传感技术学报2018，Vol.31Issue(5)：705-709,5.DOI:10.3969/j.issn.1004-1699.2018.05.009
基于小波分析的MEMS加速度计去噪优化算法
An Optimized MEMS Accelerometer De-Noising Algorithm Based on Wavelet Analysis
摘要
Abstract
In view of the large drift noise of MEMS accelerometer in the inertial navigation system,a wavelet thresh-old de-noising optimization algorithm is proposed based on the analysis and modeling of noise. The noise model is constructed using Allan variance to analyze noise characteristics,and a de-noising method based on the multi-scale threshold function is presented finally. This method effectively overcomes the limitations of soft and hard threshold function,in addition,the performance of filtering is optimized by selecting different adjustment coefficients at each scale. The simulation results show that better SNR,RMSE,and similarity could be obtained:the SNR is improved by 5 dB compared with the traditional methods and the navigation relative error within 100 meters is reduced by 2. 69％,which gets higher precision to some extent.关键词
MEMS去噪/Allan方差/小波分析/阈值函数/惯导系统Key words
MEMS de-noising/Allan variance/wavelet analysis/threshold function/inertial navigation system分类
信息技术与安全科学引用本文复制引用
李世银,张楠,武中文,王洪梅..基于小波分析的MEMS加速度计去噪优化算法[J].传感技术学报,2018,31(5):705-709,5.基金项目
国家自然科学基金项目(61771474) （61771474）
国家自然科学基金青年科学基金项目(61601464) （61601464）
