A simplified method for aperture phased array transceiver simultaneous array structure

Abstract

The application discloses a simplification method of aperture level transceiving simultaneous array structure and relates to the technical field of array antennas.The simplification method comprises the following steps: constructing a phased array antenna; constructing a target function, taking maximum effective omnidirectional isolation (EII) as the target function; adopting a genetic algorithm to calculate the EII value of each individual, i.e., the fitness value of the individual, finding an optimal individual meeting a preset condition according to the target function, and generating sparse optimization results about a transmitting array and a receiving array according to the optimal individual; adjusting the number of transmitting elements and receiving elements of the phased array antenna according to the sparse optimization results, and generating a sparse array.Compared with the prior art, the application realizes array sparseness based on the genetic algorithm, removes a part of transmitting channels, and simultaneously removes observation channels, so that the purposes of reducing system cost and maintaining good isolation performance are achieved, the time resource and the spectrum resource of the system are reduced, and various modes and application scenarios of communication and radar are supported.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of array antenna, more particularly, to a simplified method of aperture-level simultaneous transmit-receive array structure. BACKGROUND

[0002] The demand for multifunctional phased arrays is rapidly growing in the fields of radar, communication and electronic warfare. Simultaneous transmit and receive (STAR) is an important application of digital phased arrays, which can transmit and receive signals of the same frequency and time on the same environment and the same system. STAR technology can significantly improve the throughput and frequency band efficiency, while supporting multiple operating modes and multiple pulse repetition intervals, enabling continuous response to interference, while supporting joint multi-user systems. In order to fully utilize the STAR digital phased array, the isolation between the transmitter and the receiver must be strengthened.

[0003] In the prior art, the MIT team adopts aperture-level simultaneous transmit and receive (ALSTAR) technology of digital beamforming and self-interference cancellation, which is sufficient to achieve 163.9dB effective isotropic isolation (EII) on a 5x10 element digital phase of 100MHz instantaneous bandwidth. Further, they improved the theoretical research of the ALSTAR array, and under the condition of 2500W transmission power between 25 transmitting units and 25 receiving units, the isolation degree can reach 187.1dB, and the background noise is only increased by 2.2dB. This method can improve the isolation between the transmitter and the receiver. However, in the model of the ALSTAR array, self-interference cancellation (SIC) is achieved by establishing an observation channel between the output of the power amplifier and the output of the receive beamforming, and it is required that in each transmitting channel, the observation channel has the same performance as the receiving channel. Since the cost of the receiving channel is usually higher than that of the transmitting channel. With the increase of the array size, more observation channels are needed, which greatly increases the cost and complexity of the system. SUMMARY

[0004] In order to overcome the defect of high cost of large-scale phased array using STAR in the prior art, the present application provides a simplified method of aperture-level simultaneous transmit-receive array structure.

[0005] To solve the above technical problems, the technical scheme of the present application is as follows:

[0006] In a first aspect, a simplified method of aperture-level simultaneous transmit-receive array structure includes:

[0007] constructing a phased array antenna; the phased array antenna is an ALSTAR structure;

[0008] constructing an objective function, taking maximum effective omnidirectional isolation (EII) as the objective function;

[0009] adopting a genetic algorithm (GA) to calculate the EII value of each individual, i.e., the fitness value of the individual, finding an optimal individual meeting a preset condition according to the objective function, and generating sparse optimization results about the transmitting array and the receiving array according to the optimal individual, adjusting the number of transmitting elements and receiving elements of the phased array antenna according to the sparse optimization results, and generating a sparse array; the optimal individual is an individual with the maximum fitness value.

[0010] In the technical solution, the beamforming (BF) technology is introduced on the basis of the SIC technology, the maximum isolation between the transmitting aperture and the receiving aperture is ensured by constructing an objective function, and the genetic algorithm is adopted to omit the corresponding observation channels by sparsifying the elements slightly contributing to the isolation between the transmitting array and the receiving array, so that the number of antenna elements and reference links is reduced, the system cost is reduced, and the optimal isolation between the transmitting aperture and the receiving aperture is ensured.

