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Cumulants-based Radar Specific Emitter Identification

机译:基于累积量的雷达特定辐射源识别

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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,我们考虑雷达专用发射器识别(SEI)问题,目的是区分几种相同类型的发射源,这在设备法证领域是一个非常热门的话题。在设计阶段,我们基于从雷达系统发射的信号累积量评估的一些合适特征,引入分类技术。设计的功能共享一些不变性,这使它们对于SEI问题非常有吸引力。因此,我们将它们用作K最近邻(KNN)分类器的输入,该分类器执行将发射器分配给特定类的工作。在分析阶段,我们在包含来自三个相同机载发射器的雷达信号的真实数据集上评估新系统的性能。结果突出表明,获得了令人满意的分类性能。

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