Scholarlink

<p>This study presents a secure vehicle localization framework designed to maintain accuracy under GPS spoofing attacks. The framework integrates a spoofing detection mechanism operating in three adaptive modes and employs refined dynamic, measurement, and attack models. A decomposition-based Kalman filter is utilized to develop a fusion algorithm for robust state estimation. Simulation and field experiments confirm that the proposed approach achieves high localization accuracy and resilience against spoofing in complex urban environments.</p>

错误：搜索内容不能为空，请输入英文关键词
错误：关键词超出字数限制，请精简
高级检索

Secure localization of land vehicles under GPS spoofing attack with decomposition Kalman filter

  • 期刊论文

  • 出版模式：

    开放获取

  • 发表日期：

    2025年12月18日

查看全文
  • Meihong Zhao,
  • Zhengxiao Han,
  • Ende Wang,
  • Jiageng Liu

摘要

This study presents a secure vehicle localization framework designed to maintain accuracy under GPS spoofing attacks. The framework integrates a spoofing detection mechanism operating in three adaptive modes and employs refined dynamic, measurement, and attack models. A decomposition-based Kalman filter is utilized to develop a fusion algorithm for robust state estimation. Simulation and field experiments confirm that the proposed approach achieves high localization accuracy and resilience against spoofing in complex urban environments.