Depth estimation of buried objects using wavelet transform and statistical hypothesis testing

In the underground inspection problem, signature of a big target at a certain depth may give equivalent information to the signature of a smaller target at shallower depth, unless depth information is not used. This results in a difficulty in the identification process. Therefore, depth information is coming into prominence in the classification step to increase the identification performance. In this study, we propose a burial depth estimation method on GPR data. In our work, discrete wavelet transform is used in the preprocessing step. After this stage, statistical hypothesis tests are utilized to detect the statistical discrepancies in the returning signals at different depth levels.