Microstrip antenna design method and system and microstrip antenna

Abstract

The invention provides a microstrip antenna design method and system and a microstrip antenna. The design method of the microstrip antenna comprises the following steps: establishing an objective function based on a plurality of structure parameters and performance parameters of the microstrip antenna, and establishing a fitness function based on the objective function; optimizing the objective function according to a plurality of performance requirements of the microstrip antenna; and based on the optimized objective function, a plurality of structure parameters of the microstrip antenna are obtained by using a migrant bird optimization algorithm, and the plurality of structure parameters are used for designing the microstrip antenna. According to the design method and system of the microstrip antenna and the microstrip antenna provided by the invention, the problems of signal attenuation, multipath interference, poor environmental adaptability, weak anti-interference capability, high manufacturing cost, poor dynamic adaptability and the like of the microstrip antenna in different practical applications can be solved; moreover, the gain and directivity of the microstrip antenna in a complex environment can be improved, and low power consumption and high reliability can be maintained at the same time.

Description

Technical Field

[0001] The present disclosure relates to the field of wireless communication technologies, and particularly to a design method, a system, and a microstrip antenna of a microstrip antenna. Background Art

[0002] With the development of wireless communication and navigation technologies, antenna design and optimization technologies have become the core support technologies for improving communication quality, expanding coverage, and reducing energy consumption. Especially when facing complex environments, the performance optimization of traditional antenna design methods has limitations and it is difficult to meet the actual application requirements. Due to the complex environments under different actual applications, navigation antennas often face problems of signal attenuation and multipath interference, which thus limit the communication performance and positioning accuracy. Therefore, an efficient navigation system support is required to achieve precise operation and automatic control. Based on this, the antenna must have high gain, wide coverage, and strong anti-interference capabilities to meet the stable working requirements under different environments. How to optimize the antenna design to improve its gain and directivity in complex environments while maintaining low power consumption and high reliability is still a problem to be solved currently. Summary of the Invention

[0003] The present disclosure provides a design method, a system, and a microstrip antenna of a microstrip antenna, which are used to solve problems such as signal attenuation, multipath interference, poor environmental adaptability, weak anti-interference ability, high manufacturing cost, and poor dynamic adaptability faced by microstrip antennas under different actual applications, and can improve the gain and directivity of microstrip antennas in complex environments, and at the same time can maintain low power consumption and high reliability.

[0004] The present disclosure provides a design method of a microstrip antenna, which includes the following steps: Establish an objective function based on multiple structural parameters and performance parameters of the microstrip antenna, and establish a fitness function based on the objective function; Optimize the objective function according to multiple performance requirements of the microstrip antenna; Based on the optimized objective function, use the migratory bird optimization algorithm to obtain multiple structural parameters of the microstrip antenna, and the multiple structural parameters are used to design the microstrip antenna.

[0005] According to a design method of a microstrip antenna provided by the present disclosure, wherein The objective function includes: Signal coverage range objective function F1: , Antenna gain objective function F2: , Reflection loss objective function F3: , Where Zin is the input impedance of the antenna, and Z0 is the characteristic impedance of the system. The anti-interference ability objective function F4: , In the above objective function, L is the length of the conductor patch, W is the width of the conductor patch, c is the speed of light, and f is the operating frequency. The fitness function F is: F = w1F1 + w2F2 + w3F3 + w4F4, where F1, F2, F3, and F4 are the above objective functions, and w1, w2, w3, and w4 are the weight coefficients of the objective functions.

[0006] According to a design method of a microstrip antenna provided by the present disclosure, wherein Optimizing the objective function according to multiple performance requirements of the microstrip antenna includes: Collecting actual data of the microstrip antenna in an actual application scenario, comparing the difference between the output of the objective function and the actual data, adjusting the structural parameters in the objective function by a data fitting method, obtaining the optimized structural parameters, and making the output of the objective function closer to the actual data; Analyzing the performance requirements of the microstrip antenna in different scenarios, and adjusting the constraint ranges of multiple objective functions based on the performance requirements.

[0007] According to a design method of a microstrip antenna provided by the present disclosure, wherein Individually varying one of the multiple structural parameters and fixing the other structural parameters among the multiple structural parameters, and recording the influence of each variation on the objective function to determine the weight of the structural parameter; Setting the weights of multiple objective functions according to the multiple performance requirements of the microstrip antenna, and determining the optimization priority of the performance parameters according to the weights of the performance parameters; Constructing a multi-objective fitness function according to the weights of the structural parameters and the weights of the objective functions.

