Antenna optimization method and system based on right trapezoid half-mode resonator

Abstract

The invention discloses an antenna optimization method and system based on a right trapezoid half-mode resonator. The method comprises the following steps: acquiring initial structure parameters of the right trapezoid half-mode resonator; constructing a three-dimensional electromagnetic field simulation model based on the initial structure parameters, calculating electromagnetic field distribution characteristics of the right-angled trapezoidal half-mode resonator through a finite element analysis method, and performing primary verification on the electromagnetic field distribution characteristics; generating an optimization objective function; carrying out iterative optimization on the geometric parameters of the right trapezoid half-mode resonator by adopting a genetic algorithm; re-calculating electromagnetic field distribution characteristics based on the optimized geometric parameters, and carrying out secondary verification on the electromagnetic field distribution characteristics; and adjusting the position of the feed port and the thickness of the metal patch according to the deviation direction. The method has the following advantages and effects that the problem that a traditional design method depends on experience trial-and-error or single-target optimization, and collaborative optimization of multiple parameters is difficult to achieve under the complex electromagnetic coupling effect is solved.

Description

Technical Field

[0001] The present invention relates to the technical field of antennas, and particularly to an antenna optimization method and system based on a right-angled trapezoidal half-mode resonator. Background Art

[0002] In the field of microwave antenna design, right-angled trapezoidal half-mode resonators are widely used in high-frequency communication systems, such as 5G base stations and millimeter-wave radars, due to their advantages of compact structure and easy integration. However, the performance of such antennas highly depends on the precise matching of geometric parameters, the position of the feeding port, and the thickness of the metal patch. The core problem of the existing technology lies in that the traditional design method relies on empirical trial and error or single-objective optimization, and it is difficult to achieve the collaborative optimization of multiple parameters under complex electromagnetic coupling effects. The multiple parameters specifically include the main lobe width, side lobe suppression ratio, impedance matching bandwidth, and resonance frequency deviation value. Specifically, designers usually approach the target performance by manually adjusting parameters and repeatedly performing electromagnetic simulations. However, the asymmetric characteristics of the right-angled trapezoidal structure result in strong coupling relationships between parameters. For example, when adjusting the upper base length to compress the main lobe width, the side lobe suppression ratio may be significantly deteriorated; when optimizing the feeding position to improve impedance matching, it is easy to deviate from the resonance frequency. Such multiple-parameter conflicts make the traditional method extremely inefficient and difficult to converge to the global optimal solution. In addition, although commercial simulation software can provide single-performance evaluations, it lacks an intelligent decision-making mechanism for multi-objective joint optimization, resulting in a long design cycle and high costs. Ultimately, the antenna performance often compromises to the local optimum and cannot meet the stringent requirements of high-precision communication systems for radiation efficiency, anti-interference ability, and bandwidth.

[0003] Therefore, there is an urgent need for an optimization method that can automatically coordinate multiple-parameter conflicts and quickly approach the global optimal solution to break through the performance bottleneck of the antenna design of right-angled trapezoidal half-mode resonators. Summary of the Invention

[0004] The purpose of the present invention is to provide an antenna optimization method and system based on a right-angled trapezoidal half-mode resonator to solve the problems raised in the background art.

[0005] The above technical purpose of the present invention is achieved through the following technical solutions: The present invention provides an antenna optimization method based on a right-angled trapezoidal half-mode resonator, including the following steps: S100. Obtain the initial structural parameters of the right-angled trapezoidal half-mode resonator; wherein, the initial structural parameters include the dielectric constant of the substrate material, geometric parameters, the thickness of the metal patch, and the position of the feeding port, and the geometric parameters include the upper base length, lower base length, and height of the right-angled trapezoid; S200. Construct a three-dimensional electromagnetic field simulation model based on the initial structural parameters, calculate the electromagnetic field distribution characteristics of the right trapezoidal half-mode resonator through the finite element analysis method, and conduct a primary verification of the electromagnetic field distribution characteristics. If it is determined that the verification result meets the standard, output the current initial structural parameters as the final design; otherwise, execute S300; S300. Extract the main lobe width, side lobe suppression ratio, impedance matching bandwidth, and resonant frequency deviation value of the radiation pattern based on the electromagnetic field distribution characteristics, and generate an optimization objective function based on the preset performance indicators. The optimization objective function includes a radiation efficiency weight factor, a bandwidth maximization coefficient, an impedance matching optimization coefficient, and a resonant frequency error weight factor; S400. Use the genetic algorithm to iteratively optimize the geometric parameters of the right trapezoidal half-mode resonator, dynamically adjust the proportional relationship of the upper base length, lower base length, and height until the optimization objective function converges to a preset range; S500. Recalculate the electromagnetic field distribution characteristics based on the optimized geometric parameters, and conduct a secondary verification of the electromagnetic field distribution characteristics. If it is determined that the verification result meets the standard, output the current initial structural parameters as the final design; otherwise, execute S600; S600. Adjust the position of the feeding port and the thickness of the metal patch according to the deviation direction, update the updated parameters to the initial structural parameters of S100, and re-execute the steps from S200 to S500 until the termination condition is met.

[0006] By adopting the above technical solutions, a closed-loop iterative optimization framework is constructed. Through the full-process integration of parameter initialization, electromagnetic simulation verification, multi-objective function optimization, and dynamic feedback adjustment, the design efficiency and performance upper limit of the right trapezoidal half-mode resonator antenna are significantly improved. This method systematically solves the pain point of difficult collaborative optimization of multiple parameters in traditional antenna design, incorporates radiation characteristics, impedance matching, and frequency stability into a unified optimization framework, uses the global search ability of the genetic algorithm to dynamically adjust the geometric parameter ratio, and combines a dual electromagnetic field verification mechanism to ensure the physical rationality and engineering feasibility of the design results. Its core advantage lies in realizing self-correction of the design process through a parameter feedback closed-loop, avoiding local optimal traps, being compatible with different frequency bands and material configurations at the same time, and being applicable to the customized antenna development requirements in high-density integration scenarios, providing a highly reliable miniaturized antenna solution for applications such as 5G millimeter-wave communication and Internet of Things sensing nodes.

[0007] Furthermore, the specific steps of S100 are as follows: S110. Prepare a standard test sample of the substrate material, and measure the dielectric constant of the substrate material in the target frequency band through the coaxial air line method. Then, use a vector network analyzer to verify the stability of the dielectric constant in the target frequency band to ensure that the fluctuation range of its real part is lower than the preset threshold and the imaginary part approaches zero; S120. According to the target operating frequency range and the dielectric constant of the substrate material, use the equivalent circuit model of the half-mode resonator to deduce the ratio of the initial upper base length to the lower base length of the right trapezoid; S130. Based on the propagation path loss model of electromagnetic waves in the right trapezoid structure and the dielectric constant of the substrate material, determine the value range of the metal patch thickness; S140. Based on the input impedance characteristics of the equivalent circuit model of the half-mode resonator, calculate the theoretical matching position of the feeding port, analyze the surface current density distribution through three-dimensional electromagnetic field simulation, and adjust the feeding port to the current standing wave node position; then, iteratively optimize the lateral offset and longitudinal embedding depth of the feeding port until the real part of the input impedance approaches the target value and the imaginary part approaches zero.

