Optimization techniques for antenna arrays

Cheng, David K.

doi:10.1109/proc.1971.8523

Cited by 182 publications

(73 citation statements)

References 18 publications

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“…(a) the optimal excitation coefficients affording a difference pattern with maximum directivity are computed according to the guidelines in [14,15]; (b) the CPM is used to match the optimal pattern, thus defining the "best compromise" solution.…”

Section: Mathematical Formulationmentioning

confidence: 99%

“…where if m = n and b nn = 1 otherwise, ρ mn being the Euclidean distance between the m-th and the n-th element positions [15]. Moreover, T and * denote the transpose and the adjoint operation, respectively.…”

Section: Mathematical Formulationmentioning

confidence: 99%

“…Since the direction (u max , v max ) of maximum directivity, D max , of a difference pattern is not a-priori known, the maximization of D (u, v) is obtained by applying the excitation adjustment method [14,15]. In particular:…”

Section: Mathematical Formulationmentioning

confidence: 99%

“…Since the CPM is an effective and computationally-efficient excitation matching procedure and the optimal coefficients providing the maximum directivity can be easily computed through well known analytical procedures [14,15], the synthesis problem at hand is recast as the definition of the compromise solution that better matches the optimal directivity pattern.…”

Section: Introductionmentioning

confidence: 99%

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Directivity Optimization in Planar Sub-Arrayed Monopulse Antenna

Rocca¹,

Manica²,

Massa³

2008

PIER Letters

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Abstract-In this paper, the Contiguous Partition Method (CPM) is applied to the optimization of the directivity of difference patterns in monopulse planar array antennas. Since the excitations providing maximum directivity of planar arrays can be analytically computed and because of the excitation matching nature of the CPM, the problem at hand is recast as the synthesis of the difference compromise solution close as much as possible to the reference pattern with maximum directivity. Selected results are shown to point out the potentialities of the CPM-based approach.

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Section: Mathematical Formulationmentioning

confidence: 99%

Section: Mathematical Formulationmentioning

confidence: 99%

Section: Mathematical Formulationmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Directivity Optimization in Planar Sub-Arrayed Monopulse Antenna

Rocca¹,

Manica²,

Massa³

2008

PIER Letters

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“…Since its invention, continuous efforts have been put in optimizing its design for desired gain, impedance, SLL and bandwidth, etc., requirements using different optimization techniques based on traditional mathematical approaches [24,4,8,25,7,6,9] and Artificial Intelligence (AI) techniques [16,35,34,3,19,31,30].…”

Section: Introductionmentioning

confidence: 99%

Multi-objective Gain-Impedance Optimization of Yagi-Uda Antenna using NSBBO and NSPSO

Singh¹,

Mittal²,

Sachdeva³

2012

IJCA

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Biogeography-Based Optimization (BBO) is a population based algorithm which has shown impressive performance over other Evolutionary Algorithms (EAs). BBO algorithm is based on the study of distribution of biological organisms over space and time. YagiUda antenna design is most widely used antenna at VHF and UHF frequencies due to high gain, directivity and ease of construction. However, designing a Yagi-Uda antenna, that involves determination of optimal wire-lengths and their spacings, is highly complex and non-linear engineering problem. It further complicates as multiple objectives, viz. gain, and impedance, etc., are required to be optimized due to their conflicting nature, i.e., reactive antenna impedance increases significantly as antenna gain is intended to increase. In this paper Non-dominated Sorting BBO (NSBBO) is proposed and where standard and blended variants of BBO are investigated in optimizing six-element Yagi-Uda antenna designs for multiple objectives, viz., gain and impedance, where ranking of potential solutions is done using non-dominated sorting. The simulation results of BBO variants and Particle Swarm Optimization (PSO) are presented in the ending sections of the paper that depict clearly that NSBBO with blended migration operator is best option among all.

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Side-lobe reduction of a symmetric broadside array by spacing perturbation

1996

Microw. Opt. Technol. Lett.

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Side-lobe reduction of a .rynlinettic broadside array bv tuning-element spacings is presented. Through appropriate point matching and leastsquare error approximation of the radiation power distribution, Jirriher side-lobe reducrion may be achieiied without broadening the beamwidth. Three simulation results will be giL,en to show the applicability of the proposed spncing peHurbation technique in reducing side-lobe leciels. 0 1996 John Wley & Sons, Inc.

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Optimization techniques for antenna arrays

Cited by 182 publications

References 18 publications

Directivity Optimization in Planar Sub-Arrayed Monopulse Antenna

Directivity Optimization in Planar Sub-Arrayed Monopulse Antenna

Multi-objective Gain-Impedance Optimization of Yagi-Uda Antenna using NSBBO and NSPSO

Side-lobe reduction of a symmetric broadside array by spacing perturbation

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