Frequency-invariant antenna array optimization method and device based on amplitude spectrum analysis

Abstract

The embodiments of this specification provide a method and device for optimizing the arrangement of a non-frequency-variant antenna array based on amplitude spectrum analysis, wherein the method for optimizing the arrangement of a non-frequency-variant antenna array based on amplitude spectrum analysis includes: obtaining a virtual dense array composed of multiple antenna units, and determining the initial parameters of the virtual dense array; constructing a reference pattern based on the initial parameters, and determining the initial excitation of the reference pattern and the expected index parameters of the virtual dense array; constructing a space spectrum distribution based on the initial excitation and the expected index parameters, and selecting a target antenna unit in the virtual dense array according to the amplitude spectrum information corresponding to the space spectrum distribution; constructing a target non-uniform array according to the target antenna unit, wherein the target non-uniform array meets the preset antenna radiation conditions. It is possible to ensure the radiation performance of the antenna array while reducing the density of the antenna array, thereby reducing the complexity and cost of the hardware.

Description

Technical Field

[0001] The embodiments of this specification relate to the field of antenna array optimization technology, and more particularly to a method and device for optimizing the deployment of a frequency-invariant antenna array based on amplitude spectrum analysis. Background Art

[0002] An array antenna is a special antenna formed by combining multiple antenna units of the same structure according to specific rules. This antenna uses the principle of coherent superposition of electromagnetic waves. Compared with a single antenna unit, it has the advantages of high gain, narrow beam, low side lobe and strong directivity. With the vigorous development of the 5G industry and the maturity of semiconductor manufacturing technology, people prefer to use more antenna units to form array antennas to meet the needs of communication tasks in different frequency bands. However, large-scale array antennas often mean higher construction costs and complex array feeding networks.

[0003] Therefore, how to minimize the communication system cost and the difficulty of array implementation while maintaining the array radiation performance has become a major challenge in the field of array signal processing. Summary of the invention

[0004] In view of this, the embodiments of this specification provide a method for optimizing the deployment of a frequency-invariant antenna array based on amplitude spectrum analysis. One or more embodiments of this specification also relate to a frequency-invariant antenna array optimization device based on amplitude spectrum analysis, a computing device, a computer-readable storage medium, and a computer program product to solve the technical defects existing in the prior art.

[0005] According to a first aspect of an embodiment of this specification, a method for optimizing the arrangement of a frequency-invariant antenna array based on amplitude spectrum analysis is provided, comprising:

[0006] Acquire a virtual dense array composed of a plurality of antenna units, and determine initial parameters of the virtual dense array;

[0007] Constructing a reference pattern based on the initial parameters, and determining an initial excitation of the reference pattern and expected index parameters of the virtual dense array;

[0008] Constructing a spatial spectrum distribution based on the initial excitation and the expected index parameter, and selecting a target antenna unit in the virtual dense array according to amplitude spectrum information corresponding to the spatial spectrum distribution;

[0009] A target non-uniform array is constructed according to the target antenna unit, wherein the target non-uniform array meets a preset antenna radiation condition.

[0010] Optionally, the acquiring a virtual dense array formed by a plurality of antenna units and determining initial parameters of the virtual dense array includes:

[0011] Acquire a virtual dense array, and determine an initial array pattern, an initial broadband excitation, and a space-time angular frequency corresponding to the virtual dense array;

[0012] The initial array pattern, the initial broadband excitation and the space-time angular frequency are used as the initial parameters.

[0013] Optionally, constructing a target broadband pattern based on the initial parameters includes:

[0014] Determining an intermediate broadband pattern based on the space-time angular frequency and the initial array pattern;

[0015] Sampling the space-time angular frequency according to a preset sampling interval to obtain a target number of samples corresponding to the space-time angular frequency, and dimensionally expanding the initial broadband excitation according to the target number of samples to obtain an extended broadband excitation;

[0016] Update the intermediate broadband directional pattern according to the extended broadband excitation to obtain a target broadband directional pattern;

[0017] The reference directional pattern is constructed according to the operating frequency of the target broadband directional pattern.

[0018] Optionally, constructing a spatial spectrum distribution based on the initial excitation and the expected index parameter includes:

[0019] Determining the desired sidelobe level and the desired mainlobe FI beamwidth of the initial excitation;

[0020] The initial excitation is dimensionally expanded by a zero-filling rule to obtain a target excitation, and a sub-band reference pattern is calculated by an iterative fast Fourier transform single-frequency synthesis algorithm for the target excitation;

[0021] According to the expected sidelobe level and the expected mainlobe FI beamwidth, the sidelobe level and the mainlobe FI beamwidth of the subband reference pattern are corrected to obtain a target subband reference pattern, wherein the phase of the subband reference pattern remains unchanged;

[0022] A target sub-band excitation of the target sub-band reference pattern is determined, and the spatial spectrum distribution is determined according to the target sub-band excitation.

