Method for designing multi-beam multi-polarization artificial electromagnetic surface based on deep learning

An artificial electromagnetic surface and deep learning technology, which is applied in design optimization/simulation, calculation, electrical digital data processing, etc., can solve the problems of long acquisition time and complex information acquisition of artificial electromagnetic surface coding units, and shorten the complexity and time , good scalability

Active Publication Date: 2018-11-06
SOUTHEAST UNIV
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[0005] Purpose of the invention: To provide a method for designing multi-beam and multi-polarization artificial electromagnetic surfaces based on deep learning in ord...

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  • Method for designing multi-beam multi-polarization artificial electromagnetic surface based on deep learning
  • Method for designing multi-beam multi-polarization artificial electromagnetic surface based on deep learning
  • Method for designing multi-beam multi-polarization artificial electromagnetic surface based on deep learning

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[0049] The technical solution of the present invention will be further described below in conjunction with the accompanying drawings.

[0050] Taking the design of two double-beam dual-polarization artificial electromagnetic surfaces and one three-beam multi-polarization artificial electromagnetic surface as examples, the method for designing a multi-beam multi-polarization artificial electromagnetic surface based on deep learning of the present invention is described.

[0051] First, we choose a random discrete lattice as the basic pattern of unit particles, such as figure 1 . The lattice pattern includes 16×16 small squares, wherein the gray small squares are metal blocks, and the white small squares are air blocks, that is, they are not covered with any material. The gray small square is marked as "1", and the white small square is marked as "0", which correspond to "1" and "0" in the deep learning design algorithm, and are marked as 1bit unit code. The different two-dime...

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Abstract

The invention discloses a method for designing a multi-beam multi-polarization artificial electromagnetic surface based on deep learning, and the method comprises the following steps: 1) predicting apolarized wave reflection phase of a 1 bit unit through a deep learning design method; 2) combining with a binary particle swarm optimization algorithm module and a deep learning module to design a 1bit unit structure with polarized wave phase difference theta; 3) according to radiation beam design requirements of the artificial electromagnetic surface, selecting the 1 bit unit with correspondingpolarized wave phase difference to perform array coding, and obtaining the multi-beam multi-polarization artificial electromagnetic surface satisfying design requirements. The design method providedby the invention realizes automatic design of ideal reflection phase of a multi-bit unit based on deep learning, is highly efficient and convenient, has excellent expansibility, can substitute software simulation, reduces corresponding complexity and time of obtaining coding unit information, and quickly and easily designs the multi-beam multi-polarization artificial electromagnetic surface.

Description

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Claims

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Application Information

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IPC IPC(8): G06F17/50
CPCG06F30/20
Inventor 崔铁军张茜刘彻万向张磊杨艳
Owner SOUTHEAST UNIV
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