Irregular subarray arrangement method, antenna array and related device

Abstract

The invention discloses an irregular sub-array arrangement method, an antenna array and a related device, and belongs to the technical field of antennae, and the method comprises the steps: generating a plurality of candidate sub-arrays according to the type and orientation of the antenna sub-arrays and the boundary constraint of an antenna array region, and forming a candidate sub-array set; establishing a sub-array conflict list according to whether the positions of the candidate sub-arrays are overlapped or not; and according to the candidate sub-array set and the sub-array conflict list, selecting candidate sub-arrays meeting a preset quantity requirement from the candidate sub-array set by adopting an optimization algorithm, and enabling the positions of all the candidate sub-arrays not to conflict and meeting a preset performance index of an antenna array radiation pattern to obtain an optimal irregular sub-array arrangement scheme. According to the method, the continuous layout problem of the irregular antenna array surface and the multi-type antenna sub-arrays is converted into the problem of carrying out combined selection from the pre-generated and limited antenna sub-array set, conflict pruning is realized in combination with the conflict relation, and the universality and the calculation efficiency of the antenna layout design are remarkably improved.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of antennas, in particular to a non-regular subarray arrangement method based on a candidate subarray set, an antenna array and related devices. BACKGROUND

[0002] An antenna is a key device for converting guided current in a receiver or transmitter into electromagnetic waves in free space, and vice versa. It is one of the basic components of a wireless communication system. Due to the limited gain and insufficient directivity of a single antenna element, modern communication equipment generally uses an array antenna, which improves the gain and directivity by the coordinated work of multiple elements. Further, by applying a controllable phase offset to each antenna element in the array through a phase shifter, the pointing direction of the synthesized beam in space can be adjusted on demand, which is the core principle of a phased array antenna.

[0003] A phased array antenna realizes rapid beam scanning by controlling the amplitude and phase of the excitation current in the antenna channel, and is widely used in military and civilian equipment such as aircraft, satellite, and satellite communication. In order to realize the independent control of the amplitude and phase of each element, a set of independent feed channels must be provided for each antenna element, which significantly increases the cost of the phased array system. Non-regular subarray arrangement technology is an effective means to realize low-cost phased arrays. Non-regular subarray arrangement technology refers to the non-regular subarray division of a regularly arranged antenna array, and the antenna elements in the same subarray are fed through a one-to-many power divider. Since all elements in the array participate in radiation, the array based on non-regular subarray arrangement can achieve higher gain compared to traditional sparse arrays. Therefore, non-regular subarray arrangement technology has good application prospects in realizing low-cost, high-gain phased arrays.

[0004] In non-regular subarray arrangement technology, arranging a large array surface with a given subarray type has always been a key and difficult problem, and there are a large number of studies on this problem. The existing research can be divided into three categories: first, evolutionary algorithms, which have high randomness and high complexity in solving when using different types of subarrays for arrangement, and cannot guarantee accurate coverage in some cases. Second, exhaustive algorithms, which can calculate all array arrangement schemes, but as the array size increases, the number of arrangement schemes increases exponentially, making it difficult to apply this algorithm. Third, arrangement methods based on multi-level subarray division, which divide the large array surface into a number of fixed-shaped subarrays. This fixed subarray division reduces the optimization problem dimension and improves the calculation efficiency to a certain extent. However, the freedom of array layout is limited, often leading to insufficient optimization of array pattern and poor sidelobe suppression. In summary, existing arrangement techniques have low solving efficiency, limited optimization freedom, and difficulty in simultaneously considering complex array shape and pattern performance. SUMMARY

[0005] The application aims to overcome the problems in the prior art and provide an irregular subarray arraying method, an antenna array and a related device.

[0006] The application aims to overcome the problems in the prior art and provide an irregular subarray arraying method, an antenna array and a related device. According to the type, orientation and boundary constraint of the antenna array region of a predefined antenna subarray, a plurality of candidate subarrays formed by a three-tuple of the type, orientation and position of the antenna subarray are generated to form a candidate subarray set; According to whether the positions of each candidate subarray in the candidate subarray set overlap, a subarray conflict list is established to store the position conflict relationship of two candidate subarrays; According to the candidate subarray set and the subarray conflict list, an optimization algorithm is used to select candidate subarrays from the candidate subarray set to meet the preset quantity requirement, and the positions of all candidate subarrays are non-conflicting and meet the preset performance index of the antenna array radiation pattern, so as to obtain a final arraying scheme.

