CN113782977A - Multi-beam reflective array antenna based on super surface and manufacturing method thereof - Google Patents

Multi-beam reflective array antenna based on super surface and manufacturing method thereof Download PDF

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CN113782977A
CN113782977A CN202111096204.6A CN202111096204A CN113782977A CN 113782977 A CN113782977 A CN 113782977A CN 202111096204 A CN202111096204 A CN 202111096204A CN 113782977 A CN113782977 A CN 113782977A
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reflective array
directional diagram
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朱诚
胡靓亮
岳琴棉
谭玉龙
李冰琪
温富艳
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Xidian University
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Abstract

The multi-beam reflective array antenna based on the super surface and the manufacturing method thereof comprise a feed source antenna and a super surface reflective array; the feed source antenna is positioned right in front of the super-surface reflection array; the super-surface reflection array comprises N number of super-surface reflection units, and the N number of super-surface reflection units are uniformly distributed to form the super-surface reflection array. The invention can generate the corresponding amplitude and phase distribution of different multi-beams by changing the target directional diagram, can generate the super surface reflection array antenna of different multi-beams by repeating the design steps, can realize the generation of various different beams, and has simple structure and easy realization.

Description

Multi-beam reflective array antenna based on super surface and manufacturing method thereof
Technical Field
The invention belongs to the technical field of super-surface electromagnetic regulation and control, and particularly relates to a super-surface-based multi-beam reflective array antenna and a manufacturing method thereof.
Background
The new artificial electromagnetic surface is a special surface capable of artificially designing electromagnetic parameters, and is formed from sub-wavelength units which are arranged according to a period or a quasi-period. The electromagnetic properties of such materials are independent of the properties of the material itself, and are determined by the structural details of the subwavelength cell. Therefore, the phase of the electromagnetic wave irradiated to the super surface is subjected to sudden change by designing the unit structure on the super surface, so that the phase and the amplitude on the super surface are rearranged, and the propagation direction and the propagation mode of the electromagnetic wave are controlled. The characteristic of the electromagnetic wave front can be flexibly regulated and controlled to enable the electromagnetic super surface to become a proper method for beam forming, and the method has wide application prospect in the fields of radar, communication and the like.
The prior art discloses an arbitrary waveform generator based on a nanostructured surface. The antenna mainly comprises a super-structure surface with amplitude and phase regulation and control capacity and a Vivaldi antenna, and a sector wave generator is arranged by optimizing the distribution of required amplitude and phase through a genetic algorithm to form a target directional diagram in a far field. The antenna has the disadvantages that only a single beam can be generated, a plurality of beams cannot be formed, and the amplitude of the beams can be regulated.
Disclosure of Invention
The invention aims to provide a multi-beam reflective array antenna based on a super surface and a manufacturing method thereof, so as to solve the problems.
In order to achieve the purpose, the invention adopts the following technical scheme:
the multi-beam reflective array antenna based on the super surface comprises a feed source antenna and a super surface reflective array; the feed source antenna is positioned right in front of the super-surface reflection array; the super-surface reflection array comprises N number of super-surface reflection units, and the N number of super-surface reflection units are uniformly distributed to form the super-surface reflection array.
Furthermore, the feed source antenna is a Vivaldi antenna, and the distance between the Vivaldi antenna and the super-surface reflector array is F.
Furthermore, the Vivaldi antenna is composed of an upper metal patch, a middle dielectric substrate and a lower coupled feed microstrip line.
Furthermore, the super-surface reflection unit comprises an I-shaped metal patch, a dielectric substrate and a bottom metal reflection surface; the I-shaped metal patch is arranged on the upper surface of the dielectric substrate, and the bottom metal reflecting surface is arranged on the lower surface of the dielectric substrate.
Furthermore, the super-surface reflection unit has the structural parameters that the unit side length p is 6mm, and the circular ring outer diameter r is 2.7 mm.
