Radome design method

Abstract

The invention discloses an antenna housing design method, and belongs to the field of antenna design. Aiming at the problems of high design complexity and high cost of the existing radome, the invention provides the radome design method, which comprises the following steps of: determining the working broadband range of the radome, and dividing the working broadband range into a plurality of working broadband sub-frequency bands; solving a design parameter corresponding to each working broadband sub-band; performing intersection solution on the plurality of design parameters to obtain an optimal solution; and verifying whether the optimal solution accords with global performance or not. According to the invention, the working broadband range is decomposed into a plurality of sub-bands, optimization design is independently carried out in each sub-band, and finally, an intersection optimal solution capable of meeting the performance requirements of all the sub-bands is searched, so that the high-performance and high-robustness design of the antenna housing in the whole broadband is realized; and a complex high-dimensional global optimization problem is decomposed into a plurality of simple low-dimensional sub-problems, so that the optimization efficiency and the success rate are greatly improved, and the computing power cost is reduced.

Description

TECHNICAL FIELD

[0001] The present application belongs to the field of antenna design, more particularly, to a radome design method. BACKGROUND

[0002] The radome is an important component to protect the antenna from the external environment. However, the existence of the radome will inevitably change the electromagnetic performance of the antenna, introducing a series of problems such as insertion phase delay (IPD), power transmission loss, beam deflection, side lobe lifting, etc. The traditional radome design method is usually optimized for single frequency or narrow band operation, which is difficult to meet the needs of modern wideband / ultra-wideband systems (such as C to Ka band). The specific difficulties are as follows: 1. Global parameter contradiction: within the wide frequency band, the electromagnetic performance requirements of the radome are often contradictory. For example, a thicker wall thickness is needed to achieve structural strength at low frequencies, but a thick wall will introduce serious resonance and mismatch at high frequencies, resulting in a sharp decline in transmission efficiency; 2. Optimization target conflict: it is very difficult to simultaneously optimize multiple frequency bands of wave transmission rate, phase consistency, beam pointing accuracy, etc. Traditional single structure or uniform gradient structure cannot achieve optimal performance throughout the wide frequency band; 3. High design complexity: using traditional full-band collaborative optimization algorithms, the computational load is huge, convergence is difficult, and it is easy to fall into a local optimal solution, making it difficult to obtain a design scheme with excellent global performance.

[0003] For example, Chinese patent application No. CN202411167142.7, published on November 12, 2024, discloses a radome mechatronic integrated optimization method based on sparrow search algorithm, including the following steps: step (1): input radome structure parameters and electrical parameters; step (2): determine the radome optimization target and optimization variable; step (3): convert multiple objectives into single objective optimization; step (4): take the radome optimization target function as the fitness function, determine the fitness function, and establish the optimization model; step (5): find the optimal target of the radome optimization model; step (6): initialize the population radome thickness parameters in the optimization algorithm; step (7): calculate the fitness value and classify the population; step (8): update the population radome thickness; step (9): determine whether the maximum number of iterations is met; step (10): output the optimal values of the pointing error and transmission loss. The shortcomings of this patent are: the sparrow search algorithm is a meta-heuristic optimization, which is suitable for single objective but may ignore the conflict between multiple objectives, especially in the wideband scenario, the requirements of different frequency points may be contradictory, and single objective optimization is easy to fall into local optimum.

[0004] For example, Chinese patent application No. CN201911337341.7, published on May 12, 2020, discloses a design optimization method for a wave-transparent, stealth, and heat-resistant radome, belonging to the field of radome design. The present invention establishes a mapping relationship between the radome design variables and the state parameters in order to convert the multi-objective optimization problem into a single-objective optimization problem that is easier to solve without introducing target weight factors, and to simultaneously optimize the electrical performance and stealth performance of the radome. The specific form of the radome design variables is determined, and the objective function and constraint conditions in the multi-disciplinary design optimization problem of the radome are determined. The stealth performance is represented by the electrical performance index, reducing the dimensionality of the objective function. A multi-disciplinary optimization module and an analysis module are constructed to obtain sensitivity information, construct a linear approximation function, and complete the multi-disciplinary design optimization using a single-level optimization algorithm. The shortcomings of this patent are: the method is complex, and the technical implementation threshold is high. SUMMARY

[0005] 1. Problem to be solved In view of the high complexity and high cost of existing radome design, the present invention provides a radome design method. The present invention divides the working bandwidth range into several sub-frequency bands, optimizes the design independently in each sub-frequency band, and finally finds the intersection optimal solution that meets the performance requirements of all sub-frequency bands, thereby realizing high-performance and high-robustness design of the radome in the entire wide frequency band. A complex high-dimensional global optimization problem is decomposed into multiple simple low-dimensional sub-problems, greatly improving optimization efficiency and success rate, and reducing the cost of computing power.

