An antenna adaptive optimization method based on multi-objective algorithm

Abstract

This invention provides an adaptive optimization method for antennas based on a multi-objective algorithm. The antenna includes a radiating substrate, a grounding substrate, and an impedance transition interlayer. The optimization method comprises the following steps: obtaining the size of the hollow radiating slot, fine-tuning the distribution density of the protrusions, and the angle between the two surfaces, and constructing a coupling correlation matrix; calculating real-time coupling loss based on the coupling correlation matrix; collecting operating condition data of the antenna during operation, correcting polarization interference and radiation distortion using the operating condition data, obtaining the corrected polarization interference and corrected radiation distortion, and comparing and verifying them through preset quantization constraints; constructing a multi-objective optimization function with the objectives of minimizing coupling loss, minimizing radiation distortion, and optimizing impedance matching; calling the multi-objective optimization function to optimize parameters when verification fails; and fine-tuning the size of the hollow radiating slot, the distribution density of the protrusions, and the angle between the two surfaces based on the optimal parameter combination to improve the antenna's operational stability and adaptability to operating conditions.

Description

Technical Field

[0001] This invention relates to the field of antenna technology, and in particular to an adaptive optimization method for antennas based on a multi-objective algorithm. Background Technology

[0002] Currently, the mainstream structures of traditional antennas used in communication, radar, and other fields are mostly single-layer microstrip patch antennas, quad-arm spiral antennas, and ground-coupled antennas. Among them, the single-layer microstrip patch antenna consists of a single substrate, patch radiating elements, and a ground layer. It has a simple structure and small size, but its radiation efficiency is low, its bandwidth is narrow, and it is susceptible to external environmental interference. The quad-arm spiral antenna adopts a symmetrical spiral structure, which has good circular polarization performance, but its structure is complex, requires high processing precision, and is difficult to miniaturize, thus limiting its adaptability. The ground-coupled antenna achieves coupling by arranging multiple radiating elements in a common ground, but its isolation between radiating elements is poor, which easily leads to mutual interference and affects communication quality. These traditional antenna structures are mostly integrated fixed designs, and the shape, size, and layout of the radiating elements are all preset fixed values. They cannot be dynamically adjusted according to the actual working environment, resulting in insufficient performance adjustment flexibility and difficulty in adapting to complex and ever-changing application scenarios.

[0003] Meanwhile, existing conventional antennas have many inherent problems in actual operation. External environmental disturbances such as temperature changes and obstruction interference can easily cause fluctuations in the antenna's coupling and radiation performance, affecting communication stability. To address these issues, conventional antenna optimization methods mostly iteratively optimize explicit parameters such as antenna dimensions, gain, and bandwidth. The optimization process often relies on manual experience to set optimization weights and constraints, lacking the ability to adapt to changes in operating conditions in real time. Furthermore, conventional optimization methods do not fully consider the implicit correlations between various structural parameters of the antenna, and the optimization objectives are relatively singular, focusing mainly on improving explicit performance while ignoring the impact of operating condition disturbances on the antenna's implicit coupling characteristics. This results in limited optimization effects, and the optimized antenna has poor performance stability under complex operating conditions, making it difficult to meet the requirements of high precision and high reliability. Summary of the Invention

[0004] In view of this, the present invention proposes an antenna adaptive optimization method based on a multi-objective algorithm, which can achieve adaptive optimization of antenna performance, improve antenna operation stability and adaptability to operating conditions, and reduce the cost of manual intervention.

