Sparse Array Quiescent Beamformer Design Combining Adaptive and Deterministic Constraints

In this paper, we examine sparse array quiescent beamforming for multiple sources in interference-free environment. To maximize the output signal-to-noise ratio (SNR), the beamformer design comprises two intertwined stages, the determination of beamforming weights and the reconfiguration of array st...

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Bibliographic Details
Published in:IEEE transactions on antennas and propagation 2017-11, Vol.65 (11), p.5808-5818
Main Authors: Xiangrong Wang, Amin, Moeness, Xianghua Wang, Xianbin Cao
Format: Article
Language:English
Subjects:
Adaptive arrays
Array signal processing
Correlation
Frame approximation
Interference
quadratic fractional
quiescent beamforming
sequential convex programming (SCP)
Signal to noise ratio
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Summary:In this paper, we examine sparse array quiescent beamforming for multiple sources in interference-free environment. To maximize the output signal-to-noise ratio (SNR), the beamformer design comprises two intertwined stages, the determination of beamforming weights and the reconfiguration of array structure. The SNR maximization may produce high sidelobe levels, making the receiver vulnerable to interferences. We consider the problem of achieving maximum SNR beamforming subject to specified quiescent pattern constraints and, as such, combine both adaptive and deterministic approaches for sparse array configurations. We employ two convex relaxation methods and an iterative linear fractional programming algorithm to solve the nonconvex antenna selection problem for sparse array beamformers. Simulation examples demonstrate that the array configuration plays a vital role in determining the beamforming performance in interference-free scenarios.
ISSN:0018-926X
1558-2221
DOI:10.1109/TAP.2017.2751672