Detection in multiple channels having unequal noise power

Songsri Sirianunpiboon, Stephen D. Howard, Douglas Cochran

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

A Bayesian detector is formulated for the problem of detecting a signal of known rank using data collected at multiple sensors. The noise on each sensor channel is white and Gaussian, but its variance is unknown and may be different from channel to channel. A low-SNR assumption that enables approximation of one of the marginalization integrals in the likelihood ratio, yields a tractable approximate Bayesian detector for this regime. Performance of this detector is evaluated and compared to other recently introduced detectors.

Original languageEnglish (US)
Title of host publication2016 19th IEEE Statistical Signal Processing Workshop, SSP 2016
PublisherIEEE Computer Society
Volume2016-August
ISBN (Electronic)9781467378024
DOIs
StatePublished - Aug 24 2016
Event19th IEEE Statistical Signal Processing Workshop, SSP 2016 - Palma de Mallorca, Spain
Duration: Jun 25 2016Jun 29 2016

Other

Other19th IEEE Statistical Signal Processing Workshop, SSP 2016
CountrySpain
CityPalma de Mallorca
Period6/25/166/29/16

Keywords

  • Bayesian detection
  • Multiple-channel detection
  • Uncalibrated receivers

ASJC Scopus subject areas

  • Electrical and Electronic Engineering
  • Applied Mathematics
  • Signal Processing
  • Computer Science Applications

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