[0007] In an example, the antenna subarray includes one or more subarrays each of which is driven by one feed channel and includes M antenna elements, and M is a natural number.

[0008] In an example, the boundary constraint of the antenna array region includes: For the arc-shaped or curved boundary of the irregularly shaped antenna array region, if at least one antenna element in the antenna subarray is located in the antenna array region, the placement position is determined to be legal.

[0009] In an example, the final arraying scheme is obtained by: According to the subarray conflict list, candidate subarrays are iteratively selected from the candidate subarray set to join the selected subarray subset, and in each round of iteration, the current antenna array performance index is optimized to the maximum extent until the candidate subarrays reach the preset quantity or no candidate subarray is available, and an initial arraying scheme is generated. The initial arraying scheme is globally searched and optimized to obtain a final arraying scheme with better performance.

[0010] In an example, the initial arraying scheme is generated by: The candidate subarrays in the candidate subarray set are grouped and iteratively selected by group; in each round of iteration, all candidate subarrays that have not been selected and are non-conflicting with the current selected subset are tried in the current group, and one subarray that can make the sidelobe level of the antenna array pattern lowest is selected to join the current selected subarray subset until the candidate subarrays reach the preset quantity or no candidate subarray is available.

[0011] In an example, a genetic algorithm is used to globally search and optimize the initial arraying scheme, including: encoding the initial arrangement scheme as elite individuals in a first generation population; randomly generating the rest of the individuals according to a preset population size to form an initial population; wherein each individual is encoded by an ordered sequence, each gene in the sequence uniquely corresponds to a candidate subarray in the candidate subarray set, and the gene being activated indicates that the candidate subarray is selected; using the inverse of the maximum sidelobe level value of the antenna array as a fitness function to evaluate the fitness of each individual in the population; performing selection, crossover and mutation operations on the population according to the fitness to generate a new generation population; iteratively performing the evaluation, selection, crossover and mutation operations until a termination condition is met, and decoding the individual with the optimal fitness in the population to obtain the final arrangement scheme.

[0012] In an example, after the crossover and mutation operations, further comprising: decoding and conflict checking the generated new individual to determine candidate subarray duplication or conflict, and if there is duplication or conflict, starting a repair mechanism to replace the duplicated or conflicting candidate subarray with a non-conflicting candidate subarray in the candidate subarray set.

[0013] It should be further noted that the technical features of the above-mentioned arrangement method examples can be combined or replaced to form new technical solutions.

[0014] The application also includes an antenna array arranged using the arrangement method of any one of the above examples or a combination of multiple examples.

[0015] The application also includes a storage medium having computer instructions stored thereon, wherein the computer instructions perform the steps of the above-mentioned irregular subarray arrangement method when executed.

[0016] The application also includes a terminal comprising a memory and a processor, wherein the memory stores computer instructions executable on the processor, and the processor executes the steps of the above-mentioned irregular subarray arrangement method when executing the computer instructions.

[0017] Compared with the prior art, the application has the following advantages: 1. In an example, the continuous layout problem of irregular antenna array surface and multiple types of antenna subarrays is converted into a combination selection problem from a pre-generated, limited set of antenna subarrays, and the conflict pruning is realized by combining the pre-computed conflict relationship, which significantly improves the universality and computational efficiency of antenna layout design.

[0018] Meanwhile, the method is suitable for arrays of any shape, from regular rectangular arrays, circular arrays, elliptical arrays, to irregular polygonal arrays and non-planar arrays, etc. The array arrangement algorithm of the application does not depend on specific array symmetry or regular division, and thus can be universally implemented on different carrier platforms (such as fuselage curved array, phased array radar antenna cover array, etc.), greatly expanding the application range of irregular subarray arrangement technology and having strong universality.

[0019] 2. In an example, the boundary constraint rule of the antenna array region of the application breaks through the limitation of the traditional method that the antenna subarray is completely located in a regular region, and significantly improves the adaptability of the array arrangement method to different carrier platforms and complex antenna array shapes.

[0020] 3. In an example, unlike the dimension reduction method of multi-level subarray division, the application retains all degrees of freedom of subarray layout in the design, and specifically realizes the combination and placement of antennas at any position on the array surface by 1 driving M antennas, without preset grouping or template restrictions, ensuring that no potential excellent solution and optimization result is missed in the optimization process.

