31 January 2013 Sparse ground-penetrating radar imaging method for off-the-grid target problem
Ali Cafer Gurbuz, Oguzhan Teke, Orhan Arikan
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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.
© 2013 SPIE and IS&T 0091-3286/2013/$25.00 © 2013 SPIE and IS&T
Ali Cafer Gurbuz, Oguzhan Teke, and Orhan Arikan "Sparse ground-penetrating radar imaging method for off-the-grid target problem," Journal of Electronic Imaging 22(2), 021007 (31 January 2013). https://doi.org/10.1117/1.JEI.22.2.021007
Published: 31 January 2013
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CITATIONS
Cited by 12 scholarly publications.
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KEYWORDS
General packet radio service

Data modeling

Associative arrays

Ground penetrating radar

Radar imaging

Signal to noise ratio

Detection and tracking algorithms

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