Automatic system for determining the UAV coordinates in multi-position sound monitoring systems

Abstract

The purpose of the work is to develop an automatic detection system for unmanned aerial vehicles on the basis of sound information The paper deals with sensors methods and algorithms for increasing the accuracy of UAV coordinate detection based on the modified Newton method. The Newton method was studied with the aim of reducing the time of calculating coordinates. It is established that in order to obtain sufficient accuracy of coordinate detection, the Jacobi matrix must be calculated on the first three steps of the iteration. A study of parametric sensitivity of the difference-range-finding method was conducted and it was established that the relative error in detecting the arrival delay time of the signal should be within 5%, only then correct identification of the coordinates may be possible. In addition, an extremal statement of the problem of the difference-distance-finding method was investigated on the basis of the quadratic function minimization method, which allows taking into account the relative error ofdetermining the delay time of arrival of a signal on each of the stations separately by introducing a weight coefficient. The emergence of unmanned aerial vehicles with less noisy engines significantly reduced the quality of their detection and signal processing, forcing developers to look for new ways and means to increase the accuracy of detection and impedance of individual vehicles and air defense groups. In turn, passive means of sound monitoring have a significant advantage over active means, consisting mainly of the hidden work of their work. However, the exact characteristics of determining the coordinates of passive systems of the sacred location are considerably inferior to similar characteristics of the active systems. In view of the rather high errors (10% and above) of UAV coordinates measurements, the problem of increasing the accuracy of their operation remains relevant for passive sound monitoring systems.