Further, the dielectric substrate had a relative dielectric constant of 2.65 and a loss tangent of 0.003.
Further, the multi-beam reflective array antenna based on the super surface and the manufacturing method thereof comprise the following steps:
step 1, optimizing according to a genetic algorithm to obtain the amplitude and phase distribution of a one-dimensional reflective array antenna;
step 2, obtaining a two-dimensional super-surface reflective array antenna through periodic continuation according to the amplitude and phase distribution of the one-dimensional reflective array antenna; carrying out periodic continuation on the amplitude and the phase obtained by optimization to obtain the amplitude and the phase distribution of the N x N two-dimensional area array, and realizing automatic modeling and simulation by adopting an MATLAB and CST combined modeling simulation method, wherein the array surface generates a target beam after being excited by plane waves;
step 3, performing optimization compensation on the amplitude and the phase of the two-dimensional super-surface reflective array antenna according to the actual feed source simulation result;
and 4, designing the super-surface reflective array antenna generating different multi-beams by changing the target directional diagram.
Further, step 1 specifically comprises: firstly, determining an expression of a fitness function in a genetic algorithm, wherein the fitness function expresses the fitting degree of a target directional diagram and a theoretical directional diagram, and the difference between the absolute values of a current directional diagram and a target directional diagram is used as the fitness function and is expressed as follows:
Fitness＝∑|T(θ)-F(θ)|
according to a directional diagram product theory, a theoretical array directional diagram is obtained through the product of the directional diagram of the super-surface reflection unit and the array factor, the goodness and badness of each individual are graded through an adaptability function, the population is subjected to genetic evolution operation according to the adaptability evaluation condition, and circulation is carried out until an optimal solution is found, namely the amplitude and phase distribution of the directional diagram which is most approximate to a target directional diagram.
Further, step 3 specifically comprises:
compensating phase differences caused by different wave paths from the electromagnetic waves to the super surface by changing the phase of each unit in the super surface reflective array antenna; the phase of the unit compensation on the super surface satisfies:
Figure BDA0003264704940000031
wherein (x, y) is the position coordinate of the super-surface unit, F is the focal length, and lambda is the working wavelength,
Figure BDA0003264704940000032
is the phase response of the cell at the center of the super-surface.
Compared with the prior art, the invention has the following technical effects:
the multi-beam reflective array antenna designed by the invention is composed of a Vivaldi antenna as a feed source and a super surface reflective array; the Vivaldi antenna structure is a classical structure, the distance between the Vivaldi antenna and the super-surface reflection array is F, the caliber of the super-surface reflection array is D x D, and the super-surface reflection array is composed of N x N super-surface reflection units. The super-surface reflection unit is an I-shaped unit and consists of an upper I-shaped patch, a dielectric substrate and a bottom metal reflection surface; and cross polarization is adopted for feeding, and amplitude control is realized by controlling the amplitude of the converted cross polarization. The invention can generate the corresponding amplitude and phase distribution of different multi-beams by changing the target directional diagram, can generate the super surface reflection array antenna of different multi-beams by repeating the design steps, can realize the generation of various different beams, and has simple structure and easy realization.
Drawings
FIG. 1 is a schematic view of a feed source and a super-surface reflective array antenna
FIG. 2 is a schematic diagram of a cell structure and simulation
FIG. 3 is a graph showing the variation of the reflection coefficient with alpha
FIG. 4 shows the variation of the reflection coefficient with beta
FIG. 5 Single element normalized Pattern
FIG. 6 flow chart of genetic algorithm
FIG. 7 is a schematic diagram of a genetic algorithm optimized directional diagram process
FIG. 8 Convergence Curve of the fitness function
FIG. 9 is a schematic diagram of phase compensation
FIG. 10 is a schematic diagram of the phase and amplitude compensation principle
FIG. 11 asymmetric dual beam 3D pattern
FIG. 12 asymmetric Dual Beam numerical calculation vs. full wave simulation 2D Pattern
Figure 13 three beam 3D pattern
FIG. 14 comparison of three-beam numerical calculations with full-wave simulated 2D patterns
Figure 15 five-beam 3D pattern
FIG. 16 comparison of five-beam numerical calculation with full-wave simulated 2D patterns
FIG. 17 model of five-beam super-surface reflective array antenna
FIG. 18 five-beam darkroom measurement setup
FIG. 19 comparison of five-beam full-wave simulation with darkroom measured 2D directivity pattern
Detailed Description
The following describes a specific embodiment of the multi-beam super-surface reflective array antenna by way of example.
