Design method of multilayer wave-absorbing structure based on equivalent circuit and genetic optimization algorithm

Abstract

This application provides a design method for multilayer absorbing structures based on equivalent circuits and genetic optimization algorithms, including: Step 1, initializing EC-GA hyperparameters and the physical parameter range of the multilayer absorbing structure [Var min Var max ], and generate a parameter group composed of random binary codes; Step 2, according to [Var min Var max Decode the parameter group; Step 3: Calculate the reflection coefficient S of the absorbing structure based on equivalent circuit and transmission line theory. 11 Step 1: The loss function value (Loss) and individual fitness are calculated. Step 2: The minimum loss value in the current round is compared with the minimum value in the previous round, and the minimum loss value is retained as min_Loss. Step 3: A roulette wheel selection method is used to select individuals to form a new population based on their fitness values. Step 4: Crossover and mutation operations are performed on the selected population. Step 5: Steps 6-7 are repeated until the maximum number of iterations is reached. Theoretically, this application can directly obtain the physical parameters of the multilayer absorbing structure from the target reflection coefficient, realizing reverse design and improving optimization efficiency.

Description

Technical Field

[0001] This application relates to the field of metamaterial absorbing structure technology, and more specifically, to a design method for multilayer absorbing structures based on equivalent circuit and genetic algorithm (EC-GA). Background Technology

[0002] Broadband absorbing structures have broad application prospects in radar stealth due to their ability to dissipate electromagnetic wave energy over a wide frequency range. However, the influence of absorption characteristics on practical design often involves many factors, making the design and optimization of broadband absorbing structures very complex. Therefore, it is necessary to develop a simple and efficient optimization algorithm to assist in the design of broadband absorbing structures.

[0003] In the design of broadband absorbing structures, the most common method is to stack or arrange multiple layers of lossy surfaces based on impedance films or lumped resistive elements in a regular pattern. Impedance films, due to their excellent ohmic loss characteristics and the ability to be printed into various shapes to meet different electromagnetic requirements, have been widely used in the design of broadband absorbing structures. Traditional absorbing structure design relies on the experience of technicians, usually requiring a significant amount of time to adjust various physical parameters. Especially in the field of ultra-wideband absorbing, as the absorption frequency range widens, the number of layers in the absorbing structure increases, and the parameters that need to be designed also increase, which undoubtedly increases the complexity of the technicians' work. With the development of artificial intelligence technology, various optimization algorithms are widely used in optimal solution problems. Among them, genetic algorithms, by mimicking the process of species evolution, can efficiently and stably handle multi-parameter optimization problems. However, to apply genetic algorithms in the design process of absorbing structures, a complete theoretical calculation system for absorbing is required, which necessitates establishing a closed-form relationship between the lumped parameters of the equivalent circuit and the structural geometric parameters.

[0004] Previous studies have shown that the lumped resistance is related to the surface impedance and area of ​​the impedance film, while the inductance and capacitance are related to the geometry and size of the impedance film, as well as the effective dielectric constant of the surrounding medium. The dielectric environment affecting the effective dielectric constant mainly includes the type, quantity, thickness, and dielectric constant of the surrounding medium. However, many studies have neglected the influence of the surrounding dielectric environment on the effective dielectric constant, leading to significant discrepancies between theoretical calculations and simulation results. Summary of the Invention

[0005] In view of this, this application provides a design method for multilayer absorbing structures based on equivalent circuits and genetic optimization algorithms. This method can quickly and efficiently optimize the optimal combination of physical parameters of the multilayer absorbing structure according to the target reflection coefficient.

[0006] To achieve the above objectives, the technical solution adopted in this application is as follows:

[0007] A multilayer absorbing structure design method based on equivalent circuits and genetic optimization algorithms includes:

[0008] Step 1: Initialize the hyperparameters of the genetic algorithm (GA) and the physical parameters of the absorbing structure, and generate an initial encoding parameter array consisting of random binary codes of specification (paranum, popsize, DNAsize). Here, paranum is the number of optimization objects, popsize is the population size, and DNAsize is the length of the DNA sequence used for encoding. The hyperparameters of the genetic algorithm include crossover probability, mutation probability, gene sequence length, number of iterations, and loss function weights. The physical parameters of the absorbing structure include the relative permittivity ε of the intermediate dielectric layer. r The relative permittivity ε of the substrate dielectric layer s The number of layers m and the range of the optimization objective parameters [Var] max Var min ];

[0009] Step 2: Based on the parameter range [Var] max Var min The parameters are decoded using equation (1):

[0010]

[0011] ennum represents the binary encoded parameters before decoding, and denum represents the parameters after decoding.

