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A Novel Multi-Objective Maxwell's Equations Derived Optimization Algorithm and Application in Sparse Antenna Array Synthesis

  • Haoyang Zhang
  • , Xin Zhang
  • , Tong Wang
  • , Lilin Li*
  • , Donglin Su
  • *Corresponding author for this work
  • Beihang University

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

Abstract

Planar sparse array synthesis plays a critical role in modern radar and wireless communication systems. However, it remains challenging to simultaneously minimize the number of antenna elements while maintaining a low peak sidelobe level. Inspired by typical electromagnetic compatibility (EMC) phenomena, we previously developed the Maxwell's Equations Derived Optimization (MEDO) algorithm, which enables accurate and robust solutions for complex electromagnetic optimization problems. In this paper, we extend MEDO to a multi-objective version (MO-MEDO), by incorporating non-dominated sorting with elitism and an external archive mechanism for Pareto front preservation. The proposed MO-MEDO algorithm exhibits excellent performance in sparse planar array synthesis, effectively achieving a favorable trade-off between array sparsity and sidelobe suppression.

Original languageEnglish
Title of host publicationAPMC 2025 - 2025 Asia-Pacific Microwave Conference
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9798331534554
DOIs
StatePublished - 2025
Event2025 Asia-Pacific Microwave Conference, APMC 2025 - Jeju Island, Korea, Republic of
Duration: 2 Dec 20255 Dec 2025

Publication series

NameAsia-Pacific Microwave Conference Proceedings, APMC
ISSN (Electronic)2690-3946

Conference

Conference2025 Asia-Pacific Microwave Conference, APMC 2025
Country/TerritoryKorea, Republic of
CityJeju Island
Period2/12/255/12/25

Keywords

  • Maxwell's Equations Derived Optimization (MEDO)
  • multi-objective optimization
  • sparse plane array

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