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。
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.
作者
陈杰
侯帅康
刘玉县
何春华
CHEN Jie;HOU Shuaikang;LIU Yuxian;HE Chunhua(School of Electrical and Information Engineering,Zhengzhou University,Zhengzhou 450001,China;Guangdong Shunde Industrial Design and Research Institute(Guangdong Shunde Innovation Design and Research Institute),Foshan 528311,China;School of Integrated Circuits,Peking University,Beijing 100871,China)
出处
《传感器与微系统》
CSCD
北大核心
2024年第4期61-63,67,共4页
Transducer and Microsystem Technologies
基金
国家自然科学基金资助项目(62104047)。
