{"title":"Robust beampattern control for steerable frequency-invariant beamforming in the presence of sensor imperfections","authors":"Congwei Feng, Huawei Chen","doi":"10.1016/j.sigpro.2025.109893","DOIUrl":null,"url":null,"abstract":"<div><div>Wideband beamformers are known sensitive to sensor imperfections, especially for small-sized sensor arrays. Mean performance optimization (MPO) is a commonly used criterion for the design of robust wideband beamformers in the presence of sensor imperfections, which aims to synthesize the mean beampattern. However, the existing designs for robust wideband beamformers cannot guarantee precise control of the mean beampattern. In this paper, we propose a MPO-criterion-based robust design approach for steerable wideband beamformers (SWBs) using a weighted spatial response variation (SRV) measure. By exploiting the increased degrees of freedom provided by the weighted-SRV, the proposed robust SWB design can achieve a frequency-invariant mean beampattern with both mainlobe inconsistency and sidelobe level being able to be precisely controlled. We develop a theory and the corresponding algorithm to find the solution for the weighting function of the weighted-SRV-based cost function to achieve precise mean beampattern control. Some insights into the effect of sensor imperfections on the achievable frequency invariance are also revealed. The effectiveness of the proposed design is verified by the simulation results.</div></div>","PeriodicalId":49523,"journal":{"name":"Signal Processing","volume":"231 ","pages":"Article 109893"},"PeriodicalIF":3.4000,"publicationDate":"2025-01-13","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/S0165168425000088","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
Wideband beamformers are known sensitive to sensor imperfections, especially for small-sized sensor arrays. Mean performance optimization (MPO) is a commonly used criterion for the design of robust wideband beamformers in the presence of sensor imperfections, which aims to synthesize the mean beampattern. However, the existing designs for robust wideband beamformers cannot guarantee precise control of the mean beampattern. In this paper, we propose a MPO-criterion-based robust design approach for steerable wideband beamformers (SWBs) using a weighted spatial response variation (SRV) measure. By exploiting the increased degrees of freedom provided by the weighted-SRV, the proposed robust SWB design can achieve a frequency-invariant mean beampattern with both mainlobe inconsistency and sidelobe level being able to be precisely controlled. We develop a theory and the corresponding algorithm to find the solution for the weighting function of the weighted-SRV-based cost function to achieve precise mean beampattern control. Some insights into the effect of sensor imperfections on the achievable frequency invariance are also revealed. The effectiveness of the proposed design is verified by the simulation results.
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.