Adaptive Sum and Difference Beamforming with a Common Excitation Vector

In contrast to the static synthesis of sum and difference beams, this paper proposes an adaptive sum and difference beamforming method, which suppresses interference adaptively while satisfying radiation characteristics of dual-beams, including precise control of the peak sidelobe level (PSL). Moreover, unlike traditional techniques that require two separate feeding networks for dual-beam synthesis, the proposed method constructs dual-beams with a common excitation vector, thereby significantly reducing hardware complexity and system cost. Furthermore, the linearly constrained minimum variance (LCMV) criterion is employed to minimize the output power while maintaining linear constraints on the beamformer weights. Since the constructed model is convex, it is solved by CVX toolbox.

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Publication Details

Published
2025-05-23
DOI
https://doi.org/10.1109/ecie65947.2025.11086960
Primary Topic
Antenna Design and Optimization
Type
article
Field-Weighted Citation Impact
0.00

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article

Adaptive Sum and Difference Beamforming with a Common Excitation Vector

Xuhui Fan, Yuyi Wang, Yanmin Xu, Xuhong Li
Antenna Design and Optimization
article

Adaptive Sum and Difference Beamforming with a Common Excitation Vector

Xuhui Fan, Yuyi Wang, Yanmin Xu, Xuhong Li
article en

Abstract

In contrast to the static synthesis of sum and difference beams, this paper proposes an adaptive sum and difference beamforming method, which suppresses interference adaptively while satisfying radiation characteristics of dual-beams, including precise control of the peak sidelobe level (PSL). Moreover, unlike traditional techniques that require two separate feeding networks for dual-beam synthesis, the proposed method constructs dual-beams with a common excitation vector, thereby significantly reducing hardware complexity and system cost. Furthermore, the linearly constrained minimum variance (LCMV) criterion is employed to minimize the output power while maintaining linear constraints on the beamformer weights. Since the constructed model is convex, it is solved by CVX toolbox.

Xi'an University of Science and Technology (CN)
National Natural Science Foundation of China, Scientific Research Plan Projects of Shaanxi Education Department
Affordable and clean energy
Openalex Percentile: Top 75%
Antenna Design and Optimization
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