Advances and Challenges in Drone Detection and Classification Techniques

Advances and Challenges in Drone Detection and Classification Techniques

Practical Solutions and Value in Drone Detection and Classification Techniques

Introduction

In recent years, advancements in micro uncrewed aerial vehicles (UAVs) and drones have expanded applications and technical capabilities.

Comparison of Satellite, Aircraft and UAV

UAVs offer high resolution with moderate availability and operating costs, bridging the limitations of both satellite and aircraft systems.

Significance of UAV Detection

The increasing use of drones across industries raises concerns about privacy, security, and safety, necessitating effective detection systems.

Key Challenges to UAV Detection

Detecting and classifying UAVs pose significant challenges due to their diverse sizes, speeds, dynamic behaviors, and environmental conditions.

Drone Detection Technologies

Radar-Based Detection:

  • Utilizes electromagnetic waves to detect and locate objects.
  • Offers attributes like distance, velocity, azimuth, and elevation.

Radio Frequency (RF)-Based Detection:

  • Detects drones by capturing RF signals emitted by onboard electronics.
  • It often detects drones in no-fly zones by intercepting communication signals between drones and ground stations.

Acoustic-Based Detection:

  • Relies on distinct acoustic signatures generated by drones.
  • It uses specialized audio sensors to capture drone noises, analyzing frequency, amplitude, modulation, and duration for detection.

Vision-Based Detection:

  • It involves capturing visual data from drones using camera sensors and computer-vision-based object detection algorithms.
  • Processes images or videos to detect drones, utilizing image acquisition and object recognition techniques.

Sensor Fusion and Other Methods:

  • Integrates multiple modalities to enhance drone detection, tracking, and classification.
  • Utilizes fusion techniques to effectively merge data from various sensors, increasing the detection system’s robustness and accuracy.

Conclusion

The survey underscores the burgeoning field of drone detection and classification, which is crucial in addressing privacy, security, and safety concerns amid the rapid proliferation of UAVs.

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