Adaptive Optimization of Non-Uniform Phased Array Speakers Using Particle Swarm Optimization for Enhanced Directivity Control

Phased array speakers are often designed with uniform element spacing, which limits beam steering capability and sidelobe control under practical aperture and hardware constraints. This study presents an optimization-driven modelling framework for parametric array loudspeakers (PALs) that systematically links array layout synthesis with high-fidelity directivity prediction, by combining a frequency-domain convolution model with a finite element method (FEM) pipeline. We formulate array layout synthesis as a constrained optimization problem and employ particle swarm optimization (PSO) to determine non-uniform element positions that suppress sidelobes while preserving mainlobe integrity across steering angles. By integrating linear acoustic field simulation with far-field directivity prediction, the framework serves as a computationally efficient surrogate model suitable for iterative design under non-ideal spacing conditions. Simulation results and laboratory measurements demonstrate that the optimized non-uniform arrays achieve consistently lower sidelobe levels and more concentrated mainlobes than conventional uniform configurations. These results validate the proposed framework as a practical and reproducible solution for steering-capable PAL design when the conventional λ/2 spacing constraint cannot be satisfied and establish a foundation for subsequent robustness and sensitivity analyses.

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Publication Details

Journal
Modelling—International Open Access Journal of Modelling in Engineering Science
Published
2026-01-15
DOI
https://doi.org/10.3390/modelling7010020
Primary Topic
Speech and Audio Processing
Type
article
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article

Adaptive Optimization of Non-Uniform Phased Array Speakers Using Particle Swarm Optimization for Enhanced Directivity Control

Mohammad Nasr Esfahani, Shangming Mei, Y Hu
Modelling—International Open Access Journal of Modelling in Engineering Science
Speech and Audio Processing
article

Adaptive Optimization of Non-Uniform Phased Array Speakers Using Particle Swarm Optimization for Enhanced Directivity Control

Mohammad Nasr Esfahani, Shangming Mei, Y Hu
article en

Abstract

Phased array speakers are often designed with uniform element spacing, which limits beam steering capability and sidelobe control under practical aperture and hardware constraints. This study presents an optimization-driven modelling framework for parametric array loudspeakers (PALs) that systematically links array layout synthesis with high-fidelity directivity prediction, by combining a frequency-domain convolution model with a finite element method (FEM) pipeline. We formulate array layout synthesis as a constrained optimization problem and employ particle swarm optimization (PSO) to determine non-uniform element positions that suppress sidelobes while preserving mainlobe integrity across steering angles. By integrating linear acoustic field simulation with far-field directivity prediction, the framework serves as a computationally efficient surrogate model suitable for iterative design under non-ideal spacing conditions. Simulation results and laboratory measurements demonstrate that the optimized non-uniform arrays achieve consistently lower sidelobe levels and more concentrated mainlobes than conventional uniform configurations. These results validate the proposed framework as a practical and reproducible solution for steering-capable PAL design when the conventional λ/2 spacing constraint cannot be satisfied and establish a foundation for subsequent robustness and sensitivity analyses.

Modelling—International Open Access Journal of Modelling in Engineering ScienceVol. 7(1)
King's College London (GB), University of York (GB)
Openalex Percentile: Top 88%
Speech and Audio Processing
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Adaptive Optimization of Non-Uniform Phased Array Speakers Using Particle Swarm Optimization for Enhanced Directivity Control — Mohammad Nasr Esfahani, Shangming Mei, et al. · Modelling—International Open Access Journal of Modelling in Engineering Science (2026) | TGRS Research Map | TGRS