International Journal of Research in Circuits, Devices and Systems
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P-ISSN: 2708-4531, E-ISSN: 2708-454X

2025, Vol. 6, Issue 1, Part A


Adaptive beamforming using enhanced steering vector estimation with subspace-based interference suppression and validation on real-world and simulated datasets


Author(s): Tafadzwa Nyamandi, Rutendo Dube and Mandla Chikomo

Abstract: Beamforming is a fundamental technique in signal processing, widely applied in wireless communication, radar, and audio systems to enhance signal fidelity and suppress interference. However, traditional beamforming methods, such as MVDR and Capon, often exhibit performance degradation under non-ideal conditions, including high interference, multipath propagation, and sensor calibration errors. This study aims to develop and validate a robust adaptive beamforming algorithm that integrates enhanced steering vector estimation with subspace-based interference suppression. The objectives include achieving superior interference mitigation, improved signal-to-interference-plus-noise ratio (SINR), narrower beamwidth, and deeper null depth across both simulated and real-world datasets.The proposed algorithm utilizes an optimized iterative approach for steering vector estimation and employs subspace decomposition for interference suppression. Validation was conducted on datasets encompassing diverse interference scenarios and varying levels of sensor calibration errors. The algorithm’s performance was compared against traditional MVDR and Capon beamforming methods using metrics such as SINR, beamwidth, and null depth. Statistical tools, including paired t-tests and ANOVA, were employed to validate the results.The results demonstrate that the proposed method achieves a mean SINR improvement of 15% over benchmarks, with a beamwidth reduction of up to 1.2∘ and null depth improvement of over 5 dB. Additionally, the method exhibited robustness to sensor calibration errors up to 10∘, outperforming traditional techniques. Computational efficiency, comparable to MVDR, ensures its viability for real-time applications.In conclusion, the proposed algorithm addresses critical limitations in conventional beamforming, offering enhanced performance and reliability. Practical recommendations include optimizing computational efficiency through hardware acceleration and extending applicability to dynamic environments. These findings contribute significantly to advancing adaptive beamforming technologies in both theoretical and practical domains.

DOI: 10.22271/27084531.2025.v6.i1a.80

Pages: 12-16 | Views: 69 | Downloads: 20

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International Journal of Research in Circuits, Devices and Systems
How to cite this article:
Tafadzwa Nyamandi, Rutendo Dube, Mandla Chikomo. Adaptive beamforming using enhanced steering vector estimation with subspace-based interference suppression and validation on real-world and simulated datasets. Int J Res Circuits Devices Syst 2025;6(1):12-16. DOI: 10.22271/27084531.2025.v6.i1a.80
International Journal of Research in Circuits, Devices and Systems
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