基于随机误差项的小波阈值去噪算法研究

发布时间：2018-04-21 08:24

本文选题：陀螺仪 + 振动　；参考：《压电与声光》2017年06期

【摘要】：针对振动环境下陀螺仪输出信号噪声干扰严重的问题,提出了一种用随机误差项改进小波阈值的去噪算法。通过对陀螺仪输出信号进行小波分解,根据频率成分将信号分解为多层;然后,对分解在各层的信号进行随机误差项辨识,进而利用随机误差项系数获取各层的噪声阈值;最后,利用获取的阈值进行小波去噪。改进阈值的提出,旨在解决Donoho全局阈值中因阈值选取过大或过小而产生的噪声误判或噪声残留问题,使噪声去除更彻底。通过实验分析,证明了本算法既能有效去除信号噪声,解决噪声残留的问题;又能保留输出的有效信号,解决噪声误判的问题。
[Abstract]:Aiming at the serious noise disturbance of gyroscope output signal in vibration environment, a denoising algorithm using random error term to improve wavelet threshold is proposed. The output signal of gyroscope is decomposed into multi-layers by wavelet decomposition according to the frequency component, then the random error term of the decomposed signal in each layer is identified, and the noise threshold of each layer is obtained by using the coefficient of random error term. Finally, wavelet denoising is carried out by using the obtained threshold. The purpose of the improved threshold is to solve the problem of noise misjudgment or noise residue in Donoho global threshold because the threshold is too large or too small, so that the noise can be removed more thoroughly. Through the experimental analysis, it is proved that the algorithm can not only effectively remove the signal noise, solve the problem of noise residue, but also retain the output effective signal, and solve the problem of noise misjudgment.
【作者单位】：火箭军工程大学惯性技术实验室;中国人民解放军96401部队;
【基金】：国家自然科学基金资助项目(61503392)
【分类号】：TN911.7;TN96

【相似文献】