A RLS-SVM Aided Fusion Methodology for INS during GPS Outages
AbstractIn order to maintain a relatively high accuracy of navigation performance during global positioning system (GPS) outages, a novel robust least squares support vector machine (LS-SVM)-aided fusion methodology is explored to provide the pseudo-GPS position information for the inertial navigation system (INS). The relationship between the yaw, specific force, velocity, and the position increment is modeled. Rather than share the same weight in the traditional LS-SVM, the proposed algorithm allocates various weights for different data, which makes the system immune to the outliers. Field test data was collected to evaluate the proposed algorithm. The comparison results indicate that the proposed algorithm can effectively provide position corrections for standalone INS during the 300 s GPS outage, which outperforms the traditional LS-SVM method. Historical information is also involved to better represent the vehicle dynamics. View Full-Text
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Yao, Y.; Xu, X. A RLS-SVM Aided Fusion Methodology for INS during GPS Outages. Sensors 2017, 17, 432.
Yao Y, Xu X. A RLS-SVM Aided Fusion Methodology for INS during GPS Outages. Sensors. 2017; 17(3):432.Chicago/Turabian Style
Yao, Yiqing; Xu, Xiaosu. 2017. "A RLS-SVM Aided Fusion Methodology for INS during GPS Outages." Sensors 17, no. 3: 432.
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