Information for graduates

VILNIUS TECH Library invites you to follow the published new dissertations. The dissertation „Research and development of methods for detection and recognition of unmanned aerial vehicles“ prepared at VILNIUS TECH by Tomas Jačionis. The dissertation was prepared in 2018–2026. Scientific consultant – Prof. Dr Vytautas Urbanavičius. The dissertation was defended at the public meeting of the Dissertation Defence Council of the Scientific Field of Electrical and Electronic Engineering in the Aula Doctoralis Meeting Hall of Vilnius Gediminas Technical University at 10 a.m. on 16 September 2026. Unmanned Aerial Vehicle (UAV) detection has become a critical element of modern security systems. It is essential for safeguarding national security, maintaining airspace sovereignty, and protecting critical infrastructure, including power networks, military facilities, and fuel manufacturing and storage sites. As UAV technologies become more advanced and accessible, reliable detection methods are increasingly required to counter emerging threats. Artificial intelligence integrated into UAV flight-control systems is increasingly enabling UAVs to operate without emitting radio communication signals, which have traditionally been exploited for detection via electromagnetic (EM) spectrum analysis. This technological development creates substantial challenges for detecting UAVs, UAV swarms, kamikaze-type drones, and other electrically powered UAVs, particularly when they operate in complete radio silence. The dissertation proposes a novel method for detecting electrically powered multirotor UAVs by analysing and identifying the EM signatures radiated by their electric propulsion motor systems. An EM signature is the measurable pattern of the EM radiation spectrum produced by a UAV’s electric propulsion system due to time-varying electrical currents and voltages. It is characterised by distinct frequency, amplitude, and time features that enable the detection and identification of EM sources, including UAVs, through their propulsion-related EM emissions. These EM signatures vary dynamically with flight conditions, thereby providing a new detection modality even when conventional radio-frequency-based methods are ineffective. The dissertation proposes theoretical models of the EM radiation of a quadcopter UAV electric propulsion system and of the EM signature structure of UAV brushless direct current (BLDC) propulsion motors. The quadcopter UAV model enables assessment of radiation intensity and directivity. In contrast, the EM signature structure model reveals the dependence of the BLDC motor frequency spectrum on the pulse-width-modulated supply-current duty cycle and on the switching and phase-commutation frequencies. An experimental investigation was conducted to analyse the EM signatures radiated by the airborne UAV’s electric propulsion system. The findings include a detailed comparison of the EM signatures of various UAV models with those of similar electric motors used in domestic appliances. The results for the EM signatures of four serial-production UAVs are presented, including a case of a UAV swarm EM signature. The proposed mathematical model and experimental results demonstrate the feasibility of reliably recognising and classifying the EM signatures of an electrically powered multirotor UAV. Doctoral dissertation readers can search via VILNIUS TECH Virtual Library.

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