[0008] According to a design method of a microstrip antenna provided by the present disclosure, wherein The steps of obtaining multiple structural parameters of the microstrip antenna by using the migratory bird optimization algorithm include: Calculating the values of multiple objective functions by using the structural parameters of each individual, and further calculating the value of the fitness function, that is, the fitness value; Selecting the individual with the highest fitness value as the leading bird, dividing the remaining individuals into several groups, and setting the individual with the largest fitness value in each group as the deputy leading bird; Simulate the movement of the solution vectors of the population in the solution space. After each migration, update the migration direction of the group where the deputy leader bird is located, and other individuals in the group follow the deputy leader bird to move; In each migration, each of the individuals updates its position according to the following formula: ; ; ; ; ; where, is the solution vector of individual i in the t-th generation, is the velocity vector, representing the moving step size of the individual in the solution space; When the maximum number of iterations is reached or the change in the fitness value is less than a certain set threshold, stop the algorithm operation.

[0009] According to a microstrip antenna design method provided by the present disclosure, wherein, The structural parameters include at least one of the thickness, shape, size and position parameters of the dielectric substrate of the conductor patch of the microstrip antenna, the probe position, the dielectric constant and loss tangent of the dielectric material.

[0010] According to a microstrip antenna design method provided by the present disclosure, wherein, The performance parameters include at least one of the signal coverage range, gain, reflection loss, anti-interference ability, and signal reception accuracy.

[0011] According to a microstrip antenna design method provided by the present disclosure, wherein, The actual application scenarios include at least one of agricultural machinery application scenarios, forestry machinery application scenarios, livestock machinery application scenarios, fishery machinery application scenarios, transportation vehicle application scenarios, aircraft application scenarios, and ship application scenarios.

[0012] The present disclosure also provides a microstrip antenna design system, including the following units: A function construction unit that establishes an objective function based on multiple structural parameters and performance parameters of the microstrip antenna, and establishes a fitness function based on the objective function; A function optimization unit that optimizes the objective function according to multiple performance requirements of the microstrip antenna; An optimization unit based on an algorithm that, based on the optimized objective function, uses a migratory bird optimization algorithm to obtain multiple structural parameters of the microstrip antenna; A structural design unit designs the structure of the microstrip antenna based on multiple structural parameters of the microstrip antenna obtained through algorithm operations, and obtains a design scheme of the microstrip antenna.

[0013] The present disclosure also provides a microstrip antenna, which is manufactured by the design method of any of the above-mentioned microstrip antennas.

[0014] According to the design method, system and microstrip antenna of the microstrip antenna provided by the present disclosure, problems such as signal attenuation, multipath interference, poor environmental adaptability, weak anti-interference ability, high manufacturing cost and poor dynamic adaptability faced by the microstrip antenna under different actual applications can be solved, and the gain and directivity of the microstrip antenna in a complex environment can be improved. At the same time, low power consumption and high reliability can be maintained. Description of the Drawings

[0015] Figure 1 is a schematic flowchart of a design method of a microstrip antenna according to an embodiment of the present disclosure.

[0016] Figure 2 is a schematic structural diagram of a microstrip antenna according to an embodiment of the present disclosure.

[0017] Figure 3 is a theoretical radiation pattern of a microstrip antenna according to an embodiment of the present disclosure.

[0018] Figure 4 is a diagram showing the variation of the gain of a microstrip antenna with different dielectric constants ε r and thickness h according to an embodiment of the present disclosure.

[0019] Figure 5 is a block diagram showing a design system of a microstrip antenna according to an embodiment of the present disclosure. Detailed Embodiments

[0020] To make the objectives, technical solutions and advantages of the present disclosure clearer, the technical solutions in the present disclosure will be clearly and completely described below with reference to the accompanying drawings in the present disclosure. Apparently, the described embodiments are some but not all of the embodiments of the present disclosure. All other embodiments obtained by those of ordinary skill in the art without creative efforts based on the embodiments in the present disclosure belong to the scope of protection of the present disclosure.

[0021] At present, satellite navigation systems are widely used in fields such as agricultural machinery, driverless vehicles, marine exploration equipment, and emergency communication equipment. Especially in the field of agricultural machinery, they are used to achieve precise positioning and navigation. However, due to the diverse environmental conditions of different applications, such as terrain undulations, vegetation occlusion, and complex landforms, an efficient navigation system support is required to achieve precise operation and automatic control. Therefore, the antenna must have high gain, wide coverage, and strong anti-interference capabilities to meet the stable working requirements in different environments.

[0022] The main features of microstrip antennas lie in their compact structure, high gain, and good radiation directivity. As Figure 2 shown, microstrip antennas mainly consist of a conductor patch, a ground layer, a dielectric substrate, and a probe structure, etc. They are usually designed in a small and low-profile form, which is convenient for integration into various devices, such as agricultural machinery, driverless vehicles, and emergency communication equipment, etc. Microstrip antennas provide high-precision positioning and navigation functions by receiving satellite signals. However, such antennas face challenges such as signal attenuation, interference, and bandwidth limitations in a changing environment, such as areas with complex terrain and dense vegetation coverage, which affect their communication performance and positioning accuracy. As a traditional method, for example, fixed parameter design often fails to meet the requirements of different application scenarios. Therefore, it is urgent to develop more flexible and efficient antenna optimization methods to address these problems.

