• DocumentCode
    1544572
  • Title

    All-purpose and plug-in power-law detectors for transient signals

  • Author

    Wang, Zhen ; Willett, Peter K.

  • Author_Institution
    Dept. of Electr. & Syst. Eng., Connecticut Univ., Storrs, CT, USA
  • Volume
    49
  • Issue
    11
  • fYear
    2001
  • fDate
    11/1/2001 12:00:00 AM
  • Firstpage
    2454
  • Lastpage
    2466
  • Abstract
    A power-law statistic operating on discrete Fourier transform (DFT) data has emerged as a basis for a remarkably robust detector of transient signals having unknown structure, location, and strength. We offer a number of improvements to Nuttall´s (1994) original power-law detector. Specifically, the power-law detector requires that its data be prenormalized and spectrally white; a constant false-alarm rate (CFAR) and self-whitening version is developed and analyzed. Further, it is noted that transient signals tend to be contiguous both in the temporal and frequency sense, and consequently, new power-law detectors in the frequency and the wavelet domains are given. The resulting detectors offer exceptional performance and are extremely easy to implement. There are no parameters to tune. They may be considered “plug-in” solutions to the transient detection problem and are “all-purpose” in that they make minimal assumptions on the structure of the transient signal, save of some degree of agglomeration of energy in time and/or frequency
  • Keywords
    discrete Fourier transforms; frequency-domain analysis; signal detection; transients; wavelet transforms; CFAR; DFT data; all-purpose power-law detector; constant false-alarm rate; discrete Fourier transform; frequency domain; plug-in power-law detector; power-law statistic operating; prenormalized data; saddlepoint approximation; spectrally white data; transient detection; transient signals; wavelet domain; Acoustic signal detection; Detectors; Discrete Fourier transforms; Frequency domain analysis; Medical signal detection; Signal detection; Signal processing; Sonar detection; Statistics; Testing;
  • fLanguage
    English
  • Journal_Title
    Signal Processing, IEEE Transactions on
  • Publisher
    ieee
  • ISSN
    1053-587X
  • Type

    jour

  • DOI
    10.1109/78.960393
  • Filename
    960393