CN115329680A - Optimization method and system for lens in Vivaldi antenna and related equipment - Google Patents
Optimization method and system for lens in Vivaldi antenna and related equipment Download PDFInfo
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- CN115329680A CN115329680A CN202211255513.8A CN202211255513A CN115329680A CN 115329680 A CN115329680 A CN 115329680A CN 202211255513 A CN202211255513 A CN 202211255513A CN 115329680 A CN115329680 A CN 115329680A
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- G06F30/20—Design optimisation, verification or simulation
- G06F30/27—Design optimisation, verification or simulation using machine learning, e.g. artificial intelligence, neural networks, support vector machines [SVM] or training a model
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Abstract
The invention belongs to the field of antennas, and particularly relates to an optimization method, a system and related equipment for a lens in a Vivaldi antenna, wherein the method comprises the steps of taking structural parameters of the lens as optimization parameters, and constructing an initial population for a genetic algorithm; carrying out lens modeling in a simulation environment according to individuals in the initial population to obtain simulation modeling data; calculating individual fitness of the individual according to the simulation modeling data; carrying out genetic calculation on individuals in the initial population according to a preset individual selection rule to obtain genetic individuals; judging whether the genetic algorithm reaches a preset termination condition: if not, updating the iterative initial population by using the genetic individuals, and then optimizing by using a genetic algorithm; if so, outputting the optimal individual according to the genetic individual, and outputting the structural parameter corresponding to the optimal individual as the final parameter of the lens. The invention uses the genetic algorithm to optimize the parameters of the medium lens, so that the gain of the antenna loaded with the lens is obviously improved in the whole working frequency band.
Description
Technical Field
The invention belongs to the field of antennas, and particularly relates to a method and a system for optimizing a lens in a Vivaldi antenna and related equipment.
Background
The Vivaldi 8194, also called as a Tapered Slot Antenna (TSA), is an ideal Antenna for broadband applications, and has the advantages of wide bandwidth, moderate gain, slow change along with the working frequency, stable phase center and the like as one of traveling wave antennas. Although the Vivaldi antenna is a directional antenna, the gain thereof is still too low for many applications, so that it is of great significance to research the high gain technology of the Vivaldi antenna, but it is difficult to improve the gain in a wide frequency band.
At present, the method for improving the gain of the Vivaldi antenna mainly loads a metamaterial at the front end of the antenna, but due to the inherent narrow-band characteristic of the metamaterial, the gain of the antenna can be improved only in a narrow band, so that the problem of improving the gain in a wide band cannot be solved. Dielectric lenses generally have a wide operating band, so that dielectric-loaded Vivaldi antennas have become a research hotspot. In the existing research, the lens can improve the gain of the Vivaldi antenna, but the gain improvement amplitude is not ideal, and the gain can be improved only in a partial frequency band. In addition, the traditional lens with parameter sweeping optimization design still has the problems of time and labor consumption, single lens function and the like.
Disclosure of Invention
The embodiment of the invention provides an optimization method, an optimization system and related equipment for a lens in a Vivaldi antenna, and aims to solve the problem that the gain effect on a dielectric lens in the traditional Vivaldi antenna gain design is not ideal.
In a first aspect, an embodiment of the present invention provides an optimization method for a lens in a Vivaldi antenna, where the optimization method includes the following steps:
taking the structural parameters of the lens as optimization parameters to construct an initial population for a genetic algorithm;
carrying out lens modeling in a simulation environment according to the individuals in the initial population to obtain simulation modeling data;
calculating the individual fitness of the individual according to the simulation modeling data;
carrying out genetic calculation on the individuals in the initial population according to the individual fitness according to a preset individual selection rule to obtain genetic individuals;
judging whether the genetic algorithm reaches a preset termination condition:
if not, updating and iterating the initial population by the genetic individuals, and then optimizing by using the genetic algorithm;
if yes, outputting an optimal individual according to the genetic individual, and outputting the structural parameter corresponding to the optimal individual as a final parameter of the lens.
Still further, the lens includes a conical lens, a truncated cone lens and a hemispherical lens, and the structural parameters include: a bottom surface diameter of the conic lens, a top surface diameter of the truncated cone lens, a bottom surface diameter of the hemispherical lens, a height of the conic lens, a height of the truncated cone lens, a slit width of the lens, and a slit pitch of the lens.
