Attitude estimation based on a magnetic and inertial measurement unit is popular in the areas of robotics, aerospace, and unmanned aerial vehicles. Nevertheless, the magnetometer is prone to external magnetic disturbance that deteriorates the state estimation. This article proposes a novel partial state update strategy in the extended Kalman filter (PS-EKF) by optimally solving the posteriori covariance optimization problem under the Kalman gain constraint, so as to obviate the magnetic measurement update on two level angles and the inertial sensor biases. Besides, a new magnetic disturbance detection technique (vectorial detector) considering both the norm and the direction of the magnetometer measurement is proposed. Simulations and experiments show that the proposed PS-EKF method can be totally immune to the magnetic interference on the level angles and sensors biases, in contrast to the traditional extended Kalman filter using either the direct magnetic output or the indirect yaw as the measurement.

中文翻译：

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通过部分状态更新卡尔曼滤波器和矢量磁干扰检测的方向估计

基于磁性和惯性测量单元的姿态估计在机器人、航空航天和无人机领域很流行。然而，磁力计容易受到外部磁干扰，从而使状态估计恶化。本文通过优化求解扩展卡尔曼滤波器 (PS-EKF) 中的一种新的局部状态更新策略后验的卡尔曼增益约束下的协方差优化问题，从而避免两个水平角的磁测量更新和惯性传感器偏差。此外，提出了一种新的磁干扰检测技术（矢量检测器），同时考虑了磁力计测量的范数和方向。仿真和实验表明，与使用直接磁输出或间接偏航作为测量的传统扩展卡尔曼滤波器相比，所提出的 PS-EKF 方法可以完全不受水平角和传感器偏差的磁干扰。