Motivated by applications in unmanned aerial based ground penetrating radar for detecting buried landmines, we consider the problem of imaging small point like scatterers situated in a lossy medium below a random rough surface. Both the random rough surface and the absorption in the lossy medium significantly impede the target detection and imaging process. Using principal component analysis we effectively remove the reflection from the air-soil interface. We then use a modification of the classical synthetic aperture radar imaging functional to image the targets. This imaging method introduces a user-defined parameter, $\delta$, which scales the resolution by $\sqrt{\delta}$ allowing for target localization with sub wavelength accuracy. Numerical results in two dimensions illustrate the robustness of the approach for imaging multiple targets. However, the depth at which targets are detectable is limited due to the absorption in the lossy medium.
翻译:本研究旨在解决无人机地基雷达检测埋藏地雷时的问题,即对于一个带有随机粗糙表面的丢失介质下方,成像小点散射体的问题。随机粗糙表面和介质吸收对目标检测和成像过程都有很大影响。采用主成分分析方法有效地消除了空气-土壤界面的反射。然后,我们使用传统合成孔径雷达成像方法的改进版本来对目标进行成像。该成像方法引入了一个用户定义的参数 $ \delta $ ,可以通过 $ \sqrt {\ delta} $ 缩放分辨率,从而实现对目标位置的亚波长精度定位。二维数值结果展示了该方法用于成像多个点目标时的稳健性。但是,介质吸收限制了可以检测到目标的深度。