Array antenna synthesis method and device based on directional antenna radiation pattern reconstruction

Abstract

The application discloses a kind of array antenna synthesis method and device based on directional antenna radiation pattern reconstruction, method includes:A, initialization population and obtain each array element in the first section unit directional diagram data;B, superimposed each array element unit directional diagram data obtains array antenna in the first section array directional diagram data, to obtain the radiation performance index of the first section in this way;C, according to the fitness of individual radiation performance index;D, judge whether to stop iteration;If stop enter E;If not stop then execute individual variation, cross and selection, return B;E, according to the unit directional diagram data of second section of optimal individual corresponding excitation data;According to the array antenna directional diagram of second section unit directional diagram data reconstruction;F, judge whether array antenna directional diagram meets the requirement;If meet, obtain array antenna synthesis result;If not meet return A.The application can realize the synthesis of square kilometer array antenna.

Description

Technical Field

[0001] This invention belongs to the field of wireless communication, specifically relating to an array antenna synthesis method and apparatus based on directional antenna radiation pattern reconstruction. Background Technology

[0002] In this era of rapid information development in modern society, wireless communication technology has gradually permeated every aspect of people's lives and work, serving a wider audience, and people's demands for wireless communication are also increasing. Antennas are an indispensable component of communication systems, responsible for radiating and receiving electromagnetic waves and converting guided waves into electromagnetic waves. With the development of wireless communication technology, antennas play a crucial role in mobile communication, broadcasting, radar, navigation, satellite meteorology, and remote sensing, and the performance requirements for antennas are constantly increasing.

[0003] An array antenna is an antenna system composed of multiple antenna elements. By controlling the phase and amplitude of each antenna element, an array antenna can achieve functions such as beam control and interference suppression of electromagnetic waves, and has the advantages of high gain, strong directivity, strong anti-interference capability, and wide coverage. The excitation of an array antenna determines its directional characteristics. Determining the directional characteristics of an array antenna given its excitation is called array antenna analysis; conversely, determining the directional characteristics is called array antenna synthesis. Therefore, array antenna analysis and array antenna synthesis are two different research directions.

[0004] In related technologies, array antenna synthesis methods typically require acquiring relatively complete radiation pattern data and then inferring the excitation based on the acquired radiation pattern data of the entire array antenna. However, acquiring complete radiation pattern data requires a large amount of data sampling, which is a huge workload, and the computational load when inferring the excitation based on the sampled data is also relatively large, so its execution efficiency is difficult to guarantee. In particular, for square kilometer array antennas used in radio telescopes, the drawbacks of the above-mentioned existing methods limit their application in square kilometer array antennas. Summary of the Invention

[0005] To address the aforementioned problems in the prior art, this invention provides a method for reconstructing the radiation pattern of a directional antenna.

[0006] The technical problem to be solved by this invention is achieved through the following technical solution:

[0007] A method for synthesizing array antennas based on directional antenna radiation pattern reconstruction includes:

[0008] A. Initialize the population, initialize the population iteration count i = 1, set the upper limit of the population iteration count, and obtain the unit radiation pattern data of each element of the array antenna in the first cross section; the first cross section is the target cross section in the radiation pattern of the array antenna that needs to optimize the directivity; each body in the population corresponds to a set of excitation data, which consists of the excitation amplitude and excitation phase of each element of the array antenna.

[0009] B. Based on the current set of excitation data, the unit radiation pattern data of each array element in the first cross-section are superimposed to obtain the array radiation pattern data of the array antenna in the first cross-section; based on the array radiation pattern data of the array antenna in the first cross-section, the radiation performance index of the array antenna in the first cross-section is obtained.

[0010] C. Calculate the fitness of each individual in the population based on the radiation performance index of the array antenna in the first section; the fitness is used to measure the difference between the radiation performance index of the array antenna in the first section and the corresponding expected index.

[0011] D. Determine whether the current iteration cutoff condition is met; if the iteration cutoff condition is met, proceed to step E; if the iteration cutoff condition is not met, perform individual mutation, crossover, and selection operations, let i = i + 1, and then return to step B; wherein, the iteration cutoff condition includes: i reaches the upper limit of the population iteration count or an individual's fitness reaches the expected target.

[0012] E. Determine the optimal individual based on the fitness of all individuals; obtain the element pattern data of each array element in the second section based on a set of excitation data corresponding to the optimal individual; reconstruct the array antenna pattern based on the element pattern data of each array element in the second section; wherein, the second section is any section of the array antenna pattern.

[0013] F. Determine whether the currently reconstructed array antenna pattern meets the requirements; if it does, use the set of excitation data corresponding to the optimal individual as the array antenna synthesis result; if it does not meet the requirements, return to step A.

[0014] Optionally, in step B, based on the current set of excitation data, the element radiation pattern data of each array element in the first cross-section are superimposed to obtain the array radiation pattern data of the array antenna in the first cross-section, including:

[0015] Based on the current set of excitation data, the element radiation pattern data of each array element in the first section are superimposed using the array directivity function expression to obtain the array radiation pattern data of the array antenna in the first section.

[0016] The expression for the array directionality function is:

[0017]

[0018] The array antenna comprises M rows and N columns of array elements, I mn φ represents the excitation amplitude of the array element in the (m+1)th row and (n+1)th column. mn This represents the excitation phase of the array element in the (m+1)th row and (n+1)th column; This indicates the coordinates of the array element in the (m+1)th row and (n+1)th column. The direction map value at this coordinate The coordinate system in which it is located is a Cartesian coordinate system mapped from the spherical coordinate system in which the radiation pattern is located; the radiation pattern data of the array element in the (m+1)th row and (n+1)th column in the first sectional plane is obtained by... Pick The result is obtained from θ = [0°, 180°]. This is the first cross-section; The spatial rectangular coordinates corresponding to the beam pointing of the array antenna are: d x d represents the row element spacing of the array antenna. y This indicates the column element spacing of the array antenna. λ is the operating wavelength of the array antenna; This indicates that the superimposed array antenna is located in coordinates. The directional pattern value at that location.