Furthermore, in the step of calculating the individual fitness of the individual according to the simulation modeling data, the number of the structural parameters is defined asnThe size of the initial population isNWherein the individual fitness isF(x)The individual fitnessF(x)Satisfies the following relation (1):
the constraint in relation (1) satisfies the following relations (2) to (4):
in the above relations (2) to (4), minfreqAnd maxfreqRespectively representing a preset optimum minimum frequency and a preset optimum maximum frequency,Gi(x)andRi(x)individual watchShowing the target gain and the actual gain,HPBWE i (x)andHPBWHi(x)respectively represent the frequency points of the individualsiThe 3dB beamwidths of the E-plane and H-plane,Kis a real number greater than 1 and is,ω 1 andω 2 is a predetermined weight.
Further, the preset individual selection rule is specifically:
and sequencing all the individuals in the initial population according to the individual fitness, and screening the individuals meeting a preset proportion from the individuals to perform cross variation.
Further, the preset termination condition is specifically:
the individual with the highest fitness of the individual remains in the initial population for at least 15 iterations of the update.
Further, the size of the starting populationNThe value is 10.
Further, the preset optimized minimum frequency minfreqAt 2GHz, the preset optimum maximum frequency maxfreqAnd 24GHz.
In a second aspect, an embodiment of the present invention further provides an optimization system for a lens in a Vivaldi antenna, including:
the initialization module is used for constructing an initial population for a genetic algorithm by taking the structural parameters of the lens as optimization parameters;
the simulation module is used for carrying out lens modeling in a simulation environment according to the individuals in the initial population to obtain simulation modeling data;
the fitness calculation module is used for calculating the individual fitness of the individual according to the simulation modeling data;
the genetic module is used for carrying out genetic calculation on the individuals in the initial population according to the individual fitness according to a preset individual selection rule to obtain genetic individuals;
the iteration output module is used for judging whether the genetic algorithm reaches a preset termination condition:
if not, updating and iterating the initial population by the genetic individuals, and then optimizing by using the genetic algorithm;
if so, outputting an optimal individual according to the genetic individual, and outputting the structural parameter corresponding to the optimal individual as a final parameter of the lens.
In a third aspect, an embodiment of the present invention further provides a computer device, including: memory, a processor and a computer program stored on the memory and executable on the processor, the processor when executing the computer program implementing the steps in the method for optimizing a lens in a Vivaldi antenna as claimed in any of the previous embodiments.
In a fourth aspect, an embodiment of the present invention further provides a computer-readable storage medium, where a computer program is stored, and the computer program, when executed by a processor, implements the steps in the optimization method for lens in Vivaldi antenna as described in any one of the above embodiments.
The method has the advantages that the parameters of the medium lens are optimized by using a genetic algorithm, the directional diagram optimization is added in the objective function, the E-plane and H-plane beam widths of the antenna are optimized to be approximately equal while high gain and ultra-wide band are realized by the parameters, the gain of the antenna loaded with the lens is obviously improved in the whole working frequency band, and the E-plane and H-plane equal beam widths are realized at a plurality of frequency points.
Drawings
Fig. 1 is a flow chart of steps of a method for optimizing a lens in a Vivaldi antenna according to an embodiment of the present invention;
fig. 2 is a schematic structural diagram of a lens in a Vivaldi antenna according to an embodiment of the present invention;
FIG. 3 is a Vivaldi antenna S according to an embodiment of the present invention 11 A graph is shown;
FIG. 4 is a schematic diagram of a Vivaldi antenna gain curve according to an embodiment of the present invention;
FIG. 5 is a schematic structural diagram of an optimization system for lenses in Vivaldi antenna according to an embodiment of the present invention
Fig. 6 is a schematic structural diagram of a computer device according to an embodiment of the present invention.
Detailed Description
In order to make the objects, technical solutions and advantages of the present invention more apparent, the present invention is further described in detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative of the invention and are not intended to limit the invention.
Referring to fig. 1, fig. 1 is a flow chart illustrating steps of an optimization method for a lens in a Vivaldi antenna according to an embodiment of the present invention, where the optimization method includes the following steps:
s1, taking the structural parameters of the lens as optimization parameters to construct an initial population for a genetic algorithm.
Specifically, referring to fig. 2, fig. 2 is a schematic structural diagram of a lens in a Vivaldi antenna according to an embodiment of the present invention, and in general, the lens in the Vivaldi antenna mainly includes three parts, wherein a conical lens plays a role of a fixed structure in the Vivaldi antenna, a truncated cone lens is responsible for increasing a gain of a low frequency part, and a hemispherical lens is responsible for increasing a gain of a high frequency part.
