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GPR Imaging for Deeply Buried Objects: A Comparative Study Based on Compositing of Scanning Frequencies and a Chirp Excitation Function

机译:深埋物体的GPR成像:基于扫描频率和a激励函数合成的比较研究

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Compositing of ground penetrating radar (GPR) scans of differing frequencies have been found to produce cleaner images at depth using the Gaussian mixture model (GMM) feature of the expectation-maximization (EM) algorithm. GPR scans at various heights (“Stand Off”), as well as ground-based scans, have been studied. In this paper, we compare the GPR response from a chirp excitation function-based radar with the response from the EM GMM algorithm compositing process, using the same mix of frequencies. A chirp excitation pulse was found to be effective in delineating the defined buried object, but the resulting image is less sharp than the GMM EM method.
机译:已经发现,使用期望最大化(EM)算法的高斯混合模型(GMM)功能,对不同频率的探地雷达(GPR)扫描进行合成可以在深度生成更清晰的图像。已经研究了各种高度的GPR扫描(“站立”)以及基于地面的扫描。在本文中,我们使用相同的频率混合,比较了基于chi激励函数的雷达的GPR响应和EM GMM算法合成过程的响应。发现chi激励脉冲可有效地勾勒出确定的掩埋物体,但所产生的图像不如GMM EM方法清晰。

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