Performance of the adaptive sidelobe blanker detection algorithm in homogeneous environments

Christ D. Richmond

Research output: Contribution to journalArticlepeer-review

159 Scopus citations


The adaptive sidelobe blanker (ASB) algorithm is a two-stage detector consisting of a first stage adaptive matched filter (AMF) detector followed by a second-stage detector called the adaptive coherence (or cosine) estimator (ACE). Only those data test cells that survive both detection thresholdings are declared signal (target) bearing. We provide exact novel closed-form expressions for the resulting probability of detection (PD) and false alarm (PFA) for the ASB algorithm and demonstrate that under homogeneous data conditions with no signal array response mismatch that i) the ASB is a constant false alarm rate (CFAR) algorithm, ii) the ASB has a higher or commensurate PD for a given PFA than both the AMF and the ACE, and iii) the ASB has an overall performance that is commensurate with Kelly's benchmark generalized likelihood ratio test (GLRT). A compact statistical summary is derived providing distributions and dependencies among the GLRT, AMF, and the ACE decision statistics.

Original languageEnglish (US)
Pages (from-to)1235-1247
Number of pages13
JournalIEEE Transactions on Signal Processing
Issue number5
StatePublished - May 2000
Externally publishedYes


  • AMF
  • Ace, adaptive detection
  • Beamforming
  • CFAR
  • False alarms
  • GLRT
  • Sidelobe blanker

ASJC Scopus subject areas

  • Signal Processing
  • Electrical and Electronic Engineering


Dive into the research topics of 'Performance of the adaptive sidelobe blanker detection algorithm in homogeneous environments'. Together they form a unique fingerprint.

Cite this