19 April 2017 Rough ground surface clutter removal in air-coupled ground penetrating radar data using low-rank and sparse representation
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Abstract
This paper explores a low-rank and sparse representation based technique to remove the clutter produced by rough ground surface for air-coupled ground penetrating radar (GPR). For rough ground surface, the surface clutter components in different A-Scan traces are not aligned on the depth axis. To compensate for the misalignment effect and facilitate clutter removal, the A-Scan traces are aligned using cross-correlation technique first. Then the low-rank and sparse representation approach is applied to decompose the GPR data into a low-rank matrix whose columns record the ground clutter in A-Scan traces upon alignment adjustment, and a sparse matrix that features the subsurface object under test. The effectiveness of the proposed clutter removal method has been evaluated through simulations.
Conference Presentation
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Yu Zhang, Dylan Burns, Dan Orfeo, Dryver R. Huston, Tian Xia, "Rough ground surface clutter removal in air-coupled ground penetrating radar data using low-rank and sparse representation", Proc. SPIE 10169, Nondestructive Characterization and Monitoring of Advanced Materials, Aerospace, and Civil Infrastructure 2017, 1016904 (19 April 2017); doi: 10.1117/12.2261355; https://doi.org/10.1117/12.2261355
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