A hybrid electromagnetic simulation method suitable for multi-scale fine structure antenna

Abstract

The application discloses a hybrid electromagnetic simulation method suitable for a multi-scale fine structure antenna, and comprises the following steps: firstly, a multi-scale fine structure antenna model to be simulated is created, and the range of the size of the model in a calculation space is determined; a convolutional perfectly matched layer suitable for a hybrid implicit-explicit finite difference time domain method is constructed, and the range of the entire calculation space containing the convolutional perfectly matched layer is determined, then a non-uniform grid is set, a fine region and a transition region from fine to coarse are determined; the three are combined, an excitation source of an electric field is added, then a convolutional perfectly matched layer absorption term, a magnetic field value and an electric field value at the next moment are obtained; finally, the excitation source of the fine structure direction is updated, and a time step is updated. The application proposes a method of efficiently combining a hybrid implicit-explicit finite difference time domain method with a non-uniform grid technology and a convolutional perfectly matched layer, which not only improves the calculation precision, but also significantly simplifies the implementation process and improves the calculation efficiency.

Description

TECHNICAL FIELD

[0001] The present application relates to the field of physical computing, specifically to the electromagnetic simulation of multi-scale fine structures, and proposes a hybrid electromagnetic simulation method suitable for multi-scale fine structure antennas; specifically, it relates to an efficient simulation method in the Cartesian coordinate system, combining the hybrid implicit-explicit finite difference time domain method, non-uniform grid technology and convolutional perfectly matched layer. BACKGROUND

[0002] The absorbing boundary is to deal with the challenge encountered in the simulation of infinite space electromagnetic propagation problem in computational electromagnetics. In electromagnetic problems, electromagnetic waves usually propagate in infinite space, however, in numerical simulation, the calculation domain must be finite, if no measures are taken, electromagnetic waves will be reflected back at the boundary of the calculation domain, resulting in inaccurate calculation results. At present, the most representative absorbing boundary is Mur absorbing boundary, perfectly matched layer (Perfectly Matched Layer, PML) and convolutional perfectly matched layer (Convolutional PML, CPML), and CPML is an improved version of PML, which can provide better numerical stability and better absorption effect than traditional PML.

[0003] The development of non-uniform grid technology began with the application requirements of electromagnetic solution methods in high-frequency electromagnetic wave propagation, simulation of complex geometric shapes, and various non-uniform media. Using uniform grid to simulate electromagnetic field means that all points in the entire simulation region have the same spatial step. This may be sufficient in simple geometric structures, but when dealing with problems with complex geometric shapes or multi-scale features, uniform grid will result in huge computational burden. While non-uniform grid technology allows finer grid to be used in these key areas, while maintaining coarser grid in other areas, thus improving the accuracy and stability of the calculation.

[0004] Nowadays, computer technology is developing at a high speed, and electromagnetic simulation problems are becoming more and more complex. In this case, due to the limitations of traditional analytical methods, it is difficult to meet the complex electromagnetic simulation requirements, and numerical calculation methods have become the mainstream means to solve such problems. Among them, the finite-difference time-domain (FDTD) method, as one of the three main numerical algorithms, has significant advantages and is widely used in many research fields. It has become an indispensable key method in this field, providing a solid foundation for frontier exploration and technical breakthroughs. However, due to the limitations of time step size and low computational efficiency of the traditional FDTD method, it cannot efficiently and accurately simulate and analyze fine structures. In view of these shortcomings, experts have made improvements and proposed a hybrid implicit-explicit finite-difference time-domain (HIE-FDTD) method. This method reduces the number of iterations within the calculation domain, thereby improving overall computational efficiency. At the same time, by introducing an implicit method, the HIE-FDTD method can use a larger time step size without strictly following the time step size restrictions, thereby improving the stability of the time step size. However, the method currently cannot be effectively applied to the far-field radiation problem of microwave devices with multi-scale fine structures, and a grid partitioning method suitable for the HIE-FDTD method and a high-efficiency and stable absorbing boundary are urgently needed. SUMMARY

[0005] To overcome the defects of the prior art, the purpose of the present application is to provide a high-efficiency hybrid grid and boundary electromagnetic adaptation method for multi-scale fine structures, and a method based on the hybrid implicit-explicit finite-difference time-domain method combined with non-uniform grid technology and convolutional perfectly matched layer in a Cartesian rectangular coordinate system. This method can effectively reduce the reflection of electromagnetic waves at the boundary by combining non-uniform grid technology and convolutional perfectly matched layer. At the same time, this method can more accurately capture the subtle changes of electromagnetic fields in key parts and better handle numerical stability problems under high absorption conditions, reducing numerical oscillation and error.

