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An Integrated Method of PCA and PSM for Localization of Hyperbolic Signatures in Radargram

This paper describes an integrated method of Principal Component Analysis(PCA) and Phase Shm Migration(PSM) for GPR data processing. The localization of subsurface objects is carried out by PSM. When the migration method is used the image is defocused due to the ground reflections and is tackled by incorporating PCA based on singular value decomposition(SVD). This approach can point out the most prominent singular values corresponding to both clutter and the useful data to filter out the radargram. Apart from that PCA can provide remarkable data compression. The effectiveness of this method 7 is validated by the synthetic data generated by gprMax at different target locations. The results demonstrate that the method generates well localized images.