Parameter optimization method for W-band broadband low-standing-wave-ratio resonant filter network

Abstract

The invention discloses a parameter optimization method for a W-band broadband low-standing-wave-ratio resonant filter network, and relates to the field of resonant filter parameter optimization. According to the method, the variational method is adopted to optimize the design variables, and the partial derivative of the target function is utilized to calculate the influence on the design parameters, so that a more efficient optimization process is realized, and the standing-wave ratio and the insertion loss are reduced.

Description

Technical Field

[0001] The invention relates to the field of resonant filter parameter optimization, in particular to a parameter optimization method for a W-band wide-band low standing wave ratio resonant filter network. Background Art

[0002] Existing filter design technologies are increasingly used in the millimeter wave band, especially in the W band (75-110GHz). With the development of wireless communications and radar systems, the performance requirements for filters are becoming higher and higher. In the W band, due to the high frequency range, traditional filter design technologies are usually difficult to meet the requirements of low standing wave ratio and low insertion loss, so it is usually necessary to use electromagnetic simulation software to analyze and optimize the frequency response of the filter. In the design of the filter, the center frequency of the filter is usually set by determining the frequency range and bandwidth target. This process may involve an overall analysis of the bandwidth performance to meet the operating frequency band requirements of the system. In order to achieve a stable filtering effect in a high-frequency environment, the existing technology usually initializes the geometric parameters of the filter (such as the length, width and thickness of the resonator) according to the selected center frequency, and selects appropriate materials to ensure the controllability of the electromagnetic performance. For example, in the selection of the resonator, based on the characteristics of the material such as the dielectric constant and conductivity, its electromagnetic response can be optimized to achieve lower losses in the target frequency band. However, these steps are usually only preliminary adjustments in the design process and need further optimization.

[0003] Although the prior art has achieved certain results in filter design, especially in the design of filters in lower frequency bands, the existing filter design technology still faces multiple insurmountable defects in the high frequency band of the W band. First, due to the high frequency range of the W band, the electromagnetic wave has a large loss during the propagation process, so the insertion loss of the filter is difficult to control at a low level. In the traditional filter design method, it is usually difficult to optimize the standing wave ratio while ensuring low insertion loss, so that the design result may not have good frequency selectivity and stability at high frequencies. Secondly, in the prior art, the geometric parameters and material properties of the filter are often fixed at the time of initialization. Although they will be adjusted after the optimization process, the overall optimization accuracy and efficiency are low. In addition, due to the short wavelength of electromagnetic waves in the W band, the design process of the filter requires precise geometric structure parameters, and the conventional optimization method used in the prior art can usually only achieve linear or simple nonlinear optimization, which leads to limited optimization effect and difficulty in achieving high-precision adjustment for frequency response. Thirdly, the weight distribution of the objective function in the prior art is not flexible enough, and it is impossible to distribute weights for specific frequency points, which makes it difficult to meet the performance requirements of multiple frequency points at the same time during the design process. For the design of W-band filters, the existing electromagnetic simulation and optimization methods lack systematicity in dealing with the relationship between standing wave ratio and insertion loss, especially in high-frequency design, the existing technology fails to provide effective optimization means for the relationship between standing wave ratio and smoothness. The traditional optimization process lacks more advanced mathematical tools such as variational functional design, making it difficult to effectively control the smoothness of the frequency response curve, making the performance of the filter unstable. Summary of the invention

[0004] The present invention effectively solves the problem of limited optimization effect of the prior art in the high frequency band by optimizing the distribution setting of frequency points, introducing the variational method to design functionals, and establishing a weight distribution model for the relationship between the standing wave ratio and the insertion loss.