[0006] The technical solution adopted by the present application to solve the technical problem is,

[0007] In a first aspect, the present application provides a hybrid electromagnetic simulation method suitable for multi-scale fine structure antennas, wherein the multi-scale fine structure refers to a multi-size fine structure in only one spatial direction. The method includes the following steps:

[0008] Step S1, create a multi-scale fine structure antenna model that needs to be simulated, and determine the range of its size in the calculation space;

[0009] Step S2: construct a convolutional perfectly matched layer suitable for the hybrid implicit-explicit finite-difference time-domain method, determine the entire computational space range including the convolutional perfectly matched layer, set a non-uniform grid for the multi-scale fine structure antenna model to be simulated, and determine the fine area and the non-uniform area from fine to coarse;

[0010] The fine area adopts a high-resolution fine grid, and the coarse area adopts a low-resolution coarse grid;

[0011] Step S3, constructing a hybrid algorithm: introducing a convolutional perfectly matched layer absorbing boundary condition into the hybrid implicit-explicit finite-difference time-domain method to obtain the implicit equation part; then combining the implicit equation part with the non-uniform grid, redefining the difference operator according to the grid distribution, and adapting the difference operator to the non-uniform step size;

[0012] Step S4: adding an excitation source in the fine structure direction, and obtaining the convolution perfectly matched layer absorption term, magnetic field value, and electric field value at the next moment based on the hybrid algorithm constructed in step S3;

[0013] Step S5: update the excitation source in the fine structure direction and update the time step t;

[0014] Assume that the range of the time step t is 1 to T, and the time step t increases by 1 each iteration; determine whether the time step t reaches T. If not, the time step t increases by 1, and returns to step S4 to continue the iteration; if it reaches T (that is, when t = T), the iteration ends, and the magnetic field value and electric field value obtained in step S4 for each iteration are recorded.

[0015] Preferably, the multi-scale fine structure is a dual-frequency microstrip patch antenna with a multi-scale fine structure.

[0016] In a second aspect, the present invention provides an electromagnetic simulation system for implementing the above method, comprising the following modules:

[0017] Model creation module, used to create multi-scale fine structure antenna models that need to be simulated;

[0018] A hybrid module is used to combine the hybrid implicit-explicit finite-difference time-domain method, convolutional perfectly matched layers, and non-uniform grids to build a hybrid algorithm;

[0019] The simulation module is used to simulate multi-scale fine structure antenna models using a hybrid algorithm.

[0020] In a third aspect, the present invention provides a computer-readable storage medium having a computer program stored thereon, which, when executed in a computer, causes the computer to execute the above method.

[0021] In a fourth aspect, the present invention provides a computing device comprising a memory and a processor, wherein the memory stores executable code, and the processor implements the above method when executing the executable code.

[0022] Compared with the prior art, the present invention has the following advantages:

[0023] This paper introduces an efficient combination of a hybrid implicit-explicit finite-difference time-domain method, non-uniform grid technology, and convolutional perfectly matched layers. For far-field simulations with multi-scale fine structures, a finer grid is used in areas with drastic electromagnetic field changes or complex structures, while a coarser grid is used in areas with more gradual changes. This strategy can significantly reduce the number of grid points required for calculation, simplifying the implementation process, thereby reducing the overall computational effort and improving computational efficiency. Furthermore, the non-uniform grid allows for more accurate simulation of important detailed areas in electromagnetic simulations. For example, in key locations such as slits, tips, and antenna feed points in microwave circuits, a higher-resolution grid can be used to accurately capture subtle changes in the electromagnetic field. BRIEF DESCRIPTION OF THE DRAWINGS

[0024] Figure 1 It is an algorithm flow chart of the implementation method of the present invention.

