摘要
本文主要介绍了联邦卡尔曼的基本结构和工作流程和运用的组合导航的数学模型。证明了联邦滤波的有效性和可行性,提升了组合导航滤波精度、分析了不同信息分配因子的取值大小对联邦卡尔曼滤波器中主滤波器的全局状态估计产生的影响。通过对联邦卡尔曼信息分配、时间更新、量测更新和信息融合过程的公式算法进行推导,证明了不同信息分配因子β的取值不会改变主滤波器的精度估计。运用matlab系统平台对子系统不同β情况下状态估计进行仿真证明。
This article mainly introduces the basic structure and workflow of Federated Kalman and the mathematical model of integrated navigation used.The effectiveness and feasibility of federated filtering is proved,the precision of integrated navigation filtering is improved,and the influence of the value of different information distribution factors on the global state estimation of the main filter in the federated Kalman filter is analyzed.By deriving the formula algorithm of the federated Kalman information distribution,time update,measurement update and information fusion process,it is proved that the value of different information distribution factorβwill not change the accuracy estimation of the main filter.The matlab system platform is used to simulate the state estimation of the subsystem under different β conditions.
作者
姚娅珍
王虹
袁冠杰
程田莉
YAO Ya-zhen;WANG Hong;YUAN Guan-jie;CHENG Tian-li(School of Electronic and Optical Engineering,Nanjing University of Science and Technology,Nanjing 210094,China)
出处
《微波学报》
CSCD
北大核心
2021年第S01期245-248,共4页
Journal of Microwaves
关键词
组合导航
联邦滤波
信息因子分配
最优性
integrated navigation
federated filtering
information factor allocation
optimality
作者简介
姚娅珍,女,1999年生,硕士生。主要研究方向:通信和导航系统研究。E-mail:2312625244@qq.com
