Proceedings of the 2nd Annual International Conference on Electronics, Electrical Engineering and Information Science (EEEIS 2016)

Unmanned Ground Vehicle Positioning System by GPS/Dead-Reckoning/IMU Sensor Fusion

Authors
Meng Zhang, Ke Liu, Chen Li
Corresponding Author
Meng Zhang
Available Online December 2016.
DOI
10.2991/eeeis-16.2017.91How to use a DOI?
Keywords
Unmanned Vehicle; Kalman Filter; GPS/IMU; DR.
Abstract

Real-time positioning system is critical for control and navigation of unmanned ground vehicles. In this paper, we present a low-cost integrated GPS/DR/IMU positioning solution. A two-level adaptive Kalman Filter based algorithm is introduced to fuse sensor signals. Experimental results demonstrate a much better performance with accurate and robustness output even during short-time GPS signal drop-out.

Copyright
© 2017, the Authors. Published by Atlantis Press.
Open Access
This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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Volume Title
Proceedings of the 2nd Annual International Conference on Electronics, Electrical Engineering and Information Science (EEEIS 2016)
Series
Advances in Engineering Research
Publication Date
December 2016
ISBN
10.2991/eeeis-16.2017.91
ISSN
2352-5401
DOI
10.2991/eeeis-16.2017.91How to use a DOI?
Copyright
© 2017, the Authors. Published by Atlantis Press.
Open Access
This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

Cite this article

TY  - CONF
AU  - Meng Zhang
AU  - Ke Liu
AU  - Chen Li
PY  - 2016/12
DA  - 2016/12
TI  - Unmanned Ground Vehicle Positioning System by GPS/Dead-Reckoning/IMU Sensor Fusion
BT  - Proceedings of the 2nd Annual International Conference on Electronics, Electrical Engineering and Information Science (EEEIS 2016)
PB  - Atlantis Press
SP  - 737
EP  - 747
SN  - 2352-5401
UR  - https://doi.org/10.2991/eeeis-16.2017.91
DO  - 10.2991/eeeis-16.2017.91
ID  - Zhang2016/12
ER  -