[0023] Based on the above challenges, in order to improve the performance of Beidou microstrip antennas in agricultural machinery and other complex environments, numerous experts and scholars have conducted extensive research and improvement on antenna optimization algorithms in order to obtain better results. The Migrating Birds Optimization (MBO) algorithm, as an emerging swarm intelligence algorithm, has gradually been applied to the field of antenna design optimization. For example, the article "Migrating Birds Optimization Algorithm for Antenna Array Design" (published in the IEEE Access magazine) proposed an antenna array design method based on the Migrating Birds Optimization algorithm, aiming to optimize parameters such as the gain, radiation pattern shape, and sidelobe level of the antenna. Compared with the traditional Genetic Algorithm (GA), the MBO algorithm shows higher search efficiency and global optimization ability in multi-objective optimization problems through simulating the dynamic cooperation mechanism of migratory bird migration behavior, but still faces challenges of high computational complexity in high-dimensional optimization problems. In addition, another review article "A Comprehensive Review on Swarm Intelligence Algorithms for Antenna Optimization Problems" (published in the Progress in Electromagnetics Research magazine) explored the application trends of swarm intelligence algorithms in antenna optimization, including the Migrating Birds Optimization (MBO) algorithm, Particle Swarm Optimization (PSO), etc. These algorithms demonstrate good adaptability and optimization effects in the dynamic environment of antenna design, but their iteration speed and stability in solving complex multi-objective problems still need to be further improved.

[0024] The Migratory Bird Optimization (MBO) algorithm is a newly emerging swarm intelligence optimization technique inspired by the migratory behavior and ecological characteristics of migratory birds. This algorithm models the optimization problem as an ecosystem, where each migratory bird individual represents a potential solution. By simulating the behavior of migratory birds during the process of searching for food and habitats, the Migratory Bird Optimization algorithm can conduct a global search in the problem space to find the optimal solution. In recent years, the Migratory Bird Optimization algorithm has undergone several improvements: (1) Optimized parameter settings and strategy adjustments to better balance the process of exploring new solutions and exploiting known solutions; (2) Enhanced the ability to handle multi-objective optimization problems and constraint conditions, making it perform better in complex problems; (3) Improved the real-time adjustment mechanism to enable the algorithm to better adapt to dynamic environments and changes. These advancements have significantly improved the convergence speed and solution quality of the algorithm. During the iterative process, migratory bird individuals adjust their positions based on fitness evaluation values and neighborhood information. Migratory birds optimize their own solutions through information sharing and learning, and gradually approach the global optimal solution. Compared with Ant Colony Optimization (ACO), Simulated Annealing (SA), and Genetic Algorithm (GA), the Migratory Bird Optimization algorithm shows stronger adaptability when dealing with dynamic environments and multi-modal optimization problems. These traditional algorithms often face slower convergence speeds and limited multi-modal processing capabilities when dealing with complex problems, while the Migratory Bird Optimization algorithm demonstrates excellent performance in practical complex problems due to its high precision and fast optimization advantages. In the design of microstrip antennas, the Migratory Bird Optimization algorithm has shown significant application potential. Aiming at the navigation requirements under various environmental conditions, the Migratory Bird Optimization algorithm can effectively optimize the key parameters of the antenna, such as the shape, size, position of the conductor patch, and probe arrangement, thereby improving the performance and reliability of the antenna. This research direction is becoming an important topic in this technical field, aiming to improve the navigation accuracy and communication effect of the navigation system through efficient antenna optimization methods.

[0025] In view of the above problems in the prior art, the present disclosure provides a design method for a microstrip antenna. Figure 1 It is a schematic flowchart of the design method for a microstrip antenna according to an embodiment of the present disclosure, as Figure 1 shown. The design method for the microstrip antenna includes the following steps 110, 210, and 310.

[0026] Step 110: Establish an objective function based on multiple structural parameters and performance parameters of the microstrip antenna, and establish a fitness function based on the objective function. The structural parameters of the microstrip antenna include at least one of the thickness, shape, size, and position parameters of the dielectric substrate of the conductor patch of the microstrip antenna, the probe position, the dielectric constant, and the loss tangent of the dielectric material. The performance parameters of the microstrip antenna include at least one of the signal coverage range, gain, reflection loss, anti-interference ability, and signal reception accuracy.