The super-surface reflection unit adopted in the invention is an I-shaped unit, and is composed of an upper layer I-shaped patch, a dielectric substrate and a bottom layer metal reflection surface, as shown in figure 2. The structural parameters are p is 6mm, r is 2.7mm, t is 0.8mm, and the thickness h is 2.3 mm; the material using F4B as a dielectric substrate had a relative dielectric constant of 2.65, a loss tangent of 0.003, and an all-metal layer as the lowermost layer. The phase and amplitude of the reflected electromagnetic wave are determined by two parameters, alpha and beta, respectively, wherein the angle alpha controls the arm length of the I-shaped unit, and beta represents the rotation angle of the unit around the Z axis.
Compared with other searching methods, the genetic algorithm adopted by the invention has the characteristics of difficult falling into local optimum and easy finding of global optimum solution. As shown in fig. 6, the specific basic flow of the genetic algorithm is as follows:
and (5) initializing a population. Firstly, analyzing the problem, abstracting out parameters and coding optimized variables. The chromosomes are initialized by a method for generating random numbers, and an initial population is generated.
And (5) evaluating the fitness. And taking an evaluation function combining the optimization variables and the optimization target as a fitness function. Before each genetic operation, all individuals in the population are subjected to fitness evaluation through a fitness function, and reference is provided for selection operation.
And (6) selecting operation. Two groups of variables are randomly selected from the population as parent individuals to carry out offspring breeding.
And (4) performing a crossover operation. And exchanging a certain section of gene in the selected pair of parent individuals, namely a certain continuous element in the variable.
And (5) performing mutation operation. And randomly selecting an individual needing mutation operation as a parent individual according to the mutation probability, and randomly selecting a gene value at a certain position to mutate into any random value in the gene replication process of the parent individual. The diversity of the population is maintained through mutation operation, and the local search capability is improved.
And (4) selecting the environment. And selecting excellent individuals to participate in reproduction according to the fitness evaluation result to generate filial generations, and removing genes which are not suitable for population development.
And (5) judging the termination condition. In the evolution process, the evolution process is terminated when the maximum iteration number is reached or the obtained fitness value meets the requirement. And evaluating the optimal individual output by the fitness function in the population, and decoding to obtain the optimal solution.
The above steps are all processes of solving the amplitude and phase distribution of the one-dimensional super-surface reflective array antenna through a genetic algorithm, and the optimal solution is used as the amplitude and phase distribution of the one-dimensional super-surface reflective array antenna.
In the genetic algorithm, a fitness function expresses the degree of fit of a target directional diagram and a theoretical directional diagram. According to the directional diagram product theory, the theoretical array directional diagram can be solved through the product of the directional diagram of the super-surface reflection unit and the array factor. According to the theory of array antennas, the radiation pattern of a planar array consisting of M × N elements can be written as:
Figure BDA0003264704940000051
wherein the content of the first and second substances,
Figure BDA0003264704940000052
is a unit factor, AmnFor the amplitude of the excitation of the antenna element located in the mth row and nth column,
Figure BDA0003264704940000053
the phase of the excitation for the antenna element of the mth row and nth column,
Figure BDA0003264704940000054
and d is the antenna element arrangement interval as the element period in the super-surface array.
