On the False Alarm Rate of Adaptive Detection Algorithms for Channel Matrix-Based Cognitive Radar/Sonar

Touseef Ali, Douglas Cochran, Christ D. Richmond

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

Abstract

In this work, we derive an analytical expression for the probability of false alarm for the generalized likelihood ratio test (GLRT) in the channel matrix-based sonar/radar framework when the waveform-independent colored noise (WICN) covariance is assumed known. The derived expression is independent of the noise covariance and proves that the GLRT exhibits the constant probability of false alarm (CFAR) property. Monte Carlo simulations are performed to check the validity of the derived expression.

Original languageEnglish (US)
Title of host publication56th Asilomar Conference on Signals, Systems and Computers, ACSSC 2022
EditorsMichael B. Matthews
PublisherIEEE Computer Society
Pages1126-1130
Number of pages5
ISBN (Electronic)9781665459068
DOIs
StatePublished - 2022
Event56th Asilomar Conference on Signals, Systems and Computers, ACSSC 2022 - Virtual, Online, United States
Duration: Oct 31 2022Nov 2 2022

Publication series

NameConference Record - Asilomar Conference on Signals, Systems and Computers
Volume2022-October

Conference

Conference56th Asilomar Conference on Signals, Systems and Computers, ACSSC 2022
Country/TerritoryUnited States
CityVirtual, Online
Period10/31/2211/2/22

Keywords

  • cognitive radar
  • false alarm rate
  • generalized likelihood ratio test

ASJC Scopus subject areas

  • Signal Processing
  • Computer Networks and Communications

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