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Proceedings Paper

Robust signal detection with nonstandard decision regions
Author(s): Manruth Srisook; Don Halverson; Michael W. Thompson
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Paper Abstract

A reality faced in the practical application of signal detection is the inexact statistical knowledge of the underlying random processes. Accordingly, it is often desirable for a detector to possess robustness. In this paper, we review how the concept of manifold slope can be employed to admit the measurement of robustness thus allowing the degree of robustness to be a factor in the design of the signal detector. We then present new results that show how certain nonstandard decision regions can result in what we term 'negative boundaries' which have the potential to enhance robustness. An example of this approach is provided and the results compared to the classical Huber approach for robust detection.

Paper Details

Date Published: 4 October 1999
PDF: 10 pages
Proc. SPIE 3809, Signal and Data Processing of Small Targets 1999, (4 October 1999); doi: 10.1117/12.364054
Show Author Affiliations
Manruth Srisook, Texas A&M Univ. (United States)
Don Halverson, Texas A&M Univ. (United States)
Michael W. Thompson, Univ. of Texas/Pan American (United States)

Published in SPIE Proceedings Vol. 3809:
Signal and Data Processing of Small Targets 1999
Oliver E. Drummond, Editor(s)

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