基于改进的新息自适应卡尔曼MEMS陀螺仪温度补偿

Temperature Compensation of MEMS Gyroscope Based on Improved Innovation Adaptive Kalman Filter

近年来,MEMS陀螺仪在导航和自动控制领域得到广泛的应用。为提高MEMS陀螺仪测量精度抑制温度漂移,本文提出一种基于AR模型改进的新息自适应卡尔曼温度补偿算法。首先,对陀螺仪原始数据使用基于AR模型的自适应卡尔曼算法对数据预处理,再根据静态下陀螺仪输出数据随温度的变化,建立温漂模型,其次将该模型处理的数据与经预处理的数据做差分运算。最后使用阿伦方差曲线图来辨识信号中的误差源,结合某项目的实测实验数据,结果表明:该算法模型有效地抑制了MEMS陀螺仪的温度漂移,提高了陀螺仪的测量精度。

In recent years,MEMS gyroscopes have been widely used in the fields of navigation and automatic control.In order to improve the measurement accuracy of MEMS gyroscope and suppress the temperature drift,an improved innovation adaptive Kalman temperature compensation algorithm based on AR model is proposed in this paper.Firstly,the adaptive Kalman algorithm based on AR model is used to preprocess the original data of gyroscope,and then the temperature drift model is established according to the change of gyro output data with temperature under static state.Secondly,the data processed by the model and the preprocessed data are calculated by difference.Finally,the error source in the signal is identified by using the Allan variance curve.Combined with the experimental data of a project,the results show that the algorithm model can effectively suppress the temperature drift of MEMS gyroscope and improve the measurement accuracy of the gyroscope.