MEMS陀螺误差建模与滤波方法  

Error modeling and filtering method for MEMS gyroscope

作　　者：蒙涛[1] 王昊[1] 李辉[1] 贺光红[1] 金仲和[1] 

机构地区：[1]浙江大学信息与电子工程系,浙江杭州310027

出　　处：《系统工程与电子技术》2009年第8期1944-1948,共5页Systems Engineering and Electronics

基　　金：教育部新世纪优秀人才支持计划(NCET-06-051)资助课题

摘　　要：从实际工程应用角度出发,探讨了微机电系统(micro-electro-mechanical systems,MEMS)陀螺误差的有效滤波降噪方法。基于随机序列时序分析法的基本原理,采用实时平均算法对陀螺原始量测数据进行常值补偿预处理,得到随机漂移信号。对去除渐进项后的差分漂移信号进行AR模型建模,并依据该模型进行改进卡尔曼滤波,在输出差分信号滤波值的同时解算当前陀螺输出滤波值。通过对某MEMS陀螺实测数据的误差补偿结果表明,提出的滤波方法能够有效地抑制其漂移误差,提高实际应用中的测量精度。The compensating method for micro-electro mechanical systems （MEMS） gyroscopic random drift error is discussed from the point of view on practical applications. Based on the principle of the timesequence analysis from the random series, the original measurement from the MEMS gyroscope is pretreated by an real time average estimation algorithm to get random drift signals. The residual signal is modeled by an AR model and is filtered hy Kalman filtering. The compensating results for the practical testing data of an MEMS gyroscope show that the drift error can be effectively reduced by using the filtering method presented, and the measurement accuracy in practice can be further improved.

关 键 词：微机电系统陀螺 AR模型 卡尔曼滤波 

分 类 号：V241.5[航空宇航科学与技术—飞行器设计]