[0005] The technical solution of this invention is implemented as follows: An adaptive optimization method for an antenna based on a multi-objective algorithm is disclosed. The antenna includes a radiating substrate, a grounding substrate, and an impedance transition interlayer. The radiating substrate has two irregularly shaped perforated radiating slots located on opposite sides of the substrate, with their overall lengths parallel. Several fine-tuning protrusions are spaced apart on the sidewalls of the perforated radiating slots. The grounding substrate is located below the radiating substrate and is inclined along the overall length of the perforated radiating slots. The impedance transition interlayer is located between the radiating substrate and the grounding substrate and is hollow internally. The optimization method includes the following steps: Step S1: Obtain the size of the hollowed-out radiation groove, fine-tune the distribution density of the bumps and the angle between the grounding substrate and the radiation substrate, and construct the coupling correlation matrix. Calculate the real-time coupling loss based on the coupling correlation matrix. Step S2: Collect the operating condition data, original polarization interference and original radiation distortion of the antenna during operation. Correct the polarization interference and radiation distortion using the operating condition data to obtain the corrected polarization interference and corrected radiation distortion. Step S3: Compare and verify the real-time coupling loss, corrected polarization interference, and corrected radiation distortion with the preset quantization constraints. Step S4: Construct a multi-objective optimization function with the objectives of minimizing coupling loss, minimizing radiation distortion, and optimizing impedance matching. If the verification fails, call the multi-objective optimization function to optimize the parameters. Step S5: Fine-tune the size of the hollowed-out radiation groove, the distribution density of the fine-tuning protrusions, and the angle between the two planes based on the optimal parameter combination output by the multi-objective optimization function.

[0006] Preferably, the expression for the coupling correlation matrix is:

[0007] in For the coupling correlation matrix, It is an angle between skew planes. The length and width of the hollowed-out radiating grooves are given. The length of the hollowed-out radiating groove is the straight-line distance between the two farthest points of the hollowed-out radiating groove extending along its overall length. The lengths of the two hollowed-out radiating grooves are given. The width of the hollowed-out radiating groove is equal to the average width of each cross-section of the hollowed-out radiating groove, taken from the direction of the line connecting the sections perpendicular to the overall length extension direction of the hollowed-out radiating groove. To fine-tune the distribution density of the protrusions, the distribution density of the protrusions in the two hollowed-out radial grooves is equal.

[0008] Preferably, the formula for calculating the real-time coupling loss is:

[0009] in For real-time coupling loss, For correction factor, Let be the determinant of the coupling incidence matrix.

[0010] Preferably, the specific steps of step S2 are as follows: Step S21: Collect temperature data and signal attenuation during antenna operation, and quantify the degree of obstruction of the antenna by the external environment; Step S22: Collect the original polarization interference and original radiation distortion during antenna operation through the electromagnetic detection module and the radiation signal detection module, respectively; Step S23: Correct the original polarization interference and original radiation distortion based on temperature data, signal attenuation, and degree of obstruction to obtain corrected polarization interference and corrected radiation distortion.

[0011] Preferably, the expressions for the corrected polarization interference and the corrected radiation distortion are:

[0012]

[0013] in To correct for polarization interference, For the original polarization interference, For temperature data, The standard operating temperature of the antenna. The occlusion level is quantified. This is the signal attenuation amount. These are the correction coefficients corresponding to temperature data, degree of obstruction, and signal attenuation, respectively. To correct for radiation distortion, This is the original radiation distortion. This is the correction factor corresponding to temperature. This is the correction coefficient corresponding to the coupling between the degree of occlusion and the amount of signal attenuation.

[0014] Preferably, the quantization constraint is:

[0015] in For real-time coupling loss, This is the coupling loss threshold. , The minimum coupling loss required for stable antenna operation To correct for polarization interference, The polarization interference threshold, To correct for radiation distortion, This is the radiation distortion threshold; If one of the quantization constraints is not met, the verification is deemed unsuccessful, triggering the parameter optimization process.

[0016] Preferably, the expression for the multi-objective optimization function is:

[0017] in For multi-objective optimization functions, , These are the skew angle, the length of the hollowed-out radial groove, and the density of the fine-tuning protrusion distribution, respectively. This represents the real-time impedance value of the antenna. The target impedance value, For adaptive weighting coefficients, This is a penalty item.