[0019] Optionally, the fitness function for calculating the fitness is as follows:

[0020]

[0021] Where G represents the maximum gain of the array antenna, G e It is the expected value of G; The array antennas are represented sequentially in the following order. Maximum sidelobe level at that time In order are The expected value, where cost is the fitness, r0, r1, r2, and r L All of these are preset weights.

[0022] Optionally, in step E, reconstructing the array antenna pattern based on the element pattern data of each array element in the second section includes:

[0023] The complete element radiation pattern of the array element is reconstructed by interpolation based on the element radiation pattern data of each element in the second sectional plane, thus obtaining the complete element radiation pattern data of the array element.

[0024] The complete radiation pattern data of each array element are superimposed using the array directivity function expression to obtain the array antenna radiation pattern.

[0025] Optionally, the method further includes:

[0026] When superimposing the element pattern data of each array element in the first cross-section using the array directivity function expression, and when superimposing the complete pattern data of each array element using the array directivity function expression, both are done using... The excitation amplitude of the array element in the (m+1)th row and (n+1)th column is corrected;

[0027] Among them, ActiveS ii This represents the active voltage reflection coefficient of the array element in the (m+1)th row and (n+1)th column.

[0028] Optionally, the array antenna includes: a square kilometer array antenna.

[0029] The present invention also provides an array antenna synthesis device based on directional antenna radiation pattern reconstruction, comprising: a storage module and a processing module;

[0030] The storage module is used to store computer programs;

[0031] The processor is configured to execute the computer program to perform the following method steps:

[0032] A. Initialize the population, initialize the population iteration count i = 1, set the upper limit of the population iteration count, and obtain the unit radiation pattern data of each element of the array antenna in the first cross section; the first cross section is the target cross section in the radiation pattern of the array antenna that needs to optimize the directivity; each body in the population corresponds to a set of excitation data, which consists of the excitation amplitude and excitation phase of each element of the array antenna.

[0033] B. Based on the current set of excitation data, the unit radiation pattern data of each array element in the first cross-section are superimposed to obtain the array radiation pattern data of the array antenna in the first cross-section; based on the array radiation pattern data of the array antenna in the first cross-section, the radiation performance index of the array antenna in the first cross-section is obtained.

[0034] C. Calculate the fitness of each individual in the population based on the radiation performance index of the array antenna in the first section; the fitness is used to measure the difference between the radiation performance index of the array antenna in the first section and the corresponding expected index.

[0035] D. Determine whether the current iteration cutoff condition is met; if the iteration cutoff condition is met, proceed to step E; if the iteration cutoff condition is not met, perform individual mutation, crossover, and selection operations, let i = i + 1, and then return to step B; wherein, the iteration cutoff condition includes: i reaches the upper limit of the population iteration count or an individual's fitness reaches the expected target.

[0036] E. Determine the optimal individual based on the fitness of all individuals; obtain the element pattern data of each array element in the second section based on a set of excitation data corresponding to the optimal individual; reconstruct the array antenna pattern based on the element pattern data of each array element in the second section; wherein, the second section is any section of the array antenna pattern.

[0037] F. Determine whether the currently reconstructed array antenna pattern meets the requirements; if it does, use the set of excitation data corresponding to the optimal individual as the array antenna synthesis result; if it does not meet the requirements, return to step A.

[0038] Optionally, in step B, based on the current set of excitation data, the element radiation pattern data of each array element in the first cross-section are superimposed to obtain the array radiation pattern data of the array antenna in the first cross-section, including:

[0039] Based on the current set of excitation data, the element radiation pattern data of each array element in the first section are superimposed using the array directivity function expression to obtain the array radiation pattern data of the array antenna in the first section.

[0040] The expression for the array directionality function is:

[0041]

[0042] The array antenna comprises M rows and N columns of array elements, I mn φ represents the excitation amplitude of the array element in the (m+1)th row and (n+1)th column. mn This represents the excitation phase of the array element in the (m+1)th row and (n+1)th column; This indicates the coordinates of the array element in the (m+1)th row and (n+1)th column. The direction map value at this coordinate The coordinate system in which it is located is a spatial rectangular coordinate system mapped from the spherical coordinate system in which the radiation pattern is located; the element radiation pattern data of the (m+1)th row and (n+1)th column in the first sectional plane is obtained by... Pick The result is obtained from θ = [0°, 180°]. This is the first cross-section; The spatial rectangular coordinates corresponding to the beam pointing of the array antenna are: d xd represents the row element spacing of the array antenna. y This indicates the column element spacing of the array antenna. λ is the operating wavelength of the array antenna; This indicates that the superimposed array antenna is located in coordinates. The directional pattern value at that location.

[0043] Optionally, the fitness is calculated using the following formula:

[0044]

[0045] Where G represents the maximum gain of the array antenna, G e It is the expected value of G; The array antennas are represented sequentially in the following order. Maximum sidelobe level at that time In order are The expected value.

[0046] Optionally, in step E, reconstructing the array antenna pattern based on the element pattern data of each array element in the second section includes:

[0047] The complete radiation pattern of the array element is reconstructed by interpolation based on the element radiation pattern data of each element in the second cross section, thus obtaining the complete element radiation pattern data of the array element.

[0048] The complete radiation pattern data of each array element are superimposed using the array directivity function expression to obtain the array antenna radiation pattern.

[0049] The directional antenna radiation pattern reconstruction method provided by this invention first imports the unit radiation pattern data of each element of the array antenna in the first section as known data into an intelligent optimization algorithm. Then, the intelligent optimization algorithm obtains a set of optimal excitation data with good radiation performance indices in the first section. Next, based on this set of excitation data, the unit radiation pattern data of each element in the second section is obtained, and the array antenna radiation pattern is reconstructed according to the unit radiation pattern data of each element in the second section. If the array antenna radiation pattern meets the requirements at this point, the set of excitation data corresponding to the optimal individual is used as the array antenna synthesis result. If it does not meet the requirements, the target section to be optimized can be redefined based on the current array antenna radiation pattern, and a new round of iterative optimization can begin. In the iterative process using the intelligent optimization algorithm, each iteration only superimposes the unit radiation pattern data of each element in the first section, and only reconstructs the array antenna radiation pattern based on the unit radiation pattern data of each element in the second section. It does not require the radiation pattern data of the entire array antenna in both the first and second sections. Therefore, this invention requires less data for antenna synthesis, and the corresponding algorithm iteration speed is relatively fast, making it applicable to the synthesis of square kilometer array antennas.