[0008] By adopting the above technical solutions, it reflects the refined definition and scientific derivation of the initial structural parameters, laying a high-precision foundation for subsequent optimization; accurately measure the dielectric constant of the substrate material through the coaxial air line method and vector network analyzer to ensure its stability within the target frequency band, and avoid the risk of resonance frequency deviation caused by material property fluctuations; deduce the initial geometric parameters based on the equivalent circuit model of the half-mode resonator, establish the proportional constraint relationship between the upper base, lower base and height of the right trapezoid, and ensure the resonance characteristics of the initial structure from the electromagnetic theory level, significantly shortening the optimization convergence time compared with the empirical parameter setting; the value range of the metal patch thickness is determined by the propagation path loss model, balancing the requirements of ohmic loss and surface wave suppression, and the iterative optimization of the feeding port position combines equivalent circuit analysis and surface current density simulation to achieve precise matching of the input impedance; this series of measures jointly ensure the optimal balance among electromagnetic compatibility, structural rationality and manufacturing feasibility of the initial parameter set, reducing the blindness of subsequent optimization iterations.

[0009] A further setting is that the S200 specifically includes the following steps: S210. Construct a three-dimensional electromagnetic field simulation model based on the initial structural parameters, including the following sub-steps: According to the upper base length, lower base length and height of the right trapezoid in the geometric parameters, construct a three-dimensional electromagnetic field simulation model of the right trapezoid half-mode resonator, and the boundary size of the three-dimensional electromagnetic field simulation model is jointly constrained by the dielectric constant of the substrate material and the metal patch thickness; Based on the metal patch thickness and the dielectric constant of the substrate material, calculate the electric field intensity gradient distribution in the three-dimensional electromagnetic field simulation model, and mark the area with a gradient value higher than the preset threshold as the high-density grid area; Use tetrahedral unstructured meshes to densely divide the high-density grid area to generate high-density grid data; For the regions in the geometric entity model except the high-density grid region, hexahedron structured meshing is adopted to generate low-density grid data; S220. Define the dielectric constant property and wave port excitation source in the three-dimensional electromagnetic field simulation model, including the following sub-steps: Define the dielectric constant property in the base material region of the three-dimensional electromagnetic field simulation model, and its value directly references the dielectric constant of the base material in the initial structure parameters; Load a wave port excitation source at the position of the feeding port in the initial structure parameters, and its impedance matching parameters are calculated based on the thickness of the metal patch and the dielectric constant of the base material; S230. Calculate the electromagnetic field distribution characteristics by the finite element analysis method, and generate the radiation pattern, impedance matching bandwidth and resonant frequency deviation value corresponding to S300; including the following sub-steps: Based on the target operating frequency range, set the frequency scanning range of the finite element solver, and the frequency sampling interval is calculated according to the dielectric constant of the base material and the thickness of the metal patch in the initial structure parameters; Based on the high-density grid data and low-density grid data generated by S210, and the dielectric constant property and wave port excitation source defined by S220, use the finite element analysis method to solve the Maxwell equations, and calculate the three-dimensional electric field distribution, magnetic field distribution and surface current density distribution of the right trapezoidal half-mode resonator; Extract the data of the surface current density distribution, generate a normalized current density distribution diagram, and mark the positions of the current standing wave nodes, and compare and verify with the position of the feeding port in S100; Based on the three-dimensional electric field distribution and magnetic field distribution, calculate the radiation pattern of the antenna, and extract the main lobe width and sidelobe suppression ratio; Based on the parameter calculation results of the wave port excitation source, extract the real part and imaginary part of the input impedance to generate the impedance matching bandwidth; Through the simulation results in the target operating frequency range, determine the actual resonant frequency, calculate its deviation from the target resonant frequency, and obtain the resonant frequency deviation value; S240. Verify whether the main lobe width, sidelobe suppression ratio, impedance matching bandwidth and resonant frequency deviation value of the radiation pattern meet the standards; S250. If it is determined that the verification result meets the standards, output the current initial structure parameters as the final design; If it is determined that the verification result does not meet the standards, then use the main lobe width, sidelobe suppression ratio, impedance matching bandwidth and resonant frequency deviation value of the radiation pattern as the input parameters of S300.

[0010] By adopting the above technical solutions, it focuses on the high-precision construction of the three-dimensional electromagnetic field simulation model and the multi-physical field coupling analysis ability; dynamically divides the grid density through the distribution of the electric field strength gradient, uses tetrahedral unstructured encrypted grids in high-field regions to accurately capture the field mutation effect at the right-angled trapezoidal edge, and uses hexahedral structured grids in low-gradient regions to reduce the consumption of computing resources, realizing the collaborative optimization of simulation accuracy and efficiency; the parametric design of the perfectly matched layer absorption boundary condition effectively suppresses the false reflection at the edge of the simulation domain and improves the simulation credibility of the far-field radiation pattern; the finite element analysis method for solving Maxwell's equations not only outputs the three-dimensional electromagnetic field distribution, but also synchronously extracts key parameters such as surface current density, input impedance and resonant frequency to form a multi-dimensional performance evaluation system; the comparison and verification of the normalized current density distribution map and the position of the current standing wave nodes provide an intuitive basis for optimizing the position of the feeding port, and the quantitative extraction of indicators such as the main lobe width and sidelobe suppression ratio of the radiation pattern establishes a direct mapping from electromagnetic simulation to engineering indicators to ensure the comprehensiveness and objectivity of design verification.

[0011] A further setting is that the S240 specifically includes the following steps: Judge whether the main lobe width is less than or equal to a preset main lobe width target value; Judge whether the sidelobe suppression ratio is greater than or equal to a preset sidelobe suppression ratio threshold; Judge whether the impedance matching bandwidth covers the target operating frequency range; Judge whether the resonant frequency deviation value is less than or equal to a preset resonant frequency error threshold; If all the above conditions are met, it is determined that the verification result is qualified; otherwise, it is determined that the verification result is unqualified.

[0012] By adopting the above technical solutions, the comprehensiveness and robustness of the design results are strengthened through a multi-threshold joint determination mechanism; the preset main lobe width target value, sidelobe suppression ratio threshold, impedance matching bandwidth coverage range and resonant frequency error threshold constitute a four-in-one verification system, requiring that the antenna performance must simultaneously meet the requirements of radiation efficiency, interference suppression, frequency band adaptation and frequency stability, avoiding performance imbalance caused by single-index optimization; for example, exceeding the main lobe width may cause beam pointing deviation, insufficient sidelobe suppression will increase adjacent channel interference, and impedance mismatch or frequency offset directly lead to a decrease in energy transmission efficiency. This determination mechanism ensures the comprehensive performance of the antenna from the system level; the threshold setting can be dynamically adjusted according to the application scenario, such as tightening the sidelobe suppression requirements in radar systems and relaxing the main lobe width limit in broadband communications, reflecting the flexibility and scenario adaptation ability of the design method; the sub-item determination logic can also quickly locate the performance short board and guide the formulation of subsequent parameter adjustment strategies.

