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首页> 外文期刊>International Journal of Naval Architecture and Ocean Engineering >H∞ filter for flexure deformation and lever arm effect compensation in M/S INS integration
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H∞ filter for flexure deformation and lever arm effect compensation in M/S INS integration

机译：H ∞滤波器，用于M / S INS集成中的挠曲变形和杠杆效应补偿

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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 ∞ 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 ∞ 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 ∞ filter, respectively. Simulation results indicate that H ∞ filter can effectively improve the accuracy of information fusion when flexure deformation is unknown but non-ignorable.
机译：摘要在船舶上，特别是在大型船舶上，主（M）/从（S）惯性导航系统（INS）之间的挠曲变形是决定M / S INS集成系统精度的关键因素。在工程中，挠曲变形将随着船尺寸的增加而增加。在M / S INS集成系统中，由于弯曲变形，INS和SINS之间的姿态误差不能真正反映SINS的未对准角度变化。同时，挠曲变形会引起杠杆臂尺寸的变化，从而进一步引起杠杆臂速度的不确定性，从而导致速度匹配误差。为了解决这个问题，提出了一种H∞算法，将变形引起的姿态和速度匹配误差视为能量有限的测量噪声，并通过H∞滤波器的鲁棒性来抑制测量噪声。在经典的“姿态加速度”匹配方法的基础上，采用三种方案对M / S INS信息融合的过程进行了仿真和比较，这三种方案是使用已知卡尔曼滤波器的已知和未知挠曲变形，以及使用H方法的未知挠曲变形分别为∞滤波器。仿真结果表明，当弯曲变形未知但不可忽略时，H∞滤波器可以有效提高信息融合的精度。

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