[0018] Preferably, the formula for calculating the adaptive weighting coefficient is:

[0019]

[0020]

[0021] in .

[0022] Preferably, the expression for the penalty term is:

[0023] in The penalty coefficient is... and These are the upper and lower limits of the angle between skew planes. and These are the upper and lower limits for the length of the hollowed-out radial groove. and To fine-tune the upper and lower limits of the convex point distribution density, when When both are between the upper and lower limits, the penalty term is 0. When any of the values ​​exceeds the upper or lower limit, the penalty term output will not be 0.

[0024] Preferably, step S5 includes the following specific steps: Step S51: Substitute the skew angle, the length of the hollowed-out radiation slot, the distribution density of the fine-tuned protrusions, the real-time coupling loss, the polarization interference after correction, and the radiation distortion after correction into the multi-objective optimization function; Step S52: Iteratively solve the multi-objective function, filter to obtain the Pareto optimal solution set, and select the optimal parameter combination that balances the optimization objective and avoids excessive superposition of penalty terms. Step S53: Convert the optimal parameter combination into a binary decision instruction set and send it to the control unit built into the antenna. Step S54: The control unit fine-tunes the length of the hollowed-out radiation groove, the angle between opposite surfaces, and the distribution density of the protrusions through the micro-telescopic adjustment component, the angle adjustment component, and the protrusion adjustment component.

[0025] Compared with the prior art, the beneficial effects of the present invention are: This invention discloses an antenna adaptive optimization method based on a multi-objective algorithm. The antenna includes a radiating substrate, an impedance transition interlayer, and a grounding substrate arranged from top to bottom. The radiating substrate is used as a horizontal plane, and the grounding substrate is inclined along the length of its hollowed-out radiating groove, forming a natural implicit electromagnetic coupling space with the radiating substrate. This achieves high isolation of the radiating unit without the need for additional isolation and absorbing units. The middle impedance transition interlayer is a hollow structure without dielectric filling, which can replace the traditional dielectric substrate direct bonding impedance matching mode. It relies on air dielectric to achieve wideband dynamic impedance adaptive matching, greatly reducing the negative impact of processing accuracy errors on antenna performance. It is suitable for long-term stable operation under high and low temperature, multi-obstruction and complex edge conditions. During actual antenna operation, operating condition data, original polarization interference, and original radiation distortion are collected. Simultaneously, real-time coupling parameters are calculated by combining the antenna's own hollow radiating slot size, fine-tuning protrusion distribution density, and out-of-plane angle. These parameters are then compared and verified using preset quantization constraints. If the verification fails, a parameter optimization process is triggered, introducing a multi-objective optimization algorithm. The antenna parameters are optimized with the goals of minimizing coupling loss, minimizing radiation distortion, and achieving optimal impedance matching. Ultimately, the hollow radiating slot size, fine-tuning protrusion distribution density, and out-of-plane angle can be fine-tuned to achieve adaptive optimization of antenna performance, improve antenna operational stability and operating condition adaptability, and reduce manual intervention costs. Attached Figure Description

[0026] To more clearly illustrate the technical solutions in the embodiments of the present invention, the accompanying drawings used in the description of the embodiments will be briefly introduced below. Obviously, the accompanying drawings described below are only preferred embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0027] Figure 1 This is a schematic diagram of the antenna structure for an antenna adaptive optimization method based on a multi-objective algorithm according to the present invention. Figure 2 This is a flowchart of an antenna adaptive optimization method based on a multi-objective algorithm according to the present invention; Figure 3 This is a flowchart of step S2 of an antenna adaptive optimization method based on a multi-objective algorithm according to the present invention; Figure 4 This is a flowchart of step S5 of an antenna adaptive optimization method based on a multi-objective algorithm according to the present invention.

