High-Precision Time-of-Arrival Estimation in HF Sensor Networks via Multipath Separation and Independent Tracking

High-frequency (HF) sensor networks play an irreplaceable role in remote sensing and emergency communications but suffer severely from ionospheric multipath interference, which degrades Time-of-Arrival (TOA) estimation accuracy. Conventional methods, such as the Generalized Cross-Correlation (GCC) and standard Delay-Locked Loops (DLL), often treat multipath components as noise, leading to significant measurement bias in dynamic environments. To address this, we propose a Multipath Separation and Independent Tracking (MSIT) architecture. This framework transforms multipath interference into valuable observables by establishing a closed-loop synergy: a Maximum Likelihood Estimation (MLE)-based module iteratively separates signal components, while parallel tracking loops update phase and delay parameters. Additionally, a super-resolution MUSIC algorithm is employed for initialization to resolve sub-chip multipath components. Simulations demonstrate that under disturbed channel conditions, the MSIT method achieves a mean delay estimation error reduction of about two orders of magnitude relative to the GCC method. Furthermore, field experiments on the Xi’an–Ürümqi link demonstrate its capability to stably resolve and track multiple propagation paths in real-world environments. This approach significantly enhances the measurement precision and reliability of HF sensing systems.

• Publication year

  2026

• Venue

  Italian National Conference on Sensors

• Publication date

  2026-03-05

• Fields of study

  Not labeled

• Identifiers
  DOI 10.3390/s26051640PMCID PMC12986613
• External record

  Open on Semantic Scholar

• Source metadata

  Semantic Scholar

• No claims are published for this paper.

• No concepts are published for this paper.

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