Frequency selective surface structure design method and device based on random image generation algorithm

Abstract

The invention provides a frequency selective surface structure design method and device based on a random image generation algorithm, and the method comprises the steps: generating an initial image based on Berlin noise, and sequentially carrying out the Gaussian blur processing and binarization processing of the initial image, and obtaining a black-and-white image; a means for generating a frequency selective surface structure from the black-and-white image; performing simulation calculation on the unit, and determining electromagnetic performance data of the unit; generating a design database according to the units and the electromagnetic performance data of the units; wherein one-to-one corresponding units and electromagnetic performance data of the units are stored in the design database; and determining a target unit from the design database according to a preset demand. According to the scheme, the design time of the frequency selective surface structure is greatly shortened, and the labor cost is reduced.

Description

Technical Field

[0001] The invention relates to the technical field of electromagnetic frequency selective surface design, and in particular to a frequency selective surface structure design method and device based on a random image generation algorithm. Background Art

[0002] With the rapid development of modern wireless communication technology, frequency selective surfaces, as a special spatial filter, are increasingly used in radar, satellite communications, stealth technology and other fields. The working performance of frequency selective surfaces is related to factors such as unit structure, arrangement and dielectric substrate. Frequency selective surfaces with electromagnetic shielding performance can be obtained through structural design, which has a significant effect on suppressing electromagnetic scattering of radar antennas.

[0003] At present, the design of frequency selective surface structures mainly relies on manual work, especially on the experience of designers, and takes a long time. The frequency selective surface structure has many parameters, the simulation calculation time is long, the consistency between the structural performance and the required indicators also needs manual comparison, and the optimization work is trivial. Therefore, it is necessary to provide a frequency selective surface structure design method and device based on a random image generation algorithm. Summary of the invention

[0004] The present invention provides a method and device for designing a frequency selective surface structure based on a random image generation algorithm. The method greatly shortens the design time of the frequency selective surface structure and reduces the labor cost.

[0005] In a first aspect, the present invention provides a frequency selective surface structure design method based on a random image generation algorithm, comprising:

[0006] Generate an initial image based on Perlin noise, and perform Gaussian blur processing and binarization processing on the initial image in sequence to obtain a black and white image;

[0007] generating a unit of frequency selective surface structure according to the black and white image;

[0008] Performing simulation calculation on the unit to determine electromagnetic performance data of the unit;

[0009] Generate a design database according to the unit and the electromagnetic performance data of the unit; wherein the design database stores one-to-one correspondence between the unit and the electromagnetic performance data of the unit;

[0010] The target unit is determined from the design database according to preset requirements.

[0011] In a second aspect, the present invention further provides a frequency selective surface structure design device based on a random image generation algorithm, comprising:

[0012] An image generation module, used for generating an initial image based on Perlin noise, and performing Gaussian blur processing and binarization processing on the initial image in sequence to obtain a black and white image;

[0013] Constructing a simulation module for generating units of a frequency selective surface structure according to the black and white image; and performing simulation calculation on the units to determine electromagnetic performance data of the units;

[0014] A database module is used to generate a design database based on the units and the electromagnetic performance data of the units; wherein the design database stores one-to-one correspondence between the units and the electromagnetic performance data of the units; and determine the target unit from the design database according to preset requirements.

[0015] In a third aspect, the present invention further provides a computing device comprising a memory and a processor, wherein the memory stores a computer program, and when the processor executes the computer program, it implements any of the above-mentioned frequency selective surface structure design methods based on random image generation algorithm.

[0016] In a fourth aspect, the present invention further provides a computer-readable storage medium having a computer program stored thereon, which, when executed in a computer, enables the computer to execute any of the frequency selective surface structure design methods based on a random image generation algorithm described above.

[0017] In a fifth aspect, an embodiment of the present invention further provides a computer program product, comprising computer instructions, which, when executed by a processor, implement the steps of the method described in any first aspect of this specification.

