@inproceedings{7e930ef70fda4bb09a83748122669a3f,
title = "Investigation of 1D and 2D PCA for SAR ATR",
abstract = "Principal component analysis (PCA) has been used in many applications ranging from social science to space science, for the purpose of data compression and feature extraction. Usage of PCA for synthetic aperture radar (SAR) image classification, have recently been exploited by the automatic target recognition (ATR) community. PCA can be used in one dimensional as well as two dimensional mode. These different modes have recently been studied for face recognition. Following similar trends, 10 and 20 PCA has been exploited in the present paper for SAR ATR. 20 PCA based algorithm has been fine-tuned for the current usage. Contrary to the conclusions in facerecognition research, here it has been concluded that both 20 and 10 PCA perform equally well for SAR ATR. And both the algorithms outperform the conventional SAR ATR algorithms.",
author = "Mishra, \{A. K.\}",
year = "2009",
month = dec,
day = "14",
doi = "10.1109/AEMC.2009.5430578",
language = "English",
isbn = "9781424448197",
series = "Applied Electromagnetics Conference, AEMC 2009 and URSI Commission B Meeting",
publisher = "Institute of Electrical and Electronics Engineers",
booktitle = "Applied Electromagnetics Conference, AEMC 2009 and URSI Commission B Meeting",
address = "United States of America",
note = "Applied Electromagnetics Conference, AEMC 2009 and URSI Commission B Meeting ; Conference date: 14-12-2009 Through 16-12-2009",
}