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A deblurring algorithm for impulse based forward-looking ground penetrating radar images reconstructed using the delay-and-sum algorithm

机译:一种使用延迟和和算法重建基于脉冲的前瞻性地面穿透雷达图像的去误伤算法

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Presently, the delay-and-sum (DAS) algorithm, also known as the backprojection algorithm, is the most popular way to reconstruct impulse based forward-looking ground penetrating radar (FLGPR) images. Nevertheless, it is widely known that the DAS algorithm has poor clutter rejection capability and generates FLGPR images with low resolution. The advantage of the DAS algorithm is its computational speed and ability to reconstruct scatterers within a scene-of-interest that are sufficiently spaced. In this paper, we propose a deblurring algorithm that is based on a model for DAS images whereby the known system matrix depends on the transmitted signal, and the propagation delays associated with the transmitted and backscattered signals. Using a DAS image as the data, an improved FLGPR image is obtained by estimating the true reflection coefficients via a popular estimation method known as the least absolute shrinkage and selection operator (LASSO). The objective function that results from LASSO is minimized using the majorization-minimization optimization technique. We refer to the proposed algorithm as the deblurring DAS (D-DAS) algorithm. Using synthetic data, we provide subjective results where the D-DAS algorithm significantly outperformed the standard DAS algorithm.
机译:目前,延迟和总和(DAS)算法,也称为反投影算法,是最受基于前瞻性地面穿透雷达(FLGPR)图像的脉冲的最受欢迎的方式。然而,众所周知,DAS算法具有较差的杂波抑制能力并产生具有低分辨率的FLGPR图像。 DAS算法的优点是其计算速度和重建散射体的能力,其在兴趣场景中是充分间隔的。在本文中,我们提出了一种基于DAS图像模型的去孔算法,由此已知的系统矩阵取决于发送信号,以及与发送和反向散射信号相关联的传播延迟。使用DAS图像作为数据,通过经由称为最低绝对收缩和选择操作员(套索)的流行估计方法估计真实反射系数来获得改进的FLGPR图像。使用多种 - 最小化优化技术最小化来自套索的目标函数。我们将所提出的算法称为去纹理DAS(D-DAS)算法。使用合成数据,我们提供了D-DAS算法显着优于标准DAS算法的主观结果。

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