[0006] 2. Technical solution To solve the above problems, the present invention adopts the following technical solution.

[0007] A radome design method, comprising the following steps: S1: determining the working bandwidth range of the radome, and dividing the working bandwidth range into several working bandwidth sub-frequency bands; S2: solving the design parameters corresponding to each working bandwidth sub-frequency band; S3: performing intersection solving on the several design parameters to obtain an optimal solution; the several design parameters are the several design parameters corresponding to the several working bandwidth sub-frequency bands; S4: verifying whether the optimal solution meets the global performance.

[0008] Further, the step S2 specifically comprises the following steps: S21: establishing a radome parameterized model for each working bandwidth sub-frequency band; S22: defining an objective function for each working bandwidth sub-frequency band; S23: independently optimizing each working wideband sub-band by using an optimization algorithm to find the optimal design parameters corresponding to each working wideband sub-band.

[0009] Further, the step S23 of independently optimizing each working wideband sub-band further includes setting different priority optimization targets as constraint conditions according to the frequency range of the working wideband sub-band.

[0010] Further, the step S23 includes threshold judgment on a single working wideband sub-band, if the working wideband sub-band is less than a preset threshold, it is a low frequency band, and the IPD flatness is prioritized in independent optimization; if the working wideband sub-band is higher than the preset threshold, it is a high frequency band, and the IPD wave transmittance is prioritized in independent optimization.

[0011] Further, the step S21 specifically includes: parameterizing the geometric structure and material properties of the radome to obtain a set of variable design variables; establishing a mapping relationship model between the design variables and the electrical performance indicators of the radome in each working wideband sub-band.

[0012] Further, the objective function in the step S22 is a weighted combination of performance indicators in the working wideband sub-band.

[0013] Further, the optimal solution in the step S3 specifically includes searching for a common design parameter vector in the plurality of design parameters, and the common design parameter vector exists in the plurality of design parameters.

[0014] Further, the step S1 is divided according to one of the dispersion characteristics of the dielectric material, the different working modes of the antenna, and the different functional requirements of the antenna.

[0015] Further, the step S3 specifically includes substituting the optimal solution into the working wideband range model of the radome for electromagnetic simulation verification, if the global performance of the radome meets the requirements, the design is completed, and if the global performance of the radome cannot meet the requirements, the optimal solution is adjusted.

[0016] Further, the step S3 of adjusting the optimal solution includes taking the original optimal solution as a starting point, performing local optimization on the original optimal solution within the working wideband range of the radome to obtain a final optimal solution.

[0017] 3. Beneficial effects (1) This invention divides the working bandwidth of the radome into several sub-bands, optimizes each sub-band independently, and then searches for an optimal solution globally. The overall solution achieves better performance in each sub-band simultaneously, thereby significantly improving the average performance and performance uniformity of the radome throughout the entire broadband band, and ultimately significantly improving the comprehensive electromagnetic performance of the broadband radome. Furthermore, it decomposes the complex high-dimensional, multi-objective optimization problem into several simple low-dimensional sub-problems, fundamentally changing the complexity of the optimization problem, greatly improving design efficiency and optimization success rate, and reducing computational costs. At the same time, the optimal solution is the intersection of all design parameters, which means that the optimal solution has stronger adaptability to actual factors such as frequency changes, manufacturing tolerances, and material parameter fluctuations, thereby enhancing the robustness and reliability of the entire design. The entire design method can effectively solve the performance contradictions within the broadband band, with high overall computational efficiency and superior performance. (2) When optimizing each sub-band independently, the present invention sets different constraints for sub-bands in different frequency ranges, which can significantly improve the targeting and efficiency of the optimization process; by setting differentiated priority targets in different frequency bands, it essentially provides guidance for the independent optimization process of each sub-band, realizing performance consistency and feasibility across the entire frequency band; and the different constraints for low frequency and high frequency enable the low frequency optimization to ensure IPD performance while keeping its negative impact on transmittance within an acceptable range; similarly, the high frequency optimization, while pursuing high transmittance, also controls the degree of IPD degradation. (3) This invention establishes a model by combining design variables with the electrical performance indicators of the radome within the working broadband sub-band. This model can accurately and quantitatively reflect the impact of any minor adjustment of the design variables on the electrical performance indicators of a specific sub-band, ensuring the correctness of the optimization direction and improving the performance reliability of the final design. Furthermore, the objective function is a weighted combination of performance indicators within the working broadband sub-band, integrating multiple objectives into a single comprehensive evaluation index. This allows standard efficient single-objective optimization algorithms to be directly applied, greatly expanding the range of applicable algorithms and improving the solution efficiency. At the same time, by adjusting the weights of different performance indicators in the objective function, the design purpose can be clearly expressed, and the balance between different performance indicators can be flexibly adjusted, providing a flexible operational space. (4) When fine-tuning the optimal solution, the present invention starts with the original optimal solution and performs small-scale search optimization, which greatly improves efficiency and success rate, reduces computational cost, and avoids the algorithm from going off to a new and potentially unstable region. By using the previous optimization results as an efficient starting point and making precise fine-tuning with global performance as the final goal, the contradiction between efficiency and comprehensiveness in broadband optimization is successfully resolved. Attached Figure Description

[0018] Figure 1The flowchart of the present application. DETAILED DESCRIPTION

[0019] The present application will be further described below in connection with specific embodiments and drawings. Before the present application is described, it is to be understood that this application is directed to a radome facing a wideband or ultra-wideband (such as C to Ka band) system. Since the wideband or ultra-wideband has a problem of local parameter contradiction, which brings certain difficulty to the design of the radome, the technical solution of the present application is provided. Specifically as follows: As shown in Figure 1 , a radome design method comprises the following steps: S1: determining the working wideband range of the radome, and dividing the working wideband range into a plurality of working wideband sub-bands; Specifically, in step S1, the working wideband range [f min , f max ] of the radome and the index performance requirement of the radome are determined, the index performance requirement can be the wave permeability >T - dB, the insertion phase delay variation <Δφ°, the beam deflection <θ°, etc.; and then according to the change trend of the electromagnetic characteristics and the performance requirement, the wideband [f min , f max ] can be divided into N sub-bands S B1 , S B2 ,..., S BN with or without overlap; of course, the change trend of the electromagnetic characteristics and the performance requirement can be the dispersion characteristics of the dielectric material, different working modes of the antenna, different functional requirements of the system (such as search, tracking, and communication corresponding to different frequency bands, respectively); S2: solving the design parameters corresponding to each working wideband sub-band; it is explained here that S B1 , S B2 ,..., S BN each corresponds to a design parameter, and the design parameter is to find the optimal solution or approximate optimal solution set { X_i*} of S B1 , S B2 ,..., S BN by using an optimization algorithm; S3: performing intersection solving on the plurality of design parameters to obtain the optimal solution; The plurality of design parameters are the plurality of design parameters corresponding to the plurality of working wideband sub-bands; that is, S B1Corresponding to {X_1*}, SB2 corresponds to {X_2*}... Then step S2 obtains N sets of design parameter solution sets {X_1*}, {X_2*},..., {X_N*}, and a common solution is searched in the parameter solution sets, the common solution exists in (or is very close to) the optimization solution sets of all N sub-frequency bands, that is, the common solution ∈ {X_1*} ∩ {X_2*} ∩... ∩ {X_N*}, and the common solution is the optimal solution; Step S3 is to search for a common design parameter vector in several design parameters, and the common design parameter vector exists in the several design parameters.

[0020] S4: Verify whether the optimal solution meets the global performance, and further ensure the reliability of the optimal solution.

[0021] The embodiment decomposes the wide frequency band into several sub-frequency bands, independently optimizes and designs in each sub-frequency band, finally finds an intersection optimal solution meeting the performance requirements of all sub-frequency bands, and thus realizes high-performance and high-robustness design of the radome in the entire wide frequency band. The specific benefits are embodied in the following aspects: Significantly improve the comprehensive electromagnetic performance of the wideband radome: the traditional method often sacrifices the performance of part of the frequency band in order to achieve a compromise in the entire frequency band. The embodiment can achieve better performance in each sub-frequency band through independent optimization and global intersection searching of the sub-frequency band, thereby significantly improving the average performance and performance uniformity of the radome in the entire wide frequency band; Greatly improve the design efficiency and optimization success rate, and reduce the calculation cost: the complex high-dimensional and multi-objective optimization problem is decomposed into multiple simple low-dimensional sub-problems, which fundamentally changes the complexity of the optimization problem; Enhance the robustness and reliability of the design scheme: the "intersection solution" obtained by the embodiment is an excellent solution in each sub-frequency band, rather than a "compromise solution" of the entire frequency band. This means that the design parameters have stronger adaptability to actual factors such as frequency variation, manufacturing tolerance, and material parameter fluctuation.

