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Proceedings Paper

Optimal trade-off distance classifier correlation filters (OTDCCFs) for synthetic aperture radar automatic target recognition (SAR ATR)
Author(s): Daniel W. Carlson; Bhagavatula Vijaya Kumar; Robert R. Mitchell; Michael Hoffelder
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Paper Abstract

Recent developments in optimal trade-off based composite correlation filter methods have improved the recognition and classification of an object over a range of image distortions. We extend the capability of the distance classifier correlation filter introduced by Mahalanobis et al by using he optimal trade-off between different correlation criteria. These correlation filters can be used for the automatic target cueing or recognition of synthetic aperture radar (SAR) images. In this paper we will present results of designing these distortion-tolerant filters with simulated SAR imagery and testing with simulated SAR target images inserted into real SAR backgrounds.

Paper Details

Date Published: 28 July 1997
PDF: 11 pages
Proc. SPIE 3070, Algorithms for Synthetic Aperture Radar Imagery IV, (28 July 1997); doi: 10.1117/12.281548
Show Author Affiliations
Daniel W. Carlson, Hughes Missile Systems Co. (United States)
Bhagavatula Vijaya Kumar, Carnegie Mellon Univ. (United States)
Robert R. Mitchell, Northrop Grumman Corp. (United States)
Michael Hoffelder, Northrop Grumman Corp. (United States)

Published in SPIE Proceedings Vol. 3070:
Algorithms for Synthetic Aperture Radar Imagery IV
Edmund G. Zelnio, Editor(s)

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