• DocumentCode
    1301147
  • Title

    Detection of weak random signals in IID non-Gaussian noise

  • Author

    Kolodziejski, Kevin R. ; Betz, John W.

  • Author_Institution
    Mitre Corp., Bedford, MA, USA
  • Volume
    48
  • Issue
    2
  • fYear
    2000
  • fDate
    2/1/2000 12:00:00 AM
  • Firstpage
    222
  • Lastpage
    230
  • Abstract
    This paper considers the detection of weak random signals in circularly symmetric, independent, identically distributed noise. Locally optimum detectors and ad hoc nonlinearities are considered, with asymptotic expressions provided for evaluation of detection performance. The analytical expressions are used to evaluate the robustness of detectors to mismatch in the noise models. Finite-sample Monte Carlo simulation results indicate the reliability of these asymptotic measures in cases of practical interest. The results show that, as has been found for detection of weak known signals in non-Gaussian noise, reasonably configured ad hoc nonlinearities are nearly optimum and robust to modest errors in the noise statistics
  • Keywords
    Monte Carlo methods; noise; optimisation; random processes; signal detection; statistical analysis; ad hoc nonlinearities; analytical expressions; asymptotic expressions; asymptotic measures reliability; circularly symmetric independent identically distributed noise; detection performance; detector robustness; finite-sample Monte Carlo simulation results; i.i.d. nonGaussian noise; locally optimum detectors; noise models; noise statistics; weak random signals detection; Acoustic signal detection; Additive noise; Detectors; Gaussian noise; Noise robustness; Signal detection; Signal processing; Statistical analysis; Statistics; Testing;
  • fLanguage
    English
  • Journal_Title
    Communications, IEEE Transactions on
  • Publisher
    ieee
  • ISSN
    0090-6778
  • Type

    jour

  • DOI
    10.1109/26.823555
  • Filename
    823555