摘要
MEMS陀螺仪是一类新型惯性器件,具有体积小、成本低、重量轻、可靠性高等优点,但是精度较低、随机漂移误差比较大.从实际工程应用角度出发,针对MEMS陀螺仪的随机漂移误差,首先进行实时均值滤波处理,然后基于随机序列时序分析法的基本原理,建立MEMS陀螺仪随机漂移误差的一阶AR模型,然后依据kalman滤波算法的马尔科夫特性,提出了对MEMS陀螺仪每次输出进行实时多次滤波处理的新方法.通过对具体测量数据进行处理,MEMS陀螺仪的随机漂移误差减小到原来的百分之二左右.
MEMS gyroscope is a new type of inertial sensor with small size,low cost,light weight,high reliability and so on.However,it is less precise with random errors.Aiming at application in practical engineering and dealing with MEMS gyroscope random errors,real-time average filtering is first processed,and then the first-order AR model of MEMS gyroscope random error is established on the basis of principles of time series analysis of random sequence.Finally,based an Markor properties of kalman filtering algorithm,a new method is proposed that each of the MEMS gyroscope output is multiple real-time filtered.Through the specific measurement data processing,MEMS gyroscope random errors are reduced to about two percent of the original one.
出处
《沈阳理工大学学报》
CAS
2010年第2期82-85,共4页
Journal of Shenyang Ligong University
