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Optimizing the architecture of planar phased array by improved genetic algorithm

  • Hang Hu*
  • , Weicheng Qin
  • , Shuo Feng
  • *Corresponding author for this work
  • Harbin Institute of Technology

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

An architecture optimizing method in planar phased array is given based on Genetic Algorithm (GA). Pattern sidelobe is improved by optimizing array architecture via division of subarrays. Analyze subarray pattern and give out the flow chart of subarray segmentation. By adaptive crossover operator and independent genetic operation, traditional GA is improved. Convergence speed is accelerated and calculation efficiency is enhanced remarkably. Simulations of segmenting 24×28 array into 50 subarrays are provided. Pattern sidelobe is improved by 14.22dB after 60 generations of GA.

Original languageEnglish
Title of host publicationIEEE 2007 International Symposium on Microwave, Antenna, Propagation and EMC Technologies for Wireless Communications, MAPE
PublisherIEEE Computer Society
Pages676-679
Number of pages4
ISBN (Print)1424410444, 9781424410446
DOIs
StatePublished - 2007
Event2007 IEEE International Symposium on Microwave, Antenna, Propagation, and EMC Technologies for Wireless Communications, MAPE 2007 - Hangzhou, China
Duration: 14 Aug 200717 Aug 2007

Publication series

NameIEEE 2007 International Symposium on Microwave, Antenna, Propagation and EMC Technologies for Wireless Communications, MAPE

Conference

Conference2007 IEEE International Symposium on Microwave, Antenna, Propagation, and EMC Technologies for Wireless Communications, MAPE 2007
Country/TerritoryChina
CityHangzhou
Period14/08/0717/08/07

Keywords

  • Adaptive crossover operator
  • Improved genetic algorithm
  • Planar phased array
  • Subarray segmentation

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