[0023] Optionally, selecting a target antenna unit in the virtual dense array according to amplitude spectrum information corresponding to the spatial spectrum distribution includes:

[0024] Performing an inverse Fourier transform on the spatial spectrum distribution to obtain a target broadband excitation corresponding to the virtual dense array, and performing dimensionality reduction processing on the target broadband excitation to obtain a dimensionality reduction matrix;

[0025] Selecting a plurality of first target array elements from the dimension reduction matrix, performing clustering processing on the remaining array elements in the dimension reduction matrix except the plurality of first target array elements, and determining a plurality of second target array elements according to the clustering result;

[0026] The first target array element and the second target array element are used as target antenna units.

[0027] Optionally, the selecting a plurality of first target array elements from the dimension reduction matrix includes:

[0028] Determine the contribution score of each array element in the dimension reduction matrix relative to the target broadband excitation, and the comprehensive error information of the FI pattern corresponding to each array element;

[0029] According to the contribution score of each array element and the comprehensive error information of the FI pattern, a plurality of first target array elements are selected in the dimension reduction matrix.

[0030] Optionally, after constructing a target non-uniform array according to the target antenna unit, the method further includes:

[0031] Calculate the target coefficients of the filter corresponding to the target non-uniform array by a convex optimization solution algorithm;

[0032] The expected waveform corresponding to the target non-uniform array is determined by configuring the filter of the target coefficients.

[0033] According to a second aspect of an embodiment of this specification, a frequency-invariant antenna array optimization device based on amplitude spectrum analysis is provided, comprising:

[0034] A data acquisition module is configured to acquire a virtual dense array composed of a plurality of antenna units and determine initial parameters of the virtual dense array;

[0035] A reference pattern construction module is configured to construct a reference pattern based on the initial parameters, and determine an initial excitation of the reference pattern and expected index parameters of the virtual dense array;

[0036] An array element selection module is configured to construct a spatial spectrum distribution based on the initial excitation and the expected indicator parameter, and select a target antenna unit in the virtual dense array according to amplitude spectrum information corresponding to the spatial spectrum distribution;

[0037] The target array construction module is configured to construct a target non-uniform array according to the target antenna unit, wherein the target non-uniform array meets a preset antenna radiation condition.

[0038] According to a third aspect of an embodiment of this specification, a computing device is provided, including:

[0039] Memory and processor;

[0040] The memory is used to store computer programs / instructions, and the processor is used to execute the computer programs / instructions. When the computer programs / instructions are executed by the processor, the steps of the above-mentioned non-frequency-variant antenna array optimization layout method based on amplitude spectrum analysis are implemented.

[0041] According to a fourth aspect of the embodiments of this specification, a computer-readable storage medium is provided, which stores a computer program / instruction, and when the computer program / instruction is executed by a processor, the steps of the above-mentioned method for optimizing the arrangement of a non-frequency-variant antenna array based on amplitude spectrum analysis are implemented.

[0042] According to the fifth aspect of the embodiments of this specification, a computer program product is provided, including a computer program / instruction, which, when executed by a processor, implements the steps of the above-mentioned method for optimizing the deployment of a non-frequency-variant antenna array based on amplitude spectrum analysis*.

[0043] An embodiment of the present specification realizes the construction of a target non-uniform array by constructing a virtual dense array and selecting target antenna units that meet specific performance requirements. This method can ensure that the antenna array has higher performance. The method can construct a spatial spectrum distribution and select antenna units according to the expected index parameters of the virtual dense array, taking into account the preset antenna radiation conditions, so that the constructed target non-uniform array can meet specific radiation requirements. Therefore, the scheme in the embodiment of the present specification reduces the density of the antenna array while also meeting specific radiation performance. In actual deployment, it is not necessary to use all antenna units, thereby reducing the complexity and cost of the hardware. BRIEF DESCRIPTION OF THE DRAWINGS

[0044] Figure 1 This is a flow chart of a method for optimizing the deployment of a frequency-invariant antenna array based on amplitude spectrum analysis provided by an embodiment of this specification;

