• 主题
高级搜索  >
历史搜索 清空历史
首页> 美国卫生研究院文献>Sensors (Basel Switzerland) >A Survey of Spoofer Detection Techniques via Radio Frequency Fingerprinting with Focus on the GNSS Pre-Correlation Sampled Data
【2h】

A Survey of Spoofer Detection Techniques via Radio Frequency Fingerprinting with Focus on the GNSS Pre-Correlation Sampled Data

机译：通过射频指纹对射频指纹对辐射频率检测技术进行调查专注于GNSS预相关采样数据

代理获取
本网站仅为用户提供外文OA文献查询和代理获取服务，本网站没有原文。下单后我们将采用程序或人工为您竭诚获取高质量的原文，但由于OA文献来源多样且变更频繁，仍可能出现获取不到、文献不完整或与标题不符等情况，如果获取不到我们将提供退款服务。请知悉。
页面导航
  • 摘要
  • 著录项
  • 相似文献
  • 相关主题

摘要

Radio frequency fingerprinting (RFF) methods are becoming more and more popular in the context of identifying genuine transmitters and distinguishing them from malicious or non-authorized transmitters, such as spoofers and jammers. RFF approaches have been studied to a moderate-to-great extent in the context of non-GNSS transmitters, such as WiFi, IoT, or cellular transmitters, but they have not yet been addressed much in the context of GNSS transmitters. In addition, the few RFF-related works in GNSS context are based on post-correlation or navigation data and no author has yet addressed the RFF problem in GNSS with pre-correlation data. Moreover, RFF methods in any of the three domains (pre-correlation, post-correlation, or navigation) are still hard to be found in the context of GNSS. The goal of this paper was two-fold: first, to provide a comprehensive survey of the RFF methods applicable in the GNSS context; and secondly, to propose a novel RFF methodology for spoofing detection, with a focus on GNSS pre-correlation data, but also applicable in a wider context. In order to support our proposed methodology, we qualitatively investigated the capability of different methods to be used in the context of pre-correlation sampled GNSS data, and we present a simulation-based example, under ideal noise conditions, of how the feature down selection can be done. We are also pointing out which of the transmitter features are likely to play the biggest roles in the RFF in GNSS, and which features are likely to fail in helping RFF-based spoofing detection.
机译：射频指纹（RFF）方法在识别真实发射器的背景下变得越来越受欢迎，并将它们与恶意或非授权发射器区分开，例如解码器和干扰。已经在非GNSS发射器的背景下研究了RFF方法，例如WiFi，物联网或蜂窝变送器，但在GNSS发射器的背景下尚未解决它们。此外，GNSS上下文中的少数与RFF相关的作品基于后关节或导航数据，没有作者尚未在具有前相关数据的GNS中解决RFF问题。此外，在GNSS的上下文中仍然很难找到三个域中的任何三个域（预相关，相关性或导航）中的任何一个的RFF方法。本文的目标是两倍：首先，提供对适用于GNSS背景下的RFF方法的全面调查;其次，为了提出一种用于欺骗检测的新型RFF方法，专注于GNSS预相关数据，而且还适用于更广泛的背景。为了支持我们所提出的方法，我们定性地调查了在预关联预相关的GNSS数据的上下文中使用的不同方法的能力，并且我们在特征下选择的理想噪声条件下呈现了一种基于仿真的示例可以做到。我们还指出了哪些发射器功能可能在GNS中发挥最大的角色，并且在帮助基于RFF的欺骗检测方面可能会失败。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
代理获取

客服邮箱：kefu@zhangqiaokeyan.com

京公网安备：11010802029741号 ICP备案号：京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有

  • 客服微信

  • 服务号