[0013] A further setting is that the S300 specifically includes the following steps: S310. Extract the main lobe width, side lobe suppression ratio, real and imaginary parts of the input impedance, and the resonant frequency deviation value based on the main lobe width, side lobe suppression ratio, impedance matching bandwidth, and resonant frequency deviation value generated in S200. S320. Define an optimization objective function according to the preset performance indicators based on the extracted main lobe width, side lobe suppression ratio, real and imaginary parts of the input impedance, and the resonant frequency deviation value. S330. Normalize the optimization objective function and map it to the interval [0, 1]. S340. Determine whether the normalized result of the optimization objective function converges to the preset range and If the convergence condition is met, output the current geometric parameters as the optimization result; otherwise, enter S400 for iterative optimization.

[0014] By adopting the above technical solutions, a normalized multi-objective optimization function is constructed to solve the problems of multi-parameter dimension difference and optimization priority conflict; by mapping the main lobe width difference, side lobe suppression ratio, impedance matching deviation, and resonant frequency error to a unified dimensionless interval, the interference of different physical quantities on the optimization algorithm is eliminated, ensuring that the genetic algorithm performs global search under fair weight allocation; the introduction of parameters such as the radiation efficiency weight factor and the bandwidth maximization coefficient allows dynamic adjustment of the optimization direction according to actual needs. For example, in Internet of Things terminal devices, the resonant frequency error is preferentially reduced to meet the communication protocol specifications, while in satellite communication, the radiation efficiency is emphasized to enhance signal coverage; the convergence criterion uses a dynamic range instead of a fixed threshold to adapt to the accuracy requirements of different design stages. In the initial stage, larger fluctuations are allowed to accelerate the exploration of the parameter space, and the range is gradually tightened in the later stage to achieve refined tuning, taking into account both optimization efficiency and result accuracy.

[0015] A further setting is that the optimization objective function in S320 includes: Calculate the normalized difference between the main lobe width and the preset main lobe width target value with the radiation efficiency weight factor as the weight. Directly use the side lobe suppression ratio as the gain term with the bandwidth maximization coefficient as the weight. Calculate the relative deviation between the real part of the input impedance and the preset real part target value of the input impedance with the impedance matching optimization coefficient as the weight. Calculate the normalized difference between the resonant frequency deviation value and the preset resonant frequency error threshold with the resonant frequency error weight factor as the weight.

[0016] By adopting the above technical solutions, independent regulation and collaborative optimization of performance indicators are achieved through modular objective function design; the normalized difference between the main lobe width and the preset target value is used as the core driving term for radiation efficiency optimization, which is directly related to the antenna gain performance; the sidelobe suppression ratio is used as an independent gain term without normalization processing, simplifying the algorithm implementation complexity; the impedance matching deviation highlights the proportional relationship between the actual value and the target value through relative deviation calculation, strengthening the suppression of reflection loss; the normalization processing of the resonant frequency error balances the sensitivity differences in different frequency band designs; the configurable weight factor endows this method with strong scenario adaptability; this modular architecture also supports subsequent expansion of other performance indicators, such as cross-polarization suppression or environmental tolerance, improving the long-term applicability of the method.

[0017] A further setting is that the S400 specifically includes the following steps: S410. Encode the upper base length, lower base length, and height of the right trapezoid in the geometric parameters into a chromosome gene sequence, using real number encoding; S420. Generate offspring individuals through crossover operations; S430. Calculate the fitness value of each generation of individuals, where the fitness value is the normalized optimization objective function value, and select individuals within the set range of fitness rankings to enter the next generation; S440. If the fitness standard deviation of the population for N consecutive generations is less than the preset threshold and the normalized result of the optimization objective function converges to the range and between, then it is determined that convergence has occurred, and the geometric parameters corresponding to the current optimal individual are output; If convergence has not occurred but the maximum number of iterations is reached, force termination and select the historical optimal individual as the result; If the above conditions are not met, continue to execute S420 to S430 for iterative optimization.

[0018] By adopting the above technical solutions, relying on the global optimization ability and adaptive termination mechanism of the genetic algorithm, the nonlinear optimization problem of the parameter space of the right trapezoid half-mode resonator is overcome; the real number encoding directly reflects the physical meaning of the geometric parameters, avoiding the precision loss and decoding complexity of binary encoding, and improving the algorithm search efficiency; the crossover and mutation operations explore non-intuitive combinations of the upper base, lower base, and height globally, breaking through the limitations of manual experience, especially discovering high-performance parameter regions that are difficult to reach by traditional design methods in the case of non-symmetric structures of right trapezoids; the retention strategy maintains population diversity by selecting the top 20% of individuals in each generation to prevent premature convergence, while the double termination conditions of the fitness standard deviation criterion and the maximum number of iterations intelligently balance the input of computing resources and the requirements of optimization accuracy; this method shows significant advantages in solving multi-parameter coupling and high-dimensional nonlinear optimization problems, providing a general algorithm framework for the design of complex electromagnetic structures.

[0019] A further setting is that the S600 specifically includes the following steps: S610. Based on the secondary verification result of S500, extract the unqualified parameter types and deviation directions, including: If the main lobe width exceeds the preset main lobe width target value, it is determined that the radiation efficiency needs to be optimized, and the deviation direction is that the main lobe width exceeds the limit; If the side lobe suppression ratio is less than the preset side lobe suppression ratio threshold, it is determined that the side lobe suppression is insufficient, and the deviation direction is that the side lobe suppression is insufficient; If the impedance matching bandwidth does not cover the target operating frequency range or the resonance frequency deviation value exceeds the preset resonance frequency error threshold, it is determined that the impedance matching or the resonance frequency needs to be adjusted, and the deviation direction is impedance / resonance deviation; S620. Determine the parameter adjustment strategy according to the deviation direction, including: If the deviation direction is that the main lobe width exceeds the limit or the side lobe suppression is insufficient, the position of the feeding port is preferentially adjusted; If the deviation direction is impedance / resonance deviation, the thickness of the metal patch and the longitudinal embedding depth of the feeding port are preferentially adjusted; After executing the parameter adjustment strategy of S620, update the adjusted parameters to the initial structure parameters of S100, and re-execute S200 to S500 to generate new electromagnetic field distribution characteristics and verification results; S640. Judge the iteration termination conditions, including: If the updated parameters pass the primary verification of S200 or the secondary verification of S500 in the re-executed process of S200 to S500, output the final design; If not, repeat S610 to S630 until the preset maximum iteration number is reached and / or all parameters meet the standards.

