Subarray partitioning method based on rotational symmetry

Abstract

The application relates to a subarray partitioning method based on rotational symmetry. The method comprises the following steps: according to a subarray type and an antenna array surface, a dictionary matrix is constructed, each array element on the antenna array surface is labeled according to an arrangement order to obtain an initial array element order, each array element on the antenna array surface is rotated for multiple times according to the symmetry, and the array element order after each rotation is recorded; then a row of candidate subarrays is randomly selected from the dictionary matrix, corresponding multiple rows of candidate subarrays are selected from the dictionary matrix according to the relationship between the initial array element order and the array element order after multiple rotations, the multiple rows of candidate subarrays are added to a subarray partitioning matrix, the multiple rows of candidate subarrays are deleted from the dictionary matrix, the rows related to the multiple rows of candidate subarrays are deleted from the dictionary matrix to form a new dictionary matrix, the deleting operation is continuously performed on the new dictionary matrix, and finally the subarray partitioning of the antenna array surface is realized. The method can improve the speed of subarray partitioning.

Description

Technical Field

[0001] This application relates to the field of antenna technology, and in particular to a subarray partitioning method based on rotational symmetry. Background Technology

[0002] Subarray partitioning is a crucial technique for reducing the manufacturing cost of fully polarized array antennas. By dividing the array into several subarrays, the number of expensive transceiver (T / R) components can be reduced, thereby lowering the overall manufacturing cost of the array antenna. Since directly dividing the array into subarrays with uniform shape and orientation results in high sidelobes during array beam scanning, irregular subarray partitioning becomes an effective alternative. Existing methods for irregular subarray partitioning include the X algorithm and genetic algorithms.

[0003] Algorithm X is a recursive traversal algorithm. It transforms subarray partitioning into multiple "selection-dimensionality reduction" operations on the dictionary matrix, deriving all exact covering solutions for arbitrary array apertures and subarray structures. When traversing all solutions is extremely inefficient, Algorithm X can be improved by setting filtering conditions to eliminate inferior solutions, accelerating the dimensionality reduction of the dictionary matrix, and deriving near-optimal solutions. The drawback of this algorithm is its low computational efficiency when dealing with a huge number of solutions, requiring a balance between fast dimensionality reduction of the dictionary matrix and efficient scanning of near-optimal solutions.

[0004] Genetic algorithms, by designing an objective function related to scanning performance, can transform subarray partitioning into an integer optimization problem, and then use the genetic algorithm to find the optimal partitioning scheme that satisfies the objective function. The drawback of the above algorithm is that its convergence speed is slow when the total number of possible solutions is enormous. Summary of the Invention

[0005] Therefore, it is necessary to provide a method for rapidly solving the above-mentioned technical problems based on rotational symmetry for subarray partitioning.

[0006] A subarray partitioning method based on rotational symmetry, the method comprising:

[0007] Obtain the antenna array surface of the fully polarized array antenna to be subdivided and the type of subarray to be divided;

[0008] A dictionary matrix is ​​constructed based on the subarray type and antenna array, wherein the dictionary matrix is ​​a set of all candidate subarrays, and each row of the dictionary matrix represents a candidate subarray;

[0009] The array elements on the antenna array are numbered according to their arrangement order to obtain the initial array element order. The array elements on the antenna array are rotated multiple times according to symmetry, and the array element order after each rotation is recorded accordingly.

[0010] Randomly select a candidate subarray from the dictionary matrix. Based on the relationship between the initial array element order and the array element order after multiple rotations, select another multiple candidate subarrays from the dictionary matrix and add the selected multiple candidate subarrays to the subarray partitioning matrix.

[0011] The selected candidate subarrays are removed from the dictionary matrix, and the multi-column array elements involved in these candidate subarrays are found in the dictionary matrix. The rows corresponding to the candidate subarrays containing these array elements are deleted to form a new dictionary matrix.

[0012] Continue deleting entries into the new dictionary matrix until the dictionary matrix is ​​empty, thus achieving precise coverage division of the antenna array.

[0013] In one embodiment, each row of the dictionary matrix is ​​arranged according to the position order of the array elements, and "1" indicates that the array element belongs to the candidate subarray represented by the current row, and "0" indicates that the array element does not belong to the candidate subarray represented by the current row.

[0014] Each column in the dictionary matrix represents the position of an array element.

[0015] In one embodiment, when rotating each element on the antenna array multiple times according to symmetry, and recording the element order after each rotation accordingly:

[0016] Each time a rotation is performed, the number representing the current array element order rotates along with it, and then the numbers are recorded according to the order after the rotation to obtain the rotated array element order.

[0017] In one embodiment, the step of randomly selecting a candidate subarray row from the dictionary matrix and selecting corresponding additional candidate subarray rows from the dictionary matrix based on the relationship between the initial element order and the element order after multiple rotations includes:

[0018] The randomly selected row of candidate subarrays corresponds to the initial array element order, and the corresponding number representing "1" in the candidate subarray is found in the initial array element order;

[0019] In the array element order obtained after each rotation, the corresponding number position is represented as "1" and other positions are represented as "0", so that multiple rows of candidate subarrays can be obtained and selected from the dictionary matrix.

[0020] In one embodiment, when continuing to delete from a new dictionary matrix, a candidate subarray adjacent to the previously deleted candidate subarray is selected for deletion.

