Research Article | OPEN ACCESS
RBUKF Sensor Data Fusion for Localization of Unmanned Mobile Platform
Longmei Zhao, Panlong Wu and Hongjun Cao
School of Automation, Nanjing University of Science and Technology, Nanjing, 210094, P.R. China
Research Journal of Applied Sciences, Engineering and Technology 2013 18:3462-3468
Received: January 22, 2013 | Accepted: March 02, 2013 | Published: October 10, 2013
Abstract
Due to the limited localization precision of single sensor, a sensor data fusion is introduced based on Rao-Blackwellization Unscented Kalman Filter (RBUKF) that fuses the sensor data of a GPS receiver, one gyro and one compass. RBUKF algorithm is compared with that of Extended Kalman Filter (EKF) and Unscented Kalman Filter (UKF) in this study. The experimental results show that the RBUKF algorithm can more effectively improve tracking accuracy and reduce computational complexity than the other algorithms and has practical significance.
Keywords:
Data fusion, EKF, localization, RBUKF, sensor, UKF,
Competing interests
The authors have no competing interests.
Open Access Policy
This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made.
Copyright
The authors have no competing interests.
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ISSN (Online): 2040-7467
ISSN (Print): 2040-7459 |
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