[0020] By adopting the above technical solution, precise diagnosis of design defects and parameter self-healing are realized through a closed-loop feedback mechanism; based on the deviation direction analysis of the secondary verification result, a causal association model between performance indicators and physical parameters is established. For example, the excessive main lobe width is attributed to insufficient radiation efficiency, thereby triggering the adjustment of the feeding port position; the impedance matching problem is associated with the collaborative optimization of the metal patch thickness and the feeding embedding depth; the priority adjustment strategy dynamically allocates optimization resources according to the deviation type, avoiding the blindness and conflict risk of parameter adjustment. For example, when both the main lobe broadening and impedance mismatch occur simultaneously, the feeding position is preferentially optimized to quickly improve the radiation characteristics, and then the metal thickness is finely adjusted to solve the impedance problem; after the parameters are updated, the full-process verification is restarted to form a self-evolving design loop, gradually approaching the global optimal solution, and the dual termination mechanism of the maximum iteration number and the compliance condition ensures the feasibility of engineering implementation; this method significantly enhances the fault tolerance and adaptive ability of the design process, and is especially suitable for the development of highly reliable antennas under multiple constraint conditions.

[0021] The present invention also provides an antenna optimization system based on a right trapezoidal half-mode resonator, including: A parameter acquisition unit, configured to execute S100 to acquire the initial structural parameters of the right trapezoidal half-mode resonator, including the dielectric constant of the substrate material, geometric parameters, metal patch thickness, and feed port position; A simulation modeling unit, configured to execute S200 to construct a three-dimensional electromagnetic field simulation model based on the initial structural parameters and calculate the electromagnetic field distribution characteristics through the finite element analysis method; A primary verification unit, configured to verify whether the simulation result of S200 meets the standard. If it meets the standard, the final design is output; otherwise, the optimization process is triggered; An optimization target generation unit, configured to execute S300 to extract the main lobe width, side lobe suppression ratio, impedance matching bandwidth, and resonant frequency deviation value of the radiation pattern and generate an optimization target function; A genetic algorithm optimization unit, configured to execute S400 to iteratively optimize the geometric parameters using the genetic algorithm and dynamically adjust the proportional relationship between the upper base length, lower base length, and height of the right trapezoid; A secondary verification unit, configured to execute S500 to recalculate and verify the electromagnetic field distribution characteristics based on the optimized parameters. If it meets the standard, the final design is output; otherwise, the parameter adjustment process is triggered; A parameter adjustment and iteration control unit, configured to execute S600 to adjust the feed port position and metal patch thickness according to the verification result, update them to the parameter acquisition unit, and control the simulation modeling unit, primary verification unit, optimization target generation unit, genetic algorithm optimization unit, and secondary verification unit to execute again until the termination condition is met.

[0022] In summary, the present invention has the following beneficial effects: It transforms the traditional trial-and-error design relying on experience into a data-driven and algorithm-optimized method. By improving the parameter initialization accuracy, strengthening the credibility of electromagnetic field simulation, constructing a multi-objective optimization function, and integrating an adaptive feedback mechanism, it solves the problem that it is difficult for traditional design methods to achieve the collaborative optimization of multiple parameters under complex electromagnetic coupling effects. BRIEF DESCRIPTION OF THE DRAWINGS

[0023] Figure 1 It is the main process block diagram in the embodiment; Figure 2 It is the main process schematic diagram in the embodiment; Figure 3 It is the sub-process schematic diagram of S240 in the embodiment; Figure 4 It is the sub-process schematic diagram of S300 in the embodiment; Figure 5It is a schematic diagram of the sub - process of Embodiment S600; Figure 6 It is a system block diagram in the embodiment. Specific implementation manners

[0024] The present invention will be further described in detail below with reference to the accompanying drawings.

[0025] As shown in the Figures 1 to 6 accompanying drawings; This embodiment discloses an antenna optimization method based on a right - angled trapezoidal half - mode resonator, including the following steps: S100. Obtain the initial structural parameters of the right - angled trapezoidal half - mode resonator; wherein, the initial structural parameters include the dielectric constant of the substrate material, geometric parameters, metal patch thickness, and feed port position, and the geometric parameters include the upper base length, lower base length, and height of the right - angled trapezoid; S200. Construct a three - dimensional electromagnetic field simulation model based on the initial structural parameters, and calculate the electromagnetic field distribution characteristics of the right - angled trapezoidal half - mode resonator through the finite element analysis method, and conduct a primary verification on the electromagnetic field distribution characteristics; if it is determined that the verification result meets the standard, output the current initial structural parameters as the final design; otherwise, execute S300; S300. Extract the main lobe width, side lobe suppression ratio, impedance matching bandwidth, and resonance frequency deviation value of the radiation pattern based on the electromagnetic field distribution characteristics, and generate an optimization objective function based on the preset performance indicators; the optimization objective function includes a radiation efficiency weight factor, a bandwidth maximization coefficient, an impedance matching optimization coefficient, and a resonance frequency error weight factor; S400. Use the genetic algorithm to iteratively optimize the geometric parameters of the right - angled trapezoidal half - mode resonator, dynamically adjust the proportional relationship between the upper base length, lower base length, and height until the optimization objective function converges to the preset range; S500. Recalculate the electromagnetic field distribution characteristics based on the optimized geometric parameters, and conduct a secondary verification on the electromagnetic field distribution characteristics; if it is determined that the verification result meets the standard, output the current initial structural parameters as the final design; otherwise, execute S600; S600. Adjust the feed port position and metal patch thickness according to the deviation direction, update the updated parameters to the initial structural parameters of S100, and re - execute the steps of S200 to S500 until the termination condition is met.

[0026] Specifically, S100 specifically includes the following steps: S110. Prepare a standard test sample of the substrate material, and measure the dielectric constant of the substrate material in the target frequency band through the coaxial air - line method; then, use a vector network analyzer to verify the stability of the dielectric constant in the target frequency band to ensure that the real - part fluctuation range is lower than the preset threshold and the imaginary part approaches zero; S120. According to the target operating frequency range and the dielectric constant of the substrate material, use the equivalent circuit model of the half-mode resonator to derive the ratio of the initial upper base length to the lower base length of the right trapezoid, such that the difference between the lower base length and the upper base length is 1.2 to 1.8 times the height; S130. Based on the propagation path loss model of electromagnetic waves in the right trapezoid structure and the dielectric constant of the substrate material, determine that the value range of the metal patch thickness is 0.05 to 0.12 , where is the center wavelength of the target operating frequency; S140. Based on the input impedance characteristics of the equivalent circuit model of the half-mode resonator, calculate the theoretical matching position of the feeding port, analyze the surface current density distribution through three-dimensional electromagnetic field simulation, and adjust the feeding port to the current standing wave node position; then, iteratively optimize the lateral offset and longitudinal embedding depth of the feeding port until the real part of the input impedance approaches the target value and the imaginary part approaches zero.

[0027] Example 1 The process of measuring the dielectric constant of the substrate material is as follows: Select FR-4 epoxy glass fiber as the substrate material and cut it into a standard test sample of 50 mm × 50 mm; use the coaxial air line method to measure the dielectric constant in the target frequency band of 2.4 GHz, and the measured real part of the dielectric constant is 4.3 and the imaginary part approaches zero; scan in the range of 2.3 GHz to 2.5 GHz through a vector network analyzer to confirm that the fluctuation range of the dielectric constant is less than ±0.1.