[0027] AsFigure 2 As shown, the length of the conductor patch of the microstrip antenna is designed as L, the width is designed as W, the thickness of the dielectric substrate is designed as h, and the probe position is set as the coordinate (x p , y p ), the dielectric constant of the dielectric material is set as ɛ r , and the loss tangent is set as tanδ.

[0028] Using the above structural parameters of the microstrip antenna, the electromagnetic parameters of the microstrip antenna can be calculated. For example, the resonance frequency ƒ r of the antenna is calculated as: , where c is the speed of light, ɛ eff is the effective dielectric constant, and its calculation formula is: , In addition, the reflection and transmission characteristics of the antenna can also be described by S parameters. The S scattering matrix is defined as: , where S 21 represents the transmission coefficient of the output port, and S 11 represents the reflection coefficient of the input port, and its calculation formula is: , where Z0 is the characteristic impedance of the system, usually 50 ohms, and Z in is the input impedance of the antenna, that is, the input impedance of the conductor patch, and its calculation formula is: .

[0029] Next, based on multiple structural parameters and performance parameters of the microstrip antenna, an objective function is established. The objective function includes a signal coverage range objective function F1, an antenna gain objective function F2, a reflection loss objective function F3, and an anti-interference ability objective function F4.

[0030] The functional expression of the signal coverage range objective function F1 is: , where λ is the signal wavelength, and its calculation formula is λ = c / f, c is the speed of light, and f is the operating frequency. Figure 3 is the theoretical radiation pattern of the microstrip antenna in an embodiment of the present disclosure, which is used to evaluate the directivity and coverage range of the antenna. Figure 3 shows the radiation pattern of the microstrip antenna within 360 degrees. In the figure, the H plane represents the horizontal plane radiation characteristics, and the E plane represents the vertical plane radiation characteristics.

[0031] The functional expression of the antenna gain objective function F2 is: , The functional expression of the reflection loss objective function F3 is as follows: , where Z0 is the characteristic impedance of the system, and Z in is the input impedance of the antenna. The functional expression of the anti-interference ability objective function F4 is as follows: , Then, construct the fitness function F based on the above objective functions F1, F2, F3, and F4, that is: F = w1F1 + w2F2 + w3F3 + w4F4, where w1, w2, w3, and w4 are the weight coefficients of the objective functions.

[0032] Of course, a radio wave propagation model such as the Friis propagation equation can be used to quantify the signal coverage in the target area, determine the gain of the radiation pattern, and calculate the target gain value. The signal-to-noise ratio (SNR) and interference tolerance (IR) are used as the measurement criteria for anti-interference ability, and corresponding threshold targets are set. The received signal strength and stability are defined as the measurement criteria for accuracy, and the minimum received signal strength is calculated using the power budget formula.

[0033] The relationship between the structural parameters and performance parameters can also be represented by varying graphs. For example, Figure 4 is a graph showing the variation of the gain of a microstrip antenna with different dielectric constants ε r and thickness h. It is the characteristic curve of the antenna gain (G) varying with frequency, where different curves represent the characteristic curves for different dielectric substrates and thickness h.

[0034] In addition, constraint conditions can be set for the performance parameters and structural parameters. For example, constraint conditions can be imposed on the signal coverage, gain, reflection loss, anti-interference ability, and physical size, that is: , where P min is the set minimum received power; , where G min is the required minimum gain; , where S 11max is the maximum allowable reflection loss.

[0035] , where R min is the minimum anti-interference ability ratio; , where L max and W max are the maximum length and maximum width of the antenna, respectively.

[0036] By setting the constraint conditions, the subsequent algorithm can automatically search for the optimal solution within the defined constraint range, avoiding the exploration of invalid regions, thus improving the search efficiency and convergence speed, reducing the number of iterations and computational costs, and enhancing the efficiency of the optimization process and the practicality of the final design solution.

[0037] Through step 110, the specificity and measurability of the design objectives are ensured, making the optimization work more targeted, reducing the costs of subsequent design iterations and adjustments. Moreover, the requirements for performance such as signal coverage, gain, anti-interference ability, and signal reception accuracy are clarified, which helps to improve the efficiency of antenna design and shorten the R & D cycle. In addition, this step provides a quantitative basis for performance evaluation and optimization, facilitating the comparison of effects during the optimization process, and ultimately ensuring the high performance and reliability of the antenna in practical applications.

[0038] Step 210: Optimize the objective function according to multiple performance requirements of the microstrip antenna; Among them, step 210 includes step 211, step 221, and step 231: Step 211: Collect the actual data of the microstrip antenna in the actual application scenario, compare the difference between the output of the objective function and the actual data, and adjust the structural parameters in the objective function through the least squares method or other data fitting methods to obtain the optimized structural parameters, making the output of the objective function closer to the actual data. In this step, analyze the specific performance requirements of the Beidou satellite navigation system in the actual application scenario, including signal coverage, gain, anti-interference ability, signal reception accuracy, environmental adaptability, and energy efficiency, etc., and then determine the optimization objectives based on these requirements, which can provide a basis for the optimization of the objective function.

[0039] The actual application scenarios of the microstrip antenna disclosed in this disclosure include at least one of the following: agricultural machinery application scenarios, forestry machinery application scenarios, livestock machinery application scenarios, fishery machinery application scenarios, transportation vehicle application scenarios, aircraft application scenarios, and ship application scenarios.

[0040] Step 221: Analyze the performance requirements of the microstrip antenna in different scenarios, and based on the performance requirements, adjust the constraint ranges of multiple objective functions. In this step, analyze the navigation requirements of agricultural machinery in different environments (such as plains, hills, forests, etc.). For the requirements of signal coverage and anti-interference ability in different scenarios, set or adjust the constraint conditions of the corresponding objective functions, for example, set or adjust the minimum gain requirement, the maximum allowable interference amount, etc.

[0041] In addition, in order to determine the key parameters and provide a reference for prioritizing subsequent optimizations, one of the multiple structural parameters is individually varied one by one, for example, increased or decreased by a certain fixed ratio, and the other structural parameters among the multiple structural parameters are fixed. The impact of each variation on the objective function is recorded, and a trend graph of the variation is plotted using a sensitivity analysis tool such as MATLAB to determine the weights of the structural parameters. According to the multiple performance requirements of the microstrip antenna, the weights of multiple objective functions are set, and the optimization priority of the performance parameters is determined based on the weights of the performance parameters.

[0042] Specifically, the Analytic Hierarchy Process (AHP) is used to construct an objective weight matrix. According to the importance of actual application requirements, weights are assigned to each performance index such as gain, coverage range, anti-interference ability, etc. Then, based on the weight ranking results, the priority direction of optimization is clarified. For example, if the weights of gain and coverage range are the highest, these objectives are given priority in the subsequent optimization process. Next, the performance index is formulated as the expression form of the objective function, that is, a multi-objective fitness function is constructed based on the weights of the structural parameters and the weights of the objective functions. For example, an optimization function to be considered is combined by the multi-objective weight method, and it is determined how to update the parameters in each iteration, how to evaluate the current solution, and feedback to the next step of the algorithm.

[0043] Through step 210, multiple related performance requirements can be comprehensively considered, such as signal coverage range, gain, anti-interference ability, signal reception accuracy, environmental adaptability, and energy efficiency, etc. Based on these requirements, the optimization objectives are determined, providing a basis for parameter optimization. And by comprehensively considering the weights of the structural parameters and the objective functions, an optimal balance point can be found among multiple performance objectives instead of the local optimal solution of a single objective, ensuring that the antenna has better comprehensive performance in different application scenarios and improving the practicality and robustness of the design.

[0044] Step 310: Based on the optimized objective function, use the migratory bird optimization algorithm to obtain multiple structural parameters of the microstrip antenna, and the multiple structural parameters are used to design the microstrip antenna.

[0045] In step 310, the selection and migration strategies of migratory birds are as follows: First, formulate the selection strategy of the migratory bird population, that is, according to the fitness value, select the individual with the highest fitness from the population as the Lead Bird.

[0046] Second, formulate the grouping and migration strategies of the bird flock, that is: the remaining individuals are divided into several groups according to distance or performance, and each group has a Sub-lead Bird.

[0047] The bird flock migrates according to a fixed pattern, which is to simulate the movement of the solution vector of the population in the solution space. After each migration, the deputy leader bird will update the migration direction of its group, and other individuals will follow the deputy leader bird to move.

[0048] In each migration (iteration), each individual updates its position according to the following formula: ; ; ; ; .

[0049] Among them, is the solution vector of individual i in the t-th generation, is the velocity vector, which represents the moving step size of the individual in the solution space and is usually defined as the random deviation when the bird flock migrates.

[0050] During the iteration process, a random perturbation factor ɛ can be introduced for local search to increase the population diversity and avoid falling into local optima: , where ε is a random perturbation within a small range and is used to explore the surrounding solution space.

[0051] Finally, a stopping criterion is formulated, that is: when the maximum number of iterations is reached or the fitness change is less than a certain set threshold, the algorithm stops.

[0052] After the operation of the above-mentioned migratory bird optimization algorithm, the final optimal solution will be output, that is, the combination of the best design parameters of the microstrip antenna.

[0053] Through step 310, in the process of applying the migratory bird optimization algorithm based on the objective function to the global optimization of the structural parameters of the microstrip antenna, by simulating the migratory mechanism of migratory birds, it effectively optimizes multiple parameters such as the shape, size, position of the conductor patch and the probe arrangement, ensuring that the optimization process proceeds in the direction of improving the antenna performance. The global search ability of the migratory bird optimization algorithm enables it to avoid local optima and find a better antenna design scheme.

[0054] Next, an actual example is given to illustrate the operation process of the migratory bird optimization algorithm.

[0055] For example, when optimizing a microstrip antenna of a matrix, the goal is to maximize the gain and minimize the reflection coefficient. Table 1 shows the data of the initial population. The population size is N = 10, and each individual represents a possible antenna design solution. In Table 1, each column represents the length L (unit: mm), width W (unit: mm), probe position (x, y) (unit: mm), gain G (unit: dB), and reflection coefficient S 11 (unit: dB).

[0056] Table 1:

[0057] First, formulate the selection strategy of the migratory bird population and set the goal, that is, select an initial population that meets certain criteria for the gain G and the reflection coefficient S 11 , such as the higher the gain G, the better, and the reflection coefficient S 11 with the lower absolute value, the better.

[0058] Next, calculate the fitness value by combining the gain and the reflection coefficient, that is: F = w2F2 + w3F3 + w4F4 = α * G + β * |S 11 |, where α and β are weight parameters. Here, let α = 0.3 and β = 0.5. The calculated individual fitness values are shown in Table 2.

[0059] Table 2:

[0060] According to the new fitness values, it can be seen that the fitness value of individual 6 is -3.63, which is the highest among all individuals. Therefore, individual 6 is selected as the initial leading bird. For each non-leading bird individual, the following position update rule is applied to update the parameter combination.

[0061] new_parameter = old_parameter + r × (leader_parameter - old_parameter), where: r is a random number (0 < r < 1); leader_parameter is the current parameter value of the leading bird, old_parameter is the old parameter value of the non-leading bird, and new_parameter is the new parameter value of the non-leading bird.

[0062] For example, taking individual 1 as an example, assuming the random number r = 0.4, the parameters of individual 1 are updated as follows.

[0063] L new = 30 + 0.4 × (27 - 30) = 28.8 mm; Wnew = 15 + 0.4×(16 - 15) = 15.4 mm; x new = 5 + 0.4×(9 - 5) = 6.6 mm; y new = 5 + 0.4×(4 - 5) = 4.6 mm.

[0064] That is to say, the new parameter combination of individual 1 is: L = 28.8 mm, W = 15.4 mm, and the probe position is (6.6, 4.6).

[0065] Using the new parameter combination, recalculate the gain and reflection coefficient of individual 1, and obtain the fitness value. The calculated new gain value is 5.4 dB, the reflection coefficient value is -11.0 dB, and the new fitness value is: F new = 0.3×5.4 - 0.5×11.0 = -3.88.

[0066] Similarly, update individuals 2, 3.......10, and then compare the individual with the highest fitness value in the new generation, and update this individual as the new leader bird.

[0067] Continue to repeat the above process until the fitness values of all individuals converge or reach the maximum number of iterations, stop the operation of the algorithm, and output the optimization results.

[0068] Design the structure of the microstrip antenna based on the optimization results. As described above, the structure includes the ground layer, support posts, dielectric substrate, conductor patch, and probe position of the microstrip antenna to improve the working bandwidth, gain, anti-interference ability, and signal transmission stability, so as to obtain a microstrip antenna that meets the performance requirements, and formulate corresponding manufacturing plans, adopt precision manufacturing processes, and simulation tests to ensure the efficiency and performance stability of the antenna in actual applications.

[0069] Next, the microstrip antenna components based on the optimization results will be described from aspects such as material selection, structural dimensions, layout design, and manufacturing methods.

[0070] The ground layer is located at the bottom of the antenna structure and is used to reflect radio frequency signals and provide a return path for current. Regarding the design of the ground layer, specifically, a high-conductivity copper material is preferably used, such as a thickness of 0.035 mm, to ensure good conductivity and low loss. And, preferably, the ground layer is designed as a rectangle with dimensions of L g = 60 mm, W g = 40 mm. The dimensions are determined according to the antenna operating frequency and the optimization results to ensure that the antenna has the required radiation performance and impedance matching. Regarding the manufacturing method of the ground layer, it is preferably to use photolithography or chemical etching technology to etch the copper foil layer on the insulating board to form the ground layer to ensure a smooth surface and no oxides.

[0071] The dielectric substrate is located between the ground layer and the conductor patch, providing a stable dielectric environment and affecting the operating frequency and radiation characteristics of the antenna. Regarding the material of the dielectric substrate, FR-4 or Rogers 5880 materials are preferably used. For example, with a dielectric constant of 2.2 and a loss tangent of 0.0009, selecting this material can provide an appropriate dielectric constant to meet the requirements of antenna gain and bandwidth. The size of the dielectric substrate can be designed as L S = 60 mm, W S × = 40 mm, and the thickness is designed as h S = 1.6 mm, making it the same size as the ground layer to ensure coverage of the entire antenna structure. Regarding the manufacturing method of the dielectric substrate, it is preferably cut to the specified size using a high-precision cutting machine and then installed on the ground layer.

[0072] The conductor patch is placed at the top center position of the dielectric substrate, opposite to the ground layer. The shape and size of the patch are optimized to maximize the radiation efficiency and bandwidth of the antenna. Regarding the material of the conductor patch, high-conductivity copper or silver materials are preferably used. For example, with a thickness of 0.035 mm, it ensures the effective radiation of signals and antenna efficiency. The shape of the conductor patch can be designed as a rectangle, and the size is designed as L p = 28.8 mm, W p = 15.4 mm. These dimensions are determined based on the optimization results and the required operating frequency to ensure the provision of the required radiation characteristics and gain. Regarding the manufacturing method of the conductor patch, precision chemical etching technology is preferably adopted to precisely etch the conductor patch from copper foil material and fix it on the dielectric substrate through a low-temperature welding process or adhesive.

[0073] The probe is vertically installed between the ground layer and the conductor patch, at a feed point position offset by x p = 14.4 mm, y p = 7.7 mm from the center of the patch to ensure the optimal feeding of signals. Regarding the material of the probe, high-strength copper or silver-plated steel materials are preferably used to ensure good conductivity and mechanical stability. For example, the diameter d p = 0.8 mm, and the length l p = 2.0 mm. These dimensions are optimized to ensure impedance matching at the feed point and minimize signal loss. Regarding the manufacturing method of the probe, precision drilling technology is preferably used to drill holes in the dielectric substrate and the ground layer, and the probe is fixed in place through welding or crimping technology.

[0074] Cut, etch, and install the antenna components according to the above steps. All components are manufactured according to the specified dimensions and material selections to ensure manufacturing precision and avoid degradation of antenna performance due to component deviations. Specifically, assemble the ground layer, dielectric substrate, conductor patch, and probe layer by layer, fix them using non-conductive adhesive, and perform necessary calibration and debugging after assembly.

[0075] Manufacture the Beidou microstrip antenna device according to the design scheme. Conduct preliminary functional tests on the assembled antenna under laboratory conditions, including measurements of bandwidth, gain, impedance matching, and radiation characteristics, to verify the performance such as the operating bandwidth and signal stability of the antenna, so as to ensure that the manufacturing process complies with the design specifications and the antenna meets the expected performance indicators.

[0076] The present disclosure also provides a design system for a microstrip antenna, as Figure 5 shown, which includes: A function construction unit 101 that establishes an objective function based on multiple structural parameters and performance parameters of the microstrip antenna and establishes a fitness function based on the objective function; A function optimization unit 201 that optimizes the objective function according to multiple performance requirements of the microstrip antenna; An algorithm-based optimization unit 301 that, based on the optimized objective function, uses the migratory bird optimization algorithm to obtain multiple structural parameters of the microstrip antenna; A structure design unit 401 that designs the structure of the microstrip antenna based on the multiple structural parameters of the microstrip antenna obtained through algorithm operations to obtain a design scheme for the microstrip antenna.

[0077] The present disclosure also provides a microstrip antenna manufactured by the above design method of the microstrip antenna.

[0078] The microstrip antenna of the present disclosure can be applied to global navigation satellite systems, such as the Beidou navigation system, the Global Positioning System (GPS), etc.

[0079] According to the design method, system, and microstrip antenna provided by the present disclosure, problems faced by microstrip antennas under different practical applications, such as signal attenuation, multipath interference, poor environmental adaptability, weak anti-interference ability, high manufacturing cost, and poor dynamic adaptability, can be solved, the gain and directivity of the microstrip antenna in complex environments can be improved, and at the same time, low power consumption and high reliability can be maintained.

[0080] The embodiments disclosed in this document describe a design method for a microstrip antenna, which can be implemented through hardware, software modules executed by a processor, or a combination of both. The software modules can be stored in various storage media, such as random access memory (RAM), internal memory, read-only memory (ROM), programmable ROM (PROM), erasable programmable ROM (EPROM), registers, hard disks, removable disks, CD-ROMs, or other storage media well-known in the art.

[0081] As described above, those skilled in the art to which this technology pertains can understand that this technology can be implemented in various other forms without departing from the technical spirit or basic characteristics of this technology. Therefore, it should be understood that the above embodiments are illustrative in all aspects and not restrictive. The scope of this technology is defined by the appended claims rather than the specific implementation manners, and all modifications or variations derived from the meaning and scope of the claims and their equivalent forms should be understood to be included within the scope of this technology. In addition, the embodiments can be combined to form other embodiments.