[0005] The parameter optimization method of the W-band wideband low standing wave ratio resonant filter network comprises the following steps:

[0006] S1. According to the W-band frequency requirements, set the center frequency and target bandwidth range of the filter, select the optimized frequency points for distribution setting, set the initial geometric parameters as design variables based on the frequency points, and configure the material properties;

[0007] S2. Perform preliminary simulation analysis on the initialized filter structure through electromagnetic simulation software, obtain the standing wave ratio and insertion loss data within the bandwidth range, and calculate the standing wave ratio curve and loss curve at each frequency point;

[0008] S3. According to the calculated standing wave ratio and insertion loss of each frequency point, a weighted objective function model is established, wherein the objective function includes a numerical description of the standing wave ratio and the insertion loss, and the influence of each frequency point is calculated according to the weight;

[0009] S4. Designing a functional by a variational method, wherein the functional includes design variables corresponding to the frequency response, and establishing a relationship between the standing wave ratio and smoothness by setting a response function;

[0010] S5. Analyze the design variables of the objective function by using the variational method, analyze the influence of each design parameter on the standing wave ratio and insertion loss, optimize each parameter, and adjust the key dimensions and material properties of the initial geometric structure according to the optimization results;

[0011] S6. Perform simulation feedback. When the objective function change after optimization iteration is less than the set threshold, it is determined that the current optimization has converged, and a full-band simulation is performed to confirm the adjusted result. When the objective function change after optimization iteration is greater than or equal to the set threshold, continue the optimization and iterate step S5.

[0012] Furthermore, in step S1, the initial geometric parameters include the length, width, and thickness of the resonator.

[0013] Furthermore, in step S1, the material properties include dielectric constant and conductivity.

[0014] Furthermore, the step S3 specifically includes the following sub-steps:

[0015] S301. According to the calculated standing wave ratio and insertion loss at each frequency point, the deviation between the actual standing wave ratio and the target standing wave ratio is calculated;

[0016] S302. constructing a penalty term in a square form, and when the standing wave ratio deviation exceeds the target range, the penalty term increases as the deviation increases;

[0017] S303. Construct an optimization objective function containing a penalty term.

[0018] Furthermore, in step S302, the penalty term is specifically a nonlinear penalty term, which is expressed as:

[0019]

[0020] Among them, the ω i represents the i-th frequency point, the x i represents the i-th design variable, the P(ω i , x i ) represents the penalty term, the VSWR (ω i , x i) represents the actual standing wave ratio of the ith frequency point in the ith design variable, the VSWR target Indicates the target standing wave ratio.

[0021] Furthermore, in step S303, the optimization objective function is specifically expressed as:

[0022]

[0023] Wherein, J represents the objective function, n represents the total number of frequency points, i represents the index of the frequency point, γ represents the weight coefficient of the influence between the balanced standing wave ratio and the insertion loss, and L(ω i ) represents the actual insertion loss at the i-th frequency point, and the L target represents the target value of insertion loss, the β i Indicates the weight of each frequency point.

[0024] Furthermore, the step S4 specifically includes the following sub-steps:

[0025] S401. Construct a functional for describing the standing wave ratio and the smoothness of the frequency response;

[0026] S402. Find the partial derivative of each design variable and set the partial derivative of the functional to be And solve this partial derivative;

[0027] S403. Set a response function, and associate the response function with the frequency response.

[0028] Furthermore, in step S401, the functional is specifically expressed as:

[0029]

[0030] Among them, the J(x i ) represents a functional for describing the standing wave ratio and the smoothness of the frequency response, the f 1 and f 2 Used to indicate the frequency range [f 1 , f 2 ], the k 1 Represents the weight coefficient of the standing wave ratio, the VSWR (ω i , x i ) represents the actual standing wave ratio of the ith frequency point in the ith design variable, the VSWR target represents the target standing wave ratio, the k 2 represents the weight coefficient of the smoothness term, f represents the frequency point, and x i represents the i-th design variable, the ω i represents the i-th frequency point.

[0031] Furthermore, in step S402, the specific process of solving the partial derivative is expressed as follows:

[0032]

[0033] Wherein, J represents the objective function, d represents the derivative, Represents the sensitivity of the standing wave ratio to the design variables.

[0034] Furthermore, in step S403, the response function is specifically expressed as:

[0035]

[0036] Wherein, the R(x i ) represents the response function.