[0018] The present invention provides a method and device for designing a frequency selective surface structure based on a random image generation algorithm. The method randomly generates an initial image based on a Perlin noise algorithm, and then obtains a large-area continuous black-and-white image through Gaussian blur processing and binarization processing, so as to generate units of the frequency selective surface structure according to the black-and-white image. In this way, a large number of units of the frequency selective surface structure are generated in this way, and each unit is simulated and calculated to determine the electromagnetic performance data corresponding to each unit, and a design database is established based on this, and the units and the electromagnetic performance data of the units are stored one by one, so that the target unit that best meets the preset requirements is directly determined from the design database by electromagnetic performance screening, thereby greatly shortening the design time of the frequency selective surface structure, no longer completely relying on manual labor, and reducing labor costs. BRIEF DESCRIPTION OF THE DRAWINGS

[0019] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0020] Figure 1 is a flow chart of a frequency selective surface structure design method based on a random image generation algorithm provided by an embodiment of the present invention;

[0021] Figure 2 is an initial image generated based on Perlin noise provided by an embodiment of the present invention;

[0022] Figure 3 is a preprocessed image provided by an embodiment of the present invention;

[0023] Figure 4 is a black and white image provided by an embodiment of the present invention;

[0024] Figure 5 is a schematic diagram of a process of converting a first grid into a second grid provided by an embodiment of the present invention;

[0025] Figure 6 A schematic diagram of a unit periodic tessellation provided by an embodiment of the present invention;

[0026] Figure 7 is a schematic diagram of a unit of a converted frequency selective surface structure provided by an embodiment of the present invention;

[0027] Figure 8 It is a schematic diagram of adding diodes to a unit of two side-by-side frequency selective surface structures provided by one embodiment of the present invention;

[0028] Fig. 9 is a schematic diagram of a unit of a frequency selective surface structure with a diode added provided by an embodiment of the present invention;

[0029] Fig.10 is a hardware architecture diagram of a computing device provided by an embodiment of the present invention;

[0030] Fig.11 It is a structural diagram of a frequency selective surface structure design device based on a random image generation algorithm provided by one embodiment of the present invention. DETAILED DESCRIPTION

[0031] In order to make the purpose, technical solutions and advantages of the embodiments of the present invention clearer, the technical solutions in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are part of the embodiments of the present invention, rather than all the embodiments. Based on the embodiments in the present invention, all other embodiments obtained by ordinary technicians in this field without making creative work are within the scope of protection of the present invention.

[0032] Please refer to Figure 1 The embodiment of the present invention provides a frequency selective surface structure design method based on a random image generation algorithm, comprising:

[0033] Step 100, generating an initial image based on Perlin noise, and performing Gaussian blur processing and binarization processing on the initial image in sequence to obtain a black and white image;

[0034] Step 102, selecting a unit of the surface structure according to the frequency of generation of the black and white image;

[0035] Step 104, performing simulation calculation on the unit to determine the electromagnetic performance data of the unit;

[0036] Step 106, generating a design database according to the units and the electromagnetic performance data of the units; wherein the design database stores one-to-one correspondence between the units and the electromagnetic performance data of the units;

[0037] Step 108: Determine the target unit from the design database according to preset requirements.

[0038] In the present invention, an initial image is first randomly generated based on the Perlin noise algorithm, and then a large-area continuous black-and-white image is obtained through Gaussian blur processing and binarization processing, so as to generate units of the frequency selective surface structure according to the black-and-white image. In this way, a large number of units of the frequency selective surface structure are generated in this way, and each unit is simulated and calculated to determine the electromagnetic performance data corresponding to each unit, and a design database is established based on this, and the units and the electromagnetic performance data of the units are stored one by one, so that the target unit that best meets the preset requirements is directly determined from the design database by electromagnetic performance screening, thereby greatly shortening the design time of the frequency selective surface structure, no longer completely relying on manual labor, and reducing labor costs.

[0039] Described below Figure 1 How the various steps are performed.

[0040] First, in step 100, an initial image is generated based on Perlin noise, and Gaussian blur processing and binarization processing are performed on the initial image in sequence to obtain a black and white image, including:

[0041] A two-dimensional Perlin noise algorithm is used to generate a random grayscale image of a preset size to obtain an initial image;

[0042] Perform Gaussian blur processing on the initial image to obtain a preprocessed image;

[0043] The preprocessed image is binarized according to a preset threshold to obtain a black and white image.

[0044] It should be noted that the two-dimensional Perlin noise algorithm is used to generate a random grayscale image of a preset size as the initial image, which essentially generates a matrix of a preset size composed of integers between 0 and 255, and each point value represents the grayscale value of the image at that point.