[0021] Meanwhile, the use of multiple subarrays for simultaneous arrangement is realized. Specifically, the array arrangement is mixedly arranged using 1-to-1 and 1-to-multiple units, a part of the feed channels drive a single antenna unit to accurately control the radiation on the key position of the array, and the other part of the feed channels drive multiple antenna units to improve the gain and reduce the cost. The mixed array arrangement reduces the number of feed channels while taking into account the adjustment ability of the radiation pattern, realizes the improvement of the comprehensive performance of the array, and embodies the superiority of the collaborative design of 1-to-1 and 1-to-multiple subarrays.

[0022] 4. In an example, the pre-arrangement is combined with the subarray conflict list, which can quickly converge to a high-quality solution in the initial stage, significantly simplifying the large-scale combinatorial optimization problem, and then using the genetic algorithm for fine search, while ensuring that the electrical performance (such as low sidelobe) of the antenna array approaches the global optimum, greatly shortening the optimization time and realizing the balance between design efficiency and antenna performance. For an actual size array (hundreds of subarray candidate sets), the method of the application can complete the optimization in a short time.

[0023] 5. In an example, the decoding repair mechanism is used to maintain the physical feasibility (no overlap) of the antenna arrangement scheme, ensure that the evolutionary search is always efficiently performed in the legal solution space, effectively avoid the waste of search resources caused by illegal individuals, and significantly improve the search efficiency and convergence stability of the genetic algorithm for high-performance antenna arrangement schemes. BRIEF DESCRIPTION OF DRAWINGS

[0024] The specific embodiments of the present application will be further described in conjunction with the drawings, which are used to provide further understanding of the present application, form a part of the present application, and in which the same reference numerals are used to represent the same or similar parts throughout the drawings. The schematic embodiments of the present application and the descriptions thereof are used to explain the present application and do not constitute an improper limitation to the present application.

[0025] Figure 1 Method flow chart provided for an example of the present application; Figure 2 Schematic diagram of a 1 / 4 antenna array provided for an example of the present application; Figure 3 Schematic diagram of 1-drive-1 and 1-drive-2 subarray occupation position grid provided for an example of the present application; Figure 4 Method flow chart provided for a preferred example of the present application; Figure 5 Schematic diagram of optimization arraying result provided for a preferred example of the present application; Figure 6 Pattern diagram when the array is not scanned provided for a preferred example of the present application; Figure 7 Pattern diagram when the array is scanned provided for a preferred example of the present application. DETAILED DESCRIPTION

[0026] The technical solutions of the present application will be described clearly and completely in conjunction with the drawings. Obviously, the described embodiments are part of the embodiments of the present application, rather than all the embodiments. Based on the embodiments in the present application, all other embodiments obtained by those skilled in the art without creative labor fall within the protection scope of the present application.

[0027] In addition, the technical features involved in different embodiments of the present application described below can be combined with each other as long as there is no conflict.

[0028] In an example, as shown in FIG. 1, a non-regular subarray arraying method is suitable for the method, which comprises the following steps: Figure 1 S1: generating a plurality of candidate subarrays composed of a three-tuple of subarray type, orientation and subarray position according to the pre-defined type of antenna subarray, orientation and boundary constraint of the antenna array region, to form a candidate subarray set. S2: selecting a candidate subarray from the candidate subarray set according to the optimization criterion.

[0029] The antenna subarray comprises one or more antenna elements, with different numbers of antenna elements constituting different types of antenna subarrays. The entire antenna array is composed of antenna subarrays, which are arranged at equal horizontal or vertical intervals. Therefore, the method of this invention is applicable to irregularly shaped antenna arrays formed by grid-like arrangement of antenna subarrays. The orientation of the antenna subarray refers to whether it is arranged horizontally or vertically. Boundary constraints on the antenna array area ensure that the antenna elements are not arranged beyond a preset boundary range. Regarding the definition and encoding of candidate subarrays, this example first lists all subarray positions that satisfy the placement rules (type and orientation of the antenna subarray) and are located within the allowed area, assigns them codes, and stores them. The set of candidate subarrays obtained through this process is denoted as {P}. Each element p represents an antenna subarray with a fixed position, type, and orientation. Thus, the continuous array surface is transformed into a finite set of candidate positions {P}, where each element represents a possible placement of a subarray. This transforms the continuous layout optimization problem of irregular antenna array surfaces and multiple types of antenna subarrays into: selecting several subarrays from {P} such that they do not overlap and satisfy the antenna performance optimization objective.

