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A Sensor-Driven Analysis of Distributed Direction Finding Systems Based on UAV Swarms.

Zhong Chen1, Shihyuan Yeh2, Jean-Francois Chamberland3

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This research explores using swarming unmanned aerial vehicles (UAVs) for radio frequency data collection. The micro-UAV swarm-based (MUSB) system enhances direction-of-arrival (DOA) accuracy and efficiency.

Keywords:
Cramer–Rao boundMUSICUAV swarmaperiodic arraysdirection-of-arrival estimationunmanned aerial vehicles

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Area of Science:

  • Electrical Engineering
  • Aerospace Engineering
  • Signal Processing

Background:

  • Unmanned Aerial Vehicles (UAVs) offer flexible platforms for data collection.
  • Traditional antenna arrays face limitations in angle ambiguity and convergence for direction-of-arrival (DOA) estimation.
  • Radio Frequency (RF) and microwave data collection requires efficient and accurate systems.

Purpose of the Study:

  • To investigate factors influencing the accuracy and efficiency of UAV-based RF/microwave data collection.
  • To introduce and analyze a micro-UAV swarm-based (MUSB) aperiodic antenna array system.
  • To develop and validate a mathematical model for MUSB antenna arrays and data collection.

Main Methods:

  • Development of a mathematical data model for MUSB antenna arrays.
  • Derivation of the Cramer-Rao bound (CRB) for two-dimensional (2D) DOAs with sensor gain and phase variations.
  • Implementation of an iterative-MUSIC algorithm for 2D DOA estimation of emitters.
  • Exploitation of the vector-space of emitters.

Main Results:

  • The MUSB system demonstrates reduced angle ambiguity and improved convergence in DOA techniques.
  • The derived CRB provides a theoretical benchmark for 2D DOA estimation accuracy.
  • The iterative-MUSIC algorithm effectively estimates 2D DOAs of multiple signal sources.
  • Numerical simulations and practical measurements validate the proposed system's feasibility.

Conclusions:

  • The proposed MUSB data collection framework using swarming UAVs is feasible and effective.
  • The system enhances DOA estimation accuracy and efficiency compared to traditional methods.
  • This approach offers a promising solution for advanced RF and microwave data collection applications.