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

A. Burak Yoldemir; Mehmet Sezgin

doi:10.1117/12.852529

29 April 2010 Depth estimation of buried objects using wavelet transform and statistical hypothesis testing

A. Burak Yoldemir, Mehmet Sezgin

Proceedings Volume 7664, Detection and Sensing of Mines, Explosive Objects, and Obscured Targets XV; 76642C (2010) https://doi.org/10.1117/12.852529
Event: SPIE Defense, Security, and Sensing, 2010, Orlando, Florida, United States

Abstract

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.

Citation Download Citation

A. Burak Yoldemir and Mehmet Sezgin "Depth estimation of buried objects using wavelet transform and statistical hypothesis testing", Proc. SPIE 7664, Detection and Sensing of Mines, Explosive Objects, and Obscured Targets XV, 76642C (29 April 2010); https://doi.org/10.1117/12.852529

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