[0028] In the figure, 1 is the radiating substrate; 2 is the grounding substrate; 3 is the impedance transition interlayer; 4 is the hollowed-out radiating groove; and 5 is the fine-tuning protrusion. Detailed Implementation

[0029] To better understand the technical content of this invention, a specific embodiment is provided below, and the invention will be further described in conjunction with the accompanying drawings.

[0030] See Figures 1 to 4 This invention provides an adaptive antenna optimization method based on a multi-objective algorithm. The antenna includes a radiating substrate 1, a grounding substrate 2, and an impedance transition interlayer 3. The radiating substrate 1 has two irregularly shaped perforated radiating slots 4, located on opposite sides of the substrate, with their overall lengths parallel. The sidewalls of the perforated radiating slots 4 are spaced apart by several fine-tuning protrusions 5. The grounding substrate 2 is located below the radiating substrate 1 and is inclined along the overall length of the perforated radiating slots 4. The impedance transition interlayer 3 is located between the radiating substrate 1 and the grounding substrate 2, and is hollow inside. The optimization method includes the following steps: Step S1: Obtain the size of the hollowed-out radiation groove 4, fine-tune the distribution density of the bumps 5 and the skew angle formed by the grounding substrate 2 and the radiation substrate 1, and construct the coupling correlation matrix. Calculate the real-time coupling loss based on the coupling correlation matrix. Step S2: Collect the operating condition data, original polarization interference and original radiation distortion of the antenna during operation. Correct the polarization interference and radiation distortion using the operating condition data to obtain the corrected polarization interference and corrected radiation distortion. Step S3: Compare and verify the real-time coupling loss, corrected polarization interference, and corrected radiation distortion with the preset quantization constraints. Step S4: Construct a multi-objective optimization function with the objectives of minimizing coupling loss, minimizing radiation distortion, and optimizing impedance matching. If the verification fails, call the multi-objective optimization function to optimize the parameters. Step S5: Based on the optimal parameter combination output by the multi-objective optimization function, fine-tune the size of the hollowed-out radiation groove 4, the distribution density of the fine-tuning protrusions 5, and the angle between the two surfaces.

[0031] This invention discloses an adaptive antenna optimization method based on a multi-objective algorithm. The target antenna is designed with a special structure, comprising an upper radiating substrate 1, a lower non-plane coupling grounding substrate 2, and an intermediate impedance transition layer 3. The upper radiating substrate 1 has two hollowed-out radiating slots 4 on opposite sides. These slots 4 have different and irregular shapes, but their overall lengths are parallel. The sidewalls of the hollowed-out radiating slots 4 are provided with tiny sawtooth-shaped electromagnetic coupling fine-tuning protrusions 5, used to adjust the microscopic radiation current distribution and weaken the radiation dead zones of conventional slotted antennas. The lower grounding substrate 2 is not parallel to the upper radiating substrate 1. Instead, it adopts a slightly skewed layout that forms an angle with the overall length extension direction of the hollow radiating groove 4, creating a natural implicit electromagnetic coupling space. This eliminates the need for additional isolation and absorbing units to achieve high isolation of the radiating unit. The impedance transition interlayer 3 is a hollow structure without dielectric filling, replacing the traditional dielectric substrate direct bonding impedance matching mode. It relies on air dielectric to achieve wideband dynamic impedance adaptive matching, significantly reducing the negative impact of processing accuracy errors on antenna performance. This allows for long-term stable operation under complex edge conditions with high and low temperatures and multiple obstructions.

