A Decoupled Orientation Estimation Approach for Robust Roll and Pitch Measurements in Magnetically Disturbed Environment
A Decoupled Orientation Estimation Approach for Robust Roll and Pitch Measurements in Magnetically Disturbed Environment
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DOI：
10.1109/tim.2021.3135555
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发表时间：
2022
影响因子：
5.6
通讯作者：
Yujie Sun;Xiaolong Xu;Xincheng Tian;Lelai Zhou;Yibin Li
中科院分区：
文献类型：
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作者：
Yujie Sun;Xiaolong Xu;Xincheng Tian;Lelai Zhou;Yibin Li
利用惯性传感器和磁传感器进行方位估计已经渗透到各种应用中。然而，当传感器暴露在磁扰动中时，稳健的横摇和俯仰估计仍然是方位估计器的挑战。在本文中，我们提出了一种解耦方向估计方法(DOEA)，以从磁测量中分离和实现准确的横摇和俯仰估计。在所提出的DOEA中，我们构造了一个与引力矢量垂直且大小和方向保持不变的参考矢量，并推导出它的协方差，以取代磁场矢量作为观测参考。在扩展卡尔曼滤波框架中进一步融合两个正交均匀场的传感器测量值，以校正陀螺积分的预测方位。为了验证所提出的DOEA的性能，我们在四个不同的实验中将其与三种最先进的方法进行了比较。在没有传感器可靠性验证的磁扰环境中，实验结果表明，DOEA可以提供稳健而准确的横摇和纵摇测量，其均方根误差为0.001和0.007拉德。磁扰对DOEA的影响仅在偏航方向上受控制。在机器人的大范围静态和动态混合运动跟踪中，实验结果表明，所提出的DOEA无奇异性地获得了0.035、0.024和0.018 rad的横摇、俯仰和偏航的均方根估计。此外，DOEA的收敛速度快于流行的优化滤波器，计算效率比两步方位估计器快56%，这有利于在嵌入式系统上实现。
Orientation estimation using inertial and magnetic sensors has permeated into various applications. However, robust roll and pitch estimates are still challenging for the orientation estimators when the sensors are exposed to magnetic disturbances. In this article, we proposed a decoupled orientation estimation approach (DOEA) to separate and achieve accurate roll and pitch estimates from the magnetic measurements. In the proposed DOEA, we formulate a reference vector, which is perpendicular to the gravitational vector and keeps constant size and direction, and derive its covariances to replace the magnetic field vector as the observation references. The sensor measurements of the two orthogonal homogeneous fields are further fused in the extended Kalman filter frame to correct the predicted orientation of the gyroscope integration. To validate the performance of the proposed DOEA, we compare it with three state-of-the-art approaches in four different experiments. In the magnetically disturbed environment without reliability validation of the sensors, experiment results show that the DOEA could provide robust and accurate roll and pitch measurements with 0.001- and 0.007-rad root-mean-square error (RMSE). The influence of the magnetic disturbances on the DOEA is controlled only on the yaw direction. In the wide-range static and dynamic mixed motion tracking of the robot, experiment results show that the proposed DOEA achieves 0.035-, 0.024-, and 0.018-rad RMSE of roll, pitch, and yaw estimates without singularities. Moreover, the proposed DOEA converges faster than the popular optimization filters and achieves computational efficiency 56% faster than the two-step orientation estimator, which is beneficial for realization on the embedded system.