论文标题
基于SVDCKF算法的改进的非线性速度AHR估计
An improved nonlinear FastEuler AHRS estimation based on the SVDCKF algorithm
论文作者
论文摘要
在本文中，我们提出了一个基于改进的非线性快速态度和标题参考和系统（AHRS）估计模型的奇异值分解立方体Kalman滤波器（SVDCKF）融合算法。这项工作的贡献是低成本IMU/MAG Integrated AHRS模型的推导，并结合了季节态度的确定，并使用FastEuler纠正陀螺仪态度更新，这可以增加实时解决方案。此外，SVDCKF算法融合了各种原始传感器数据，以提高与CKF相比的滤波器精度。模拟和实验结果表明，在低和高动态飞行条件下，与CKF相比，所提出的算法具有更出色的态度解决方案精度。
In this paper, we present a Singular Value Decomposition Cubature Kalman Filter(SVDCKF) fusion algorithm based on the improved nonlinear FastEuler Attitude and Heading Reference and System(AHRS) estimation model for small-UAV attitude. The contributions of this work are the derivation of the low-cost IMU/MAG integrated AHRS model combined with the quaternion attitude determination, and use the FastEuler to correct the gyroscope attitude update, which can increase the real-time solution. In addition, the SVDCKF algorithm is fused the various raw sensors data in order to improve the filter accuracy compared with the CKF. The simulation and experiment results demonstrate the proposed algorithm has the more excellent attitude solution accuracy compared with the CKF in the low and high dynamic flight conditions.
