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Forward-Looking GPR Imaging with Near-Optimal 3-D Synthetic Array

机译:具有近乎最佳的3D合成阵列的前瞻性GPR成像

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In this paper, we propose an Elevation-Radial scanned Synthetic Aperture Radar (E-RadSAR) for forward-looking ground penetrating radar (GPR) imaging. The E-RadSAR exploits the advantages of both RadSAR and Elevation-Circular SAR (E-CSAR) by utilizing the SAR technique in the cross- and down-range directions for signal acquisition. It could be implemented with fewer antennas compared to the RadSAR but provides higher spatial resolutions than that of E-CSAR. These features make it very attractive for space-and/or cost-constrained imaging applications, for instance, the GPR systems used for tunnel boring machines (TBM). However, the E-RadSAR synthesizes a three-dimensional (3-D) array by taking measurements in a volume, which makes the traditional sampling criterion no longer applicable for its sampling strategy design. To tackle 3-D (synthetic) array sampling/design, we formulate it as a sensor selection problem and suggest an efficient selection algorithm, i.e., modified clustered FrameSense (modified CFS). Then it is used for 3-D array sampling design. The imaging performances of the resultant near-optimal 3-D arrays are demonstrated through numerical simulations.
机译:在本文中,我们提出了一种高程径向扫描合成孔径雷达(E-RadSAR),用于前视探地雷达(GPR)成像。 E-RadSAR通过利用横向和向下范围的SAR技术来捕获信号,从而充分利用了RadSAR和高空循环SAR(E-CSAR)的优势。与RadSAR相比,它可以用更少的天线来实现,但比E-CSAR可以提供更高的空间分辨率。这些功能使其对于空间和/或成本受限的成像应用非常有吸引力,例如,用于隧道掘进机(TBM)的GPR系统。但是,E-RadSAR通过在一个体积中进行测量来合成三维(3-D)阵列,这使得传统的采样标准不再适用于其采样策略设计。为了解决3-D(合成)阵列采样/设计问题,我们将其公式化为传感器选择问题,并提出了一种有效的选择算法,即修改后的群集FrameSense(修改后的CFS)。然后将其用于3-D阵列采样设计。通过数值模拟证明了所得近乎最佳的3D阵列的成像性能。

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