• DocumentCode
    1490606
  • Title

    Distributed signal detection under the Neyman-Pearson criterion

  • Author

    Yan, Qing ; Blum, Rick S.

  • Author_Institution
    Dept. of Electr. Eng. & Comput. Sci., Lehigh Univ., Bethlehem, PA, USA
  • Volume
    47
  • Issue
    4
  • fYear
    2001
  • fDate
    5/1/2001 12:00:00 AM
  • Firstpage
    1368
  • Lastpage
    1377
  • Abstract
    A procedure for finding the Neyman-Pearson optimum distributed sensor detectors for cases with statistically dependent observations is described. This is the first valid procedure we have seen for this case. This procedure is based on a theorem proven in this paper. These results clarify and correct a number of possibly misleading discussions in the existing literature. Cases with networks of sensors in fairly general configurations are considered along with cases where the sensor detectors make multiple bit sensor decisions
  • Keywords
    distributed processing; optimisation; signal detection; Neyman-Pearson criterion; distributed signal detection; multiple bit sensor decisions; optimum distributed sensor detectors; statistically dependent observations; theorem; Detectors; Probability; Random variables; Sensor fusion; Sensor phenomena and characterization; Signal design; Signal detection; Statistical analysis; Testing; Topology;
  • fLanguage
    English
  • Journal_Title
    Information Theory, IEEE Transactions on
  • Publisher
    ieee
  • ISSN
    0018-9448
  • Type

    jour

  • DOI
    10.1109/18.923720
  • Filename
    923720