基于多传感融合和卡尔曼滤波的定位导航算法研究  

Research on Location and Navigation Algorithm Based on Multi Sensor Fusion and Kalman Filter

作　　者：陈秀端 朱笑花 CHEN Xiu-duan;ZHU Xiao-hua(College of Intelligent Manufacturing,Zhangzhou Vocational and Technical College,Zhangzhou 363000,Fujian,China;School of Physics and Information Engineering,Minnan Normal University,Zhangzhou 363000,Fujian,China)

机构地区：[1]漳州职业技术学院智能制造学院,福建漳州363000 [2]闽南师范大学物理与信息工程学院,福建漳州363000

出　　处：《兰州文理学院学报（自然科学版）》2024年第4期38-43,共6页Journal of Lanzhou University of Arts and Science(Natural Sciences)

基　　金：2021年福建省教育厅中青年教师教育科研项目(JAT210856);2021年校级课题(ZZY2021B047);2022年校级课题(ZZY2022Z23)。

摘　　要：为了融合各类定位传感器的优势,满足复杂条件下导航系统的使用需求,利用误差状态的卡尔曼滤波器融合惯性传感器和全局传感器等设备的观测数据,并通过EVO轨迹评估工具分析了该算法性能.实验结果表明,融合算法在x轴与z轴上与理想采样值基本吻合,在x轴上与理想采样值的最大误差为4.8 m,在z轴上最大误差为2.6 m,绝对轨迹误差均方根值为3.02 m,每秒的相对位姿误差为0.12 m,从而证明了卡尔曼滤波融合的方案可以满足定位精度的需求.研究搭建了一个基于多传感融合的定位算法,使得该融合方案在复杂环境下的定位精度得到了提升,并且面对各种干扰环境下具有一定的稳定性.In order to integrate the advantages of various positioning sensors and meet the needs of navigation systems under complex conditions,Kalman filter with error state is used to fuse the observation data of inertial sensor and global sensor,and the performance of the algorithm is analyzed by EVO trajectory evaluation tool.The results show that the fusion algorithm is basically consistent with the ideal sampling value on the X-axis and Z-axis.The maximum error between the fusion algorithm and the ideal sampling value on the X-axis is 4.8 m,the maximum error on the Z-axis is 2.6 m,the absolute trajectory error is 3.02 m,and the relative pose error per second is 0.12 m.It is proved that the Kalman filter fusion scheme can meet the demand of positioning accuracy.A positioning algorithm based on multi-sensor fusion is researched and built,which improves the positioning accuracy in complex environments and has certain stability in the face of various interference environments.

关 键 词：IMU SINS ESKF 多传感融合 定位导航 

分 类 号：TP391[自动化与计算机技术—计算机应用技术]