多输入多输出雷达波束扫描的联合波形设计和天线选择

IF 4.6 2区 工程技术 Q1 ENGINEERING, ELECTRICAL & ELECTRONIC
Wen Fan;Xuhui Fan;Junli Liang;Hing Cheung So
{"title":"多输入多输出雷达波束扫描的联合波形设计和天线选择","authors":"Wen Fan;Xuhui Fan;Junli Liang;Hing Cheung So","doi":"10.1109/TSP.2024.3468724","DOIUrl":null,"url":null,"abstract":"A key task of antenna array is to radiate multiple patterns for beam scanning. While antenna selection can offer additional degrees of freedom in beampattern synthesis. This paper presents a method for antenna selection and beam scanning in a colocated wideband multiple-input multiple-output radar system. Our approach integrates the peak-to-average power ratio (PAPR), energy, and binary constraints, where the last one is employed for antenna selection, in the design. The aim is to match a set of given beampattern masks by jointly determining the antenna positions and a set of probing waveforms, allowing for effective beam scanning. The resultant problem is complex due to the involvement of large-scale, nonconvex, and nonsmooth optimization caused by the PAPR and nonconvex binary constraints, as well as max and modulus operations in the objective function. To address the issues, we start by converting the min-max optimization problem into an iteratively reweighted least squares (IRLS) problem using the Lawson algorithm. Then, we replace the nonsmooth nonconvex objective function with a convex majorization function. Finally, we apply the alternating direction method of multipliers to solve the majorized IRLS problem. Our convergence analysis shows that the proposed algorithms ensure a stationary solution. Additionally, we provide numerical examples to demonstrate the effectiveness of the algorithm.","PeriodicalId":13330,"journal":{"name":"IEEE Transactions on Signal Processing","volume":"72 ","pages":"4479-4492"},"PeriodicalIF":4.6000,"publicationDate":"2024-09-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Joint Waveform Design and Antenna Selection for MIMO Radar Beam Scanning\",\"authors\":\"Wen Fan;Xuhui Fan;Junli Liang;Hing Cheung So\",\"doi\":\"10.1109/TSP.2024.3468724\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"A key task of antenna array is to radiate multiple patterns for beam scanning. While antenna selection can offer additional degrees of freedom in beampattern synthesis. This paper presents a method for antenna selection and beam scanning in a colocated wideband multiple-input multiple-output radar system. Our approach integrates the peak-to-average power ratio (PAPR), energy, and binary constraints, where the last one is employed for antenna selection, in the design. The aim is to match a set of given beampattern masks by jointly determining the antenna positions and a set of probing waveforms, allowing for effective beam scanning. The resultant problem is complex due to the involvement of large-scale, nonconvex, and nonsmooth optimization caused by the PAPR and nonconvex binary constraints, as well as max and modulus operations in the objective function. To address the issues, we start by converting the min-max optimization problem into an iteratively reweighted least squares (IRLS) problem using the Lawson algorithm. Then, we replace the nonsmooth nonconvex objective function with a convex majorization function. Finally, we apply the alternating direction method of multipliers to solve the majorized IRLS problem. Our convergence analysis shows that the proposed algorithms ensure a stationary solution. Additionally, we provide numerical examples to demonstrate the effectiveness of the algorithm.\",\"PeriodicalId\":13330,\"journal\":{\"name\":\"IEEE Transactions on Signal Processing\",\"volume\":\"72 \",\"pages\":\"4479-4492\"},\"PeriodicalIF\":4.6000,\"publicationDate\":\"2024-09-26\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"IEEE Transactions on Signal Processing\",\"FirstCategoryId\":\"5\",\"ListUrlMain\":\"https://ieeexplore.ieee.org/document/10695033/\",\"RegionNum\":2,\"RegionCategory\":\"工程技术\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"ENGINEERING, ELECTRICAL & ELECTRONIC\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"IEEE Transactions on Signal Processing","FirstCategoryId":"5","ListUrlMain":"https://ieeexplore.ieee.org/document/10695033/","RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"ENGINEERING, ELECTRICAL & ELECTRONIC","Score":null,"Total":0}
引用次数: 0

摘要

天线阵列的一项关键任务是为波束扫描辐射出多种图案。而天线选择可以为波束花样合成提供额外的自由度。本文提出了一种在同位宽带多输入多输出雷达系统中进行天线选择和波束扫描的方法。我们的方法在设计中整合了峰均功率比 (PAPR)、能量和二进制约束,其中二进制约束用于天线选择。目的是通过联合确定天线位置和一组探测波形来匹配一组给定的贝型掩模,从而实现有效的波束扫描。由于目标函数中的 PAPR 和非凸二元约束以及最大值和模数运算导致大规模、非凸和非平滑优化,因此问题十分复杂。为了解决这些问题,我们首先使用 Lawson 算法将最小-最大优化问题转换为迭代加权最小二乘法(IRLS)问题。然后,我们用凸大化函数取代非光滑的非凸目标函数。最后,我们运用乘数交替方向法来解决大化 IRLS 问题。我们的收敛分析表明,所提出的算法能确保获得静态解。此外,我们还提供了数值示例来证明算法的有效性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Joint Waveform Design and Antenna Selection for MIMO Radar Beam Scanning
A key task of antenna array is to radiate multiple patterns for beam scanning. While antenna selection can offer additional degrees of freedom in beampattern synthesis. This paper presents a method for antenna selection and beam scanning in a colocated wideband multiple-input multiple-output radar system. Our approach integrates the peak-to-average power ratio (PAPR), energy, and binary constraints, where the last one is employed for antenna selection, in the design. The aim is to match a set of given beampattern masks by jointly determining the antenna positions and a set of probing waveforms, allowing for effective beam scanning. The resultant problem is complex due to the involvement of large-scale, nonconvex, and nonsmooth optimization caused by the PAPR and nonconvex binary constraints, as well as max and modulus operations in the objective function. To address the issues, we start by converting the min-max optimization problem into an iteratively reweighted least squares (IRLS) problem using the Lawson algorithm. Then, we replace the nonsmooth nonconvex objective function with a convex majorization function. Finally, we apply the alternating direction method of multipliers to solve the majorized IRLS problem. Our convergence analysis shows that the proposed algorithms ensure a stationary solution. Additionally, we provide numerical examples to demonstrate the effectiveness of the algorithm.
求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
IEEE Transactions on Signal Processing
IEEE Transactions on Signal Processing 工程技术-工程:电子与电气
CiteScore
11.20
自引率
9.30%
发文量
310
审稿时长
3.0 months
期刊介绍: The IEEE Transactions on Signal Processing covers novel theory, algorithms, performance analyses and applications of techniques for the processing, understanding, learning, retrieval, mining, and extraction of information from signals. The term “signal” includes, among others, audio, video, speech, image, communication, geophysical, sonar, radar, medical and musical signals. Examples of topics of interest include, but are not limited to, information processing and the theory and application of filtering, coding, transmitting, estimating, detecting, analyzing, recognizing, synthesizing, recording, and reproducing signals.
×
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
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
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 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信