[0011] In a second aspect, the application further provides a phased array antenna device, comprising a plurality of aperture-level transceiving simultaneous array structures, and the aperture-level transceiving simultaneous array structure is a sparse array generated by the simplified method of the aperture-level transceiving simultaneous array structure according to the first aspect.

[0012] In a third aspect, the application further provides a storage medium having a computer program stored thereon, and the computer program is executed by a processor to execute the simplified method of the aperture-level transceiving simultaneous array structure according to the first aspect.

[0013] Compared with the prior art, the technical solution of the application has the following beneficial effects:

[0014] The application proposes to perform array sparsification based on the genetic algorithm, to subtract a part of transmitting channels, and to simultaneously subtract observation channels, so as to reduce the system cost and maintain good isolation performance, so that the aperture-level digital phased array can perform transmitting and receiving simultaneously, the time resource and the spectrum resource of the system are reduced, and the deployment of the genetic algorithm can enable the entire system to support communication, radar, various modes and application scenarios. BRIEF DESCRIPTION OF DRAWINGS

[0015] Figure 1 The flowchart of the simplified method of the aperture-level transceiving simultaneous array structure;

[0016] Figure 2 The schematic diagram of the phased array antenna model;

[0017] Figure 3 Schematic diagram of sparse before and after for transmit array and receive array

[0018] Figure 4 Flow chart of simplified method of aperture level transceiving simultaneous array structure in embodiment 1

[0019] Figure 5 Port reflection coefficient diagram of transmit array to receive array in embodiment 2

[0020] Figure 6 Coupling coefficient diagram of No. 1 transmit array element and each receive array element in embodiment 2

[0021] Figure 7 Pattern diagram of No. 1 transmit array element and No. 17 receive array element in embodiment 2

[0022] Figure 8 EII comparison diagram of SIC, SIC-BF and SIC-BF-Sparse at different scanning angles in embodiment 2

[0023] Figure 9 Performance comparison diagram of SIC, SIC-BF and SIC-BF-Sparse with sparse rate of 0.75 at noise power P n , transmit gain G t and receive gain G r in embodiment 2

[0024] Figure 10 Performance comparison diagram of SIC, SIC-BF and SIC-BF-Sparse at beam scanning to 0° on transmit gain G t and receive gain G r in embodiment 2 DETAILED DESCRIPTION

[0025] The drawings are only for illustrative purposes and should not be construed as limiting the patent;

[0026] In order to better illustrate the embodiments, some parts of the drawings may be omitted, enlarged or reduced, and do not represent the actual size of the product;

[0027] It is understandable that some well-known structures and their descriptions in the drawings may be omitted for those skilled in the art.

[0028] The technical solutions of the present application will be further described below in combination with the drawings and embodiments.

[0029] Embodiment 1

[0030] This embodiment proposes a simplified method of aperture level transceiving simultaneous array structure, which is described with reference toFigure 1 , comprising:

[0031] constructing a phased array antenna; the phased array antenna is an ALSTAR structure;

[0032] constructing an objective function for calculating the maximum value of effective isotropic isolation (EII);

[0033] adopting a genetic algorithm to take the effective isotropic isolation (EII) as a fitness function, to find an optimal individual satisfying a preset condition according to the objective function, and to generate sparse optimization results about the transmitting array and the receiving array according to the optimal individual, to adjust the number of transmitting elements and receiving elements of the phased array antenna according to the sparse optimization results, and to generate a sparse array; the optimal individual is an individual with the maximum fitness value.

[0034] In a specific implementation, the phased array antenna adopts a U-shaped slot microstrip patch antenna with high gain and low coupling characteristics as an antenna element in a continuous wave radar scenario. The center frequency of the antenna is 4.3 GHz, the working bandwidth is 100 MHz, the coupling between the No. 1 transmitting element and each receiving element is less than -40 dB, and the maximum gain of the antenna reaches 5.5 dBi.

