• DocumentCode
    1330002
  • Title

    Signal-to-noise ratio threshold effect in track before detect

  • Author

    Morelande, Mark ; Ristic, Branko

  • Author_Institution
    Dept. of EEE, Univ. of Melbourne, Melbourne, VIC, Australia
  • Volume
    3
  • Issue
    6
  • fYear
    2009
  • fDate
    12/1/2009 12:00:00 AM
  • Firstpage
    601
  • Lastpage
    608
  • Abstract
    Track before detect (TBD) refers to simultaneous detection and tracking using unthresholded sensor responses over time. The motivation for TBD is its capacity to deal with low signal-to-noise ratio (SNR) targets. Previously, the achievable error for TBD has been established using Crameacuteracute-Rao analysis. Although computationally simple the Crameacuteracute-Rao bound is not useful at low SNR as it does not predict the threshold effect. A more accurate notion of the achievable performance at low SNRs is provided by the computationally more complicated Barankin bound. The computational complexity of the Barankin bound arises from the need to optimise over a number of test points, with the tightness of bound increasing with the number of test points. An approximation to the Barankin bound is proposed which permits the use of multiple test points with reasonable computational expense. The improvements in threshold SNR prediction offered by the proposed bound are demonstrated in numerical examples.
  • Keywords
    computational complexity; image segmentation; mean square error methods; object detection; signal detection; target tracking; Barankin bound analysis; CRB; Crameacuteracute-Rao bound analysis; MSE; TBD; approximation theory; computational complexity; mean-squared-error method; multiple test point; numerical example; signal-to-noise ratio threshold effect; target tracking detection algorithm; threshold SNR prediction; track before detect; unthresholded sensor response;
  • fLanguage
    English
  • Journal_Title
    Radar, Sonar & Navigation, IET
  • Publisher
    iet
  • ISSN
    1751-8784
  • Type

    jour

  • DOI
    10.1049/iet-rsn.2009.0017
  • Filename
    5332153