[0021] In one embodiment, the shape of the antenna array includes: a square, an equilateral triangle, and a regular hexagon.

[0022] In one embodiment, the antenna array is square, and the array elements on the antenna array are rotated by 90°, 180° and 270° to obtain three different rotated array element sequences.

[0023] A subarray partitioning device based on rotational symmetry, the device comprising:

[0024] The antenna array surface and subarray type acquisition module is used to acquire the antenna array surface and the subarray type of the fully polarized array antenna to be subarrayed.

[0025] A dictionary matrix construction module is used to construct a dictionary matrix according to the subarray type and antenna array, wherein the dictionary matrix is ​​a set of all candidate subarrays, and each row of the dictionary matrix represents a candidate subarray;

[0026] The antenna array rotation module is used to label each array element on the antenna array according to the arrangement order to obtain the initial array element order, rotate each array element on the antenna array multiple times according to symmetry, and record the array element order after each rotation accordingly.

[0027] The subarray partitioning matrix generation module is used to randomly select a row of candidate subarrays in the dictionary matrix, select other rows of candidate subarrays in the dictionary matrix according to the relationship between the initial array element order and the array element order after multiple rotations, and add the selected rows of candidate subarrays to the subarray partitioning matrix.

[0028] The deletion operation module is used to delete the selected multi-row candidate subarrays from the dictionary matrix, and find the multi-column array elements involved in these candidate subarrays in the dictionary matrix, delete the rows corresponding to the candidate subarrays containing these array elements, and form a new dictionary matrix.

[0029] The subarray partitioning module is used to continue deleting new dictionary matrices until the dictionary matrices are empty, thus achieving precise coverage partitioning of the antenna array.

[0030] A computer device includes a memory and a processor, the memory storing a computer program, and the processor executing the computer program performing the following steps:

[0031] Obtain the antenna array surface of the fully polarized array antenna to be subdivided and the type of subarray to be divided;

[0032] A dictionary matrix is ​​constructed based on the subarray type and antenna array, wherein the dictionary matrix is ​​a set of all candidate subarrays, and each row of the dictionary matrix represents a candidate subarray;

[0033] The array elements on the antenna array are numbered according to their arrangement order to obtain the initial array element order. The array elements on the antenna array are rotated multiple times according to symmetry, and the array element order after each rotation is recorded accordingly.

[0034] Randomly select a candidate subarray from the dictionary matrix. Based on the relationship between the initial array element order and the array element order after multiple rotations, select another multiple candidate subarrays from the dictionary matrix and add the selected multiple candidate subarrays to the subarray partitioning matrix.

[0035] The selected candidate subarrays are removed from the dictionary matrix, and the multi-column array elements involved in these candidate subarrays are found in the dictionary matrix. The rows corresponding to the candidate subarrays containing these array elements are deleted to form a new dictionary matrix.

[0036] Continue deleting entries into the new dictionary matrix until the dictionary matrix is ​​empty, thus achieving precise coverage division of the antenna array.

[0037] A computer-readable storage medium having a computer program stored thereon, the computer program performing the following steps when executed by a processor:

[0038] Obtain the antenna array surface of the fully polarized array antenna to be subdivided and the type of subarray to be divided;

[0039] A dictionary matrix is ​​constructed based on the subarray type and antenna array, wherein the dictionary matrix is ​​a set of all candidate subarrays, and each row of the dictionary matrix represents a candidate subarray;

[0040] The array elements on the antenna array are numbered according to their arrangement order to obtain the initial array element order. The array elements on the antenna array are rotated multiple times according to symmetry, and the array element order after each rotation is recorded accordingly.

[0041] Randomly select a candidate subarray from the dictionary matrix. Based on the relationship between the initial array element order and the array element order after multiple rotations, select another multiple candidate subarrays from the dictionary matrix and add the selected multiple candidate subarrays to the subarray partitioning matrix.

[0042] The selected candidate subarrays are removed from the dictionary matrix, and the multi-column array elements involved in these candidate subarrays are found in the dictionary matrix. The rows corresponding to the candidate subarrays containing these array elements are deleted to form a new dictionary matrix.

[0043] Continue deleting entries into the new dictionary matrix until the dictionary matrix is ​​empty, thus achieving precise coverage division of the antenna array.

[0044] The aforementioned subarray partitioning method based on rotational symmetry constructs a dictionary matrix according to the subarray type and antenna array. It then labels the array elements on the antenna array according to their arrangement order to obtain the initial element order. The array elements on the antenna array are rotated multiple times according to symmetry, and the element order after each rotation is recorded. Next, a candidate subarray row is randomly selected from the dictionary matrix. Based on the relationship between the initial element order and the element order after multiple rotations, several other candidate subarray rows are selected from the dictionary matrix and added to the subarray partitioning matrix. Simultaneously, these selected candidate subarray rows are deleted from the dictionary matrix. Then, the dictionary matrix is ​​searched for columns of elements involved in these candidate subarray rows, and the rows corresponding to the candidate subarrays containing these elements are deleted, forming a new dictionary matrix. This deletion operation continues until the dictionary matrix is ​​empty and the subarray partitioning matrix satisfies the exact coverage principle, thus achieving the subarray partitioning of the antenna array. This method utilizes rotational symmetry to improve the dictionary matrix dimensionality reduction in the X algorithm, quickly solving for all exact coverage solutions that satisfy this characteristic. The defined "rotational symmetry" ensures that subarray partitioning schemes that satisfy this property have consistent sidelobe performance across multiple scanning angles. Attached Figure Description

