Intelligent CFAR processor based on data variability

Michael E. Smith, Pramod K. Varshney

Research output: Contribution to journalArticlepeer-review

162 Scopus citations

Abstract

An intelligent constant false alarm rate (CFAR) processor to perform adaptive threshold target detection is presented. It employs a composite approach based on the well-known cell averaging CFAR (CA-CFAR), smallest-of CFAR (SO-CFAR), and greatest-of CFAR (GO-CFAR) processors. Data in the reference window is used to compute a second-order statistic called the variability index (VI) and the ratio of the means of the leading and lagging windows. Based on these statistics, the VI-CFAR dynamically tailors the background estimation algorithm. The VI-CFAR processor provides low loss CFAR performance in a homogeneous environment and also performs robustly in nonhomogeneous environments including multiple targets and extended clutter edges.

Original languageEnglish (US)
Pages (from-to)837-847
Number of pages11
JournalIEEE Transactions on Aerospace and Electronic Systems
Volume36
Issue number3 PART 1
DOIs
StatePublished - Dec 1 2000

ASJC Scopus subject areas

  • Aerospace Engineering
  • Electrical and Electronic Engineering

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