[0028] The process of deriving the initial geometric parameters is as follows: The target operating frequency is 2.4 GHz, and the corresponding wavelength is 125 mm; according to the equivalent circuit model of the half-mode resonator, set the upper base length a = 20 mm, the lower base length b = 40 mm, and the height h = 15 mm of the right trapezoid, satisfying b - a = 4 / 3h; The process of determining the metal patch thickness is as follows: According to the propagation path loss model, the metal patch thickness is in the range of 6.25 mm to 15 mm; The process of optimizing the feeding port position is as follows: Based on the input impedance characteristics, the initial feeding port is located at the midpoint of the bottom edge of the right trapezoid, the lateral offset is 0 mm, and the longitudinal embedding depth is 2 mm; analyze the surface current distribution through three-dimensional electromagnetic simulation and adjust the feeding port to the lowest point of the current density to make the real part of the input impedance close to 50 Ω.

[0029] Specifically, S200 specifically includes the following steps: S210. Build a three-dimensional electromagnetic field simulation model based on the initial structural parameters, including the following sub-steps: According to the upper base length, lower base length and height of the right trapezoid in the geometric parameters, a three-dimensional electromagnetic field simulation model of the right trapezoid half-mode resonator is constructed, and the boundary size of the three-dimensional electromagnetic field simulation model is jointly constrained by the dielectric constant of the substrate material and the thickness of the metal patch; The specific constraint relationship is: ; Among them, is the boundary size; is the dielectric constant of the substrate material; is the thickness of the metal patch; is the height of the right trapezoid in the geometric parameter definition; is the preset proportionality coefficient; Based on the thickness of the metal patch and the dielectric constant of the substrate material, calculate the electric field intensity gradient distribution in the three-dimensional electromagnetic field simulation model, and mark the area with a gradient value higher than the preset threshold as the high-density grid area; The high-density grid area is encrypted and divided using tetrahedral unstructured grids to generate high-density grid data. The grid side length is set to 1 / 20 to 1 / 30 of the center wavelength of the target operating frequency and is inversely proportional to the thickness of the metal patch; The area in the geometric solid model except the high-density grid area is divided using hexahedral structured grids to generate low-density grid data. The grid step size gradually increases along the height direction of the right trapezoid in the geometric parameters, and the step size increment has a linear proportional relationship with the height of the right trapezoid; S220. Define the dielectric constant attribute and wave port excitation source in the three-dimensional electromagnetic field simulation model, including the following sub-steps: Define the dielectric constant attribute in the substrate material area of the three-dimensional electromagnetic field simulation model, and its value is directly referenced from the dielectric constant of the substrate material in the initial structure parameters; Load the wave port excitation source at the position of the feeding port in the initial structure parameters, and its impedance matching parameter is calculated based on the thickness of the metal patch and the dielectric constant of the substrate material; The specific calculation process is: ; Among them, is the impedance matching parameter; is the vacuum permeability; is the vacuum permittivity; is the center wavelength of the target operating frequency; Set the perfectly matched layer absorbing boundary condition on the periphery of the simulation domain of the three-dimensional electromagnetic field simulation model. The layer thickness is 1.5 to 2 times the height of the right trapezoid in the geometric parameters, and the gradual conductivity parameter is optimized according to the dielectric constant of the substrate material; S230. Calculate the electromagnetic field distribution characteristics by the finite element analysis method, and generate the radiation pattern, impedance matching bandwidth, and resonant frequency deviation value corresponding to S300, including the following sub-steps: Based on the target operating frequency range, set the frequency scanning range of the finite element solver, and the frequency sampling interval is calculated according to the dielectric constant of the substrate material and the thickness of the metal patch in the initial structure parameters; The specific calculation process is as follows: ; Among them, is the frequency sampling interval; c is the speed of light; Based on the high-density grid data and low-density grid data generated by S210, and the dielectric constant attributes and wave port excitation sources defined by S220, solve the Maxwell's equations by the finite element analysis method, and calculate the three-dimensional electric field distribution, magnetic field distribution, and surface current density distribution of the right trapezoidal half-mode resonator; Extract the data of the surface current density distribution, generate a normalized current density distribution map, and mark the positions of the current standing wave nodes, and compare and verify with the position of the feeding port in S100; Based on the three-dimensional electric field distribution and magnetic field distribution, calculate the radiation pattern of the antenna, and extract the main lobe width and sidelobe suppression ratio; Based on the parameter calculation results of the wave port excitation source, extract the real part and imaginary part of the input impedance, and generate the impedance matching bandwidth; Based on the real part and imaginary part of the input impedance, calculate the reflection coefficient ; ; Among them, is the input impedance, is the characteristic impedance, usually set to 50Ω; The impedance matching bandwidth is defined as the frequency range when the reflection coefficient ≤0.1.

[0030] Through the simulation results within the target operating frequency range, determine the actual resonant frequency, calculate its deviation value from the target resonant frequency, and obtain the resonant frequency deviation value; S240. Verify whether the main lobe width, sidelobe suppression ratio, impedance matching bandwidth, and resonant frequency deviation value of the radiation pattern meet the standards; S250. If it is determined that the verification result meets the standards, output the current initial structure parameters as the final design; If it is determined that the verification result does not meet the standards, use the main lobe width, sidelobe suppression ratio, impedance matching bandwidth, and resonant frequency deviation value of the radiation pattern as the input parameters of S300.

[0031] Specifically, S240 specifically includes the following steps: Determine whether the main lobe width is less than or equal to a preset main lobe width target value; Determine whether the sidelobe suppression ratio is greater than or equal to a preset sidelobe suppression ratio threshold; Determine whether the impedance matching bandwidth covers the target operating frequency range; Determine whether the resonant frequency deviation value is less than or equal to a preset resonant frequency error threshold; If all the above conditions are met, determine that the verification result is qualified; otherwise, determine that the verification result is unqualified.

[0032] Embodiment 2 Construct a right trapezoidal half-mode resonator model in 3D electromagnetic simulation, with dimensions a = 20mm, b = 40mm, h = 15mm, and the boundary dimension ≈10.8mm.

[0033] After mesh division, the high-density mesh area is the area where the gradient value is greater than 100 V / m, close to the feeding port, and the mesh side length is about 5mm; the mesh step size in the high-density mesh area gradually increases from 1mm to 5mm; The impedance matching parameters in the wave port excitation source ≈50Ω.

[0034] Extract the main lobe width of 30° and the sidelobe suppression ratio of 18 dB from the radiation pattern; The reflection coefficient in the impedance matching bandwidth ≤0.1, the bandwidth is 2.35 GHz - 2.45 GHz, covering the target operating frequency range of 2.4 GHz ± 50 MHz; The actual resonant frequency is 2.38 GHz, and the calculated resonant frequency deviation value is 20 MHz; The verification result is that the main lobe width exceeds the limit and the sidelobe suppression ratio is insufficient, triggering S300.

