• DocumentCode
    2790813
  • Title

    Online sensor registration

  • Author

    Vermaak, Jaco ; Maskell, Simon ; Briers, Mark

  • Author_Institution
    Dept. of Eng., Cambridge Univ.
  • fYear
    2005
  • fDate
    5-12 March 2005
  • Firstpage
    2117
  • Lastpage
    2125
  • Abstract
    In a multi-sensor scenario, accurate data fusion is best achieved by processing the measurements from all the sensors at a fusion node to produce tracks. However, inaccuracies in the position and/or rotation of the sensor can lead to "ghost" tracks, particularly when the sensors are not co-located. This paper presents a framework which models the uncertainty over the sensors\´ registration parameter (e.g. position and rotation) and discloses an unscented implementation technique (other methods based on particle filters can be accommodated within our framework), where each sensor self-localises using targets of opportunity. The aim is to solve the sensor registration problem whilst adding minimal overhead to an existing tracker, which is facilitated by making the standard assumption that the state of the joint target factorises over the individual targets
  • Keywords
    particle filtering (numerical methods); sensor fusion; target tracking; uncertainty handling; data fusion; ghost tracks; online sensor registration; particle filters; sensor self-localisation; unscented implementation; Cams; Data engineering; Electrical capacitance tomography; Noise measurement; Notice of Violation; Remotely operated vehicles; Sensor fusion; Uncertainty;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Aerospace Conference, 2005 IEEE
  • Conference_Location
    Big Sky, MT
  • Print_ISBN
    0-7803-8870-4
  • Type

    conf

  • DOI
    10.1109/AERO.2005.1559503
  • Filename
    1559503