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Abstract
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Article Information:
RBUKF Sensor Data Fusion for Localization of Unmanned Mobile Platform
Longmei Zhao, Panlong Wu and Hongjun Cao
Corresponding Author: Panlong Wu
Submitted: January 22, 2013
Accepted: March 02, 2013
Published: October 10, 2013 |
Abstract:
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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.
Key words: Data fusion, EKF, localization, RBUKF, sensor, UKF,
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Cite this Reference:
Longmei Zhao, Panlong Wu and Hongjun Cao, . RBUKF Sensor Data Fusion for Localization of Unmanned Mobile Platform. Research Journal of Applied Sciences, Engineering and Technology, (18): 3462-3468.
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ISSN (Online): 2040-7467
ISSN (Print): 2040-7459 |
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