International Journal of Naval Architecture and Ocean Engineering

The Society of Naval Architects of Korea (대한조선학회)
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$H_{\infty}$ filter for flexure deformation and lever arm effect compensation in M/S INS integration

  • Liu, Xixiang (Key Laboratory of Micro-inertial Instrument and Advanced Navigation Technology, Ministry of Education, Southeast University) ;
  • Xu, Xiaosu (Key Laboratory of Micro-inertial Instrument and Advanced Navigation Technology, Ministry of Education, Southeast University) ;
  • Wang, Lihui (Key Laboratory of Micro-inertial Instrument and Advanced Navigation Technology, Ministry of Education, Southeast University) ;
  • Li, Yinyin (Key Laboratory of Micro-inertial Instrument and Advanced Navigation Technology, Ministry of Education, Southeast University) ;
  • Liu, Yiting (Key Laboratory of Micro-inertial Instrument and Advanced Navigation Technology, Ministry of Education, Southeast University)
  • Published : 2014.09.30
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Abstract

On ship, especially on large ship, the flexure deformation between Master (M)/Slave (S) Inertial Navigation System (INS) is a key factor which determines the accuracy of the integrated system of M/S INS. In engineering this flexure deformation will be increased with the added ship size. In the M/S INS integrated system, the attitude error between MINS and SINS cannot really reflect the misalignment angle change of SINS due to the flexure deformation. At the same time, the flexure deformation will bring the change of the lever arm size, which further induces the uncertainty of lever arm velocity, resulting in the velocity matching error. To solve this problem, a $H_{\infty}$ algorithm is proposed, in which the attitude and velocity matching error caused by deformation is considered as measurement noise with limited energy, and measurement noise will be restrained by the robustness of $H_{\infty}$ filter. Based on the classical "attitude plus velocity" matching method, the progress of M/S INS information fusion is simulated and compared by using three kinds of schemes, which are known and unknown flexure deformation with standard Kalman filter, and unknown flexure deformation with $H_{\infty}$ filter, respectively. Simulation results indicate that $H_{\infty}$ filter can effectively improve the accuracy of information fusion when flexure deformation is unknown but non-ignorable.

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References

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