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Self-Alignment for Inertial System in Vibration Environment Based on Improved EEMD

机译:基于改进EEMD的振动环境惯性系统自对准

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Vibration is an important error source of inertial system. Eliminating vibration is important for improving the performance of initial alignment. In this paper, the improved Ensemble Empirical Mode Decomposition (IEEMD) and permutation entropy are used to eliminate the noises and the vibrations. Firstly, on the basis of the research on the influence of the frequency of artificial noise on the Empirical Mode Decomposition (EMD) decomposition, an improved EEMD is proposed to ensure that the vibration signal can be accurately decomposed. Second, the noise-related Intrinsic Mode Functions (IMFs), vibration-related IMFs and signal-related IMFs are separated according to the permutation entropy of each IMF. Finally, to achieve the purpose of eliminating noise and vibration interference, the signal-related IMFs are acted as the output of fiber optic gyroscopes and accelerometers. The experimental results show that the proposed method can effectively reduce the vibration and improve the efficiency and accuracy of the initial alignment.
机译:振动是惯性系统的重要误差源。消除振动对于提高初始对准的性能很重要。本文采用改进的集成经验模态分解(IEEMD)和置换熵来消除噪声和振动。首先,在对人工噪声频率对经验模态分解(EMD)分解的影响进行研究的基础上,提出了一种改进的EEMD,以确保振动信号能够被准确地分解。第二,根据每个IMF的置换熵,将与噪声相关的本征函数(IMF),与振动相关的IMF和与信号相关的IMF分开。最后,为了达到消除噪声和振动干扰的目的,与信号相关的IMF充当光纤陀螺仪和加速度计的输出。实验结果表明,该方法可以有效地减少振动,提高初始对准的效率和准确性。

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