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• W2564767511 startingPage "2127" @default.
• W2564767511 abstract "The Kalman filter is an optimal estimator with numerous applications in technology, especially in systems with Gaussian distributed noise. Moreover, the adaptive Kalman filtering algorithms, based on the Kalman filter, can control the influence of dynamic model errors. In contrast to the adaptive Kalman filtering algorithms, the H-infinity filter is able to address the interference of the stochastic model by minimization of the worst-case estimation error. In this paper, a novel adaptive H-infinity filtering algorithm, which integrates the adaptive Kalman filter and the H-infinity filter in order to perform a comprehensive filtering algorithm, is presented. In the proposed algorithm, a robust estimation method is employed to control the influence of outliers. In order to verify the proposed algorithm, experiments with real data of the Global Positioning System (GPS) and Inertial Navigation System (INS) integrated navigation, were conducted. The experimental results have shown that the proposed algorithm has multiple advantages compared to the other filtering algorithms." @default.
• W2564767511 created "2017-01-06" @default.
• W2564767511 creator A5005517878 @default.
• W2564767511 creator A5035478113 @default.
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• W2564767511 date "2016-12-19" @default.
• W2564767511 modified "2023-09-30" @default.
• W2564767511 title "A New Adaptive H-Infinity Filtering Algorithm for the GPS/INS Integrated Navigation" @default.
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• W2564767511 doi "https://doi.org/10.3390/s16122127" @default.
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• W2564767511 hasPublicationYear "2016" @default.
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