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Formation-Constrained Cooperative Localization for UAV Swarms in GNSS-Denied Environments.

Qin Li1, Peng Wang1, Xiaochun Li1

  • 1College of Information and Navigation, Air Force Engineering University, Xi'an 710077, China.

Sensors (Basel, Switzerland)
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PubMed
Summary
This summary is machine-generated.

This study introduces a formation-constrained method for cooperative localization in unmanned aerial vehicle (UAV) swarms operating without GPS. The approach enhances accuracy and reliability by integrating known formation geometry into the localization process.

Keywords:
GNSS-denied environmentsUAV swarmbackbone-listener schemecooperative localizationformation constraints

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Area of Science:

  • Robotics
  • Navigation Systems
  • Artificial Intelligence

Background:

  • Cooperative localization is essential for Unmanned Aerial Vehicle (UAV) swarms in Global Navigation Satellite System (GNSS)-denied environments.
  • The backbone-listener scheme optimizes communication and scalability by designating some UAVs as active backbone nodes and others as passive listeners.
  • Existing methods may lack accuracy when dealing with complex formation geometries or dynamic environments.

Purpose of the Study:

  • To develop a formation-constrained cooperative localization method for UAV swarms in GNSS-denied environments.
  • To improve the accuracy, reliability, and stability of UAV swarm localization by leveraging known formation geometry.
  • To enhance the adaptability of cooperative localization techniques for practical deployment in diverse formation scenarios.

Main Methods:

  • Proposed a formation-constrained greedy node activation (GNA) strategy for backbone node selection, incorporating weighted distance fusion.
  • Integrated formation constraints into Chan's algorithm for listener node localization, coupled with angle-of-arrival (AOA) refinement.
  • Employed gradient descent-based global optimization to enforce formation constraints across all agent positions in two-dimensional (2D) space.

Main Results:

  • The formation-constrained method significantly improved localization accuracy and reliability compared to existing schemes.
  • The greedy node activation strategy with weighted distance fusion enabled near-optimal backbone node selection aligned with formation structure.
  • Listener localization using Chan's algorithm with AOA refinement and global optimization successfully maintained expected inter-agent distances.

Conclusions:

  • The proposed formation-constrained cooperative localization method enhances UAV swarm performance in GNSS-denied conditions.
  • The method demonstrates robust adaptability to various formation types, including asymmetric geometries, making it suitable for practical applications.
  • Simulation results validate the effectiveness and stability of the approach, highlighting its potential for real-world UAV swarm operations.