This paper deals with monocular image-based aircraft Sense and Avoid for small UAVs. After summarizing previous results of the authors it proposes a complete solution which calculates time to closest point of approach, relative closest point of approach (CPA) and the direction of intruder at CPA. These parameters are enough to make a collision decision and design the avoidance maneuver. The applicability of the proposed solution is demonstrated considering an omnidirectional multi-camera system in an extensive software- in-the-loop test campaign covering the whole possible size and velocity range of manned aircraft as intruder. Straight aircraft paths with constant velocity and camera pixelization errors were considered. Almost 100% decision success was achieved. After the simulations the solution is demonstrated on real flight test data and even in real flight giving 90% avoidance success (10% missed detection) in close and 60% decision success (40% false alarm) in far encounters.


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    Titel :

    Monocular image-based intruder direction estimation at closest point of approach


    Beteiligte:
    Bauer, Peter (Autor:in) / Hiba, Antal (Autor:in) / Bokor, Jozsef (Autor:in)


    Erscheinungsdatum :

    2017-06-01


    Format / Umfang :

    459011 byte




    Medientyp :

    Aufsatz (Konferenz)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch