Research on MIMU adaptive filter method based on wavelet analysis
Research on MIMU adaptive filter method based on wavelet analysis
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DOI：
10.1117/12.716950
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发表时间：
2006-11
期刊：
影响因子：
--
通讯作者：
Xiaoguang Chen;Jiancheng Fang
中科院分区：
文献类型：
--
作者：
Xiaoguang Chen;Jiancheng Fang
微惯性测量单元是基于MEMS元件的微导航系统的核心。其精度对系统精度有至关重要的影响。消除MIMU信号中的随机噪声对提高系统精度具有重要意义。针对MIMU信号经过小波分析后在各个尺度空间表现出的不同特征，提出了一种分解水平和阈值自适应调整的自适应滤波方法。采用紧凑支持的db4正交小波对信号进行基于白噪声序列校验的自适应水平多尺度空间分解。采用改进的自适应阈值决策进行阈值滤波。在去除随机噪声产生的高频细节项后，利用小波反变换重构原始信号。实验结果表明，该方法能有效地消除MIMU随机噪声，并取得满意的精度。该算法简单实用。
Micro Inertia Measurement Unit based on MEMS component, is the core of the Micro Navigation System. Its accuracy has a crucial effect on system precision. Eliminating stochastic noise in MIMU signal is of great significance to increase the system accuracy. Aiming at the different characteristics showed at every scale space after wavelet analysis on MIMU signal, an adaptive filtering method with decomposition level and threshold value self-adaptive adjusting is proposed by this paper. The compactly supported Daubechies4 (db4) orthogonal wavelet is applied to decompose the signal in multi-scale space with self-adaptive level based on white noise sequence check. An improved self-adaptive threshold decision making is adopt for threshold filtering. After removing high frequency detail items generated by stochastic noise, inverse wavelet transform is applied to reconstruct the original signal. The experimental results indicate that the method can eliminate MIMU stochastic noise effectively and achieve satisfactory accuracy. And the algorithm is simple and practical.