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.

翻译：微机电系统姿态航向参考系统被广泛用于确定系统姿态，但传感器测量偏置限制了其精度。本文提出一种新颖的基于因子图的方法，称为磁力计与陀螺仪校准法。该方法利用角速率陀螺仪的三轴角速率测量值，增强了批处理和在线应用的校准能力。我们的方法降低了对校准所需仪器运动的限制条件，无需已知当地磁场或仪器姿态信息，并便于集成到平滑与建图框架中的因子图算法。我们通过数值仿真和安装在潜航器上的传感器现场实验评估了所提方法。最终，在标准海底测绘任务中，所提方法将潜航器航向误差标准差从6.21度降低至0.57度。