OS Characterization for Local CFAR Detection

Kevin D. Donohue

Research output: Contribution to journalArticlepeer-review

4 Scopus citations


An order statistic (OS) characterization for modeling clutter statistics at local detectors is presented. Important features of the OS characterization include its structure, allowing for parallel computations, and its degrees of freedom, which enable it to track various changes in the clutter statistics. Constant false alarm rate (CFAR) performance for local detectors designed from the OS characterization is compared to conventional CFAR detectors that operate locally at each receiver. The results demonstrate the ability of the local OS detectors to adapt to changes in the skewness of the clutter distribution. For the cases tested, the local OS detectors maintain the expected value for the false alarm probability better than the local conventional CFAR detectors by factors ranging from 2 to 100. OS detectors also provide information to the data fusion center that can be useful in discriminating different types of interference and detecting small targets in clutter. Examples of utilizing OS detections at the data fusion center are discussed.

Original languageEnglish
Pages (from-to)1212-1216
Number of pages5
JournalIEEE Transactions on Systems, Man and Cybernetics
Issue number5
StatePublished - 1991

Bibliographical note

Funding Information:
Manuscript received August 24, 1990; revised March 1, 1991. This work was supported by the SDIO/IST managed by the Office of Naval Research under Contract N000014-86-K-0520. K.D. Donohue was with the Drexel University, Philadelphia, PA. He is now with the Department of Electrical Engineering, University of Kentucky, 453 Anderson Hall, Lexington, KY 40506-0046. N.M. Bilgutay is with the Department of Electrical and Computer Engineering, Drexel University, Philadelphia, PA, 19104. IEEE Log Number 9102029.

ASJC Scopus subject areas

  • Engineering (all)


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