2020
DOI: 10.1002/jnm.2753
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3D printed wideband flat gain multilayer nonuniform reflectarray antenna for X‐band applications

Abstract: Reflectarray antenna designs have become an efficient solution alternative to their counterpart designs due to their beam scanning capability, low profile, high gain, and mounting flexibility. Herein, design and realization of a wideband, flat gain multi-layer nonuniform reflectarray (MNURA) using 3D printing technology is presented. Design optimization of the proposed MNURA has been achieved in the two stages: First, a 3D CST Microwave Studio based Multilayer Perceptron Neural Network (MLP NN) model establish… Show more

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Cited by 13 publications
(11 citation statements)
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“…65 The challenging problem in reflectarray designs is their need of high computational power for optimization process, which requires a high-performance hardware setup or long simulation duration. 66,67 One of the efficient solutions for having fast design optimization of reflectarray designs is the usage of data-driven surrogate models that create a mapping between geometrical design parameters of unit elements and the reflected EM wave phase. 63 In Ref.…”
Section: Surrogate Modeling Of Reflection Phase Characteristics Of a Non-uniform Reflectarray Elementmentioning
confidence: 99%
“…65 The challenging problem in reflectarray designs is their need of high computational power for optimization process, which requires a high-performance hardware setup or long simulation duration. 66,67 One of the efficient solutions for having fast design optimization of reflectarray designs is the usage of data-driven surrogate models that create a mapping between geometrical design parameters of unit elements and the reflected EM wave phase. 63 In Ref.…”
Section: Surrogate Modeling Of Reflection Phase Characteristics Of a Non-uniform Reflectarray Elementmentioning
confidence: 99%
“…This data is obtained as the phases of the reflected waves from the unit cell placed at the termination plane of the TEM mode waveguide simulator implemented the 3D CST MWS‐based analysis (Figure 1B). 3,4 The optimum MLP NN structure is generated by applying Backpropagation Bayesian regularization, which is resulted with the three hidden layers having 15, 30, and 15 neurons respectively, with Mean Absolute Error value of 0.5°. Thus this MLP NN provides an accurate and fast model for the continuous function of the reflection phase φ R for a unit semi‐elliptic ring RA element in terms of the geometrical variables and frequency for the selected ring width w = 2.5 mm.…”
Section: The Unit Cell Elementmentioning
confidence: 99%
“…The dielectric reflectarray based on 3D-printed has a wider bandwidth, low cost and simple production. [13][14][15][16][17][18] The multi-layer non-uniform reflectarray 13 and the circular-hole dielectric reflectarray [14][15][16][17][18] using PLA printing technology have improved a certain operating bandwidth.…”
Section: Introductionmentioning
confidence: 99%