Even though ground penetrating radar data signal processing has already been studied by many researchers, more research is needed and expected from automatic ground penetrating radar data analysis. An automatic band-pass filtering procedure can lead to sufficient real-time data interpretation as signal buried in noise could be amplified. Ground penetrating radar traces are highly non stationary, requiring time-varying processing techniques. An algorithm, based on self-inverse filtering, which is a special case of inverse filtering, was implemented. It is a ground penetrating radar trace filtering approach and is implemented by applying inverse filtering in each time sample in the time-frequency domain. Applied on a synthetic trace, this algorithm performed better than a stationary band-pass filter and empirical mode decomposition family methods, whereas its application on real ground penetrating radar data from two different sites enhanced reflections buried in noise without the need to test different high-frequency band stops and with minimum distortion of the signal and the initial temporal resolution of the data.
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