• DocumentCode
    3000133
  • Title

    Detection versus False Alarm Characterisation of a Vision-Based Airborne Dim-Target Collision Detection System

  • Author

    Lai, John ; Ford, Jason J. ; Mejias, Luis ; O´Shea, Peter ; Walker, Rodney

  • Author_Institution
    Australian Res. Centre for Aerosp. Autom. (ARCAA), Queensland Univ. of Technol., Brisbane, QLD, Australia
  • fYear
    2011
  • fDate
    6-8 Dec. 2011
  • Firstpage
    448
  • Lastpage
    455
  • Abstract
    This paper presents a preliminary flight test based detection range versus false alarm performance characterisation of a morphological-hidden Markov model filtering approach to vision-based airborne dim-target collision detection. On the basis of compelling in-flight collision scenario data, we calculate system operating characteristic (SOC) curves that concisely illustrate the detection range versus false alarm rate performance design trade-offs. These preliminary SOC curves provide a more complete dim-target detection performance description than previous studies (due to the experimental difficulties involved, previous studies have been limited to very short flight data sample sets and hence have not been able to quantify false alarm behaviour). The preliminary investigation here is based on data collected from 4 controlled collision encounters and supporting non-target flight data. This study suggests head-on detection ranges of approximately 2.22 km under blue sky background conditions (1.26 km in cluttered background conditions), whilst experiencing false alarms at a rate less than 1.7 false alarms/hour (ie. less than once every 36 minutes). Further data collection is currently in progress.
  • Keywords
    aerospace computing; aerospace testing; autonomous aerial vehicles; collision avoidance; filtering theory; hidden Markov models; object detection; robot vision; Machine vision; data collection; detection characterisation; dim-target detection performance description; false alarm characterisation; false alarm rate performance design trade-offs; in-flight collision scenario data; morphological-hidden Markov model filtering approach; system operating characteristic curves; test based detection range; unmanned aerial vehicle airborne collision avoidance problem; vision-based airborne dim-target collision detection system; Aircraft; Cameras; Clouds; Hidden Markov models; Object detection; Sensors; System-on-a-chip; collision; detection; false alarm; hidden Markov model; morphology; vision;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Digital Image Computing Techniques and Applications (DICTA), 2011 International Conference on
  • Conference_Location
    Noosa, QLD
  • Print_ISBN
    978-1-4577-2006-2
  • Type

    conf

  • DOI
    10.1109/DICTA.2011.82
  • Filename
    6128759