Robust beamforming in circular arrays using phase‐mode transformation

Askari, Mohsen; Karimi, Mahmood; Atbaee, Zakiyeh

doi:10.1049/iet-spr.2012.0236

Cited by 13 publications

(3 citation statements)

References 28 publications

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“…The circular sensor arrays has a 3600 isotropic coverage of the azimuth angle, and its noise covariance matrix is a circulant matrix. If the matrix is MxM, to express it, there need merely one lxM vector [6], [7].…”

Section: Introductionmentioning

confidence: 99%

Robust beamforming based on wiener filter for circular sensor arrays

Lin

Yan

et al. 2014

2014 12th International Conference on Signal Processing (ICSP)

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A robust wiener-filer beamformer on the circular sensor arrays (CWFB), which is an efficient and robust method, is proposed in this article. The weighted vector will be solved through an unique way, which is derived from the fact that the noise covariance matrix of circular sensor arrays is a circulant matrix. Using the individual feature, the solution is exchanged to solve the one-dimensional wiener filter. It can be processed effi ciently in frequency domain. However, the circular characteristics of the noise covariance matrix can lead to extreme sensitivity to random errors. In this article, by adding regularization coefficient, the robustness of CWFB is to be improved. Simulation results demonstrate the more robust and efficient superiority of the proposed CWFB than the conventional beamformer.

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Section: Introductionmentioning

confidence: 99%

Robust beamforming based on wiener filter for circular sensor arrays

Lin

Yan

et al. 2014

2014 12th International Conference on Signal Processing (ICSP)

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“…ULA partially and in some cases completely fails to for beam near the array end fires. To have full coverage (360o), uniform circular arrays (UCAs) could be considered [15]. They provide 2-D coverage which includes both elevation and azimuth directions.…”

Section: Introductionmentioning

confidence: 99%

Improved Adaptive Beamforming for Smart Antennas

Dakulagi

Yeap

et al. 2021

Preprint

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In this paper, we propose a new antenna array configuration for smart antenna beamforming. In this new method, we displace two antenna elements of a uniform linear array (ULA) and place them at the top and bottom of the array axis. We investigate the efficacy of this method by deploying the variable step size least mean square algorithm (VSSLMS). The proposed method is compared with popular LMS and normalized LMS algorithms. Computer simulations show that the proposed method has enhanced convergence rate and high data transmission compared to the LMS and the NLMS methods. Also, the new method has the same performance for middle angles, near boresight and array endfires which is not possible for the LMS and the NLMS method using a ULA.

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“…The work in [3–6] has shown these phase‐mode transformations can be extended to UCAs of directional elements with benefits to array performance. This technique relies on approximations, however, and degraded performance results in the usual application, direction‐of‐arrival estimation [7–9].…”

Section: Introductionmentioning

confidence: 99%

Uniform circular array pattern synthesis using second‐order cone programming

Dorsey

Coleman

Pickles

2015

IET microw. antennas propagation

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Here, the authors formulate second-order cone programs (SOCPs) for synthesising complex weights for far-field directional (single-point mainbeam) patterns for narrowband arrays. These formulations, while constructed here with the uniform circular array (UCA) in mind, are actually quite general in that they control the arbitrary-pol sidelobe level (SLL) and co-pol signal-to-noise ratio loss relative to ideal by minimising either while upper bounding the other. The SLL can be addressed in either an L-infinity sense or an L1 sense, and elements are assumed characterised by individual embedded complex patterns, modelled or measured, and so need not be identical. Conformal arrays are the obvious application, but we leave that for others and here instead apply the SOCPs to UCAs of directional elements. Design examples assume an antipodal Vivaldi element design with an embedded element pattern obtained through simulation using appropriate unitcell boundary conditions. Rotation and translation of that simulated pattern provides embedded element patterns for all elements of the circular array.

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Robust beamforming in circular arrays using phase‐mode transformation

Cited by 13 publications

References 28 publications

Robust beamforming based on wiener filter for circular sensor arrays

Robust beamforming based on wiener filter for circular sensor arrays

Improved Adaptive Beamforming for Smart Antennas

Uniform circular array pattern synthesis using second‐order cone programming

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