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<p>The increasing complexity of wireless transmission environments and the growing demand for precise localization in non-line-of-sight (NLOS) scenarios present significant challenges for conventional localization methods. While reconfigurable intelligent surfaces (RIS) offer a promising solution by creating virtual signal paths, existing RIS-assisted methods face critical challenges in high-frequency regimes where spatial aliasing occurs. This paper introduces a novel RIS-assisted localization system designed for high-frequency signal positioning under NLOS conditions. Our proposed approach addresses these challenges through a cost-effective system and proposes a spatio-temporal-frequency information fusion (STFIF) direct localization algorithm that effectively resolves spatial aliasing issues in high-frequency applications. The STFIF framework integrates three key components: (1) sparse signal reconstruction via semi-definite programming for spatial domain parameter estimation, (2)frequency difference processing to suppress spatial aliasing and artifact targets, and (3) temporal-domain information exploitation through RIS’s time-varying configurations. Comparative analysis with existing frequency difference-based techniques demonstrates the superior performance of our approach in both single and multiple snapshot scenarios, highlighting its robustness and practical applicability.</p>

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RIS-assisted anti-spatial aliasing direct localization in NLOS scenarios via spatio-temporal-frequency information fusion

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2025年8月1日

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  • Jingjing Li,
  • Jianhui Wang,
  • Lihao Liu,
  • Weijia Cui,
  • Chunxiao Jian

摘要

The increasing complexity of wireless transmission environments and the growing demand for precise localization in non-line-of-sight (NLOS) scenarios present significant challenges for conventional localization methods. While reconfigurable intelligent surfaces (RIS) offer a promising solution by creating virtual signal paths, existing RIS-assisted methods face critical challenges in high-frequency regimes where spatial aliasing occurs. This paper introduces a novel RIS-assisted localization system designed for high-frequency signal positioning under NLOS conditions. Our proposed approach addresses these challenges through a cost-effective system and proposes a spatio-temporal-frequency information fusion (STFIF) direct localization algorithm that effectively resolves spatial aliasing issues in high-frequency applications. The STFIF framework integrates three key components: (1) sparse signal reconstruction via semi-definite programming for spatial domain parameter estimation, (2)frequency difference processing to suppress spatial aliasing and artifact targets, and (3) temporal-domain information exploitation through RIS’s time-varying configurations. Comparative analysis with existing frequency difference-based techniques demonstrates the superior performance of our approach in both single and multiple snapshot scenarios, highlighting its robustness and practical applicability.