[0030] S2: Based on whether the positions of each candidate subarray in the candidate subarray set overlap, establish a subarray conflict list to store the positional conflict relationships of each candidate subarray.

[0031] Specifically, a conflict index structure is constructed to pre-record the conflict relationships between any two subarrays. No position can be repeatedly covered by two different subarrays; if two candidate subarrays have the same coordinates at a certain position, they are considered to be in conflict. A conflict list is created, with the subarray number as the index and all other subarray numbers that conflict with it as list elements. By using a lookup table, it is possible to quickly determine whether a newly added subarray conflicts with the currently selected set when selecting subarrays, thereby achieving conflict pruning and significantly reducing the generation of illegal solutions.

[0032] S3: Based on the candidate subarray set and the subarray conflict list, an optimization algorithm is used to select candidate subarrays that meet the preset quantity requirements from the candidate subarray set, and ensure that the positions of all candidate subarrays do not conflict and meet the preset performance indicators of the antenna array radiation pattern, so as to obtain the optimal subset and thus obtain the final array scheme.

[0033] According to the candidate subarray set and the subarray conflict list, a high degree of freedom physical layout problem is defined and solved as a combinatorial optimization problem of selecting the optimal subset from the discrete candidate set. Specifically, this step automatically searches and determines the optimal candidate subarray subset by calling one or more optimization algorithms. The optimal subset must meet three conditions: first, the number and type ratio of the subarrays contained in the subset meet the preset requirements (such as channel number constraints); second, based on the conflict list judgment, all subarrays in the subset do not overlap with each other in physical position; third, the key performance indicators (such as the maximum side lobe level SLL) of the antenna array formed by the subset meet the preset optimal target. Finally, the subarray type and location information corresponding to the optimal subset directly constitutes the required irregular subarray layout scheme. It should be noted that the optimization algorithm here can be a variety of metaheuristic algorithms such as greedy algorithm, genetic algorithm, simulated annealing, or their hybrid strategies.

[0034] In an example, the antenna subarray includes one or more subarrays driven by one feed channel and M antenna elements, where M is a natural number. The antenna subarray in this example includes two forms of 1-drive-1 subarray and 1-drive-2 subarray, where 1-drive-1 subarray refers to one feed channel driving one antenna element, and 1-drive-2 subarray refers to one feed channel driving two antenna elements. Embodiments of the present application partially use these two subarrays to layout the array antenna.

[0035] Unlike dimension reduction methods such as multi-level subarray division, this example retains all degrees of freedom of subarray layout in the design. 1-drive-1 and 1-drive-2 subarrays can be placed in any position on the array surface without preset grouping or template restrictions, ensuring that potential excellent schemes and optimization results are not missed during the optimization process. At the same time, the mixed layout uses 1-drive-1 and 1-drive-2 subarrays, which accurately controls the radiation at key positions of the array by allowing a portion of the feed channels to drive a single antenna element, and improves the gain and reduces the cost by allowing another portion of the feed channels to drive multiple antenna elements. Mixed layout reduces the number of feed channels while taking into account the ability to adjust the radiation pattern, achieving an improvement in the comprehensive performance of the array and reflecting the superiority of the collaborative design of 1-drive-1 and 1-drive-2 subarrays.

[0036] In an example, the boundary constraints of the antenna array region include: For the arc-shaped or curved boundary of the irregularly shaped antenna array region, if at least one antenna element in the antenna subarray is located within the antenna array region, the placement position is determined to be legal.

[0037] Specifically, the antenna array is in the form of 1 / 4 rotational symmetry, and the outline is approximately polygonal or circular. Figure 2As shown, the 1 / 4 antenna array is a 90° sector intersecting with a rectangle, and multiple sub-arrays are arranged in the intersection area. The array is rotated 90° around the center three times for splicing. The sub-arrays are allowed to partially exceed the circular arc boundary of the sector, but cannot exceed the two radial straight boundaries. At this time, the placement rules of the sub-arrays include: (1) Sub-array shape and orientation (direction): As shown in Figure 3 , each 1-drive-1 sub-array is a single grid; and the 1-drive-2 sub-array is composed of two adjacent grids, and has a shape of a 1×2 rectangle. The sub-array can have two orientations: horizontally placed or vertically placed.

[0038] (2) Occupied grid (coordinate grid): The 1-drive-1 sub-array occupies the grid (i, j); if the 1-drive-2 sub-array is horizontally placed, it will occupy two grids with coordinates (i, j) and (i+1, j); and if it is vertically placed, it will occupy two grids with coordinates (i, j) and (i, j+1). The (i, j) can be regarded as the reference position of the sub-array.