[0050] The present invention will now be described in further detail with reference to the accompanying drawings. Attached Figure Description

[0051] Figure 1 This is a flowchart of an array antenna synthesis method based on directional antenna radiation pattern reconstruction provided by an embodiment of the present invention;

[0052] Figure 2 This is a schematic diagram of the array element arrangement of the antenna array;

[0053] Figure 3 This is a schematic diagram of pattern interpolation reconstruction in a rectangular coordinate system according to an embodiment of the present invention;

[0054] Figure 4 This is a comparison diagram of the interpolation reconstruction result of the radiation pattern of a planar dipole antenna by referring to the direct reconstruction method in the existing technology and its actual radiation pattern;

[0055] Figure 5 This is an exemplary schematic diagram of the array element arrangement of an array antenna;

[0056] Figure 6 It refers to the direct reconstruction method in existing technologies. Figure 5 The diagram shows the result of interpolating and reconstructing the radiation pattern of the array antenna and comparing it with the actual radiation pattern.

[0057] Figure 7 yes Figure 6 Cross-sectional radiation pattern data in the radiation pattern;

[0058] Figure 8 The method of indirect reconstruction in the embodiments of the present invention is referred to. Figure 5 The diagram shows the result of interpolating and reconstructing the radiation pattern of the array antenna and comparing it with the actual radiation pattern.

[0059] Figure 9 yes Figure 8 Cross-sectional radiation pattern data in the radiation pattern;

[0060] Figure 10 This is a comparison between the optimized radiation pattern of an SKA obtained using the method of this embodiment and its actual radiation pattern;

[0061] Figure 11 yes Figure 10 The cross-sectional radiation pattern data in the radiation pattern. Detailed Implementation

[0062] The present invention will be further described in detail below with reference to specific embodiments, but the implementation of the present invention is not limited thereto.

[0063] To improve the synthesis efficiency of array antennas and thus achieve the synthesis of square kilometer array antennas, this invention provides an array antenna synthesis method based on directional antenna radiation pattern reconstruction, such as... Figure 1 As shown, the method includes the following steps:

[0064] A. Initialize the population, initialize the population iteration count i = 1, set the upper limit of the population iteration count, and obtain the unit radiation pattern data of each element of the array antenna in the first cross section; the first cross section is the target cross section in the radiation pattern of the array antenna that needs to optimize the directivity; each body in the population corresponds to a set of excitation data, which consists of the excitation amplitude and excitation phase of each element of the array antenna.

[0065] There are several ways to obtain the element radiation pattern data of each element in the first cross-section of the array antenna. For example, the array antenna can be modeled and simulated, and the current set of excitation data can be input into the modeled array antenna, causing each element to radiate according to its own excitation data, thereby obtaining the radiation pattern of each element, and then extracting the element radiation pattern data of that element in the first cross-section. Alternatively, the current set of excitation data can be input into the array antenna through actual measurement to obtain the element radiation pattern data of each element in the first cross-section. In both of the above methods, the AEP method can be used to obtain the radiation pattern of the array element. The AEP method was first proposed by Hansen in the paper "Microwave Scanning Antennas" in 1966. It refers to obtaining the far-field radiation pattern of the array element by exciting only one reference element in the array environment while connecting the other elements to a matched load.

[0066] In this embodiment of the invention, the length of an individual in the population is 2X, where the first X bits represent the excitation amplitude of each element, the last X bits represent the excitation phase of each element, and X is the number of elements in the array antenna. The structure of the array antenna is described below. Figure 2 As shown, it includes M×N array elements.

[0067] B. Based on the current set of excitation data, the unit radiation pattern data of each array element in the first section are superimposed to obtain the array radiation pattern data of the array antenna in the first section; based on the array radiation pattern data of the array antenna in the first section, the radiation performance index of the array antenna in the first section is obtained.

[0068] Specifically, based on the current set of excitation data, the element radiation pattern data of each array element in the first section are superimposed using the array directivity function expression to obtain the array radiation pattern data of the array antenna in the first section.

[0069] The expression for the array directivity function is as follows:

[0070]

[0071] The array antenna comprises M rows and N columns of array elements, I mn φ represents the excitation amplitude of the array element in the (m+1)th row and (n+1)th column. mn This represents the excitation phase of the array element in the (m+1)th row and (n+1)th column; This indicates the coordinates of the array element in the (m+1)th row and (n+1)th column. The direction map value at this coordinate The coordinate system in which it is located is a spatial rectangular coordinate system mapped from the spherical coordinate system in which the radiation pattern is located; the element radiation pattern data of the (m+1)th row and (n+1)th column in the first sectional plane is obtained by... Pick The result is obtained from θ = [0°, 180°]. This is the first cross-section; The spatial rectangular coordinates corresponding to the beam pointing of the array antenna are: d x d represents the row element spacing of the array antenna. y This indicates the column element spacing of the array antenna. λ is the operating wavelength of the array antenna; This indicates that the superimposed array antenna is located in coordinates. The directional pattern value at that location.

[0072] In the expression for the array's directivity function, the phase shift Δφ along the x and y directions... x and Δφ y They are independent of each other, and can be changed by Δφ x and Δφ y It is possible to achieve this in the condition 0 ≤ θ ≤ π / 2. Inside, beam scanning in any direction.

[0073] Understandably, with the array pattern data of the array antenna in the first cross-section, the radiation performance indicators of the array antenna in the first cross-section can be obtained. For example, these radiation performance indicators may include the maximum gain of the array antenna and the maximum sidelobe level of the array antenna in the first cross-section, but are not limited to these.

