Performance of a class of adaptive detection algorithms in nonhomogeneous environments

Christ D. Richmond

Research output: Contribution to journalArticlepeer-review

125 Scopus citations


A two-dimensional (2-D) adaptive sidelobe blanker (ASB) detection algorithm was developed through experimentation as an extenuate for false alarms caused by undernulled interference encountered when applying the adaptive matched filter (AMF) in nonhomogeneous environments. The algorithm's utility has been demonstrated empirically. Considering theoretic performance analyses of the ASB detection algorithm as well as the AMF, generalized likelihood ratio test (GLRT), and the adaptive cosine estimator (ACE), under nonideal conditions, can become fairly intractable rather quickly, especially in an adaptive processing context involving covariance estimation. In this paper, however, we have developed and exploited a theoretic framework through which the performance of these algorithms under nonhomogeneous conditions can be examined theoretically. It is demonstrated through theoretic analysis that in the presence of undernulled interference, the ASB is a pliable false alarm regulatory (FAR) detector that maintains good target sensitivity. A viable method of ASB threshold selection is also presented and demonstrated.

Original languageEnglish (US)
Pages (from-to)1248-1262
Number of pages15
JournalIEEE Transactions on Signal Processing
Issue number5
StatePublished - May 2000
Externally publishedYes


  • ACE
  • AMF
  • Adaptive detection
  • Beamforming
  • CFAR
  • False alarms
  • GER
  • GLRT
  • Inhomogeneities
  • Sidelobe blanker
  • Undernulled interference

ASJC Scopus subject areas

  • Signal Processing
  • Electrical and Electronic Engineering


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