When the rotation angle β of the super-surface reflection unit is 45 ° and the opening angle α of the control arm length is 44 °, the plane wave y is incident in a polarized manner, and a normalized directional diagram of a single unit is obtained, as shown in fig. 5, as a unit factor of the array. In order to simplify the design and simplify the problems, the linear array is optimized and then expanded into a planar array. Equally spaced linear arrays of N units arranged along the x-axis in
Figure BDA0003264704940000055
The in-plane pattern can be simplified as follows:
Figure BDA0003264704940000056
the designed target pattern is symmetrically distributed, so the amplitude and the phase of excitation are also symmetrically distributed, and the positions and the amplitude and the phase of the units have the following relations:
Figure BDA0003264704940000057
Figure BDA0003264704940000061
therefore, the one-dimensional linear array directional diagram can be simplified as follows:
Figure BDA0003264704940000062
wherein f (θ) is a single unit
Figure BDA0003264704940000063
Scattering pattern on the surface, AnThe electric field amplitude of the electromagnetic wave reflected by the element denoted by the reference numeral n,
Figure BDA0003264704940000064
the phase of the electric field of the electromagnetic wave reflected by the cell denoted by the reference numeral n, k is the wave constant, and d is the period of the cell. Therefore, for any amplitude and phase combination, a corresponding theoretical directional diagram of any combination can be obtained.
The basic steps for using genetic algorithms to optimize patterns are shown in figure 7. Assuming that the number of individuals contained in the population is NP, NP arrays containing 2N vectors are randomly generated
Figure BDA0003264704940000065
As an initial population (initial solution set), where A1～ANThe weight of the amplitude is a random number in the interval of (0, 1),
Figure BDA0003264704940000066
the weighted value of the phase is a random number in the interval of (0, 360). And then calculating a far-field directional diagram corresponding to each individual by using a directional diagram product theorem, scoring the quality degree of each individual by using an adaptability function, carrying out genetic evolution operation on the population according to the fitness evaluation condition, and circulating until an optimal solution is found. The fitness function is used for evaluating the approximation degree of the current directional diagram and the target directional diagram, and is expressed by using the difference between the absolute values of the current directional diagram and the target directional diagram:
Fitness＝∑|T(θ)-F(θ)|
in the above equation, T (θ) is a designed target pattern, and F (θ) is a current individual pattern. Therefore, the pattern optimization problem is converted into the problem of solving the minimum value by adopting a genetic algorithm.
A specific genetic algorithm flow chart, as shown in fig. 6. In the optimization process of the genetic algorithm, individuals with higher fitness evaluation are selected through selection operation to generate filial generations, and the population quality mean value is favorably improved. Through crossover and mutation operations, the diversity of offspring is improved, and the possibility of solution is increased. And (4) carrying out circular evolution until a preset maximum evolution algebra is reached or the value of the fitness function converges to a preset interval, terminating the genetic evolution process, and selecting the individual with the best fitness evaluation in the current population as a final result, namely the amplitude and phase distribution of the directional diagram which is most approximate to the target directional diagram.
The number of optimization units is set to 10, so that the optimization variables are 10 amplitude values and 10 phase values, and the chromosomes are
Figure BDA0003264704940000067
The initial population number is set to be 50, the mutation probability is 0.1, the cross probability is set to be 0.15, and the selection mode is a tournament method. As shown in fig. 7, the fitness function varies with the evolution algebra during the evolution process, the genetic function can converge within 100 generations, and the fitness function does not change significantly after 100 generations. After the amplitude optimization is introduced, the number of optimization variables and the search space are increased, so that the value of the fitness function after convergence is reduced andthe transfer function converges faster.
And periodically extending the amplitude and the phase obtained by optimization to obtain the amplitude and phase distribution of the two-dimensional area array. In the full-wave simulation, in order to reduce the shielding of the feed source on the reflected wave as much as possible, a Vivaldi antenna is selected as the feed source for simulation. By full wave simulation of the antenna in CST, the gain of the antenna was 5.46dB, with the phase center at 9.5mm from the leading edge of the antenna opening. In simulation, the distance between the Vivaldi antenna and the super-surface reflection array is F, the Vivaldi antenna is arranged right in front of the super-surface along the y axis, and the phase center of the antenna is located at a focus F.