[0025] Figure 2 Schematic diagram of the geometric model of the antenna structure of an embodiment of the implementation method of the present invention; wherein (a) is the front side of the antenna in embodiment 1 of the present invention, and (b) is the back side of the antenna.

[0026] Figure 3 1 is an S-parameter diagram of the antenna in Example 1 of the present invention compared with a high-frequency simulator under different CFLN (Courant-Friedrich-Levy number, stability constant) conditions.

[0027] Figure 4 1 is an S-parameter diagram of the antenna in Example 1 of the present invention compared with a high-frequency simulator under different CFLN conditions.

[0028] Figure 5 : These are the gain patterns of the antenna in Example 1 of the present invention under different CFLN conditions; (a) is a comparison curve diagram at 2.4 GHz at different azimuth angles phi; (b) is a comparison curve diagram at 3.7 GHz at different azimuth angles phi; (c) is a comparison curve diagram at 2.4 GHz at different azimuth angles theta; and (d) is a comparison curve diagram at 3.7 GHz at different azimuth angles theta. DETAILED DESCRIPTION

[0029] The present invention will be further described below with reference to the embodiments and accompanying drawings.

[0030] The present invention is applied to the hybrid implicit-explicit finite-difference time-domain method in computational electromagnetics. The recursive formula involved can be obtained based on the hybrid implicit-explicit finite-difference time-domain method. The specific implementation method is described using the electromagnetic simulation problem of an antenna as an example. The actual application scope is not limited to this, and the present invention is also applicable to fields such as wireless communications and integrated circuits.

[0031] The present invention provides a method for implementing a hybrid non-uniform grid technology and a convolutional perfectly matched layer, specifically a method based on a hybrid implicit-explicit finite-difference time-domain method combined with a non-uniform grid technology and a convolutional perfectly matched layer in a Cartesian rectangular coordinate system. Figure 1 As shown, the specific steps of this method are:

[0032] (1) Create a multi-scale fine structure model that needs to be simulated and determine the range of its size in the computational space.

[0033] First, a multi-scale fine structure simulation model is created, and then the size range of the antenna is determined based on the model. The size range of the antenna is defined as (X min ,Y min ,Z min ) to (X max ,Y max ,Z max ). Among them, X min and X max Represents the minimum and maximum positions on the x-axis, Y min and Y max Represents the minimum and maximum positions on the y-axis, Z min and Z max Represents the minimum and maximum positions on the z-axis respectively.

[0034] (2) Construct a convolutional perfectly matched layer suitable for the hybrid implicit-explicit finite-difference time-domain method and determine the entire computational space range including the convolutional perfectly matched layer. For the multi-scale fine structure antenna model that needs to be simulated, set a non-uniform grid and determine the fine area and the non-uniform area from fine to coarse.

[0035] Without loss of generality, the three-dimensional Maxwell equations inside the convolution perfectly matched layer in a lossy medium are expressed as:

[0036]

[0037] Among them, j represents an imaginary number, ω represents the angular velocity, ε η (η=x,y,z) represents the dielectric constant in the η direction, represents the spatial difference operator of the first-order derivative along the η direction, μ η Indicates the magnetic permeability in the η direction, E ηdenotes the electric field quantity in the η direction, H η denotes the magnetic field quantity in the η direction, and is the conductivity in the truncated medium, S eη and S mη denotes the stretching coordinate factor, see equation (7) for details:

[0038]

[0039] where ε0denotes the vacuum permittivity, σ eη , σ mη , κ η , α eη and α mη are non-negative real numbers, and are given by:

[0040]

[0041] where σ eη and σ mη denote the conductivity, σ ηmax denotes the maximum value of σ η , ρ denotes the distance of the electromagnetic field quantity to the interface between the computation domain and the absorbing layer, d denotes the thickness of the absorbing layer, m denotes the order of the polynomial, Δη denotes the spatial step in the η direction, κ ηmax denotes the maximum value of κ η , α min and α max denote the minimum and maximum values of α η ;

[0042] The size of the computation domain is defined as from (X min -d, Y min -d, Z min -d) to (X max +d, Y max +d, Z max +d) according to the antenna size range and the thickness d of the absorbing layer determined by the model. Wherein, X min -d and X max +d denote the minimum and maximum positions of the computation domain in the x-axis, Y min -d and Y max +d denote the minimum and maximum positions of the computation domain in the y-axis, and Z min -d and Z max +d denote the minimum and maximum positions of the computation domain in the z-axis.