[0045] Figure 1 This is a flowchart illustrating a subarray partitioning method based on rotational symmetry in one embodiment;

[0046] Figure 2 This is a schematic diagram illustrating the rotational symmetry of subarray partitioning in one embodiment;

[0047] Figure 3 This is a schematic diagram of the optimal rotational symmetry partitioning scheme solved by the present invention on a 12×12 array in one embodiment;

[0048] Figure 4 The results of the second and third simulation experiments were used to verify the experiment, and the diagrams are shown below:

[0049] Figure 4 (a) is the azimuth section of the main polarization (H polarization) and cross polarization (V polarization) pattern when the array emits H polarization at the beam direction (90°, 20°);

[0050] Figure 4 (b) is the azimuth section of the main polarization (V polarization) and cross polarization (H polarization) pattern when the array emits V polarization at the beam direction (90°, 20°);

[0051] Figure 4 (c) is the azimuth section of the main polarization (H polarization) and cross polarization (V polarization) pattern when the array receives H polarization at the beam pointing (90°, 20°);

[0052] Figure 4 (d) is the azimuth section of the main polarization (V polarization) and cross polarization (H polarization) pattern when the array receives V polarization at the beam pointing (90°, 20°);

[0053] Figure 5 This is a structural block diagram of a subarray partitioning device based on rotational symmetry in one embodiment;

[0054] Figure 6 This is an internal structural diagram of a computer device in one embodiment. Detailed Implementation

[0055] To make the objectives, technical solutions, and advantages of this application clearer, the following detailed description is provided in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative and not intended to limit the scope of this application.

[0056] like Figure 1 As shown, a subarray partitioning method based on rotational symmetry is provided, including the following steps:

[0057] Step S100: Obtain the antenna array surface of the fully polarized array antenna to be subdivided and the type of subarray to be subdivided;

[0058] Step S110: Construct a dictionary matrix according to the subarray type and antenna array. The dictionary matrix is ​​a set of all candidate subarrays, where each row of the dictionary matrix represents a candidate subarray.

[0059] Step S120: Label each element on the antenna array according to the arrangement order to obtain the initial element order; rotate each element on the antenna array multiple times according to symmetry; and record the element order after each rotation accordingly.

[0060] Step S130: Randomly select a candidate subarray in the dictionary matrix, select other candidate subarrays in the dictionary matrix according to the relationship between the initial array element order and the array element order after multiple rotations, and add the selected candidate subarrays to the subarray partitioning matrix.

[0061] Step S140: Remove the selected candidate subarrays from the dictionary matrix, find the multi-column array elements involved in these candidate subarrays in the dictionary matrix, delete the rows corresponding to the candidate subarrays containing these array elements, and form a new dictionary matrix.

[0062] Step S150: Continue deleting new dictionary matrices until the dictionary matrix is ​​empty and the subarray partitioning matrix satisfies the precise coverage principle, thus realizing the subarray partitioning of the antenna array.

[0063] In this embodiment, a geometric property called "rotational symmetry" is defined on the existing n×n array antenna, i.e., the square antenna array surface. This property means that the subarray partitioning scheme remains geometrically unchanged after the antenna array is rotated by multiple angles, resulting in consistent sidelobe performance across multiple scanning angles. This geometric property is used to improve the X algorithm, allowing for faster dictionary matrix dimensionality reduction to solve for accurate coverage schemes that satisfy this property. Furthermore, the number of schemes satisfying "rotational symmetry" is very small relative to the total number of schemes, enabling the efficient finding of partitioning schemes with good sidelobe performance across multiple scanning angles.

[0064] It should be noted that the shape of the antenna array that can satisfy the "rotational symmetry" scheme is not limited to a square. In this article, only a square is used as an example to illustrate this method.

[0065] In this embodiment, the shape of the antenna array can be an equilateral triangle, a regular hexagon, or a near-circular shape, etc. Furthermore, this method can also use a combination of several square arrays to solve the subarray division of a rectangular array.

[0066] In step S100, the method of this application is for a square antenna array. The subarray types to be divided include "T" type, "L" type, etc.

[0067] In step S110, assume an array of size n×n with N elements (N=n 2 An antenna array has K candidate subarrays. Accurate coverage of the entire array requires M subarrays, and the value of M can be calculated by the number of elements in the candidate subarrays. Therefore, a K×N dictionary matrix L can be defined. For the i-th row of L, "1" indicates that the element is selected by the i-th candidate subarray, and "0" indicates that it is not selected. In other words, each row of the dictionary matrix L represents a candidate subarray in sequence. Each column of the dictionary matrix L represents the position of an element on the antenna array.

[0068] Furthermore, the dictionary matrix L represents the candidate subarrays arranged in different positions and configurations on the antenna array as a sequence. Figure 2 For example, in Figure 2 The top left corner is used to represent the antenna array before rotation. You can see that the numbers on each array element are arranged in order. At this time, "1110010000000000" can be used to represent the downward-facing "T"-shaped subarray composed of four array elements in the top left corner of the figure.