[0045] Figure 2 It is a schematic diagram of an FIR filter network of a filter summation array of a frequency-invariant antenna array optimization method based on amplitude spectrum analysis provided by another embodiment of the present specification;

[0046] Figure 3 It is a schematic diagram of array element layout of a target non-uniform linear array of a frequency-invariant antenna array optimization method based on amplitude spectrum analysis provided by another embodiment of the present specification;

[0047] Figure 4 It is a schematic diagram of spatial spectrum distribution of FI directional pattern containing uniform SLL in a frequency-invariant antenna array optimization method based on amplitude spectrum analysis provided by another embodiment of this specification;

[0048] Figure 5 A broadband discrete frequency FI pattern containing uniform SLL in a non-frequency-variant antenna array optimization method based on amplitude spectrum analysis provided by another embodiment of the present specification;

[0049] Figure 6 is a normalized filter coefficient h of a frequency-invariant antenna array optimization method based on amplitude spectrum analysis provided by another embodiment of this specification. l,n Distribution diagram;

[0050] Figure 7 It is a schematic diagram of the expected and designed frequency responses of the FIR filter of the second array element of a frequency-invariant antenna array optimization method based on amplitude spectrum analysis provided by another embodiment of the present specification;

[0051] Figure 8 is a flow chart of a method for optimizing the deployment of a frequency-invariant antenna array based on amplitude spectrum analysis provided by another embodiment of the present specification;

[0052] Fig. 9 is a structural schematic diagram of a non-frequency-variant antenna array optimization arrangement device based on amplitude spectrum analysis provided by another embodiment of the present specification;

[0053] Fig.10 It is a structural block diagram of a computing device provided by an embodiment of this specification. DETAILED DESCRIPTION

[0054] Many specific details are described in the following description to facilitate a full understanding of this specification. However, this specification can be implemented in many other ways than those described herein, and those skilled in the art can make similar generalizations without violating the connotation of this specification, so this specification is not limited to the specific implementation disclosed below.

[0055] The terms used in one or more embodiments of this specification are only for the purpose of describing specific embodiments, and are not intended to limit one or more embodiments of this specification. The singular forms of "a", "said" and "the" used in one or more embodiments of this specification and the appended claims are also intended to include plural forms, unless the context clearly indicates other meanings. It should also be understood that the term "and / or" used in one or more embodiments of this specification refers to and includes any or all possible combinations of one or more associated listed items.

[0056] It should be understood that although the terms first, second, etc. may be used to describe various information in one or more embodiments of this specification, this information should not be limited to these terms. These terms are only used to distinguish the same type of information from each other. For example, without departing from the scope of one or more embodiments of this specification, the first may also be referred to as the second, and similarly, the second may also be referred to as the first. Depending on the context, the word "if" as used herein may be interpreted as "at the time of" or "when" or "in response to determining".

[0057] In addition, it should be noted that the user information (including but not limited to user device information, user personal information, etc.) and data (including but not limited to data used for analysis, stored data, displayed data, etc.) involved in one or more embodiments of this specification are all information and data authorized by the user or fully authorized by all parties, and the collection, use and processing of relevant data must comply with the relevant laws, regulations and standards of the relevant countries and regions, and provide corresponding operation entrances for users to choose to authorize or refuse.

[0058] First, the terms involved in one or more embodiments of this specification are explained.

[0059] Directional Pattern or Radiation Pattern is a graphical representation of the intensity distribution of electromagnetic waves radiated or received by an antenna in different directions in three-dimensional space. It shows how the antenna transmits or senses energy directionally in space and is a key parameter when evaluating antenna performance and designing antenna systems.

[0060] SOCP: Second-Order Cone Programming is a branch of convex optimization problems, which mainly deals with a special type of optimization problems, in which the objective function is a convex function and the constraints involve inequalities in the second-order cone.

[0061] In this specification, a method for optimizing the deployment of a frequency-invariant antenna array based on amplitude spectrum analysis is provided. This specification also relates to a device for optimizing the deployment of a frequency-invariant antenna array based on amplitude spectrum analysis, a computing device, and a computer-readable storage medium, which are described in detail one by one in the following embodiments.

[0062] See also Figure 1 , Figure 1 This is a flowchart of a method for optimizing the deployment of a frequency-invariant antenna array based on amplitude spectrum analysis provided by an embodiment of the present specification, which specifically includes the following steps.

[0063] Step 102: Acquire a virtual dense array consisting of a plurality of antenna units, and determine initial parameters of the virtual dense array.

