摘要
针对基于Davenport的四元数法和扩展卡尔曼(extended Kalman filtering,EKF)的姿态估计算法的精度受特征值精度影响的问题,设计一种基于反幂法与EKF算法的姿态估计算法。根据Davenport矩阵K的近似特征值,利用反幂法迭代计算出Davenport矩阵K的特征向量,将其作为EKF的测量值,降低EKF测量值对特征值的敏感度。为验证算法有效性,搭建四旋翼无人机实验平台,实测实验结果表明,该算法能为无人机提供高精度、实时的姿态信息,实现了无人机的稳定飞行。
Aiming at the problems that the accuracy of attitude estimation algorithm based on Davenport’quaternion method and extended Kalman filtering(EKF)is affected by the accuracy of eigenvalues,an attitude estimation algorithm based on inverse power method and EKF algorithm was designed.According to the approximate eigenvalue of Davenport matrix K,the inverse power method was used to iteratively calculate the eigenvector of Davenport matrix K as the observed value of the EKF,to reduce the sensitivity of the EKF observed value to the eigenvalues.A quad-rotor unmanned aerial vehicle test platform was built to verify the effectiveness of the designed algorithm.Experimental results show that the designed algorithm can provide the high precision and real-time attitude information,and realize the stabilized flight for the unmanned aerial vehicle.
作者
张雄
黄卫华
陈劲峰
ZHANG Xiong;HUANG Wei-hua;CHEN Jing-feng(School of Information Science and Engineering,Wuhan University of Science and Technology,Wuhan 430081,China)
出处
《计算机工程与设计》
北大核心
2020年第1期100-106,共7页
Computer Engineering and Design
基金
国家自然科学基金项目(61773298)
冶金自动化与检测技术教育部工程研究中心开放基金项目(MADT201603)
武汉科技大学研究生创新创业基金重点基金项目(JCX2016018)
关键词
反幂法
扩展卡尔曼滤波
近似特征值
无人机
姿态估计
inverse power method
extended Kalman filtering
eigenvalue
unmanned aerial vehicle
attitude estimation