[0012] Step 3, the equivalent circuit of the multi-layer absorbing structure is as follows: Figure 2 As shown, the square ring resistive film is equivalent to a series circuit of resistor, inductor, and capacitor. The dielectric layer is represented by its characteristic impedance, and the metal substrate is equivalent to a short circuit. The reflection coefficient S of the absorbing structure is calculated based on the equivalent circuit and transmission line theory. 11 Loss function value and individual fitness;

[0013] Step 4: Compare the minimum loss value in the current round of the population with the minimum value in the previous round, and retain the minimum loss value as min_Loss; for the first round of iteration, the minimum loss value of the population is taken as min_Loss.

[0014] Step 5: Use the roulette wheel selection method to select individuals to form a new group based on their fitness values. The higher the fitness of an individual, the greater the probability of it being selected.

[0015] Step 6: Perform crossover and mutation operations on the selected population. Crossover refers to the crossover recombination of the parent DNA sequence under the control of crossover probability; mutation refers to the inversion of the binary code of certain gene positions in the parent DNA sequence under the control of mutation probability, that is, 0 becomes 1 or 1 becomes 0, thereby forming a new offspring population.

[0016] Step 7: Repeat steps 2-6 until the maximum number of iterations is reached;

[0017] Step 8: Output the optimal parameter combination X_best after decoding and its corresponding reflection coefficient S. 11 And the loss function value min_Loss; where X_best refers to the target optimization parameters, including the period p of the absorbing element and the thickness h of the intermediate dielectric layer. r,1 ,h r,2 ...h r,m The thickness h of the substrate dielectric layer s,1 ,h s,2 ...h s,m The sheet resistances R1, R2...R of the ITO impedance film m The side lengths of the square ring are d1, d2...d m The widths of the square rings are w1, w2...w m , m represents the number of layers in the absorbing structure.

[0018] Furthermore, in step 3, the reflection coefficient S of the absorbing structure is calculated based on equivalent circuit and transmission line theory. 11 The specific processes for calculating the loss function value (Loss) and the individual fitness (Fitness) are as follows:

[0019] Step 3.1: Calculate the characteristic impedance Z of the dielectric surrounding the nth square ring ITO impedance film. g,n and effective dielectric constant ε eff,n n = 1, 2, ..., m:

[0020]

[0021] In the formula ε av,n The average dielectric constant of the surrounding medium is:

[0022]

[0023] In the formula, when the impedance film is a square ring, the coefficient α = 18, and ε rh,n The expression is as follows:

[0024]

[0025] Among them, h s,n and h r,nThese represent the thicknesses of the nth substrate dielectric and the intermediate dielectric, respectively.

[0026] The surrounding medium of the final ITO metal film is the substrate medium and free space air, and its average dielectric constant is calculated as follows:

[0027]

[0028] Step 3.2: For each frequency point, calculate the equivalent lumped resistance R of the nth layer square ring ITO impedance film based on the physical parameters of the nth layer after decoding. n Equivalent capacitance C n and equivalent inductance L n n = 1, 2, ..., m:

[0029]

[0030]

[0031] In the formula,

[0032]

[0033] In equations (7)-(12), p represents the unit period of the absorbing structure, and d n w represents the side length of the square ring of the ITO impedance thin film. n Indicates the width of the square ring; ε represents angular frequency. eff,n Z represents the effective dielectric constant of the surrounding medium, which affects the equivalent capacitance. g,n The characteristic impedance of the medium surrounding the square ring of the ITO impedance thin film is represented by F(p,x,λ) and G(p,x,λ), which are functions related to the geometric parameters of the impedance thin film and the wavelength λ, and α and β are two intermediate variables.