[0035] Specifically, S300 specifically includes the following steps: S310. Based on the main lobe width, sidelobe suppression ratio, impedance matching bandwidth, and resonant frequency deviation value in the radiation pattern generated in S200, extract the main lobe width, sidelobe suppression ratio, real and imaginary parts of the input impedance, and the resonant frequency deviation value; S320. Based on the extracted main lobe width, sidelobe suppression ratio, real and imaginary parts of the input impedance, and the resonant frequency deviation value, define an optimization objective function according to the preset performance indicators; S330. Normalize the optimization objective function and map it to the [0,1] interval; S340. Determine whether the normalized result of the optimization objective function converges to the preset range and between, where The value is 0.85, the value is 0.95; if the convergence condition is met, the current geometric parameters are output as the optimization result; otherwise, go to S400 for iterative optimization.

[0036] Specifically, the optimization objective function in S320 includes: Calculating the normalized difference between the main lobe width and the preset main lobe width target value with the radiation efficiency weight factor as the weight; Taking the bandwidth maximization coefficient as the weight and directly using the sidelobe suppression ratio as the gain term; Calculating the relative deviation between the real part of the input impedance and the preset real part target value of the input impedance with the impedance matching optimization coefficient as the weight; Calculating the normalized difference between the resonant frequency deviation value and the preset resonant frequency error threshold with the resonant frequency error weight factor as the weight.

[0037] The optimization objective function is specifically: ; where , , , are the radiation efficiency weight factor, the bandwidth maximization coefficient, the impedance matching optimization coefficient, and the resonant frequency error weight factor respectively, and satisfy ; is the main lobe width; is the preset main lobe width target value; is the sidelobe suppression ratio; is the real part of the input impedance; is the preset real part target value of the input impedance; is the resonant frequency deviation value; is the preset resonant frequency error threshold.

[0038] Embodiment 3 Extract parameters = 30°, = 18 dB, = 48 Ω, = 20 MHz; the weight distribution is specifically , , , are 0.4, 0.3, 0.2, and 0.1 respectively; After calculation, the optimization objective function = 5.06, and the normalized result obtained after mapping to the [0, 1] interval is 0.72, which is not within the preset range and between, triggering S400.

[0039] Specifically, S400 specifically includes the following steps: S410. Encode the upper base length, lower base length, and height of the right trapezoid in the geometric parameters into the chromosome gene sequence, using the real number encoding method; set the population size to 50 to 100 groups, and randomly generate the initial individuals within the preset geometric parameter range; S420. Generate offspring individuals through the crossover operation, set the crossover probability to 0.6 to 0.8, the mutation probability to 0.01 to 0.05, and the mutation step size decreases adaptively with the number of iterations; S430. Calculate the fitness value of each generation of individuals, where the fitness value is the normalized optimization objective function value, and select the individuals within the set range of fitness rankings to enter the next generation; the set range is the top 20% of the fitness rankings; S440. If the fitness standard deviation of the population for 5 consecutive generations is less than the preset threshold and the normalized result of the optimization objective function converges to the preset range and within, then determine convergence and output the geometric parameters corresponding to the current optimal individual; If it does not converge but reaches the maximum number of iterations, force termination and select the historical optimal individual as the result; If the above conditions are not met, continue to execute S420 to S430 for iterative optimization.

[0040] Example 4 The population size is 80 groups, the parameter range is a ∈ [15, 25] mm, b ∈ [35, 45] mm, h ∈ [10, 20] mm; In the crossover operation, the crossover probability is 0.7, the mutation probability is 0.03, and the mutation step size decreases from 0.5 mm to 0.1 mm with the number of iterations; The convergence determination result is: the fitness standard deviation of 5 consecutive generations is less than 0.01 and the normalized result of the optimization objective function converges to the preset range ∈ [0.85, 0.95]; the parameters of the optimal individual in the 15th generation are a = 22 mm, b = 38 mm, h = 13 mm.

[0041] Specifically, S600 specifically includes the following steps: S610. Based on the secondary verification results of S500, extract the unqualified parameter types and deviation directions, including: If the main lobe width exceeds the preset main lobe width target value, it is determined that the radiation efficiency needs to be optimized, and the deviation direction is that the main lobe width exceeds the limit; If the sidelobe suppression ratio is less than the preset sidelobe suppression ratio threshold, it is determined that the sidelobe suppression is insufficient, and the deviation direction is that the sidelobe suppression is insufficient; If the impedance matching bandwidth does not cover the target operating frequency range or the deviation value of the resonant frequency exceeds the preset resonant frequency error threshold, it is determined that the impedance matching or the resonant frequency needs to be adjusted, and the deviation direction is the impedance / resonant deviation; S620. Determine the parameter adjustment strategy according to the deviation direction, including: If the deviation direction is that the main lobe width exceeds the limit or the side lobe suppression is insufficient, the position of the feeding port is preferentially adjusted; If the deviation direction is the impedance / resonant deviation, the thickness of the metal patch and the longitudinal embedding depth of the feeding port are preferentially adjusted; Specifically, based on the initial position of the feeding port in S100, calculate the lateral offset and the adjustment amount of the longitudinal embedding depth ; The adjustment formula is: ; ; Where, is the main lobe width; is the preset target value of the main lobe width; is the deviation value of the resonant frequency; is the preset resonant frequency error threshold; and are preset proportionality coefficients, and the value range is from 0.1 to 0.5; It should be added that needs to be restricted within the minimum and maximum allowable adjustment amounts of the longitudinal embedding depth; According to the value range of the metal patch thickness of 0.05 to 0.12 , increase or decrease the thickness in a preset step .

[0042] S630. After executing the parameter adjustment strategy of S620, update the adjusted parameters to the initial structural parameters of S100, and re-execute S200 to S500 to generate new electromagnetic field distribution characteristics and verification results; S640. Judge the iteration termination conditions, including: If the updated parameters pass the first verification of S200 or the second verification of S500 in the re-executed S200 to S500 process, output the final design; If not, repeat S610 to S630 until the preset maximum number of iterations is reached and / or all parameters meet the standards.

[0043] Example 5 Update the parameters a = 22mm, b = 38mm, h = 13mm, and re-execute S200; The verification results show that the main lobe width is 24°, the side lobe suppression ratio is 21 dB, the impedance matching bandwidth is 2.38 GHz - 2.42 GHz, and the resonant frequency deviation value is 10 MHz; Among them, the impedance matching bandwidth does not cover the target frequency band, and it is necessary to adjust the thickness of the metal patch and the longitudinal embedding depth of the feeding port: The thickness of the metal patch is increased by 0.01 , and it becomes 11.25 mm; the longitudinal embedding depth of the feeding port is 0.06, and the position is updated to 1.56 mm; finally, after the update, the bandwidth is extended to 2.36 GHz - 2.44 GHz, and all parameters meet the standards, and the final design is output.