Claims

1. A method for designing a microstrip antenna, characterized in that: include: Establishing an objective function based on a plurality of structural parameters and performance parameters of the microstrip antenna, and establishing a fitness function based on the objective function; Optimizing the objective function according to multiple performance requirements of the microstrip antenna; Based on the optimized objective function, a plurality of structural parameters of the microstrip antenna are obtained by using a migratory bird optimization algorithm, and the plurality of structural parameters are used to design the microstrip antenna.

2. The design method of a microstrip antenna according to claim 1, characterized in that: The objective function includes: Signal coverage objective function F1: ， Antenna gain objective function F2: ， Reflection loss objective function F3: , Among them, Z in is the input impedance of the antenna, Z0 is the characteristic impedance of the system, Anti-interference capability objective function F4: ， In the above objective function, L is the length of the conductor patch, W is the width of the conductor patch, c is the speed of light, and f is the operating frequency. The fitness function F is: F = w1F1+w2F2+w3F3+w4F4, Among them, F1, F2, F3, and F4 are the objective functions, and w1, w2, w3, and w4 are weight coefficients of the objective functions.

3. The design method of a microstrip antenna according to claim 2, characterized in that: Optimizing the objective function according to the multiple performance requirements of the microstrip antenna includes: Collecting actual data of the microstrip antenna in actual application scenarios, comparing the difference between the output of the objective function and the actual data, adjusting the structural parameters in the objective function by a data fitting method, obtaining the optimized structural parameters, and making the output of the objective function closer to the actual data; The performance requirements of the microstrip antenna in different scenarios are analyzed, and based on the performance requirements, the constraint ranges of multiple objective functions are adjusted.

4. The design method of the microstrip antenna according to claim 3, characterized in that: One by one, a structural parameter of the plurality of structural parameters is individually changed, and the other structural parameters of the plurality of structural parameters are fixed, and the influence of each change on the objective function is recorded to determine the weight of the structural parameter; According to the multiple performance requirements of the microstrip antenna, weights of multiple objective functions are set, and the optimization priority of the performance parameters is determined according to the weights of the performance parameters; A multi-objective fitness function is constructed according to the weights of the structural parameters and the weights of the objective function.

5. The design method of a microstrip antenna according to claim 3 or 4, characterized in that: The step of obtaining a plurality of structural parameters of the microstrip antenna by using the migratory bird optimization algorithm comprises: The structural parameters of each individual are used to calculate the values ​​of multiple objective functions, and then the value of the fitness function, i.e., the fitness value, is calculated; Select the individual with the highest fitness value as the leader bird, divide the remaining individuals into several groups, and set the individual with the largest fitness value in each group as the deputy leader bird; Simulating the movement of the solution vector of the population in the solution space, after each migration, updating the migration direction of the group where the deputy leader bird is located, and other individuals in the group follow the deputy leader bird to move; In each migration, each individual updates its position according to the following formula: ； ； ； ； ； Among them, x i （t） is the solution vector of individual i in the tth generation, v i （t） is the velocity vector, which represents the moving step of the individual in the solution space; When the maximum number of iterations is reached or the change in fitness value is less than a certain set threshold, the algorithm stops running.

6. The design method of the microstrip antenna according to claim 1, characterized in that: The structural parameters include: at least one of the thickness, shape, size and position parameters of the dielectric substrate of the conductor patch of the microstrip antenna, the probe position, the dielectric constant and the loss tangent of the dielectric material.

7. The design method of the microstrip antenna according to claim 1, characterized in that: The performance parameters include: at least one of: signal coverage, gain, reflection loss, anti-interference capability, and signal reception accuracy.

8. The design method of the microstrip antenna according to claim 1, characterized in that: The actual application scenarios include: at least one of: agricultural machinery application scenarios, forestry machinery application scenarios, animal husbandry machinery application scenarios, fishery machinery application scenarios, transportation vehicle application scenarios, aircraft application scenarios, and ship application scenarios.

9. A design system for a microstrip antenna, characterized in that: include: A function construction unit, which establishes an objective function based on a plurality of structural parameters and performance parameters of the microstrip antenna, and establishes a fitness function based on the objective function; A function optimization unit, which optimizes the objective function according to multiple performance requirements of the microstrip antenna; An algorithm-based optimization unit obtains a plurality of structural parameters of the microstrip antenna using a migratory bird optimization algorithm based on the optimized objective function; A structural design unit designs the structure of the microstrip antenna based on a plurality of structural parameters of the microstrip antenna obtained through algorithmic calculation, and obtains a design scheme of the microstrip antenna.

10. A microstrip antenna, characterized in that: The microstrip antenna is manufactured by the design method of the microstrip antenna described in any one of claims 1 to 8.

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