The calibration of MEMS triaxial gyroscopes is crucial for achieving precise attitude estimation for various wearable health monitoring applications. However, gyroscope calibration poses greater challenges compared to accelerometers and magnetometers. This paper introduces an efficient method for calibrating MEMS triaxial gyroscopes via only a servo motor, making it well-suited for field environments. The core strategy of the method involves utilizing the fact that the dot product of the measured gravity and the rotational speed in a fixed frame remains constant. To eliminate the influence of rotating centrifugal force on the accelerometer, the accelerometer data is measured while stationary. The proposed calibration experiment scheme, which allows gyroscopic measurements when operating each axis at a specific rotation speed, making it easier to evaluate the linearity across a related speed range constituted by a series of rotation speeds. Moreover, solely the classical least squares algorithm proves adequate for estimating the scale factor, notably streamlining the analysis of the calibration process. Extensive numerical simulations were conducted to analyze the proposed method's performance in calibrating a triaxial gyroscope model. Experimental validation was also carried out using a commercially available MEMS inertial measurement unit (LSM9DS1 from Arduino nano 33 BLE SENSE) and a servo motor capable of controlling precise speed. The experimental results effectively demonstrate the efficacy of the proposed calibration approach.

翻译：MEMS三轴陀螺仪的校准对于实现可穿戴健康监测应用中的精确姿态估计至关重要。然而，与加速度计和磁力计相比，陀螺仪的校准面临更大挑战。本文提出一种仅通过伺服电机即可高效校准MEMS三轴陀螺仪的方法，特别适用于现场环境。该方法的核心策略是利用固定坐标系中重力测量值与旋转速度的点积保持恒定的特性。为消除旋转离心力对加速度计的影响，加速度计数据在静止状态下测量。所提出的校准实验方案允许在每个轴以特定转速运行时获取陀螺仪测量值，从而便于评估由一系列转速构成的关联速度范围内的线性度。此外，仅需经典最小二乘算法即可有效估计标度因子，显著简化了校准过程的分析。通过大量数值仿真分析了该方法在三轴陀螺仪模型校准中的性能，并采用商用MEMS惯性测量单元（Arduino nano 33 BLE SENSE搭载的LSM9DS1）与可精确控制转速的伺服电机进行了实验验证。实验结果充分证明了所提校准方法的有效性。