Stochastic Integration H∞ Filter for Rapid Transfer Alignment of INS
1
School of Instrumentation Science and Opto-Electronics Engineering, Beihang University, Beijing 100191, China
2
Science and Technology on Aircraft Control Laboratory, Beihang University, Beijing 100191, China
3
School of Automation Science and Electrical Engineering, Beihang University, Beijing 100191, China
*
Author to whom correspondence should be addressed.
Sensors 2017, 17(11), 2670; https://doi.org/10.3390/s17112670
Received: 21 September 2017
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Revised: 11 November 2017
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Accepted: 15 November 2017
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Published: 18 November 2017
(This article belongs to the Special Issue Inertial Sensors for Positioning and Navigation)
The performance of an inertial navigation system (INS) operated on a moving base greatly depends on the accuracy of rapid transfer alignment (RTA). However, in practice, the coexistence of large initial attitude errors and uncertain observation noise statistics poses a great challenge for the estimation accuracy of misalignment angles. This study aims to develop a novel robust nonlinear filter, namely the stochastic integration H filter (SIH F) for improving both the accuracy and robustness of RTA. In this new nonlinear H filter, the stochastic spherical-radial integration rule is incorporated with the framework of the derivative-free H filter for the first time, and the resulting SIH F simultaneously attenuates the negative effect in estimations caused by significant nonlinearity and large uncertainty. Comparisons between the SIH F and previously well-known methodologies are carried out by means of numerical simulation and a van test. The results demonstrate that the newly-proposed method outperforms the cubature H filter. Moreover, the SIH F inherits the benefit of the traditional stochastic integration filter, but with more robustness in the presence of uncertainty.
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MDPI and ACS Style
Zhou, D.; Guo, L. Stochastic Integration H∞ Filter for Rapid Transfer Alignment of INS. Sensors 2017, 17, 2670. https://doi.org/10.3390/s17112670
AMA Style
Zhou D, Guo L. Stochastic Integration H∞ Filter for Rapid Transfer Alignment of INS. Sensors. 2017; 17(11):2670. https://doi.org/10.3390/s17112670
Chicago/Turabian StyleZhou, Dapeng, and Lei Guo. 2017. "Stochastic Integration H∞ Filter for Rapid Transfer Alignment of INS" Sensors 17, no. 11: 2670. https://doi.org/10.3390/s17112670
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