[0043] The non-uniform grid technology is divided into fine areas and non-uniform areas. The fine area uses a fine grid, and the non-uniform area uses a non-uniform grid. First, set the direction parameter dir = 'η' of the non-uniform grid technology. Then set the fine area size and the fine grid size of the fine area. The fine area size is rΔs, where Δs represents the fine grid size of the fine area and r represents the number of fine grids. Finally, determine the grid size of the non-uniform area. The grid size of the non-uniform area is determined by ΔM and can be expressed as:

[0044] ΔM=R M Δs (11)

[0045] Where R represents the rate of change between subsequent half-grids, and M represents the index of the grid in the non-uniform region. The grid size of the coarse region adjacent to the non-uniform region is expressed as:

[0046]

[0047] Among them, N nu represents the number of grids in the non-uniform region. Therefore, the total length of the non-uniform region plus one grid at each end of the uniform region can be expressed as:

[0048]

[0049] R, N nu It can be obtained from formula (13):

[0050]

[0051] (3) The hybrid implicit-explicit finite-difference time-domain method is effectively combined with the convolutional perfectly matched layer to obtain the implicit equation part of the hybrid implicit-explicit finite-difference time-domain method combined with the convolutional perfectly matched layer.

[0052] Without loss of generality, the fine structure is defined as the z direction. According to the hybrid implicit-explicit FDTD method, the three-dimensional hybrid implicit-explicit FDTD method with convolutional perfectly matched layer is expressed as:

[0053]

[0054]

[0055] Where n, n+1 / 2 and n+1 represent time indices, Δt is the time step, is an auxiliary function; a1=Δt / ε, b1=Δt / μ, ε represents the dielectric constant, μ represents the magnetic permeability; Θ at time T1 η , Θ=E, H, T1=n-1 / 2,n,n+1 / 2,n+1; and Respectively represent the electric field E in the η2 direction at time T2 η1 and magnetic field H η1 The corresponding absorption term, T2=n,n+1 / 2,

[0056] Substitute equation (20) into equation (17) to eliminate H y n+1 We can get:

[0057]

[0058] Substitute equation (19) into equation (18) to eliminate H x n+1 We can get:

[0059]

[0060] The absorption term It can be expressed as:

[0061]

[0062]

[0063] where c eη 、c mη d eη and d mη are all non-negative real numbers and can be expressed as:

[0064]

[0065] (4) The equations after the hybrid implicit-explicit time-domain finite difference method is effectively combined with the convolutional perfectly matched layer, and then combined with the non-uniform grid technology.

[0066] The spatial step lengths in the three directions of the non-uniform grid are defined as Δx i ,Δy j ,Δz k Δx i represents the non-uniform grid size in the x-direction, Δy j represents the non-uniform grid size in the y direction, Δz k represents the non-uniform grid size in the z direction. η Re-expressed as Δη is replaced by the non-uniform grid Δx i ,Δy j ,Δz k :

[0067]

[0068] (5) Add an excitation source in the direction of the fine structure, and obtain the convolution perfectly matched layer absorption term, magnetic field value, and electric field value at the next moment based on an algorithm combining a hybrid implicit-explicit finite-difference time-domain method with a convolution perfectly matched layer and a non-uniform grid technology;

[0069] Add an excitation source J in the z direction of the fine structure, that is, add the required excitation source to equation (37), which is expressed as:

[0070]

[0071] According to the algorithm combining the hybrid implicit-explicit finite-difference time-domain method with the convolution perfectly matched layer and non-uniform grid technology, namely, Equations (38) to (43), the convolution perfectly matched layer absorption term, magnetic field value, and electric field value at the next moment are obtained through iteration.

