{"title":"Generalization of the classical delay-and-sum technique by using nonlinear dirac-delta functions","authors":"H. Nieto-Chaupis","doi":"10.1109/INTERCON.2017.8079636","DOIUrl":null,"url":null,"abstract":"We presented a generalization of the delay-and-sum beamforming based on the Dirac-Delta functions but with nonlinear argument. For this end, a closed-form expression of the beampattern $\\mathcal{B}(r)=\\sum\\nolimits_{k,q}w(k,q,r)x(k,q,r)$ with r = r(θ), was derived. This expression is computationally simulated through an algorithm that includes integer-order Bessel input functions and random noise. The 4M+N model parameters provided by the Dirac-Delta method are extracted by using a Monte-Carlo-like step which selects the best values for B(r) minimizing the Monte-Carlo error for Δθ = 0.5% for the case of beam response of θ0=30 degrees. These results might sustain the fact that beamforming techniques can use Dirac-Delta functions for modeling arrival signal even in those cases where strong nonlinearity is involved.","PeriodicalId":229086,"journal":{"name":"2017 IEEE XXIV International Conference on Electronics, Electrical Engineering and Computing (INTERCON)","volume":"51 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2017-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2017 IEEE XXIV International Conference on Electronics, Electrical Engineering and Computing (INTERCON)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/INTERCON.2017.8079636","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 1
Abstract
We presented a generalization of the delay-and-sum beamforming based on the Dirac-Delta functions but with nonlinear argument. For this end, a closed-form expression of the beampattern $\mathcal{B}(r)=\sum\nolimits_{k,q}w(k,q,r)x(k,q,r)$ with r = r(θ), was derived. This expression is computationally simulated through an algorithm that includes integer-order Bessel input functions and random noise. The 4M+N model parameters provided by the Dirac-Delta method are extracted by using a Monte-Carlo-like step which selects the best values for B(r) minimizing the Monte-Carlo error for Δθ = 0.5% for the case of beam response of θ0=30 degrees. These results might sustain the fact that beamforming techniques can use Dirac-Delta functions for modeling arrival signal even in those cases where strong nonlinearity is involved.