• DocumentCode
    311192
  • Title

    Adaptive detector statistics using moment-based approximations

  • Author

    Smith, Steven T.

  • Author_Institution
    Lincoln Lab., MIT, Lexington, MA, USA
  • fYear
    1996
  • fDate
    3-6 Nov. 1996
  • Firstpage
    1118
  • Abstract
    Adaptive filtering techniques are used for many detection applications such as communications and radar, yet the complicated statistics of adaptive detectors frustrate a closed form analysis of their performance. This paper offers a partial solution to this problem by providing closed form moments of the adaptive matched filter (AMF) and generalized likelihood ratio test (GLRT) that can be used in a Laguerre series expansion to efficiently complete the probabilities of detection and false alarm of these adaptive detectors. The radar case is considered in particular. Furthermore, exact closed form statistics of the AMF are given which are convenient for probability of false alarm computations and describing the asymptotic behavior of this test.
  • Keywords
    adaptive filters; adaptive signal detection; approximation theory; matched filters; method of moments; radar detection; statistical analysis; stochastic processes; Laguerre series expansion; adaptive detector statistics; adaptive filtering techniques; adaptive matched filter; asymptotic behavior; closed form moments; closed form statistics; communications; false alarm; generalized likelihood ratio test; moment-based approximations; probabilities; radar; Adaptive filters; Detectors; Matched filters; Performance analysis; Probability; Radar applications; Radar detection; Statistical analysis; Statistics; Testing;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Signals, Systems and Computers, 1996. Conference Record of the Thirtieth Asilomar Conference on
  • Conference_Location
    Pacific Grove, CA, USA
  • ISSN
    1058-6393
  • Print_ISBN
    0-8186-7646-9
  • Type

    conf

  • DOI
    10.1109/ACSSC.1996.599117
  • Filename
    599117