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Radar Determination of Elevation of Two Nearby Targets Using Neural Network

The result's identifiers

  • Result code in IS VaVaI

    <a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216275%3A25530%2F24%3A39922709" target="_blank" >RIV/00216275:25530/24:39922709 - isvavai.cz</a>

  • Result on the web

    <a href="https://ieeexplore.ieee.org/document/10616003" target="_blank" >https://ieeexplore.ieee.org/document/10616003</a>

  • DOI - Digital Object Identifier

    <a href="http://dx.doi.org/10.1109/ACCESS.2024.3436078" target="_blank" >10.1109/ACCESS.2024.3436078</a>

Alternative languages

  • Result language

    angličtina

  • Original language name

    Radar Determination of Elevation of Two Nearby Targets Using Neural Network

  • Original language description

    Monopulse methods have been successfully used in radar to determine the direction of arrival of a reflected signal, giving good results when a single isolated target is involved. However, when two nearby targets need to be detected and their angular position determined, this method fails. We show that it is possible to train and use a neural network to recognize two nearby targets. This neural network is then used to determine the angle of arrival of the reflected signal with sufficient accuracy, even when the distance of the targets is less than the beamwidth. We show the results on an eight-beam antenna model by measuring the elevation using an amplitude monopulse and neural network method. While using monopulse, we can reliably discriminate and determine the angular position of two targets only when their distance is larger than one beamwidth. The neural network method works reliably even for targets at distances much smaller.

  • Czech name

  • Czech description

Classification

  • Type

    J<sub>imp</sub> - Article in a specialist periodical, which is included in the Web of Science database

  • CEP classification

  • OECD FORD branch

    20201 - Electrical and electronic engineering

Result continuities

  • Project

  • Continuities

    I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace

Others

  • Publication year

    2024

  • Confidentiality

    S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Data specific for result type

  • Name of the periodical

    IEEE ACCESS

  • ISSN

    2169-3536

  • e-ISSN

  • Volume of the periodical

    12

  • Issue of the periodical within the volume

    Neuveden

  • Country of publishing house

    US - UNITED STATES

  • Number of pages

    7

  • Pages from-to

    105481-105487

  • UT code for WoS article

    001286621500001

  • EID of the result in the Scopus database

    2-s2.0-85200201690