[0039] (3) Non-overlapping: If the positions of two candidate sub-arrays have overlapping grids, they cannot exist in the array layout at the same time.

[0040] (4) Boundary condition: The sub-array cannot exceed the boundary range of the sector, and specifically, it can partially extend beyond the arc outer boundary, and needs to consider the radial straight boundary and the circular arc boundary respectively: (5) Straight boundary: The sub-array cannot cross the two straight angle boundaries. This can be reflected by coordinate constraints: if any grid coordinate (i, j) of a unit does not satisfy i>0, j>0, the placement of the sub-array is illegal. For the sub-array with the reference grid on the boundary, since the other grid will extend towards the inside (horizontally placed along the x-axis to the right, and vertically placed along the y-axis upwards), it will not exceed the boundary, so the reference position in the straight boundary can ensure that the sub-array does not cross the straight boundary.

[0041] (6) Circular arc boundary: The sub-array is allowed to have a part exceeding the circular arc boundary, as long as at least one grid of the unit is still in the sector area, it is considered that the sub-array can be placed.

[0042] The candidate sub-array set obtained through the above process is denoted as {P}. Each element p in the set is a fixed type, orientation and position of the antenna sub-array. Thus, the continuous sector array is converted into a finite candidate position set {P}, where each element represents a sub-array. At this time, for the problem of realizing the 1 / 4 irregular phased array antenna layout with low sidelobe level under the given 144 independent feeding channel constraints and the condition of covering 256 antenna unit grids, it can be described as: selecting exactly 112 1-drive-2 sub-arrays and 32 1-drive-1 sub-arrays from {P} so that they do not overlap with each other and meet the performance optimization target (minimum SLL).

[0043] In one example, the final array configuration is obtained, including: Based on the subarray conflict list, candidate subarrays are iteratively selected from the candidate subarray set and added to the selected subarray subset. In each iteration, the performance indicators of the current antenna array are optimized to the greatest extent until the number of candidate subarrays reaches the preset number or there are no candidate subarrays to choose from, and an initial array layout scheme is generated. A global search optimization is performed on the initial array scheme to obtain a final array scheme with better performance.

[0044] In this example, during the generation of the initial array layout, subarrays are selected one by one and placed in the array. Each time, the optimal subarray position is chosen and added to the array until the specified number of subarrays is filled. Here, "optimal" refers to the array with the lowest sidelobes after selecting this subarray from among all available options. To further approximate the global optimum, a genetic algorithm is introduced for global search optimization. The initial array layout is encoded as an initial elite individual, and several other individuals are randomly generated for genetic optimization.

[0045] In one example, generating an initial array scheme includes: The candidate subarrays in the candidate subarray set are grouped and iteratively selected by group. In each iteration, all candidate subarrays that have not yet been selected and do not conflict with the currently selected subset are tried in the current group, and the subarray that makes the antenna array pattern sidelobe level the lowest is added to the currently selected subset, until the number of candidate subarrays reaches the preset number or there are no candidate subarrays to choose from.

[0046] Specifically, the following is an example of generating the initial array configuration: (1) First, number each optional subarray, with the numbering rule being 1 for each subarray first, and the cell coordinates (i) 2 +j 2 ) 1 / 2 The smaller ones, which are closer to the center, are placed first. If the distances are equal, the smaller ones are placed first. If the distances are equal, the horizontal subarrays with 1 drive and 2 subarrays are placed first.

[0047] (2) After numbering, the subarrays are divided into groups of 30 numbers each, from smallest to largest.

[0048] (3) Start arranging from the first group of subarrays. Try to place all the subarrays in the first group into the array in numerical order. When placing each subarray, check whether they overlap. If they do, discard the subarray. If not, calculate the maximum sidelobe level after the arrangement.

[0049] (4) Fix the subarray that produces the minimum SLL in this group on the array, and then continue to select subarrays in the first group and judge and calculate them according to the method in step 3).

[0050] (5) If all subarrays in the first group are discarded, then jump to the second group and perform the same operation in a loop.

[0051] (6) Until the 112 1-drive-2 subarrays and the 32 1-drive-1 subarrays are arranged, output the final arrangement scheme and the arrangement order of each subarray.

