基于AR模型的MEMS传感器误差建模及分析OA
Error modeling and analysis of MEMS sensor based on AR model
基于微机电系统(MEMS)的惯性传感器以其低成本、低能耗、体积小等优势被广泛应用,低成本的惯性传感器使得MEMS/GNSS组合导航系统具有很大的发展空间.相比GNSS,MEMS在面对信号干扰时具有更好的抑制性能,但是,MEMS陀螺仪和加速度计的精度常受到陀螺、加速度计测量误差的影响.为了减少测量误差对导航精度造成的影响,提高组合导航的精度,通过建立自回归过程(AR)模型来减小MEMS传感器随机误差,并通过扩展卡尔曼滤波提高MEMS/GNSS组合系统精度,最后利用试验数据验证了理论模型,得到了较好的效果.
Inertial sensor based on microelectromechanical system(MEMS)with its advantage of low cost,low power consumption and small volume is widely used,low-cost inertial sensor maked the MEMS/GNSS integrated navigation systems have a great space of development.Compared with the GNSS,MEMS had better performance in the face of signal interference,however,the MEMS gyroscope and accelerometer precision often effected by gyro and acceleration measurement error.In order to reduce the error of the effects,and improve the accuracy of integrated navigation,autoregressive process(AR)model is used to reduce the random error of MEMS sensor,and through extended Kalman filter to improve the precision of MEMS/GNSS integrated system,finally theoretical model was validated by the experimental data,which obtained a good effect.
程果
湖南中森通信科技有限公司,湖南 长沙 410006
航空航天
组合导航MEMS随机误差AR模型
Intergrated navigationMEMSrandom errorAR model
《船电技术》 2026 (1)
23-28,6
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