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A Uniform Funnel Array for DOA Estimation in FANET Using Fibonacci Sampling.

Siwei Huo1, Ming Zhang1, Yongxi Liu1

  • 1School of Information and Communications Engineering, Xi'an Jiaotong University, Xi'an 710049, China.

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|May 14, 2025
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Summary
This summary is machine-generated.

This study introduces an improved direction-of-arrival (DOA) estimation method for unmanned aerial vehicle (UAV) networks. The novel Uniform Funnel Array (UFA) and Fibonacci sampling significantly enhance positioning accuracy where satellite navigation fails.

Keywords:
Fibonacci samplingcorrelative interferometerdirection-of-arrival (DOA) estimationphase differencessimilarity function

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Area of Science:

  • Wireless Communication
  • Signal Processing
  • Navigation Systems

Background:

  • Flying Ad-Hoc Networks (FANETs) are crucial for 6G communication systems.
  • Precise positioning of unmanned aerial vehicles (UAVs) is essential, especially when satellite navigation is unavailable.
  • Existing direction-of-arrival (DOA) estimation methods lack accuracy for UAVs in FANETs, particularly at large polar angles.

Purpose of the Study:

  • To propose a simple and accurate DOA estimation method for UAVs in FANETs.
  • To enhance positioning accuracy in environments with denied satellite navigation signals.
  • To address the polar clustering phenomenon in sampling strategies.

Main Methods:

  • An improved correlative interferometer method utilizing a Uniform Funnel Array (UFA) configuration.
  • UFA combines a Uniform Circular Array (UCA) with an additional central element for vertical aperture utilization.
  • Fibonacci sampling strategy to mitigate polar clustering, partial phase difference usage, and triangular function for similarity calculation.

Main Results:

  • The proposed UFA configuration improves DOA estimation accuracy by 65.56% compared to a planar UCA for large polar angles.
  • Fibonacci sampling enhances DOA estimation accuracy by 11.54% over traditional latitude-longitude sampling.
  • Reduced storage burden and improved computational efficiency achieved through method optimization.

Conclusions:

  • The developed UFA-based correlative interferometer method offers superior DOA estimation accuracy for UAVs in FANETs.
  • The method effectively addresses challenges posed by large polar angles and sampling limitations.
  • This advancement contributes to robust and precise UAV navigation in 6G communication systems.