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This study presents a low-cost, three-stage framework to detect invading unmanned aerial vehicles (UAVs) in sensitive areas. The system effectively identifies even stealthy UAVs, offering a portable surveillance solution.

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Area of Science:

  • Aerospace Engineering
  • Security Technology
  • Computer Vision

Background:

  • Unmanned aerial vehicles (UAVs) have advanced significantly, increasing their use.
  • The proliferation of UAVs poses security risks, especially in restricted or private areas.
  • Existing detection methods may be costly or lack effectiveness against stealthy threats.

Purpose of the Study:

  • To develop a low-cost, multi-stage framework for detecting unauthorized UAV incursions.
  • To create a portable system for monitoring vulnerable zones against aerial threats.
  • To address the security challenges posed by the increasing use of UAVs.

Main Methods:

  • Conducted an extensive analysis of the Chinese UAV market.
  • Designed a three-stage detection framework based on market research.
  • Evaluated the framework's performance across various operational scenarios.
  • Implemented the framework on a portable hardware platform.

Main Results:

  • The proposed framework successfully detected invading UAVs at an early stage.
  • The system demonstrated effectiveness even when UAVs were operating in stealth mode.
  • The framework's design is based on a thorough investigation of commercially available UAVs.

Conclusions:

  • The developed framework offers a viable solution for early-stage UAV detection.
  • The system's portability makes it suitable for deployment in restricted regions.
  • This technology can contribute to enhanced security in UAV-restricted zones.