[0074] In a preferred implementation, during step B, when superimposing the element radiation pattern data of each array element in the first sectional plane, the following can be utilized: The excitation amplitude of the array element in the (m+1)th row and (n+1)th column is corrected; that is, the I input to the array element in the (m+1)th row and (n+1)th column is adjusted. mn Based on this, multiply it by Replace the old I with the obtained value. mn Among them, ActiveS ii This represents the active voltage reflection coefficient of the array element in the (m+1)th row and (n+1)th column. The active voltage reflection coefficient ActiveS for any array element... ii The calculation formula is:

[0075]

[0076] Among them, a i This indicates the target array element whose active voltage reflection coefficient needs to be calculated, a. k These are other array elements that influence the target array element, typically array elements adjacent to the target array element. Their number, num, is related to the array element spacing, and this embodiment of the invention does not limit this number. ik β represents the transmission coefficient from the k-th element to the i-th element.k The input voltage phase of the kth other array element relative to the target array element.

[0077] It is understandable that in an antenna array, due to the surrounding environment and the mutual coupling between array elements, the radiation pattern of some array elements will deviate, and the active reflection coefficient will also change. This will lead to different directivity functions for many array elements and the radiation current not being equal to the input current. If the coupling is severe, the impact will be even greater. Therefore, in this embodiment of the invention, considering the mutual coupling between array elements, an active voltage reflection coefficient is further introduced into the array directivity function expression, making the final superposition result more realistic and accurate.

[0078] C. Calculate the fitness of each individual in the population based on the radiation performance index of the array antenna in the first section; this fitness is used to measure the difference between the radiation performance index of the array antenna in the first section and the corresponding expected index.

[0079] Understandably, the fitness function used to calculate the fitness of an individual will vary depending on the radiation performance indicators considered and the first aspect to be optimized.

[0080] For example, taking radiation performance indicators including the maximum gain of the antenna and the maximum sidelobe level of the array antenna in the first section as an example, the fitness can be calculated using the following fitness function:

[0081]

[0082] Where G represents the maximum gain of the array antenna, G e It is the expected value of G; The array antennas are represented sequentially in the following order. Maximum sidelobe level at that time In order are The expected value, where cost is fitness, r0, r1, r2, and r L All of these are preset weights.

[0083] It is understood that, based on the fitness function described above, other forms of fitness functions can be obtained by changing the radiation performance index considered, which will not be elaborated further in the embodiments of this invention.

[0084] D. Determine if the iteration cutoff condition is met; if the iteration cutoff condition is met, proceed to step E; if the iteration cutoff condition is not met, perform individual mutation, crossover, and selection operations, let i = i + 1, and then return to step B.

[0085] The iteration cutoff conditions include: i reaches the upper limit of the population iteration count or an individual's fitness reaches the expected target.

[0086] Understandably, since fitness measures the difference between the radiation performance index of the array antenna in the first section and the corresponding expected index, an individual with lower fitness is more likely to become the optimal individual. Therefore, this step determines the optimal individual based on the fitness of all individuals, specifically the individual with the lowest fitness. When an individual's fitness reaches the expected target, for example, when an individual's fitness is equal to or close to 0, then that individual's fitness is considered to have reached the expected target.

[0087] E. Determine the optimal individual based on the fitness of all individuals; obtain the element pattern data of each array element in the second section based on a set of excitation data corresponding to the optimal individual; reconstruct the array antenna pattern based on the element pattern data of each array element in the second section; wherein, the second section is any section of the array antenna pattern.

[0088] In this process, the unit radiation pattern data of each array element in the second sectional plane is obtained based on a set of excitation data corresponding to the optimal individual. The implementation method of obtaining the unit radiation pattern data of each array element in the first sectional plane in step A can be referred to, and will not be repeated here.

[0089] The array antenna pattern is reconstructed based on the element pattern data of each element in the second section, including:

[0090] (1) Based on the element radiation pattern data of each element in the second sectional plane, the complete element radiation pattern of the array element is reconstructed by interpolation to obtain the complete element radiation pattern data of the array element;

[0091] Specifically, for the element radiation pattern data of each array element in the second sectional plane, the element radiation pattern data is first transformed into a Cartesian coordinate system. Then, in the range θ = 0 to π, Within a certain range, sampling boundaries are uniformly selected to divide the coordinate-transformed cell pattern data into multiple regions, and then interpolation reconstruction is performed on each region.

[0092] For example, such as Figure 3 As shown, uniformly selected As sampling boundaries, the coordinate-transformed cell radiation pattern data is divided into four regions: I, II, III, and IV, and then interpolation reconstruction is performed on each region.

[0093] Taking region I as an example, based on the idea of ​​one-dimensional interpolation, first fix θ, and then along... First-order Lagrange interpolation is performed in the direction:

[0094]

[0095] Where G1(θ) and G2(θ) represent the directional pattern values ​​on the left and right boundaries of region I, respectively. It is obtained by interpolation. Direction value, G1(θ) and The distance between them G2(θ) and The distance between them.

[0096] Then, fix First-order Lagrange interpolation along the θ direction:

[0097]

[0098] in, and H(θ) represents the directional pattern values ​​on the upper and lower boundaries of region I, respectively. H(θ) is the interpolated θ direction value, and θ2 is... The distance between H(θ) and θ1 is The distance between H(θ) and H(θ).

[0099] Then, the final interpolation is performed, and the interpolation formula is defined as:

[0100]

[0101] in, Represents the position function along the θ direction. Indicates along The position function of direction, α, β, p, q ∈ Z, where Z represents an integer. Typically, α and β both take the value 1, and p and q both take the value 2. It is the direction pattern value obtained by interpolation.

[0102] In existing technologies, the above interpolation reconstruction process is usually directly applied to antennas. For example, for a planar dipole antenna model with an operating frequency of 6 GHz, the radiation pattern of this antenna is interpolated and reconstructed according to the above interpolation reconstruction process, as follows: From the radiation pattern data of the planar dipole antenna, select θ = (0°, 30°, 60°, 90°, 120°, 150°, 180°). The element pattern data is used as the sampling boundary for interpolation reconstruction. The comparison between the reconstructed result and the actual pattern of the planar dipole antenna is as follows: Figure 4 As shown, the maximum error is 1.0585dB and the average error is 0.1303dB. It can be seen that for a single planar dipole antenna, the reconstruction accuracy is relatively high when directly reconstructing the antenna based on the element pattern data of several cross-sections (referred to as direct reconstruction).

