• DocumentCode
    1749411
  • Title

    Wavelets in the frequency domain for narrowband process detection

  • Author

    Willett, Peter ; Wang, Zhen ; Streit, Roy

  • Author_Institution
    Connecticut Univ., Storrs, CT, USA
  • Volume
    5
  • fYear
    2001
  • fDate
    2001
  • Firstpage
    3193
  • Abstract
    Detecting signals that are long, weak, and narrowband is a well known and important problem in acoustic signal processing. In this paper an ad hoc scheme is developed: its stages include the DFT, a multiresolution decomposition in the frequency domain, and a GLRT. The computational load is light, and the performance is remarkably good. This is so not just in the original narrowband situation, but also, due to an inherent adaptivity to the data, in the detection of signals that are relatively broadband in nature. Generalizations are given to CFAR operation in both prewhitened and unwhitened cases, and to the detection of multi-band signals. As regards the last, it is discovered that there is little loss from over-estimating the number of bands
  • Keywords
    acoustic signal processing; adaptive signal detection; discrete Fourier transforms; frequency-domain analysis; signal resolution; wavelet transforms; DFT; GLRT; acoustic signal processing; adaptive signal detection; computational load; frequency domain; multi-band signal detection; multiresolution decomposition; narrowband process detection; wavelets; Acoustic signal detection; Bandwidth; Detectors; Frequency domain analysis; Maximum likelihood detection; Narrowband; Signal detection; Signal processing; Testing; Wavelet domain;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Acoustics, Speech, and Signal Processing, 2001. Proceedings. (ICASSP '01). 2001 IEEE International Conference on
  • Conference_Location
    Salt Lake City, UT
  • ISSN
    1520-6149
  • Print_ISBN
    0-7803-7041-4
  • Type

    conf

  • DOI
    10.1109/ICASSP.2001.940337
  • Filename
    940337