Antenna array synthesis method and device based on Taylor distribution and Kirchhoff circle

Abstract

The invention provides an antenna array synthesis method and device based on Taylor distribution and a Kirchhoff circle, and belongs to the technical field of radar antennae, and the method comprises the steps: determining an initial excitation coefficient and an initial array zero point position of an array element through a Taylor distribution function according to the array synthesis requirement, and obtaining an initial directional diagram with the side lobe suppression and main lobe characteristics; the initial array zero point position is converted to a Kirchhoff unit circle, a to-be-optimized zero point position of the to-be-optimized area is identified based on the principle of the Kirchhoff unit circle, and the to-be-optimized zero point position is finely adjusted by using a genetic algorithm; and calculating the excitation coefficient of the array element corresponding to the fine-tuned specific zero point position, and replacing the initial excitation coefficient to obtain a final array element excitation coefficient. According to the invention, fine optimization of the antenna array directional diagram is realized, and rapid beamforming, multi-beam and adaptive interference suppression of the antenna array are completed.

Description

Technical Field

[0001] The present invention belongs to the technical field of radar antennas, and particularly relates to an antenna array synthesis method and device based on Taylor distribution and Kirchhoff circle. Background Art

[0002] With the development of radar technology towards miniaturization and integration, traditional array synthesis methods have exposed many deficiencies when dealing with complex application scenarios, and it is difficult to meet the growing diverse requirements. Especially in scenarios with strict space and energy limitations such as satellite platforms, the array synthesis method needs to achieve higher requirements in terms of computational efficiency and accuracy.

[0003] Currently, common array synthesis methods include analytical methods, optimization algorithms, and methods based on specific distributions. Although the Fourier transform method in analytical methods has a simple theoretical basis, it is difficult to obtain an accurate analytical expression under complex beam shapes, which limits its application scope. While the Woodward synthesis method performs well in the shaping region, its control effect on the sidelobe level in the non-shaping region is not good, affecting the performance of the radar system. Among optimization algorithms, direct search methods such as Powell are fast in calculation speed, but are prone to falling into local optimal solutions, affecting the beam shaping effect. Intelligent search methods such as genetic algorithms have global search capabilities, but are slow in calculation speed and are difficult to balance various objectives in multi-objective optimization. The Taylor array synthesis method based on specific distributions can effectively suppress the sidelobe level and regulate the main lobe shape, but it is highly dependent on parameter settings, and has obvious limitations and insufficient flexibility in the case of irregular arrays.

[0004] In summary, existing array synthesis technologies have different degrees of limitations in aspects such as complex beam shaping, sidelobe level control, computational efficiency, and multi-objective optimization balance, and it is difficult to meet the diverse requirements of modern radar systems in complex scenarios. Summary of the Invention

[0005] To solve the above technical problems, the present invention proposes an antenna array synthesis method and device based on Taylor distribution and Kirchhoff circle. By combining the characteristics of the Taylor distribution function and Kirchhoff circle, first, the Taylor distribution is used to achieve preliminary suppression of sidelobes and optimization of the main lobe. Subsequently, the pattern is finely adjusted through the Kirchhoff polynomial to optimize key parameters such as sidelobe level and main lobe shape. The present invention integrates the systematicness of the Taylor array synthesis method and the fine-tuning ability of the Kirchhoff unit circle, and is applicable to radar systems with high requirements for target detection accuracy and anti-interference ability, as well as the design and application of high-precision radar antennas.

[0006] To achieve the above object, the present invention adopts the following technical solutions:

[0007] An antenna array synthesis method based on Taylor distribution and Kirchhoff circle, comprising the following steps:

[0008] Step 1: According to the requirements of array synthesis, use the Taylor distribution function to determine the initial excitation coefficients of the array elements and the initial array null positions, and obtain the initial pattern with sidelobe suppression and main lobe characteristics.

[0009] Step 2: Convert the initial array null positions determined in Step 1 to the Kirchhoff unit circle. Based on the principle of the Kirchhoff unit circle, identify the null positions to be optimized in the area to be optimized, and use the genetic algorithm to finely adjust the null positions to be optimized.