[0069] The problem of subarray partitioning that satisfies exact coverage can be represented as finding a binary subarray selection vector x = [x1,...,x...]. K ] T The selection vector satisfies the following formula:

[0070]

[0071] Formula (1) can also be understood as selecting M rows from the dictionary matrix L to form an M×N submatrix partition matrix L1. Each column of L1 has only one element that is 1, and the rest are 0.

[0072] The traditional X algorithm first randomly selects a candidate subarray in the dictionary matrix L, and then deletes the candidate subarray in the column containing "1" that also contains "1" in other rows, forming a new dictionary matrix L. This process is repeated until the dictionary matrix L is empty. However, this method has the disadvantages of slow convergence and a huge number of subarray partitioning schemes, requiring the selection of a better-performing scheme from among them.

[0073] This method, based on the geometric property of "rotational symmetry," can also be understood as follows: after reordering each column of L1 according to the rotation angle, the newly obtained subarray partitioning matrix L2 can still be obtained by swapping each row of L1. In other words, the subarray partitioning scheme with "rotational symmetry" still yields the same subarray partitioning scheme after being rotated according to the rotation angle.

[0074] Specifically Figure 2 Let's take an example to illustrate. Figure 2 This demonstrates the rotationally symmetric partitioning of a 4x4 array antenna with 4-element "T"-shaped subarrays. The subarray partitioning matrix L1 before rotation can be represented as:

[0075]

[0076] At this point, the order of each column in L1 can be represented by I1 = [1,2,3,4,5,6,7,8,9,10,11,12,13,14,15,16].

[0077] go through Figure 1 After a 270° rotation, each column of L1 can be reordered according to I2 = [4,8,12,16,3,7,11,15,2,6,10,14,1,5,9,13] to obtain a new submatrix partition matrix L2:

[0078]

[0079] Meanwhile, L2 can be obtained by reordering each row of the original submatrix L1 in the order of [2,3,4,1].

[0080] Based on the above understanding of rotational symmetry, this method improves upon the X algorithm. Assume I1 is the order in which each column of the submatrix L1 is partitioned before rotation, and I2, I3, and I4 are the orders in which each column of the submatrix L1 is partitioned after rotations of 90°, 180°, and 270°, respectively.

[0081] During the dimensionality reduction of the dictionary matrix L, whenever a row of L is selected into the submatrix L1, each column of that row is swapped in the order of I2, I3, and I4, and the resulting three rows are also selected into the submatrix L1.

[0082] In step S120, when rotating each element on the antenna array multiple times according to symmetry and recording the element order after each rotation: each time a rotation is performed, the number indicating the current element order rotates along with it, and the number is recorded according to the order after the rotation to obtain the rotated element order. As mentioned above, the initial element order before rotation is: I1 = [1,2,3,4,5,6,7,8,9,10,11,12,13,14,15,16], and after rotating 270°, the obtained element order is: I2 = [4,8,12,16,3,7,11,15,2,6,10,14,1,5,9,13].

[0083] In step S130, a candidate subarray is randomly selected from the dictionary matrix L. Based on the relationship between the initial element order and the element order after multiple rotations, several other candidate subarrays are selected from the dictionary matrix L. This includes: for the randomly selected candidate subarray corresponding to the initial element order, finding the corresponding number representing "1" in the initial element order. In the element order obtained after each rotation, the corresponding number position is represented as "1", and other positions are represented as "0". This yields several other candidate subarrays, which are then selected from the dictionary matrix L.

[0084] Specifically, in the dictionary matrix L, a candidate subarray is randomly selected. Through rotational correspondence, three other candidate subarrays are also selected and added to the subarray partitioning matrix. Simultaneously, the selected candidate subarrays are deleted from the dictionary matrix. To avoid subarray overlap and achieve precise coverage of the entire array, multiple columns of array elements related to these candidate subarrays are found in the dictionary matrix. Rows corresponding to candidate subarrays containing these elements are deleted, forming a new dictionary matrix. This deletion operation is undoubtedly much faster in convergence than the traditional X algorithm.

[0085] When deleting from a new dictionary matrix, adjacent candidate subarrays are selected from those previously deleted. At this step, multiple candidate subarrays can be selected based on their positions or arrangement, thus generating multiple subarray partitioning matrices.

[0086] The specific algorithm of this method is as follows: the input to the algorithm is a dictionary matrix L and the subarray type (e.g., 4-element T-type, 4-element L-type, 8-element L-type, etc.), and the element order I1, I2, I3, and I4 before and after rotation. The algorithm outputs the subarray partitioning matrix L1. This is achieved through ∑... c L(i,c)=min{∑ j Find the c-th column of the dictionary matrix L(i,j). For all rows satisfying L(i,c) = 1, find the corresponding three other rows through the relationships I1, I2, I3, and I4. Remove these four rows from the dictionary matrix L and add them to the submatrix L1. Simultaneously, remove the columns corresponding to the elements of these four rows from the dictionary matrix L. Use the L after the above row and column processing as the new input to the algorithm, and continue recursively until an exact cover is achieved.

[0087] The subarray partitioning matrices found by this method all satisfy the geometric property of "rotational symmetry". This method can achieve rapid solution of subarray partitioning only on the basis that subarray partitioning matrices that satisfy the geometric property of "rotational symmetry" have good sidelobe performance. Therefore, in the following text, it is proved that subarray partitioning matrices that satisfy "rotational symmetry" have good sidelobe performance.

