The Miniaturised Asteroid Remote Geophysical Observer (M-ARGO) mission is designed to be ESA’s first stand-alone CubeSat to independently travel in deep space with its own electric propulsion and direct-to-Earth communication systems in order to rendezvous with a near-Earth asteroid. Deep-space Cubesats are appealing owing to the scaled mission costs. However, the operational costs are comparable to those of traditional missions if ground-based orbit determination is employed. Thus, autonomous navigation methods are required to favour an overall scaling of the mission cost for deep-space CubeSats. M-ARGO is assumed to perform an autonomous navigation experiment during the deep-space cruise phase. This paper elaborates on the deep-space navigation experiment exploiting the line-of-sight directions to visible beacons in the Solar System. The aim is to assess the experiment feasibility and to quantify the performances of the method. Results indicate feasibility of the autonomous navigation for M-ARGO with a 3σ accuracy in the order of 1000 km for the position components and 1 m/s for the velocity components in good observation conditions, utilising miniaturized optical sensors.


    Zugriff

    Download


    Exportieren, teilen und zitieren



    Titel :

    Deep-Space Optical Navigation for M-ARGO Mission


    Weitere Titelangaben:

    J Astronaut Sci


    Beteiligte:
    Franzese, V. (Autor:in) / Topputo, F. (Autor:in) / Ankersen, F. (Autor:in) / Walker, R. (Autor:in)

    Erschienen in:

    Erscheinungsdatum :

    2021-12-01


    Format / Umfang :

    22 pages




    Medientyp :

    Aufsatz (Zeitschrift)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch





    Deep-Space Optical Navigation for M-ARGO Mission

    Franzese, V. / Topputo, F. / Ankersen, F. et al. | BASE | 2021

    Freier Zugriff

    Sustainability of the new Argo mission

    Pouliquen, S. / Thierry, Virginie / Claustre, H. | DataCite | 2019


    Deep Space Mission Design and Navigation

    Guinn, Joseph | NTRS | 2019



    Deep space navigation mission design and analysis tool

    Kolcio, Ksenia / Graven, Paul | IEEE | 2014