[0010] Step 3: Calculate the excitation coefficients of the array elements corresponding to the finely adjusted null positions obtained in Step 2, replace the initial excitation coefficients in Step 1, and obtain the final excitation coefficients of the array elements, so as to achieve fine optimization of the antenna array pattern, and complete the fast beamforming, multi-beam and adaptive interference suppression of the antenna array.

[0011] The present invention also provides an antenna array synthesis device based on Taylor distribution and Kirchhoff circle, including the following modules:

[0012] Initial pattern acquisition module: According to the requirements of array synthesis, use the Taylor distribution function to determine the initial excitation coefficients of the array elements and the initial array null positions, and obtain the initial pattern with sidelobe suppression and main lobe characteristics.

[0013] Fine-tuning module: Convert the initial array null positions to the Kirchhoff unit circle. Based on the principle of the Kirchhoff unit circle, identify the null positions to be optimized, and use the genetic algorithm to finely adjust the null positions to be optimized.

[0014] Fine optimization module: Calculate the excitation coefficients of the array elements corresponding to the finely adjusted null positions, replace the initial excitation coefficients in Step 1, and obtain the final excitation coefficients of the array elements, so as to achieve fine optimization of the antenna array pattern, and complete the fast beamforming, multi-beam and adaptive interference suppression of the antenna array.

[0015] The present invention also provides an electronic device, including a memory, a processor, and a computer program stored on the memory and executable on the processor. When the processor executes the program, the steps of the above-mentioned antenna array synthesis method based on Taylor distribution and Kirchhoff circle are implemented.

[0016] The present invention also provides a non-transitory computer-readable storage medium, on which a computer program is stored. When the computer program is executed by a processor, the steps of the above-mentioned antenna array synthesis method based on Taylor distribution and Kirchhoff circle are implemented.

[0017] Compared with the existing array synthesis methods, the present invention has precise sidelobe control ability and flexible main lobe shape optimization. The specific beneficial effects are as follows:

[0018] By combining the advantages of the Taylor distribution function and the Kirchhoff unit circle, the present invention achieves a significant improvement in the performance of the antenna array. On the one hand, the Taylor distribution function effectively reduces the sidelobe level by optimizing the element excitation coefficients and the null distribution, especially in the region close to the main lobe. On this basis, the Kirchhoff unit circle can further fine-tune the sidelobes and optimize the sidelobe level at specific angles, thus exceeding the traditional technologies of single methods in terms of the accuracy and flexibility of sidelobe control. On the other hand, the Taylor distribution function can determine the element excitation coefficients and the null distribution according to the sidelobe level requirements, while the Kirchhoff unit circle further optimizes the width and gain of the main lobe by adjusting the radial and angular positions of the nulls, while maintaining the stability of the sidelobe level. This combination method not only improves the sidelobe control ability but also enhances the flexibility of main lobe shape optimization, solving the problem that is difficult to balance by conventional methods. BRIEF DESCRIPTION OF THE DRAWINGS

[0019] Figure 1 Schematic diagram of the shaping iteration situation for the direct genetic method;

[0020] Figure 2 Schematic diagram of the shaping iteration situation for the antenna array synthesis method based on Taylor distribution and Kirchhoff circle of the present invention;

[0021] Figure 3 Comparison diagram of cosecant squared shaping results;

[0022] Figure 4 Schematic diagram of the interference suppression iteration situation for the direct genetic method;

[0023] Figure 5 Schematic diagram of the interference suppression iteration situation for the antenna array synthesis method based on Taylor distribution and Kirchhoff circle of the present invention;

[0024] Figure 6 Comparison diagram of adaptive interference suppression results;

[0025] Figure 7 Flowchart of the antenna array synthesis method based on Taylor distribution and Kirchhoff circle of the present invention;

[0026] Figure 8 Schematic diagram of the antenna array synthesis device based on Taylor distribution and Kirchhoff circle of the present invention. DETAILED DESCRIPTION OF THE INVENTION

[0027] In order to make the objectives, technical solutions and advantages of the present invention clearer and more understandable, the present invention will be further described in detail below in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present invention and are not used to limit the present invention. In addition, the technical features involved in the various embodiments of the present invention described below can be combined with each other as long as they do not conflict with each other.

