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机构地区:[1]北京航空航天大学仪器科学与光电工程学院,北京100083
出 处:《航天控制》2007年第4期51-56,共6页Aerospace Control
基 金:国防基础研究重大项目(D2120060013);新世纪人才项目(NCET-04-0162)
摘 要:针对微惯性测量单元信号进行小波多分辨率分析后在各尺度空间呈现的不同特性,提出了一种分解层数和阈值门限自适应选取的滤波去噪方法,同时采用具有紧支集特性的Daubechies正交小波基和改进的阈值函数,自适应选取分解层数并逐层进行阈值自适应滤波,然后经小波逆变换重构原始信号,最后应用实际的M IMU信号进行滤波仿真。实验结果表明该方法能有效消除M IMU信号随机误差,大幅改善其零偏稳定性和信噪比,且算法简练通用性强,有很强的实用性。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. The compactly supported Daubechies 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 adopted for threshold filtering. After removing high frequency detail items gen- erated by stochastic noise, inverse wavelet transform is applied to reconstruct the original signal. Simulation of the adaptive filtering method with real MIMU signal is processed at last. The experimental results indicate that the method can eliminate MIMU stochastic noise effectively and achieve satisfactory accuracy. And the algorithm is simple, universal and practical.
关 键 词:微惯性测量单元 自适应滤波 DAUBECHIES小波 小波分析
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