基于改进自适应滤波的MEMS陀螺振动误差抑制研究

Research on vibration error suppression of MEMS gyroscope based on improved adaptive filtering

陈杰 ¹侯帅康 ¹刘玉县 ²何春华³

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作者信息

1. 郑州大学电气与信息工程学院,河南郑州 450001;广东顺德工业设计研究院(广东顺德创新设计研究院),广东佛山 528311
2. 广东顺德工业设计研究院(广东顺德创新设计研究院),广东佛山 528311;北京大学集成电路学院,北京 100871
3. 北京大学集成电路学院,北京 100871
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摘要

本文提出一种基于改进自适应滤波的MEMS陀螺随机振动误差的补偿算法.该算法采用简化Sage-Husa自适应滤波算法估计量测噪声,并通过协方差匹配技术引入收敛性判据抑制了滤波的发散,它提高了实时性且减少了计算量.实验结果表明:经过改进算法滤波后,MEMS陀螺随机振动误差的方差减少97.76％,与常规卡尔曼滤波相比,改进算法的方差减少了 72.66％,验证了改进的自适应卡尔曼滤波算法可以有效地抑制MEMS陀螺因随机振动引起的输出误差.

Abstract

A compensation algorithm for random vibration error of MEMS gyroscope based on improved adaptive filtering is proposed.The algorithm uses a simplified Sage-Husa adaptive filtering algorithm to estimate measurement noise and convergence criterion is introduced to suppress filtering divergence by the covariance matching technique,which improves the real-time performance and reduces the computation quantity.The experimental results show that the variance of random vibration error of MEMS gyroscope is reduced by 97.76％after the algorithm filtering is improved,and the variance of the improved algorithm is reduced by 72.66％,compared with the conventional Kalman filtering.It is verified that the improved adaptive Kalman filtering algorithm can effectively suppress the output error caused by the random vibration of the MEMS gyroscope.

关键词

MEMS陀螺/简化Sage-Husa自适应滤波/时间序列模型

Key words

MEMS gyroscope/simplified Sage-Husa adaptive filtering/time-series model

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基金项目

国家自然科学基金(62104047)

出版年

2024

传感器与微系统

中国电子科技集团公司第四十九研究所

传感器与微系统

CSTPCD北大核心

影响因子：0.61

ISSN：1000-9787

参考文献量10

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