NASA Goddard Space Flight Center is developing Autonomous Navigation Guidance and Control (autoNGC) as a flight software system for future onboard use for missions in a variety of orbital regimes, including cislunar space and beyond. This paper describes processor-in-the-loop (PIL) testing using a lunar landing scenario with terrain relative navigation (TRN) and weak-signal GPS. We give an overview of the autoNGC project and describe preliminary navigation simulation results. We also describe the TRN PIL tests on a flight-like development board, using simulated images rendered from Lunar Reconnaissance Orbit high-resolution digital terrain models. The navigation simulations show that weak-signal GPS combined with TRN during a descent from a low lunar parking orbit results in sufficiently low navigation uncertainties to support such a mission profile independent of ground-based navigation. The PIL tests show that onboard image processing and landmark correlation is achievable at a sufficiently high measurement rate.


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    Titel :

    Terrain Relative Navigation in a Lunar Landing Scenario Using autoNGC


    Beteiligte:
    Michael A Shoemaker (Autor:in) / Sun Hur-Diaz (Autor:in) / Andrew J Liounis (Autor:in) / John M Van Eepoel (Autor:in) / Michael J Romeo (Autor:in) / Victoria C Wu (Autor:in) / Sarah D Dangelo (Autor:in) / Noble Hatten (Autor:in) / Lauren G Schlenker (Autor:in) / Steven P Hughes (Autor:in)

    Kongress:

    AIAA SciTech Forum and Exposition ; 2022 ; Virtual, US



    Erscheinungsdatum :

    2022-01-03


    Medientyp :

    Aufsatz (Konferenz)


    Format :

    Keine Angabe


    Sprache :

    Englisch




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