DocumentCode :
59333
Title :
Efficient Algorithm Design for GPR Imaging of Landmines
Author :
Krueger, Kyle R. ; McClellan, James H. ; Scott, Waymond R.
Author_Institution :
Dept. of Electr. & Comput. Eng., Georgia Inst. of Technol., Atlanta, GA, USA
Volume :
53
Issue :
7
fYear :
2015
fDate :
Jul-15
Firstpage :
4010
Lastpage :
4021
Abstract :
Ground-penetrating radar (GPR) is used to image and detect subterranean objects, for example, in landmine detection. Although full 3-D inversion of GPR measurements is possible for simple algorithms such as backprojection, it is impractical when using more advanced algorithms that involve ℓ1 - minimization. Many of the algorithms used for GPR imaging involve the storage, or online generation, of a huge dictionary matrix created from discretizing a high-dimensional nonlinear model. This parametric model includes all the target features that need to be extracted, including 3-D location, object orientation, and target type. As more parameters are added to the model, the dimensionality increases. If uniform sampling is done over high-dimensional parameter space, the size of the dictionary and the complexity of the inversion algorithms rapidly grow, exceeding the capability of real-time processors. This paper shows that strategic structuring of the dictionary, which takes advantage of translational invariance in the model, can reduce the dictionary storage by several orders of magnitude and exploit the fast Fourier transform for fast computation of previously highly impractical, bordering on impossible, 3-D GPR imaging problems.
Keywords :
fast Fourier transforms; ground penetrating radar; landmine detection; GPR imaging; dictionary storage; fast Fourier transform; ground-penetrating radar; landmines; subterranean objects; translational invariance; Convolution; Dictionaries; Ground penetrating radar; Landmine detection; Sensors; Vectors; Compressive sensing (CS); fast Fourier transform (FFT); ground-penetrating radar (GPR);
fLanguage :
English
Journal_Title :
Geoscience and Remote Sensing, IEEE Transactions on
Publisher :
ieee
ISSN :
0196-2892
Type :
jour
DOI :
10.1109/TGRS.2015.2388786
Filename :
7036055
Link To Document :
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