• DocumentCode
    1459948
  • Title

    Adaptive detection for unknown noise power spectral densities

  • Author

    Kay, Steven

  • Author_Institution
    Dept. of Electr. & Comput. Eng., Rhode Island Univ., Kingston, RI, USA
  • Volume
    47
  • Issue
    1
  • fYear
    1999
  • fDate
    1/1/1999 12:00:00 AM
  • Firstpage
    10
  • Lastpage
    21
  • Abstract
    The detection of a known broadband signal in colored noise of unknown power spectral density is addressed. Motivated by the consistency of the integrated periodogram, a new detector is proposed. Its asymptotic performance is proven to be only slightly poorer than the optimal but unrealizable Neyman-Pearson detector. It also possesses the CFAR property asymptotically and should therefore be quite valuable in practice. For finite data records, it is shown by computer simulation to significantly outperform the conventional matched filter (without prewhitening) under realistic conditions encountered in practice
  • Keywords
    Gaussian noise; adaptive signal detection; spectral analysis; CFAR property; adaptive detection; asymptotic performance; broadband signal; colored noise; finite data records; integrated periodogram; unknown noise power spectral densities; Autocorrelation; Colored noise; Computer simulation; Detectors; Gaussian noise; Helium; Matched filters; Narrowband; Statistical analysis; Testing;
  • fLanguage
    English
  • Journal_Title
    Signal Processing, IEEE Transactions on
  • Publisher
    ieee
  • ISSN
    1053-587X
  • Type

    jour

  • DOI
    10.1109/78.738235
  • Filename
    738235