Abstract
The paper considers basic provisions concerning the formulation and solution of the problem of detecting small unmanned aerial vehicles (drones) based on the analysis of acoustic fields generated by the drone. The concept of the potential detection range is introduced as the maximum attainable value of the distance between the drone and the place of installation of the receiving microphone, at which the acoustic signal exceeds the level of thermal noise of the receiving device by ten decibels. Distinctive features of drone noise from background noise are detected by the method of model correlation analysis introduced by the authors in previous works. As a result, three-dimensional structures are formed in the shape of a matrix of correlation coefficients between a sample of drone noise signals or background noise and a model of the component of the signal. As a result of comparing the three-dimensional structures of the drone noise and background noise, it is concluded that the analysis of period fluctuations at small time intervals makes it possible to increase the distinguishability of signs of the drone signal in developed background noise. The averaging is calculated along the axis of the time shift of the three-dimensional structure, the dependence of the correlation coefficient on the period of the model with its subsequent normalization to the maximum. It is concluded that the parametrization of such dependence will make it possible to formalize the process of detection and classification of signals relative to the model of the detected drone.
Published Version
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