[0034] Step 3.3: The input impedance Z of the last layer of the equivalent circuit of the absorbing structure. in,m The reflection coefficient Γ is obtained from the free-space characteristic impedance Z0:

[0035]

[0036] Step 3.4: Calculate the loss value, Loss. The weighted mean square error between the reflection coefficient obtained from the equivalent circuit and the target reflection coefficient is used as the value of the loss function. The expression for calculating the weighted mean square error is as follows:

[0037]

[0038] R i (f j ) and G i (f j) represent the reflection coefficient and the target reflection coefficient calculated based on transmission line theory, respectively, when R i (f j )≤G i (f j When ), the penalty function E i (f j If ) = 0, then the penalty function is the absolute value of the difference between the two. i represents the weighting order, and j represents the frequency order within the i-th weighting region.

[0039] Step 3.5: Calculate the individual fitness, which is an exponential function of the loss function, and its expression is as follows:

[0040]

[0041] Furthermore, step 3.3 calculates the input impedance Z of the last layer of the equivalent circuit of the absorbing structure. in,m Specifically, it includes:

[0042] Step 3.3.1: Calculate the characteristic impedance and propagation constant of the intermediate dielectric layer and the substrate dielectric layer for each frequency point:

[0043]

[0044] Where, ε s,n and ε r,n Let be the dielectric constants of the nth substrate dielectric and the intermediate dielectric, respectively. Next, calculate the equivalent impedance of the nth ITO impedance film:

[0045] Z ec,n =R n +jωL n +1 / (jωC n (20)

[0046] ω=2πf (21)

[0047] Step 3.3.2, Calculate Z' n Its characteristic impedance Z with the intermediate medium r,n Propagation constant β r,n Thickness h r,n and the input impedance Z of the previous layer in,n-1 Relatedly, since the metal base plate is equivalent to a short-circuit impedance of 0, the input impedance Z of the layer preceding the first layer is... in,0 =0:

[0048]

[0049] Step 3.3.3: Calculate Z n Its characteristic impedance Z with respect to the substrate dielectric s,n Propagation constant β s,nThickness h s,n and Z' n related:

[0050]

[0051] Step 3.3.4: Calculate the input impedance Z of the nth layer. in,n It equals Z n and Z ec,n in parallel:

[0052] Z in,n =Z n ||Z ec,n (twenty four)

[0053] Step 3.3.5: Repeat steps 3.3.2-3.3.4 to calculate the input impedance Z of the last layer. in,m .

[0054] Furthermore, step 5 specifically includes:

[0055] Step 5.1: Calculate the probability that each individual will be inherited by the next generation, where N is the population size, and f(x) i ) represents the fitness of the i-th individual:

[0056]

[0057] Step 5.2: Calculate the cumulative probability q for each individual. i :

[0058]

[0059] Step 5.3: Generate a random number r in the interval [0, 1], when q i-1 ≤r≤q i If the time is right, then select the i-th individual;

[0060] Step 5.4: Repeat steps 5.1-5.3 N times, where N is equal to the population size popsize.

[0061] Furthermore, each layer of the absorbing structure is composed of multiple absorbing units with the same period, and each absorbing unit includes a metal base plate and n layers of absorbing assembly from bottom to top; the absorbing assembly includes a material dielectric layer, an air layer and a loss layer from bottom to top.

[0062] Furthermore, the loss layer is an ITO impedance film in the shape of a square ring.

[0063] Furthermore, the dielectric layer has a relative permeability μ = 1 and a relative permittivity ε ≤ 15.

[0064] The beneficial effects of this application are:

[0065] 1. In theory, this application can directly obtain the physical parameters of the multi-layer absorbing structure from the target reflection coefficient, realize reverse design, and improve optimization efficiency;

[0066] 2. The optimized object has a simple structure and is easy to manufacture. The optimized result has advantages such as ultra-wide bandwidth, low profile and small cycle size. Attached Figure Description

[0067] To more clearly illustrate the technical solutions of the embodiments of this application, the accompanying drawings used in the embodiments will be briefly introduced below. It should be understood that the following drawings only show some embodiments of this application and should not be regarded as a limitation of the scope. For those skilled in the art, other related drawings can be obtained based on these drawings without creative effort.

