Analysis of the frequency-time structure of acoustic noises of unmanned aerial vehicles in the STM32 CubeIDE environment - Leonidov, V.I.; Semenets, V.V.; Grigoriev, A.B. (Radiotekhnika, 2023)
The formulation of the task of detecting small unmanned aerial vehicles (drones) is presented, the expediency of building a drone detection system in the stm32 cubeide environment based on the principle of reception and analysis of acoustic signals emitted by drones during their flight mission is substantiated. The study of temporal fluctuations in the period of acoustic signals of a drone is carried out by the method of model-correlation analysis, as a result of which three-dimensional structures are formed: time – period – correlation coefficient of the acoustic signal with the model in the form of a time-limited sinusoidal function. The resulting structures are formed as matrices of correlation coefficient values. The members located along the columns are calculated by time shifting the model function along the signal sample. The members in each column are calculated with a constant period of the model function given from a series of values. It is shown that the correlation coefficients between the rows of the matrices calculated from drone signals are significantly higher than the same values obtained from background noise measurements. The functions showing the change in time of the correlation coefficients between the rows of the time-period matrix structures for drone signals and background noise do not overlap and show a consistently larger difference in correlation coefficients, which allows us to use the correlation coefficient as a feature that classifies the presence of drone signals.