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Proceedings Paper

Expert system constant false alarm rate processor
Author(s): William J. Baldygo; Michael C. Wicks
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Paper Abstract

The requirements for high detection probability and low false alarm probability in modern wide area surveillance radars are rarely met due to spatial variations in clutter characteristics. Many filtering and CFAR detection algorithms have been developed to effectively deal with these variations; however, any single algorithm is likely to exhibit excessive false alarms and intolerably low detection probabilities in a dynamically changing environment. A great deal of research has led to advances in the state of the art in Artificial Intelligence (AI) and numerous areas have been identified for application to radar signal processing. The approach suggested here, discussed in a patent application submitted by the authors, is to intelligently select the filtering and CFAR detection algorithms being executed at any given time, based upon the observed characteristics of the interference environment. This approach requires sensing the environment, employing the most suitable algorithms, and applying an appropriate multiple algorithm fusion scheme or consensus algorithm to produce a global detection decision.

Paper Details

Date Published: 22 October 1993
PDF: 12 pages
Proc. SPIE 1954, Signal and Data Processing of Small Targets 1993, (22 October 1993); doi: 10.1117/12.157777
Show Author Affiliations
William J. Baldygo, Rome Lab. (United States)
Michael C. Wicks, Rome Lab. (United States)


Published in SPIE Proceedings Vol. 1954:
Signal and Data Processing of Small Targets 1993
Oliver E. Drummond, Editor(s)

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