[0044] This embodiment also discloses an antenna optimization system based on a right-angled trapezoidal half-mode resonator, including: A parameter acquisition unit, configured to execute S100 to acquire the initial structural parameters of the right-angled trapezoidal half-mode resonator, including the dielectric constant of the substrate material, geometric parameters, the thickness of the metal patch, and the position of the feeding port; A simulation modeling unit, configured to execute S200 to construct a three-dimensional electromagnetic field simulation model based on the initial structural parameters, and calculate the electromagnetic field distribution characteristics by the finite element analysis method; A primary verification unit, configured to verify whether the simulation results of S200 meet the standards. If they meet the standards, the final design is output; otherwise, the optimization process is triggered; An optimization target generation unit, configured to execute S300 to extract the main lobe width, side lobe suppression ratio, impedance matching bandwidth, and resonant frequency deviation value of the radiation pattern, and generate an optimization target function; A genetic algorithm optimization unit, configured to execute S400 to iteratively optimize the geometric parameters by using the genetic algorithm, and dynamically adjust the proportional relationship between the upper base length, lower base length, and height of the right-angled trapezoid; A secondary verification unit, configured to execute S500 to recalculate the electromagnetic field distribution characteristics based on the optimized parameters and perform verification. If they meet the standards, the final design is output; otherwise, the parameter adjustment process is triggered; A parameter adjustment and iteration control unit, configured to execute S600 to adjust the position of the feeding port and the thickness of the metal patch according to the verification results, update them to the parameter acquisition unit, and control the simulation modeling unit, primary verification unit, optimization target generation unit, genetic algorithm optimization unit, and secondary verification unit to execute again until the termination condition is met.

[0045] This specific embodiment is only an interpretation of the present invention, and it is not a limitation of the present invention. Those skilled in the art can make modifications without creative contributions to this embodiment according to needs after reading this specification, but as long as they are within the scope of the claims of the present invention, they are protected by the patent law.

Claims

1. An antenna optimization method based on a right-angle trapezoidal half-mode resonator, characterized in that: The following steps are involved: S100, obtaining initial structural parameters of a right-angled trapezoidal half-mode resonator; wherein the initial structural parameters include a dielectric constant of a substrate material, geometric parameters, a thickness of a metal patch, and a position of a feeding port, and the geometric parameters include an upper base length, a lower base length, and a height of the right-angled trapezoid; S200, constructing a three-dimensional electromagnetic field simulation model based on the initial structural parameters, and calculating the electromagnetic field distribution characteristics of the right-angle trapezoidal half-mode resonator by finite element analysis, and verifying the electromagnetic field distribution characteristics; if the verification result is determined to be up to standard, outputting the current initial structural parameters as the final design; otherwise, executing S300; S300, extracting the main lobe width, side lobe suppression ratio, impedance matching bandwidth and resonant frequency deviation value of the radiation pattern according to the electromagnetic field distribution characteristics, and generating an optimization objective function based on preset performance indicators; the optimization objective function includes a radiation efficiency weight factor, a bandwidth maximization coefficient, an impedance matching optimization coefficient and a resonant frequency error weight factor; S400, iteratively optimizing the geometric parameters of the right-angle trapezoidal half-mode resonator by using a genetic algorithm, and dynamically adjusting the proportional relationship between the upper base length, the lower base length and the height, until the optimization objective function converges to a preset range; S500, recalculating the electromagnetic field distribution characteristics based on the optimized geometric parameters, and performing a second verification on the electromagnetic field distribution characteristics; if the verification result is determined to be up to standard, outputting the current initial structural parameters as the final design; otherwise, executing S600; S600, adjusting the feeding port position and the metal patch thickness according to the deviation direction, updating the updated parameters to the initial structural parameters of S100, and re-executing steps S200 to S500 until the termination condition is met.

2. The antenna optimization method based on the right-angle trapezoidal half-mode resonator according to claim 1 is characterized in that: The S100 specifically includes the following steps: S110, preparing a standard test sample of the substrate material, and measuring the dielectric constant of the substrate material within the target frequency band by a coaxial air line method; then, using a vector network analyzer to verify the stability of the dielectric constant within the target frequency band, ensuring that the real part fluctuation range is lower than a preset threshold and the imaginary part approaches zero; S120, deriving the ratio of the initial upper base length to the lower base length of the right-angle trapezoid using a half-mode resonator equivalent circuit model according to the target operating frequency range and the dielectric constant of the substrate material; S130, determining a value range of the metal patch thickness based on a propagation path loss model of an electromagnetic wave in a right-angle trapezoidal structure and a dielectric constant of the substrate material; S140. Based on the input impedance characteristics of the half-mode resonator equivalent circuit model, the theoretical matching position of the feeding port is calculated, the surface current density distribution is analyzed through three-dimensional electromagnetic field simulation, and the feeding port is adjusted to the current standing wave node position; then, the lateral offset and longitudinal embedding depth of the feeding port are iteratively optimized until the real part of the input impedance approaches the target value and the imaginary part approaches zero.

3. The antenna optimization method based on the right-angle trapezoidal half-mode resonator according to claim 2 is characterized in that: The S200 specifically includes the following steps: S210, constructing a three-dimensional electromagnetic field simulation model based on the initial structural parameters, comprising the following sub-steps: According to the upper base length, lower base length and height of the right-angled trapezoid in the geometric parameters, a three-dimensional electromagnetic field simulation model of the right-angled trapezoidal half-mode resonator is constructed, and the boundary size of the three-dimensional electromagnetic field simulation model is constrained by the dielectric constant of the substrate material and the thickness of the metal patch; Based on the thickness of the metal patch and the dielectric constant of the substrate material, the electric field intensity gradient distribution in the three-dimensional electromagnetic field simulation model is calculated, and the area where the gradient value is higher than a preset threshold is marked as a high-density grid area; The high-density grid area is divided into encrypted tetrahedral unstructured grids to generate high-density grid data; Hexahedral structured meshing is used to divide the areas except the high-density mesh area in the geometric solid model to generate low-density mesh data; S220, defining dielectric constant properties and wave port excitation sources in a three-dimensional electromagnetic field simulation model, including the following sub-steps: Define a dielectric constant property in a substrate material region of a three-dimensional electromagnetic field simulation model, wherein the dielectric constant property is directly referenced by the dielectric constant of the substrate material in the initial structural parameters; A load wave port excitation source is placed at the feeding port position in the initial structural parameters, and its impedance matching parameters are calculated based on the thickness of the metal patch and the dielectric constant of the substrate material.

4. The antenna optimization method based on the right-angle trapezoidal half-mode resonator according to claim 3 is characterized in that: The S200 specifically further includes the following steps: S230, calculating the electromagnetic field distribution characteristics by finite element analysis method, and generating the radiation pattern, impedance matching bandwidth and resonant frequency deviation value corresponding to S300; including the following sub-steps: Based on the target operating frequency range, the frequency scanning range of the finite element solver is set, and the frequency sampling interval is calculated according to the dielectric constant of the substrate material and the thickness of the metal patch in the initial structural parameters; Based on the high-density mesh data and low-density mesh data generated by S210, as well as the dielectric constant properties and wave port excitation sources defined by S220, the finite element analysis method is used to solve Maxwell's equations to calculate the three-dimensional electric field distribution, magnetic field distribution and surface current density distribution of the right-angle trapezoidal half-mode resonator; Extract the data of the surface current density distribution, generate a normalized current density distribution diagram, mark the current standing wave node position, and compare and verify it with the feeding port position in S100; Based on the three-dimensional electric field distribution and magnetic field distribution, the radiation pattern of the antenna is calculated, and the main lobe width and the side lobe suppression ratio are extracted; Based on the parameter calculation results of the wave port excitation source, the real and imaginary parts of the input impedance are extracted to generate the impedance matching bandwidth; The actual resonant frequency is determined through simulation results within the target operating frequency range, and its deviation from the target resonant frequency is calculated to obtain the resonant frequency deviation value; S240, verify whether the main lobe width, side lobe suppression ratio, impedance matching bandwidth and resonant frequency deviation of the radiation pattern meet the standards; S250, if the verification result is determined to be up to standard, output the current initial structural parameters as the final design; If it is determined that the verification result does not meet the standard, the main lobe width, side lobe suppression ratio, impedance matching bandwidth and resonant frequency deviation value of the radiation pattern are used as input parameters of S300.

