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      • Department of Electrical and Electronics Engineering
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      Sparse ground-penetrating radar imaging method for off-the-grid target problem

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      Author
      Gurbuz, A. C.
      Teke, O.
      Arıkan, Orhan
      Date
      2013
      Source Title
      Journal of Electronic Imaging
      Print ISSN
      1017-9909
      Publisher
      SPIE
      Volume
      22
      Issue
      2
      Language
      English
      Type
      Article
      Item Usage Stats
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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 highresolution 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 gradientbased 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.
      Keywords
      Ground Penetrating Radar
      High resolution image
      Imaging performance
      Optimization problems
      Practical systems
      Reconstruction error
      Sparse reconstruction
      Through the wall imaging
      Geological surveys
      Radar imaging
      Iterative methods
      Permalink
      http://hdl.handle.net/11693/21023
      Published Version (Please cite this version)
      http://dx.doi.org/10.1117/1.JEI.22.2.021007
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      • Department of Electrical and Electronics Engineering 3524
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