[0037] The beneficial effects of the invention are:

[0038] The present invention adopts the variational method to optimize the design variables and uses the partial derivative of the objective function to calculate the influence on the design parameters, thereby realizing a more efficient optimization process and reducing the standing wave ratio and the insertion loss. BRIEF DESCRIPTION OF THE DRAWINGS

[0039] Figure 1 A method flow chart of a parameter optimization method for a W-band wideband low standing wave ratio resonant filter network provided by an embodiment of the present invention. DETAILED DESCRIPTION

[0040] The technical solution of the present invention is further described in detail below in conjunction with the accompanying drawings, but the protection scope of the present invention is not limited to the following.

[0041] In order to make the purpose, technical solutions and advantages of the present invention more clear, the present invention is further described in detail in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present invention and are not used to limit the present invention, that is, the described embodiments are only part of the embodiments of the present invention, rather than all of the embodiments. Generally, the components of the embodiments of the present invention described and shown in the drawings herein can be arranged and designed in various different configurations.

[0042] Therefore, the following detailed description of the embodiments of the present invention provided in the accompanying drawings is not intended to limit the scope of the claimed invention, but merely represents selected embodiments of the present invention. All other embodiments obtained by those skilled in the art based on the embodiments of the present invention without creative work are within the scope of protection of the present invention. It should be noted that relational terms such as the terms "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.

[0043] Moreover, the terms "comprises", "includes" or any other variations thereof are intended to cover non-exclusive inclusion, so that a process, method, article or apparatus that includes a list of elements includes not only those elements, but also includes other elements not explicitly listed, or also includes elements inherent to such process, method, article or apparatus. In the absence of more restrictions, an element defined by the phrase "comprises a ..." does not exclude the presence of additional identical elements in the process, method, article or apparatus that includes the element.

[0044] The features and performance of the present invention are further described in detail below in conjunction with the embodiments.

[0045] Among them, Figure 1 , a parameter optimization method for a W-band wideband low standing wave ratio resonant filter network comprises the following steps:

[0046] S1. According to the W-band frequency requirements, set the center frequency and target bandwidth range of the filter, select the optimized frequency points for distribution setting, set the initial geometric parameters as design variables based on the frequency points, and configure the material properties;

[0047] S2. Perform preliminary simulation analysis on the initialized filter structure through electromagnetic simulation software, obtain the standing wave ratio and insertion loss data within the bandwidth range, and calculate the standing wave ratio curve and loss curve at each frequency point;

[0048] S3. According to the calculated standing wave ratio and insertion loss of each frequency point, a weighted objective function model is established, wherein the objective function includes a numerical description of the standing wave ratio and the insertion loss, and the influence of each frequency point is calculated according to the weight;

[0049] S4. Designing a functional by a variational method, wherein the functional includes design variables corresponding to the frequency response, and establishing a relationship between the standing wave ratio and smoothness by setting a response function;

[0050] S5. Analyze the design variables of the objective function by using the variational method, analyze the influence of each design parameter on the standing wave ratio and insertion loss, optimize each parameter, and adjust the key dimensions and material properties of the initial geometric structure according to the optimization results;

[0051] S6. Perform simulation feedback. When the objective function change after optimization iteration is less than the set threshold, it is determined that the current optimization has converged, and a full-band simulation is performed to confirm the adjusted result. When the objective function change after optimization iteration is greater than or equal to the set threshold, continue the optimization and iterate step S5.

[0052] Furthermore, in step S1, the initial geometric parameters include the length, width, and thickness of the resonator.

[0053] Furthermore, in step S1, the material properties include dielectric constant and conductivity.

[0054] Specifically, in step S1, based on the frequency requirements of the W band, the center frequency and target bandwidth range of the filter are selected to ensure that the required communication bandwidth is covered. According to the distribution of different frequency points within the range, the initial design geometric parameters are determined and used as design variables. The selected frequency points can cover the key points in the frequency response curve, and may include the upper and lower limits of the bandwidth, as well as the center frequency position, etc. The material properties are configured according to the high-frequency requirements of the filter, and may include dielectric constants, conductivity, etc., which directly affect the standing wave ratio and insertion loss performance of the filter at the W band frequency. The above implementation steps select a more comprehensive frequency point for optimization setting at the beginning of the design, so that the subsequent optimization process is more targeted and accurate.