[0035] As non-limiting examples, the phased array includes but is not limited to a uniform planar array and a non-uniform planar array.

[0036] In a specific implementation, referring to Figure 2 , the phased array is a 4x8 phased planar array, 8 elements are uniformly arranged along the X axis with a spacing of the wavelength λ = 0.5 corresponding to the center frequency of the antenna in free space, 4 elements are uniformly arranged along the Y axis with a spacing of 0.5, and an antenna aperture of 32 elements is formed. The 4x4 elements on the left side of the array are defined as a transmitting array, and the 4x4 elements on the right side of the array are defined as a receiving array; wherein, the transmitting elements and the receiving elements are both 4x4 planar arrays, and the working states of the transmitting elements and the receiving elements are both represented by 0 and 1: 1 represents that there is an element at the corresponding position, i.e. it is retained; 0 represents that there is no element at the corresponding position, i.e. it is removed.

[0037] After the phased array is constructed, the maximum value of effective omnidirectional isolation EII is taken as a target function, a genetic algorithm is used to realize sparse optimization of the phased array structure, the value of effective omnidirectional isolation EII of the array structure is taken as the fitness value of an individual, and according to the iterative optimization search mechanism of the genetic algorithm, an optimal individual satisfying a preset condition, i.e., an individual with the maximum fitness value, is found out, and the value of effective omnidirectional isolation EII of the corresponding array structure is the maximum; a sparse optimization result about the transmitting array and the receiving array is generated according to the optimal individual, and the number of transmitting elements and receiving elements of the phased array antenna is adjusted according to the sparse optimization result, so that the phased array antenna can still obtain an ideal isolation while reducing the number of transmitting elements and receiving elements and the number of reference links, and the purpose of reducing the design cost and system complexity is achieved.

[0038] In a specific implementation process, refer to Figure 3 , wherein Figure 3 (a) represents the structure of the transmitting array and the receiving array before being sparse, Figure 3 (b) represents the structure of the transmitting array and the receiving array after being sparse, 1 represents that there is an element in the corresponding position, i.e., being reserved; 0 represents that there is no element in the corresponding position, i.e., being removed. Among them, the uniform planar array containing 16 transmitting elements and 16 receiving elements is finally reserved as a sparse planar array containing 12 transmitting elements and 12 receiving elements, and the sparse rate is 0.75.

[0039] In a preferred embodiment, the target function expression is:

[0040]

[0041] In the formula,

[0042]

[0043]

[0044] M sparse = M.*ff i ff i H

[0045]

[0046]

[0047] Among them, P t represents the transmitting signal power; q t / r (φ,θ) represents the transmitting and receiving array steering vectors before being sparse; g t / r (φ,θ) represents the transmitting and receiving array element gain before being sparse; M represents the coupling matrix between the transmitting array and the receiving array before being sparse; M sparsedenotes the coupling matrix between the sparse transmit array and the receive array; denotes the covariance matrix of the residual interference and noise after sparsing; denotes the total gain of the transmit array; denotes the total gain of the receive array; denotes the gain of a single element; denotes the beamforming vector of the transmit array and the receive array, respectively; denotes the steering vector of the transmit array and the receive array, respectively, and φ, θ denote the azimuth angle and the elevation angle, respectively, λ denotes the signal wavelength, x denotes the distance of each element in the array plane to the x-axis, and y denotes the distance of each element in the array plane to the y-axis; i = (ff i1 , ff i2 , …, ff id ) denotes the array state of the i-th individual after sparsing of the transmit array or the receive array, ff id denotes the working state of the element in the corresponding array, and d is the number of the transmit array elements and the receive array elements in the full array state; id = 1 indicates that the element at the position is reserved, and ff id = 0 indicates that the element at the position is removed.

