@article{ref1,
title="Enhanced heuristic drift elimination with adaptive zero-velocity detection and heading correction algorithms for pedestrian navigation",
journal="Sensors (Basel)",
year="2020",
author="Zhu, Ruihui and Wang, Yunjia and Yu, Baoguo and Gan, Xingli and Jia, Haonan and Wang, Boyuan",
volume="20",
number="4",
pages="e951-e951",
abstract="As pedestrian dead-reckoning (PDR), based on foot-mounted inertial sensors, suffers from accumulated error in velocity and heading, an improved heuristic drift elimination (iHDE) with a zero-velocity update (ZUPT) algorithm was proposed for simultaneously reducing the error in heading and velocity in complex paths, i.e., with pathways oriented at 45°, curved corridors, and wide areas. However, the iHDE algorithm does not consider the changes in pedestrian movement modes, and it can deteriorate when a pedestrian walks along a straight path without a pre-defined dominant direction. To solve these two problems, we propose enhanced heuristic drift elimination (eHDE) with an adaptive zero-velocity update (AZUPT) algorithm and novel heading correction algorithm. The relationships between the magnitude peaks of the <i>y</i>-axis angular rate and the detection thresholds were established only using the readings of the three-axis accelerometer and the three-axis gyroscopic, and a mechanism for constructing temporary dominant directions in real time was introduced. Real experiments were performed and the results showed that the proposed algorithm can improve the still-phase detection accuracy of a pedestrian at different movement motions and outperforms the iHDE algorithm in complex paths with many straight features.<p /> <p>Language: en</p>",
language="en",
issn="1424-8220",
doi="10.3390/s20040951",
url="http://dx.doi.org/10.3390/s20040951"
}