Drone Detection Approach Based on Radio-Frequency Using Convolutional Neural Network

Sara Al-Emadi, Felwa Al-Senaid

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

95 Citations (Scopus)

Abstract

Recently, Unmanned Aerial Vehicles, also known as drones, are becoming rapidly popular due to the advancement of their technology and the significant decrease in their cost. Although commercial drones have proven their effectiveness in many day to day applications such as cinematography, agriculture monitoring and search and rescue, they are also being used in malicious activities that are targeting to harm individuals and societies which raises great privacy, safety and security concerns. In this research, we propose a new drone detection solution based on the Radio Frequency (RF) emitted during the live communication session between the drone and its controller using a Deep Learning (DL) technique, namely, the Convolutional Neural Network (CNN). The results of the study have proven the effectiveness of using CNN for drone detection with accuracy and F1 score of over 99.7% and drone identification with accuracy and F1 score of 88.4%. Moreover, the results yielded from this experiment have outperformed those reported in the literature for RF based drone detection using Deep Neural Networks.

Original languageEnglish
Title of host publication2020 IEEE International Conference on Informatics, IoT, and Enabling Technologies, ICIoT 2020
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages29-34
Number of pages6
ISBN (Electronic)9781728148212
DOIs
Publication statusPublished - Feb 2020
Externally publishedYes
Event2020 IEEE International Conference on Informatics, IoT, and Enabling Technologies, ICIoT 2020 - Doha, Qatar
Duration: 2 Feb 20205 Feb 2020

Publication series

Name2020 IEEE International Conference on Informatics, IoT, and Enabling Technologies, ICIoT 2020

Conference

Conference2020 IEEE International Conference on Informatics, IoT, and Enabling Technologies, ICIoT 2020
Country/TerritoryQatar
CityDoha
Period2/02/205/02/20

Keywords

  • CNN
  • Convolutional Neural Networks
  • DL
  • Deep learning
  • Drone Detection
  • Drone Identification
  • Infrastructure Security
  • ML
  • RF
  • Radio Frequency
  • machine learning

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