摘要
针对在组合导航中扩展卡尔曼滤波器(EKF)会发散的问题,采用了一种基于模糊控制的自适应卡尔曼滤波算法(FAKF)方法,通过模糊控制器来计算指数加权因子,实时对量测噪声的大小进行调整,保证滤波精度,有效抑制滤波过程的发散问题;针对GPS无法提供姿态角进行组合解算的情况,使用偏振光与SINS的组合进行姿态解算;通过对GPS/SINS/偏振光组合导航系统进行仿真,将基于模糊控制的自适应卡尔曼滤波算法(FAKF)和扩展卡尔曼滤波算法(EKF)进行对比验证,东、北、天向位置上分别提升精度56.81%、65.17%、45.99%,东、北、天向速度上分别提升精度46.99%、54.01%、43.82%,俯仰角、航向角分别提升精度58.01%、53.58%,验证了该方法的优势。
Aimed at the problem that extended Kalman filter(EKF)will diverge in combined navigation,an fuzzy control-based adaptive Kalman filter algorithm(FAKF)is studied,which calculates the exponential weighting factor through a fuzzy controller to adjust the size of the measurement noise in real time to ensure the filtering accuracy,and effectively suppress the filtering divergence.Aimed at the situation that GPS cannot provide the attitude angle for combined solution,the combination of polarized light and SINS is used for the attitude solution.In this paper,the fuzzy control-based FAKF and EKF algorithms are compared and verified by simulating the GPS/SINS/polarized light combined navigation system,the positional accuracy of the system increases by 56.81%,65.17%,and 45.99%in the east,north,and heading,respectively,the velocity accuracy by 46.99%,54.01%,and 43.82%,and the pitch angle and heading angle by 58.01%and 53.58%,respectively,which proves the advantages of the method.
作者
任彩鸣
李沅
边宇峰
李怡纲
张朝锋
REN Caiming;Li Yuan;BIAN Yufeng;LI Yigang;ZHANG Chaofeng(State Key Laboratory of Electronic Testing Technology,North University of China,Taiyuan 030051,China;Jinzhong Cloud Age Technology Co.,Jinzhong 030600,China)
出处
《计算机测量与控制》
2024年第4期129-134,共6页
Computer Measurement &Control
基金
山西省科技成果转化引导专项项目(202204021301044)。
