Solutions to the problems of sparsity enhanced subsurface imaging for stepped frequency GPRs

In Stepped Frequency Ground Penetrating Radars (GPR), an image of the target space can be constructed with making measurements at only a small number of randomfrequencies by Compressive Sensing (CS) based imaging method. Although this methodgreatly reduces the data acquisition time, it wastes time in imaging.Orthogonal Matching Pursuit (OMP) which is faster than CS based imaging methodis proposed as an alternative method. Similar results are obtained within much shorter times. Additionally, sparsity enhanced imaging methods do not removeground reflections. Standard methods can not be directly applicablefor removing the ground reflections because of randomand fewer number of measurements. A surface reflectionremoval method for random and fewer measurements isdeveloped and compared with standard ground reflection methods. Finally, the performanceof the CS based subsurface imaging methods are analyzed for the velocity mismatch and off-grid problems and possible solutions are discussed. It is shown that target positions could be find correctly with the developed OMP based method.