[0028] The Taylor array synthesis method mainly designs the element excitation coefficients through a specific Taylor distribution function to achieve the suppression of the sidelobe level of the antenna pattern and the optimization of the main lobe characteristics. The Kirchhoff unit circle (Schelkunoff unit circle) optimizes the shape of the antenna pattern and the sidelobe level by controlling the zero positions on the unit circle. The present invention combines the Taylor distribution function and the Kirchhoff polynomial to provide an antenna array synthesis method based on the Taylor distribution and the Kirchhoff circle, as Figure 7 shown, including the following steps:

[0029] Step 1: According to the array synthesis requirements, use the Taylor distribution function to determine the initial excitation coefficients of the elements and the initial array zero positions, and obtain an initial pattern with sidelobe suppression and main lobe characteristics;

[0030] Step 2: Convert the initial array zero positions determined in Step 1 to the Kirchhoff unit circle. Based on the principle of the Kirchhoff unit circle, identify the zero positions to be optimized in the area to be optimized, and use the genetic algorithm to finely adjust the zero positions to be optimized;

[0031] Step 3: On the basis of Step 2, calculate the excitation coefficients of the elements corresponding to the finely adjusted specific zero positions obtained in Step 2, replace the corresponding initial excitation coefficients in Step 1, obtain the final element excitation coefficients, realize the fine optimization of the antenna array pattern, and complete the fast beamforming, multi-beam and adaptive interference suppression of the antenna array.

[0032] Specifically, in the above Step 1, using the Taylor distribution function to determine the initial excitation coefficients of the elements includes:

[0033] The Taylor distribution function is obtained based on the mathematical analysis and approximation of the ideal pattern. Its purpose is to design the excitation coefficients through a special function form (Formula (2)) so that the antenna array pattern meets the desired sidelobe level and main lobe characteristics.

[0034] For an N-element uniform linear array, the far-field array factor has the following expression:

[0035] (1)

[0036] where N is the number of elements; is the excitation coefficient of the nth array element; j is the imaginary unit; k is the wave number; d is the element spacing; is the observation angle.

[0037] Let the desired sidelobe level be SLL, and the Taylor distribution function can be expressed as:

[0038] (2)

[0039] where, is the coefficient related to the array structure; the intermediate parameter is , and the intermediate parameter . cosh represents the hyperbolic cosine function.

[0040] To determine the coefficient related to the array structure, using the normalization condition, that is, the array factor is maximum in the main lobe direction, we have:

[0041] (3)

[0042] Substitute the Taylor distribution expression of into it, and we can get:

[0043] (4)

[0044] Solve this equation to obtain the expression of , so as to determine the excitation coefficient of the nth array element.

[0045] Using the Taylor distribution function to determine the initial array zero positions includes:

[0046] According to the characteristics of the Taylor distribution, calculate the zero positions of the far-field array factor.

[0047] Let , that is:

[0048] (5)

[0049] Substitute into it to get:

[0050] (6)

[0051] Make a substitution with the intermediate variable u: , and rewrite the above formula as:

[0052] (7)

[0053] When is an integer, the value of the sin function is ±1 or 0, then n makes When approaching an integer, the contribution to is relatively large. Using this property, the null positions of the array can be solved. Next, the method for solving the null positions will be described in detail.

[0054] Near the null position, the far-field array factor is approximately expanded as:

[0055] (8)

[0056] where is the derivative of with respect to and is the minimum value of

[0057] Taking the derivative of with respect to and substituting the variable substitution , through mathematical operations, an equation about

[0058] (9)

[0059] can be obtained. Solving this equation can get the approximate expression of the null position. In the common Taylor distribution model, the null position can be expressed as: where the intermediate parameter is ; is the operating wavelength;

[0060] Specifically, in step 2, converting the initial array null position determined by the above Taylor distribution function to the Kirchhoff unit circle includes:

[0061] Making a substitution through the variable z: , the far-field array factor The result F after variable substitution can be written as:

[0062] (10)

[0063] This polynomial has N - 1 complex roots, which are factorized as:

[0064] (11)

[0065] where I N is the amplitude value of the factorization; , is the null position of the nth array element the corresponding value after conversion on the Kirchhoff unit circle, and j is the imaginary unit.

