Investigation of 1D and 2D PCA for SAR ATR

Research output: Chapter in Book/Report/Conference proceedingConference Proceeding (Non-Journal item)

1 Citation (Scopus)

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.

Original languageEnglish
Title of host publicationApplied Electromagnetics Conference, AEMC 2009 and URSI Commission B Meeting
PublisherIEEE Press
Number of pages4
ISBN (Print)9781424448197
DOIs
Publication statusPublished - 14 Dec 2009
Externally publishedYes
EventApplied Electromagnetics Conference, AEMC 2009 and URSI Commission B Meeting - Kolkata, India
Duration: 14 Dec 200916 Dec 2009

Publication series

NameApplied Electromagnetics Conference, AEMC 2009 and URSI Commission B Meeting

Conference

ConferenceApplied Electromagnetics Conference, AEMC 2009 and URSI Commission B Meeting
Country/TerritoryIndia
CityKolkata
Period14 Dec 200916 Dec 2009

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