Constant-Beamwidth LCMV Beamformer with Rectangular Arrays

This paper presents a novel approach utilizing uniform rectangular arrays to design a constant-beamwidth (CB) linearly constrained minimum variance (LCMV) beamformer, which also improves white noise gain and directivity. By employing a generalization of the convolutional Kronecker product beamformin...

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Main Authors: Vitor Probst Curtarelli, Israel Cohen
Format: Article
Language:English
Published: MDPI AG 2023-08-01
Series:Algorithms
Subjects:
Online Access:https://www.mdpi.com/1999-4893/16/8/385
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author Vitor Probst Curtarelli
Israel Cohen
author_facet Vitor Probst Curtarelli
Israel Cohen
author_sort Vitor Probst Curtarelli
collection DOAJ
description This paper presents a novel approach utilizing uniform rectangular arrays to design a constant-beamwidth (CB) linearly constrained minimum variance (LCMV) beamformer, which also improves white noise gain and directivity. By employing a generalization of the convolutional Kronecker product beamforming technique, we decompose a physical array into virtual subarrays, each tailored to achieve a specific desired feature, and we subsequently synthesize the original array’s beamformer. Through simulations, we demonstrate that the proposed approach successfully achieves the desired beamforming characteristics while maintaining favorable levels of white noise gain and directivity. A comparative analysis against existing methods from the literature reveals that the proposed method performs better than the existing methods.
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spelling doaj.art-86d097885f2e41a29e2d674682a2fec72023-11-18T23:56:38ZengMDPI AGAlgorithms1999-48932023-08-0116838510.3390/a16080385Constant-Beamwidth LCMV Beamformer with Rectangular ArraysVitor Probst Curtarelli0Israel Cohen1Graduate Program in Electrical Engineering, Universidade Federal de Santa Catarina, Florianópolis CEP 88040-900, SC, BrazilAndrew and Erna Viterbi Faculty of Electrical and Computer Engineering, Technion–Israel Institute of Technology, Technion City, Haifa 3200003, IsraelThis paper presents a novel approach utilizing uniform rectangular arrays to design a constant-beamwidth (CB) linearly constrained minimum variance (LCMV) beamformer, which also improves white noise gain and directivity. By employing a generalization of the convolutional Kronecker product beamforming technique, we decompose a physical array into virtual subarrays, each tailored to achieve a specific desired feature, and we subsequently synthesize the original array’s beamformer. Through simulations, we demonstrate that the proposed approach successfully achieves the desired beamforming characteristics while maintaining favorable levels of white noise gain and directivity. A comparative analysis against existing methods from the literature reveals that the proposed method performs better than the existing methods.https://www.mdpi.com/1999-4893/16/8/385LCMV beamformerconstant-beamwidth beamformingKronecker product beamformerarray signal processingrectangular sensor arrays
spellingShingle Vitor Probst Curtarelli
Israel Cohen
Constant-Beamwidth LCMV Beamformer with Rectangular Arrays
Algorithms
LCMV beamformer
constant-beamwidth beamforming
Kronecker product beamformer
array signal processing
rectangular sensor arrays
title Constant-Beamwidth LCMV Beamformer with Rectangular Arrays
title_full Constant-Beamwidth LCMV Beamformer with Rectangular Arrays
title_fullStr Constant-Beamwidth LCMV Beamformer with Rectangular Arrays
title_full_unstemmed Constant-Beamwidth LCMV Beamformer with Rectangular Arrays
title_short Constant-Beamwidth LCMV Beamformer with Rectangular Arrays
title_sort constant beamwidth lcmv beamformer with rectangular arrays
topic LCMV beamformer
constant-beamwidth beamforming
Kronecker product beamformer
array signal processing
rectangular sensor arrays
url https://www.mdpi.com/1999-4893/16/8/385
work_keys_str_mv AT vitorprobstcurtarelli constantbeamwidthlcmvbeamformerwithrectangulararrays
AT israelcohen constantbeamwidthlcmvbeamformerwithrectangulararrays