Please use this identifier to cite or link to this item: https://hdl.handle.net/20.500.11851/6065
Title: A Compressive Sensing Data Acquisition and Imaging Method for Stepped Frequency GPRs
Authors: Gürbüz, Ali Cafer
McClellan, James H.
Scott, Waymond R.
Keywords: Compressive sensing
l(1) minimization
ground penetrating radar (GPR)
sparsity
stepped frequency systems
subsurface imaging
Issue Date: 2009
Publisher: IEEE-Inst Electrical Electronics Engineers Inc
Abstract: A novel data acquisition and imaging method is presented for stepped-frequency continuous-wave ground penetrating radars (SFCW GPRs). It is shown that if the target space is sparse, i.e., a small number of point like targets, it is enough to make measurements at only a small number of random frequencies to construct an image of the target space by solving a convex optimization problem which enforces sparsity through l(1) minimization. This measurement strategy greatly reduces the data acquisition time at the expense of higher computational costs. Imaging results for both simulated and experimental GPR data exhibit less clutter than the standard migration methods and are robust to noise and random spatial sampling. The images also have increased resolution where closely spaced targets that cannot be resolved by the standard migration methods can be resolved by the proposed method.
URI: https://doi.org/10.1109/TSP.2009.2016270
https://hdl.handle.net/20.500.11851/6065
ISSN: 1053-587X
1941-0476
Appears in Collections:Elektrik ve Elektronik Mühendisliği Bölümü / Department of Electrical & Electronics Engineering
Scopus İndeksli Yayınlar Koleksiyonu / Scopus Indexed Publications Collection
WoS İndeksli Yayınlar Koleksiyonu / WoS Indexed Publications Collection

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