[0045] In a specific implementation, a two-dimensional Perlin noise algorithm is used to generate a random grayscale image of a preset size to obtain an initial image, including:

[0046] Construct a two-dimensional Perlin noise function;

[0047] According to the two-dimensional Perlin noise function, the direction vector of each grid point is determined;

[0048] According to the direction vector and the center point located in the grid point, the gradient and the pointing vector of the adjacent grid point are calculated;

[0049] According to the gradient and the pointing vector of each adjacent grid point, the noise influence value of the four adjacent grid points around the center point on the center point is determined;

[0050] The Perlin noise value of the center point is calculated according to the noise influence value, and the Perlin noise value is used as the grayscale value of the initial image.

[0051] Specifically, assume that the noise function is defined on a regular grid as:

[0052]

[0053] Each grid point is defined as a corresponding integer value, and the value with a decimal part is located between each grid point. Therefore, for any point (x, y) (x, y are not integers), it falls within the square area surrounded by four adjacent grid points (x0, y0), (x1, y0), (x0, y1), (x1, y1). In order to construct the Perlin noise function, a pseudo-random gradient with a length of 1 is constructed at each grid point to obtain its vector pointing to the center point (x, y);

[0054] Then determine the four adjacent grid points around the center point on the two-dimensional plane, and use these four adjacent grid points as the origin to obtain four direction vectors, namely g(x0,y0), g(x1,y0), g(x0,y1), and g(x1,y1). Through these four direction vectors and the center point, the gradient and direction vector of the adjacent grid points can be obtained. The gradients of the center point and the four adjacent grid points are (x,y)-(x0,y0), (x,y)-(x1,y0), (x,y)-(x0,y1), and (x,y)-(x1,y1). First, calculate the dot product of the gradient and direction vector of each adjacent grid point to obtain the noise impact value of each adjacent grid point on the sweet spot:

[0055] s=g(x0,y0)·((x,y)-(x0,y0)) (2)

[0056] t=g(x1,y0)·((x,y)-(x1,y0)) (3)

[0057] u=g(x0,y1)·((x,y)-(x0,y1)) (4)

[0058] v=g(x1,y1)·((x,y)-(x1,y1)) (5)

[0059] Then use the function 3p 3 -2p 3 Smooth the difference of the noise impact value, first calculate the value of the smooth curve at x-x0, and get the direction weight S of x x ; Then use the constructor to get the weighted average of s and t. Similarly, we can get the weighted average of u and v.

[0060] S x =3(x-x0) 2 -2(x-x0) 3 (6)

[0061] a=s+S x (ts) (7)

[0062] b=s+S x (vu) (8)

[0063] Finally, calculate the value of the smooth curve at y-y0 to get the weight S in the y direction y , perform weighted average on the above-obtained a and b, which is the final output Perlin noise value z;

[0064] S y =3(y-y0) 2 -2(y-y0) 3 (9)

[0065] z=a+S y (ba) (10)

[0066] The final generated initial image is as follows Figure 2 shown.

[0067] In the present invention, the irregular noise points in the initial image are smoothed by Gaussian blur processing to generate a relatively continuous pre-processed image, such as Figure 3 Specifically, the standard deviation of the Gaussian kernel selected by the present invention when performing Gaussian blur is relatively large, preferably 30.

[0068] In a preferred embodiment, binarization is performed on the preprocessed image according to a preset threshold to obtain a black and white image, including:

[0069] Get the gray value of each pixel in the preprocessed image;

[0070] The grayscale values ​​of pixels not less than the preset threshold are converted to 255, and the grayscale values ​​of pixels less than the preset threshold are converted to 0.

[0071] It should be noted that the grayscale value is the color depth of each pixel in a black and white image, ranging from 0 to 255, where 0 represents black and 255 represents white. Specifically, for example, if the preset threshold is 128, that is, grayscale values ​​of 0 to 127 are converted to black, and grayscale values ​​of 128 to 255 are converted to white. Figure 3 After the binarization process, we get Figure 4 .

[0072] In the present invention, a global threshold method is used in the binarization processing, which not only reduces the data dimension, but also eliminates the interference caused by the noise in the original image, and directly highlights the contour range of the area, which is conducive to the subsequent direct setting of conductor patch sub-units in the highlighted area to obtain units with frequency selective surface structures without the need for manual special design, thereby reducing the design difficulty.