[0055] Furthermore, in step S2, the initialization structure is simulated and analyzed by electromagnetic simulation software to obtain the standing wave ratio (VSWR) and insertion loss (IL) data within the specified bandwidth range, and the simulation results are summarized into curves to analyze the standing wave ratio and loss performance at each frequency point. This implementation can be used to identify defects in the initial design, such as frequency points where the standing wave ratio is too high or the insertion loss is abnormally high. Compared with the traditional method of performing simulation analysis only at specific frequency points, this process can provide a more comprehensive understanding of the response of the filter over the entire bandwidth range and provide basic data support for subsequent optimization processes.

[0056] Furthermore, the step S3 specifically includes the following sub-steps:

[0057] S301. According to the calculated standing wave ratio and insertion loss of each frequency point, the deviation between the actual standing wave ratio and the target standing wave ratio is calculated respectively; specifically, according to the simulation results, the deviation between the actual standing wave ratio of each frequency point and the preset target standing wave ratio is calculated, and the part exceeding the target is identified. This implementation method is used to identify the frequency range that most needs to be optimized, so as to optimize resource allocation more efficiently.

[0058] S302. constructing a penalty term in a square form, and when the standing wave ratio deviation exceeds the target range, the penalty term increases as the deviation increases;

[0059] S303. Construct an optimization objective function containing a penalty term.

[0060] Furthermore, in step S302, the penalty term is specifically a nonlinear penalty term, which is expressed as:

[0061]

[0062] Among them, the ω i represents the i-th frequency point, the x i represents the i-th design variable, the P(ω i , x i ) represents the penalty term, the VSWR (ω i , x i ) represents the actual standing wave ratio of the ith frequency point in the ith design variable, the VSWR target Indicates the target standing wave ratio.

[0063] Specifically, for the above standing wave ratio deviation ΔVSWR(ω i , x i ), it should be noted that the specific calculation process is to calculate the actual standing wave ratio VSWR (ω i , x i ) and target standing wave ratio VSWR target The deviation between i , x i )=VSWR(ω i , x i )-VSWR target , thus quantifying the degree to which the standing wave ratio deviates from the target range. In addition, when ΔVSWR(ω i , x i ) exceeds VSWR target , that is, ΔVSWR(ω i , x i)>0, it means that the actual VSWR is higher than the target VSWR, that is, the performance of the filter at this frequency point is not as expected and needs to be adjusted, prompting the optimization algorithm to adjust the design parameters to reduce the VSWR and reach the target value; otherwise, it means that the VSWR performance is good, so no penalty is needed and the optimization algorithm can make no adjustments.

[0064] Furthermore, a penalty term is constructed in a square form. When the standing wave ratio deviation exceeds the target range, the priority of the frequency point is increased by increasing the penalty value of the deviation, so that the optimization process focuses on the standing wave ratio control of the key frequency point. The above implementation method ensures that the optimization algorithm can effectively reduce the excessive standing wave ratio in subsequent iterations and obtain a smooth response curve.

[0065] Furthermore, in step S303, the optimization objective function is specifically expressed as:

[0066]

[0067] Wherein, J represents the objective function, n represents the total number of frequency points, i represents the index of the frequency point, γ represents the weight coefficient of the influence between the balanced standing wave ratio and the insertion loss, and L(ω i ) represents the actual insertion loss at the i-th frequency point, and the L target represents the target value of insertion loss, the β i Represents the weight of each frequency point. Specifically, the penalty term is integrated into the optimization objective function to make it more targeted and constrained. Compared with the traditional objective function model, the control of the frequency points beyond the VSWR range is strengthened, and the optimization of the objective function within the frequency band is more balanced through the adjustment of the weighted penalty term.