[0048] In a preferred embodiment, referring to Figure 4 , the genetic algorithm is used to calculate the EII value of each individual, i.e., the fitness value of the individual, to find the optimal individual satisfying the preset condition according to the objective function, and to generate the sparsing optimization result about the transmit array and the receive array according to the optimal individual, and to adjust the number of the transmit array elements and the receive array elements of the phased array antenna according to the sparsing optimization result, comprising:

[0049] Genetic algorithm coding: an initial population satisfying the preset sparsing rate is constructed, the population size is set to N, each individual in the population is a binary parameter vector, representing a situation of deleting an element position, and the gene dimension of each individual is equal to the number N t of the transmit array elements or the number N r of the receive array elements; g i,k denotes the i-th individual of the genetic generation k, wherein i = 1, 2, …, N; the effective omnidirectional isolation EII is used as the fitness function, and the fitness value of each individual g i,k is generated by the fitness function, i.e., the fitness value of each individual g i,k is the EII value;

[0050] The number of the transmit array elements or the receive array elements after sparsing is set to N L , and N t or N ra random number following Gaussian distribution, sorting the random number in descending order, setting the values of the first N L genes as 1 and the values of the rest of the genes as 0, and establishing the initial search point of the sparse transmitting and receiving elements after initial encoding of each individual;

[0051] Genetic algorithm selection: based on the roulette algorithm, the possibility of retaining the offspring of each individual is determined according to the proportion of the fitness fit i of the i-th individual in the total fitness of the population; wherein, the probability p i of selecting the i-th individual is:

[0052]

[0053] A uniform random number in the interval [0, 1] is generated, and the random number is used as a selection pointer of the roulette to determine the selected individual in the current round; the selected individual g i,k and g i+1,k are used for crossover operation;

[0054] Genetic algorithm crossover: according to the adaptive crossover probability p c , the crossover operation of a certain probability is performed between the selected two individuals g i,k and g i+1,k in the population; the genes represent the retention or removal of the elements;

[0055] Genetic algorithm mutation: for each individual in the population after the crossover operation, the adaptive mutation probability p m is used to perform the mutation operation of the genes in the individual;

[0056] Maintain the sparsity: it is judged whether the sparsity of each individual in the newly generated population is unchanged, i.e. whether the number of elements in each individual in the offspring population is equal to N L ; if yes, no operation is performed; otherwise, according to the difference between the number of elements in each individual in the offspring population and N L , the working state of the elements is randomly selected; wherein, when the working state of the element is 1, it means that the element at this position is retained, and when the working state of the element is 0, it means that the element at this position is removed;

[0057] The genetic algorithm is terminated: the newly generated individual is evaluated, the fitness value of the new individual is calculated, the individual with the maximum fitness value is taken as the current optimal individual according to the objective function; it is judged whether the number of iterations of the genetic algorithm is not less than the preset maximum number of iterations: if yes, the optimal individual is output as the sparse optimization result, and the transmitting array elements and the receiving array elements are adjusted according to the sparse optimization result, the optimal individual dimension parameter is matched with the transmitting array and the receiving array element position, the elements with the position of 1 are retained, and the elements with the position of 0 are deleted, and a sparse array is generated; otherwise, the optimal individual is retained in the new generation population, and the next genetic algorithm operation is performed.

[0058] In the preferred embodiment, when the genetic algorithm is executed, the effective isotropic isolation EII is taken as the fitness function, and the retention and deletion states of the array elements are represented by binary symbols (1, 0), that is, the retention or removal of the corresponding position elements, the length of each binary parameter vector represents the number of transmitting array elements and receiving array elements, so that each individual in each generation population of the genetic algorithm corresponds to a situation of deleting array element positions, and the transmitting array element or receiving array element steering vector of the array can be dynamically changed with the deletion of the array elements. Through the genetic algorithm, the situations of deleting the transmitting array elements and the receiving array elements are randomly traversed, the effective isotropic isolation EII under the corresponding situation is calculated, the performance of the number of parameter combinations is checked, the optimal individual corresponding to the maximum effective isotropic isolation EII is screened out, and the transmitting array element and receiving array element settings after coefficient optimization are obtained.