[0103] For array antennas, direct interpolation reconstruction results in relatively poor accuracy. For example, a 3×3 SKA (Square Kilometer Array) model was created, using a log-periodic antenna structure as the array elements. Based on the design dimensions of the selected structure and the continuity of the boundary surfaces between different structures, a geometric model was performed on the selected structure, and the elements were uniformly arranged at 2m intervals. The sequence number and position of each element in this SKA are as follows: Figure 5 As shown. Taking the SKA operating at a frequency of 350MHz as an example, the excitation amplitude and excitation phase shown in Table 1 are applied to each element in the above SKA:

[0104] Table 1

[0105]

[0106] Then, direct interpolation reconstruction is performed. Specifically, from the entire SKA radiation pattern data, θ = (0°, 30°, 60°, 90°, 120°, 150°, 180°) is selected. The array pattern data is used as the sampling boundary for interpolation reconstruction. The comparison results between the reconstructed result and the true pattern of the SKA are as follows: Figure 6 and Figure 7 As shown. Among them, the maximum error of the upper half-space radiation pattern is 43.8376dB, and the average error is 2.1302dB. For directional antennas, the lower half-space radiation pattern is often not a concern. It can be seen that for SKA, the reconstruction accuracy of direct interpolation reconstruction is poor. Therefore, in this embodiment of the invention, the direct interpolation reconstruction method is not used to reconstruct the array antenna pattern. Instead, the pattern of each array element is first interpolated and reconstructed to obtain the complete pattern data of each array element. Then, the complete pattern data of each array element are superimposed according to the method shown in step (2) below to obtain the array antenna pattern. This reconstruction method of this embodiment of the invention will be referred to as indirect reconstruction.

[0107] (2) The complete unit radiation pattern data of each array element are superimposed using the above array directivity function expression to obtain the array antenna radiation pattern;

[0108] Specifically, the expression for the array directionality function has been given above, as follows:

[0109]

[0110] in, That is, the array element in the (m+1)th row and (n+1)th column is in coordinates The radiation pattern values ​​at the location; therefore, each array element is located at coordinates By substituting the radiation pattern values ​​at a given location into the array's directivity function expression and superimposing them, the array antenna's position in coordinates can be obtained. directional pattern values ​​at the location Therefore, by using the obtained radiation pattern values ​​of the array antenna at all coordinates, the radiation pattern of the array antenna can be obtained.

[0111] In step E, when superimposing the complete radiation pattern data of each array element using the array directivity function expression, the approach of introducing the active voltage reflection coefficient in step B can also be referenced, that is, using... The excitation amplitude of the array element in the (m+1)th row and (n+1)th column is corrected.

[0112] To verify the effectiveness of the indirect reconstruction method used in this embodiment of the invention, a 3×3 SKA model was created exemplarily. A log-periodic antenna structure was selected as the array element. Based on the design dimensions of the selected structure and the continuity of the boundary surfaces between different structures, a geometric model was created for the selected structure, and the elements were uniformly arranged with dx = 28 mm and dy = 37 mm. Excitation amplitudes and phases as shown in Table 1 above were applied to each element. The radiation pattern of the SKA was then reconstructed using the array directivity function expression. The comparison results between the reconstructed result and the actual radiation pattern of the SKA are shown below. Figure 8 and Figure 9 As shown, the reconstructed pattern is basically consistent with the original simulation pattern, indicating that the indirect reconstruction used in this embodiment is accurate and reliable. Furthermore, from... Figure 8 and Figure 9 Furthermore, it can be obtained that the maximum error of the upper half-space radiation pattern is 30.1331 dB, and the average error is 0.5306 dB, compared to... Figure 6 and Figure 7 As shown in the experimental results of direct reconstruction, the embodiments of the present invention reduced the maximum error by 13.7dB and the average error by 1.6, and the reconstruction accuracy was significantly improved.

[0113] F. Determine whether the current reconstructed array antenna pattern meets the requirements; if it does, use the set of excitation data corresponding to the optimal individual as the array antenna synthesis result; if it does not meet the requirements, return to step A.

[0114] In determining whether the reconstructed array antenna pattern meets the requirements, it is possible to check whether the directivity of the first cross section to be optimized in the array antenna pattern meets the requirements, and at the same time, it is possible to check whether the directivity of other cross sections in the array antenna pattern meets the requirements. That is, the directivity of the entire array antenna pattern can be evaluated. If the reconstructed array antenna pattern meets the requirements, it means that the set of excitation data corresponding to the optimal individual determined in step E is better and can be used as the array antenna synthesis result. If the evaluation finds that the reconstructed array antenna pattern still does not meet the requirements, it is possible to return to step A, and then redetermine the target cross section to be optimized based on the reconstructed array antenna pattern, that is, redetermine the first cross section. The subsequent process can be performed as above until the final reconstructed array antenna pattern meets the requirements.

[0115] The directional antenna radiation pattern reconstruction method provided in this invention first imports the element radiation pattern data of each array element in the first section as known data into an intelligent optimization algorithm. Then, the intelligent optimization algorithm obtains a set of optimal excitation data with good radiation performance indices in the first section. Next, based on this set of excitation data, the element radiation pattern data of each element in the second section is obtained, and the array antenna radiation pattern is reconstructed according to the element radiation pattern data of each element in the second section. If the array antenna radiation pattern meets the requirements, the set of excitation data corresponding to the optimal individual is used as the array antenna synthesis result. If it does not meet the requirements, the target section to be optimized is redefined based on the current array antenna radiation pattern, and a new round of iterative optimization begins. In the iterative process using the intelligent optimization algorithm, each iteration only superimposes the element radiation pattern data of each element in the first section and only reconstructs the array antenna radiation pattern based on the element radiation pattern data of each element in the second section. It does not require the array radiation pattern data of the entire array antenna in both the first and second sections. Therefore, this invention requires less data for antenna synthesis, and the corresponding algorithm iteration speed is relatively fast, making it suitable for the synthesis of square kilometer array antennas.

[0116] To verify the effectiveness of the array antenna synthesis method based on directional antenna radiation pattern reconstruction provided in this embodiment of the invention, the following simulation experiments were conducted:

[0117] Specifically, initialize a population of size 300, with individuals of length 2N, where N = 3, and an operating frequency of 300MHz. x =d y =2m. The maximum number of iterations for initializing the population is 20,000. The first sectional area is initially determined to be (0°, 90°). The fitness function used in the corresponding iteration process is:

[0118]

[0119]

[0120] in, G e =14dBi.

