Ground penetrating radars (GPR's) have been often applied to underground object imaging. However, conventional radar systems do not work sufficiently to detect anti-personnel plastic landmines. ⋯ The system deals with interferometric images using complex-valued self-organizing map (C-SOM). We demonstrate a successful visualization of a plastic mine buried near the ground surface.
Department of Frontier Informatics, The University of Tokyo, 7-3-1 Hongo, Bunkyo-ku, Tokyo 113-8656, Japan.
Neural Netw. 2004 Oct 1; 17 (8-9): 1201-10.
AbstractGround penetrating radars (GPR's) have been often applied to underground object imaging. However, conventional radar systems do not work sufficiently to detect anti-personnel plastic landmines. We propose a novel radar imaging system, which processes adaptively interferometric front-end data obtained at multiple-frequency points. The system deals with interferometric images using complex-valued self-organizing map (C-SOM). We demonstrate a successful visualization of a plastic mine buried near the ground surface.