用TRIAD增强曼达托尔滤波，提升磁力计干扰下的姿态估计鲁棒性。
Robust Orientation Estimation with TRIAD-aided Manifold EKF
- 将TRIAD算法特性融入曼达托尔扩展卡尔曼滤波，抑制磁力计干扰
- 实验验证在磁干扰下俯仰和翻滚轴估计精度显著提升
- 适合高精度姿态估计场景，尤其磁环境复杂时
曼达托尔扩展卡尔曼滤波（Manifold EKF）广泛用于姿态确定。磁力计作为姿态估计传感器，易受校准误差和外部磁场干扰。TRIAD（三轴姿态确定）算法虽为次优姿态估计算法，但其特性可被利用来减弱磁力计读数对俯仰与翻滚轴估计的影响。本文将此特性引入曼达托尔EKF算法中，有效抑制磁力计干扰。通过实验验证了方法的有效性。
原文摘要 · Abstract (English)
The manifold extended Kalman filter (Manifold EKF) has found extensive application for attitude determination. Magnetometers employed as sensors for such attitude determination are easily prone to disturbances by their sensitivity to calibration and external magnetic fields. The TRIAD (Tri-Axial Attitude Determination) algorithm is well known as a sub-optimal attitude estimator. In this article, we incorporate this sub-optimal feature of the TRIAD in mitigating the influence of the magnetometer reading in the pitch and roll axis determination in the Manifold EKF algorithm. We substantiate our results with experiments.
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