Abstract
This document analyses the performance of subspace signal processing techniques applied to ground penetrating radar (GPR) images in order to reduce the amount of clutter and noise in the measured GPR image. Two methods considered in this work are Principal Component Analysis (PCA) and Independent Component Analysis (ICA). An approach to combine those two techniques to improve their effectiveness when applied to GPR data is proposed in this paper. The experiments performed to gather GPR data and evaluate proposed algorithms are also described. The aim of undertaken experiments is to replicate conditions found in water reservoirs where cracks and holes in the reservoir foundations and joints cause excessive water leakages and losses to water companies and the UK economy in general. Performance of implemented algorithms is discussed and compared to the results achieved by a highly skilled human - GPR image analyst.© (2012) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
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