Go-Caterpillar Mutation and Its Optimization Algorithm for Synthesis of Large-Scale Sparse Planar Arrays

Optimizing the layout of sparse planar arrays constrained by minimum element spacing to reduce the peak sidelobe level (PSLL) is a difficult and challenging task in engineering applications. Here, a new sparse array design method is proposed under the constraints of aperture size, the number of arra...

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Vydané v:IEEE transactions on antennas and propagation Ročník 71; číslo 3; s. 2194 - 2207
Hlavní autori: Zhao, Heng, Ban, Yong-Ling, Liu, Yanhui, Hu, Jun, Nie, Zaiping
Médium: Journal Article
Jazyk:English
Vydavateľské údaje: New York IEEE 01.03.2023
The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Predmet:
Algorithms
Antenna array
Antenna radiation patterns
Apertures
Arrays
Caterpillars
Constraints
Encoding
Finite element analysis
go-caterpillar-mutation (GCM)
Layout
Layouts
Mutation
Optimization
optimization algorithm
Optimization algorithms
Planar arrays
position perturbation model (PPM)
Sidelobes
sparse planar array
Stochastic processes
ISSN:0018-926X, 1558-2221
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Popis
Shrnutí:Optimizing the layout of sparse planar arrays constrained by minimum element spacing to reduce the peak sidelobe level (PSLL) is a difficult and challenging task in engineering applications. Here, a new sparse array design method is proposed under the constraints of aperture size, the number of array elements, and minimum spacing between elements. The approach is based on a new element mutation method which is proposed for mutating the position of any element within the aperture without changing the position of other elements. Because a mutating element can be thought of as being placed inside the board like a black/white stone in go or crawling somewhere nearby like a caterpillar, we call it go-caterpillar-mutation (GCM). Based on GCM, a stochastic optimization algorithm (GCM-OA) is proposed to optimize the layout of sparse planar arrays. Several examples demonstrate the robustness and rapidity of GCM-OA in reducing PSLL by adjusting the array element positions under various constraints.
Bibliografia:ObjectType-Article-1
SourceType-Scholarly Journals-1
ObjectType-Feature-2
content type line 14
ISSN:0018-926X
1558-2221
DOI:10.1109/TAP.2023.3234658