【摘要】 离心机标定能够持续提供大于1g的向心加速度，可以充分激励加速度计的高阶非线性项，已经成为标定高精度加速度计最常用的方法。但受试验设备误差的影响，传统的离心机标定模型精度较低，从而导致传统标定方法的标定精度较差，为此，本文提出了一种高精度加速度计标定方法。通过引入数理统计学中半参数回归的思想，将试验设备误差引起的系统误差视为非参数向量，建立了一种包含试验设备误差的高精度半参数标定模型，进而采用自然样条半参数估计法对待标定参数和非参数向量进行估计，消除试验设备误差对待标定参数标定精度的影响。仿真验证表明，所提方法可以有效估计由试验设备误差引起的系统误差，具有比传统标定方法更高的标定精度。更多还原

【Abstract】 Centrifuge calibration can continuously provide centripetal acceleration of more than 1g, and can fully stimulate the high-order nonlinear term of accelerometer. It has become the most commonly used method to calibrate high-precision accelerometer. However, affected by the error of test equipment, the accuracy of the traditional centrifuge calibration model is low, which leads to the low calibration accuracy of the traditional calibration method. Therefore, a high-precision accelerometer centrifuge calibration method is proposed in this paper. By introducing the idea of semi-parametric regression in mathematical statistics, the system error caused by the error of test equipment is regarded as a non-parametric vector, and a high-precision semi-parametric calibration model including the error of test equipment is established. Then the natural spline semi-parametric estimation method is used to estimate the calibration parameters and the non-parametric vector, so as to eliminate the influence of test equipment error on the calibration accuracy of calibration parameters. Simulation results show that the proposed method can effectively estimate the system error caused by the error of test equipment, and has higher calibration accuracy than the traditional calibration method.更多还原