H. Khudov, Serhii Yarosh, Oleksandr Kostyria, O. Oleksenko, Mykola Khomik, Andrey Zvonko, Bohdan Lisohorskyi, Petro Mynko, S. Sukonko, T. Kravets
{"title":"Improving a method for non-coherent processing of signals by a network of two small-sized radars for detecting a stealth unmanned aerial vehicle","authors":"H. Khudov, Serhii Yarosh, Oleksandr Kostyria, O. Oleksenko, Mykola Khomik, Andrey Zvonko, Bohdan Lisohorskyi, Petro Mynko, S. Sukonko, T. Kravets","doi":"10.15587/1729-4061.2024.298598","DOIUrl":null,"url":null,"abstract":"The object of this study is the process of detecting stealth unmanned aerial vehicles by a network of two small-sized radars with incoherent signal processing. The main hypothesis of the study assumed that combining two small-sized radars into a network could improve the quality of detection of stealth unmanned aerial vehicles with incoherent signal processing.\nThe improved method for detecting a stealth unmanned aerial vehicle by a network of two small-sized radars with incoherent signal processing, unlike the known ones, provides for the following:\n– synchronous inspection of the airspace by small-sized radars;\n– sounding signal emission by each small-sized radar;\n– reception of echo signals from a stealth unmanned aerial vehicle by two small-sized radars;\n– coordinated filtering of incoming echo signals (separation of echo signals);\n– quadratic detection of signals at the outputs of matched filters;\n– summation of the detected signals at the outputs of the matched filters;\n– summation of the outputs of adders of two small-sized radars.\nThe scheme of a stealth unmanned aerial vehicle detector is presented, optimal according to the Neumann-Pearson criterion, with incoherent signal processing.\nThe quality of detection of a stealth unmanned aerial vehicle by a network of two small-sized radars with incoherent signal processing was evaluated. It was found that with incoherent processing, the gain in the value of the conditional probability of correct detection is on average from 19 % to 26 %, depending on the value of the signal-to-noise ratio. The gain in the value of the conditional probability of correct detection is greater at low values of the signal-to-noise ratio. At the same time, the gain in signal-to-noise value is more significant with coherent signal processing than with non-coherent signal processing by a network of two small-sized radars","PeriodicalId":11433,"journal":{"name":"Eastern-European Journal of Enterprise Technologies","volume":"13 2","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2024-02-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Eastern-European Journal of Enterprise Technologies","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.15587/1729-4061.2024.298598","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"Mathematics","Score":null,"Total":0}
引用次数: 0
Abstract
The object of this study is the process of detecting stealth unmanned aerial vehicles by a network of two small-sized radars with incoherent signal processing. The main hypothesis of the study assumed that combining two small-sized radars into a network could improve the quality of detection of stealth unmanned aerial vehicles with incoherent signal processing.
The improved method for detecting a stealth unmanned aerial vehicle by a network of two small-sized radars with incoherent signal processing, unlike the known ones, provides for the following:
– synchronous inspection of the airspace by small-sized radars;
– sounding signal emission by each small-sized radar;
– reception of echo signals from a stealth unmanned aerial vehicle by two small-sized radars;
– coordinated filtering of incoming echo signals (separation of echo signals);
– quadratic detection of signals at the outputs of matched filters;
– summation of the detected signals at the outputs of the matched filters;
– summation of the outputs of adders of two small-sized radars.
The scheme of a stealth unmanned aerial vehicle detector is presented, optimal according to the Neumann-Pearson criterion, with incoherent signal processing.
The quality of detection of a stealth unmanned aerial vehicle by a network of two small-sized radars with incoherent signal processing was evaluated. It was found that with incoherent processing, the gain in the value of the conditional probability of correct detection is on average from 19 % to 26 %, depending on the value of the signal-to-noise ratio. The gain in the value of the conditional probability of correct detection is greater at low values of the signal-to-noise ratio. At the same time, the gain in signal-to-noise value is more significant with coherent signal processing than with non-coherent signal processing by a network of two small-sized radars
期刊介绍:
Terminology used in the title of the "East European Journal of Enterprise Technologies" - "enterprise technologies" should be read as "industrial technologies". "Eastern-European Journal of Enterprise Technologies" publishes all those best ideas from the science, which can be introduced in the industry. Since, obtaining the high-quality, competitive industrial products is based on introducing high technologies from various independent spheres of scientific researches, but united by a common end result - a finished high-technology product. Among these scientific spheres, there are engineering, power engineering and energy saving, technologies of inorganic and organic substances and materials science, information technologies and control systems. Publishing scientific papers in these directions are the main development "vectors" of the "Eastern-European Journal of Enterprise Technologies". Since, these are those directions of scientific researches, the results of which can be directly used in modern industrial production: space and aircraft industry, instrument-making industry, mechanical engineering, power engineering, chemical industry and metallurgy.