[0068] Figure 1 This is a flowchart of the design method for the multilayer absorbing structure of this application;

[0069] Figure 2 This is a schematic diagram of the multilayer absorbing structure and its equivalent circuit of this application;

[0070] Figure 3 This is a diagram of a multilayer absorbing structure according to an embodiment of this application;

[0071] Figure 4 This is a comparison chart of the simulation and theoretical calculation results of the reflection coefficient of the embodiments of this application;

[0072] Figure 5 This is a comparison chart of the simulation and theoretical calculation results of the absorption rate of the embodiments of this application;

[0073] Figure 6 This is a graph showing the reflection coefficient results of an embodiment of this application under the condition of oblique incidence of TE-polarized electromagnetic waves;

[0074] Figure 7 This is a graph showing the reflection coefficient results of an embodiment of this application under oblique incidence of TM polarized electromagnetic waves. Detailed Implementation

[0075] To make the objectives, technical solutions, and advantages of the embodiments of this application clearer, the technical solutions of the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are some embodiments of this application, but not all embodiments.

[0076] Genetic Algorithm (GA) was proposed by Holland. It is an optimization algorithm inspired by natural selection and genetic mechanisms in genetics. Its basic idea is to solve complex optimization problems by simulating biological and human evolution.

[0077] like Figure 2 and 3 As shown, the absorbing structure in this application consists of multiple absorbing units with the same period, each absorbing unit comprising a metal base plate and n layers of absorbing assembly from bottom to top. The absorbing assembly comprises a dielectric layer, an air layer, and a loss layer from bottom to top; where n = 1, 2, ..., m; the loss layer is a square ring-shaped ITO impedance film. In the equivalent circuit of this application, the square ring ITO impedance film is equivalent to a series circuit of resistor, capacitor, and inductor, the dielectric layer is equivalent to the characteristic impedance of a transmission line, and the metal base plate is equivalent to a short circuit.

[0078] like Figure 1 As shown, this application provides a multilayer absorbing structure design method based on equivalent circuit (EC) and genetic optimization algorithm (GA), including:

[0079] Step 1: Initialize the hyperparameters of the genetic algorithm and the physical parameters of the absorbing structure, and generate an initial encoding parameter array of size (paranum, popsize, DNAsize) consisting of random binary codes. Here, paranum is the number of optimization objects, popsize is the population size, and DNAsize is the length of the DNA sequence used for encoding. The genetic algorithm hyperparameters include crossover probability, mutation probability, gene sequence length, number of iterations, and loss function weights. The physical parameters of the absorbing structure include the relative permittivity ε of the intermediate dielectric layer. r The relative permittivity ε of the substrate dielectric layer s The number of layers m and the range of the optimization objective parameters [Var] max Var min The relationship between the number of physical parameters and the number of layers, which are the optimization targets, is paranum = 2 + 4m. The optimization target refers to the mask curve of the target's reflection coefficient.

[0080] Step 2: Based on the parameter range [Var] max Var min The parameter ennum is decoded into denum using equation (1):

[0081]

[0082] ennum represents the binary encoded parameters before decoding, and denum represents the parameters after decoding;

[0083] Step 3, the equivalent circuit of the multi-layer absorbing structure is as follows: Figure 2 As shown, each layer of the square ring resistive film is equivalent to a series circuit of resistor, inductor, and capacitor. The dielectric layer is represented by its characteristic impedance, and the metal substrate is equivalent to a short circuit. The reflection coefficient S of the absorbing structure is calculated based on the equivalent circuit and transmission line theory. 11 Loss function value and individual fitness;

[0084] Furthermore, in step 3, the reflection coefficient S of the absorbing structure is calculated based on equivalent circuit and transmission line theory. 11 The specific processes for calculating the loss function value (Loss) and the individual fitness (Fitness) are as follows:

[0085] Step 3.1: Calculate the characteristic impedance Z of the dielectric surrounding the nth square ring ITO impedance film. g,n and effective dielectric constant ε eff,n n = 1, 2, ..., m:

[0086]

[0087] In the formula ε av,n The average dielectric constant of the surrounding medium is:

[0088]

[0089] In the formula, when the impedance film is a square ring, the coefficient α = 18, and ε rh,n The expression is as follows:

[0090]

[0091] Among them, h s,n and h r,n These represent the thicknesses of the nth substrate dielectric and the intermediate dielectric, respectively.

