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Classification of FOD Targets based on Polarimetric Characteristics

机译:基于极化特征的外来目标分类

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The invasion of foreign object debris (FOD) on the airport runway seriously threatens the safety of flight, and the accurate small radar targets classification used for the hazard level discrimination is a challenge. In this paper, a classification method based on polarization information is proposed to be used for FOD targets classification. We utilize electromagnetic simulation software for obtaining radar cross section (RCS) polarimetric data in various incident angles based on typical FOD (e.g. Spanners, Screwdrivers, PVC Pipe) targets. In addition, polarization invariant is applied to characterize targets for classification using support vector machines (SVM). Experimental results indicate that this method can classify the three objects effectively and the great potential of polarization information for FOD targets classification.
机译:异物碎片(FOD)在机场跑道上的入侵严重威胁了飞行安全,而用于危险等级识别的精确小型雷达目标分类是一个挑战。本文提出了一种基于极化信息的分类方法用于外来物目标分类。我们基于典型的FOD(例如,扳手,螺丝刀,PVC管)目标,利用电磁仿真软件获取各种入射角下的雷达横截面(RCS)极化数据。此外,使用支持向量机(SVM)将极化不变性应用于表征目标以进行分类。实验结果表明,该方法可以有效地对三个物体进行分类,极化信息对于外来物目标分类具有很大的潜力。

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