the geometry of the antenna array to design the proposed algorithm. A prototype is built using a single access point (AP), without knowing its location, and a two dimensional (2D) antenna array to validate the proposed method. Experiments, conducted in strong non-line-of-sight (NLOS) scenarios with rich multipaths indoors, have shown that the median error for heading direction estimation is 6.9°, which surpasses the inertial sensors. With the high accuracy and low cost, it illustrates the proposed system as a promising solution to large varieties of applications that require accurate heading direction information.
BibTeX
@inproceedings{icassp2020_indoorheadingdir,
title = {Indoor Heading Direction Estimation Using Rf Signals},
author = {Yusen Fan and Feng Zhang and Chenshu Wu and Beibei Wang and K. J. Ray Liu},
booktitle = {ICASSP 2020},
year = {2020}
}