Constant-Beamwidth LCMV Beamformer with Rectangular Arrays

Vitor Probst Curtarelli, Israel Cohen

Research output: Contribution to journalArticlepeer-review

Abstract

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.

Original languageEnglish
Article number385
JournalAlgorithms
Volume16
Issue number8
DOIs
StatePublished - Aug 2023

Keywords

  • Kronecker product beamformer
  • LCMV beamformer
  • array signal processing
  • constant-beamwidth beamforming
  • rectangular sensor arrays

All Science Journal Classification (ASJC) codes

  • Computational Mathematics
  • Theoretical Computer Science
  • Numerical Analysis
  • Computational Theory and Mathematics

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