Threshold setting for adaptive matched filter and adaptive coherence estimator

Jun Liu, Hongbin Li, Braham Himed

Research output: Contribution to journalArticlepeer-review

14 Scopus citations

Abstract

It is known that the probabilities of false alarm (PFAs) of several celebrated adaptive detectors including the adaptive matched filter (AMF) and the adaptive coherence estimator (ACE) can be expressed as integral forms. Nevertheless, it is inconvenient to set the detection thresholds by using these integral expressions. Here, we propose two computationally efficient schemes to calculate the thresholds of the AMF and ACE. In the first method, approximate expressions, in forms of elementary functions, for the PFAs of the AMF and ACE are derived. The thresholds of the AMF and ACE can be numerically computed by using these elementary expressions instead of the integrals, for reducing computational complexity. In the second approach, further approximations are employed to lead to highly simple expressions for the thresholds of the AMF and ACE, which enable us to directly compute the thresholds for a given PFA. Compared to the first one, the second scheme is more computationally efficient, but at the cost of a slight loss in accuracy. Numerical results verify the effectiveness of the two proposed schemes.

Original languageEnglish
Article number6875898
Pages (from-to)11-15
Number of pages5
JournalIEEE Signal Processing Letters
Volume22
Issue number1
DOIs
StatePublished - Jan 2015

Keywords

  • Adaptive coherence estimator
  • Laplace approximation
  • Rao test
  • adaptive detection
  • adaptive matched filter
  • generalized likelihood ratio test

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