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Low RCS Antenna Design Using Genetic Algorithm Combined with Tabu List.

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Τίτλος: Low RCS Antenna Design Using Genetic Algorithm Combined with Tabu List.
Συγγραφείς: Zhu, Xinyue, Shao, Wei, Li, Jia-Lin
Πηγή: Applied Computational Electromagnetics Society Journal; Jul2013, Vol. 27 Issue 7, p574-580, 7p
Θεματικοί όροι: Antenna design, Radar cross sections, Genetic algorithms, Mathematical optimization, VBScript (Computer program language), Electromagnetic fields, Computer simulation, Parameters (Statistics)
Περίληψη: In this paper, a simple and efficient approach is presented to reduce the radar cross section (RCS) of patch antennas with defected ground structures (DGSs). This approach consists of an optimization algorithm, which combines a genetic algorithm (GA) with tabu list, and electromagnetic field solver. A tabu list, embedded into the GA frame, defines the acceptable neighborhood region of parameters and screens out the bad individuals. Thus, the repeats of search are avoided and the amount of electromagnetic simulation is largely reduced. Moreover, the whole design procedure is auto-controlled by programming the VBScript language. A patch antenna example is provided to verify the accuracy and efficiency of the proposed design method. [ABSTRACT FROM AUTHOR]
Copyright of Applied Computational Electromagnetics Society Journal is the property of River Publishers and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
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  Data: Low RCS Antenna Design Using Genetic Algorithm Combined with Tabu List.
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  Data: <searchLink fieldCode="AR" term="%22Zhu%2C+Xinyue%22">Zhu, Xinyue</searchLink><br /><searchLink fieldCode="AR" term="%22Shao%2C+Wei%22">Shao, Wei</searchLink><br /><searchLink fieldCode="AR" term="%22Li%2C+Jia-Lin%22">Li, Jia-Lin</searchLink>
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  Data: Applied Computational Electromagnetics Society Journal; Jul2013, Vol. 27 Issue 7, p574-580, 7p
– Name: Subject
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  Data: <searchLink fieldCode="DE" term="%22Antenna+design%22">Antenna design</searchLink><br /><searchLink fieldCode="DE" term="%22Radar+cross+sections%22">Radar cross sections</searchLink><br /><searchLink fieldCode="DE" term="%22Genetic+algorithms%22">Genetic algorithms</searchLink><br /><searchLink fieldCode="DE" term="%22Mathematical+optimization%22">Mathematical optimization</searchLink><br /><searchLink fieldCode="DE" term="%22VBScript+%28Computer+program+language%29%22">VBScript (Computer program language)</searchLink><br /><searchLink fieldCode="DE" term="%22Electromagnetic+fields%22">Electromagnetic fields</searchLink><br /><searchLink fieldCode="DE" term="%22Computer+simulation%22">Computer simulation</searchLink><br /><searchLink fieldCode="DE" term="%22Parameters+%28Statistics%29%22">Parameters (Statistics)</searchLink>
– Name: Abstract
  Label: Abstract
  Group: Ab
  Data: In this paper, a simple and efficient approach is presented to reduce the radar cross section (RCS) of patch antennas with defected ground structures (DGSs). This approach consists of an optimization algorithm, which combines a genetic algorithm (GA) with tabu list, and electromagnetic field solver. A tabu list, embedded into the GA frame, defines the acceptable neighborhood region of parameters and screens out the bad individuals. Thus, the repeats of search are avoided and the amount of electromagnetic simulation is largely reduced. Moreover, the whole design procedure is auto-controlled by programming the VBScript language. A patch antenna example is provided to verify the accuracy and efficiency of the proposed design method. [ABSTRACT FROM AUTHOR]
– Name: Abstract
  Label:
  Group: Ab
  Data: <i>Copyright of Applied Computational Electromagnetics Society Journal is the property of River Publishers and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.)
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RecordInfo BibRecord:
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    Languages:
      – Code: eng
        Text: English
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      Pagination:
        PageCount: 7
        StartPage: 574
    Subjects:
      – SubjectFull: Antenna design
        Type: general
      – SubjectFull: Radar cross sections
        Type: general
      – SubjectFull: Genetic algorithms
        Type: general
      – SubjectFull: Mathematical optimization
        Type: general
      – SubjectFull: VBScript (Computer program language)
        Type: general
      – SubjectFull: Electromagnetic fields
        Type: general
      – SubjectFull: Computer simulation
        Type: general
      – SubjectFull: Parameters (Statistics)
        Type: general
    Titles:
      – TitleFull: Low RCS Antenna Design Using Genetic Algorithm Combined with Tabu List.
        Type: main
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          Name:
            NameFull: Zhu, Xinyue
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            NameFull: Shao, Wei
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            NameFull: Li, Jia-Lin
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          Dates:
            – D: 01
              M: 07
              Text: Jul2013
              Type: published
              Y: 2012
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              Value: 27
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              Value: 7
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            – TitleFull: Applied Computational Electromagnetics Society Journal
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