基于LMD-WSVD的半球谐振陀螺混合去噪方法

doi:10.12305/j.issn.1001-506X.2023.02.21

Abstract

Abstract:

In order to reduce the impact of hemispherical resonant gyroscope (HRG) output noise on navigation accuracy, a hybrid denoising method based on local mean decomposition-permutation entropy-wavelet transform-singular value decomposition is proposed. Firstly, the signal of the HRG is decomposed using the local mean decomposition method; then these components are divided into two categories: low-frequency components and mixed components by the permutation entropy; lately, for the mixed components, the wavelet transform and singular value decomposition are cascaded to form a two-stage filter for noise reduction, and finally, components are reconstructed to obtain the final signal. The effectiveness of the proposed method is verified by the experiments. The results show that the proposed algorithm can effectively reduce the output noise in the HRG and improve its measurement accuracy, among which the angular random walk is reduced by 99.9% and the bias instability is reduced by 60.3% compared with the original signal.

Key words: hemispherical resonant gyroscope (HRG), local mean decomposition, permutation entropy, wavelet transform, singular value decomposition

CLC Number:

Longkang CHANG, Jianxiong WEI, Fei YU, Guochang ZHANG, Wei GAO, Qiang HAO. A hybrid denoising method for hemispherical resonant gyroscope based on LMD-WSVD[J]. Systems Engineering and Electronics, 2023, 45(2): 497-503.

Figures/Tables 10

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参数	HRG	EMD-LPF	EMD-LMS	LMD-WSVD
零偏稳定性/(°/h)	0.865 6	0.663 6	0.578 9	0.343 6
角度随机游走/(°/h/ $ \sqrt{\mathrm{Hz}}$)	16.733 3	2.903 3	3.800 0	0.015 5

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A hybrid denoising method for hemispherical resonant gyroscope based on LMD-WSVD

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