Effects of Different Soil Types on Strip-Map GPR SAR Images

In this study, we present generation of Strip-map Synthetic Aperture Radar (SAR) images using impulse GPR system, and investigate effects of different soil types on SAR images. The SAR images of buried objects have been interpreted via 2D inverse Fourier transformation. GPR buried target data have been collected from three soil pools having different dielectric constants and B-scan images have been reconstructed from the received data using mean A-scan signal subtraction method. In order to reconstruct SAR images, the time domain data collected from multiple observation points have been transformed to 2D spectral domain. Non-uniform data have been interpolated over spatial Cartesian grid by using uniform interval. Thus, the SAR images have been reconstructed via 2D inverse FFT of interpolated data on ky-kz plane. When examined mathematical background of SAR algorithm, the values of different dielectric constants change the wave number of k. This can lead to deterioration of the SAR imagery. In this study, we investigate the effect of the dielectric constant of different soils on SAR images. Finally, resolution difference between background removed B-Scan data and SAR images is considered.