CA-CFAR detection against K-Distributed clutter in GPR

In this study buried object detection on the GPR data is examined using CA-CFAR detector. In the first part of the study the background signals of B-scan frames from a pulse GPR are statistically inspected. The results revealed that the background signals residual from a removing process of the dominant GPR signals due to air-to-ground interface have shown K-Distributed statistics. The form and scale parameters of K-Distribution are estimated using the fractional moments. The background or the clutter signals from three different soils have resulted in distinctive shape parameters. The shape parameter of the distribution could generally discriminate three soils. In the second part of the study the receiver loss of CA-CFAR detector is estimated using a numerical method and the Monte-Carlo simulation. The receiver loss is also associated to the K-Distribution and CA-CFAR detector parameters in the simulation. Time series with statistical properties similar to those of the real measurements are obtained using SIRV and employed in the Monte-Carlo simulation. In the third part of the study effectiveness of CA-CFAR detector on B-scan frames is analyzed by measuring the ROC of the detector. High detection probabilities of buried objects at relatively low SNR data are obtained by CA-CFAR detector.