[0088] When evaluating the sidelobe performance of the subarray partitioning scheme, both transmit and receive operating modes of the array are considered. The polarization pattern of the array is calculated as follows:

[0089]

[0090] In formula (4), w H and w V These are the weight vectors for the H-polarization ports and V-polarization ports of the subarray, respectively. HH (θ,φ) is the pattern vector of the H-polarization subarray corresponding to the H-polarization port, g HV (θ,φ) is the pattern vector of the H-polarized subarray corresponding to the V-polarized port.

[0091] In the transmission mode, taking the transmission of H-polarized electromagnetic waves as an example, w H and w V satisfy:

[0092]

[0093] In formula (5), p i(i = 1, 2, ..., M) represents the H-polarization electric field phase of the i-th subarray at the beam pointing direction. H This allows the H-polarized electric fields of each subarray to be superimposed in phase at the beam pointing direction, thereby maximizing radiation.

[0094] In receive mode, since the data has already been collected, w H and w V Both the amplitude and phase can be adjusted. Taking the reception of H-polarized electromagnetic waves as an example, consider using a convex optimization method to form an H-polarized beam with a beam direction of (θ0, φ0), a main lobe polarization isolation of less than -30dB, and as low a side lobe as possible:

[0095]

[0096] In formula (6), Ω m and Ω s These represent the main lobe and side lobe regions, respectively. The constraint is max{|f H (Θ,Φ)|}≤|f H (θ0,φ0)|=G is to maximize the amplitude of the radiation pattern pointing at (θ0,φ0). Δθ and Δφ are used to select the angles around (θ0,φ0) for this constraint, and can be set to 1°.

[0097] Meanwhile, in order to verify that the subarray partitioning method based on rotational symmetry provided in this paper (hereinafter referred to as this method) can quickly solve for partitioning schemes that satisfy rotational symmetry, the first simulation experiment was conducted.

[0098] Experimental objective: To verify that the proposed method can quickly solve for accurate coverage schemes that satisfy rotational symmetry for arrays of different sizes.

[0099] Experimental conditions: Consider using a 4-element T-shaped subarray to divide the array into sizes of 8×8, 12×12, and 16×16, and evaluate the computation time of this method to solve for an exact covering scheme that satisfies rotational symmetry.

[0100] Experimental results: For arrays of different sizes, the computation time and the number of rotationally symmetric subarray partitioning schemes obtained by this method are as follows:

[0101] Array size Number of schemes that satisfy rotational symmetry computation time Total number of schemes 8×8 6 0.03s 84 12×12 36 0.06s 78696 16×16 468 0.48s 1668091536 24×24 787896 812s <![CDATA[Greater than 3.8×10 19 >

[0102] As can be seen, this method can quickly solve for an exact coverage scheme that satisfies rotational symmetry. The number of schemes that satisfy rotational symmetry is much smaller than the total number of schemes, avoiding the need to evaluate all schemes and facilitating subsequent evaluation of sidelobe performance.

[0103] To verify that this method can guarantee good scanning performance of the partitioning scheme at multiple angles, a second simulation experiment was conducted, as follows: Figure 4 As shown in (a) to (b).

[0104] Experimental Objective: To verify that the proposed method can quickly solve for partitioning schemes that maintain good scanning performance at multiple angles. A 12×12 dual-polarized microstrip patch array antenna is partitioned using a 4-element T-shaped subarray. The rotationally symmetric partitioning schemes obtained by the proposed method are optimized through a traversal process to obtain partitioning scheme A, as shown below. Figure 3 As shown, partition scheme B is found by traversing and optimizing all possible partitioning schemes; the scanning performance of scheme A and scheme B in emission mode is compared.

[0105] Experimental conditions: Considering the mutual coupling and boundary effects in the actual array, the HFSS simulation software was selected to calculate the active radiation pattern data of all elements of the 12×12 dual-polarized microstrip patch array antenna. According to the subarray partitioning scheme, the active radiation patterns of corresponding elements in each subarray were summed to obtain the subarray radiation pattern, and the weights w were calculated. H and w V This leads to the array pattern in the transmission mode. During the optimization process, the scheme with the smallest average sidelobe level under the transmission H polarization at the eight scanning angles (90°, 20°), (90°, -20°), (70°, 0°), (110°, 0°), (75°, 15°), (75°, -15°), (105°, 15°), and (105°, -15°) is considered the optimal partitioning scheme for scanning performance.

[0106] Figure 4 In figures (a) to (b), the horizontal axis represents the azimuth angle in degrees; the vertical axis represents the relative radiation pattern, obtained by normalizing the maximum amplitude of the principal polarization pattern, in dB. The dark solid line in the figure represents the horizontal polarization pattern of the partition scheme A solved by this invention in the emission mode, denoted by f. H (θ,φ) represents the vertical polarization pattern of the partitioning scheme A solved by this invention in the emission mode, denoted by f. V (θ,φ) represents the horizontal polarization pattern of partition scheme B obtained through traversal optimization among all schemes in the emission mode. The dotted line represents the vertical polarization pattern of partition scheme B obtained through traversal optimization among all schemes in the emission mode. express. Figure 4 (a) shows the azimuth section of the main polarization (H polarization) and cross polarization (V polarization) patterns when the array emits H polarization at the beam direction (90°, 20°). Figure 4 (b) represents the azimuth section of the main polarization (V polarization) and cross polarization (H polarization) patterns when the array emits V polarization at the beam pointing (90°, 20°).

