A Mutual Coupling-Resistant Technique for Uncalibrated Narrowband Beamforming

Abstract Mutual coupling between antenna array elements causes radiation pattern distortion and performance degradation, leading to undesired signal suppression and a significant reduction in the signal-to-interference-plus-noise ratio (SINR). Adaptive array signal processing typically mitigates these distortions. However, it depends on a previous calibration of the array. Such calibration requires previous knowledge of the in-situ or realistic array manifold vector (AMV), whose estimation can be achieved through various techniques extensively explored by the antenna community over the past decades. These techniques often rely on pre-measurements or electromagnetic simulations of the array and are typically design-specific. In practical scenarios where the realistic AMV is unknown, adaptive beamforming algorithms tend to converge to distorted solutions, which deviate substantially from the performance of a calibrated system, resulting in significant SINR loss. This work addresses this challenge by proposing an algorithm that mitigates signal distortion effects without requiring prior knowledge of the realistic AMV. Also, the algorithm does not rely on a specific structure for the mutual coupling matrix (MCM), such as Toeplitz. The main idea is to combine a robust design with a technique that enforces sidelobe suppression while keeping the distortionless constraint, using additional linear constraints to the adaptive filter. As case studies, the MCMs of three uniform linear array antennas are estimated using full-wave 3D electromagnetic simulations. The results demonstrate the effectiveness of the proposed approach in significantly improving beamforming performance and SINR in scenarios where the realistic array manifold vector is unknown.

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Publication Details

Journal
Circuits Systems and Signal Processing
Published
2026-06-18
DOI
https://doi.org/10.1007/s00034-026-03614-2
Primary Topic
Direction-of-Arrival Estimation Techniques
Type
article
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article

A Mutual Coupling-Resistant Technique for Uncalibrated Narrowband Beamforming

Vitor T. Klingelfus, Claudio A. B. Saunders Filho, José A. Apolinário, António L. L. Ramos
Circuits Systems and Signal Processing
Direction-of-Arrival Estimation Techniques
article

A Mutual Coupling-Resistant Technique for Uncalibrated Narrowband Beamforming

Vitor T. Klingelfus, Claudio A. B. Saunders Filho, José A. Apolinário, António L. L. Ramos
article en

Abstract

Abstract Mutual coupling between antenna array elements causes radiation pattern distortion and performance degradation, leading to undesired signal suppression and a significant reduction in the signal-to-interference-plus-noise ratio (SINR). Adaptive array signal processing typically mitigates these distortions. However, it depends on a previous calibration of the array. Such calibration requires previous knowledge of the in-situ or realistic array manifold vector (AMV), whose estimation can be achieved through various techniques extensively explored by the antenna community over the past decades. These techniques often rely on pre-measurements or electromagnetic simulations of the array and are typically design-specific. In practical scenarios where the realistic AMV is unknown, adaptive beamforming algorithms tend to converge to distorted solutions, which deviate substantially from the performance of a calibrated system, resulting in significant SINR loss. This work addresses this challenge by proposing an algorithm that mitigates signal distortion effects without requiring prior knowledge of the realistic AMV. Also, the algorithm does not rely on a specific structure for the mutual coupling matrix (MCM), such as Toeplitz. The main idea is to combine a robust design with a technique that enforces sidelobe suppression while keeping the distortionless constraint, using additional linear constraints to the adaptive filter. As case studies, the MCMs of three uniform linear array antennas are estimated using full-wave 3D electromagnetic simulations. The results demonstrate the effectiveness of the proposed approach in significantly improving beamforming performance and SINR in scenarios where the realistic array manifold vector is unknown.

Circuits Systems and Signal Processing
University of South-Eastern Norway (NO), Military Institute of Engineering (BR)
Openalex Percentile: Top 4%
Direction-of-Arrival Estimation Techniques
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