[0121] After initializing the population iteration count i = 1, iteration can begin. During iteration, the optimal individual in the current population is saved every 30 generations. For detailed iteration procedures, refer to steps A to E above, which will not be repeated here. Experiments show that the average iteration time in this embodiment is only about 1 second, while existing array antenna synthesis methods generally require about 30 seconds. Therefore, this embodiment significantly improves synthesis efficiency. Finally, a set of excitation data is obtained as shown in Table 2. This set of excitation data is substituted into simulation software to draw a radiation pattern, and the results are compared with the simulation pattern initially used as the optimization target. Figure 10 and Figure 11 As shown, the simulation results obtained through synthesis are basically consistent with the optimization target, proving the effectiveness of the embodiments of the present invention.

[0122] Table 2

[0123]

[0124] Corresponding to the above-described array antenna synthesis method based on directional antenna radiation pattern reconstruction, this embodiment of the invention also provides an array antenna synthesis device based on directional antenna radiation pattern reconstruction, including: a storage module and a processing module;

[0125] This storage module is used to store computer programs;

[0126] The processor is configured to execute the computer program to perform the following method steps:

[0127] A. Initialize the population, initialize the population iteration count i = 1, set the upper limit of the population iteration count, and obtain the unit radiation pattern data of each element of the array antenna in the first cross section; the first cross section is the target cross section in the radiation pattern of the array antenna that needs to optimize the directivity; each body in the population corresponds to a set of excitation data, which consists of the excitation amplitude and excitation phase of each element of the array antenna.

[0128] B. Based on the current set of excitation data, the unit radiation pattern data of each array element in the first cross-section are superimposed to obtain the array radiation pattern data of the array antenna in the first cross-section; based on the array radiation pattern data of the array antenna in the first cross-section, the radiation performance index of the array antenna in the first cross-section is obtained.

[0129] C. Calculate the fitness of each individual in the population based on the radiation performance index of the array antenna in the first section; the fitness is used to measure the difference between the radiation performance index of the array antenna in the first section and the corresponding expected index.

[0130] D. Determine whether the current iteration cutoff condition is met; if the iteration cutoff condition is met, proceed to step E; if the iteration cutoff condition is not met, perform individual mutation, crossover, and selection operations, let i = i + 1, and then return to step B; wherein, the iteration cutoff condition includes: i reaches the upper limit of the population iteration count or an individual's fitness reaches the expected target.

[0131] E. Determine the optimal individual based on the fitness of all individuals; obtain the element pattern data of each array element in the second section based on a set of excitation data corresponding to the optimal individual; reconstruct the array antenna pattern based on the element pattern data of each array element in the second section; wherein, the second section is any section of the array antenna pattern.

[0132] F. Determine whether the currently reconstructed array antenna pattern meets the requirements; if it does, use the set of excitation data corresponding to the optimal individual as the array antenna synthesis result; if it does not meet the requirements, return to step A.

[0133] Optionally, in step B,

[0134] Based on the current set of excitation data, the element radiation pattern data of each array element in the first cross-section are superimposed to obtain the array radiation pattern data of the array antenna in the first cross-section, including:

[0135] Based on the current set of excitation data, the element radiation pattern data of each array element in the first section are superimposed using the array directivity function expression to obtain the array radiation pattern data of the array antenna in the first section.

[0136] The expression for the array directionality function is:

[0137]

[0138] The array antenna comprises M rows and N columns of array elements, I mn φ represents the excitation amplitude of the array element in the (m+1)th row and (n+1)th column. mn This represents the excitation phase of the array element in the (m+1)th row and (n+1)th column; This indicates the coordinates of the array element in the (m+1)th row and (n+1)th column. The direction map value at this coordinate The coordinate system in which it is located is a spatial rectangular coordinate system mapped from the spherical coordinate system in which the radiation pattern is located; the element radiation pattern data of the (m+1)th row and (n+1)th column in the first sectional plane is obtained by... Pick The result is obtained from θ = [0°, 180°]. This is the first cross-section; The spatial rectangular coordinates corresponding to the beam pointing of the array antenna are: d x d represents the row element spacing of the array antenna. y This indicates the column element spacing of the array antenna. λ is the operating wavelength of the array antenna; This indicates that the superimposed array antenna is located in coordinates. The directional pattern value at that location.

[0139] Alternatively, the formula for calculating fitness is as follows:

[0140]

[0141] Where G represents the maximum gain of the array antenna, G e It is the expected value of G; The array antennas are represented sequentially in the following order. Maximum sidelobe level at that time In order are The expected value.

[0142] Optionally, in step E,

[0143] The array antenna pattern is reconstructed based on the element pattern data of each element in the second section, including:

[0144] The complete radiation pattern of the array element is reconstructed by interpolation based on the element radiation pattern data of each element in the second cross section, thus obtaining the complete element radiation pattern data of the array element.

[0145] The complete radiation pattern data of each array element are superimposed using the array directivity function expression to obtain the array antenna radiation pattern.

[0146] Optionally, the method steps implemented by the processor when executing the above computer program may further include:

[0147] When superimposing the element pattern data of each array element in the first cross-section using the array directivity function expression, and when superimposing the complete pattern data of each array element using the array directivity function expression, both are done using... The excitation amplitude of the array element in the (m+1)th row and (n+1)th column is corrected;

[0148] Among them, ActiveS ii This represents the active voltage reflection coefficient of the array element in the (m+1)th row and (n+1)th column.

[0149] Optionally, the array antenna includes: a square kilometer array antenna.

[0150] It should be noted that, for the device embodiment, since it is basically similar to the method embodiment, the description is relatively simple, and relevant parts can be referred to in the description of the method embodiment.

[0151] In summary, in this embodiment of the invention, the radiation pattern of the array elements is reconstructed using a small amount of cross-sectional data interpolation, which reduces the complexity of the data sampling stage, reduces measurement costs, and saves computer resources. In this embodiment of the invention, the active radiation patterns of the antenna array elements (radio patterns obtained considering the active voltage reflection coefficient) are superimposed to obtain a more accurate array antenna radiation pattern, which is applicable to complex square kilometer arrays. In this embodiment of the invention, by using an intelligent optimization algorithm for array antenna synthesis, a set of optimal excitation data that meets or closely approximates the target conditions can be obtained, thereby achieving better antenna array synthesis.

