摘要
针对MEMS陀螺仪输出信号随机漂移噪声较大的问题,结合室内行人导航应用需求,在分析传统小波阈值去噪方法的基础上,设计了一种优化的小波阈值去噪方法。该方法构造了一种小波系数介于软硬阈值之间的连续小波阈值函数,在一定程度上克服了软硬阈值函数自身固有的缺陷。最后,分别采用传统阈值去噪法与优化小波阈值去噪法对行人导航系统中采集到的MEMS陀螺仪数据进行去噪处理,结果表明,相对传统的软硬阈值滤波法,优化阈值去噪法处理后的信号获得了更高的信噪比40.8748 d B,同时均方差降低了40%,MEMS陀螺信号中的随机噪声被有效剔除,满足了行人导航后续研究工作的需求。
In view that the random drift noise of MEMS gyro output signals is relatively large,an optimized wavelet threshold method is proposed based on the analysis of traditional wavelet threshold de-nosing method for indoor pedestrian navigation applications.A continuous wavelet threshold function is constructed by this method,whose wavelet coefficients are between those from the soft and hard threshold function.In a certain degree,the new method overcomes the inherent defects of the traditional threshold function.Finally,the experiments are made by using different methods to de-noise the MEMS gyro data from the pedestrian navigation system,and the results show that the signal processed by the optimized threshold method achieves higher SNR of 40.8748 d B,and the MSE is reduced by 40%.The random noise in the MEMS gyro is removed effectively,and the optimized wavelet threshold method meets the needs of the follow-up study on the pedestrian navigation.
作者
田晓春
陈家斌
韩勇强
宋春雷
杨黎明
TIAN Xiao-chun;CHEN Jia-bin;HAN Yong-qiang;SONG Chun-lei;YANG Li-ming(School of Automation,Beijing Institute of Technology,Beijing 100081,China;Huabei Optical Instrument C0.LTD,Beijing 100053,China)
出处
《中国惯性技术学报》
EI
CSCD
北大核心
2015年第4期442-445,共4页
Journal of Chinese Inertial Technology
基金
国防预研基金项目资助(9140A09050313BQ01127)
关键词
小波阈值
去噪
数据处理
信噪比
行人导航
wavelet threshold
de-noising
signal process
signal-to-noise ratio
pedestrian navigation
