MEMS-IMUs have an extensive application in multifarious studies, as well as industrial and commercial areas. It is crucial to diminish their intrinsic errors in a suitable calibration procedure. In this paper, a novel calibration procedure was proposed for Inertial Measurement Units (IMUs) on a turntable. A general nonlinear model of the IMU output including the effects of bias, scale factor, misalignment, and lever arm was derived. Transformed Unscented Kalman Filter (TUKF) was utilized to perform the estimation of error parameters for gyroscopes and accelerometers. The calibration maneuvers were applied using a tri-axis turntable to create input signals. In addition, assuming the sensors not placing in the center of the table makes angular acceleration become another variable which affects the estimation of the error parameters. Therefore, a suitable angular acceleration estimator was designed utilizing the angular velocity output. According to experimental results, applying the proposed method caused 66% and 63% increase in the accuracy of gyroscopes and accelerometers outputs, respectively, compared with the calibrated signals based on the least square method.

中文翻译：

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使用非线性模型和 TUKF 校准低精度 MEMS IMU

MEMS-IMU 在各种研究以及工业和商业领域都有广泛的应用。在合适的校准程序中减少它们的固有误差是至关重要的。在本文中，针对转台上的惯性测量单元 (IMU) 提出了一种新的校准程序。推导出了 IMU 输出的一般非线性模型，包括偏置、比例因子、未对准和杠杆臂的影响。转换后的无迹卡尔曼滤波器 (TUKF) 用于估计陀螺仪和加速度计的误差参数。使用三轴转台应用校准操作以创建输入信号。此外，假设传感器没有放置在工作台的中心，角加速度成为另一个影响误差参数估计的变量。所以，利用角速度输出设计了一个合适的角加速度估计器。根据实验结果，与基于最小二乘法的校准信号相比，应用所提出的方法使陀螺仪和加速度计输出的精度分别提高了 66% 和 63%。