High resolution radar target identification

Author

Novak, Leslie M. ; Irving, William W. ; Verbout, Shawn M. ; Owirka, Gregory J.

Author_Institution

MIT Lincoln Lab., Lexington, MA, USA

fYear

1992

Firstpage

1048

Abstract

The application of neural networks to the synthetic aperture radar (SAR) automatic target recognition (ATR) problem is discussed. In particular, initial studies investigating the use of an ART-2 self organizing neural-network in a 2-D SAR ATR system are summarized. The performance of the new neural net pattern-matching algorithm is compared with that of the baseline correlation pattern matching algorithm developed previously. This comparison includes evaluating the ability of the pattern matcher to reject nontargets (clutter discretes) and to classify the remaining detections into tank/APC/Howitzer categories

Keywords

feature extraction; image recognition; military systems; neural nets; radar theory; synthetic aperture radar; 2-D SAR ATR system; ART-2 self organizing neural-network; adaptive resonance theory; automatic target recognition; baseline correlation pattern matching; neural networks; pattern-matching algorithm; radar target identification; synthetic aperture radar; tank/APC/Howitzer categories; Clutter; Detectors; Laboratories; Matched filters; Neural networks; Pattern matching; Radar detection; Radar imaging; Synthetic aperture radar; Target recognition;

fLanguage

English

Publisher

ieee

Conference_Titel

Signals, Systems and Computers, 1992. 1992 Conference Record of The Twenty-Sixth Asilomar Conference on

Conference_Location

Pacific Grove, CA

ISSN

1058-6393

Print_ISBN

0-8186-3160-0

Type

conf

DOI

10.1109/ACSSC.1992.269138

Filename

269138