In order to convert spherical waves radiated by the feed source into plane waves in the emergent direction and improve the antenna gain, the phase difference caused by different wave paths from electromagnetic waves to the super surface needs to be compensated by changing the phase of each unit in the super surface reflective array antenna, as shown in fig. 9. Therefore, the phase of the cell compensation on the super surface satisfies:
Figure BDA0003264704940000071
wherein (x, y) is the position coordinate of the super-surface unit, F is the focal length, and lambda is the working wavelength,
Figure BDA0003264704940000072
is the phase response of the cell at the center of the super-surface.
The amplitude and phase compensation values obtained by the above calculation are shown in fig. 10 (c) and (f). FIG. 10 shows a specific method of amplitude and phase compensation, i.e., amplitude multiplication and phase addition, combined with MATLAB to create a super-surface array, which can accomplish the design of the present invention.
In order to verify the correctness of the design method of the present invention, fig. 11 and 12 show the normalized 3D directional diagram and 2D directional diagram of the asymmetric dual-beam super surface reflective array antenna. Comparing the two-dimensional pattern of the numerical calculation with the full-wave simulation, the dual-beam being located at
Figure BDA0003264704940000073
Theta is equal to +/-28 DEG squareAnd upward, the dotted line in the graph is a-3 dB line, and the directional patterns of full-wave simulation and numerical calculation are both lower by 3dB than one beam, which is consistent with the design target and realizes the control of beam energy.
Fig. 13 and 14 show normalized 3D and 2D patterns of a three-beam super-surface reflective array antenna. Comparing the two-dimensional pattern of the numerical calculation and the full-wave simulation, it can be seen that three beams respectively face to θ ═ 0 ° and θ ═ 27 °, the full-wave simulation is substantially consistent with the beam direction of the numerical calculation, and the amplitudes of the three beams are balanced and are consistent with the design target.
Fig. 15 and 16 show normalized 3D and 2D patterns for a five-beam super-surface reflective array antenna. Comparing the two-dimensional pattern of the numerical calculation with the full-wave simulation, it can be seen that the five beams are respectively oriented to θ ═ 0 °, θ ═ 25 °, θ ═ 42 °, and the full-wave simulation is substantially consistent with the beam direction of the numerical calculation and is consistent with the design target.
Darkroom measurements were made on a five-beam super surface reflective array antenna model, as shown in fig. 17 and 18. FIG. 19 shows a comparison of five-beam full-wave simulation with the 2D pattern results of darkroom measurements, with the solid line being full-wave simulation of the subsurface in CST
Figure BDA0003264704940000081
The directional diagram and the dotted line are the measurement results of the super-surface real object in the microwave darkroom, and the two can be seen to be well matched. The above results can verify the correctness and feasibility of the design method of the present invention.

Claims (9)

1. The multi-beam reflective array antenna based on the super surface is characterized by comprising a feed source antenna and a super surface reflective array; the feed source antenna is positioned right in front of the super-surface reflection array; the super-surface reflection array comprises N number of super-surface reflection units, and the N number of super-surface reflection units are uniformly distributed to form the super-surface reflection array.
2. The multi-beam reflectarray antenna based on super-surface of claim 1, characterized in that the feed antenna is a Vivaldi antenna, and the distance between the Vivaldi antenna and the super-surface reflectarray is F.
3. The multi-beam reflectarray antenna based on a super-surface, according to claim 2, wherein the Vivaldi antenna is composed of an upper metal patch, a middle dielectric substrate, and a lower coupled-feed microstrip line.