[0068] Furthermore, the step S4 specifically includes the following sub-steps:

[0069] S401. Construct a functional for describing the standing wave ratio and the smoothness of the frequency response;

[0070] S402. Find the partial derivative of each design variable and set the partial derivative of the functional to be And solve this partial derivative;

[0071] S403. Set a response function, and associate the response function with the frequency response.

[0072] Furthermore, in step S401, the functional is specifically expressed as:

[0073]

[0074] Among them, the J(x i ) represents a functional for describing the standing wave ratio and the smoothness of the frequency response, the f 1 and f2 Used to indicate the frequency range [f 1 , f 2 ], the k 1 Represents the weight coefficient of the standing wave ratio, the VSWR (ω i , x i ) represents the actual standing wave ratio of the ith frequency point in the ith design variable, the VSWR target represents the target standing wave ratio, the k 2 represents the weight coefficient of the smoothness term, f represents the frequency point, and x i represents the i-th design variable, the ω i Represents the i-th frequency point. Specifically, a functional is constructed to describe the smoothness of the standing wave ratio and frequency response, and the changes of the standing wave ratio and insertion loss are incorporated into the variational model. Through the construction of the functional, the standing wave ratio and insertion loss can change smoothly in the whole frequency band to achieve a smooth and non-fluctuating response.

[0075] Furthermore, in step S402, the specific process of solving the partial derivative is expressed as follows:

[0076]

[0077] Wherein, J represents the objective function, d represents the derivative, It represents the sensitivity of the standing wave ratio to the design variables. Specifically, the partial derivative of each design variable of the functional is calculated to determine the influence of each variable on the standing wave ratio and insertion loss response. This process is used to optimize the parameter direction in the subsequent optimization adjustment to provide specific optimization directions for different design parameters. The solution of partial derivatives makes the response curve optimization more accurate and can more quickly find the best path for optimizing the standing wave ratio and insertion loss. In addition, the sensitivity of the standing wave ratio to the design variables is to measure the dependence of the standing wave ratio on these variables by calculating the rate of change of the standing wave ratio (VSWR) to each design variable (such as the geometric parameters of the resonator, the dielectric constant of the material, etc.). The core of this process is to understand how the response of the standing wave ratio changes under different design parameter values, so as to find the optimal parameter configuration. The sensitivity value of the standing wave ratio to the design variables provides a quantitative direction of the influence of each design variable on the standing wave ratio. When the sensitivity of a variable is large, it indicates that the variable has a significant effect on the standing wave ratio; on the contrary, when the sensitivity is small, it indicates that the variable has little effect. With this information, the variables that have a greater impact on the standing wave ratio can be adjusted first, thereby optimizing the filter performance more effectively. In order to minimize the functional, it is necessary to calculate the partial derivatives (i.e., sensitivity) of the standing wave ratio with respect to each design variable, and adjust the variable value in combination with the numerical optimization method. The sensitivity value will serve as a guide for the direction and magnitude of the gradient descent, and by gradually reducing the value of the functional, the optimization and smoothness improvement of the standing wave ratio within the bandwidth can be achieved.

[0078] Furthermore, the sensitivity of the SWR to the design variables is calculated as follows:

[0079]

[0080] In this case, a small increment Δx is applied to each variable by the finite difference method. i , recalculate the standing wave ratio change to estimate the sensitivity. Preferably, in the electromagnetic simulation software, through the parameter scanning function, each variable is adjusted to observe the change of the standing wave ratio, so as to obtain the sensitivity of the standing wave ratio to the variable.

[0081] Furthermore, in step S403, the response function is specifically expressed as:

[0082]

[0083] Wherein, the R(x i ) represents the response function. Specifically, through the relationship between the response function and the frequency response, the standing wave ratio value and the frequency response smoothness of each frequency point are optimized to ensure that the final response curve meets the low standing wave ratio requirements of the W-band wide frequency band.