Still further, the lens includes a conical lens, a truncated cone lens and a hemispherical lens, and the structural parameters include: the bottom surface diameter of the conical lens, the top surface diameter of the truncated cone-shaped lens, the bottom surface diameter of the hemispherical lens, the height of the conical lens, the height of the truncated cone-shaped lens, the slit width of the lens, and the slit distance of the lens. Specifically, referring to the reference numerals in fig. 2, dD1 represents the diameter of the bottom surface of the conical lens, dD2 represents the diameter of the top surface of the truncated cone lens, dD3 represents the diameter of the bottom surface of the hemispherical lens, dH1 represents the height of the conical lens, dD2 represents the height of the truncated cone lens, dw represents the slit width of the lens, and ds represents the slit pitch of the lens.
And S2, carrying out lens modeling in a simulation environment according to the individuals in the initial population to obtain simulation modeling data.
Illustratively, embodiments of the present invention use CST as the simulation environment.
And S3, calculating the individual fitness of the individual according to the simulation modeling data.
Furthermore, in the step of calculating the individual fitness of the individual according to the simulation modeling data, the number of the structural parameters is defined asnThe size of the initial population isNWherein the individual fitness isF(x)The individual fitnessF(x)Satisfies the following relation (1):
the constraint in relation (1) satisfies the following relations (2) to (4):
in the above relations (2) to (4), minfreqAnd maxfreqRespectively representing a preset optimum minimum frequency and a preset optimum maximum frequency,Gi(x)andRi(x)the target gain and the actual gain are represented separately,HPBWE i (x)andHPBWHi(x)respectively represent the frequency points of the individualsiThe 3dB beamwidths of the E-plane and H-plane,Kis a real number greater than 1 and is,ω 1 andω 2 is a predetermined weight.
For a linearly polarized antenna, a section passing through the maximum radiation direction and parallel to the electric field vector is called an E-plane, and a section passing through the maximum radiation direction and parallel to the magnetic field vector is called an H-plane. Gain constraints of the relational expressions (2) and (3) enable the optimal individual gain to be close to the target gain, so that the high gain characteristic of the antenna is achieved, finally, the relational expression (4) represents the constraint on the E surface and H surface 3dB beam width of an individual directional diagram, and the E surface and H surface 3dB beam width of the individual can be approximately equal after optimization;
for the target gain and the actual gain, if the actual gain is greater than a desired valueQ i (x)=0, otherwiseQ i (x)Equal to the difference between the target gain and the actual gain;
f 2 (x)output isHPBWE i (x)AndHPBWH i (x)absolute value of difference divided byK，HPBWE i (x)AndHPBWH i (x)the smaller the difference off 2 (x)The closer to 0, the higher the fitness of the individual, wherein,Kfor real numbers greater than 1, in embodiments of the invention for adjustmentf 2 (x)Of a size off 1 (x)Andf 2 (x)in the same order of magnitude and therefore can be set as desired, for example, in embodiments of the inventionKThe value 3.
Further, the size of the initial populationNThe value is 10.NAnd meanwhile, the number of individuals in the initial population is represented, in the genetic algorithm, the more the number of the individuals is, the higher the accuracy of the result is, but the more the time is spent, so that the value is required to be matched with the size of the optimized parameter.
Further, the preset optimized minimum frequency minfreqAt 2GHz, the preset optimum maximum frequency maxfreqAnd 24GHz.
And S4, carrying out genetic calculation on the individuals in the initial population according to the individual fitness according to a preset individual selection rule to obtain genetic individuals.
Further, the preset individual selection rule is specifically:
and sequencing all the individuals in the initial population according to the individual fitness, and screening the individuals meeting a preset proportion from the individuals to perform cross variation.
In contrast, in the prior art, the sweep parameter optimization is usually used as a method for selecting the optimal result, and in the embodiment of the present invention, the optimization direction of the lens is controlled by the objective function to evolve toward the favorable direction, and finally the best result is selected, so that time and labor are saved.
S5, judging whether the genetic algorithm reaches a preset termination condition:
if not, updating and iterating the initial population by the genetic individuals, and then optimizing by using the genetic algorithm;
if yes, outputting an optimal individual according to the genetic individual, and outputting the structural parameter corresponding to the optimal individual as a final parameter of the lens.