[0032] During actual antenna operation, changes in the external environment can easily cause fluctuations in the antenna's coupling and radiation performance. To ensure communication stability, adaptive optimization of the antenna is necessary. The coupling parameters to be optimized include the size of the hollowed-out radiating slot 4, the distribution density of the fine-tuning protrusions 5, and the out-of-plane angle. By fine-tuning the size of the hollowed-out radiating slot 4, the effective radiating aperture and current path length of the antenna can be changed, improving radiation matching characteristics and suppressing signal distortion. Fine-tuning the distribution density of the fine-tuning protrusions 5 can regulate the local electromagnetic coupling strength, correcting issues such as uneven radiation waveforms and polarization distortion. Fine-tuning the out-of-plane angle can dynamically change the coupling distance and coupling field distribution between the two substrate layers, achieving continuous adjustment of coupling loss. After collecting the above three parameters during actual antenna operation, a coupling correlation matrix is ​​constructed. Based on the parameters in the coupling correlation matrix, real-time coupling loss can be calculated first. Simultaneously, operating condition data of the antenna during operation is collected, and the original polarization interference and original radiation distortion are corrected based on the operating condition data. Finally, the real-time... The coupling loss, corrected polarization interference, and corrected radiation distortion are compared and verified against the preset quantization constraints to determine whether the quantization constraints are met. If any of the real-time coupling loss, corrected polarization interference, or corrected radiation distortion does not meet the requirements, the verification is deemed unsuccessful, and communication will be abnormal. In this case, adaptive optimization of the antenna is required. By introducing a multi-objective optimization algorithm with the objectives of minimizing coupling loss, minimizing radiation distortion, and optimizing impedance matching, the optimal target parameters can be selected for the dimensions of the two hollowed-out radiation slots 4, the distribution density of the fine-tuning protrusions 5, and the angle between the two surfaces. Finally, fine-tuning can be performed based on the target parameters. Since the lengths of the two hollowed-out radiation slots 4 and the distribution density of the fine-tuning protrusions 4 are set to be the same, the fine-tuning can adjust the angle between the two surfaces, uniformly adjust the lengths of the two hollowed-out radiation slots 4, and uniformly adjust the distribution density of the fine-tuning protrusions 5 of the two hollowed-out radiation slots 4 to minimize coupling performance and radiation distortion, while optimizing impedance matching.

[0033] Preferably, the expression for the coupling correlation matrix is:

[0034] in For the coupling correlation matrix, It is an angle between skew planes. The length and width of the hollowed-out radiation groove 4 are given. The length of the hollowed-out radiation groove 4 is the straight-line distance between the two farthest endpoints of the hollowed-out radiation groove 4 along its overall length extension direction. The lengths of the two hollowed-out radiation grooves 4 are given. The width of the hollowed-out radiation groove 4 is equal to the average width of each cross-section of the hollowed-out radiation groove 4, taken from the direction of the line connecting the lines perpendicular to the overall length extension direction of the hollowed-out radiation groove 4. To fine-tune the distribution density of the protrusions 5, the distribution density of the protrusions 5 in the two hollowed-out radial grooves 4 is equal.

[0035] The elements of the coupling correlation matrix correspond to the correlation weights between each implicit coupling parameter. The weight values ​​are determined through previous electromagnetic simulation tests and range from [0.1, 0.9], which are used to quantify the influence of each parameter on the antenna coupling performance.

[0036] Preferably, the formula for calculating the real-time coupling loss is:

[0037] in For real-time coupling loss, The correction factor is determined based on the air dielectric characteristics of the impedance transition interlayer 3, and its value ranges from [0.05, 0.15]. Let be the determinant of the coupling incidence matrix.

[0038] The real-time coupling loss is dynamically updated according to the changes in the size of the hollowed-out radiation slot 4, the distribution density of the fine-tuning protrusions 5, and the angle between the two surfaces, and is synchronized with the real-time working status of the antenna.