[0073] In step 102, a unit of a frequency-selective surface structure is generated according to a black-and-white image, including:

[0074] A plurality of regular hexagonal unit grids are tiled to obtain a first grid; wherein the area of ​​the first grid is the same as the area of ​​the black-and-white image;

[0075] Any two adjacent edges of the first grid are truncated to obtain a complementary unit grid, and the untruncated edge of the first grid is complemented by the complementary unit grid to obtain a second grid of the same size as the black-and-white image; wherein when the second grids are tiled, the complementary unit grids at the common edges of any two second grids can be spliced ​​to obtain a complete regular hexagonal unit grid;

[0076] The black-and-white image is divided according to the second grid, and the unit grid and the complementary unit grid where the black area in the black-and-white image is located are used as the conductor patch sub-units of the unit to obtain the unit.

[0077] In the present invention, in order to facilitate simulation calculation, hexagons are used as the basic units of frequency selective surfaces. Since square units have three relationships of "edge to edge", "point to point" and "non-adjacent" when periodically paved, "point to point" will cause non-manifold patterns, and some simulation algorithms cannot calculate such patterns. Therefore, in order to avoid this problem, regular hexagons that can be periodically paved are selected, in which the relationships between units are only "edge to edge" and "non-adjacent".

[0078] Specifically, Figure 5 As shown, 16 regular hexagonal unit grids are arranged in 4*4 tiles to obtain the first grid (as shown in Figure 5 As shown in the left figure), the right and bottom sides of the first grid are cut off to obtain a complementary unit grid (as shown in the left figure). Figure 5 The 1,4-complementary unit grid, 2,4-complementary unit grid, 3,4-complementary unit grid, 4,4-complementary unit grid, 4,2-complementary unit grid, shown in the right figure, are then used to complement the left and top sides of the first grid, that is, the right side complements the left side, and the bottom side complements the top side, and the following is obtained: Figure 5 The second grid shown in the right figure, when the second grid is tiled, the complementary unit grids at the common edges of adjacent second grids can be spliced ​​to obtain a complete regular hexagonal unit grid (such as Figure 6 shown).

[0079] Continuing from the previous example, Figure 4 The process of converting into frequency selective surface structural units according to the above method is as follows: Figure 7 As shown, we can use hexagons to divide and reorganize it into approximate shapes, and get the following Figure 7 The cell shown on the right, where each hexagon in the black area can accommodate a conductor patch subcell.

[0080] In a preferred embodiment, after generating the unit of the frequency selective surface structure according to the black and white image in step 102, the method further includes: replacing the conductor patch sub-unit with an electronic component.

[0081] In the present invention, the conductor patch subunits in each unit of the frequency selective surface structure can be selected to add electronic components according to actual needs. If the actual need is a frequency selective surface with adjustable working frequency band, some conductor patch subunits need to be replaced with electronic components.

[0082] In a preferred embodiment, when the electronic component is a diode, determining the position of the diode and the direction of current flow;

[0083] Delete all conductor patch sub-units except the diode in the direction perpendicular to the current flow.

[0084] In the present invention, since the diode has unidirectional conductivity, when it is turned on, the current flows into the positive electrode and flows out of the negative electrode, and the conductor patch sub-units are usually connected. Therefore, in order to determine the unidirectional conductivity of the diode, it is necessary to delete all the conductor patch sub-units in the direction perpendicular to the current flow of the diode and only retain the diode.

[0085] In a more preferred embodiment, all conductor patch sub-units except the diode in the direction perpendicular to the current flow are deleted, including:

[0086] When the units are arranged periodically, all conductor patch sub-units except the diode in the current unit where the diode is located and in the adjacent units in the direction perpendicular to the current flow direction are deleted.

[0087] In the present invention, since the units with a frequency selective surface structure are used in a periodic paving manner, when adjacent units are tiled, conductor patch sub-units in a direction perpendicular to the diode current flow will appear on adjacent units. The existence of the conductor patch sub-unit will affect the unidirectional conduction performance of the diode, so it is necessary to further delete the conductor patch sub-unit.

