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A High-Precision Cooperative Localization Method for UAVs Based on Multi-Condition Constraints.

Haiqiao Liu1, Wen Jiang2, Qing Long2

  • 1The School of Electrical and Information, Hunan Institute of Engineering, Xiangtan 411104, China.

Sensors (Basel, Switzerland)
|March 14, 2026
PubMed
Summary
This summary is machine-generated.

This study introduces a novel air-ground cooperative localization method for Unmanned Aerial Vehicles (UAVs) to overcome Global Navigation Satellite System (GNSS) errors in challenging environments. Integrating ground reference stations significantly improves UAV swarm localization accuracy and robustness.

Keywords:
GARSGDOPUAVcooperative localizationformation optimization

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Area of Science:

  • Robotics and Autonomous Systems
  • Navigation and Control
  • Geospatial Intelligence

Background:

  • Global Navigation Satellite Systems (GNSS) face significant localization errors in signal-denied environments.
  • Multi-Unmanned Aerial Vehicle (UAV) cooperative localization accuracy is sensitive to swarm geometric configuration.
  • Existing methods struggle with robustness and precision in complex operational scenarios.

Purpose of the Study:

  • To develop a high-precision and robust cooperative localization method for UAV swarms.
  • To optimize UAV swarm quantity and geometric configuration for improved localization.
  • To enhance localization performance by integrating ground-based reference infrastructure.

Main Methods:

  • Optimized UAV swarm quantity and geometric configuration by minimizing Geometric Dilution of Precision (GDoP).
  • Introduced Ground-Assisted Reference Stations (GARS) or Unmanned Ground Vehicles (UGVs) for an air-ground cooperative system.
  • Leveraged Time Difference of Arrival (TDoA) constraints for enhanced accuracy and robustness.

Main Results:

  • Purely air-based geometric optimization improved horizontal coverage but showed Z-axis errors (3.0-5.0 m).
  • Air-ground cooperative scheme with edge-deployed ground stations reduced Position Dilution of Precision (PDoP) to 0.75.
  • The proposed air-ground system effectively suppressed error divergence and outperformed pure air-based methods.

Conclusions:

  • Air-ground cooperative localization significantly enhances UAV swarm positioning accuracy and robustness.
  • Optimizing geometric configuration and integrating ground references are crucial for reliable navigation.
  • The proposed method offers substantial theoretical and practical value for advanced UAV operations.