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Caractérisation de drones en vue de leur localisation et de leur suivi à partir d’une antenne de microphones

Abstract : This thesis work focuses on the acoustic identification of drones in order to design an array with few microphones (up to 10) and adapted to the frequencies emitted for localizing and tracking these devices. Characterization measurements have shown the inherent harmonic structure of the signal emitted by the UAV propulsion systems. A filtering step before the localization, adapted to this type of signal, is proposed. It consists of the detection of the fundamental frequency by the HPS (Harmonic Product Spectrum) algorithm and a series of bandpass filters to preserve the useful harmonics of the signal. Two methods of localization are compared through numerical simulations and experimental measurements. The first is beamforming in the time domain. Usually used for angular source localization, it is extended for localization in 3D space. The second, called acoustic goniometry, estimates the angular position of the target as a solution to an inverse problem. A Kalman filter is then used to track the target. An experimental measurement campaign made it possible to establish a database of the displacement of a small four-engine drone for different trajectories. Data analysis showed that a small number of harmonics (3 to 6) in the signal spectrum of the source to be located is sufficient to estimate the position of a source without significant loss in accuracy relative to a location without processing. The choice of this strategy is justified for localization and tracking in the presence of several drones.
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Submitted on : Friday, July 24, 2020 - 4:32:08 PM
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  • HAL Id : tel-02906392, version 1


Torea Blanchard. Caractérisation de drones en vue de leur localisation et de leur suivi à partir d’une antenne de microphones. Acoustique [physics.class-ph]. Université du Maine, 2019. Français. ⟨NNT : 2019LEMA1042⟩. ⟨tel-02906392⟩



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