[0088] Specifically, in the unit of the frequency selective surface structure obtained by the above method, k regular hexagonal positions are randomly selected, where k is the number of diodes to be added, and a value j ranging from 1 to 6 integers is randomly generated for each position to determine the direction of the diode at that position, corresponding to the 6 combinations of regular hexagons connecting relative vertices. Diodes are added to the selected positions in the direction represented by the corresponding j, and a column of units parallel to the diode direction is deleted until a blank area. It should be noted that since the units are arranged periodically in actual applications, the units connected after the periodic arrangement should also be deleted. For example, in Figure 8 In the example, k=2, the location of the red dot is determined as the randomly added diode location, and the blue area is the regular hexagonal conductor patch subunit to be deleted. Figure 8 A schematic diagram showing two side-by-side frequency selective surface structure units with diodes added. After deleting the conductor patch sub-unit in the blue area, the resulting frequency selective surface structure unit is as follows Fig. 9 shown.

[0089] In the present invention, by repeating steps 100 to 104, n different units of frequency selective surface structures are generated, where n is the size of the design database to be established. Each time a unit is generated, it is modeled and simulated to obtain electromagnetic performance data, and the unit and the electromagnetic performance data of the unit are stored in a one-to-one correspondence to obtain a design database.

[0090] After step 108, the method further includes: optimizing the target unit based on design experience.

[0091] In the present invention, in the subsequent use process, the user only needs to compare the preset requirements with the electromagnetic performance data in the established design database one by one, and select the target unit that meets the requirements as much as possible. If the selected target unit cannot fully meet the requirements, manual improvement design can be performed based on the selected unit, thereby reducing manual design time and improving design efficiency.

[0092] like Fig.10 , Fig.11 As shown, the embodiment of the present invention provides a frequency selective surface structure design device based on a random image generation algorithm. The device embodiment can be implemented by software, or by hardware or a combination of software and hardware. From the hardware level, Fig.10 As shown in FIG. 1 , a hardware architecture diagram of a computing device where a frequency selective surface structure design device based on a random image generation algorithm provided by an embodiment of the present invention is located is shown in FIG. Fig.10 In addition to the processor, memory, network interface, and non-volatile memory shown in the figure, the computing device in which the device is located in the embodiment may also generally include other hardware, such as a forwarding chip responsible for processing messages, etc. Taking software implementation as an example, Fig.11 As shown, as a device in a logical sense, the CPU of the computing device in which it is located reads the corresponding computer program in the non-volatile memory into the memory and runs it. This embodiment provides a frequency selective surface structure design device based on a random image generation algorithm, including:

[0093] An image generation module 110 is used to generate an initial image based on Perlin noise, and perform Gaussian blur processing and binarization processing on the initial image in sequence to obtain a black and white image;

[0094] Constructing a simulation module 112, for generating units of the frequency selective surface structure according to the black and white image; and performing simulation calculations on the units to determine electromagnetic performance data of the units;

[0095] The database module 114 is used to generate a design database based on the units and the electromagnetic performance data of the units; wherein the design database stores one-to-one correspondence between the units and the electromagnetic performance data of the units; and determine the target unit from the design database according to preset requirements.

[0096] In some specific implementations, the image generation module 110 may be used to execute the above step 100 , the construction simulation module 112 may be used to execute the above steps 102 and 104 , and the database module 114 may be used to execute the above steps 106 and 108 .

[0097] In some specific implementations, the image generation module 110 is further configured to perform the following operations:

[0098] A two-dimensional Perlin noise algorithm is used to generate a random grayscale image of a preset size to obtain an initial image;

[0099] Perform Gaussian blur processing on the initial image to obtain a preprocessed image;

[0100] The preprocessed image is binarized according to a preset threshold to obtain a black and white image.

[0101] In some specific implementations, the image generation module 110 is further configured to perform the following operations:

[0102] Get the gray value of each pixel in the preprocessed image;

[0103] The grayscale values ​​of pixels not less than the preset threshold are converted to 255, and the grayscale values ​​of pixels less than the preset threshold are converted to 0.

[0104] In some specific implementations, the construction simulation module 112 is further configured to perform the following operations:

[0105] A plurality of regular hexagonal unit grids are tiled to obtain a first grid; wherein the area of ​​the first grid is the same as the area of ​​the black-and-white image;

[0106] Any two adjacent edges of the first grid are truncated to obtain a complementary unit grid, and the untruncated edge of the first grid is complemented by the complementary unit grid to obtain a second grid of the same size as the black-and-white image; wherein when the second grids are tiled, the complementary unit grids at the common edges of any two second grids can be spliced ​​to obtain a complete regular hexagonal unit grid;

[0107] The black-and-white image is divided according to the second grid, and the unit grid and the complementary unit grid where the black area in the black-and-white image is located are used as the conductor patch sub-units of the unit to obtain the unit.

