Stochastic Integration H∞ Filter for Rapid Transfer Alignment of INS
School of Instrumentation Science and Opto-Electronics Engineering, Beihang University, Beijing 100191, China
Science and Technology on Aircraft Control Laboratory, Beihang University, Beijing 100191, China
School of Automation Science and Electrical Engineering, Beihang University, Beijing 100191, China
Author to whom correspondence should be addressed.
Received: 21 September 2017 / Revised: 11 November 2017 / Accepted: 15 November 2017 / Published: 18 November 2017
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
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.
Zhou D, Guo L. Stochastic Integration H∞ Filter for Rapid Transfer Alignment of INS. Sensors. 2017; 17(11):2670.
Zhou, Dapeng; Guo, Lei. 2017. "Stochastic Integration H∞ Filter for Rapid Transfer Alignment of INS." Sensors 17, no. 11: 2670.
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