[0052] Further, the calculation principle of the array pattern is as follows: First, the electromagnetic simulation software is used to simulate the 1-drive-2 and 1-drive-1 antenna subarray structures respectively, and the far-field pattern results of the two subarrays are obtained. The synthesis array factor of each unit (antenna subarray structure) is calculated independently and multiplied by the subarray pattern, and the calculation formula is as follows: wherein, is the total radiation pattern function of the antenna array in the far-field space; is the elevation angle; is the azimuth angle; N is the number of each subarray; is the current amplitude of the excited unit; represents the first n subarray in the direction ; E is the subarray unit pattern; k is the wave number; d is the unit spacing; is the phase difference between adjacent subarrays. The results of the two subarrays are added to obtain the pattern result of the entire array.

[0053] In an example, a genetic algorithm is used to globally search and optimize the initial arrangement scheme, including: (1) The initial arrangement scheme is coded into elite individuals in the first generation population.

[0054] (2) The remaining individuals are randomly generated according to the preset population size to form the initial population. Each individual is coded by an ordered sequence, and each gene in the sequence uniquely corresponds to a candidate subarray in the candidate subarray set. The gene is activated to indicate that the candidate subarray is selected. Specifically, the chromosome of each individual has 144 genes, which correspond to the numbers of the 112 1-drive-2 subarrays and the 32 1-drive-1 subarrays. The subarray corresponding to the number in the gene is selected and placed in the array.

[0055] (3) The reciprocal of the maximum sidelobe level value of the antenna array is used as the fitness function to evaluate the fitness of each individual in the population.

[0056] Specifically, the off-axis angle is 54°, the rotation angle is between 40° and 140°, and a value is taken every 10°. The maximum sidelobe of the array at these scan angles is recorded as SLL, and -SLL is used as the fitness function.

[0057] (4) Perform selection, crossover and mutation operations on the population according to fitness to generate a new generation of population.

[0058] Wherein, the crossover operation generates new offspring to explore new layout combinations, and each gene priority value of the offspring is inherited from the elite parent with a probability P, and the rest is taken from the other parent. The mutation operator randomly changes the individual to provide population diversity and prevent convergence to a local extremum. Once the genes of 20% individuals are mutated to obtain new individuals, and whether there is a conflict is checked, and the legal individual is repaired.

[0059] (5) Iteratively perform the evaluation, selection, crossover and mutation operations until the termination condition is met, such as the iteration reaches the preset number of generations, and the layout scheme obtained by decoding the individual with the optimal fitness in the population of each generation is taken as the final layout scheme.

[0060] In an example, after the crossover and mutation operations, the following are also included: The new individuals generated are decoded and conflict checked to determine whether the candidate subarray is repeated or conflicted, and if repeated or conflicted, a repair mechanism is started to automatically repair (remove the conflicting subarray and replace it with the nearest non-conflicting unit selected) to ensure that all individuals are legal and feasible solutions before entering the next round of iteration.

[0061] The above examples are combined to obtain a preferred example of the present application, as shown in Figure 4 The method includes the following steps: S10: According to the pre-defined type of antenna subarray, orientation and boundary constraint of the antenna array region, a plurality of candidate subarrays composed of a three-tuple of antenna subarray type, orientation and antenna subarray position are generated to form a candidate subarray set; S20: According to whether the positions of each candidate subarray in the candidate subarray set overlap, a subarray conflict list is established to store the position conflict relationship of two candidate subarrays; S30: Group the candidate subarrays in the candidate subarray set, and select iteratively by group; in each iteration, all candidate subarrays that have not been selected and do not conflict with the current selected subset are tried in the current group, and the one that can make the antenna array pattern sidelobe level lowest is selected to join the current selected subarray subset, until the candidate subarray reaches the preset number or there is no candidate subarray to be selected, and an initial layout scheme is output. S40: encode the initial array arrangement scheme into elite individuals in the first generation population; randomly generate the rest of the individuals according to a preset population size to form an initial population; take the reciprocal of the maximum sidelobe level of the antenna array as the fitness function to evaluate the fitness of each individual in the population; perform selection, crossover and mutation operations on the population according to the fitness to generate a new generation of population; decode the new individuals and perform conflict checking to determine whether the candidate subarrays are repeated or conflicted, and if so, replace the repeated or conflicted candidate subarrays with non-conflicted candidate subarrays in the candidate subarray set; iteratively perform the evaluation, selection, crossover and mutation operations until a termination condition is met, and decode the individual with the optimal fitness in the population to obtain the final array arrangement scheme as shown in Figure 5 .

