Most navigation systems currently operated by NASA are ground-based, and require extensive support to produce accurate results. Recently developed systems that use Kalman filter and GPS data for orbit determination greatly reduce dependency on ground support, and have potential to provide significant economies for NASA spacecraft navigation. These systems, however, still rely on manual tuning from analysts. A sophisticated neuro-fuzzy component fully integrated with the flight navigation system can perform the self-tuning capability for the Kalman filter and help the navigation system recover from estimation errors in real time.


    Zugriff

    Zugriff über TIB

    Verfügbarkeit in meiner Bibliothek prüfen


    Exportieren, teilen und zitieren



    Titel :

    A Self-Tuning Kalman Filter for Autonomous Navigation using the Global Positioning System (GPS)


    Beteiligte:
    Truong, S. H. (Autor:in)


    Erscheinungsdatum :

    01.05.1999


    Medientyp :

    Aufsatz (Konferenz)


    Format :

    Keine Angabe


    Sprache :

    Englisch




    A Self-Tuning Kalman Filter for Autonomous Navigation Using the Global Positioning System (GPS)

    Truong, S. / United States; National Aeronautics and Space Administration | British Library Conference Proceedings | 1999




    Dynamic ship positioning using a self-tuning Kalman filter

    Fung, P.T. / Grimble, M.J. | Tema Archiv | 1983


    Correction of autonomous navigation systems using the Kalman filter

    Neusypin, K. A. / Selezneva, M. S. / Huong, Truong Ngoc et al. | American Institute of Physics | 2019