Abstract
Ground Penetrating Radar (GPR) signatures of shallowly buried landmines are normally obscured by a strong background signal comprised of the reflections from the ground surface and the antenna crosstalk. Based on the notion that buried landmine produces an anomaly in the soil dielectric an automated procedure has been developed which detects soil dieletric anomalies of the size comparable to the size of landmine in GPR data and enhances the signatures of such anomalies. A local background estimate is computed and a soil dielectric anomaly is detected at the spatial position where a change from the estimated background signal occurs. A translation invariant wavelet packet decomposition is applied for detection. The computation takes place in a running window which allows for the algorithm to adapt to the variations in ground conditions and antenna height. The technique was tested using a number of minelike targets buried in several different soil environments and the testing results are presented.
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Carevic, D. Clutter Reduction and Detection of Minelike Objects in Ground Penetrating Radar Data Using Wavelets. Subsurface Sensing Technologies and Applications 1, 101–118 (2000). https://doi.org/10.1023/A:1010126810896
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DOI: https://doi.org/10.1023/A:1010126810896