[0092] The surrounding medium of the final ITO metal film is the substrate medium and free space air, and its average dielectric constant is calculated as follows:

[0093]

[0094] Step 3.2: For each frequency point, calculate the equivalent lumped resistance R of the nth layer ITO impedance film based on the physical parameters of the decoded nth layer. n Equivalent capacitance C n and equivalent inductance L n n = 1, 2, ..., m. When the ITO impedance film is a square ring, the lumped resistance R in the equivalent circuit is... n The surface sheet resistance R of the ITO impedance thin film can be determined. s,n The area S of the period and the area S of the square ringd,n Find:

[0095]

[0096] In the formula,

[0097]

[0098] In equations (7)-(12), p represents the unit period of the absorbing structure, and d n w represents the side length of the square ring of the ITO impedance thin film. n Indicates the width of the square ring; ε represents angular frequency. eff,n Z represents the effective dielectric constant of the surrounding medium, which affects the equivalent capacitance. g,n The characteristic impedance of the medium surrounding the square ring of the ITO impedance thin film is represented by F(p,x,λ) and G(p,x,λ), which are functions related to the geometric parameters of the impedance thin film and the wavelength λ, and α and β are two intermediate variables.

[0099] Step 3.3: The input impedance Z of the last layer of the equivalent circuit of the absorbing structure. in,m The reflection coefficient Γ is obtained from the free-space characteristic impedance Z0:

[0100]

[0101] Furthermore, step 3.3 calculates the input impedance Z of the last layer of the equivalent circuit. in,m Specifically, it includes:

[0102] Step 3.3.1: Calculate the characteristic impedance and propagation constant of the intermediate dielectric layer and the substrate dielectric layer for each frequency point:

[0103]

[0104] Where, ε s,n and ε r,n Let be the dielectric constants of the nth substrate dielectric and the intermediate dielectric, respectively. Next, calculate the equivalent impedance of the nth ITO impedance film:

[0105] Z ec,n =R n +jωL n +1 / (jωC n (17)

[0106] ω=2πf (18)

[0107] Step 3.3.2, Calculate Z′ n Its characteristic impedance Z with the intermediate medium r,n Propagation constant β r,n Thickness hr,n and the input impedance Z of the previous layer in,n-1 Relatedly, since the metal base plate is equivalent to a short-circuit impedance of 0, the input impedance Z of the layer preceding the first layer is... in,0 =0:

[0108]

[0109] Step 3.3.3: Calculate Z n Its characteristic impedance Z with respect to the substrate dielectric s,n Propagation constant β s,n Thickness h s,n and Z' n related:

[0110]

[0111] Step 3.3.4: Calculate the input impedance Z of the nth layer. in,n It equals Z n and Z ec,n in parallel:

[0112] Z in,n =Z n ||Z ec,n (twenty one)

[0113] Step 3.3.5: Repeat steps 3.3.2-3.3.4 to calculate the input impedance Z of the last layer. in,m .

[0114] Step 3.4: Calculate the loss value, Loss. The weighted mean square error between the reflection coefficient obtained from the equivalent circuit and the target reflection coefficient is used as the value of the loss function. The expression for calculating the weighted mean square error is as follows:

[0115]

[0116] R i (f j ) and G i (f j ) represent the reflection coefficient and the target reflection coefficient calculated based on transmission line theory, respectively, when R i (f j )≤G i (f j When ), the penalty function E i (f j If ) = 0, then the penalty function is the absolute value of the difference between the two. i represents the weighting order, and j represents the frequency order within the i-th weighting region.

[0117] Step 3.5: Calculate the individual fitness, which is an exponential function of the loss function, and its expression is as follows:

[0118]

[0119] Step 4: Compare the minimum loss value in the current round of the population with the minimum value in the previous round, and retain the minimum loss value as min_Loss; for the first round of iteration, the minimum loss value of the population is taken as min_Loss.

[0120] Step 5: Use the roulette wheel selection method to select individuals to form a new population based on their fitness values. The higher the fitness of an individual, the greater its probability of being selected. Specifically, this includes:

[0121] Step 5.1: Calculate the probability that each individual will be inherited by the next generation, where N is the population size, and f(x) i ) represents the fitness of the i-th individual:

[0122]

[0123] Step 5.2: Calculate the cumulative probability q for each individual. i :

[0124]

[0125] Step 5.3: Generate a random number r in the interval [0, 1], when q i-1 ≤r≤q i If the time is right, then select the i-th individual;

[0126] Step 5.4: Repeat steps 5.1-5.3 N times, where N is equal to the population size popsize.

