MEMS陀螺仪随机误差分析与小波阈值去噪研究  

Random error analysis and wavelet threshold denoising of MEMS gyroscope

作　　者：吴保锋 夏林元[1] 吴东金[1] 祝宏宇 WU Bao-feng;XIA Lin-yuan;WU Dong-jin;ZHU Hong-yu(School of Geography and Planning,Sun Yat-sen University,Guangzhou 510275,China)

机构地区：[1]中山大学地理科学与规划学院,广东广州510275

出　　处：《电子设计工程》2020年第15期1-5,共5页Electronic Design Engineering

基　　金：国家自然科学基金(41704020);国家重点研发计划(2017YFB0504103);中央高校基本科研业务费专项(17lgpy43)。

摘　　要：微机电(MEMS)陀螺仪的随机漂移误差较大,严重影响导航精度。针对上述问题,首先利用Allan方差分析了MEMS陀螺的随机漂移误差;然后基于小波阈值去噪算法处理陀螺信号的高频噪声,建立了硬阈值函数和软阈值函数,并通过两种函数对陀螺信号进行小波阈值去噪处理。实验结果表明:较之硬阈值函数,软阈值函数去噪效果更佳,去噪后信号标准差更低,量化噪声、角度随机游走和零偏不稳定性分别下降了97.34%、97.62%、57.07%。The random drift error of MEMS gyroscope is large,which seriously affects the navigation accuracy.In order to solve these problems,firstly,Allan variance is used to analyze the random drift error of MEMS gyroscope;secondly,the high-frequency noise of gyroscope signal is processed based on wavelet threshold de-noising algorithm,and the hard threshold function and soft threshold function are established,and the wavelet threshold value de-noising of gyroscope signal is processed through two functions.The experimental results show that the soft threshold function is better than the hard threshold function in de-noising,the standard deviation of the signal after de-noising is lower,and the quantization noise,angle random walk and zero bias instability are reduced by 97.34%,97.62%and 57.07%,respectively.

关 键 词：MEMS陀螺仪随机漂移误差 ALLAN方差 高频噪声 小波阈值去噪 

分 类 号：TN98[电子电信—信息与通信工程]