[0084] Furthermore, as a preferred implementation scheme of the above embodiment, an implementation process is exemplarily proposed:

[0085] First, the main operating frequency band of the filter is determined based on the requirements of the W-band wideband, ranging from 75GHz to 110GHz. The center frequency is selected as the design core, and several key frequency points are set on both sides of the center frequency to ensure performance optimization within the wideband coverage range. The initial parameters of the filter structure, including the size of the resonator (length, width, thickness), the dielectric constant and conductivity of the configuration material, are determined to ensure that the initial design meets the basic requirements;

[0086] The initially designed filter model is simulated by electromagnetic simulation software to obtain the standing wave ratio (VSWR) and insertion loss curves at each frequency point. By analyzing the standing wave ratio and insertion loss values ​​of the initial simulation, the performance of each frequency point can be understood;

[0087] Construct a weighted objective function, in which the VSWR and insertion loss at each frequency point are described according to preset weights, and the weights are assigned according to the importance of the frequency points;

[0088] The objective function is processed by the variational method, and the corresponding functional is designed. This functional contains variables related to the filter frequency response, such as geometric size parameters and material properties. The response function of the functional is established, and the relationship between the standing wave ratio and smoothness is integrated into the optimization framework to balance the standing wave ratio optimization and frequency response smoothness;

[0089] Use partial derivatives to quantify the effect of each design variable on the VSWR and insertion loss. Adjust the design variables, including key dimensions and material properties, based on the direction and magnitude of the derivative calculations. After each adjustment, repeat the simulation to obtain new VSWR and insertion loss data, and gradually optimize the frequency response.

[0090] Observe the change of the objective function after optimization. If the change value of the objective function is lower than the preset convergence threshold, it means that the optimization process has been basically stable, and then enter the full-band simulation to confirm the performance of the current parameters. If the change of the objective function is greater than or equal to the set threshold, it means that the optimization has not been completed, and then continue to iterate the optimization until the convergence condition is reached.

[0091] In addition, as a preferred implementation scheme of the above embodiment, in the design of broadband filters, in order to make the standing wave ratio and insertion loss at the edge of the band have a more significant impact on the overall filtering performance, the weights of the edge frequency points are adjusted separately in the objective function, so that the optimization process pays more attention to the performance of the edge frequency. Exemplarily, according to the specific requirements of the W-band broadband, the frequency range of the bandwidth is divided into "edge frequency band" and "center frequency band", wherein the weights of the upper and lower edge frequency points of the bandwidth are higher through:

[0092]

[0093] Among them, the a edge Represents the weight coefficient of the edge frequency point, the a center represents the weight coefficient of the center frequency point, the ω min and ω max Represent the lowest frequency and highest frequency in the filter design respectively.

[0094] The above is only a preferred embodiment of the present invention. It should be understood that the present invention is not limited to the form disclosed herein, and should not be regarded as excluding other embodiments, but can be used in various other combinations, modifications and environments, and can be modified within the scope of the concept described herein through the above teachings or the technology or knowledge of the relevant field. The changes and modifications made by those skilled in the art shall not deviate from the spirit and scope of the present invention, and shall be within the scope of protection of the claims attached to the present invention.

Claims

1. A parameter optimization method for a W-band wideband low standing wave ratio resonant filter network, characterized in that: The following steps are involved: S1. According to the W-band frequency requirements, set the center frequency and target bandwidth range of the filter, select the optimized frequency points for distribution setting, set the initial geometric parameters as design variables based on the frequency points, and configure the material properties; S2. Perform preliminary simulation analysis on the initialized filter structure through electromagnetic simulation software, obtain the standing wave ratio and insertion loss data within the bandwidth range, and calculate the standing wave ratio curve and loss curve at each frequency point; S3. According to the calculated standing wave ratio and insertion loss of each frequency point, a weighted objective function model is established, wherein the objective function includes a numerical description of the standing wave ratio and the insertion loss, and the influence of each frequency point is calculated according to the weight; S4. Designing a functional by a variational method, wherein the functional includes design variables corresponding to the frequency response, and establishing a relationship between the standing wave ratio and smoothness by setting a response function; S5. Analyze the design variables of the objective function by using the variational method, analyze the influence of each design parameter on the standing wave ratio and insertion loss, optimize each parameter, and adjust the key dimensions and material properties of the initial geometric structure according to the optimization results; S6. Perform simulation feedback. When the objective function change after optimization iteration is less than the set threshold, it is determined that the current optimization has converged, and a full-band simulation is performed to confirm the adjusted result. When the objective function change after optimization iteration is greater than or equal to the set threshold, continue the optimization and iterate step S5.

