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改进Sage-Husa算法结合小波模糊阈值算法的MEMS陀螺去噪 被引量:4

Improved Sage-Husa algorithm and wavelet fuzzy threshold algorithm for MEMS gyroscope denoising
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摘要 为解决微机电系统(MEMS)中陀螺仪输出噪声大、精度低的问题,基于自适应滤波算法与小波阈值算法的基础上,将小波阈值算法与模糊理论结合,提出了Sage-Husa自适应滤波算法联合小波模糊阈值去噪算法应用在MEMS陀螺去噪中。首先使用改进的Sage-Husa自适应滤波算法进行预处理,通过修正状态的预测值抑制干扰数据对滤波的影响,然后使用小波模糊阈值去噪算法对信号进行后处理,实现抑制随机噪声的效果。实验结果表明:在静态实验中,该算法去噪效果优于Sage-Husa自适应滤波算法和小波阈值算法,其与Sage-Husa自适应滤波算法、小波模糊阈值算法相比,噪声方差分别降低78.7%和14.6%,信噪比分别提高43.7%和16.3%。在动态实验中,该算法能够自适应地减少异常值的不利影响,保持原始信号的波形,其与Sage-Husa自适应滤波算法、小波模糊阈值算法相比,噪声方差分别降低62.7%和31.6%,信噪比分别提高47.8%和10.0%。 To solve the problem of high output noise and low output precision of gyroscope in micro-electromechanical systems(MEMS). Based on the adaptive filtering algorithm and the wavelet threshold algorithm, the wavelet threshold algorithm and the fuzzy theory are combined, this paper proposed to apply the Sage-Husa adaptive filtering algorithm combined with the wavelet fuzzy threshold denoising algorithm to MEMS gyroscope denoising. Firstly, the improved Sage-Husa adaptive filtering algorithm is used to preprocess, and the influence of interference data on filtering is suppressed by modifying the predicted value of the state. Then, the wavelet fuzzy threshold denoising algorithm is used to post-process the signal, so as to achieve the effect of suppressing random noise. The experimental results show that the denoising effect of the algorithm is better than the Sage-Husa adaptive filtering algorithm and the wavelet threshold algorithm, the noise variance is reduced by 78.4% and 14.6%, and the signal-to-noise ratio is increased by 43.7% and 16.3% respectively in the static experiment. The algorithm can adaptively reduce the adverse effects of outliers and maintain the original signal waveform. Compared with Sage-Husa adaptive filtering algorithm and wavelet fuzzy threshold algorithm, the noise variance is reduced by 62.7% and 31.6%, and the signal-to-noise ratio is increased by 47.8% and 10.0% respectively in dynamic experiments.
作者 于玉丹 林伟 俞朝阳 Yu Yudan;Lin Wei;Yu Zhaoyang(School of Electrical and Electronic Engineering,Shanghai Institute of Technology,Shanghai 201418,China)
出处 《电子测量技术》 北大核心 2022年第19期64-69,共6页 Electronic Measurement Technology
关键词 陀螺仪 自适应滤波 小波模糊滤波 联合滤波 gyroscope adaptive filtering wavelet fuzzy filtering joint filtering
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