Volume 13 Issue 6
. 
Turn off MathJax
Article Contents
Article Navigation >  Journal of Traffic and Transportation Engineering  > 2013  >  13(6): 113-118
HAN Ping, GAN Hao-liang, HE Wei-kun, ALAZARD Daniel. Aircraft attitude estimation method based on CKF[J]. Journal of Traffic and Transportation Engineering, 2013, 13(6): 113-118.
Citation: HAN Ping, GAN Hao-liang, HE Wei-kun, ALAZARD Daniel. Aircraft attitude estimation method based on CKF[J]. Journal of Traffic and Transportation Engineering, 2013, 13(6): 113-118.
shu

Aircraft attitude estimation method based on CKF

  • 1.

    Tianjin Key Laboratory for Advanced Signal Processing, Civil Aviation University of China

  • 2.

    Chongqing Air Traffic Mangement Sub-Bureau of Civil Aviation Administration of China

  • 3.

    Department of Mathematics and Control, Institut Supérieur de l'AéRonautique et de L'Espace

More Information
  • Author Bio:

    HAN Ping(1966-), female, professor, PhD, + 86-20-24092450, hanpingcauc@163.com

  • Received Date: 2013-07-18
  • Publish Date: 2013-12-25
    Abstract
  • In order to improve the estimation accuracy of aircraft attitude in nonlinear model, a nonlinear estimation model based on the quaternion and the sensors with less accuracy and higher noise was established, and the cubature Kalman filter(CKF) algorithm based on spherical-radial cubature rules was applied to estimate the attitude. The model and algorithm were verified by using the real flying data. The estimation results of cubature Kalman filter algorithm, extended Kalman filter (EKF) algorithm and central difference Kalman filter (CDKF) algorithm were compared. Comparison result indicates that the estimation precision and stability of CKF are higher, its estimation time and error are minimum, and the derivation and adjustable parameters are not required in the estimation. 1 tab, 7 figs, 15 refs.

     

    • FullText(HTML)
  • loading
    • References(15)
  • [1]
    CRASSIDIS J L, MARKLEY F L. Unscented filtering for spacecraft attitude estimation[J]. Journal of Guidance, Control and Dynamics, 2003, 26(4): 536-542.
    [2]
    MARINS J L, YUN Xiao-ping, BACHMANN E R, et al. An extended Kalman filter for quaternion-based orientation estimation using MARG sensors[C]∥IEEE. Proceedings of the 2001 IEEE/RSJ International Conference on Intelligence Robots and Systems. Maui: IEEE, 2001: 2003-2011.
    [3]
    NORGAARD M, POULSEN N K, RAVN O. New developments in state estimation for nonlinear systems[J]. Automatica, 2000, 36(11): 1627-1638. doi: 10.1016/S0005-1098(00)00089-3
    [4]
    NORGAARD M, POULSEN N K, RAVN O. Advances in derivative-free state estimation for nonlinear system[R]. Copenhagen: Technical University of Denmark, 2004.
    [5]
    MERWE R, WAN E. Sigma-point Kalman filters for probabilistic inference in dynamic state-space models[D]. Portland: Oregon Health and Science University, 2004.
    [6]
    WU Yuan-xin, HU De-wen, WU Mei-ping, et al. An numerical-integration perspective on Guassian filters[J]. IEEE Transactions on Signal Processing, 2006, 54(8): 2910-2921. doi: 10.1109/TSP.2006.875389
    [7]
    ARASARATNAM I, HAYKIN S. Cubature Kalman filters[J]. IEEE Transactions on Automatic Control, 2009, 54(6): 1254-1269. doi: 10.1109/TAC.2009.2019800
    [8]
    ARASARATNAM I. Cubature Kalman filtering: theory and applications[D]. Hamilton: McMaster University, 2009.
    [9]
    FEMANDEZ-PRADES C, VILA-VALLS J. Bayesian nonlinear filtering using quadrature and cubature rules applied to sensor data fusion for positioning[C]∥IEEE. 2010 IEEE International Conference on Communications. Cape Town: IEEE, 2010: 1-5.
    [10]
    LIU Jiang, CAI Bai-gen, TANG Tao, et al. A CKF based GNSS/INS train integrated positioning method[C]∥IEEE. 2010 International Conference on Mechatronics and Automation. Xi'an: IEEE, 2010: 1686-1689.
    [11]
    PESONEN H, PICHE R. Cubature-based Kalman filters for positioning[C]∥IEEE. Proceedings of the 7th Workshop on Positioning, Navigation and Communication. Dresden: IEEE, 2010: 45-49.
    [12]
    LI Wen-ling, JIA Ying-ming. Location of mobile station with maneuvers using an IMM-based cubature Kalman filter[J]. IEEE Transactions on Industrial Electronics, 2012, 59(11): 4338-4348. doi: 10.1109/TIE.2011.2180270
    [13]
    鹿传国, 冯新喜, 张迪. 基于改进容积卡尔曼滤波的纯方位目标跟踪[J]. 系统工程与电子技术, 2012, 34(1): 28-33. https://www.cnki.com.cn/Article/CJFDTOTAL-XTYD201201005.htm

    LU Chuan-guo, FENG Xin-xi, ZHANG Di. Pure bearing tracking based on improved cubature Kalman filter[J]. Systems Engineering and Electronics, 2012, 34(1): 28-33. (in Chinese) https://www.cnki.com.cn/Article/CJFDTOTAL-XTYD201201005.htm
    [14]
    SHUSTER M D. Survey of attitude representations[J]. Journal of the Astronautical Sciences, 1993, 41(4): 439-517.
    [15]
    KARLGAARD C, SCHAUB H. Adaptive huber-based filtering using projection statistics: application to spacecraft attitude estimation[C]∥AIAA. 2008 AIAA Guidance, Navigation, and Control Conference. Honolulu: AIAA, 2008: 1-20.
    • Relative Articles
    • Supplements(0)
    • Cited By
  • 加载中

Catalog

    通讯作者: 陈斌, bchen63@163.com
    • 1. 

      沈阳化工大学材料科学与工程学院 沈阳 110142

    1. 本站搜索
    2. 百度学术搜索
    3. 万方数据库搜索
    4. CNKI搜索
    Get Citation
    PDF
    XML

    Article Metrics

    Article views (502) PDF downloads(1437) Cited by()
    Proportional views
    Related

    Copyright《Journal of Traffic and Transportation Engineering》编辑部陕ICP备05001904号-1

    Address ：Editorial Department of Journal of Traffic and Transportation Engineering, Chang 'an University, Middle Section of South Second Ring Road, Xi 'an, Shaanxi（710064） Tel：029-82334388 Email：jygc@chd.edu.cn

    All visit:Today's visit:

    Supported by: Beijing Renhe Information Technology Co. Ltd    

    /

    DownLoad:  Full-Size Img  PowerPoint
    Return
    Return