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8 June 2012 Dictionary reduction technique for 3D stepped-frequency GPR imaging using compressive sensing and the FFT
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Abstract
Compressive sensing (CS) techniques have shown promise for subsurface imaging applications using wideband sensors such as stepped-frequency ground-penetrating radars (GPR). Excellent images can be computed using the CS techniques. However, the problem size is severely limited for 3-dimensional imaging problems which seem to require an explicit representation matrix that involves six dimensions. This paper shows how the underlying propagation model leads to a block-Toeplitz structure in two of the dimensions which can be exploited to reduce both the storage and computational complexity. The reduction by three orders of magnitude in computational resources for the CS problem will make 3-dimensional imaging applications feasible.
© (2012) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Kyle Krueger, James H. McClellan, and Waymond R. Scott Jr. "Dictionary reduction technique for 3D stepped-frequency GPR imaging using compressive sensing and the FFT", Proc. SPIE 8365, Compressive Sensing, 83650Q (8 June 2012); https://doi.org/10.1117/12.919582
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