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Authors: Alberto Lupidi 1 ; Alessandro Cantelli-Forti 1 ; Edmond Jajaga 2 and Walter Matta 3

Affiliations: 1 CNIT, National Laboratory of Radar and Surveillance Systems, Pisa, Italy ; 2 Mother Teresa University, Skopje, North Macedonia ; 3 Link Campus University, Roma, Italy

Keyword(s): Artificial Intelligence, Miniradar, UAS, ATS, Data Assurance.

Abstract: The foundation of Internet Information Systems has been initially inspired by military applications. Means of air attack are pervasive in all modern armed conflicts or terrorist actions. Thus, building web-enabled, real-time, rapid and intelligent distributed decision-making systems is of immense importance. We present the intermediate results of the NATO-SPS project “Anti-Drones” that aims to fuse data from low-probability-of-intercept mini radars and a network of optical sensors communicating with web interfaces. The main focus of this paper is describing the architecture of the system and the low-cost miniradar sensor exploiting micro-Doppler effect to detect, track and recognize threats. The recognition of the target via an artificial intelligence system is the pillar to assess these threats in a reliable way.

CC BY-NC-ND 4.0

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Paper citation in several formats:
Lupidi, A. ; Cantelli-Forti, A. ; Jajaga, E. and Matta, W. (2022). An Artificial Intelligence Application for a Network of LPI-FMCW Mini-radar to Recognize Killer-drones. In Proceedings of the 18th International Conference on Web Information Systems and Technologies - WEBIST; ISBN 978-989-758-613-2; ISSN 2184-3252, SciTePress, pages 320-326. DOI: 10.5220/0011590300003318

@conference{webist22,
author={Alberto Lupidi and Alessandro Cantelli{-}Forti and Edmond Jajaga and Walter Matta},
title={An Artificial Intelligence Application for a Network of LPI-FMCW Mini-radar to Recognize Killer-drones},
booktitle={Proceedings of the 18th International Conference on Web Information Systems and Technologies - WEBIST},
year={2022},
pages={320-326},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0011590300003318},
isbn={978-989-758-613-2},
issn={2184-3252},
}

TY - CONF

JO - Proceedings of the 18th International Conference on Web Information Systems and Technologies - WEBIST
TI - An Artificial Intelligence Application for a Network of LPI-FMCW Mini-radar to Recognize Killer-drones
SN - 978-989-758-613-2
IS - 2184-3252
AU - Lupidi, A.
AU - Cantelli-Forti, A.
AU - Jajaga, E.
AU - Matta, W.
PY - 2022
SP - 320
EP - 326
DO - 10.5220/0011590300003318
PB - SciTePress

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