[0066] Based on the principle of the Kirchhoff unit circle, identify the zero positions to be optimized, and use the genetic algorithm to fine-tune the zero positions to be optimized, including:

[0067] Let , and obtain the far-field array factor The formula for the result F after variable substitution is:

[0068] (12)

[0069] where x n is the real part of z n ; y n is the imaginary part of z n ; the intermediate parameter ψ is kdcosθ + β, and β is the array beam pointing parameter.

[0070] During the process of antenna array synthesis, identify the zero positions to be optimized in the area to be optimized, place the corresponding roots outside the Kirchhoff unit circle, and limit the roots in the sidelobe area on the Kirchhoff unit circle. After normalization, a total of ones or form a vector x, obtain the intermediate parameter and the function of vector x ; if it is desired to reduce the sidelobe level at a certain position, according to the zero position corresponding to the sidelobe at that certain position, add the or to be adjusted to vector x, and then use the genetic algorithm to calculate the appropriate zero position to achieve precise control of the sidelobe level and rapid optimization of the main lobe shape.

[0071] The fine-tuned zero position is expressed on the Kirchhoff unit circle as:

[0072] (13)

[0073] where is the fine-tuned zero position; is the initial zero position obtained by the Taylor array synthesis method and transformed onto the Kirchhoff unit circle; is the optimization adjustment amount of the zero position.

[0074] Specifically, in step 3, recalculating the excitation coefficients of the array elements includes:

[0075] According to the fine-tuned zero position , substitute it into formula (11) and replace , calculate the result after variable substitution of the far-field array factor corresponding to the area to be optimized, expand this result to obtain the element excitation coefficients of the area to be optimized, replace the initial excitation coefficients in step 1, and obtain the final element excitation coefficients.

[0076] Embodiment:

[0077] To verify the technical advantages of the method of the present invention, taking a certain type of digital array antenna as an example, for the design requirements of cosecant-squared beamforming, simultaneous multi-beam, and adaptive interference suppression, simulation optimization was carried out on 10-element cosecant-squared beamforming and 32-element interference suppression respectively. By comparing with the optimization results of the genetic algorithm, the remarkable characteristics of the method of the present invention in terms of rapidity and accuracy are clearly demonstrated.

[0078] (1) The case of cosecant-squared beamforming and simultaneous multi-beam:

[0079] According to the application requirements of a certain type of digital array antenna, the maximum pointing of the antenna beam is 1.97°, the beam coverage is 19.83°, and the cosecant-squared function is used for beamforming to construct the objective function as follows:

[0080] (14)

[0081] where, SLL is the sidelobe level; θ0~θ min is the beam pointing of the array antenna; θ min ~θ max is the beamforming angle of the array antenna; the design target θ0 is 1.97°, the minimum value θ min is 6°, and the maximum value θ max is 21.80°.

[0082] The optimization objective is to minimize the cost function, and the cost function is defined as:

[0083] (15)

[0084] where, q is the number of sampling points of the cost function; is the error in the sidelobe region; is the deviation in the cosecant-squared region; w1, w2 are the weights of different errors.

[0085] The present invention uses the genetic algorithm to optimize 2 parameters in the beamforming area, which takes 6.637 s. As a comparison, directly using the genetic algorithm to optimize 20 parameters of amplitude and phase of 10 elements takes 167.346 s. The time consumed by the present invention is only 3.96% of the direct genetic algorithm.

[0086] Figure 1The iterative situation of directly using the genetic algorithm for the synthesis design of the cosecant-squared shaped array is given. It can be seen that the direct genetic algorithm requires more than 1500 generations to complete the array optimization design. In contrast, as Figure 2 shown, the present invention only needs 30 generations to obtain the design result, greatly improving the optimization speed of the array optimization.

