Аннотация:The increasingly widespread use of unmanned aerial vehicles (UAVs) requires improved methods of their detection. In some cases, this is only possible by analyzing the physical fields created by the UAV. This work is dedicated to the study of the UAV’s acoustic field as applied to the problem of passive detection. In the laboratory, the acoustic fields of the most popular quadcopters were studied, as well as the properties of individual propellers of various designs. The influence of blade defects on the resulting spectral portrait was analyzed. Based on the results of numerical simulations in the COMSOL Multiphysics software package, directional patterns and pressure variations caused by a rotating propeller are obtained. A neural network has been trained to analyze the kepstrum coefficients calculated from acoustic records. The neural network allows monitoring and recognizing the presence of a quadrocopter in an area of interest, taking into account natural and anthropogenic noises. Field experiments carried out in urban conditions made it possible to estimate the range of possible passive detection of an unmanned aerial vehicle. This work was financially supported by the Russian Foundation for Basic Research (project No. 19-29-06062).