[0107] Experimental results: This method found the partition scheme A with the best scanning performance in just 16.7 seconds. In contrast, finding partition scheme B by traversing all schemes took 988 seconds, further validating the computational advantage of this method. Figure 4 As shown in (a), when the array transmits with horizontal polarization, the sidelobe performance of the partitioning scheme A solved by this invention and the theoretically optimal partitioning scheme B are very close at a beam scanning angle of (90°, 20°), with a difference of less than 0.1dB. At the eight scanning angles (90°, 20°), (90°, -20°), (70°, 0°), (110°, 0°), (75°, 15°), (75°, -15°), (105°, 15°), and (105°, -15°), the average sidelobe value of the theoretically optimal partitioning scheme B is -11.17dB, while the average sidelobe value of the partitioning scheme A solved by this invention is -10.99dB, a difference of less than 0.18dB. Similarly, as... Figure 4 As shown in (b), when the array transmits vertically polarized, the sidelobe performance of the partitioning scheme A solved by this invention and the theoretically optimal partitioning scheme B are still very close at the beam scanning angle of (90°, 20°), with a difference of less than 0.23dB.

[0108] To verify that the fully polarized array antenna subarray partitioning method provided in this invention can quickly solve for a partitioning scheme that maintains good scanning performance at multiple angles, a third simulation experiment was conducted, as follows: Figure 4 As shown in (c) to (d).

[0109] Experimental Objective: To verify that the proposed method for partitioning fully polarized array antenna subarrays can quickly solve for a partitioning scheme that maintains good scanning performance at multiple angles. The scanning performance of partitioning scheme A obtained by this invention and partitioning scheme B obtained by traversing all schemes in Experiment 2 will be compared in receiving mode.

[0110] Experimental conditions: Considering the mutual coupling and boundary effects in the actual array, the active radiation pattern data of all elements of the 12×12 dual-polarized microstrip patch array antenna were calculated using HFSS simulation software. According to the subarray partitioning scheme, the active radiation patterns of corresponding elements in each subarray were summed to obtain the subarray radiation pattern. The convex optimization problem involved in receiving beamforming was solved using MATLAB's CVX toolbox to obtain the weights w that satisfy the constraints. H and w V This allows us to obtain the array pattern in the receiving mode.

[0111] Illustration content: Figure 4In the figures (c) to (d), the horizontal axis represents the azimuth angle in degrees; the vertical axis represents the normalized receiver gain, obtained by normalizing the maximum amplitude of the main polarization pattern, in dB. The dark solid line in the figure represents the horizontal polarization pattern of the partitioning scheme A solved by this invention in the receiver mode, denoted by f. H (θ,φ) represents the vertical polarization pattern of the partitioning scheme A solved by this invention in the receiving mode, denoted by f. V (θ,φ) represents the horizontal polarization pattern of the partition scheme B obtained through traversal optimization among all schemes in the receiving mode. The dotted line represents the vertical polarization pattern of the partition scheme B obtained through traversal optimization among all schemes in the receiving mode. express. Figure 4 (c) represents the azimuth section of the main polarization (H polarization) and cross polarization (V polarization) patterns when the array receives H polarization at the beam pointing (90°, 20°). Figure 4 (d) represents the azimuth section of the main polarization (V polarization) and cross polarization (H polarization) patterns when the array receives V polarization at the beam pointing (90°, 20°).

[0112] Experimental results: such as Figure 4 As shown in (a), when the array receives horizontal polarization, while satisfying the constraint that the main lobe polarization isolation is less than -30dB, the sidelobe performance of the partitioning scheme A solved by this method is very close to that of the theoretically optimal partitioning scheme B at a beam scanning angle of (90°, 20°), with a difference of less than 0.2dB. At the eight scanning angles (90°, 20°), (90°, -20°), (70°, 0°), (110°, 0°), (75°, 15°), (75°, -15°), (105°, 15°), and (105°, -15°), the average sidelobe value of the theoretically optimal partitioning scheme B is -18.48dB, while the average sidelobe value of the partitioning scheme A solved by this method is -18.16dB, with a difference of less than 0.4dB. Similarly, as... Figure 4 As shown in (b), when the array receives vertical polarization, the sidelobe performance of the partition scheme A obtained by this method and the theoretically optimal partition scheme B are still very close at the beam scanning angle of (90°, 20°), with a difference of less than 0.4dB.

[0113] In the aforementioned subarray partitioning method based on rotational symmetry, rotational symmetry is utilized to improve the dimensionality reduction of the dictionary matrix in the X algorithm, enabling rapid solving for all exact coverage solutions that satisfy this property. The defined rotational symmetry ensures that subarray partitioning schemes satisfying this property exhibit consistent sidelobe performance across multiple scanning angles. This method only requires traversing and optimizing subarray partitioning schemes that satisfy rotational symmetry. Since the number of such schemes is relatively small, it can efficiently find partitioning schemes with good sidelobe performance across multiple scanning angles. The partitioning schemes found by this method enable the array antenna to have good sidelobe performance in both transmit and receive modes. Furthermore, it maintains good sidelobe performance even on n×n fully polarized array antennas containing mutual coupling and boundary effects.