[0072] (6) Update the excitation source in the fine structure direction and update the time step t;

[0073] The time step t will iterate in a loop, with the range of t being between 1 and T. Each time the loop iterates, t increases by 1, and a check is performed to see if T has been reached. If the time step t has not reached T, the loop returns to step S5. When t equals T, the number of iterations has been reached, and the loop ends. The magnetic field and electric field values ​​obtained in step S5 are recorded for each loop.

[0074] Example 1

[0075] This embodiment is an example of electromagnetic simulation of an antenna, and all simulation results are derived from the implementation method of the present invention.

[0076] See Figure 2 , is a schematic diagram of the geometric model of the antenna structure used in this embodiment, the thickness of the dielectric substrate is 1.6 mm, and the remaining geometric dimension parameters are detailed in Table 1:

[0077] Table 1 Geometric dimensions of the antenna in Example 1

[0078] Parameter W [CD AT W1] <![CDATA[W2]]> <![CDATA[W3]]> L <L1> <L2> ​ ​ [L5] Dimensions (mm) 38.00 16.15 4.15 2.50 19.00 4.00 9.50 0.50 5.50 4.00

[0079] The implementation process of the embodiment is the same as that of the detailed implementation method; the Gaussian excitation source J is set at the z-center position of the side surface in the fine structure direction in the simulation space, and the spatial step size of the fine grid area is Δx = 0.35mm, Δy = 0.50mm, and Δz = 0.04mm. The spatial step size of the coarse grid area is Δx = Δy = 0.50mm, and Δz = 0.04mm. The spatial step size of the fine grid in the non-uniform grid area is Δx = 0.35mm, Δy = 0.50mm, and Δz = 0.04mm, and the coarse grid is Δx = 0.50mm. The grid resolution is 20, the CFLN is 1, 3, and 5 respectively, and the convolution perfectly matched layer thickness is 8 layers in the x-, y-, and z-directions.

[0080] The embodiment 1 was measured in a computer. It should be noted that all measurement results of the method of the present application are measured in the same measurement environment. The computer CPU uses i5-14600K, and the running memory is 32G.

[0081] The results are shown in Figure 3 , Figure 4 . Figure 3 , Figure 4 The ratio of the HIE-FDTD method involved in the method of the present application to the time step of the traditional FDTD method is represented by CFLN, and CFLN takes values of 1, 3, and 5, respectively. Among them, Figure 3 and Figure 4 involve the combination method of FDTD method and CPML (i.e. FDTD-CPML method), the combination method of HIE-FDTD method using fine grid simulation and CPML (i.e. FG-HIE-CPML method, referred to as FG in the figure), the combination method of HIE-FDTD method and non-uniform grid technology and CPML (i.e. NG-HIE-CPML method, referred to as NG in the figure), and the combination method of HIE-FDTD method using coarse grid simulation and CPML (i.e. CG-HIE-CPML method, referred to as CG in the figure).

[0082] Specifically, Figure 3 The S parameters and simulation results obtained by simulation calculation of the method of the present application and the FG-HIE-CPML method are shown in Table 1. Even if CFLN increases to 5, the simulation results of the method of the present application are still very consistent with the results of the High Frequency Structural Simulator (HFSS) and the FDTD-CPML method, effectively verifying the high calculation precision thereof. Among them, the method of the present application is the combination method of HIE-FDTD method, non-uniform grid technology (NG), and CPML (i.e. NG-HIE-CPML method).

[0083] Specifically, Figure 4 The S parameters and simulation results obtained by simulation calculation of the method of the present application and the CG-HIE-CPML method are shown in Table 2. By comparing the method of the present application with other methods, the simulation results of the method of the present application are very consistent with the results of the FDTD-CPML method, again verifying the high calculation precision of the HIE-CPML method using non-uniform grid technology.

