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Detection and Identification of Non-cooperative UAV Using a COTS mmWave Radar

Published: 16 February 2024 Publication History

Abstract

Small Unmanned Aerial Vehicles (UAVs) are becoming potential threats to security-sensitive areas and personal privacy. A UAV can shoot photos at height, but how to detect such an uninvited intruder is an open problem. This article presents mmHawkeye, a passive approach for non-cooperative UAV detection and identification with a commercial off-the-shelf millimeter wave (mmWave) radar. mmHawkeye does not require prior knowledge of the type, motions, and flight trajectory of the UAV, while exploiting the signal feature induced by the UAV’s periodic micro-motion (PMM) for long-range accurate detection. The design is therefore effective in dealing with low signal-to-noise ratio and uncertain reflected signals from the UAV. After analyzing the theoretical model of the PMM feature, mmHawkeye can further track the UAV’s position containing range, azimuth and altitude angle with dynamic programming and particle filtering and then identify it with a Long Short-Term Memory–based detector. We implement mmHawkeye on a commercial mmWave radar and evaluate its performance under varied settings. The experimental results show that mmHawkeye has a detection accuracy of 95.8% and can realize detection at a range up to 80 m.

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Cited By

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  • (2024)RaDro: Indoor Drone Tracking Using Millimeter Wave RadarProceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies10.1145/36785498:3(1-23)Online publication date: 9-Sep-2024

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Information

Published In

cover image ACM Transactions on Sensor Networks
ACM Transactions on Sensor Networks  Volume 20, Issue 2
March 2024
572 pages
EISSN:1550-4867
DOI:10.1145/3618080
  • Editor:
  • Wen Hu
Issue’s Table of Contents

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Association for Computing Machinery

New York, NY, United States

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Publication History

Published: 16 February 2024
Online AM: 27 December 2023
Accepted: 23 December 2023
Revised: 01 November 2023
Received: 19 July 2023
Published in TOSN Volume 20, Issue 2

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Author Tags

  1. Passive detection
  2. periodic micro-motion
  3. LSTM
  4. millimeter Wave
  5. UAV

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  • National Science Fund of China
  • Tsinghua University - Meituan Joint Institute for Digital Life

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  • (2024)RaDro: Indoor Drone Tracking Using Millimeter Wave RadarProceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies10.1145/36785498:3(1-23)Online publication date: 9-Sep-2024

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