Drone classification using RF signal based spectral features-Reference-Cited by-同舟云学术

Drone classification using RF signal based spectral features

Published:2022-04 Issue: Volume:28 Page:101028
ISSN:2215-0986
Container-title:Engineering Science and Technology, an International Journal
language:en
Short-container-title:Engineering Science and Technology, an International Journal

Author:

Kılıç Rabiye,Kumbasar Nida,Oral Emin Argun,Ozbek Ibrahim Yucel

Publisher

Elsevier BV

Subject

Metals and Alloys,Computer Networks and Communications,Fluid Flow and Transfer Processes,Hardware and Architecture,Mechanical Engineering,Biomaterials,Civil and Structural Engineering,Electronic, Optical and Magnetic Materials

Reference43 articles.

1. U. Commercial, Commercial drone market analysis by product (fixed wing, rotary blade, nano, hybrid), by application (agriculture, energy, government, media & entertainment) and segment forecasts to 2022, Grand View Research: San Francisco, CA, USA

2. An amateur drone surveillance system based on the cognitive internet of things;Ding;IEEE Communications Magazine,2018

3. Radar Cross Section;Knott,2004

4. Classification of small uavs and birds by micro-doppler signatures, in: 2013 European Radar Conference;Molchanov,2013

5. Classification of uav and bird target in low-altitude airspace with surveillance radar data;Chen;The Aeronautical Journal,2019

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