[0039] Preferably, the specific steps of step S2 are as follows: Step S21: Collect temperature data and signal attenuation during antenna operation, and quantify the degree of obstruction of the antenna by the external environment; Step S22: Collect the original polarization interference and original radiation distortion during antenna operation through the electromagnetic detection module and the radiation signal detection module, respectively; Step S23: Based on temperature data, signal attenuation, and the degree of obstruction, correct the original polarization interference and original radiation distortion to obtain the corrected polarization interference and corrected radiation distortion. The expressions for the corrected polarization interference and corrected radiation distortion are as follows:

[0040]

[0041] in To correct for polarization interference, For the original polarization interference, For temperature data, The standard operating temperature for the antenna is 25℃ ± 2℃. This represents the quantified degree of occlusion, ranging from 1 to 10. A higher value indicates more severe occlusion. This is the signal attenuation amount. These are the correction coefficients corresponding to temperature data, degree of obstruction, and signal attenuation, respectively. , , All of these were determined by preliminary experiments. To correct for radiation distortion, This is the original radiation distortion. This is the correction factor corresponding to temperature. , This is a correction coefficient that couples the degree of occlusion with the amount of signal attenuation. .

[0042] During antenna operation, the operating conditions of the external environment can affect polarization interference and radiation distortion. Therefore, after collecting temperature data, signal attenuation, and the degree of obstruction, the original polarization interference and original radiation distortion can be corrected respectively, thereby eliminating the measurement deviations caused by external factors such as temperature, obstruction, and signal attenuation, and obtaining the true electromagnetic performance indicators of the antenna itself, providing an accurate and reliable basis for subsequent optimization decisions.

[0043] Preferably, the quantization constraint is:

[0044] in For real-time coupling loss, This is the coupling loss threshold. , The minimum coupling loss required for stable antenna operation was obtained from previous experimental tests. To correct for polarization interference, To correct for radiation distortion, The polarization interference threshold, , The radiation distortion threshold. All of these are designed in accordance with the special structure of the antenna and relevant industry standards.

[0045] If one of the quantization constraints is not met, the verification is deemed unsuccessful, triggering the parameter optimization process.

[0046] when If the verification is successful, the current antenna parameters are maintained, and data is continuously collected for the next round of monitoring. If any indicator is not met, the verification is failed, and the process proceeds to the parameter optimization process in step S4.

[0047] Preferably, the expression for the multi-objective optimization function is:

[0048] in For multi-objective optimization functions, , These are the skew angle, the length of the hollowed-out radial groove 4, and the distribution density of the fine-tuning protrusions 5, respectively. This represents the real-time impedance value of the antenna. The target impedance value, For adaptive weighting coefficients, The penalty term is defined by the following formula:

[0049]

[0050]

[0051] in The weighting coefficients are dynamically adjusted based on real-time parameter deviations, so that the greater the deviation, the higher the target weight, and the more targeted the optimization.

[0052] The expression for the penalty term is:

[0053] in The penalty coefficient is... and These are the upper and lower limits of the skew angle, taken as 3.2° and 2.8° respectively. and The upper and lower limits of the length of the hollowed-out radiation groove 4 are set at 25mm and 15mm respectively. and To fine-tune the upper and lower limits of the distribution density of 5 protrusions, values ​​of 1.5 protrusions / mm and 0.5 protrusions / mm were set respectively. When both are between the upper and lower limits, the penalty term is 0. When any of the values ​​exceeds the upper or lower limit, the penalty term output will not be 0.

[0054] The multi-objective optimization function performs iterative calculations with the objectives of minimizing coupling loss, minimizing radiation distortion, and optimizing impedance matching. In its expression, the coupling loss term is expressed as a square term. Increase the optimization weight when coupling loss exceeds the limit, improve the priority of coupling performance optimization, and use a logarithmic term for radiation distortion. This approach avoids over-optimization when radiation distortion is small, while ensuring optimization sensitivity when distortion exceeds the limit. A cubic term is used for the impedance matching term. This can strengthen the optimization effort when the impedance deviates from the target value. At the same time, an exponential penalty term is introduced. When any optimization variable exceeds the preset fine-tuning range, the penalty term will increase the objective function value exponentially, forcing the algorithm to avoid parameters from exceeding a reasonable range during iteration.

