A Multi‐Objective Optimization‐Based Reflective Metasurface for Enhanced Multi‐Point Focusing With Diffraction Suppression

Metasurface arrays can achieve beam control at low cost and high quality by providing different phase compensations for each unit, effectively focusing microwave energy on target locations. With the development of short‐range communication technology or microwave power transmission technology, the d...

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Veröffentlicht in:Radio science Jg. 59; H. 7
Hauptverfasser: Xiao, Dongping, Xu, Lanxin, Su, Dongping, Shi, Zhuxin, Zhang, Huaiqing
Format: Journal Article
Sprache:Englisch
Veröffentlicht: Washington Blackwell Publishing Ltd 01.07.2024
Schlagworte:
Algorithms
Arrays
Electric fields
Electromagnetic radiation
Fresnel diffraction
Genetic algorithms
Metasurfaces
Microwave power beaming
multi‐objective optimization algorithm
multi‐point focusing
near field
reflective metasurface
Sorting algorithms
Wave diffraction
Wave propagation
ISSN:0048-6604, 1944-799X
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Zusammenfassung:Metasurface arrays can achieve beam control at low cost and high quality by providing different phase compensations for each unit, effectively focusing microwave energy on target locations. With the development of short‐range communication technology or microwave power transmission technology, the demand for focusing has also increased. Using metasurface arrays to achieve multi‐target focusing has wide application value. However, as the number of focal points increases, the superposition of electromagnetic wave propagation paths leads to significant interference phenomena, which can impact potential applications. Existing solutions are unable to solve such complex problems involving a large number of targets with conflicts between them. Multi‐objective algorithms, by iteratively obtaining a set of optimal solutions, provide decision support for designers in complex multi‐objective problems. This paper alters the phase of cells in a reflective array, calculates the near‐field electric field model using the Fresnel diffraction formula, and employs various solutions using the Non‐dominated Sorting Genetic Algorithm III (NSGA‐III) combined with different constraints. Finally, we select the balanced solution to establish the array. After simulation, three adjacent focal points with normalized central values of 1, 0.86, and 0.88 were obtained, with the maximum electric field value outside the focal points being only 0.58, demonstrating the feasibility of multi‐objective algorithms in solving complex multi‐focal problems. Key Points Near field multi‐objective focusing is the concentration of microwave energy on multiple target locations within the near‐field range Multiple‐objective algorithms is a computational methods for multi‐objective optimization problems and provides a set of optimal solutions
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ISSN:0048-6604
1944-799X
DOI:10.1029/2024RS007968