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Augmentation of Training Data for AI-based Drone Detection System

Farkas, Gábor (2026) Augmentation of Training Data for AI-based Drone Detection System. HADMÉRNÖK, 21 (2). pp. 119-135. ISSN 1788-1919

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Abstract

The increasing use of FPV drones in modern conflicts necessitates compact and energy-efficient detection systems capable of operating in dynamic electromagnetic environments. AI-based RF signal detection is a promising solution. However, its application can be limited by the lack of labelled datasets and the constraints of embedded platforms. This article presents a method for generating and augmenting training data directly from signals captured from analogue FPV video transmitters. Finally, a convolutional neural network was trained using the generated dataset and evaluated in a real-time environment. Experimental results demonstrate reliable detection performance, indicating that the proposed method is an effective and efficient solution for embedded FPV drone detection systems.

Item Type: Article
Uncontrolled Keywords: machine learning; electronic warfare; CUAV; ESM; Software-defined-radio; FPV drone;
Subjects: Q Science / természettudomány > QA Mathematics / matematika > QA76.527 Network technologies / Internetworking / hálózati technológiák, hálózatosodás
U Military Science / hadtudomány > U1 Military Science (General) / hadtudomány általában
SWORD Depositor: MTMT SWORD
Depositing User: MTMT SWORD
Date Deposited: 30 Sep 2026 08:13
Last Modified: 30 Sep 2026 08:13
URI: https://real.mtak.hu/id/eprint/248007

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