[0087] The array synthesis result is as Figure 3 shown. From Figure 3 it can be seen that when directly using the genetic method, the sidelobe of the pattern in the sidelobe region reaches -10.0 dB, which cannot meet the requirement of the sidelobe level of -30 dB; and the main lobe points to 0°, which is quite different from the setting of the objective function of 1.97°. This indicates that the direct genetic algorithm falls into local convergence and does not converge to the global optimal solution. Compared with the optimization of the direct genetic algorithm, the main lobe of the optimized pattern of the present invention points to 2°, and the sidelobe level is -29.1°. The reason why the sidelobe level does not reach -30 dB is that considering the optimization speed, only the zero amplitude in the shaped area is optimized.

[0088] Similar to the beamforming principle, in the direction where multiple beams are required simultaneously, by using the genetic algorithm to optimize the zero amplitude in the direction on the Kirchhoff unit circle, multiple beams can be obtained simultaneously. Compared with directly using the genetic algorithm to optimize the parameters twice the number of array elements, the present invention optimizes 2 - 3 parameters, having the advantage of fast optimization. At the same time, due to the introduction of the Taylor distribution function, the sidelobe level is also well controlled.

[0089] (2) Perform adaptive interference suppression:

[0090] According to the application requirements, on the basis of having multiple beams simultaneously, the digital array antenna also needs to have the ability of adaptive interference suppression. To reduce the simulation calculation amount, here the 32-element digital array is simulated. The sidelobe level is -25 dB, the null position is from -22° to -25°, the null depth is -40 dB, and the objective function is constructed as follows:

[0091] (16)

[0092] where IL is the interference suppression level; SLL is the sidelobe level; θ il ~θ ih is the interference suppression angle of the array antenna; θ min ~θ max is the beam pointing of the array antenna; θ il is -25°, θ ih is -22°, θ min is -2°, θ max is 2°.

[0093] The optimization objective is to minimize the cost function, and the construction method of the cost function is the same as that in the beamforming case. The genetic algorithm is directly used to optimize the amplitude and phase of 32 elements, which takes 393.028 s. In contrast, the present invention uses two parameters in the null region of the genetic algorithm for optimization, taking 10.414 s. The time-consuming of the method of the present invention is only 2.65% of that of the direct genetic algorithm.

[0094] Figure 4 The iterative situation of directly using the genetic method for comprehensive design against interference is given. It can be seen that the direct genetic algorithm needs 2000 generations to complete the array optimization design. In contrast, as Figure 5 shown, the present invention only needs 40 generations to obtain the design result, having a significant advantage in optimization efficiency.

[0095] The adaptive interference suppression result is as Figure 6 shown. From Figure 6 it can be seen that the null position optimized by the direct genetic algorithm is from -22° to -25°, the null depth is -40.0°, and there are 6 side lobes near the main lobe exceeding -25 dB, and the side lobe level is as high as -17.9 dB, which cannot meet the requirement of the side lobe level of -25 dB. This indicates that the direct genetic algorithm does not converge to the global optimal solution. Compared with the optimization of the direct genetic algorithm, the null position optimized by the method of the present invention is from -22° to -25°, the null depth is -39.1°, and the side lobe level is -22.2°. The optimization result is significantly better than that of the direct genetic algorithm. The side lobe level does not reach -25 dB because considering the optimization speed, only the zero-phase of the shaping area is optimized.

[0096] In summary, compared with directly using the genetic algorithm, the method of the present invention has the advantages of fast convergence speed and high shaping accuracy, and is applicable to different forms of beamforming and adaptive null generation.

[0097] As Figure 8 shown, the present invention also provides an antenna array synthesis device based on the Taylor distribution and the Kirchhoff circle, including the following modules:

[0098] An initial pattern obtaining module, according to the array synthesis requirements, uses the Taylor distribution function to determine the initial excitation coefficient of the array element and the initial array zero position, and obtains an initial pattern with side lobe suppression and main lobe characteristics;

[0099] A fine-tuning module, converts the initial array zero position to the Kirchhoff unit circle, based on the principle of the Kirchhoff unit circle, identifies the zero position to be optimized, and uses the genetic algorithm to fine-tune the zero position to be optimized;

[0100] The fine optimization module calculates the excitation coefficients of the array elements corresponding to the fine-tuned specific zero positions obtained, replaces the initial excitation coefficients, and obtains the final array element excitation coefficients, realizing the fine optimization of the antenna array pattern and completing the fast beamforming, multi-beam, and adaptive interference suppression of the antenna array.

