Near-Field Pattern Synthesis for Sparse Focusing Antenna Arrays Based on Bayesian Compressive Sensing and Convex Optimization

An effective method based on Bayesian compressive sensing (BCS) and convex optimization for near-field sparse array synthesis is presented in this paper. An algorithm to generate reference-shaped beams in the near-field region with controllable sidelobe levels is first proposed. Then, the multitask...

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Published inIEEE transactions on antennas and propagation Vol. 66; no. 10; pp. 5249 - 5257
Main Authors Huang, Zi Xuan, Cheng, Yu Jian
Format Journal Article
LanguageEnglish
Published New York IEEE 01.10.2018
The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subjects
Antenna arrays
Antennas
Bayes methods
Bayesian analysis
Bayesian compressive sensing (BCS)
Compressed sensing
Computational geometry
Computer simulation
Convex analysis
convex optimization
Convexity
Couplings
Excitation
Finite element analysis
Focusing
Layouts
Microwave antenna arrays
near-field beam shaping
Optimization
Sidelobes
sparse array
Synthesis
Online AccessGet full text
ISSN0018-926X
1558-2221
DOI10.1109/TAP.2018.2860044

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Abstract An effective method based on Bayesian compressive sensing (BCS) and convex optimization for near-field sparse array synthesis is presented in this paper. An algorithm to generate reference-shaped beams in the near-field region with controllable sidelobe levels is first proposed. Then, the multitask BC is modified and generalized to synthesize a near-field sparse array radiating a desired near-field pattern with the co-polarization component. After that, a postprocessing of the final array excitation is employed to put constraints on the minimum element spacing to make the sparse layout practicable. The degradation of the near-field pattern is mitigated through reestimating the array excitation by a convex optimization. Three numerical examples show the effectiveness of the proposed method with more than 50% of elements saved compared to the uniformly distributed layout. The comparison to the result obtained by a full-wave simulator FEKO is also presented to demonstrate the validity of this method considering strong antenna mutual couplings.
AbstractList An effective method based on Bayesian compressive sensing (BCS) and convex optimization for near-field sparse array synthesis is presented in this paper. An algorithm to generate reference-shaped beams in the near-field region with controllable sidelobe levels is first proposed. Then, the multitask BC is modified and generalized to synthesize a near-field sparse array radiating a desired near-field pattern with the co-polarization component. After that, a postprocessing of the final array excitation is employed to put constraints on the minimum element spacing to make the sparse layout practicable. The degradation of the near-field pattern is mitigated through reestimating the array excitation by a convex optimization. Three numerical examples show the effectiveness of the proposed method with more than 50% of elements saved compared to the uniformly distributed layout. The comparison to the result obtained by a full-wave simulator FEKO is also presented to demonstrate the validity of this method considering strong antenna mutual couplings.
Author Huang, Zi Xuan
Cheng, Yu Jian
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SubjectTerms Antenna arrays
Antennas
Bayes methods
Bayesian analysis
Bayesian compressive sensing (BCS)
Compressed sensing
Computational geometry
Computer simulation
Convex analysis
convex optimization
Convexity
Couplings
Excitation
Finite element analysis
Focusing
Layouts
Microwave antenna arrays
near-field beam shaping
Optimization
Sidelobes
sparse array
Synthesis
Title Near-Field Pattern Synthesis for Sparse Focusing Antenna Arrays Based on Bayesian Compressive Sensing and Convex Optimization
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