MEMS陀螺随机误差辨识与降噪技术

Random Error Identification and Noise Reduction of MEMS Gyroscope

针对MEMS陀螺精度受随机误差的影响,并随测姿积分算法逐渐增长的问题,采用时间序列分析法对MEMS陀螺的输入输出数据进行辨识,建立系统的ARMA模型,利用卡尔曼滤波方法对随机误差进行降噪处理,最后对随机误差降噪技术进行实验验证.实验结果表明,降噪后随机误差方差为降噪前的7.17%,由降噪后的MEMS陀螺数据计算得到的姿态角误差小于1°,能够满足低成本导航系统的需要.

MEMS gyroscope accuracy is affected by random error,and the gradually growing with measuring posture integral algorithm,input-output data of MEMS gyroscope is identified by using time series analysis.ARMA model of the system is established,and then the kalman filtering method is used to random noise errors reduction processing.Finally,the noise reduction technique of random error is verified by experiments.Experimental results show that the variance of random errors reduce to 7.17%than before,the calculated attitude angle error use of noise reducing data is less than 1°,and applies to low-cost navigation system.