[0059] In an optional embodiment, the adaptive crossover probability p c is determined according to the following formula: i,k The crossover operation with a certain probability is performed, and part of the genes between the two selected individuals g i+1,k and g c in the population are exchanged, including:

[0060] A pair of individuals to be crossed is taken out, and the adaptive crossover probability p c is generated.

[0061] The p c is compared with a random number generated in the interval [0, 1]: when the p t is small, according to the bit string length N r or N t , a whole number m in the interval [1, N r -1] or [1, N r -1] is randomly selected as the crossover position, and the paired individuals exchange their respective part of the genes at the crossover position, thereby forming a pair of new individuals; otherwise, the individual is retained.

[0062] As a non-limiting example, the expression of the adaptive crossover probability p c is as follows:

[0063]

[0064] where f c is the fitness value of the individual with greater fitness value in the crossover operation, f max is the maximum fitness value of the population, f mean is the average fitness value of the population, k c1 and k c2 represent a scaling factor of the adaptive mutation probability p c .

[0065] In a specific implementation, k c1 is preset to 0.85, and k c2 is preset to 0.25.

[0066] As a non-limiting example, the adaptive mutation probability p c may also be expressed as:

[0067]

[0068] where f max is the maximum fitness value of the population, f ave is the average fitness value of the population, 0 < k1≤ 1, and k1is a preset constant.

[0069] In an alternative embodiment, the mutation operation is performed on each individual in the population after the crossover operation with an adaptive mutation probability p m , which includes:

[0070] The adaptive mutation probability p m is generated for each individual in the population after the crossover operation.

[0071] A random number r is generated in the interval [0, 1], and if r < p m , the selected individual g i,k (i = 1, 2,..., N) is subjected to a mutation operation on its nth gene: if the selected gene value is 1, it is changed to 0; if the selected gene value is 0, it is changed to 1; where n = 1, 2,..., Nt or n = 1, 2,..., Nr.

[0072] If r ≥ p m , no mutation operation is performed, i.e., the genes of the individual g i,k remain unchanged and are inherited to the next generation population.

[0073] As a non-limiting example, the adaptive mutation probability p m may be expressed as:

[0074]

[0075] In the formula, f m It is the fitness of the individual undergoing mutation, f max It is the maximum value of the population fitness, f mean It is the average fitness of the population, k m1 and k m2 Represents the adaptive mutation probability p m The scaling factor.

[0076] In a specific implementation process, k m1 The default value is 0.05, k m2 The default value is 0.025.

[0077] As a non-limiting example, the adaptive mutation probability p m It can also be expressed as:

[0078]

[0079] Among them, f max f is the maximum fitness value of the population. ave k2 represents the average fitness of the population, where 0 < k2 ≤ 1, and k2 is a preset constant.

[0080] In an optional embodiment, the step of determining the number of array elements corresponding to each individual in the offspring population and N... L The difference in quantity is used to randomly select array elements for setting their working status, including:

[0081] When the number of elements corresponding to individuals in the offspring population exceeds N L At that time, randomly select the difference in the number of array elements from the array elements in state 1, and force their working state to be 0;

[0082] When the number of elements corresponding to individuals in the offspring population is less than N L At that time, a difference in the number of array elements are randomly selected from the array elements in state 0, and their working state is forced to be 1.

[0083] Example 2

[0084] This embodiment uses a 16Tx×16Rx uniform planar U-shaped slot microstrip patch antenna phased array, and applies the simplified method of aperture-level simultaneous transmit and receive array structure proposed in Embodiment 1 (hereinafter referred to as SIC-BF-Sparse) to conduct experiments.

[0085] Experimental parameters are as follows Figures 5-7 As shown, the antenna has a center frequency of 4.3 GHz and an operating bandwidth of 100 MHz. The coupling between the transmitting array element 1 and each receiving array element is less than -40 dB, and the antenna's maximum gain reaches 5.5 dBi. This antenna exhibits excellent low-coupling and high-gain characteristics.

