Clutter Reduction of GPR Images using Multiscale Products

D. Flores-Tapia, G. Thomas, and M.C. Phelan (Canada)


Radar, Radar Imaging, Signal Processing Wavelets.


Ground Penetrating Radar (GPR) has been a valuable tool for subsurface object detection and identification. Usually the echoes reflected by the buried objects have a low signal to noise ratio (SNR) and clutter can hardly be considered a stationary process. This paper presents an algorithm based on the multiplication of adjacent wavelet subbands in order to enhance target echoes while reducing noise. In these multiscale products, target signatures can be effectively distinguished from noise. A simple threshold is applied to the signal in the wavelet domain in order to eliminate the clutter responses. This final signal is reconstructed to the time domain in order to correct range migration and obtain a final focused image.

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