[0055] Preferably, step S5 includes the following specific steps: Step S51: Substitute the skew angle, the length of the hollowed-out radiation groove 4, the distribution density of the fine-tuning protrusions 5, the real-time coupling loss, the corrected polarization interference, and the corrected radiation distortion into the multi-objective optimization function. Step S52: Iteratively solve the multi-objective function, filter to obtain the Pareto optimal solution set, and select the optimal parameter combination that balances the optimization objective and avoids excessive superposition of penalty terms. Step S53: Convert the optimal parameter combination into a binary decision instruction set and send it to the control unit built into the antenna. Step S54: The control unit fine-tunes the length of the hollowed-out radiation groove 4, the angle between opposite surfaces, and the distribution density of the protrusions 5 through the micro-telescopic adjustment component, the angle adjustment component, and the protrusion adjustment component.

[0056] After receiving real-time parameters, the multi-objective optimization function performs iterative solutions, with the number of iterations controlled between 50 and 100. The Pareto optimal solution set is then selected from the Pareto optimal solution set to balance the three major optimization objectives without excessive superposition of penalty terms. This optimal parameter combination is then converted into a binary decision instruction set and driven by the control unit to adjust the corresponding adjustment components. The micro-telescopic adjustment component is used to adjust the length of the hollow radiation slot 4, the angle adjustment component can adjust the skew angle, and the convex point adjustment component can adjust the distribution density of the fine-tuning convex points 5. The fine-tuning process does not damage the main structure of the antenna. After the fine-tuning is completed, the parameters can be re-acquired, the coupling loss calculated, the electromagnetic parameters corrected, and the comparison and verification performed until the verification is passed, forming a closed-loop adaptive optimization and achieving full-process unmanned intervention.

[0057] The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present invention should be included within the protection scope of the present invention.

Claims

1. A method for antenna adaptive optimization based on multi-objective algorithm, characterized in that, The antenna includes a radiating substrate, a grounding substrate, and an impedance transition interlayer. The radiating substrate has two irregularly shaped perforated radiating slots located on opposite sides of the substrate, with their overall lengths parallel. The sidewalls of the perforated radiating slots are spaced apart with several fine-tuning protrusions. The grounding substrate is located below the radiating substrate and is inclined along the overall length of the perforated radiating slots. The impedance transition interlayer is located between the radiating substrate and the grounding substrate and is hollow inside. The optimization method includes the following steps: Step S1: Obtain the size of the hollowed-out radiation groove, fine-tune the distribution density of the bumps and the angle between the grounding substrate and the radiation substrate, and construct the coupling correlation matrix. Calculate the real-time coupling loss based on the coupling correlation matrix. Step S2: Collect the operating condition data, original polarization interference and original radiation distortion of the antenna during operation. Correct the polarization interference and radiation distortion using the operating condition data to obtain the corrected polarization interference and corrected radiation distortion. Step S3: Compare and verify the real-time coupling loss, corrected polarization interference, and corrected radiation distortion with the preset quantization constraints. Step S4: Construct a multi-objective optimization function with the objectives of minimizing coupling loss, minimizing radiation distortion, and optimizing impedance matching. If the verification fails, call the multi-objective optimization function to optimize the parameters. Step S5: Fine-tune the size of the hollowed-out radiation groove, the distribution density of the fine-tuning protrusions, and the angle between the two planes based on the optimal parameter combination output by the multi-objective optimization function.

2. The antenna adaptive optimization method based on multi-objective algorithm according to claim 1, characterized in that, The expression for the coupling correlation matrix is: in For the coupling correlation matrix, It is an angle between skew planes. The length and width of the hollowed-out radiating grooves are given. The length of the hollowed-out radiating groove is the straight-line distance between the two farthest points of the hollowed-out radiating groove extending along its overall length. The lengths of the two hollowed-out radiating grooves are given. The width of the hollowed-out radiating groove is equal to the average width of each cross-section of the hollowed-out radiating groove, taken from the direction of the line connecting the sections perpendicular to the overall length extension direction of the hollowed-out radiating groove. To fine-tune the distribution density of the protrusions, the distribution density of the protrusions in the two hollowed-out radial grooves is equal.