[0022] In a specific embodiment, the step S2 specifically includes the following steps: S21: Establish a radome parameterized model for each working wideband sub-frequency band; specifically, the step S21 specifically includes: Parameterize the geometric structure and material properties of the radome to obtain a set of variable design variables; Establish a mapping relationship model between the design variables and the electrical performance indicators of the radome in each working wideband sub-frequency band; In step S21, the experience-dependent physical design (such as thickness, dielectric constant) is discretized into a set of controllable design variables, which lays a physical foundation for automatic optimization using subsequent optimization algorithms, and overcomes the subjectivity and inefficiency of the traditional trial-and-error method; meanwhile, the mapping relationship model can accurately and quantitatively reflect the influence of any slight adjustment of the design variable on the specific sub-band electrical performance index, and provides reliable gradient information or fitness evaluation basis for the optimization algorithm, ensuring the correctness of the optimization direction and the performance reliability of the final design scheme. S22: defining a target function for each working wideband sub-band; wherein as preferred, the target function is a weighted combination of performance indicators in the working wideband sub-band; it should be noted that in the design of radomes, multiple performance indicators such as transmission efficiency, pointing error, and sidelobe level often need to be considered simultaneously, and these indicators often conflict with each other; the weighted combination is used to define the target function, which combines multiple targets into a single comprehensive evaluation index, so that the standard efficient single-target optimization algorithm can be directly applied, greatly widening the selection range of applicable algorithms and improving the solving efficiency; and by adjusting the weight of different performance indicators in the target function, the performance indicators can be flexibly weighted, ensuring the stability and comprehensiveness of the entire optimization process. S23: using an optimization algorithm to independently optimize each working wideband sub-band to find the optimal design parameters corresponding to each working wideband sub-band.

[0023] Furthermore, in step S23, when each working wideband sub-band is independently optimized, different priority optimization targets are set as constraint conditions according to the frequency range of the working wideband sub-band.

[0024] More specifically, step S23 includes threshold judgment for a single working wideband sub-band, if the working wideband sub-band is less than a preset threshold, it is a low frequency band, and IPD flatness is prioritized in independent optimization; if the working wideband sub-band is higher than the preset threshold, it is a high frequency band, and IPD wave transmittance is prioritized in independent optimization.

[0025] It is to be noted that, in the low frequency band, the antenna cover structure is significantly more sensitive to phase consistency than to transmission loss due to the longer wavelength of electromagnetic waves, and in this case, setting the IPD flatness as the primary optimization target can directly address the core contradiction affecting the radar angle measurement accuracy; in the high frequency band, the skin effect and material loss of electromagnetic waves are intensified, and the transmission efficiency becomes the bottleneck restricting system performance, and in this case, setting the wave transmittance as the primary optimization target can ensure the detection distance and signal strength of the radar; in view of the differentiated optimization targets of different frequency bands, the multi-objective optimization problem originally conflicting with each other in the global wide frequency band and difficult to reconcile is decomposed into a series of sub-problems with clear target and clear physical meaning, for the optimization algorithm, only one dominant target needs to be focused on in each sub-problem, and the secondary target needs to be considered under the constraint condition, thereby greatly reducing the effective search space of the algorithm, avoiding the difficulty of local optimization or convergence in the complex Pareto frontier, and finally realizing the efficient use of optimization calculation resources and the significant improvement of convergence speed.

[0026] In one specific embodiment, the division in step S1 is based on one of the dispersion characteristics of the dielectric material, different operating modes of the antenna, and different functional requirements of the antenna. The division can be made according to specific circumstances, and the flexibility and freedom of adjustment are high.

[0027] In one specific embodiment, step S3 specifically includes: substituting the optimal solution into the working wideband range model of the radome for electromagnetic simulation verification, if the global performance of the radome meets the requirements, the design is completed; if the global performance of the radome does not meet the requirements, the optimal solution is adjusted. The electromagnetic simulation verification establishes a reliable performance guarantee mechanism and a closed-loop design process, ensuring the reliability of the final result.

