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Identifying GNSS Signals Based on Their Radio Frequency (RF) Features—A Dataset with GNSS Raw Signals Based on Roof Antennas and Spectracom Generator

机译:根据其射频(RF)特性识别GNSS信号-基于车顶天线和Spectracom发生器的GNSS原始信号数据集

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This is a data descriptor paper for a set of raw GNSS signals collected via roof antennas and Spectracom simulator for general-purpose uses. We give one example of possible data use in the context of Radio Frequency Fingerprinting (RFF) studies for signal-type identification based on front-end hardware characteristics at transmitter or receiver side. Examples are given in this paper of achievable classification accuracy of six of the collected signal classes. The RFF is one of the state-of-the-art, promising methods to identify GNSS transmitters and receivers, and can find future applicability in anti-spoofing and anti-jamming solutions for example. The uses of the provided raw data are not limited to RFF studies, but can extend to uses such as testing GNSS acquisition and tracking, antenna array experiments, and so forth.
机译:这是一份数据描述符文件,用于收集通过车顶天线和Spectracom模拟器收集的,用于通用用途的一组原始GNSS信号。我们给出了一个可能的数据示例,该数据可能会在射频指纹(RFF)研究的背景下用于基于发射器或接收器端的前端硬件特性进行信号类型识别。本文给出了六个采集信号类别可实现的分类精度示例。 RFF是识别GNSS发射器和接收器的最新技术,很有前途的方法之一,并且可以在例如防欺骗和防干扰解决方案中找到未来的适用性。提供的原始数据的用途不限于RFF研究,而是可以扩展到诸如测试GNSS采集和跟踪,天线阵列实验等用途。

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