2-D Entropy and Short-Time Fourier Transform to Leverage GPR Data Analysis Efficiency

Abstract

Accurate detection of singular region using ground-penetrating radar (GPR) is very useful in assessing roadway pavement, bridge deck concrete structure, and railroad ballast conditions. To locate an object within the large radargram involves extensive computational resources and time, especially when the data of interests only possess a small portion of the whole big data set. Therefore, an efficient GPR signal-processing technique is highly demanded. This paper proposes the use of 2-D entropy analysis to narrow down the data scope to the interested regions, which can considerably reduce computational cost for more sophisticated data postprocessing. Joint time-frequency analysis using short-time Fourier transform is then performed for singular region location detection and refinement. The proposed methodology is tested with different laboratory setups. The analysis results show good agreement with physical configurations.