Consistent CFAR detection of a linear signal based on partially consistent observations

Jonathan Friedmann, Hagit Messer

Research output: Contribution to journalArticlepeer-review


This letter addresses the problem of consistent constant false-alarm rate (CFAR) detection based on partially consistent observations. The term "partially consistent observations" refers to the fact that the number of unknown parameters increases with the number of samples, and therefore, the number of observed samples is insufficient for consistent estimation of all parameters. Specifically, the problem of detecting a deterministic signal with unknown linear parameters in nonstationary white Gaussian noise is addressed. Two families of CFAR detectors are proposed; their consistency is discussed; and their performance is examined.

Original languageEnglish
Pages (from-to)237-240
Number of pages4
JournalIEEE Signal Processing Letters
Issue number8
StatePublished - Aug 2002
Externally publishedYes


  • Constant false-alarm rate (CFAR) detection
  • Nonstationary noise
  • Partially consistent observations


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