[0086] Experimental results are as followsFigures 8-10

[0087] Figure 8 shows the performance of SIC, SIC-BF and SIC-BF-Sparse when the transmit signal power p t is 1000W at different scanning angles. It can be seen that the SIC-BF technology achieves EII>183dB at the beam scanning angle [-30°, 30°], which is 43dB higher than that of SIC; while the SIC-BF-Sparse method applied in this embodiment, when the sparsity is 0.75 and the scanning angle is 0°, the EII value is 185dB, which is only 3dB lower than that of SIC-BF, the number of observation links is reduced by 25%, and the system cost can be significantly reduced. In addition, this embodiment also discusses the EII curves achieved by SIC-BF-Sparse technology across scanning angles at different sparsities, please refer to Figure 8 .

[0088] Figure 9 (a) shows the performance comparison of SIC, SIC-BF and SIC-BF-Sparse with sparsity of 0.75 at noise power P n , Figure 9 (b) shows the performance comparison of the three technologies at transmit gain G t , Figure 9 (c) shows the performance comparison of the three technologies at receive gain G r . It can be seen that the P n value of SIC-BF and SIC-BF-Sparse at the scanning angle of 0° is 0.9dB and 1.8dB higher than the noise floor, which is 46.2dB and 45.3dB higher than that of SIC respectively; the G t and G r of SIC-BF-Sparse technology are reduced by 1.5dBi and 1.2dBi respectively compared with SIC-BF.

[0089] Figure 10 (a) shows the performance comparison of SIC, SIC-BF and SIC-BF-Sparse at transmit gain G t when the beam is scanned to 0°, Figure 10 (b) shows the performance comparison of SIC, SIC-BF and SIC-BF-Sparse at receive gain G r when the beam is scanned to 0°. It can be seen that the peak directivity of G t and G r of the three technologies at the scanning angle of 0° is basically similar. The G t ​is 16.4dBi, which is reduced by 3.2dBi and 1.3dBi compared with SIC and SIC-BF, respectively. Thus, it is concluded that the transmit and receive aperture efficiency of the sparse array generated by the simplified method of the aperture-level transceiving simultaneous array structure applied in this embodiment is not reduced. It is further proved that good ALSTAR performance can be obtained by using sparse technology while reducing the number of transmit and receive elements and the number of observation links.

[0090] Embodiment 3

[0091] This example proposes a phased array antenna device, which includes a plurality of aperture-level transceiving simultaneous arrays, and the aperture-level transceiving simultaneous array structure is a sparse array generated by the simplified method of the aperture-level transceiving simultaneous array structure proposed in embodiment 1.

[0092] Embodiment 4

[0093] This example proposes a storage medium, which stores a computer program, and the computer program is executed by a processor to execute the simplified method of the aperture-level transceiving simultaneous array structure proposed in embodiment 1.

[0094] The same or similar reference signs correspond to the same or similar components;

[0095] The terms describing the positional relationship in the drawings are only used for illustrative description, and should not be understood as a limitation on the patent;

[0096] Obviously, the above embodiments of the present application are only examples for clearly illustrating the present application, and are not intended to limit the implementation manner of the present application. Based on the above description, other different forms of changes or variations can be made by those skilled in the art. Here, it is not necessary and impossible to enumerate all the implementation manners. Any modification, equivalent replacement and improvement made within the spirit and principle of the present application should be included in the protection scope of the claims of the present application.

