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Cumulants-based Radar Specific Emitter Identification

机译:基于累积的雷达特定发射极识别

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In this paper we consider the problem of Radar Specific Emitter Identification (SEI) with the aim of distinguishing among several transmitting sources of the same kind which is a very hot topic in the device forensic field. At the design stage, we introduce a classification technique based on some suitable features evaluated from the cumulants of the signal emitted by the radar system. The devised features share some invariance properties which make them very attractive for the SEI problem. Hence, we use them as the input to a K-Nearest Neighbor (KNN) classifier which performs the assignment of the emitter to a specific class. At the analysis stage, we assess the performance of the new system on a real dataset containing radar signals from three identical airborne emitters. The results highlight that a satisfactory classification performance is achieved.
机译:在本文中,我们考虑了雷达特定发射极识别(SEI)的目的,其目的是区分同一类型的多个传输来源,这是设备法医领域非常热门的话题。在设计阶段,我们介绍了一种基于从雷达系统发出的信号的累积量评估的一些合适的特征的分类技术。设计的功能共享一些不变性的属性,使它们对SEI问题非常有吸引力。因此,我们将它们用作k-collect邻(knn)分类器的输入,其执行发射器的分配给特定类。在分析阶段,我们评估新系统在包含三个相同空中发射器的雷达信号的实际数据集上的性能。结果强调了实现令人满意的分类性能。

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