考虑横向灵敏度的三轴加速度传感器标定方法研究

横向灵敏度是单轴加速度传感器的重要指标之一,它直接影响到三轴加速度传感器的标定模型与测量精度。本论文以三轴MEMS加速度传感器为研究对象,在传统的标定模型中引入了导致测量耦合的横向灵敏度误差,建立了一种新的三轴加速度传感器标定模型,该模型将传感器的横向灵敏度以对称矩阵的形式引入现有的标定公式,构建了包含零位偏差、标度因数误差、非正交安装误差及横向灵敏度的标定函数表达式。最后利用十二位置标定法采集了三轴加速度传感器的原始测量数据,通过极大似然参数估计算法解算新的标定模型完成标定。结果表明,与常用标定数学模型相比,本数学模型的补偿误差均值与方差更小,补偿后数据精度更高且稳定性更好,本研究成果对提升三轴MEMS加速度传感器精度有十分重要的指导意义,因此具有较高的理论研究和工程应用价值。

Research on the calibration method of triaxial acceleration sensor with transverse sensitivity

Transverse sensitivity of the single-axis accelerometer is one of the most important performance metrics, which has significant influence on the calibration model and accuracy. In this study, a novel model considering the transverse sensitivity is proposed to calibrate the three-axis micro-electro-mechanical systems ( MEMS) acceleration sensors. The transverse sensitivity of the model is introduced into the calibration equation as a symmetric matrix. The established calibration function includes zero deviation, scale factor error, non-orthogonal installation error and transverse sensitivity. Finally, the 12-position calibration method is utilized to collect experimental data. The maximum likelihood parameter estimation algorithm is used to solve the calibration model to achieve sensor calibration. Experimental results show that the compensation error of the calibration mathematical model is smaller in terms of mean values and variance than current calibration mathematical model. The accuracy after compensation is higher and the stability is better, which show positive effectiveness on improving the accuracy of MEMS three-axis acceleration sensor. This study has important theoretical significance and engineering application value