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Generalization of the classical delay-and-sum technique by using nonlinear dirac-delta functions

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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 si...

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Detalles Bibliográficos
Autor: Nieto Chaupis, Huber
Formato: objeto de conferencia
Fecha de Publicación:2017
Institución:Universidad de Ciencias y Humanidades
Repositorio:UCH-Institucional
Lenguaje:inglés
OAI Identifier:oai:repositorio.uch.edu.pe:uch/330
Enlace del recurso:http://repositorio.uch.edu.pe/handle/uch/330
http://dx.doi.org/10.1109/INTERCON.2017.8079636
https://ieeexplore.ieee.org/abstract/document/8079636
Nivel de acceso:acceso embargado
Materia:Beamforming
Monte Carlo methods
Beamforming technique
Closed-form expression
Delay and sum beamforming
Delay and sums
Dirac delta function
Input functions
Model parameters
Strong nonlinearity
Delta functions
Descripción
Sumario: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.
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