Detection of Weak Signals in Narrowband Non-Gaussian Noise

James W. Modestino, Aaron Y. Ningo

Research output: Contribution to journalArticle

43 Scopus citations

Abstract

A class of nonlinear receiver structures is described for the detection of weak signals in non-Gaussian narrowband noise. In particular, the concept of a locally optimum receiver structure is extended to the case of narrowband signal and noise models. A useful class of non-Gaussian narrowband signal and noise models. A useful class of non-Gaussian narrowband noise models is developed for which the locally optimum receiver implementation is explicitly determined. These structure are shown to provide considerable improvement over conventional linear receiver structures. The basis of comparison is taken as the asymptotic relative efficiency (ARE). Unfortunately, the locally optimum receiver requires explicit a priori knowledge of the underlying noise distribution. To circumvent this difficulty a rather simple adaptive nonlinear receiver structure is described which attempts to adapt to the unknown prevailing noise environment.

Original languageEnglish (US)
Pages (from-to)592-600
Number of pages9
JournalIEEE Transactions on Information Theory
Volume25
Issue number5
DOIs
StatePublished - Sep 1979

ASJC Scopus subject areas

  • Information Systems
  • Computer Science Applications
  • Library and Information Sciences

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