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基于机器学习的GNSS NLOS探测器的坚固设计具有多频特征

Omar García Crespillo1, Juan Carlos Ruiz-Sicilia1, Ana Kliman1

  • 1Navigation Department, Institute of Communication and Navigation, German Aerospace Center (DLR), Oberpfaffenhofen, Germany.

Frontiers in robotics and AI
|August 14, 2023
PubMed
概括

本研究引入了一种新的机器学习方法,用于准确检测全球导航卫星系统 (GNSS) 的非视线 (NLOS) 信号,这对于安全导航至关重要. 该方法增强了算法概括性,并提高了复杂环境中的检测准确性.

关键词:
全球导航卫星系统全球导航卫星系统当地威胁 当地威胁机器学习是机器学习.视线之外的传播传播城市环境 城市环境

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