Title :
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
fDate :
10/1/2000 12:00:00 AM
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;
Journal_Title :
Aerospace and Electronic Systems, IEEE Transactions on