[0152] It should be noted that the terms "first," "second," etc., are used to distinguish similar objects and are not necessarily used to describe a specific order or sequence. It should be understood that such data can be interchanged where appropriate so that the embodiments of the invention described herein can be implemented in orders other than those illustrated or described herein. The embodiments described in the following exemplary embodiments do not represent all embodiments consistent with the present invention. Rather, they are merely examples of apparatuses and methods consistent with some aspects of the invention.

[0153] In the description of this specification, the references to terms such as "one embodiment," "some embodiments," "example," "specific example," or "some examples," etc., indicate that a specific feature or characteristic described in connection with that embodiment or example is included in at least one embodiment or example of the present invention. In this specification, the illustrative expressions of the above terms do not necessarily refer to the same embodiment or example. Furthermore, the specific features or characteristics described may be combined in any suitable manner in one or more embodiments or examples. In addition, those skilled in the art can combine and integrate the different embodiments or examples described in this specification.

[0154] Although the invention has been described herein in conjunction with various embodiments, those skilled in the art will understand and implement other variations of the disclosed embodiments by reviewing the accompanying drawings and the disclosure in carrying out the claimed invention. In the description of the invention, the word "comprising" does not exclude other components or steps, "a" or "an" does not exclude a plurality, and "a plurality" means two or more, unless otherwise explicitly specified. Furthermore, while different embodiments may describe certain measures, this does not mean that these measures cannot be combined to produce good results.

[0155] Those skilled in the art will understand that embodiments of the present invention can be provided as methods, apparatus (devices), or computer program products. Therefore, the present invention can take the form of a completely hardware embodiment, a completely software embodiment, or an embodiment combining software and hardware aspects, all of which are collectively referred to herein as "modules" or "systems." Furthermore, 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 storage, CD-ROM, optical storage, etc.) containing computer-usable program code. The computer program may be stored / distributed in a suitable medium, provided with or as part of other hardware, or may take other distribution forms, such as via the Internet or other wired or wireless telecommunications systems.

[0156] This invention is described with reference to flowchart illustrations and / or block diagrams of methods, apparatus (devices), and computer program products according to embodiments of the invention. It will be understood that each block of the flowchart illustrations and / or block diagrams, and combinations of blocks in the flowchart illustrations and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, special-purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, generate instructions for implementing the flowchart illustrations and / or block diagrams. Figure 1 One or more processes and / or boxes Figure 1 A device that provides the functions specified in one or more boxes.

[0157] These computer program instructions may also be stored in a computer-readable storage medium that can direct a computer or other programmable data processing device to function in a particular manner, such that the instructions stored in the computer-readable storage medium produce an article of manufacture including instruction means, which are implemented in a process Figure 1 One or more processes and / or boxes Figure 1 The function specified in one or more boxes.

[0158] These computer program instructions may also be loaded onto a computer or other programmable data processing equipment to cause a series of operational steps to be performed on the computer or other programmable equipment to produce a computer-implemented process, thereby providing instructions that execute on the computer or other programmable equipment for implementing the process. Figure 1 One or more processes and / or boxes Figure 1 The steps of the function specified in one or more boxes.

[0159] The above description, in conjunction with specific preferred embodiments, provides a further detailed explanation of the present invention. It should not be construed that the specific implementation of the present invention is limited to these descriptions. For those skilled in the art, various simple deductions or substitutions can be made without departing from the concept of the present invention, and all such modifications and substitutions should be considered within the scope of protection of the present invention.

Claims

1. A method for synthesizing array antennas based on radiation pattern reconstruction of directional antennas, characterized in that, include: A. Initialize the population and initialize the number of population iterations. i =1, set the upper limit of the number of population iterations, and obtain the unit radiation pattern data of each element of the array antenna in the first cross section; The first cross section is the target cross section in the radiation pattern of the array antenna that needs to be optimized for directivity; each individual in the population corresponds to a set of excitation data, which consists of the excitation amplitude and excitation phase of each element of the array antenna; B. Based on the current set of excitation data, the unit radiation pattern data of each array element in the first cross-section are superimposed to obtain the array radiation pattern data of the array antenna in the first cross-section; based on the array radiation pattern data of the array antenna in the first cross-section, the radiation performance index of the array antenna in the first cross-section is obtained. C. Calculate the fitness of each individual in the population based on the radiation performance index of the array antenna in the first section; the fitness is used to measure the difference between the radiation performance index of the array antenna in the first section and the corresponding expected index. D. Determine whether the iteration deadline condition is met; If the iteration cutoff condition is met, proceed to step E; If the iteration deadline is not met, perform mutation, crossover, and selection operations on the individual, and let... i = i +1, then return to step B; wherein the iteration cutoff condition includes: i The population reaches its maximum number of iterations or an individual's fitness reaches the expected target. E. Determine the optimal individual based on the fitness of all individuals; obtain the element pattern data of each array element in the second section based on a set of excitation data corresponding to the optimal individual; reconstruct the array antenna pattern based on the element pattern data of each array element in the second section; wherein, the second section is any section of the array antenna pattern. F. Determine whether the currently reconstructed array antenna pattern meets the requirements; if it does, use the set of excitation data corresponding to the optimal individual as the array antenna synthesis result; if it does not meet the requirements, return to step A. In step B, based on the current set of excitation data, the element radiation pattern data of each array element in the first cross-section are superimposed to obtain the array radiation pattern data of the array antenna in the first cross-section, including: Based on the current set of excitation data, the element radiation pattern data of each array element in the first section are superimposed using the array directivity function expression to obtain the array radiation pattern data of the array antenna in the first section. The expression for the array directionality function is: ； Among them, the array antenna includes M OK, N The array elements of the column, Indicates the first m+ Line 1, No. n+ The excitation amplitude of an array element in column 1, Indicates the first m+ Line 1, No. n+ The excitation phase of an array element in one column; Indicates the first m+ Line 1, No. n+ The array elements in column 1 are in coordinates The direction map value at this coordinate The coordinate system in which it is located is a rectangular coordinate system mapped from the spherical coordinate system in which the radiation pattern is located; the first m+ Line 1, No. n+ The element pattern data of one column of array elements in the first section is obtained by analyzing the element pattern data of the first section of array elements. Pick , What was obtained This is the first cross-section; , The beam pointing of the array antenna corresponds to the spatial rectangular coordinates as follows: , This indicates the row element spacing of the array antenna. This indicates the column element spacing of the array antenna. , The operating wavelength of the array antenna; This indicates that the superimposed array antenna is located in coordinates. The directional pattern value at that location.

