A GLRT for multichannel radar detection in the presence of both compound Gaussian clutter and additive white Gaussian noise

Bin Liu, Biao Chen, James H. Michels

Research output: Contribution to journalArticle

10 Scopus citations

Abstract

Motivated by multichannel radar detection applications in the presence of both white Gaussian noise and Gaussian clutter with unknown power, we develop maximum likelihood parameter estimates for the disturbance process. Both cases with known and unknown white noise variance are treated. As the estimators do not admit closed-form solutions, numerical iterative procedures are developed that are guaranteed to at least converge to the local maximum. The developed estimates allow us to construct a generalized likelihood ratio test (GLRT) for the detection of a signal with constant but unknown amplitude. This GLRT has important applications in multichannel radar detection involving both white Gaussian noise and spherically invariant random process clutter and is shown to have better detection performance and CFAR property compared with existing statistics.

Original languageEnglish (US)
Pages (from-to)437-454
Number of pages18
JournalDigital Signal Processing: A Review Journal
Volume15
Issue number5
DOIs
StatePublished - Sep 2005

Keywords

  • Generalized likelihood ratio test
  • Maximum likelihood estimate
  • Multichannel radar detection
  • Spherically invariant random processes

ASJC Scopus subject areas

  • Signal Processing
  • Electrical and Electronic Engineering

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