Specifically, the genetic algorithm belongs to an iterative loop algorithm, and through continuous updating of population, individuals subjected to cross inheritance are closer to expected results.
Further, the preset termination condition is specifically:
the individual with the highest fitness of the individual remains in the initial population for at least 15 iterations of the update. By determining that the individual in multiple iterations has the performance closest to the expected value, the genetic algorithm termination condition set by the embodiment of the invention is related to the individual, and when the individual goes through enough cycles, the structural parameter corresponding to the individual is considered to be capable of reflecting higher gain effect most.
Exemplarily, the optimization method of the lens in the Vivaldi antenna provided by the embodiment of the present invention is applied to the Vivaldi antenna S using the dielectric lens obtained by using the lens structure as the optimization parameter as the component 11 The curve is shown in FIG. 3, the gain curve is shown in FIG. 4, and the beam widths of 3dB at different frequency points of the E surface and the H surfaceThe schematic is shown in table 1 below.
Watch (CN)
3dB beam width representation table at different frequency points of E surface and H surface
It can be seen that the Vivaldi antenna is S around 3 GHz after loading the lens with the structural parameters obtained by the embodiment of the present invention 11 Greater than-10 dB, and the rest frequency bands S 11 The total power is less than-10 dB, and the antenna integrally meets the requirement of broadband operation; in the working frequency band, the gain of the feed source antenna is 5.3-10 dBi, the gain of the lens antenna is 8-19.1 dBi, the lowest gain of the antenna is improved by 2.7 dB (2 GHz) after the lens is loaded, and the highest gain of the antenna is improved by 9.3 dB (16 GHz); and for the comparison of the beam widths of the E surface and the H surface of the feed source and the lens antenna with different frequencies, the difference of the beam widths of the E surface and the H surface of the Vivaldi antenna becomes small after the lens is loaded, the difference of the beam widths of the E surface and the H surface of each frequency point in the table is smaller than 10 degrees, and the practicability of the genetic algorithm used in the embodiment of the invention for optimizing the lens parameters is proved.
The method has the advantages that the parameters of the dielectric lens are optimized by using a genetic algorithm, the directional diagram optimization is added in the objective function, the E-plane and H-plane beam widths of the antenna are optimized to be approximately equal while high gain and ultra-wide band are realized through the parameters, the gain of the antenna loaded with the lens is obviously improved in the whole working frequency band, and the E-plane and H-plane equal beam widths are realized at a plurality of frequency points.
Referring to fig. 5, fig. 5 is a schematic structural diagram of an optimization system for a lens in a Vivaldi antenna according to an embodiment of the present invention, which includes:
an initialization module 201, configured to construct an initial population for a genetic algorithm by using the structural parameters of the lens as optimization parameters;
the simulation module 202 is configured to perform lens modeling in a simulation environment according to the individuals in the initial population to obtain simulation modeling data;
a fitness calculating module 203, configured to calculate an individual fitness of the individual according to the simulation modeling data;
a genetic module 204, configured to perform genetic calculation on the individuals in the initial population according to the individual fitness according to a preset individual selection rule, so as to obtain genetic individuals;
an iteration output module 205, configured to determine whether the genetic algorithm reaches a preset termination condition:
if not, updating and iterating the initial population by the genetic individuals, and then optimizing by using the genetic algorithm;
if so, outputting an optimal individual according to the genetic individual, and outputting the structural parameter corresponding to the optimal individual as a final parameter of the lens.
The optimization system 200 for lenses in Vivaldi antenna can implement the steps of the optimization method for lenses in Vivaldi antenna in the above embodiments, and can implement the same technical effects, and will not be described herein again with reference to the description in the above embodiments.
Referring to fig. 6, fig. 6 is a schematic structural diagram of a computer device provided in an embodiment of the present invention, where the computer device 300 includes: a memory 302, a processor 301, and a computer program stored on the memory 302 and executable on the processor 301.
The processor 301 calls the computer program stored in the memory 302 to execute the steps of the method for optimizing a lens in a Vivaldi antenna provided by the embodiment of the present invention, and with reference to fig. 1, the method specifically includes:
taking the structural parameters of the lens as optimization parameters, and constructing an initial population for a genetic algorithm;
performing lens modeling in a simulation environment according to individuals in the initial population to obtain simulation modeling data;
calculating the individual fitness of the individual according to the simulation modeling data;
carrying out genetic calculation on the individuals in the initial population according to the individual fitness according to a preset individual selection rule to obtain genetic individuals;
judging whether the genetic algorithm reaches a preset termination condition:
if not, updating and iterating the initial population by the genetic individuals, and then optimizing by using the genetic algorithm;
if so, outputting an optimal individual according to the genetic individual, and outputting the structural parameter corresponding to the optimal individual as a final parameter of the lens.