[0064] Specifically, the antenna unit is the basic building block of the antenna array and is the smallest functional part of the antenna system that can independently radiate or receive electromagnetic waves. Each antenna unit has its own specific electromagnetic radiation characteristics, which can be designed individually or work in conjunction with other units to form the required radiation pattern or direction diagram.

[0065] Based on this, in the embodiments of this specification, the antenna array composed of multiple antenna units is a virtual dense array, and the virtual dense array is used to achieve different radiation performances.

[0066] See also Figure 2 , Figure 2 is a schematic diagram of an FIR filter network of a filter summation array of a frequency-invariant antenna array optimization method based on amplitude spectrum analysis provided by another embodiment of the present specification. In one embodiment of the present specification, a given virtual dense array is composed of N antenna units, and the arrangement position of the array elements is x. n =[-(N-1) / 2+n] T λ U / 8, each antenna unit of the virtual dense array is connected to a FIR filter with a length of L.

[0067] Furthermore, the method of obtaining a virtual dense array composed of multiple antenna units and determining initial parameters of the virtual dense array includes: obtaining the virtual dense array, determining an initial array pattern, an initial broadband excitation, and a space-time angular frequency corresponding to the virtual dense array; and using the initial array pattern, the initial broadband excitation, and the space-time angular frequency as the initial parameters.

[0068] Specifically, the initial array pattern reflects the radiation characteristics of the virtual dense array in the broadband frequency range and is the basis for antenna array design. The initial broadband excitation refers to the excitation amplitude and phase distribution of each antenna unit in the broadband frequency range, which determines the radiation pattern of the antenna array. The space-time angular frequency describes the characteristics of electromagnetic wave propagation in space and is of great significance for the design and optimization of antenna arrays.

[0069] Using the above example, after the virtual dense array is determined, the directivity pattern corresponding to the virtual dense array, that is, the initial array directivity pattern, can be expressed by equation (1), and the initial broadband excitation can be expressed by equation (2):

[0070]

[0071]

[0072] Where θ is the angle between the incoming wave direction and the array normal, c is the propagation speed of the wave in free space, h1,n is the lth coefficient of the nth FIR filter, Δ t is the time sampling interval. Obviously, and h1,n are a pair of Fourier transforms, and the form of excitation integrated with the single frequency array is similar, so H(f,n) can be regarded as broadband excitation. Because the virtual array satisfies Δ x =λ U / 8<λ U / 2, which can effectively avoid spatial aliasing.

[0073] For broadband array synthesis, f is a variable rather than a constant. Therefore, in the exponential term There are three variables, f, n and θ, while there are only two variables in the exponential term of Fourier transform. Therefore, the comprehensive problem of broadband directional pattern cannot be solved directly by Fourier transform. Variable substitution is also required to obtain the standard Fourier transform relationship.

[0074] The normalized space-time angular frequency can be obtained by the variable ζ = 2πfΔ x sinθ / c means that ζ increases with the frequency f, and its value range is [-2πfΔ x / c,2πfΔ x / c], if and only if f = f U and Δ x =λ U / 2, the maximum range is [-π,π].

[0075] The embodiments of this specification achieve a preliminary description and configuration of the antenna array by obtaining relevant parameters of the virtual dense array, which can provide effective data support for the subsequent optimization of the antenna array based on these initial parameters using the amplitude spectrum analysis method.

[0076] Step 104: construct a reference pattern based on the initial parameters, and determine an initial excitation of the reference pattern and expected index parameters of the virtual dense array.

[0077] Specifically, a reference pattern is constructed based on the initial parameters of the virtual dense array that have been obtained, as well as the design requirements and goals. This reference pattern may contain the radiation performance that the virtual dense array is expected to achieve under certain specific frequencies, directions or conditions. After the reference pattern is constructed, the initial excitation corresponding to the reference pattern is determined. The determination of the initial excitation is crucial to the subsequent optimization process, because it directly determines whether the radiation performance of the antenna array can approach or reach the requirements of the reference pattern. The expected indicator parameters are a series of quantitative indicators formulated based on the actual application environment and requirements of the antenna array. The expected indicator parameters include the expected sidelobe level and mainlobe FI beamwidth of the expected broadband-free pattern, the operating frequency band [fL, fU], the expected non-frequency-variant beamwidth, the designed sidelobe SLL and the expected null, and the mainlobe scanning pointing angle θlook and other parameters.

