Data fusion algorithm design of GPS/IMU based on fuzzy adaptive federated Kalman filter

被引：0
|
作者：
Wu, Jianhong [1 ]
Zhang, Hongcai [1 ]
机构：
[1] NW Polytech Univ, Sch Automat, Xian 710072, Peoples R China
来源：
PROCEEDINGS OF THE 2009 2ND INTERNATIONAL CONGRESS ON IMAGE AND SIGNAL PROCESSING, VOLS 1-9 | 2009年
关键词：
federated Kalman filtering; contextual information; fuzzy logic control; integrated navigation; data fusion;
D O I：
暂无
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
The aim of this paper is to develop a fuzzy adaptive federated Kalman filtering (FAFKF) algorithm which takes contextual information into consideration, and focus on its application to the integrated GPS(Global Positioning System)/IMU(inertial measurement unit) navigation. A No-Reset structure filter that is no information feedback is employed to improve the efficiency of computing, and fault tolerant capability of the system. A fuzzy logic controller is used to compute the information distribution coefficients real-time according to the contextual information which comes from the innovation sequences of each sub-filter and optimally adjust the Kalman filter, so that the accuracy of integrated navigation System is enhanced. Simulation results show that both the precision and fault tolerance of data fusion are improved.
引用
收藏
页码：3884 / 3887
页数：4
相关论文
共 50 条
  • [31] Data assimilation algorithm based on an adaptive suboptimal Kalman filter
    Klimova, E.G., 2005, Allerton Press Inc.
  • [32] Application of Adaptive Kalman Filtering Algorithm in IMU/GPS Integrated Navigation System
    GAO Weiguang YANG Yuanxi CUI Xianqiang ZHANG Shuangcheng Institute of Surveying and Mapping
    Geo-spatial Information Science, 2007, (01) : 22 - 26
  • [33] Application of Adaptive Kalman Filtering Algorithm in IMU/GPS Integrated Navigation System
    Gao Weiguang
    Yang Yuanxi
    Cui Xianqiang
    Zhang Shuangcheng
    GEO-SPATIAL INFORMATION SCIENCE, 2007, 10 (01) : 22 - 26
  • [34] Sensor fusion based on fuzzy Kalman filter
    Sasiadek, JZ
    Khe, J
    ROMOCO'01: PROCEEDINGS OF THE SECOND INTERNATIONAL WORKSHOP ON ROBOT MOTION AND CONTROL, 2001, : 275 - 283
  • [35] Fuzzy adaptive extended Kalman filter SLAM algorithm based on the improved PSO algorithm
    Pan, Qinghui
    Zhang, Yubo
    Liu, Yanhong
    2019 CHINESE AUTOMATION CONGRESS (CAC2019), 2019, : 3488 - 3493
  • [36] Data Fusion of UWB and IMU Based on Unscented Kalman Filter for Indoor Localization of Quadrotor UAV
    You, Weide
    Li, Fanbiao
    Liao, Liqing
    Huang, Meili
    IEEE ACCESS, 2020, 8 : 64971 - 64981
  • [37] Hybrid Kalman filter-fuzzy logic adaptive multisensor data fusion architectures
    Escamilla-Ambrosio, PJ
    Mort, N
    42ND IEEE CONFERENCE ON DECISION AND CONTROL, VOLS 1-6, PROCEEDINGS, 2003, : 5215 - 5220
  • [38] Reliable integrated navigation system based on adaptive fuzzy federated Kalman filter for automated vehicles
    Li, Xu
    Zhang, Weigong
    PROCEEDINGS OF THE INSTITUTION OF MECHANICAL ENGINEERS PART D-JOURNAL OF AUTOMOBILE ENGINEERING, 2010, 224 (D3) : 327 - 346
  • [39] A Fusion Location Algorithm Based on Federated Kalman Filtering
    Lv Long-hui
    Jin Hong-xia
    PROCEEDINGS OF THE 2016 4TH INTERNATIONAL CONFERENCE ON MACHINERY, MATERIALS AND COMPUTING TECHNOLOGY, 2016, 60 : 2001 - 2005
  • [40] Adaptive Fusion Design Using Multiscale Unscented Kalman Filter Approach for Multisensor Data Fusion
    Wang, Huadong
    Dong, Shi
    MATHEMATICAL PROBLEMS IN ENGINEERING, 2015, 2015
12345