[0101] The present invention also provides an electronic device, including a memory, a processor, and a computer program stored on the memory and executable on the processor. When the processor executes the program, the steps of the above antenna array synthesis method based on the Taylor distribution and the Kirchhoff circle are implemented.

[0102] The present invention also provides a non-transitory computer-readable storage medium, on which a computer program is stored. When the computer program is executed by a processor, the steps of the above antenna array synthesis method based on the Taylor distribution and the Kirchhoff circle are implemented.

[0103] Those skilled in the art should understand that the embodiments of the present invention can be provided as a method, a system, or a computer program product. Therefore, the present invention can take the form of a complete hardware embodiment, a complete software embodiment, or an embodiment combining software and hardware aspects. Moreover, the present invention can take the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to disk memories, CD-ROMs, optical memories, etc.) containing computer-usable program codes. The solutions in the embodiments of the present invention can be implemented in various computer languages. For example, object-oriented programming languages such as Java and interpreted scripting languages such as JavaScript.

[0104] The present invention is described with reference to the flowcharts and / or block diagrams of methods, devices (systems), and computer program products according to the embodiments of the present invention. It should be understood that each flow and / or block in the flowchart and / or block diagram can be implemented by computer program instructions, and the combination of the flows and / or blocks in the flowchart and / or block diagram can also be implemented by computer program instructions. These computer program instructions can be provided to the processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing devices to generate a machine, so that the instructions executed by the processor of the computer or other programmable data processing devices generate a device for implementing the specified function in Figure 1 one process or multiple processes and / or blocks Figure 1 one block or multiple blocks.

[0105] These computer program instructions can also be stored in a computer-readable memory that can direct a computer or other programmable data processing device to work in a specific manner, so that the instructions stored in the computer-readable memory generate a manufactured product including an instruction device, and the instruction device implements the specified function in Figure 1 one process or multiple processes and / or blocks Figure 1The functions specified in one or more boxes.

[0106] These computer program instructions can also be loaded onto a computer or other programmable data processing device, so that a series of operation steps are executed on the computer or other programmable device to generate a computer-implemented process. Thus, the instructions executed on the computer or other programmable device provide for implementing the steps of the functions specified in one Figure 1 process or more processes and / or boxes Figure 1 or more boxes.

[0107] Although the preferred embodiments of the present invention have been described, those skilled in the art can make additional changes and modifications once they learn the basic creative concepts. Therefore, the appended claims are intended to be construed as including the preferred embodiments and all changes and modifications falling within the scope of the present invention.

[0108] Obviously, those skilled in the art can make various changes and modifications to the present invention without departing from the spirit and scope of the present invention. Thus, if these modifications and variations of the present invention fall within the scope of the claims of the present invention and their equivalent technologies, the present invention is also intended to include these modifications and variations.

Claims

1. An antenna array synthesis method based on Taylor distribution and Kirchhoff circle, characterized in that: The steps include: Step 1: According to the array synthesis requirements, the Taylor distribution function is used to determine the initial excitation coefficient of the array element and the initial array zero point position, and an initial radiation pattern with sidelobe suppression and mainlobe characteristics is obtained; Step 2, converting the initial array zero point position determined in step 1 to the Kirchhoff unit circle, identifying the zero point position to be optimized in the area to be optimized based on the principle of Kirchhoff unit circle, and fine-tuning the zero point position to be optimized using a genetic algorithm; Step 3: Calculate the array element excitation coefficient of the array element corresponding to the fine-tuned zero point position obtained in step 2, replace the initial excitation coefficient in step 1, and obtain the final array element excitation coefficient to achieve fine optimization of the antenna array radiation pattern and complete the fast beamforming, multi-beam and adaptive interference suppression of the antenna array.

2. The antenna array synthesis method based on Taylor distribution and Kirchhoff circle according to claim 1, characterized in that: In step 2, converting the initial array zero point position determined in step 1 to the Kirchhoff unit circle includes: Substitute through the variable z, that is , and obtain the result F after replacing the far-field array factor variable: （10） Where j is the imaginary unit, k is the wave number, and d is the array element spacing. is the observation angle, exp() represents the exponential function; is the array element excitation coefficient of the nth array element; N represents the total number of array elements.

