VI-CFAR: a novel CFAR algorithm based on data variability

Michael E. Smith, Pramod Kumar Varshney

Research output: Chapter in Book/Report/Conference proceedingConference contribution

29 Scopus citations

Abstract

The VI-CFAR processor performs adaptive threshold target detection using a composite approach based on the well known CA-CFAR, SO-CFAR, and GO-CFAR background estimation algorithms. After envelope detection, radar range samples are stored in a tapped delay line such that a test cell is surrounded on either side by a set of reference cells. The VI-CFAR dynamically chooses either the leading reference cells, the lagging reference cells, or the combined leading and lagging reference cells for background noise/clutter power estimation. Selection of the reference cells and the background estimation algorithm is based on the ratio of the means of the two half reference windows and on the 'variability index (VI)' values calculated for the leading and lagging reference windows. The VI is a second-order statistic that is related to the shape parameter. Hypothesis tests based on the variability indices and the mean ratio are used to decide if the environment is homogeneous, contains multiple targets, or contains an extended clutter edge. Based on the decision, the VI-CFAR tailors the background estimation algorithm as discussed. The VI-CFAR processor provides low loss constant false alarm rate performance in a homogeneous environment and also performs robustly in non-homogeneous environments including multiple targets and extended clutter edges.

Original languageEnglish (US)
Title of host publicationIEEE National Radar Conference - Proceedings
Editors Anon
PublisherIEEE Computer Society
Pages263-268
Number of pages6
StatePublished - 1997
Externally publishedYes
EventProceedings of the 1997 IEEE National Radar Conference - Syracuse, NY, USA
Duration: May 13 1997May 15 1997

Other

OtherProceedings of the 1997 IEEE National Radar Conference
CitySyracuse, NY, USA
Period5/13/975/15/97

ASJC Scopus subject areas

  • Electrical and Electronic Engineering

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  • Cite this

    Smith, M. E., & Varshney, P. K. (1997). VI-CFAR: a novel CFAR algorithm based on data variability. In Anon (Ed.), IEEE National Radar Conference - Proceedings (pp. 263-268). IEEE Computer Society.