2. The parameter optimization method of the W-band wideband low standing wave ratio resonant filter network as claimed in claim 1, characterized in that: In the step S1, the initial geometric parameters include the length, width, and thickness of the resonator.

3. The parameter optimization method of the W-band wideband low standing wave ratio resonant filter network as claimed in claim 1, characterized in that: In the step S1, the material properties include dielectric constant and conductivity.

4. The parameter optimization method of the W-band wideband low standing wave ratio resonant filter network as claimed in claim 1, characterized in that: The step S3 specifically includes the following sub-steps: S301. According to the calculated standing wave ratio and insertion loss at each frequency point, the deviation between the actual standing wave ratio and the target standing wave ratio is calculated; S302. constructing a penalty term in a square form, and when the standing wave ratio deviation exceeds the target range, the penalty term increases as the deviation increases; S303. Construct an optimization objective function containing a penalty term.

5. The parameter optimization method of the W-band wideband low standing wave ratio resonant filter network as claimed in claim 4, characterized in that: In step S302, the penalty term is specifically a nonlinear penalty term, which is expressed as: Among them, the ω i represents the i-th frequency point, the x i represents the i-th design variable, the P(ω i ,x i ) represents the penalty term, the VSWR (ω i ,x i ) represents the actual standing wave ratio of the ith frequency point in the ith design variable, the VSWR target Indicates the target standing wave ratio.

6. The parameter optimization method of the W-band wideband low standing wave ratio resonant filter network as claimed in claim 5, characterized in that: In step S303, the optimization objective function is specifically expressed as: Wherein, J represents the objective function, n represents the total number of frequency points, i represents the index of the frequency point, γ represents the weight coefficient of the influence between the balanced standing wave ratio and the insertion loss, and L(ω i ) represents the actual insertion loss at the i-th frequency point, and the L target represents the target value of insertion loss, the β i Indicates the weight of each frequency point.

7. The parameter optimization method of the W-band wideband low standing wave ratio resonant filter network as claimed in claim 1, characterized in that: The step S4 specifically includes the following sub-steps: S401. Construct a functional for describing the standing wave ratio and the smoothness of the frequency response; S402. Find the partial derivative of each design variable and set the partial derivative of the functional to be And solve this partial derivative; S403. Set a response function, and associate the response function with the frequency response.

8. The parameter optimization method of the W-band wideband low standing wave ratio resonant filter network as claimed in claim 7, characterized in that: In step S401, the functional is specifically expressed as: Among them, the J(x i ) represents a functional for describing the standing wave ratio and the smoothness of the frequency response, the f1 and f2 are used to represent the frequency range [f1, f2], the k1 represents the weight coefficient of the standing wave ratio, the VSWR (ω i ,x i ) represents the actual standing wave ratio of the ith frequency point in the ith design variable, the VSWR target represents the target standing wave ratio, k2 represents the weight coefficient of the smoothness term, f represents the frequency point, and x i represents the i-th design variable, the ω i represents the i-th frequency point.

9. The parameter optimization method of the W-band wideband low standing wave ratio resonant filter network as claimed in claim 8, characterized in that: In step S402, the specific process of solving the partial derivative is expressed as follows: Wherein, J represents the objective function, d represents the derivative, Represents the sensitivity of the standing wave ratio to the design variables.

10. The parameter optimization method of the W-band wideband low standing wave ratio resonant filter network as claimed in claim 9, characterized in that: In step S403, the response function is specifically expressed as: Wherein, the R(x i ) represents the response function.

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