3. The antenna array synthesis method based on Taylor distribution and Kirchhoff circle according to claim 2, characterized in that: In the step 2, converting the initial array zero point position determined in step 1 to the Kirchhoff unit circle further comprises: The result F after substitution of far-field array factor variables has N-1 complex roots, which can be factored into: （11） Among them, I N is the magnitude value of the factorization; , is the zero position of the nth array element The converted corresponding values ​​on the Kirchhoff unit circle.

4. The antenna array synthesis method based on Taylor distribution and Kirchhoff circle according to claim 3, characterized in that: In step 2, based on the principle of Kirchhoff's unit circle, the zero point position to be optimized is identified, and the zero point position to be optimized is fine-tuned using a genetic algorithm, including: make , the formula for the result F after replacing the far-field array factor variable is: （12） Among them, x n For z n Real part; y n For z n Imaginary part; intermediate parameter is kdcosθ+β, where β is the array beam pointing parameter.

5. The antenna array synthesis method based on Taylor distribution and Kirchhoff circle according to claim 4, characterized in that: In step 2, based on the principle of Kirchhoff's unit circle, the zero point position to be optimized is identified, and the zero point position to be optimized is fine-tuned using a genetic algorithm, which further includes: In the process of antenna array synthesis, the zero point position to be optimized in the area to be optimized is identified and the corresponding The roots are placed outside Kirchhoff's unit circle, and the sidelobe region The roots are restricted to Kirchhoff's unit circle, and after normalization, indivual or Compose vector x and get the intermediate parameters and a function of the vector x If you want to reduce the sidelobe level at a certain position, according to the zero point position corresponding to the sidelobe at that position, you need to adjust or It is added to the vector x, and then the appropriate zero point position is calculated with the help of genetic algorithm to achieve precise control of the sidelobe level and rapid optimization of the mainlobe shape.

6. The antenna array synthesis method based on Taylor distribution and Kirchhoff circle according to claim 5, characterized in that: In step 2, based on the principle of Kirchhoff's unit circle, the zero point position to be optimized is identified, and the zero point position to be optimized is fine-tuned using a genetic algorithm, which further includes: The zero position after fine-tuning is expressed on Kirchhoff's unit circle as: （13） in, is the zero position after fine-tuning; It is the optimal adjustment amount for the zero point position.

7. The antenna array synthesis method based on Taylor distribution and Kirchhoff circle according to claim 6, characterized in that: In step 3, the final array element excitation coefficient is obtained by: According to the zero position after fine-tuning , substitute into formula (11), and replace , calculate the result after replacing the far-field array factor variable corresponding to the area to be optimized, expand the result to obtain the array element excitation coefficient of the area to be optimized, replace the initial excitation coefficient in step 1, and obtain the final array element excitation coefficient.

8. An antenna array synthesis device based on Taylor distribution and Kirchhoff circle, characterized in that: Includes the following modules: The initial pattern acquisition module determines the initial excitation coefficient of the array element and the initial array zero position using the Taylor distribution function according to the array synthesis requirements, and obtains the initial pattern with sidelobe suppression and mainlobe characteristics; The fine-tuning module converts the initial array zero point position to the Kirchhoff unit circle, identifies the zero point position to be optimized based on the principle of Kirchhoff unit circle, and uses the genetic algorithm to fine-tune the zero point position to be optimized; The fine optimization module calculates the array element excitation coefficient of the array element corresponding to the fine-tuned zero point position, replaces the initial excitation coefficient of step 1, and obtains the final array element excitation coefficient, thereby realizing fine optimization of the antenna array radiation pattern and completing fast beamforming, multi-beam and adaptive interference suppression of the antenna array.

9. An electronic device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that: When the processor executes the program, the steps of the antenna array synthesis method based on Taylor distribution and Kirchhoff circle described in one of claims 1-7 are implemented.

10. A non-transitory computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the steps of the antenna array synthesis method based on Taylor distribution and Kirchhoff circle described in any one of claims 1 to 7 are implemented.

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