Performance of 10- and 20-target MSE classifiers

Author

Novak, Leslie M. ; Owirka, Gregory J. ; Brower, William S.

Author_Institution

Lincoln Lab., MIT, Lexington, MA, USA

Volume

36

Issue

4

fYear

2000

fDate

10/1/2000 12:00:00 AM

Firstpage

1279

Lastpage

1289

Abstract

MIT Lincoln Laboratory is responsible for developing the ATR (automatic target recognition) system for the DARPA-sponsored SAIP program; the baseline ATR system recognizes 10 GOB (ground order of battle) targets; the enhanced version of SAIP requires the ATR system to recognize 20 GOB targets. This paper presents ATR performance results for 10- and 20-target mean square error (MSE) classifiers using high-resolution SAR (synthetic aperture radar) imagery.

Keywords

image classification; learning (artificial intelligence); mean square error methods; radar computing; radar imaging; radar target recognition; synthetic aperture radar; ATR performance; automatic target recognition system; confusion matrices; extended operating conditions; ground order of battle targets; high-resolution SAR imaging; spotlight mode; target MSE classifiers; template-based classifiers; training images; Fast Fourier transforms; Image resolution; Image sensors; Laboratories; Mean square error methods; Sensor systems; Synthetic aperture radar; Target recognition; Testing; US Government;

fLanguage

English

Journal_Title

Aerospace and Electronic Systems, IEEE Transactions on

Publisher

ieee

ISSN

0018-9251

Type

jour

DOI

10.1109/7.892675

Filename

892675