[0078] Furthermore, constructing a target broadband pattern based on the initial parameters includes: determining an intermediate broadband pattern based on the space-time angular frequency and the initial array pattern; sampling the space-time angular frequency at a preset sampling interval to obtain a target number of samples corresponding to the space-time angular frequency, and dimensionally expanding the initial broadband excitation according to the target number of samples to obtain an extended broadband excitation; updating the intermediate broadband pattern according to the extended broadband excitation to obtain a target broadband pattern; and constructing a reference pattern according to the operating frequency of the target broadband pattern.

[0079] Specifically, the intermediate broadband pattern is obtained by preliminary adjustment based on the initial array pattern and the space-time angular frequency, which reflects the approximate radiation characteristics of the antenna array within the broadband frequency range. In order to maintain dimensional consistency, the space-time angular frequency needs to be sampled, and the initial broadband excitation is dimensionally expanded according to the number of samples in the sampling result to obtain the extended broadband excitation. In this way, the extended broadband excitation contains more information about frequency and direction, and can more accurately describe the radiation performance of the antenna array within the broadband frequency range. Finally, the intermediate broadband pattern is updated according to the extended broadband excitation to obtain the target broadband pattern. The target broadband pattern is the radiation performance that the antenna array is ultimately expected to achieve within the broadband frequency range. The reference pattern is constructed based on the operating frequency of the target broadband pattern, which directly reflects the expected radiation performance of the antenna array at a specific frequency.

[0080] Using the above example, we can transform the space-time angular frequency ζ into m =-π+2πm / M Substituting into the initial array pattern equation (1), the intermediate broadband pattern obtained can be expressed by equation (3):

[0081]

[0082] To ζ m=-π+2πm / M for equally spaced sampling, where m = 0, 1, ..., M-1. Usually, the value of M is set to be much larger than N to obtain higher resolution. In order to keep the dimensions consistent, the initial broadband excitation needs to be expanded to M dimensions through zero-filling technology to obtain extended broadband excitation, that is, Substituting the extended broadband excitation into the intermediate pattern equation (3), the target broadband pattern obtained can be expressed by equation (4):

[0083]

[0084] where θ = arcsincζ if and only if m / 2πfΔ x And |ζ m |≤2πfΔ x / c, F ζ (f,ζ m )=F(f,θ) holds. In summary, {F ζ (f,ζ m ); m = 0, 1, ... M-1} can be regarded as the distribution of broadband directional patterns in the space spectrum domain. Obviously, if the desired {F ζ (f,ζ m )} Spatial spectrum distribution, you can perform an IDFT, split according to the array element index, and you can get the required broadband excitation

[0085] To avoid the super-directivity of the comprehensive target broadband pattern at low frequencies, the reference pattern should be L The electrical dimensions of the target broadband pattern are satisfied, and the electrical dimensions at high frequencies can certainly meet the requirements of the reference pattern. Therefore, at the lowest frequency f of the target broadband pattern, L For the i-th subband, the required reference pattern is defined by equation (5):

[0086]

[0087] Generated reference pattern excitation It can be obtained through mature single-frequency synthesis technology. In order to save the design time of the reference pattern and improve the overall algorithm efficiency, the reference pattern is obtained by iterative fast Fourier transform synthesis. Select an initial excitation from the reference pattern excitation

[0088] The embodiments of this specification provide clear goals and basis for the subsequent optimization process by constructing a reference pattern and determining its initial excitation and the expected index parameters of the virtual dense array, which will help to complete the optimization design of the antenna array more efficiently and accurately.

[0089] Step 106: constructing a spatial spectrum distribution based on the initial excitation and the expected indicator parameters, and selecting a target antenna unit in the virtual dense array according to amplitude spectrum information corresponding to the spatial spectrum distribution.

[0090] Specifically, based on the determined initial excitation and expected indicator parameters, such as the expected sidelobe level, main lobe beamwidth, operating frequency band, etc., a spatial spectrum distribution can be constructed. This spatial spectrum distribution describes how the radiation intensity of the antenna array should be distributed at different frequencies and directions. In order to achieve this spatial spectrum distribution, it is necessary to select target antenna elements in the virtual dense array according to their corresponding amplitude spectrum information. These target antenna elements will be responsible for generating the desired radiation intensity at specific frequencies and directions. The process of selecting the target antenna element usually involves evaluating each possible antenna element in the virtual dense array to see if it can meet the amplitude requirements of the spatial spectrum distribution at specific frequencies and directions.

