Accession Number:

ADA256896

Title:

Algorithms for Optimum Detection of Signals in Gaussian Noise

Descriptive Note:

Technical rept.

Corporate Author:

NORTH CAROLINA UNIV AT CHAPEL HILL DEPT OF STATISTICS

Personal Author(s):

Report Date:

1991-03-01

Pagination or Media Count:

34.0

Abstract:

Algorithms are presented for detection of signals in Gaussian noise. The signals can be Gaussian or nonGaussian. The algorithms are derived from a general solution to the continuous-time problem, and are approximations to the continuous-time likelihood ratio. They do not require knowledge of the probability distributions for the signal-plus-noise process, but instead require knowledge or estimation of a function. Independent sampling is not assumed. One algorithm is fully adaptive to the signal-plus-noise process. The algorithms have the potential of providing significant performance improvements, as compared to classical detection methods, when the signal-plus-noise process is broadband stationary or nonstationary, and particularly when it is nonGaussian.

Subject Categories:

  • Acoustic Detection and Detectors
  • Electricity and Magnetism

Distribution Statement:

APPROVED FOR PUBLIC RELEASE