4. The multi-beam reflective array antenna based on the super surface of claim 1, wherein the super surface reflection unit comprises an I-shaped metal patch, a dielectric substrate and an underlying metal reflection surface; the I-shaped metal patch is arranged on the upper surface of the dielectric substrate, and the bottom metal reflecting surface is arranged on the lower surface of the dielectric substrate.
5. The multi-beam reflective array antenna based on super-surface as claimed in claim 1, wherein the super-surface reflection unit has the structural parameters that the unit side length p is 6mm, and the outer diameter r of the circular ring is 2.7 mm.
6. The multi-beam reflectarray antenna based on a super-surface, according to claim 1, wherein the dielectric substrate has a relative dielectric constant of 2.65 and a loss tangent of 0.003.
7. A multi-beam reflective array antenna based on a super surface and a manufacturing method thereof, wherein the multi-beam reflective array antenna based on the super surface of any one of claims 1 to 6 comprises the following steps:
step 1, optimizing according to a genetic algorithm to obtain the amplitude and phase distribution of a one-dimensional reflective array antenna;
step 2, obtaining a two-dimensional super-surface reflective array antenna through periodic continuation according to the amplitude and phase distribution of the one-dimensional reflective array antenna; carrying out periodic continuation on the amplitude and the phase obtained by optimization to obtain the amplitude and the phase distribution of the N x N two-dimensional area array, and realizing automatic modeling and simulation by adopting an MATLAB and CST combined modeling simulation method, wherein the array surface generates a target beam after being excited by plane waves;
step 3, performing optimization compensation on the amplitude and the phase of the two-dimensional super-surface reflective array antenna according to the actual feed source simulation result;
and 4, designing the super-surface reflective array antenna generating different multi-beams by changing the target directional diagram.
8. The multi-beam reflective array antenna based on super surface and the manufacturing method thereof according to claim 7, wherein the step 1 is specifically: firstly, determining an expression of a fitness function in a genetic algorithm, wherein the fitness function expresses the fitting degree of a target directional diagram and a theoretical directional diagram, and the difference between the absolute values of a current directional diagram and a target directional diagram is used as the fitness function and is expressed as follows:
Fitness＝∑|T(θ)-F(θ)|
according to a directional diagram product theory, a theoretical array directional diagram is obtained through the product of the directional diagram of the super-surface reflection unit and the array factor, the goodness and badness of each individual are graded through an adaptability function, the population is subjected to genetic evolution operation according to the adaptability evaluation condition, and circulation is carried out until an optimal solution is found, namely the amplitude and phase distribution of the directional diagram which is most approximate to a target directional diagram.
9. The multi-beam reflective array antenna based on super surface and the manufacturing method thereof according to claim 7, wherein the step 3 is specifically:
compensating phase differences caused by different wave paths from the electromagnetic waves to the super surface by changing the phase of each unit in the super surface reflective array antenna; the phase of the unit compensation on the super surface satisfies:
Figure FDA0003264704930000021
wherein (x, y) is the position coordinate of the super-surface unit, F is the focal length, and lambda is the working wavelength,
Figure FDA0003264704930000022
is the phase response of the cell at the center of the super-surface.
CN202111096204.6A 2021-09-15 2021-09-15 Multi-beam reflective array antenna based on super surface and manufacturing method thereof Pending CN113782977A (en)

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Cited By (4)

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CN115101948A (en) * 2022-06-29 2022-09-23 电子科技大学 Super-surface beam deflection antenna based on plane mechanical regulation and design method thereof
CN115332812A (en) * 2022-08-25 2022-11-11 中国人民解放军空军工程大学 Active super-surface-based reflective array antenna and manufacturing method thereof
CN115764323A (en) * 2023-01-05 2023-03-07 湖南第一师范学院 Method, apparatus and medium for designing polarization independent super surface with specific function
WO2023226528A1 (en) * 2022-05-24 2023-11-30 普罗斯通信技术（苏州）有限公司 Frequency selective surface for antenna, and antenna system

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