A multi-objective optimization approach for beam pattern synthesis of UAV virtual rectangular antenna array

IF 1.6 4区工程技术 Q3 ENGINEERING, ELECTRICAL & ELECTRONIC

International Journal of Numerical Modelling-Electronic Networks Devices and Fields Pub Date : 2024-03-08 DOI:10.1002/jnm.3222

Fang Mei, Xinrong Guo, Hui Kang, Geng Sun, Tingting Zheng, Jianbo Wen

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引用次数: 0

Abstract

Virtual antenna array (VAA) formed by unmanned aerial vehicle (UAV) antenna units using collaborative beamforming (CB) technology plays an important role in the air communication system, and can be used in radar, military, disaster rescue and other places. However, there are still some issues with the beam pattern formed by this method, such as high sidelobe level (SLL), high cost and low efficiency. In this article, each UAV carries an omnidirectional antenna unit, and a large number of UAVs form a UAV virtual rectangular antenna array (UVRAA) to communicate with the ground base station (BS). We formulate an overhead minimization and efficient communication multi-objective optimization problem (OMECMOP) which jointly optimize the excitation current weights of the UVRAA and reduce the number of UAVs in operation to improve the beam pattern, enhance the communication efficiency and decrease the overhead of UVRAA. In addition, we also propose an improved multi-objective multi-verse optimization algorithm based on the inverse $S$ decline curve type (ISDT-MOMVO) which introduces a strategy optimization initialization solution with quasi-opposition based learning (QBL) and a hybrid solution updating operators to solve the OMECMOP. The simulation results show that compared with other traditional swarm intelligence (SI) optimization algorithms the ISDT-MOMVO algorithm produces better beam pattern and the thinning rate can reach 50%.

查看原文本刊更多论文

无人机虚拟矩形天线阵列波束模式合成的多目标优化方法

无人机天线单元利用协同波束成形（CB）技术形成的虚拟天线阵（VAA）在空中通信系统中发挥着重要作用，可用于雷达、军事、灾难救援等领域。然而，这种方法形成的波束模式仍存在一些问题，如侧叶水平（SLL）高、成本高、效率低等。在本文中，每架无人机携带一个全向天线单元，大量无人机组成无人机虚拟矩形天线阵（UVRAA）与地面基站（BS）通信。我们提出了一个开销最小化和高效通信多目标优化问题（OMECMOP），通过联合优化 UVRAA 的激励电流权值和减少运行中的无人机数量来改善波束模式、提高通信效率并降低 UVRAA 的开销。此外，我们还提出了一种基于反 S$ S$ 下降曲线类型的改进型多目标多逆向优化算法（ISDT-MOMVO），该算法引入了基于准位置学习（QBL）的策略优化初始化解和混合解更新算子来求解 OMECMOP。仿真结果表明，与其他传统的群智能（SI）优化算法相比，ISDT-MOMVO 算法能产生更好的光束模式，减薄率可达 50%。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

International Journal of Numerical Modelling-Electronic Networks Devices and Fields 工程技术-工程：电子与电气

CiteScore

4.60

自引率

6.20%

发文量

101

审稿时长

>12 weeks

期刊介绍： Prediction through modelling forms the basis of engineering design. The computational power at the fingertips of the professional engineer is increasing enormously and techniques for computer simulation are changing rapidly. Engineers need models which relate to their design area and which are adaptable to new design concepts. They also need efficient and friendly ways of presenting, viewing and transmitting the data associated with their models. The International Journal of Numerical Modelling: Electronic Networks, Devices and Fields provides a communication vehicle for numerical modelling methods and data preparation methods associated with electrical and electronic circuits and fields. It concentrates on numerical modelling rather than abstract numerical mathematics. Contributions on numerical modelling will cover the entire subject of electrical and electronic engineering. They will range from electrical distribution networks to integrated circuits on VLSI design, and from static electric and magnetic fields through microwaves to optical design. They will also include the use of electrical networks as a modelling medium.