Sparsity enhanced fast subsurface imaging for stepped frequency GPRs

Abstract

A sparsity enhanced and fast data acquisition and imaging method is presented for stepped-frequency continuous-wave ground penetrating radars (SFCW GPRs). In previous work it is shown that if the target space is sparse like the point like targets, an image of the target space can be constructed with making measurements at only a small number of random frequencies by solving an l1 minimization problem. This greatly reduces the data acquisition time but the computational complexity for the imaging method is high. In this work, subsurface imaging is done with a suboptimal but fast method, orthogonal matching pursuit. Similar results to l1 minimization images are obtained within much shorter times. Also the results are sparse and less cluttered compared to standard backprojection images.