• DocumentCode
    2493940
  • Title

    Joint PDF construction for sensor fusion and distributed detection

  • Author

    Kay, S. ; Quan Ding ; Emge, D.

  • Author_Institution
    Dept. of Electr., Comput., & Biomed. Eng., Univ. of Rhode Island, Kingston, RI, USA
  • fYear
    2010
  • fDate
    26-29 July 2010
  • Firstpage
    1
  • Lastpage
    6
  • Abstract
    A novel method of constructing a joint PDF under H1, when the joint PDF under H0 is known, is developed. It has direct application in distributed detection systems. The construction is based on the exponential family and it is shown that asymptotically the constructed PDF is optimal. The generalized likelihood ratio test (GLRT) is derived based on this method for the partially observed linear model. Interestingly, the test statistic is equivalent to the clairvoyant GLRT, which uses the true PDF under H1, even if the noise is non-Gaussian.
  • Keywords
    probability; sensor fusion; signal detection; distributed detection systems; generalized likelihood ratio test; joint PDF construction; partially observed linear model; probability density function; sensor fusion; Biomedical measurements; Gaussian noise; Joints; Maximum likelihood estimation; Probability density function; Vectors; Distributed detection; Gaussian mixture; data fusion; exponential family; joint PDF;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Information Fusion (FUSION), 2010 13th Conference on
  • Conference_Location
    Edinburgh
  • Print_ISBN
    978-0-9824438-1-1
  • Type

    conf

  • DOI
    10.1109/ICIF.2010.5711848
  • Filename
    5711848
    • Link To Document
    https://search.isc.ac/dl/search/defaultta.aspx?DTC=49&DC=2493940