Bin Kong , Yongjun Li , Pengfei Zhao , Pin Wen , Foxiang Liu
{"title":"Synthesis of maximally sparse conformal circular arc array with a required beam pattern by unitary matrix pencil method","authors":"Bin Kong , Yongjun Li , Pengfei Zhao , Pin Wen , Foxiang Liu","doi":"10.1016/j.dsp.2024.104771","DOIUrl":null,"url":null,"abstract":"<div><p>This paper extends the unitary matrix pencil (UMP) method to synthesize maximally sparse conformal circular-arc array with a required beam pattern. Due to the nonlinearity between the circular-arc array pattern and its element pattern, Fourier transform preprocessing for the required beam pattern is introduced to achieve a mathematical expression, i.e., sum of a series of undamped complex exponentials, which is related to array element positions and their excitations. Then, the UMP method is used to determine the reduced number of elements and their position distributions. Moreover, the complex excitations of array elements are reconstructed by obtaining the least-square solution of an over-determined equation. A set of examples for synthesizing sparse conformal circular-arc arrays with different desired patterns and E-type patch element including the mutual coupling are conducted. Results show that the proposed UMP method can achieve a considerably lower pattern reconstruction error with a reduced number of elements than results in the literature, which demonstrates its effectiveness and robustness.</p></div>","PeriodicalId":51011,"journal":{"name":"Digital Signal Processing","volume":"156 ","pages":"Article 104771"},"PeriodicalIF":2.9000,"publicationDate":"2024-09-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Digital Signal Processing","FirstCategoryId":"5","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S1051200424003968","RegionNum":3,"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
This paper extends the unitary matrix pencil (UMP) method to synthesize maximally sparse conformal circular-arc array with a required beam pattern. Due to the nonlinearity between the circular-arc array pattern and its element pattern, Fourier transform preprocessing for the required beam pattern is introduced to achieve a mathematical expression, i.e., sum of a series of undamped complex exponentials, which is related to array element positions and their excitations. Then, the UMP method is used to determine the reduced number of elements and their position distributions. Moreover, the complex excitations of array elements are reconstructed by obtaining the least-square solution of an over-determined equation. A set of examples for synthesizing sparse conformal circular-arc arrays with different desired patterns and E-type patch element including the mutual coupling are conducted. Results show that the proposed UMP method can achieve a considerably lower pattern reconstruction error with a reduced number of elements than results in the literature, which demonstrates its effectiveness and robustness.
期刊介绍:
Digital Signal Processing: A Review Journal is one of the oldest and most established journals in the field of signal processing yet it aims to be the most innovative. The Journal invites top quality research articles at the frontiers of research in all aspects of signal processing. Our objective is to provide a platform for the publication of ground-breaking research in signal processing with both academic and industrial appeal.
The journal has a special emphasis on statistical signal processing methodology such as Bayesian signal processing, and encourages articles on emerging applications of signal processing such as:
• big data• machine learning• internet of things• information security• systems biology and computational biology,• financial time series analysis,• autonomous vehicles,• quantum computing,• neuromorphic engineering,• human-computer interaction and intelligent user interfaces,• environmental signal processing,• geophysical signal processing including seismic signal processing,• chemioinformatics and bioinformatics,• audio, visual and performance arts,• disaster management and prevention,• renewable energy,