Sensor-fusion-based Trajectory Reconstruction for Mobile Devices

Jielei Zhang, Jie Feng, Bingfeng Zhou

2018

Abstract

In this paper, we present a novel sensor-fusion method that reconstructs trajectory of mobile devices from MEMS inertial measurement unit (IMU). In trajectory reconstruction, the position estimation suffers seriously from the errors in the raw MEMS data, e.g. accelerometer signal, especially after its second-order integration over time. To eliminate the influence of the errors, a new error model is proposed for MEMS devices. The error model consists of two components, i.e. noise and bias, corresponding to different types of errors. For the noise component, a low-pass filter with down sampling is applied to reduce the inherent noise in the data. For the bias component, an algorithm is designed to detect the events of movement in a manner of sensor fusion. Then, the denoised data is further calibrated, according to different types of events to remove the bias. We apply our trajectory reconstruction method on a quadrotor drone with low-cost MEMS IMU devices, and experiments show the effectiveness of the method.

Paper Citation

in Harvard Style

Zhang J., Feng J. and Zhou B. (2018). Sensor-fusion-based Trajectory Reconstruction for Mobile Devices. In Proceedings of the 13th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications (VISIGRAPP 2018) - Volume 1: GRAPP; ISBN 978-989-758-287-5, SciTePress, pages 48-58. DOI: 10.5220/0006532900480058

in Bibtex Style

@conference{grapp18,
author={Jielei Zhang and Jie Feng and Bingfeng Zhou},
title={Sensor-fusion-based Trajectory Reconstruction for Mobile Devices},
booktitle={Proceedings of the 13th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications (VISIGRAPP 2018) - Volume 1: GRAPP},
year={2018},
pages={48-58},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0006532900480058},
isbn={978-989-758-287-5},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 13th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications (VISIGRAPP 2018) - Volume 1: GRAPP
TI - Sensor-fusion-based Trajectory Reconstruction for Mobile Devices
SN - 978-989-758-287-5
AU - Zhang J.
AU - Feng J.
AU - Zhou B.
PY - 2018
SP - 48
EP - 58
DO - 10.5220/0006532900480058
PB - SciTePress