Analysis of orthogonal matching pursuit based subsurface imaging for compressive ground penetrating radars

Authors : Mehmet Ali Çağrı TUNCER, Ali Cafer GÜRBÜZ

Pages : 979-989

View : 21 | Download : 9

Publication Date : 0000-00-00

Article Type : Research Paper

Abstract :It is shown that compressive sensing insert ignore into journalissuearticles values(CS); theory can be used for subsurface imaging in stepped frequency ground penetrating radars insert ignore into journalissuearticles values(GPR);, resulting in robust sparse images, using fewer measurements. Although the data acquisition time is decreased by CS, the computational complexity of the minimization based imaging algorithm is too costly, which makes the algorithm useless, especially for extensive discretization or 3D imaging. In this paper, a greedy alternative, orthogonal matching pursuit insert ignore into journalissuearticles values(OMP); is used for imaging subsurface and its performance under various conditions is compared to CS imaging method. Results show that OMP could reconstruct sparse signals robustly as well as CS imaging. It is faster and easier to implement so it can be said that OMP is a fascinating alternative to CS imaging method for subsurface GPR imaging.
Keywords : Ground Penetrating Radar GPR, Radar, Subsurface Imaging, Compressive Sensing CS, ell1 minimization, Orthogonal Matching Pursuit insert ignore into journaliss