Improving a method for detecting and measuring coordinates of a stealth aerial vehicle by a network of two small-sized radars
DOI:
https://doi.org/10.15587/1729-4061.2023.293276Keywords:
small-sized radar, determination of coordinates, two-position network, conditional probability of correct detectionAbstract
The object of this study is the process of detecting and determining the coordinates of stealth unmanned aerial vehicles by a network of two small-sized radars. The main hypothesis of the study assumes that the use of two small-sized radars, which are connected in a network, could improve the quality of detection and determination of the coordinates of stealth unmanned aerial vehicles.
The improved method for detecting and determining the coordinates of a stealth unmanned aerial vehicle, unlike the known ones, enables the following:
– synchronous inspection of the airspace;
– reception of the signal reflected from a stealth unmanned aerial vehicle by two small-sized radars;
– carrying out coordinated filtering of incoming signals;
– compensation of phase shifts and coherent addition of output signals from matched filters;
– formation of Doppler channels in each small-sized radar and formation of a complex envelope from the output of the corresponding Doppler channel;
– coherent processing (addition) of signals;
– compensation of the random initial phase of signals reflected from a stealth unmanned aerial vehicle by detecting the output signal from the coherent adder;
– measuring the range to a stealth unmanned aerial vehicle by each small-sized radar;
– calculation of the coordinates of a stealth unmanned aerial vehicle.
It was established that at low signal/noise values, the gain in terms of the conditional probability of correct detection is from 25 % to 32 %. It was determined that the use of a network of two small-sized radars makes it possible to reduce the mean square error in determining the coordinates of a stealth unmanned aerial vehicle from 28 % to 37 % on average
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Copyright (c) 2023 Hennadii Khudov, Andrii Berezhnyi, Serhii Yarosh, Oleksandr Oleksenko, Mykola Khomik, Iryna Yuzova, Andrii Zvonko, Serhii Yarovyi, Sergey Glukhov, Anatolii Sobora
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