Claims

1. A simplified method for an aperture-level simultaneous transmit / receive array structure, characterized in that, include: Construct a phased array antenna; The phased array antenna is an ALSTAR structure; Construct an objective function, taking the maximization of effective omnidirectional isolation (EII) as the objective function; A genetic algorithm is used to calculate the EII value of each individual, i.e., the fitness value of the individual. The optimal individual that meets the preset conditions is found according to the objective function. Based on the optimal individual, sparse optimization results for the transmitting and receiving arrays are generated. The number of transmitting and receiving elements of the phased array antenna is adjusted according to the sparse optimization results to generate a sparse array. The optimal individual is the individual with the highest fitness value; The process employs a genetic algorithm to calculate the EII value (fitness value) of each individual, finds the optimal individual that meets preset conditions based on the objective function, and generates sparse optimization results for the transmit and receive arrays based on these optimal individuals. The number of transmit and receive elements of the phased array antenna is then adjusted according to these sparse optimization results to generate a sparse array, including: Genetic Algorithm Encoding: Construct an initial population that satisfies a preset sparsity rate. Set the population size to N. Each individual in the population is a binary parameter vector, representing a case of pruning array element positions. The gene dimension of each individual is equal to the number of emitted array elements, N. t Or the number of receiving array elements N r Define g i,k Let g represent the i-th individual in the k-th generation, where i = 1, 2, ..., N; and let Efficient Omnidirectional Isolation (EII) be used as the fitness function, i.e., g for each individual. i,k The fitness value is the EII value; After setting the number of transmitting or receiving elements to sparse, let N be the number of elements. L N is generated between [0,1]. t or N r Take N random numbers that follow a Gaussian distribution, sort them in descending order, and select the top N... L The value of one gene is set to 1, and the value of the remaining genes is set to 0. After the initial encoding of each individual, the search initial point for sparse emission and reception array elements is established. Genetic algorithm selection: Based on the roulette wheel algorithm, the selection is based on the fitness of the i-th individual. i The probability of an individual's offspring being retained is determined by the proportion of its population fitness to the total population fitness; where the probability p of the i-th individual being selected is... i The expression is: Generate a uniformly distributed random number within the interval [0, 1]. Use this random number as the selection pointer in a roulette wheel to determine the selected individual in the current round. The selected individual g i,k and g i+1,k Used for cross operations; Genetic algorithm crossover: based on adaptive crossover probability p c Perform a crossover operation with a specific probability, swapping two selected individuals g from the population. i,k and g i+1,k The genes between; the genes correspond to the elements to be retained or removed; Genetic algorithm mutation: For each individual in the population after crossover, with an adaptive mutation probability p m To perform gene mutation operations within an individual; Maintaining constant sparsity: Determine whether the sparsity of each individual in the newly generated population remains unchanged, i.e., calculate whether the number of array elements in each individual in the offspring population is equal to N. L If yes, no action is taken; otherwise, the number of array elements in each individual in the offspring population is determined by N. L The difference in quantity is used to randomly select array elements for setting their working status; where, when the array element's working status is 1, it means that the array element at that position is retained, and when the array element's working status is 0, it means that the array element at that position is removed. Genetic Algorithm Termination: Evaluate the newly generated individuals, calculate their fitness values, and select the individual with the highest fitness value as the current optimal individual based on the objective function; determine if the number of iterations of the genetic algorithm is not less than the preset maximum number of iterations: if so, output the optimal individual as the sparse optimization result, and adjust the transmitting and receiving array elements according to the sparse optimization result, matching the dimension parameters of the optimal individual with the positions of the transmitting and receiving array elements, retaining the elements with positions displayed as 1, deleting the elements with positions displayed as 0, and generating a sparse array; otherwise, retain the optimal individual in the new generation population and perform the next genetic algorithm operation.

2. The simplified method for an aperture-level simultaneous transmit / receive array structure according to claim 1, characterized in that, The objective function expression is: In the formula, M sparse =M.*ff i f i H Among them, P t Indicates the transmitted signal power; q t / r (φ,θ) represents the transmit and receive array steering vectors before sparsity; g t / r (φ,θ) represents the element gain of the transmit and receive arrays before sparsity; M represents the coupling matrix between the transmit and receive arrays before sparsity; M sparse Represents the coupling matrix after sparsening; Represents the covariance matrix of the interference and noise after sparsity; Indicates the total gain of the transmitting array; Indicates the total gain of the receiving array; Indicates the gain of a single array element; These represent the beamforming vectors of the transmitting array and the receiving array, respectively; These represent the steering vectors of the transmitting array and the receiving array, respectively. φ and θ represent the azimuth and elevation angles, respectively; λ represents the signal wavelength; x represents the distance from each element in the array plane to the x-axis; and y represents the distance from each element in the array plane to the y-axis. i =(ff i1 ,ff i2 ,…,ff id ) represents the sparse array state of the transmit or receive array mapped to the i-th individual, ff id This indicates the working state of the array elements in the corresponding array, where d is the number of transmitting and receiving array elements in the full array state, and ff... id =1 indicates that the array element at that position is reserved, ff id =0 indicates that the element at that position has been removed.