[0062] The simulation results of the optimized final array arrangement scheme are shown in Figures 6-7 . Figure 6 , where (a) is a profile graph when the array is not scanned, =0°, and (b) is a profile graph when the array is not scanned, =90°. Figure 7 , where (a) is a directional pattern profile graph when the array is scanned to =54°, =0°, and (b) is a directional pattern profile graph when the array is scanned to =54°, =90°. According to Figures 6-7 , it can be seen that the array arrangement optimized by the algorithm of the present application can achieve good sidelobe suppression performance.

[0063] Further, the same type of subarray is used for array arrangement by the method of the present application and the traditional method (multi-stage subarray division optimization algorithm), and the array arrangement results are compared as shown in Table 1: Table 1 Comparison of results of different optimization methods As can be seen from Table 1, the array arrangement optimized by the method of the present application is superior to the traditional method in sidelobe suppression, effectively solving the problems of the prior art that the non-regular subarray arrangement technology is limited by the regular array shape and the optimization is inefficient, and being able to obtain a high-performance array at a lower cost, with wide applicability and excellent performance.

[0064] The present application also includes an antenna array arranged by the array arrangement method formed by any one of the above examples or a combination of multiple examples.

[0065] The application further provides a storage medium having the same inventive concept as the irregular subarray arraying method formed by any one or combination of the examples, and computer instructions stored thereon, which, when executed, perform the steps of the irregular subarray arraying method formed by any one or combination of the examples.

[0066] Based on the understanding, the technical solution of the embodiments or the part of the technical solution that essentially contributes to the prior art or the part of the technical solution can be embodied in the form of a software product stored in a storage medium, including instructions to make a computer device (which can be a personal computer, a server, or a network device, etc.) execute all or part of the steps of the method described in the embodiments. The foregoing storage medium includes a U disk, a mobile hard disk, a read-only memory (ROM), a random access memory (RAM), a magnetic disk or an optical disk, and various media that can store program codes.

[0067] The application further provides a terminal having the same inventive concept as any one or combination of the examples corresponding to the irregular subarray arraying method, including a memory and a processor, the memory storing computer instructions executable on the processor, and the processor executing the steps of the irregular subarray arraying method when executing the computer instructions. The processor can be a single-core or multi-core central processing unit or a specific integrated circuit, or one or more integrated circuits configured to implement the application.

[0068] In an example, the terminal, i.e., the electronic device, is in the form of a general-purpose computing device, and the components of the electronic device can include but are not limited to the at least one processing unit (processor), the at least one storage unit, and a bus connecting different system components including the storage unit and the processing unit.

[0069] The storage unit stores program codes executable by the processing unit, so that the processing unit executes the steps according to various exemplary embodiments of the application described in the “Exemplary Method” section of the specification. For example, the processing unit can execute the irregular subarray arraying method.

[0070] The storage unit can include a readable medium in the form of a volatile storage unit, such as a random access memory (RAM) 3201 and / or a cache storage unit, and can further include a read-only memory (ROM).

[0071] The storage unit may also include a program / utility having a set (at least one) of program modules, including but not limited to: an operating system, one or more application programs, other program modules, and program data, each or some combination of these examples may include an implementation of a network environment.

[0072] A bus can represent one or more of several types of bus structures, including a memory cell bus or memory cell controller, a peripheral bus, a graphics acceleration port, a processing unit, or a local bus that uses any of the various bus structures.

[0073] The electronic device can also communicate with one or more external devices (e.g., keyboards, pointing devices, Bluetooth devices, etc.), one or more devices that enable a user to interact with the electronic device, and / or any device that enables the electronic device to communicate with one or more other computing devices (e.g., routers, modems, etc.). This communication can be performed via input / output (I / O) interfaces. Furthermore, the electronic device can communicate with one or more networks (e.g., local area networks (LANs), wide area networks (WANs), and / or public networks, such as the Internet) via a network adapter. The network adapter communicates with other modules of the electronic device via a bus. It should be understood that other hardware and / or software modules can be used in conjunction with the electronic device, including but not limited to: microcode, device drivers, redundant processing units, external disk drive arrays, RAID systems, tape drives, and data backup storage systems.

