首页> 外文期刊>Neural Networks: The Official Journal of the International Neural Network Society >Plastic mine detecting radar system using complex-valued self-organizing map that deals with multiple-frequency interferometric images.
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Plastic mine detecting radar system using complex-valued self-organizing map that deals with multiple-frequency interferometric images.

机译:使用复值自组织图处理多频干涉图像的塑料探雷雷达系统。

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摘要

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. 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.
机译:探地雷达(GPR)通常已应用于地下物体成像。但是,传统的雷达系统无法有效地探测杀伤人员塑料地雷。我们提出了一种新颖的雷达成像系统,可以处理在多个频率点获得的自适应干涉式前端数据。该系统使用复数值自组织图(C-SOM)处理干涉图像。我们演示了埋在地面附近的塑料矿井的成功可视化。

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