[0114] It should be understood that, although Figure 1 The steps in the flowchart are shown sequentially as indicated by the arrows, but these steps are not necessarily executed in the order indicated by the arrows. Unless otherwise specified in this document, there is no strict order in which these steps are executed, and they can be performed in other orders. Figure 1 At least some of the steps in the process may include multiple sub-steps or multiple stages. These sub-steps or stages are not necessarily executed at the same time, but may be executed at different times. The execution order of these sub-steps or stages is not necessarily sequential, but may be executed in turn or alternately with other steps or at least some of the sub-steps or stages of other steps.

[0115] In one embodiment, such as Figure 5 As shown, a subarray partitioning device based on rotational symmetry is provided, including: an antenna array and subarray type acquisition module 200, a dictionary matrix construction module 210, an antenna array rotation module 220, a subarray partitioning matrix generation module 230, a deletion operation module 240, and a subarray partitioning implementation module 250, wherein:

[0116] Antenna array surface and subarray type acquisition module 200 is used to acquire the antenna array surface and subarray type of the fully polarized array antenna to be subarrayed.

[0117] The dictionary matrix construction module 210 is used to construct a dictionary matrix according to the subarray type and the antenna array, wherein the dictionary matrix is ​​a set of all candidate subarrays, and each row of the dictionary matrix represents a candidate subarray.

[0118] The antenna array rotation module 220 is used to label each array element on the antenna array according to the arrangement order to obtain the initial array element order, rotate each array element on the antenna array multiple times according to symmetry, and record the array element order after each rotation accordingly.

[0119] The subarray partitioning matrix generation module 230 is used to randomly select a row of candidate subarrays in the dictionary matrix, select other rows of candidate subarrays in the dictionary matrix according to the relationship between the initial array element order and the array element order after multiple rotations, and add the selected rows of candidate subarrays to the subarray partitioning matrix.

[0120] The deletion operation module 240 is used to delete the selected multi-row candidate subarrays from the dictionary matrix, and find the multi-column array elements involved in these candidate subarrays in the dictionary matrix, delete the rows corresponding to the candidate subarrays containing these array elements, and form a new dictionary matrix.

[0121] The subarray partitioning implementation module 250 is used to continue deleting new dictionary matrices until the dictionary matrices are empty, thereby achieving precise coverage partitioning of the antenna array.

[0122] Specific limitations regarding the subarray partitioning device based on rotational symmetry can be found in the limitations of the rotational symmetry-based subarray partitioning method described above, and will not be repeated here. Each module in the aforementioned rotational symmetry-based subarray partitioning device can be implemented entirely or partially through software, hardware, or a combination thereof. These modules can be embedded in or independent of the processor in a computer device in hardware form, or stored in the memory of a computer device in software form, so that the processor can call and execute the operations corresponding to each module.

[0123] In one embodiment, a computer device is provided, which may be a terminal, and its internal structure diagram may be as follows: Figure 6 As shown, the computer device includes a processor, memory, network interface, display screen, and input devices connected via a system bus. The processor provides computing and control capabilities. The memory includes non-volatile storage media and internal memory. The non-volatile storage media stores the operating system and computer programs. The internal memory provides an environment for the operation of the operating system and computer programs stored in the non-volatile storage media. The network interface is used to communicate with external terminals via a network connection. When executed by the processor, the computer program implements a subarray partitioning method based on rotational symmetry. The display screen can be a liquid crystal display (LCD) or an e-ink display. The input devices can be a touch layer covering the display screen, buttons, a trackball, or a touchpad mounted on the computer device casing, or an external keyboard, touchpad, or mouse.

[0124] Those skilled in the art will understand that Figure 6The structure shown is merely a block diagram of a portion of the structure related to the present application and does not constitute a limitation on the computer device to which the present application is applied. Specific computer devices may include more or fewer components than those shown in the figure, or combine certain components, or have different component arrangements.

[0125] In one embodiment, a computer device is provided, including a memory and a processor, wherein the memory stores a computer program, and the processor executes the computer program to perform the following steps:

[0126] Obtain the antenna array surface of the fully polarized array antenna to be subdivided and the type of subarray to be divided;

[0127] A dictionary matrix is ​​constructed based on the subarray type and antenna array, wherein the dictionary matrix is ​​a set of all candidate subarrays, and each row of the dictionary matrix represents a candidate subarray;

[0128] The array elements on the antenna array are numbered according to their arrangement order to obtain the initial array element order. The array elements on the antenna array are rotated multiple times according to symmetry, and the array element order after each rotation is recorded accordingly.

[0129] Randomly select a candidate subarray from the dictionary matrix. Based on the relationship between the initial array element order and the array element order after multiple rotations, select another multiple candidate subarrays from the dictionary matrix and add the selected multiple candidate subarrays to the subarray partitioning matrix.

[0130] The selected candidate subarrays are removed from the dictionary matrix, and the multi-column array elements involved in these candidate subarrays are found in the dictionary matrix. The rows corresponding to the candidate subarrays containing these array elements are deleted to form a new dictionary matrix.

[0131] Continue deleting entries into the new dictionary matrix until the dictionary matrix is ​​empty, thus achieving precise coverage division of the antenna array.