[0028] More specifically, the adjustment of the optimal solution in step S3 includes: taking the original optimal solution as the starting point, and performing local optimization on the original optimal solution within the working wideband range of the radome to obtain the final optimal solution. That is, when performing electromagnetic simulation verification, if the performance of some boundary frequency points is slightly insufficient, the original optimal solution X_common is taken as the initial value, and small-range fine-tuning optimization is performed within the global range to finally determine the design scheme X_final.

[0029] The small-range fine-tuning starting from the original optimal solution greatly improves the optimization efficiency and convergence speed: because the original optimal solution is screened by the sub-band optimization and is very close to the optimal solution required by the global, taking the high-performance solution as the initial point of local optimization, compared with the global optimization starting from zero or a random point, the search range is greatly reduced, and then the optimization algorithm does not need to search aimlessly, saving a lot of computing resources and time cost. Meanwhile, the range of local optimization is carried out in the complete working bandwidth range, and the optimization target directly aims at the global performance short board; since the search is limited in the neighborhood of the original optimal solution, this process can maximize the retention of the good performance of the original solution in each sub-band, effectively avoiding the risk of sacrificing the performance of other frequency bands to improve a certain index, thereby obtaining a design scheme with stronger robustness, which is balanced and fine-tuned on the basis of meeting the global performance standard.

[0030] The examples described in the present application are only used to describe the preferred embodiments of the present application, and do not limit the concept and scope of the present application. Without departing from the design idea of the present application, various modifications and improvements of the technical solutions of the present application made by the engineering and technical personnel in the art shall fall within the protection scope of the present application.

Claims

1. A method for designing an antenna radome, characterized in that: Includes the following steps: S1: Determine the operating bandwidth of the radome, and divide the operating bandwidth into several operating bandwidth sub-bands; S2: Solve for the design parameters corresponding to each working broadband sub-band; S3: Solve for the intersection of several design parameters to obtain the optimal solution; S4: Verify whether the optimal solution meets global performance requirements.

2. The radome design method according to claim 1, characterized in that: Step S2 specifically includes the following steps: S21: Establish a parametric model of the radome for each working broadband sub-band; S22: Define the objective function for each working broadband sub-band; S23: An optimization algorithm is used to independently optimize each working broadband sub-band to find the optimal design parameters corresponding to each working broadband sub-band.

3. The radome design method according to claim 2, characterized in that: In step S23, when optimizing each working broadband sub-band independently, different priority optimization targets are set as constraints based on the frequency range of the working broadband sub-band.

4. A radome design method according to claim 2 or 3, characterized in that: Step S23 includes: performing threshold judgment on a single working broadband sub-band; if the working broadband sub-band is less than a preset threshold, it is a low frequency band, and IPD flatness is optimized first when performing independent optimization. If the working broadband sub-band is higher than the preset threshold, it is a high-frequency band, and IPD transmittance will be optimized first when performing independent optimization.

5. The radome design method according to claim 2, characterized in that: Step S21 specifically involves: The geometry and material properties of the radome are parameterized to obtain a set of variable design variables; Establish a mapping model between design variables and the radome electrical performance indicators in each operating broadband sub-band.

6. The radome design method according to claim 2, characterized in that: In step S22, the objective function is a weighted combination of performance indicators within the working broadband sub-band.

7. The radome design method according to claim 1, characterized in that: The optimal solution in step S3 specifically includes: searching for a common design parameter vector among several design parameters, wherein the common design parameter vector exists simultaneously in several design parameters.

8. The radome design method according to claim 1, characterized in that: The division in step S1 is based on one of the following: the dispersion characteristics of the dielectric material, the different operating modes of the antenna, or the different functional requirements of the antenna.

9. The radome design method according to claim 1, characterized in that: Step S3 specifically includes: substituting the optimal solution into the working broadband range model of the radome for electromagnetic simulation verification; if the global performance of the radome meets the requirements, the design is completed; if the global performance of the radome does not meet the requirements, the optimal solution is adjusted.

10. The radome design method according to claim 9, characterized in that: Step S3 involves adjusting the optimal solution by: starting from the original optimal solution and performing local optimization within the working bandwidth of the radome to obtain the final optimal solution.

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