用角速度数据校准磁力计和陀螺仪偏置，提升姿态系统精度。
Towards a Factor Graph-Based Method using Angular Rates for Full Magnetometer Calibration and Gyroscope Bias Estimation
- 基于因子图，利用三轴角速度实现无需已知磁场或姿态的校准
- 水下车辆航向误差标准差从6.21度降至0.57度
- 适合需高精度姿态估计的水下导航与机器人应用
MEMS姿态航向参考系统广泛用于确定系统姿态，但传感器测量偏置限制了其精度。本文提出一种新型基于因子图的方法MAGYC（Magnetometer and Gyroscope Calibration），利用陀螺仪三轴角速度测量，提升批量与在线校准性能。该方法对设备运动条件要求更宽松，无需知晓本地磁场或仪器姿态，且可无缝集成至平滑与建图框架中的因子图算法。通过数值仿真及安装于水下车辆的实地实验评估，所提方法使水下车辆在标准海底测绘任务中航向误差标准差由6.21度降低至0.57度。
原文摘要 · Abstract (English)
MEMS Attitude Heading Reference Systems are widely employed to determine a system's attitude, but sensor measurement biases limit their accuracy. This paper introduces a novel factor graph-based method called MAgnetometer and GYroscope Calibration (MAGYC). MAGYC leverages three-axis angular rate measurements from an angular rate gyroscope to enhance calibration for batch and online applications. Our approach imposes less restrictive conditions for instrument movements required for calibration, eliminates the need for knowledge of the local magnetic field or instrument attitude, and facilitates integration into factor graph algorithms within Smoothing and Mapping frameworks. We evaluate the proposed methods through numerical simulations and in-field experimental assessments using a sensor installed on an underwater vehicle. Ultimately, our proposed methods reduced the underwater vehicle's heading error standard deviation from 6.21 to 0.57 degrees for a standard seafloor mapping survey.
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