Special Section on Compressive Sensing for Imaging

Sparse ground-penetrating radar imaging method for off-the-grid target problem

[+] Author Affiliations
Ali Cafer Gurbuz

TOBB University of Economics and Technology, Department of Electrical and Electronics Engineering, Sogutozu Cad. No 43, Ankara 06560, Turkey

Oguzhan Teke

Bilkent University, Department of Electrical and Electronics Engineering, TR-06800 Bilkent, Ankara, Turkey

Orhan Arikan

Bilkent University, Department of Electrical and Electronics Engineering, TR-06800 Bilkent, Ankara, Turkey

J. Electron. Imaging. 22(2), 021007 (Jan 31, 2013). doi:10.1117/1.JEI.22.2.021007
History: Received August 17, 2012; Revised November 8, 2012; Accepted November 19, 2012
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Abstract.  Spatial sparsity of the target space in subsurface or through-the-wall imaging applications has been successfully used within the compressive-sensing framework to decrease the data acquisition load in practical systems, while also generating high-resolution images. The developed techniques in this area mainly discretize the continuous target space into grid points and generate a dictionary of model data that is used in image-reconstructing optimization problems. However, for targets that do not coincide with the computation grid, imaging performance degrades considerably. This phenomenon is known as the off-grid problem. This paper presents a novel sparse ground-penetrating radar imaging method that is robust for off-grid targets. The proposed technique is an iterative orthogonal matching pursuit-based method that uses gradient-based steepest ascent-type iterations to locate the off-grid target. Simulations show that robust results with much smaller reconstruction errors are obtained for multiple off-grid targets compared to standard sparse reconstruction techniques.

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Citation

Ali Cafer Gurbuz ; Oguzhan Teke and Orhan Arikan
"Sparse ground-penetrating radar imaging method for off-the-grid target problem", J. Electron. Imaging. 22(2), 021007 (Jan 31, 2013). ; http://dx.doi.org/10.1117/1.JEI.22.2.021007


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