Still further, the lenses include a conical lens, a truncated cone lens and a hemispherical lens, and the structural parameters include: the bottom surface diameter of the conical lens, the top surface diameter of the truncated cone-shaped lens, the bottom surface diameter of the hemispherical lens, the height of the conical lens, the height of the truncated cone-shaped lens, the slit width of the lens, and the slit distance of the lens.
Furthermore, in the step of calculating the individual fitness of the individual according to the simulation modeling data, the number of the structural parameters is defined asnThe size of the starting population isNWherein the individual fitness isF(x)The individual fitnessF(x)Satisfies the following relation (1):
the constraint in relation (1) satisfies the following relations (2) to (4):
in the above relations (2) to (4), minfreqAnd maxfreqRespectively representing a preset optimized minimum frequency and a preset optimized maximum frequency,Gi(x)andRi(x)the target gain and the actual gain are represented separately,HPBWE i (x)andHPBWHi(x)respectively represent the frequency points of the individualsiThe 3dB beamwidth of the E-plane and H-plane,Kis a real number greater than 1 and is,ω 1 andω 2 is a predetermined weight.
Further, the preset individual selection rule is specifically:
and sequencing all the individuals in the initial population according to the individual fitness, and screening the individuals meeting a preset proportion from the individuals to perform cross variation.
Further, the preset termination condition is specifically:
the individual with the highest fitness of the individual remains in the initial population for at least 15 iterations of the update.
Further, the size of the initial populationNThe value is 10.
Further, the preset optimized minimum frequency minfreqAt 2GHz, the preset optimum maximum frequency maxfreqIs 24GHz.
The computer device 300 according to the embodiment of the present invention can implement the steps in the method for optimizing a lens in a Vivaldi antenna according to the above embodiment, and can achieve the same technical effects, which are described in the above embodiment and are not described herein again.
An embodiment of the present invention further provides a computer-readable storage medium, where a computer program is stored on the computer-readable storage medium, and when the computer program is executed by a processor, the computer program implements each process and step in the method for optimizing a lens in a Vivaldi antenna provided in the embodiment of the present invention, and can implement the same technical effect, and in order to avoid repetition, details are not repeated here.
It will be understood by those skilled in the art that all or part of the processes of the methods of the embodiments described above may be implemented by a computer program, which may be stored in a computer readable storage medium and executed by a computer to implement the processes of the embodiments of the methods described above. The storage medium may be a magnetic disk, an optical disk, a Read-Only Memory (ROM), a Random Access Memory (RAM), or the like.
It should be noted that, in this document, the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, article, or apparatus. Without further limitation, an element defined by the phrases "comprising a component of' 8230; \8230;" does not exclude the presence of another like element in a process, method, article, or apparatus that comprises the element.
Through the above description of the embodiments, those skilled in the art will clearly understand that the method of the above embodiments can be implemented by software plus a necessary general hardware platform, and certainly can also be implemented by hardware, but in many cases, the former is a better implementation manner. Based on such understanding, the technical solutions of the present invention may be embodied in the form of a software product, which is stored in a storage medium (such as ROM/RAM, magnetic disk, optical disk) and includes instructions for enabling a terminal (such as a mobile phone, a computer, a server, an air conditioner, or a network device) to execute the method according to the embodiments of the present invention.
While the present invention has been described with reference to the preferred embodiments, it is to be understood that the invention is not limited to the disclosed embodiments, which are illustrative, but not restrictive, and that various changes may be made therein by those skilled in the art without departing from the spirit and scope of the invention as defined by the appended claims.
Claims (10)
1. A method of optimizing a lens in a Vivaldi antenna, the method comprising the steps of:
taking the structural parameters of the lens as optimization parameters to construct an initial population for a genetic algorithm;
carrying out lens modeling in a simulation environment according to the individuals in the initial population to obtain simulation modeling data;
calculating the individual fitness of the individual according to the simulation modeling data;
carrying out genetic calculation on the individuals in the initial population according to the individual fitness according to a preset individual selection rule to obtain genetic individuals;
judging whether the genetic algorithm reaches a preset termination condition:
if not, updating and iterating the initial population by the genetic individuals, and then optimizing by using the genetic algorithm;
if so, outputting an optimal individual according to the genetic individual, and outputting the structural parameter corresponding to the optimal individual as a final parameter of the lens.
