Method for reconstructing the directional pattern of opportunistic array radar with dynamic elements

IF 3.4 2区 工程技术 Q2 ENGINEERING, ELECTRICAL & ELECTRONIC Signal Processing Pub Date : 2025-01-18 DOI:10.1016/j.sigpro.2025.109890
Weijun Long, Qinghua Zhao, Chuan Du
{"title":"Method for reconstructing the directional pattern of opportunistic array radar with dynamic elements","authors":"Weijun Long,&nbsp;Qinghua Zhao,&nbsp;Chuan Du","doi":"10.1016/j.sigpro.2025.109890","DOIUrl":null,"url":null,"abstract":"<div><div>In order to solve the pattern synthesis problem of opportunity array radar, a dynamic array element pattern synthesis mathematical model and opportunity unit reconstruction scheme based on correlation chance programming under uncertain scenarios are established. The model is optimized to maximize the reliability of task requirements,and is solved by fuzzy simulation and mathematical analysis under given relevant constraints. In addition, a parallel differential evolution algorithm with secondary mutation(SMPDE) is proposed to improve the adaptability of opportunity array radar to different environments and tasks. By constructing Hanke matrices using different ideal radar arrays, feasible and base regions for initial population evolution can be obtained. On this basis, elements are added or deleted according to the requirements and new elements are flexibly arranged through differential evolution to obtain the best performance. In the process of iteration, the time point of secondary mutation is determined in real time according to the evolution curve and the potential inferior evolution is terminated in time. The simulation and analysis show that the model can achieve the maximum reliability of the task target in the current environment when the pattern reconstruction problem is involved, especially the opportunity array radar with multiple dynamic elements. Moreover, the model can flexibly reconstruct and optimize the pattern according to different requirements under different conditions to further enhance the overall robustness of the system.</div></div>","PeriodicalId":49523,"journal":{"name":"Signal Processing","volume":"231 ","pages":"Article 109890"},"PeriodicalIF":3.4000,"publicationDate":"2025-01-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Signal Processing","FirstCategoryId":"5","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S0165168425000052","RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"ENGINEERING, ELECTRICAL & ELECTRONIC","Score":null,"Total":0}
引用次数: 0

Abstract

In order to solve the pattern synthesis problem of opportunity array radar, a dynamic array element pattern synthesis mathematical model and opportunity unit reconstruction scheme based on correlation chance programming under uncertain scenarios are established. The model is optimized to maximize the reliability of task requirements,and is solved by fuzzy simulation and mathematical analysis under given relevant constraints. In addition, a parallel differential evolution algorithm with secondary mutation(SMPDE) is proposed to improve the adaptability of opportunity array radar to different environments and tasks. By constructing Hanke matrices using different ideal radar arrays, feasible and base regions for initial population evolution can be obtained. On this basis, elements are added or deleted according to the requirements and new elements are flexibly arranged through differential evolution to obtain the best performance. In the process of iteration, the time point of secondary mutation is determined in real time according to the evolution curve and the potential inferior evolution is terminated in time. The simulation and analysis show that the model can achieve the maximum reliability of the task target in the current environment when the pattern reconstruction problem is involved, especially the opportunity array radar with multiple dynamic elements. Moreover, the model can flexibly reconstruct and optimize the pattern according to different requirements under different conditions to further enhance the overall robustness of the system.
查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
求助全文
约1分钟内获得全文 去求助
来源期刊
Signal Processing
Signal Processing 工程技术-工程:电子与电气
CiteScore
9.20
自引率
9.10%
发文量
309
审稿时长
41 days
期刊介绍: Signal Processing incorporates all aspects of the theory and practice of signal processing. It features original research work, tutorial and review articles, and accounts of practical developments. It is intended for a rapid dissemination of knowledge and experience to engineers and scientists working in the research, development or practical application of signal processing. Subject areas covered by the journal include: Signal Theory; Stochastic Processes; Detection and Estimation; Spectral Analysis; Filtering; Signal Processing Systems; Software Developments; Image Processing; Pattern Recognition; Optical Signal Processing; Digital Signal Processing; Multi-dimensional Signal Processing; Communication Signal Processing; Biomedical Signal Processing; Geophysical and Astrophysical Signal Processing; Earth Resources Signal Processing; Acoustic and Vibration Signal Processing; Data Processing; Remote Sensing; Signal Processing Technology; Radar Signal Processing; Sonar Signal Processing; Industrial Applications; New Applications.
期刊最新文献
Frequency offset deception velocity-based method for discriminating between physical targets and active false targets Low interactive direct position determination of radio emitters with hybrid measurements High-accuracy image steganography with invertible neural network and generative adversarial network TOA estimation via cross-correlation-based atomic norm minimization A language-guided cross-modal semantic fusion retrieval method
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 联系我们:info@booksci.cn
Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。
Copyright © 2023 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1