首页|基于VB-EKF的GPS/INS松组合导航定位算法

基于VB-EKF的GPS/INS松组合导航定位算法

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针对应用在无人机(Unmanned Aerial Vehicle,UAV)中的全球定位系统/惯性导航系统(GPS/INS)松组合导航非线性系统受到外界噪声干扰导致量测噪声在滤波时不断变化,从而造成滤波精度下降等问题,提出一种变分贝叶斯扩展卡尔曼滤波(VB-EKF)算法.该算法利用EKF(Extended Kalman Filter)将非线性系统中的状态函数和量测函数展开为线性方程,并将两个不同的导航系统数据进行融合,避免了单系统导航定位发散的问题.考虑到组合系统中量测噪声的时变特性,引入变分贝叶斯算法进行改进,有效解决了系统滤波精度下降问题.仿真结果表明,VB-EKF较EKF算法可有效提高滤波稳定性,进而提高系统导航定位精度.
GPS/INS LOOSE INTEGRATED NAVIGATION AND POSITIONING ALGORITHM BASED ON VB-EKF
The GPS/INS loose integrated navigation system applied in UAVs is affected by external noise interference,causing the measurement noise to constantly change in the filtering process,so that the filtering accuracy is reduced.Aimed at this problem,an algorithm based on variational Bayesian extended Kalman filtering(VB-EKF)is proposed.The algorithm used EKF to expand the state function and measurement function of the nonlinear system into a linear equation,and the data of two different navigation systems were fused,so as to avoid the divergence of navigation and positioning of the single system.Considering the time-varying characteristics of measurement noise in the combined system,variational Bayesian algorithm was introduced to improve and effectively solve the problem of the system filtering accuracy decline.The simulation results show that compared with EKF algorithm,VB-EKF algorithm can effectively improve the filtering stability,thereby improving the accuracy of system navigation and positioning.

UAVGPSINSIntegrated navigationVariational BayesExtended Kalman filtering

侯华、程萌、黄鼎盛、郭胜杰、王天昊

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河北工程大学信息与电气工程学院 河北邯郸 056038

英国布鲁内尔大学工程、设计和物理科学学院 英国伦敦UB83PH

无人机 全球定位系统 惯性导航系统 组合导航 变分贝叶斯 扩展卡尔曼滤波

河北省教育厅科学技术研究重点项目

ZD2019019

2024

计算机应用与软件
上海市计算技术研究所 上海计算机软件技术开发中心

计算机应用与软件

CSTPCD北大核心
影响因子:0.615
ISSN:1000-386X
年,卷(期):2024.41(6)
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