[0084] Figure 5The antenna's radiation pattern simulation results at 2.4 GHz and 3.7 GHz are presented, showing the gain distribution in the xoy and xoz planes. The CFLN values ​​are 1, 3, and 5, respectively. Dphi in the figure represents the change in the antenna's directivity at different azimuth angles, phi, and Dtheta represents the change in the antenna's directivity at different azimuth angles, theta. Phi and theta are parameters used to describe the antenna's radiation directivity. It can be observed that although the simulation results of the NG-HIE-CPML method exhibit slight deviations with increasing CFLN, they maintain a high degree of consistency overall, with minimal impact on the overall simulation and evaluation of antenna performance, effectively verifying the high stability of the proposed method. When the CFLN is increased to 5, the results remain very close to those of the FDTD-CPML method, demonstrating the accuracy of the NG-HIE-CPML method and validating the effective combination of non-uniform grid technology, CPML, and the HIE-FDTD method.

[0085] The comparison of the calculation results of different algorithms is shown in Table 2. As CFLN increases, it can be seen that the time required for NG-HIE-CPML is shortened. When CFLN rises to 5, the calculation time of the proposed method is 46.66% faster than that of the traditional FDTD-CPML method, demonstrating its high computational efficiency.

[0086] Table 2 Calculation results of different methods in Example 1

[0087]

[0088] In summary, the method of the present invention is verified to be accurate and effective in processing the simulation of multi-scale fine structure models by simulating a dual-band microstrip patch antenna and comparing the simulation results of S parameters and radiation patterns of the method of the present invention with those of HFSS software. Compared with the traditional FDTD-CPML method, the calculation time of the method of the present invention is only 53.34% of that of the traditional FDTD-CPML method, which proves its high computational efficiency.

[0089] While the present invention has been disclosed above with reference to preferred embodiments, this is not intended to limit the present invention. Persons skilled in the art will readily appreciate that various modifications and variations can be made without departing from the spirit and scope of the present invention. Therefore, the scope of protection of the present invention shall be determined by the claims.

Claims

1. A hybrid electromagnetic simulation method suitable for multi-scale fine structure antennas, characterized in that: The method comprises the following steps: Step S1: Create a multi-scale fine structure antenna model to be simulated and determine the range of its size in the calculation space; Step S2: Construct a convolutional perfectly matched layer suitable for the hybrid implicit-explicit finite-difference time-domain method, determine the entire computational space range including the convolutional perfectly matched layer, set a non-uniform grid for the multi-scale fine structure antenna model to be simulated, and determine the fine area and the non-uniform area from fine to coarse. The details are as follows: First, set the direction parameter dir = 'η' of the non-uniform grid. Then, set the fine region size and the fine grid size of the fine region. The fine region size is nΔs, where Δs represents the fine grid size of the fine region and n represents the number of fine grids. Finally, determine the non-uniform region grid size. The non-uniform region grid size is determined by ΔM and is expressed as: ΔM=R M Δs (11) Where R represents the rate of change between subsequent half-grids, and M represents the index of the grid in the non-uniform region; The mesh size of the coarse area adjacent to the non-uniform area is expressed as: Among them, N nu Indicates the number of grids in the non-uniform area; Therefore, the total length of the non-uniform region plus one grid at each end of the uniform region is expressed as: From formula (13), we can get R and N nu : Step S3, constructing a hybrid algorithm: introducing a convolutional perfectly matched layer absorbing boundary condition into the hybrid implicit-explicit finite-difference time-domain method to obtain the implicit equation part; then combining the implicit equation part with the non-uniform grid, redefining the difference operator according to the grid distribution, and adapting the difference operator to the non-uniform step size; The spatial step lengths in the three directions of the non-uniform grid are defined as Δx i ,Δy j ,Δz k , where Δx i represents the non-uniform grid size in the x-direction, Δy j represents the non-uniform grid size in the y direction, Δz k Indicates the non-uniform grid size in the z direction; replace the spatial difference operator δ in the update formula of the electric field at half time step n+1 / 2, the update formula of the magnetic field at half time step n+1 / 2, the update formula of the electric field at full time step n, and the update formula of the magnetic field at full time step n η Re-expressed as Δη is replaced by the non-uniform grid Δx i ,Δy j ,Δz k : Step S4: adding an excitation source in the fine structure direction, and obtaining the convolution perfectly matched layer absorption term, magnetic field value, and electric field value at the next moment based on the hybrid algorithm constructed in step S3; Step S5, update the excitation source in the fine structure direction and update the time step t; assume that the range of the time step t is 1 to T, and the time step t increases by 1 each iteration; determine whether the time step t reaches T, if not, increase the time step t by 1, and return to step S4 to continue iteration; if reached, the iteration ends, and the magnetic field value and electric field value obtained in step S4 for each iteration are recorded.

