Detection and Classification of Multirotor Drones in Radar Sensor Networks: A Review
Thanks to recent technological advances, a new generation of low-cost, small, unmanned aerial vehicles (UAVs) is available. Small UAVs, often called drones, are enabling unprecedented applications but, at the same time, new threats are arising linked to their possible misuse (e.g., drug smuggling, t...
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doaj-491dbd9b99ab4843b666eeb82e921b172020-11-25T03:28:36ZengMDPI AGSensors1424-82202020-07-01204172417210.3390/s20154172Detection and Classification of Multirotor Drones in Radar Sensor Networks: A ReviewAngelo Coluccia0Gianluca Parisi1Alessio Fascista2Dipartimento di Ingegneria dell’Innovazione, University of Salento, via Monteroni, 73100 Lecce, ItalyDipartimento di Ingegneria dell’Innovazione, University of Salento, via Monteroni, 73100 Lecce, ItalyDipartimento di Ingegneria dell’Innovazione, University of Salento, via Monteroni, 73100 Lecce, ItalyThanks to recent technological advances, a new generation of low-cost, small, unmanned aerial vehicles (UAVs) is available. Small UAVs, often called drones, are enabling unprecedented applications but, at the same time, new threats are arising linked to their possible misuse (e.g., drug smuggling, terrorist attacks, espionage). In this paper, the main challenges related to the problem of drone identification are discussed, which include detection, possible verification, and classification. An overview of the most relevant technologies is provided, which in modern surveillance systems are composed into a network of spatially-distributed sensors to ensure full coverage of the monitored area. More specifically, the main focus is on the frequency modulated continuous wave (FMCW) radar sensor, which is a key technology also due to its low cost and capability to work at relatively long distances, as well as strong robustness to illumination and weather conditions. This paper provides a review of the existing literature on the most promising approaches adopted in the different phases of the identification process, i.e., detection of the possible presence of drones, target verification, and classification.https://www.mdpi.com/1424-8220/20/15/4172multi-rotor dronesUAVdetectionclassificationradar |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Angelo Coluccia Gianluca Parisi Alessio Fascista |
spellingShingle |
Angelo Coluccia Gianluca Parisi Alessio Fascista Detection and Classification of Multirotor Drones in Radar Sensor Networks: A Review Sensors multi-rotor drones UAV detection classification radar |
author_facet |
Angelo Coluccia Gianluca Parisi Alessio Fascista |
author_sort |
Angelo Coluccia |
title |
Detection and Classification of Multirotor Drones in Radar Sensor Networks: A Review |
title_short |
Detection and Classification of Multirotor Drones in Radar Sensor Networks: A Review |
title_full |
Detection and Classification of Multirotor Drones in Radar Sensor Networks: A Review |
title_fullStr |
Detection and Classification of Multirotor Drones in Radar Sensor Networks: A Review |
title_full_unstemmed |
Detection and Classification of Multirotor Drones in Radar Sensor Networks: A Review |
title_sort |
detection and classification of multirotor drones in radar sensor networks: a review |
publisher |
MDPI AG |
series |
Sensors |
issn |
1424-8220 |
publishDate |
2020-07-01 |
description |
Thanks to recent technological advances, a new generation of low-cost, small, unmanned aerial vehicles (UAVs) is available. Small UAVs, often called drones, are enabling unprecedented applications but, at the same time, new threats are arising linked to their possible misuse (e.g., drug smuggling, terrorist attacks, espionage). In this paper, the main challenges related to the problem of drone identification are discussed, which include detection, possible verification, and classification. An overview of the most relevant technologies is provided, which in modern surveillance systems are composed into a network of spatially-distributed sensors to ensure full coverage of the monitored area. More specifically, the main focus is on the frequency modulated continuous wave (FMCW) radar sensor, which is a key technology also due to its low cost and capability to work at relatively long distances, as well as strong robustness to illumination and weather conditions. This paper provides a review of the existing literature on the most promising approaches adopted in the different phases of the identification process, i.e., detection of the possible presence of drones, target verification, and classification. |
topic |
multi-rotor drones UAV detection classification radar |
url |
https://www.mdpi.com/1424-8220/20/15/4172 |
work_keys_str_mv |
AT angelocoluccia detectionandclassificationofmultirotordronesinradarsensornetworksareview AT gianlucaparisi detectionandclassificationofmultirotordronesinradarsensornetworksareview AT alessiofascista detectionandclassificationofmultirotordronesinradarsensornetworksareview |
_version_ |
1724583117752107008 |