[0074] Through the above description, those skilled in the art will readily understand that the exemplary embodiments described herein can be implemented by software or by combining software with necessary hardware. Therefore, the technical solution according to this exemplary embodiment can be embodied in the form of a software product, which can be stored in a non-volatile storage medium (such as a CD-ROM, USB flash drive, external hard drive, etc.) or on a network, including several instructions to cause a computing device (such as a personal computer, server, terminal device, or network device, etc.) to execute the method of the exemplary embodiment of this application.

[0075] The above detailed embodiments are a description of the present invention. It should not be considered that the specific embodiments of the present invention are limited to these descriptions. For those skilled in the art, several simple deductions and substitutions can be made without departing from the concept of the present invention, and all of these should be considered to fall within the protection scope of the present invention.

Claims

1. A method for arranging irregular subarrays, characterized in that, Includes the following steps: Based on the predefined antenna subarray type, orientation, and boundary constraints of the antenna array region, multiple candidate subarrays are generated, consisting of triples of antenna subarray type, orientation, and antenna subarray position, forming a candidate subarray set. Based on whether the positions of each candidate subarray in the candidate subarray set overlap, a subarray conflict list is established to store the positional conflict relationships of each candidate subarray. Based on the candidate subarray set and the subarray conflict list, an optimization algorithm is used to select candidate subarrays that meet the preset quantity requirements from the candidate subarray set, ensuring that the positions of all candidate subarrays do not conflict and meet the preset performance indicators of the antenna array radiation pattern, thus obtaining the final array layout scheme.

2. The irregular subarray arrangement method according to claim 1, characterized in that, The antenna subarray comprises one or more subarrays with M antenna elements driven by a single feed channel, where M is a natural number.

3. The irregular subarray arrangement method according to claim 1, characterized in that, The boundary constraints of the antenna array region include: For irregularly shaped antenna array regions with arc or curved boundaries, if at least one antenna element in the antenna subarray is located within the antenna array region, the placement is deemed legal.

4. The irregular subarray arrangement method according to claim 1, characterized in that, The final array arrangement is obtained as follows: Based on the subarray conflict list, candidate subarrays are iteratively selected from the candidate subarray set and added to the selected subarray subset. In each iteration, the performance indicators of the current antenna array are optimized to the greatest extent until the number of candidate subarrays reaches the preset number or there are no candidate subarrays to choose from, and an initial array layout scheme is generated. A global search optimization is performed on the initial array scheme to obtain a final array scheme with better performance.

5. The irregular subarray arrangement method according to claim 4, characterized in that, The generation of the initial array scheme includes: The candidate subarrays in the candidate subarray set are grouped and iteratively selected by group. In each iteration, all candidate subarrays that have not yet been selected and do not conflict with the currently selected subset are tried in the current group, and the subarray that makes the antenna array pattern sidelobe level the lowest is added to the currently selected subset, until the number of candidate subarrays reaches the preset number or there are no candidate subarrays to choose from.

6. The irregular subarray arrangement method according to claim 4, characterized in that, A genetic algorithm is used to perform a global search optimization of the initial array scheme, including: The initial deployment scheme is encoded as the elite individuals in the first generation population; The remaining individuals are randomly selected according to the preset population size to form the initial population; each individual is encoded by an ordered sequence, and each gene in the sequence uniquely corresponds to a candidate subarray in the candidate subarray set. The activation of the gene indicates that the candidate subarray is selected. The fitness of each individual in the population is evaluated using the inverse of the maximum sidelobe level of the antenna array as the fitness function. Based on fitness, selection, crossover, and mutation operations are performed on the population to generate a new generation of population; Iteratively perform evaluation, selection, crossover, and mutation operations until the termination condition is met. The final array scheme is obtained by decoding the individual with the best fitness in each generation of the population.

7. The irregular subarray arrangement method according to claim 6, characterized in that, Following crossover and mutation operations, the following also applies: The newly generated individuals are decoded and conflict checked to determine whether the candidate subarrays are duplicated or conflicting. If duplicates or conflicts are found, a repair mechanism is initiated to replace the duplicated or conflicting candidate subarrays with non-conflicting candidate subarrays from the candidate subarray set.

8. An antenna array, characterized in that, The array is obtained by arranging the array using the method described in any one of claims 1-7.

9. A storage medium storing computer instructions thereon, characterized in that, When the computer instructions are executed, they perform the steps of the irregular subarray arrangement method according to any one of claims 1-7.

10. A terminal comprising a memory and a processor, wherein the memory stores computer instructions executable on the processor, characterized in that, When the processor executes the computer instructions, it performs the steps of the irregular subarray arrangement method according to any one of claims 1-7.

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