[0127] Step 6: Perform crossover and mutation operations on the selected population. Crossover refers to the crossover recombination of the parent DNA sequence under the control of crossover probability; mutation refers to the inversion of the binary code of certain gene positions in the parent DNA sequence under the control of mutation probability, that is, 0 becomes 1 or 1 becomes 0, thereby forming a new offspring population.

[0128] Step 7: Repeat steps 2-6 until the maximum number of iterations is reached;

[0129] Step 8: Output the optimal parameter combination X_best after decoding and its corresponding reflection coefficient S. 11 And the loss function value min_Loss; where X_best refers to the target optimization parameters, including the period p of the absorbing element and the thickness h of the intermediate dielectric layer. r,1 ,h r,2 ...h r,m The thickness h of the substrate dielectric layer s,1 ,h s,2 ...hs,m The sheet resistances R1, R2...R of the ITO impedance film m The side lengths of the square ring are d1, d2...d m The widths of the square rings are w1, w2...w m , m represents the number of layers in the absorbing structure.

[0130] To demonstrate the feasibility of the above algorithm, an embodiment is provided below. It is implemented using Python in the PyCharm editor, and the physical parameters obtained by the EC-GA optimization algorithm are directly modeled and simulated in CST Studio Suite 2022 simulation software. The simulation results of the reflection coefficient of the multilayer absorbing structure are compared with the results calculated based on the equivalent circuit and transmission line theory. This proves that the proposed multilayer absorbing structure calculation method has high accuracy in calculating the reflection coefficient and is feasible in the optimization design of multilayer ultra-wideband absorbing structures.

[0131] Example:

[0132] The embodiment is a 6-layer ultrawideband absorbing structure based on an ITO impedance thin film square ring, such as... Figure 3 As shown, the absorbing structural units are arranged periodically, with a metal base plate, and the dielectric constant of the substrate dielectric is ε. s =1, the dielectric constant ε of the intermediate medium s =1.05, loss tangent tanδ = 0.001. The target reflection coefficient is set to be less than -10dB in the range of 0.1GHz-50GHz, with 1000 iterations, a crossover probability of 0.6, and a mutation probability of 0.026. The target parameter values ​​obtained through EC-GA optimization algorithm iteration are: period p = 27.2mm, and the substrate dielectric height is the same for each layer h. s =0.46mm; the thickness of the intermediate medium from bottom to top h r,1 =11.9mm, h r,2 = 9.58mm, h r,3 = 9.54mm, h r,4 =8.24mm, h r,5 =4.97mm, h r,6=2mm; The sheet resistance of the square ring ITO impedance film from bottom to top is R1 = 265Ω / sqr, R2 = 279Ω / sqr, R3 = 752Ω / sqr, R4 = 766Ω / sqr, R5 = 703Ω / sqr, R6 = 929Ω / sqr; The side lengths of the square ring from bottom to top are d1 = 27.08mm, d2 = 26.86mm, d3 = 26.18mm, d4 = 26.76mm, d5 = 25.97mm, d6 = 22.77mm; The widths of the square ring from bottom to top are w1 = 10mm, w2 = 6.97mm, w3 = 8.47mm, w4 = 8.59mm, w5 = 6.54mm, w6 = 8.25mm; The overall thickness is 48.98mm, and the relative profile height is 0.119λ. L .

[0133] The reflection coefficient results of the embodiment are shown in the figure below. Figure 4 As shown, the dotted line represents the reflection coefficient calculated based on the EC-GA algorithm, and the solid line represents the reflection coefficient curve obtained from modeling and simulation in CST based on the physical parameters given by the EC-GA algorithm. It can be seen that the calculated results and simulation results almost completely coincide, proving the theoretical accuracy of the design method in this application. Furthermore, both the calculated and simulated results achieve a reflection coefficient S0 within the frequency range of 0.729 GHz to 50 GHz (relative bandwidth 194.25%). 11 ≤-10dB (e.g.) Figure 4 As shown), 90% absorption rate (e.g. Figure 5 As shown in the figure, this demonstrates that the optimization design method proposed in this application can be well applied to the optimization design of ultra-wideband multilayer absorbing structures. Furthermore, the oblique incidence performance of this absorbing structure under TE and TM polarized electromagnetic wave incidence is shown in the figure. Figure 6 and Figure 7 As shown, it exhibits good absorption stability within the oblique incidence range of θ = 0°-50°.

