用角速度估计磁力计和陀螺仪偏置，提升水下导航精度
Full Magnetometer and Gyroscope Bias Estimation using Angular Rates: Theory and Experimental Evaluation of a Factor Graph-Based Approach
- 利用三轴角速度数据，通过因子图建模同时估计磁力计与陀螺仪偏置
- 实测显示水下定位误差从10%降至0.5%，大幅改善惯性导航性能
- 无需已知地磁强度或姿态，适合集成到实时定位系统中
尽管微机电系统（MEMS）姿态与航向参考系统（AHRS）广泛用于确定系统姿态，但其受限于传感器测量偏置。本文提出一种名为MAGYC的方法，利用陀螺仪的三轴角速度测量，同时估计磁力计的硬铁与软铁偏置及陀螺仪偏置。基于批量和在线增量因子图，提出了两种实现方式。该方法对设备运动要求更低，无需事先知道局部磁场强度或设备姿态，且可无缝集成至平滑与地图构建框架中的因子图算法。通过数值仿真和搭载于水下车辆的实地实验验证，将海底测绘任务中基于死区推算的位置误差由行驶距离的10%降低至0.5%。
原文摘要 · Abstract (English)
Despite their widespread use in determining system attitude, Micro-Electro-Mechanical Systems (MEMS) Attitude and Heading Reference Systems (AHRS) are limited by sensor measurement biases. This paper introduces a method called MAgnetometer and GYroscope Calibration (MAGYC), leveraging three-axis angular rate measurements from an angular rate gyroscope to estimate both the hard- and soft-iron biases of magnetometers as well as the bias of gyroscopes. We present two implementation methods of this approach based on batch and online incremental factor graphs. Our method imposes fewer restrictions on instrument movements required for calibration, eliminates the need for knowledge of the local magnetic field magnitude or instrument's attitude, and facilitates integration into factor graph algorithms for Smoothing and Mapping frameworks. We validate the proposed methods through numerical simulations and in-field experimental evaluations with a sensor onboard an underwater vehicle. By implementing the proposed method in field data of a seafloor mapping dive, the dead reckoning-based position estimation error of the underwater vehicle was reduced from 10% to 0.5% of the distance traveled.
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