Threat object classification with a close range polarimetric imaging system by means of H-alpha decomposition
Threat object classification with a close range polarimetric imaging system by means of H-alpha decomposition
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DOI：
10.1017/s1759078714000075
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发表时间：
2013-12
期刊：
影响因子：
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通讯作者：
J. Adametz;L. Schmidt
中科院分区：
文献类型：
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作者：
J. Adametz;L. Schmidt
本文研究了在安全应用中区分各种介电威胁对象的方法。从全极化单基地合成孔径雷达（SAR）中获得了相关场景的Sinclair矩阵形式的散射信息。提出了一种可能的极化校准方法。采用H - α分解算法对雷达数据进行处理。利用加权平均法分析了威胁目标的H - α散射特性。它示出了对象分类是可能的，即使是隐藏在厚层的衣服下的威胁对象。测量结果来说明的主题。
In this paper, an approach to differentiate between various dielectric threat objects in security applications is investigated. The scattering information in form of the Sinclair matrix of relevant scenarios is gained from a fully polarimetric, monostatic synthetic aperture radar (SAR). A possible polarimetric calibration procedure is presented. The radar data are processed with the H - α decomposition algorithm. The H - α scattering characteristics of threat objects are analyzed in terms of a weighted averaging. It is shown that an object classification is possible even for threat objects conceiled under thick layers of clothing. Measurement results are presented to illustrate the topic.