2. The method for optimizing a lens in a Vivaldi antenna of claim 1, wherein the lens comprises a conical lens, a truncated cone lens, and a hemispherical lens, and the structural parameters comprise: a bottom surface diameter of the conic lens, a top surface diameter of the truncated cone lens, a bottom surface diameter of the hemispherical lens, a height of the conic lens, a height of the truncated cone lens, a slit width of the lens, and a slit pitch of the lens.
3. The method for optimizing a lens in a Vivaldi antenna of claim 1, wherein in the step of calculating the individual fitness of the individual based on the simulation modeling data, the step of determining the individual fitness of the individual is performedDefining the number of said structural parameters asnThe size of the starting population isNWherein the individual fitness isF(x)The individual fitnessF(x)Satisfies the following relation (1):
the constraint in the relational expression (1) satisfies the following relational expressions (2) to (4):
min in the above relations (2) to (4)freqAnd maxfreqRespectively representing a preset optimized minimum frequency and a preset optimized maximum frequency,Gi(x)andRi(x)the target gain and the actual gain are represented separately,HPBWE i (x)andHPBWHi(x)respectively represent the frequency points of the individualsiThe 3dB beamwidths of the E-plane and H-plane,Kis a real number greater than 1 and is,ω 1 andω 2 is a predetermined weight.
4. The method for optimizing lenses in Vivaldi antennas of claim 1, wherein said preset individual selection rule is specifically:
and sequencing all the individuals in the initial population according to the individual fitness, and screening the individuals meeting a preset proportion from the individuals to perform cross variation.
5. The method of optimizing a lens in a Vivaldi antenna of claim 1, wherein the predetermined termination condition is specifically:
the individual with the highest fitness of the individual remains in the initial population for at least 15 iterations of the update.
6. A method for optimizing lenses in Vivaldi antennas as claimed in claim 3, wherein the size of said initial populationNThe value is 10.
7. A method for optimizing a lens in a Vivaldi antenna as claimed in claim 3, characterized in that said preset optimized minimum frequency minfreqAt 2GHz, the preset optimum maximum frequency maxfreqAnd 24GHz.
8. An optimization system for a lens in a Vivaldi antenna, comprising:
the initialization module is used for constructing an initial population for a genetic algorithm by taking the structural parameters of the lens as optimization parameters;
the simulation module is used for carrying out lens modeling in a simulation environment according to the individuals in the initial population to obtain simulation modeling data;
the fitness calculation module is used for calculating the individual fitness of the individual according to the simulation modeling data;
the genetic module is used for carrying out genetic calculation on the individuals in the initial population according to the individual fitness according to a preset individual selection rule to obtain genetic individuals;
the iteration output module is used for judging whether the genetic algorithm reaches a preset termination condition:
if not, updating and iterating the initial population by the genetic individuals, and then optimizing by using the genetic algorithm;
if so, outputting an optimal individual according to the genetic individual, and outputting the structural parameter corresponding to the optimal individual as a final parameter of the lens.
9. A computer device, comprising: memory, processor and computer program stored on said memory and executable on said processor, said processor implementing the steps in the method for optimization of a lens in a Vivaldi antenna according to any of the claims 1 to 7 when executing said computer program.
10. A computer readable storage medium, characterized in that a computer program is stored thereon, which computer program, when being executed by a processor, carries out the steps in the method for optimization of a lens in a Vivaldi antenna as claimed in any one of the claims 1 to 7.
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| PCT/CN2023/115063 WO2024078157A1 (en) | 2022-10-13 | 2023-08-25 | Method and system for optimizing lens in vivaldi antenna, and related device |
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| CN116611273A (en) * | 2023-07-20 | 2023-08-18 | 深圳飞骧科技股份有限公司 | Optimized design method, system and related equipment for broadband high-gain transmission array antenna |
| WO2024078157A1 (en) * | 2022-10-13 | 2024-04-18 | 深圳飞骧科技股份有限公司 | Method and system for optimizing lens in vivaldi antenna, and related device |
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| CN115329680B (en) | 2023-01-31 |
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