Investigation of 1D and 2D PCA for SAR ATR

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, 1D and 2D PCA has been exploited in the present paper for SAR ATR. 2D PCA based algorithm has been fine-tuned for the current usage. Contrary to the conclusions in face-recognition research, here it has been concluded that both 2D and 1D PCA perform equally well for SAR ATR. And both the algorithms outperform the conventional SAR ATR algorithms.