摘要
微机电系统(MEMS)陀螺仪具有尺寸小,可靠性强的特点,已广泛应用于各种微姿态仪中,而陀螺的安装误差是影响姿态仪输出精度的主要因素之一。现有的陀螺安装误差模型是建立在确定的刻度因子和零偏基础上,但实际应用中,陀螺的刻度因子存在误差,且零偏随温度和转速发生变化。该文提出了一种改进的误差标定和补偿方法,并针对模型中MEMS的零偏温度和转速非线性误差问题,运用BP神经网络,实现了模型零偏动态补偿。实验表明,采用该文提出的标定方法,陀螺的角速率误差由1.5(°)/s提高至0.05(°)/s。验证了标定方法的可行性。
The micro-electro-mechanical system（MEMS）gyroscope has the features of small size,high reliability,and has been widely used in various micro attitude indicator,while the installation error of the gyro is one of the main factors that affect the accuracy of attitude meter.The existing gyro installation error model was established on the basis of the determined scale factor and zero bias,but in the practical applications,the scale factor of gyro exists error,and the zero bias changes with the temperature and rotating speed.An improved error calibration and compensation method has been proposed in this paper.Aiming at the zero-offset temperature and non-linear error problems in the existing MEMS model,the BP neural network is used to compensate the model zero bias dynamically.The experimental results show that the angular rate error of gyro has been increased from 1.5（°）/s to 0.05（°）/s by using the proposed calibration method.The feasibility of the calibration method has been verified.
出处
《压电与声光》
CAS
CSCD
北大核心
2016年第2期298-303,共6页
Piezoelectrics & Acoustooptics
基金
国家自然科学基金项目资助(51175535)
MEMS振动传感与微姿态组合测井技术国际联合研究中心科技平台与基地建设基金资助项目(cstc2014gjhz0038)
重庆市研究生科研创新基金资助项目(CYS15163)
关键词
BP神经网络
微机电系统(MEMS)陀螺仪
安装误差
零偏补偿
温度
转速
BP neural network
micro-electro-mechanical system（MEMS）gyroscope
installation error
bias compensation
temperature
rotating speed