2. The array antenna synthesis method based on directional antenna radiation pattern reconstruction according to claim 1, characterized in that, The fitness function for calculating the fitness is as follows: in, This indicates the maximum gain of the array antenna. Yes Expected value; , , The array antennas are represented sequentially in the following order. Maximum sidelobe level at that time , , In order are , , The expected value, For fitness, , , as well as All of these are preset weights.

3. The array antenna synthesis method based on directional antenna radiation pattern reconstruction according to claim 1, characterized in that, In step E, the array antenna pattern is reconstructed based on the element pattern data of each array element in the second section, including: The complete element radiation pattern of the array element is reconstructed by interpolation based on the element radiation pattern data of each element in the second sectional plane, thus obtaining the complete element radiation pattern data of the array element. The complete radiation pattern data of each array element are superimposed using the array directivity function expression to obtain the array antenna radiation pattern.

4. The array antenna synthesis method based on directional antenna radiation pattern reconstruction according to claim 3, characterized in that, The method further includes: When superimposing the element pattern data of each array element in the first cross-section using the array directivity function expression, and when superimposing the complete pattern data of each array element using the array directivity function expression, both are done using... For the m+ Line 1, No. n+ The excitation amplitude of the array elements in column 1 is corrected; in, Indicates the first m+ Line 1, No. n+ The active voltage reflection coefficient of an array element in column 1.

5. The array antenna synthesis method based on directional antenna radiation pattern reconstruction according to any one of claims 1 to 4, characterized in that, The array antenna includes: a square kilometer array antenna.

6. A device for synthesizing array antennas based on directional antenna radiation pattern reconstruction, characterized in that, include: Storage module and processing module; The storage module is used to store computer programs; The processing module is configured to execute the computer program to implement the following method steps: A. Initialize the population and initialize the number of population iterations. i =1, set the upper limit of the number of population iterations, and obtain the unit radiation pattern data of each element of the array antenna in the first cross section; The first cross section is the target cross section in the radiation pattern of the array antenna that needs to be optimized for directivity; each individual in the population corresponds to a set of excitation data, which consists of the excitation amplitude and excitation phase of each element of the array antenna; B. Based on the current set of excitation data, the unit radiation pattern data of each array element in the first cross-section are superimposed to obtain the array radiation pattern data of the array antenna in the first cross-section; based on the array radiation pattern data of the array antenna in the first cross-section, the radiation performance index of the array antenna in the first cross-section is obtained. Specifically, based on the current set of excitation data, the element radiation pattern data of each array element in the first cross-section are superimposed to obtain the array radiation pattern data of the array antenna in the first cross-section, including: Based on the current set of excitation data, the element radiation pattern data of each array element in the first section are superimposed using the array directivity function expression to obtain the array radiation pattern data of the array antenna in the first section. The expression for the array directionality function is: ； Among them, the array antenna includes M OK, N The array elements of the column, Indicates the first m+ Line 1, No. n+ The excitation amplitude of an array element in column 1, Indicates the first m+ Line 1, No. n+ The excitation phase of an array element in one column; Indicates the first m+ Line 1, No. n+ The array elements in column 1 are in coordinates The direction map value at this coordinate The coordinate system in which it is located is a rectangular coordinate system mapped from the spherical coordinate system in which the radiation pattern is located; the first m+ Line 1, No. n+ The element pattern data of one column of array elements in the first section is obtained by analyzing the element pattern data of the first section of array elements. Pick , What was obtained This is the first cross-section; , The beam pointing of the array antenna corresponds to the spatial rectangular coordinates as follows: , This indicates the row element spacing of the array antenna. This indicates the column element spacing of the array antenna. , The operating wavelength of the array antenna; This indicates that the superimposed array antenna is located in coordinates. directional pattern values ​​at the location C. Calculate the fitness of each individual in the population based on the radiation performance index of the array antenna in the first section; the fitness is used to measure the difference between the radiation performance index of the array antenna in the first section and the corresponding expected index. D. Determine if the iteration cutoff condition is met; if it is, proceed to step E; if not, perform mutation, crossover, and selection operations on the individual, letting... i = i +1, then return to step B; wherein the iteration cutoff condition includes: i The population reaches its maximum number of iterations or an individual's fitness reaches the expected target. E. Determine the optimal individual based on the fitness of all individuals; obtain the element pattern data of each array element in the second section based on a set of excitation data corresponding to the optimal individual; reconstruct the array antenna pattern based on the element pattern data of each array element in the second section; wherein, the second section is any section of the array antenna pattern. F. Determine whether the currently reconstructed array antenna pattern meets the requirements; if it does, use the set of excitation data corresponding to the optimal individual as the array antenna synthesis result; if it does not meet the requirements, return to step A.

7. The array antenna synthesis device based on directional antenna radiation pattern reconstruction according to claim 6, characterized in that, The formula for calculating fitness is as follows: in, This indicates the maximum gain of the array antenna. Yes Expected value; , , The array antennas are represented sequentially in the following order. Maximum sidelobe level at that time , , In order are , , The expected value.

8. The array antenna synthesis device based on directional antenna radiation pattern reconstruction according to claim 6, characterized in that, In step E, the array antenna pattern is reconstructed based on the element pattern data of each array element in the second section, including: The complete radiation pattern of the array element is reconstructed by interpolation based on the element radiation pattern data of each element in the second cross section, thus obtaining the complete element radiation pattern data of the array element. The complete radiation pattern data of each array element are superimposed using the array directivity function expression to obtain the array antenna radiation pattern.

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