Advanced classification of UXO using fully polarimetric GPR and frequency-polarization features

H. Youn, Minh Evans, J. Kobashigawa, M. Iskander
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引用次数: 1

Abstract

The classification of buried UXO has been a difficult task due to the large amount of false alarms resulted from troublesome clutter objects. This paper closely examined scattering characteristics of such clutter objects by using numerical simulations. From the numerical study, we found that some clutter objects, which mainly causes the false alarms, produce multiple resonances at different frequencies and different polarizations. Based on these observations, we developed new classification algorithms which utilize the frequency-polarization dependent responses of complex targets in order to discriminate UXO-like objects form such trouble some clutters. The developed algorithms were tested by experiments in a test plot. In the test, the new classification algorithms clearly discriminated such clutters from UXO-like targets. In this paper, we present the simulation results for scattering characteristics of complex clutters and the new classification algorithm based on frequency-polarization dependent responses will be discussed. Finally, results from experimental verification will be presented.
利用全极化探地雷达和频率极化特征对未爆弹药进行高级分类
埋藏未爆炸弹药的分类一直是一项艰巨的任务,因为大量的假警报是由麻烦的杂波物体引起的。本文采用数值模拟的方法研究了这类杂波物体的散射特性。通过数值研究,我们发现一些杂波目标在不同频率和不同极化下产生多重共振,这是导致误报警的主要原因。基于这些观察结果,我们开发了新的分类算法,利用复杂目标的频率极化相关响应来区分类uxo目标和杂波。本文提出的算法在试验田进行了实验验证。在测试中,新的分类算法可以清楚地将此类杂波与类uxo目标区分开来。本文给出了复杂杂波散射特性的仿真结果,并讨论了基于频率偏振相关响应的分类算法。最后给出了实验验证的结果。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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