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Optical Engineering

Composite filters for inverse synthetic aperture radar classification of small ships
Author(s): Chao Yuan; David P. Casasent
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Paper Abstract

Pattern recognition of small ship inverse synthetic aperture radar (ISAR) images is considered. This represents a formidable new distortion-invariant pattern recognition problem. New weighted correlation range alignment and weighted multiple-scatterer motion compensation variations to standard image formation steps were developed and used. A new algorithm to determine if an input image is useful was developed and found to be necessary for small ship ISAR data. Initial recognition results using distortion-invariant (composite) filters are presented. These provide new concepts including: use of a validation set and a goodness measure to select filter parameters, use of new output criteria for which a filter in a bank of filters is best for class determination, rejection of decisions on some poor test input images, and use of voting over a time sequence of test inputs.

Paper Details

Date Published: 1 January 2002
PDF: 11 pages
Opt. Eng. 41(1) doi: 10.1117/1.1425789
Published in: Optical Engineering Volume 41, Issue 1
Show Author Affiliations
Chao Yuan, Carnegie Mellon Univ. (United States)
David P. Casasent, Carnegie Mellon Univ. (United States)


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