[0134] The above are merely specific embodiments of this application, but the scope of protection of this application is not limited thereto. Any variations or substitutions that can be easily conceived by those skilled in the art within the scope of the technology disclosed in this application should be included within the scope of protection of this application. Therefore, the scope of protection of this application should be determined by the scope of the claims.

Claims

1. A multilayer absorbing structure design method based on equivalent circuit and genetic optimization algorithm, characterized in that, include: Step 1: Initialize the hyperparameters of the genetic algorithm and the physical parameters of the absorbing structure, and generate an initial encoding parameter array consisting of random binary codes of specifications paranum, popsize, and DNAsize, where paranum is the number of optimization objects, popsize is the population size, and DNAsize is the length of the DNA sequence used for encoding. The genetic algorithm hyperparameters include crossover probability, mutation probability, gene sequence length, number of iterations, and loss function weights. The physical parameters of the absorbing structure include the relative permittivity ε of the intermediate dielectric layer. r The relative permittivity ε of the substrate dielectric layer s The number of layers m and the range of the optimization objective parameters [Var] max Var min ]; Step 2: Based on the parameter range [Var] max Var min The parameters are decoded using equation (1): ennum represents the binary encoded parameters before decoding, and denum represents the parameters after decoding; Step 3: Equivalently represent the square ring resistive film as a series circuit of resistor, inductor, and capacitor. Represent the dielectric layer by its characteristic impedance. Equivalent represent the metal substrate as a short circuit. Calculate the reflection coefficient S of the absorbing structure based on the equivalent circuit and transmission line theory. 11 Loss function value and individual fitness; Step 4: Compare the minimum loss value in the current round of the population with the minimum value in the previous round, and retain the minimum loss value as min_Loss; for the first round of iteration, the minimum loss value of the population is used as min_Loss; Step 5: Use the roulette wheel selection method to select individuals to form a new group based on their fitness values. The higher the fitness of an individual, the greater the probability of it being selected. Step 6: Perform crossover and mutation operations on the selected population. Crossover refers to the crossover recombination of the parent DNA sequence under the control of crossover probability; mutation refers to the inversion of the binary code of certain gene positions in the parent DNA sequence under the control of mutation probability, that is, 0 becomes 1 or 1 becomes 0, thereby forming a new offspring population. Step 7: Repeat steps 2-6 until the maximum number of iterations is reached; Step 8: Output the optimal parameter combination X_best after decoding and its corresponding reflection coefficient S. 11 And the loss function value min_Loss; where X_best refers to the target optimization parameters, including the period p of the absorbing structure and the thickness h of the intermediate dielectric layer. r,1 ,h r,2 ...h r,m The thickness h of the substrate dielectric layer s,1 ,h s,2 ...h s,m The sheet resistances R1, R2...R of the ITO impedance film m The side lengths of the square ring are d1, d2...d m The widths of the square rings are w1, w2...w m , m represents the number of layers in the absorbing structure.