3. The simplified method for an aperture-level simultaneous transmit / receive array structure according to claim 1, characterized in that, The adaptive crossover probability p c Perform a crossover operation with a specific probability, swapping two selected individuals g from the population. i,k and g i+1,k Some genes between them, including: Select a pair of individuals to mate and generate an adaptive crossover probability p. c ; p c Compare with the random numbers generated in the interval [0,1]: when p c When the length N is small, it depends on the length of the bit string. t or N r For a pair of individuals to be crossed, randomly select the interval [1, N]. t -1] or [1,N] r The integer m in [-1] serves as the intersection position. Paired individuals exchange some of their genes at the intersection position to form a new pair of individuals; otherwise, the individual is retained.

4. A simplified method for an aperture-level simultaneous transmit / receive array structure according to claim 3, characterized in that, The adaptive crossover probability p c The expression is as follows: In the formula, f c f is the individual with the higher fitness value among the two individuals undergoing the crossover operation. max It is the maximum value of the population fitness, f mean It is the average fitness of the population, k c1 and k c2 Represents the adaptive crossover probability p c The scaling factor.

5. A simplified method for an aperture-level simultaneous transmit / receive array structure according to claim 1, characterized in that, For each individual in the population after the crossover operation, an adaptive mutation probability p is used. m Performing gene mutation operations within an individual, including: For each individual in the population after the crossover operation, generate an adaptive mutation probability p. m ; Generate a random number r in the interval [0,1]. <p m Then for the selected individual g i,k (i = 1, 2, ..., N) The nth gene undergoes a mutation operation: if the value of the selected gene is 1, then its value becomes 0; if the value of the selected gene is 0, then its value becomes 1; where n = 1, 2, ..., Nt or n = 1, 2, ..., Nr; If r≥p m If the mutation operation is not performed, then individual g will not be mutated. i,k The genes remain unchanged and are passed on to the next generation.

6. A simplified method for an aperture-level simultaneous transmit / receive array structure according to claim 5, characterized in that, The adaptive mutation probability p m The expression is as follows: In the formula, f m It is the fitness of the individual undergoing mutation, f max It is the maximum value of the population fitness, f mean It is the average fitness of the population, k m1 and k m2 Represents the adaptive mutation probability p m The scaling factor.

7. A simplified method for an aperture-level simultaneous transmit / receive array structure according to claim 1, characterized in that, The number of array elements corresponding to each individual in the offspring population and N are used as the basis for this. L The difference in quantity is used to randomly select array elements for setting their working status, including: When the number of elements corresponding to individuals in the offspring population exceeds N L At that time, randomly select the difference in the number of array elements from the array elements in state 1, and force their working state to be 0; When the number of elements corresponding to individuals in the offspring population is less than N L At that time, a difference in the number of array elements are randomly selected from the array elements in state 0, and their working state is forced to be 1.

8. A phased array antenna device, comprising a plurality of aperture-level simultaneous transmit / receive arrays, characterized in that, The aperture-level simultaneous transmit and receive array structure is a sparse array generated by applying a simplified method of the aperture-level simultaneous transmit and receive array structure according to any one of claims 1-7.

9. A storage medium having a computer program stored thereon, characterized in that, When the computer program is executed by the processor, it performs a simplified method for an aperture-level simultaneous transmit and receive array structure as described in any one of claims 1-7.

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