A primary study of independent component analysis for GPR signal processing

Ground penetrating radar(GPR) signal processing has all along been a hard task because of its poor signal-to-noise ratio(SNR) of the raw GPR signals and almost "blind" about the latent targets what we want to detect beforehand.A new approach that uses Independent Component Analysis(ICA),a newly developing blind signal processing(BSP) technique,to GPR signal processing has been proposed in this paper.With the help of FastICA algorithm,it has successfully extracted quite weak target signals from the raw GPR data with much strong background.So the SNR of the GPR signal and the detection performance of the GPR have both improved greatly.The ambiguities of rightly sequencing and the sign uncertainty problems of separated target signal components in ICA practical use have also been overcome.Two examples,FDTD simulated and field-test GPR data for local targets,such as landmines and underground pipelines,to be processed by FastICA,are included to demonstrate the effectiveness of the approach.Quite ideal results are got from them.