5. The antenna optimization method based on right-angle trapezoidal half-mode resonator according to claim 4 is characterized in that: The S240 specifically includes the following steps: Determine whether the main lobe width is less than or equal to a preset main lobe width target value; Determine whether the sidelobe suppression ratio is greater than or equal to a preset sidelobe suppression ratio threshold; Determine whether the impedance matching bandwidth covers the target operating frequency range; Determine whether the resonant frequency deviation value is less than or equal to a preset resonant frequency error threshold; If all the above conditions are met, the verification result is judged to be up to standard; otherwise, the verification result is judged to be not up to standard.

6. The antenna optimization method based on right-angle trapezoidal half-mode resonator according to claim 4 is characterized in that: The S300 specifically includes the following steps: S310, extracting the main lobe width, the side lobe suppression ratio, the real part and the imaginary part of the input impedance, and the resonant frequency deviation value based on the main lobe width, the side lobe suppression ratio, the impedance matching bandwidth, and the resonant frequency deviation value of the radiation pattern generated in S200; S320, based on the extracted main lobe width, side lobe suppression ratio, real part and imaginary part of input impedance, and resonant frequency deviation value, define an optimization objective function according to a preset performance indicator; S330, normalizing the optimization objective function and mapping it to the interval [0, 1]; S340: Determine whether the normalized result of the optimization objective function converges to a preset range. and If the convergence condition is met, the current geometric parameters are output as the optimization result; otherwise, enter S400 for iterative optimization.

7. The antenna optimization method based on right-angle trapezoidal half-mode resonator according to claim 6 is characterized in that: The optimization objective function in S320 includes: Taking the radiation efficiency weight factor as the weight, the normalized difference between the main lobe width and the preset main lobe width target value is calculated; Taking the bandwidth maximization coefficient as the weight, the sidelobe suppression ratio is directly used as the gain term; Using the impedance matching optimization coefficient as a weight, calculating the relative deviation between the real part of the input impedance and a preset target value of the real part of the input impedance; The normalized difference between the resonant frequency deviation value and the preset resonant frequency error threshold is calculated using the resonant frequency error weight factor as the weight.

8. The antenna optimization method based on right-angle trapezoidal half-mode resonator according to claim 5 is characterized in that: The S400 specifically includes the following steps: S410, encoding the upper base length, lower base length and height of the right-angled trapezoid in the geometric parameters into a chromosome gene sequence, using a real number encoding method; S420, generating offspring individuals through a crossover operation; S430, calculating the fitness value of each generation of individuals, where the fitness value is the normalized optimization objective function value, and selecting individuals within a set fitness ranking range to enter the next generation; S440: If the fitness standard deviation of the population for N consecutive generations is less than the preset threshold and the normalized result of the optimization objective function converges to the preset range and If the value is within the range of , it is determined to be convergent and the geometric parameters corresponding to the current optimal individual are output; If convergence has not occurred but the maximum number of iterations has been reached, the algorithm is forced to terminate and the best individual in history is selected as the result. If the above conditions are not met, continue to execute S420 to S430 for iterative optimization.

9. The antenna optimization method based on right-angle trapezoidal half-mode resonator according to claim 1, characterized in that: The S600 specifically includes the following steps: S610: Based on the secondary verification result of S500, extract the parameter types and deviation directions that do not meet the standards, including: If the main lobe width exceeds the preset main lobe width target value, it is determined that the radiation efficiency needs to be optimized, and the deviation direction is that the main lobe width exceeds the limit; If the sidelobe suppression ratio is less than the preset sidelobe suppression ratio threshold, it is determined that the sidelobe suppression is insufficient, and the deviation direction is insufficient sidelobe suppression; If the impedance matching bandwidth does not cover the target operating frequency range or the resonant frequency deviation value exceeds the preset resonant frequency error threshold, it is determined that the impedance matching or resonant frequency needs to be adjusted, and the deviation direction is the impedance / resonance deviation; S620, determining a parameter adjustment strategy according to the deviation direction, including: If the deviation direction is that the main lobe width exceeds the limit or the side lobe suppression is insufficient, the feed port position should be adjusted first; If the deviation direction is impedance / resonance deviation, the thickness of the metal patch and the longitudinal embedding depth of the feeding port are adjusted first; S630, after executing the parameter adjustment strategy of S620, the adjusted parameters are updated to the initial structural parameters of S100, and S200 to S500 are re-executed to generate new electromagnetic field distribution characteristics and verification results; S640, determining the iteration termination condition, including: If the updated parameters pass the primary verification of S200 or the secondary verification of S500 in the re-executed process of S200 to S500, the final design is output; If it fails, S610 to S630 are repeated until a preset maximum number of iterations is reached and / or all parameters meet the standards.

10. An antenna optimization system based on a right-angled trapezoidal half-mode resonator, applied to an antenna optimization method based on a right-angled trapezoidal half-mode resonator according to any one of claims 1 to 9, characterized in that: include: A parameter acquisition unit, used to execute S100, to acquire initial structural parameters of the right-angle trapezoidal half-mode resonator, including a dielectric constant of a substrate material, geometric parameters, a thickness of a metal patch, and a feeding port position; A simulation modeling unit, configured to execute S200, construct a three-dimensional electromagnetic field simulation model based on the initial structural parameters, and calculate electromagnetic field distribution characteristics by a finite element analysis method; The primary verification unit is used to verify whether the simulation results of S200 meet the standards. If so, the final design is output, otherwise the optimization process is triggered; An optimization target generating unit, used to execute S300, extract the main lobe width, side lobe suppression ratio, impedance matching bandwidth and resonant frequency deviation value of the radiation pattern, and generate an optimization target function; A genetic algorithm optimization unit, used to execute S400, iteratively optimize geometric parameters using a genetic algorithm, and dynamically adjust the proportional relationship between the upper base length, the lower base length, and the height of the right-angled trapezoid; A secondary verification unit is used to execute S500, recalculate the electromagnetic field distribution characteristics based on the optimized parameters and verify them, and output the final design if the standards are met, otherwise trigger the parameter adjustment process; The parameter adjustment and iteration control unit is used to execute S600, adjust the feeding port position and the metal patch thickness according to the verification result, update to the parameter acquisition unit, and control the simulation modeling unit, the primary verification unit, the optimization target generation unit, the genetic algorithm optimization unit and the secondary verification unit to re-execute until the termination condition is met.

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