[0108] In some specific implementations, the construction simulation module 112 is further configured to perform the following operations:

[0109] After generating units of the frequency selective surface structure based on the black and white image, the conductor patch subunits are replaced with electronic components.

[0110] In some specific implementations, the construction simulation module 112 is further configured to perform the following operations:

[0111] After generating units of frequency-selective surface structures according to black and white images,

[0112] Replace the conductor patch subunit with a diode and determine the position of the diode and the direction of current flow;

[0113] All conductor patch sub-units except the diode in the direction perpendicular to the current flow are deleted, and when the units are arranged periodically, all conductor patch sub-units except the diode in the direction perpendicular to the current flow in the current unit where the diode is located and the adjacent units are deleted.

[0114] In some specific implementations, the device further includes an optimization module, and the optimization module is used to optimize the target unit based on design experience.

[0115] It is to be understood that the structure illustrated in the embodiment of the present invention does not constitute a specific limitation on a frequency selective surface structure design device based on a random image generation algorithm. In other embodiments of the present invention, a frequency selective surface structure design device based on a random image generation algorithm may include more or fewer components than shown in the figure, or combine some components, or split some components, or arrange the components differently. The components shown in the figure may be implemented in hardware, software, or a combination of software and hardware.

[0116] The information interaction, execution process and other contents between the modules in the above-mentioned device are based on the same concept as the embodiment of the method of the present invention. For specific contents, please refer to the description in the embodiment of the method of the present invention, and no further description is given here.

[0117] An embodiment of the present invention further provides a computing device, including a memory and a processor, wherein the memory stores a computer program, and when the processor executes the computer program, a frequency selective surface structure design method based on a random image generation algorithm in any embodiment of the present invention is implemented.

[0118] An embodiment of the present invention further provides a computer-readable storage medium, on which a computer program is stored. When the computer program is executed by a processor, the processor executes a frequency selective surface structure design method based on a random image generation algorithm in any embodiment of the present invention.

[0119] An embodiment of the present application also provides a computer program product, which includes a computer program. A processor of a computer device reads the computer program from a computer-readable storage medium, and the processor executes the computer program, so that the computer device executes a frequency selective surface structure design method based on a random image generation algorithm as described in any of the above embodiments.

[0120] Specifically, a system or device equipped with a storage medium can be provided, on which software program code that implements the functions of any of the above-mentioned embodiments is stored, and a computer (or CPU or MPU) of the system or device can read and execute the program code stored in the storage medium.

[0121] In this case, the program code itself read from the storage medium can realize the function of any one of the above-mentioned embodiments, and thus the program code and the storage medium storing the program code constitute a part of the present invention.

[0122] The storage medium embodiments for providing the program code include a floppy disk, a hard disk, a magneto-optical disk, an optical disk (such as CD-ROM, CD-R, CD-RW, DVD-ROM, DVD-RAM, DVD-RW, DVD+RW), a magnetic tape, a non-volatile memory card, and a ROM. Alternatively, the program code can be downloaded from a server computer by a communication network.

[0123] In addition, it should be clear that the functions of any of the above embodiments can be implemented not only by executing the program code read by the computer, but also by enabling an operating system operating on the computer to complete part or all of the actual operations based on instructions from the program code.

[0124] In addition, it can be understood that the program code read from the storage medium is written to a memory provided in an expansion board inserted into the computer or to a memory provided in an expansion module connected to the computer, and then based on the instructions of the program code, a CPU installed on the expansion board or expansion module is enabled to perform part or all of the actual operations, thereby realizing the functions of any of the above-mentioned embodiments.

[0125] It should be noted that, in this article, relational terms such as first and second are only used to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Moreover, the terms "include", "comprise" or any other variants thereof are intended to cover non-exclusive inclusion, so that a process, method, article or device including a series of elements includes not only those elements, but also other elements not explicitly listed, or also includes elements inherent to such process, method, article or device. In the absence of further restrictions, the elements defined by the statement "comprise a ..." do not exclude the presence of other identical factors in the process, method, article or device including the elements.

[0126] A person of ordinary skill in the art can understand that all or part of the steps of implementing the above method embodiments can be completed by hardware related to program instructions, and the aforementioned program can be stored in a computer-readable storage medium. When the program is executed, it executes the steps of the above method embodiments; and the aforementioned storage medium includes: ROM, RAM, magnetic disk or optical disk, etc., various media that can store program codes.

