摘要
本文提出了一种建立在信号小波函数虚拟野值思想上的微机械(MEMS)陀螺信号降噪方法。同时针对微机械陀螺信号中含有野值的问题,设计了一维信号小波函数线性压缩的野值剔除方法。首先,本文提出了对信号小波函数模极大值邻域进行线性压缩的信号野值剔除方法,有效地改善了重构时野值点附近信号的震荡问题。然后,提出了信号小波函数虚拟野值降噪方法,利用野值剔除思想设计小波函数降噪阈值,重构信号获得了比通用阈值降噪方法更好的信噪比,实现了信号的平滑和增强。最后,针对船用测量的应用背景对滤波后的信号进行了分析和对比,并给出实现在线滤波的条件。结果显示,陀螺信号零偏稳定性获得提高,同时滤波后信号能够满足系统测量带宽要求。
In this paper a micro-mechanical (MEMS) gyroscope signal de-noising method based on virtual outliers is presented. Aiming at the gyroscope signal with outliers, a method of eliminating outliers is presented based on detecting the modulus maxima and linear compressing. This method effectively improves the reconstruction quality. The method of calculating the de-noising threshold using virtual outliers is presented. The SNR for this method is better than that using universal threshold. Finally, for the applications of marine measurement, the filtered signals are analyzed and compared, and the condition of online filtering is presented. Results show that the zero offset stability of the gyro signal is improved, and the filtered signals meet the system measurement bandwidth requirement.
出处
《仪器仪表学报》
EI
CAS
CSCD
北大核心
2010年第5期1194-1200,共7页
Chinese Journal of Scientific Instrument
关键词
MEMS信号滤波
小波降噪
野值剔除
虚拟野值
MEMS signal filtering
wavelet de-noising
linear removal of outlier
virtual outlier