2. The multilayer absorbing structure design method based on equivalent circuit and genetic optimization algorithm as described in claim 1, characterized in that, In step 3, the reflection coefficient S of the absorbing structure is calculated based on equivalent circuit and transmission line theory. 11 The specific processes for calculating the loss function value (Loss) and the individual fitness (Fitness) are as follows: Step 3.1: Calculate the characteristic impedance Z of the dielectric surrounding the nth square ring ITO impedance film. g,n and effective dielectric constant ε eff,n n = 1, 2, ..., m: In the formula ε av,n The average dielectric constant of the surrounding medium is: In the formula, when the impedance film is a square ring, the coefficient α = 18, and ε rh,n The expression is as follows: Among them, h s,n and h r,n These are the thicknesses of the nth substrate dielectric and the intermediate dielectric, respectively; The surrounding medium of the final ITO metal film is the substrate medium and free space air, and its average dielectric constant is calculated as follows: Step 3.2: For each frequency point, calculate the equivalent lumped resistance R of the nth layer square ring ITO impedance film based on the physical parameters of the nth layer after decoding. n Equivalent capacitance C n and equivalent inductance L n n = 1, 2, ..., m: In the formula, In equations (7)-(12), p represents the unit period of the absorbing structure, and d n w represents the side length of the square ring of the ITO impedance thin film. n Indicates the width of the square ring; ε represents angular frequency. eff,n Z represents the effective dielectric constant of the surrounding medium, which affects the equivalent capacitance. g,n The characteristic impedance of the medium surrounding the square ring of the ITO impedance thin film is represented by F(p,x,λ) and G(p,x,λ), which are functions related to the geometric parameters of the impedance thin film and the wavelength λ, and α and β are two intermediate variables. Step 3.3: The input impedance Z of the last layer of the equivalent circuit of the absorbing structure. in,m The reflection coefficient Γ is obtained from the free-space characteristic impedance Z0: Step 3.4: Calculate the loss value, Loss. The weighted mean square error between the reflection coefficient obtained from the equivalent circuit and the target reflection coefficient is used as the value of the loss function. The expression for calculating the weighted mean square error is as follows: R i (f j ) and G i (f j ) represent the reflection coefficient and the target reflection coefficient calculated based on transmission line theory, respectively, when R i (f j )≤G i (f j When ), the penalty function E i (f j ) = 0, otherwise the penalty function is the absolute value of the difference between the two; i represents the weighting order, and j represents the frequency order within the i-th weighting region; Step 3.5: Calculate the individual fitness, which is an exponential function of the loss function, and its expression is as follows:

3. The multilayer absorbing structure design method based on equivalent circuit and genetic optimization algorithm as described in claim 2, characterized in that, Step 3.3 calculates the input impedance Z of the last layer of the equivalent circuit of the absorbing structure. in,m Specifically, it includes: Step 3.3.1: Calculate the characteristic impedance and propagation constant of the intermediate dielectric layer and the substrate dielectric layer for each frequency point: Where, ε s,n and ε r,n Let be the dielectric constants of the nth substrate dielectric and the intermediate dielectric, respectively; then, calculate the equivalent impedance of the nth ITO impedance film: Z ec,n =R n +jωL n +1 / (jωC n ) (20) ω=2πf (21) Step 3.3.2, Calculate Z ’ n Its characteristic impedance Z with the intermediate medium r,n Propagation constant β r,n Thickness h r,n and the input impedance Z of the previous layer in,n-1 Relatedly, since the metal base plate is equivalent to a short-circuit impedance of 0, the input impedance Z of the layer preceding the first layer is... in,0 =0: Step 3.3.3: Calculate Z n Its characteristic impedance Z with respect to the substrate dielectric s,n Propagation constant β s,n Thickness h s,n and Z ’ n related: Step 3.3.4: Calculate the input impedance Z of the nth layer. in,n It equals Z n and Z ec,n in parallel: WITH in,n =Z n ||From ec,n (24) Step 3.3.5: Repeat steps 3.3.2-3.3.4 to calculate the input impedance Z of the last layer. in,m .

4. The multilayer absorbing structure design method based on equivalent circuit and genetic optimization algorithm as described in any one of claims 1-3, characterized in that, Step 5 specifically includes: Step 5.1: Calculate the probability that each individual will be inherited by the next generation, where N is the population size, and f(x) i ) represents the fitness of the i-th individual: Step 5.2: Calculate the cumulative probability q for each individual. i : Step 5.3: Generate a random number r in the interval [0, 1], when q i-1 ≤r≤q i If the time is right, then select the i-th individual; Step 5.4: Repeat steps 5.1-5.3 N times, where N is equal to the population size popsize.

5. The multilayer absorbing structure design method based on equivalent circuit and genetic optimization algorithm as described in claim 4, characterized in that, Each layer of the absorbing structure is composed of multiple absorbing units with the same period. Each absorbing unit includes a metal base plate and n layers of absorbing assembly from bottom to top. The absorbing assembly includes a material dielectric layer, an air layer and a loss layer from bottom to top.

6. The multilayer absorbing structure design method based on equivalent circuit and genetic optimization algorithm as described in claim 5, characterized in that, The loss layer is an ITO impedance film in the shape of a square ring.

7. The multilayer absorbing structure design method based on equivalent circuit and genetic optimization algorithm as described in claim 6, characterized in that, The dielectric layer has a relative permeability μ = 1 and a relative permittivity ε ≤ 15.

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