[0127] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit it. Although the present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the aforementioned embodiments, or make equivalent replacements for some of the technical features therein. However, these modifications or replacements do not deviate the essence of the corresponding technical solutions from the spirit and scope of the technical solutions of the embodiments of the present invention.

Claims

1. A frequency selective surface structure design method based on a random image generation algorithm, characterized in that: include: Generate an initial image based on Perlin noise, and perform Gaussian blur processing and binarization processing on the initial image in sequence to obtain a black and white image; generating a unit of frequency selective surface structure according to the black and white image; Performing simulation calculation on the unit to determine electromagnetic performance data of the unit; Generate a design database according to the unit and the electromagnetic performance data of the unit; wherein the design database stores one-to-one correspondence between the unit and the electromagnetic performance data of the unit; The target unit is determined from the design database according to preset requirements.

2. The method according to claim 1, characterized in that The generating of the initial image based on Perlin noise, and sequentially performing Gaussian blur processing and binarization processing on the initial image to obtain a black-and-white image, comprises: A two-dimensional Perlin noise algorithm is used to generate a random grayscale image of a preset size to obtain an initial image; Performing the Gaussian blur processing on the initial image to obtain a preprocessed image; The preprocessed image is subjected to the binarization process according to a preset threshold value to obtain the black-and-white image.

3. The method according to claim 2, characterized in that The binarization process is performed on the pre-processed image according to a preset threshold value to obtain the black-and-white image, including: Obtaining the grayscale value of each pixel in the preprocessed image; The grayscale values ​​of pixels not less than the preset threshold are converted to 255, and the grayscale values ​​of pixels less than the preset threshold are converted to 0.

4. The method according to claim 1, characterized in that The unit for generating a frequency selective surface structure according to the black and white image comprises: Arrange a plurality of regular hexagonal unit grids in a tiled manner to obtain a first grid; wherein the area of ​​the first grid is the same as the area of ​​the black-and-white image; Truncating any two adjacent edges of the first grid to obtain a complementary unit grid, and using the complementary unit grid to complement the untruncated edge of the first grid to obtain a second grid of the same size as the black-and-white image; wherein when the second grids are tiled, the complementary unit grids at the common edges of any two of the second grids can be spliced ​​to obtain a complete regular hexagonal unit grid; The black-and-white image is divided according to the second grid, and the unit grid and the complementary unit grid where the black area in the black-and-white image is located are used as conductor patch sub-units of the unit to obtain the unit.

5. The method according to claim 4, characterized in that After the unit generating the frequency selective surface structure according to the black and white image, it also includes: Replacing the conductor patch subunit with electronic components; and / or, Replacing the conductor patch subunit with a diode, and determining the position of the diode and the current flow direction; The conductor patch sub-units except the diode in the direction perpendicular to the current flow direction are all deleted.

6. The method according to claim 5, characterized in that Deleting all the conductor patch sub-units except the diode in a direction perpendicular to the current flow direction includes: When the units are arranged periodically, the conductor patch sub-units except for the diode in the current unit where the diode is located and the adjacent units in the direction perpendicular to the current flow direction are all deleted.

7. The method according to any one of claims 1 to 6, characterized in that: After determining the target unit from the design database according to the preset requirements, the method further includes: The target unit is optimized based on design experience.

8. A frequency selective surface structure design device based on a random image generation algorithm, characterized in that: include: An image generation module, used to generate an initial image based on Perlin noise, and perform Gaussian blur processing and binarization processing on the initial image in sequence to obtain a black and white image; constructing a simulation module for generating units of a frequency selective surface structure according to the black and white image; and performing simulation calculation on the unit to determine electromagnetic performance data of the unit; A database module is used to generate a design database based on the units and the electromagnetic performance data of the units; wherein the design database stores one-to-one correspondence between the units and the electromagnetic performance data of the units; and determine the target unit from the design database according to preset requirements.

9. A computing device, comprising a memory and a processor, wherein the memory stores a computer program, and when the processor executes the computer program, the method according to any one of claims 1 to 7 is implemented.

10. A computer-readable storage medium having a computer program stored thereon, which, when executed in a computer, causes the computer to execute the method according to any one of claims 1 to 7.

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