[0132] In one embodiment, a computer-readable storage medium is provided having a computer program stored thereon, the computer program performing the following steps when executed by a processor:

[0133] Obtain the antenna array surface of the fully polarized array antenna to be subdivided and the type of subarray to be divided;

[0134] A dictionary matrix is ​​constructed based on the subarray type and antenna array, wherein the dictionary matrix is ​​a set of all candidate subarrays, and each row of the dictionary matrix represents a candidate subarray;

[0135] The array elements on the antenna array are numbered according to their arrangement order to obtain the initial array element order. The array elements on the antenna array are rotated multiple times according to symmetry, and the array element order after each rotation is recorded accordingly.

[0136] Randomly select a candidate subarray from the dictionary matrix. Based on the relationship between the initial array element order and the array element order after multiple rotations, select another multiple candidate subarrays from the dictionary matrix and add the selected multiple candidate subarrays to the subarray partitioning matrix.

[0137] The selected candidate subarrays are removed from the dictionary matrix, and the multi-column array elements involved in these candidate subarrays are found in the dictionary matrix. The rows corresponding to the candidate subarrays containing these array elements are deleted to form a new dictionary matrix.

[0138] Continue deleting entries into the new dictionary matrix until the dictionary matrix is ​​empty, thus achieving precise coverage division of the antenna array.

[0139] Those skilled in the art will understand that all or part of the processes in the methods of the above embodiments can be implemented by a computer program instructing related hardware. The computer program can be stored in a non-volatile computer-readable storage medium, and when executed, it can include the processes of the embodiments of the above methods. Any references to memory, storage, databases, or other media used in the embodiments provided in this application can include non-volatile and / or volatile memory. Non-volatile memory can include read-only memory (ROM), programmable ROM (PROM), electrically programmable ROM (EPROM), electrically erasable programmable ROM (EEPROM), or flash memory. Volatile memory can include random access memory (RAM) or external cache memory. By way of illustration and not limitation, RAM is available in various forms, such as static RAM (SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), dual data rate SDRAM (DDRSDRAM), enhanced SDRAM (ESDRAM), synchronous link DRAM (SLDRAM), Rambus direct RAM (RDRAM), direct memory bus dynamic RAM (DRDRAM), and memory bus dynamic RAM (RDRAM), etc.

[0140] The technical features of the above embodiments can be combined in any way. For the sake of brevity, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

[0141] The embodiments described above are merely illustrative of several implementation methods of this application, and while the descriptions are relatively specific and detailed, they should not be construed as limiting the scope of the invention patent. It should be noted that those skilled in the art can make various modifications and improvements without departing from the concept of this application, and these all fall within the protection scope of this application. Therefore, the protection scope of this patent application should be determined by the appended claims.

Claims

1. A subarray partitioning method based on rotational symmetry, characterized in that, The method includes: Obtain the antenna array surface of the fully polarized array antenna to be subdivided and the type of subarray to be divided; A dictionary matrix is ​​constructed based on the subarray type and antenna array, wherein the dictionary matrix is ​​a set of all candidate subarrays, and each row of the dictionary matrix represents a candidate subarray; The array elements on the antenna array are numbered according to their arrangement order to obtain the initial array element order. The array elements on the antenna array are rotated multiple times according to symmetry, and the array element order after each rotation is recorded accordingly. Randomly select a candidate subarray from the dictionary matrix. Based on the relationship between the initial array element order and the array element order after multiple rotations, select another multiple candidate subarrays from the dictionary matrix and add the selected multiple candidate subarrays to the subarray partitioning matrix. The selected candidate subarrays are removed from the dictionary matrix, and the multi-column array elements involved in these candidate subarrays are found in the dictionary matrix. The rows corresponding to the candidate subarrays containing these array elements are deleted to form a new dictionary matrix. Continue deleting entries into the new dictionary matrix until the dictionary matrix is ​​empty, thus achieving precise coverage division of the antenna array.

2. The subarray partitioning method according to claim 1, characterized in that, Each row in the dictionary matrix is ​​arranged according to the position of the array elements, and "1" indicates that the array element belongs to the candidate subarray represented by the current row, and "0" indicates that the array element does not belong to the candidate subarray represented by the current row. Each column in the dictionary matrix represents the position of an array element.

3. The subarray partitioning method according to claim 2, characterized in that, When rotating each element on the antenna array multiple times according to symmetry, and recording the element order after each rotation: Each time a rotation is performed, the number representing the current array element order rotates along with it, and then the numbers are recorded according to the order after the rotation to obtain the rotated array element order.

4. The subarray partitioning method according to claim 3, characterized in that, The step of randomly selecting a candidate subarray from the dictionary matrix and selecting multiple corresponding candidate subarrays from the dictionary matrix based on the relationship between the initial element order and the element order after multiple rotations includes: The randomly selected row of candidate subarrays corresponds to the initial array element order, and the corresponding number representing "1" in the candidate subarray is found in the initial array element order; In the array element order obtained after each rotation, the corresponding number position is represented as "1" and other positions are represented as "0", so that multiple rows of candidate subarrays can be obtained and selected from the dictionary matrix.

5. The subarray partitioning method according to claim 4, characterized in that, When continuing to delete from a new dictionary matrix, the candidate subarray adjacent to the one deleted in the previous step is selected for deletion.

6. The subarray partitioning method according to claim 5, characterized in that, The antenna array shape includes: square, equilateral triangle and regular hexagon.

7. The subarray partitioning method according to claim 6, characterized in that, The antenna array is square. The array elements on the antenna array are rotated by 90°, 180° and 270° to obtain three different rotated array element sequences.

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