{"title":"基于战争策略优化的天线阵列图案合成和微带贴片天线优化方法","authors":"Renjing Gao, Wei Tong, Mingyue Zhang, Qi Wang","doi":"10.1007/s10825-024-02210-4","DOIUrl":null,"url":null,"abstract":"<div><p>This paper first presents an application of the war strategy optimization (WSO) algorithm in pattern synthesis of antenna arrays and dimensions optimization of microstrip patch antenna. As a new type of evolutionary algorithm inspired by nature, the WSO algorithm has global optimization ability in solving complex problem including nonlinearity and nonconvexity; therefore, it will exhibit the potential advantages in the above two typical multivariate nonlinear problems. For solving pattern synthesis problem, the sidelobe reduction synthesis and null controlling of linear antenna arrays with different element are selected as numerical cases, and the WSO algorithm achieves the desired main beams width and null depth by optimizing the amplitude-only and the phase-only, respectively. For dimensions optimization of microstrip patch antenna, the WSO algorithm realizes the minimized reflection coefficient (S<sub>11</sub>) of − 80 dB at 3.1G Hz by optimizing the width and length of rectangle patch antenna. Moreover, compared with the Grasshopper optimization algorithm, the gray wolf optimization algorithm, and the invasive weed optimization algorithm, the WSO algorithm shows higher computational accuracy and faster convergence speed for solving the above two types of optimization problem. Therefore, the WSO algorithm can be widely used to in electromagnetic structure design.</p></div>","PeriodicalId":620,"journal":{"name":"Journal of Computational Electronics","volume":"23 5","pages":"1125 - 1134"},"PeriodicalIF":2.2000,"publicationDate":"2024-08-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"War strategy optimization-based methods for pattern synthesis of antenna arrays and optimization of microstrip patch antenna\",\"authors\":\"Renjing Gao, Wei Tong, Mingyue Zhang, Qi Wang\",\"doi\":\"10.1007/s10825-024-02210-4\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><p>This paper first presents an application of the war strategy optimization (WSO) algorithm in pattern synthesis of antenna arrays and dimensions optimization of microstrip patch antenna. As a new type of evolutionary algorithm inspired by nature, the WSO algorithm has global optimization ability in solving complex problem including nonlinearity and nonconvexity; therefore, it will exhibit the potential advantages in the above two typical multivariate nonlinear problems. For solving pattern synthesis problem, the sidelobe reduction synthesis and null controlling of linear antenna arrays with different element are selected as numerical cases, and the WSO algorithm achieves the desired main beams width and null depth by optimizing the amplitude-only and the phase-only, respectively. For dimensions optimization of microstrip patch antenna, the WSO algorithm realizes the minimized reflection coefficient (S<sub>11</sub>) of − 80 dB at 3.1G Hz by optimizing the width and length of rectangle patch antenna. Moreover, compared with the Grasshopper optimization algorithm, the gray wolf optimization algorithm, and the invasive weed optimization algorithm, the WSO algorithm shows higher computational accuracy and faster convergence speed for solving the above two types of optimization problem. Therefore, the WSO algorithm can be widely used to in electromagnetic structure design.</p></div>\",\"PeriodicalId\":620,\"journal\":{\"name\":\"Journal of Computational Electronics\",\"volume\":\"23 5\",\"pages\":\"1125 - 1134\"},\"PeriodicalIF\":2.2000,\"publicationDate\":\"2024-08-08\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Journal of Computational Electronics\",\"FirstCategoryId\":\"5\",\"ListUrlMain\":\"https://link.springer.com/article/10.1007/s10825-024-02210-4\",\"RegionNum\":4,\"RegionCategory\":\"工程技术\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q3\",\"JCRName\":\"ENGINEERING, ELECTRICAL & ELECTRONIC\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Computational Electronics","FirstCategoryId":"5","ListUrlMain":"https://link.springer.com/article/10.1007/s10825-024-02210-4","RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"ENGINEERING, ELECTRICAL & ELECTRONIC","Score":null,"Total":0}
War strategy optimization-based methods for pattern synthesis of antenna arrays and optimization of microstrip patch antenna
This paper first presents an application of the war strategy optimization (WSO) algorithm in pattern synthesis of antenna arrays and dimensions optimization of microstrip patch antenna. As a new type of evolutionary algorithm inspired by nature, the WSO algorithm has global optimization ability in solving complex problem including nonlinearity and nonconvexity; therefore, it will exhibit the potential advantages in the above two typical multivariate nonlinear problems. For solving pattern synthesis problem, the sidelobe reduction synthesis and null controlling of linear antenna arrays with different element are selected as numerical cases, and the WSO algorithm achieves the desired main beams width and null depth by optimizing the amplitude-only and the phase-only, respectively. For dimensions optimization of microstrip patch antenna, the WSO algorithm realizes the minimized reflection coefficient (S11) of − 80 dB at 3.1G Hz by optimizing the width and length of rectangle patch antenna. Moreover, compared with the Grasshopper optimization algorithm, the gray wolf optimization algorithm, and the invasive weed optimization algorithm, the WSO algorithm shows higher computational accuracy and faster convergence speed for solving the above two types of optimization problem. Therefore, the WSO algorithm can be widely used to in electromagnetic structure design.
期刊介绍:
he Journal of Computational Electronics brings together research on all aspects of modeling and simulation of modern electronics. This includes optical, electronic, mechanical, and quantum mechanical aspects, as well as research on the underlying mathematical algorithms and computational details. The related areas of energy conversion/storage and of molecular and biological systems, in which the thrust is on the charge transport, electronic, mechanical, and optical properties, are also covered.
In particular, we encourage manuscripts dealing with device simulation; with optical and optoelectronic systems and photonics; with energy storage (e.g. batteries, fuel cells) and harvesting (e.g. photovoltaic), with simulation of circuits, VLSI layout, logic and architecture (based on, for example, CMOS devices, quantum-cellular automata, QBITs, or single-electron transistors); with electromagnetic simulations (such as microwave electronics and components); or with molecular and biological systems. However, in all these cases, the submitted manuscripts should explicitly address the electronic properties of the relevant systems, materials, or devices and/or present novel contributions to the physical models, computational strategies, or numerical algorithms.