2. The method according to claim 1, characterized in that The size range of the multi-scale fine structure antenna model in step S1 is defined as (X min ,Y min ,Z min ) to (X max ,Y max ,Z max ); where X min and X max Represents the minimum and maximum positions on the x-axis, Y min and Y max Represents the minimum and maximum positions on the y-axis, Z min and Z max Represents the minimum and maximum positions on the z-axis respectively.

3. The method according to claim 1, characterized in that In step S2, the three-dimensional Maxwell equations inside the convolution perfectly matched layer in the lossy medium are expressed as: Where η = x, y, z; j represents an imaginary number, ω represents the angular velocity, ε η represents the dielectric constant in the η direction, represents the spatial difference operator of the first-order derivative along the η direction, μ η Indicates the magnetic permeability in the η direction, E η represents the electric field in the η direction, H η represents the magnetic field in the η direction, and To cut off the conductivity in the medium, S eη and S mη Represents the stretching coordinate factor, see formula (7) for details: Where ε0 represents the dielectric constant of vacuum, σ eη ,σ mη , κ η , α eη and α mη are all non-negative real numbers, expressed as: Among them, σ eη and σ mη represents the conductivity, σ ηmax Represents σ η The maximum value of ρ represents the distance from the electromagnetic field to the interface between the calculation area and the absorption layer, d represents the thickness of the absorption layer, m represents the order of the polynomial, Δη represents the spatial step in the η direction, and κ ηmax Represents κ η The maximum value of α min and α max Represents α η The minimum and maximum values ​​of According to the antenna size range and the absorption layer thickness d determined by the model, the size range of the calculation space is defined as (X min -d,Y min -d,Z min -d) to (X max +d,Y max +d,Z max +d).

4. The method according to claim 1, characterized in that In step S3, the implicit equation part is obtained by the following method: The fine structure direction is defined as the z direction. According to the hybrid implicit-explicit FDTD method, the three-dimensional hybrid implicit-explicit FDTD method with convolutional perfectly matched layer is expressed as: Where n, n+1 / 2 and n+1 represent time indices, Δt is the time step, is an auxiliary function; a1=Δt / ε, b1=Δt / μ, ε represents the dielectric constant, μ represents the magnetic permeability; Θ at time T1 η , Θ=E, H, T1=n-1 / 2,n,n+1 / 2,n+1; and Respectively represent the electric field E in the η2 direction at time T2 η1 and magnetic field H η1 The corresponding absorption term, T2=n,n+1 / 2, Substitute equation (20) into equation (17) to eliminate H y n+1 We can get: Substitute equation (19) into equation (18) to eliminate H x n+1 We can get: The absorption term It can be expressed as: where c eη 、c mη d eη and d mη are all non-negative real numbers and can be expressed as:

5. The method according to claim 1, characterized in that: The specific process of step S4 is: Adding the required excitation source J to equation (37) yields: According to equations (38) to (43), the convolution perfectly matched layer absorption term, magnetic field value, and electric field value at the next moment are obtained through iteration.

6. An electromagnetic simulation system for implementing the method according to any one of claims 1 to 5, characterized in that: Includes the following modules: Model creation module, used to create multi-scale fine structure antenna models that need to be simulated; A hybrid module is used to combine the hybrid implicit-explicit finite-difference time-domain method, convolutional perfectly matched layers, and non-uniform grids to build a hybrid algorithm; The simulation module is used to simulate multi-scale fine structure antenna models using a hybrid algorithm.

7. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed in a computer, the computer is caused to execute the method according to any one of claims 1 to 5.

8. A computing device comprising a memory and a processor, characterized in that: The memory stores executable code, and when the processor executes the executable code, the method according to any one of claims 1 to 5 is implemented.

Images