3. The antenna adaptive optimization method based on a multi-objective algorithm according to claim 2, characterized in that, The formula for calculating the real-time coupling loss is as follows: in For real-time coupling loss, For correction factor, Let be the determinant of the coupling incidence matrix.

4. The antenna adaptive optimization method based on a multi-objective algorithm according to claim 1, characterized in that, The specific steps of step S2 are as follows: Step S21: Collect temperature data and signal attenuation during antenna operation, and quantify the degree of obstruction of the antenna by the external environment; Step S22: Collect the original polarization interference and original radiation distortion during antenna operation through the electromagnetic detection module and the radiation signal detection module, respectively; Step S23: Correct the original polarization interference and original radiation distortion based on temperature data, signal attenuation, and degree of obstruction to obtain corrected polarization interference and corrected radiation distortion.

5. The antenna adaptive optimization method based on a multi-objective algorithm according to claim 4, characterized in that, The expressions for the corrected polarization interference and the corrected radiation distortion are as follows: in To correct for polarization interference, For the original polarization interference, For temperature data, The standard operating temperature of the antenna. The occlusion level is quantified. This is the signal attenuation amount. These are the correction coefficients corresponding to temperature data, degree of obstruction, and signal attenuation, respectively. To correct for radiation distortion, This is the original radiation distortion. This is the correction factor corresponding to temperature. This is the correction coefficient corresponding to the coupling between the degree of occlusion and the amount of signal attenuation.

6. The antenna adaptive optimization method based on a multi-objective algorithm according to claim 1, characterized in that, The quantization constraint is as follows: in For real-time coupling loss, This is the coupling loss threshold. , The minimum coupling loss required for stable antenna operation To correct for polarization interference, The polarization interference threshold, To correct for radiation distortion, This is the radiation distortion threshold; If one of the quantization constraints is not met, the verification is deemed unsuccessful, triggering the parameter optimization process.

7. The antenna adaptive optimization method based on a multi-objective algorithm according to claim 6, characterized in that, The expression for the multi-objective optimization function is: in For multi-objective optimization functions, , These are the skew angle, the length of the hollowed-out radial groove, and the density of the fine-tuning protrusion distribution, respectively. This represents the real-time impedance value of the antenna. The target impedance value, For adaptive weighting coefficients, This is a penalty item.

8. The antenna adaptive optimization method based on a multi-objective algorithm according to claim 7, characterized in that, The formula for calculating the adaptive weighting coefficient is as follows: in .

9. The antenna adaptive optimization method based on a multi-objective algorithm according to claim 7, characterized in that, The expression for the penalty term is: in The penalty coefficient is... and These are the upper and lower limits of the angle between skew planes. and These are the upper and lower limits for the length of the hollowed-out radial groove. and To fine-tune the upper and lower limits of the convex point distribution density, when When both are between the upper and lower limits, the penalty term is 0. When any of the values ​​exceeds the upper or lower limit, the penalty term output will not be 0.

10. The antenna adaptive optimization method based on a multi-objective algorithm according to claim 1, characterized in that, The specific steps of step S5 include: Step S51: Substitute the skew angle, the length of the hollowed-out radiation slot, the distribution density of the fine-tuned protrusions, the real-time coupling loss, the polarization interference after correction, and the radiation distortion after correction into the multi-objective optimization function; Step S52: Iteratively solve the multi-objective function, filter to obtain the Pareto optimal solution set, and select the optimal parameter combination that balances the optimization objective and avoids excessive superposition of penalty terms. Step S53: Convert the optimal parameter combination into a binary decision instruction set and send it to the control unit built into the antenna. Step S54: The control unit fine-tunes the length of the hollowed-out radiation groove, the angle between opposite surfaces, and the distribution density of the protrusions through the micro-telescopic adjustment component, the angle adjustment component, and the protrusion adjustment component.

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