[0091] Furthermore, constructing a spatial spectrum distribution based on the initial excitation and the expected index parameters includes: determining an expected sidelobe level and an expected mainlobe FI beamwidth of the initial excitation; dimensionally expanding the initial excitation by a zero-filling rule to obtain a target excitation, and calculating the target excitation using an iterative fast Fourier transform single-frequency synthesis algorithm to obtain a subband reference pattern; correcting the sidelobe level and the mainlobe FI beamwidth of the subband reference pattern according to the expected sidelobe level and the expected mainlobe FI beamwidth to obtain a target subband reference pattern, wherein the phase of the subband reference pattern remains unchanged; determining a target subband excitation of the target subband reference pattern, and determining the spatial spectrum distribution according to the target subband excitation.

[0092] Specifically, the expected sidelobe level and the expected mainlobe FI beamwidth of the initial excitation are determined. These parameters determine the radiation performance of the optimized array. Then, in order to make the dimensions consistent, the initial excitation is dimensionally expanded using the zero-filling technique to obtain the target excitation. Then, the target excitation is calculated using the iterative fast Fourier transform single-frequency synthesis algorithm to obtain the sub-band reference pattern, which describes the radiation characteristics of the antenna array in a certain sub-band. However, since the initial excitation may not fully meet the requirements of the expected indicator parameters, the sub-band reference pattern needs to be corrected.

[0093] The correction process mainly includes two aspects: first, adjusting the sidelobe level to reach the desired sidelobe level value; second, adjusting the mainlobe FI beamwidth to meet the desired mainlobe FI beamwidth requirements. In this process, the phase of the sub-band reference pattern is kept unchanged, and only its amplitude is adjusted. After correction, the target sub-band reference pattern is obtained.

[0094] Finally, the target subband excitation can be determined based on the target subband reference pattern. This target subband excitation is the array excitation required to achieve the target subband reference pattern. Through the target subband excitation, the entire spatial spectrum distribution can be determined. This spatial spectrum distribution is the basis and goal of the subsequent optimization process.

[0095] Using the above example, after selecting an initial excitation from the reference pattern excitation, set the desired sidelobe level and the desired mainlobe FI beamwidth. Use the zero-filling technique to fill the initial excitation Expand from N points to M points, that is, fill (MN) zeros to get the target excitation; use the FFT of M points to get the expanded target excitation Calculate the subband reference pattern According to the requirements of the reference pattern, i.e. the expected sidelobe level and the expected mainlobe FI beamwidth, the correction The main lobe and side lobe parts of the subband are corrected, the main lobe beam width and side lobe level are corrected, and the subband reference pattern The phase of remains unchanged, and the target subband reference pattern is obtained.

[0096] Use a rectangular window to reduce the dimension of the target stimulus and cut it off. Cut off from point M to point N;

[0097] By following the above steps and setting the same main lobe and side lobe requirements for different sub-bands, we can get a set of target sub-band excitations corresponding to the required reference patterns. By obtaining the target subband excitation That is, the desired spatial spectrum distribution can be obtained, which can be expressed by formula (6):

[0098]

[0099] Among them, for the i-th sub-band, the frequency range is

[0100] The embodiments of this specification implement the optimal configuration of the antenna array by constructing the spatial spectrum distribution and selecting the target antenna unit in the virtual dense array. This method can not only improve the radiation performance of the antenna array, but also reduce the design cost and time, providing strong support for the application of various communication and radar systems.

[0101] Furthermore, in order to reduce the density of array elements in the virtual dense array, the target antenna unit is selected in the virtual dense array according to the amplitude spectrum information corresponding to the spatial spectrum distribution, including: performing an inverse Fourier transform on the spatial spectrum distribution to obtain a target broadband excitation corresponding to the virtual dense array, performing dimensionality reduction processing on the target broadband excitation to obtain a reduced dimension matrix; selecting multiple first target array elements from the reduced dimension matrix, clustering the remaining array elements in the reduced dimension matrix except the multiple first target array elements, and determining multiple second target array elements according to the clustering results; and using the first target array elements and the second target array elements as target antenna units.

[0102] Specifically, performing an inverse Fourier transform on the spatial spectrum distribution is the process of converting the spatial radiation intensity distribution into array excitation. This step is to convert from the frequency domain to the time domain, so as to obtain the excitation distribution that the virtual dense array should have in the broadband range. Since the virtual dense array contains a large number of array elements, directly optimizing it will be very time-consuming and computationally intensive. Therefore, it is necessary to perform dimensionality reduction processing to reduce the number of array elements that need to be optimized.

[0103] The specific method of dimensionality reduction processing can be to use a certain criterion or algorithm to screen or merge the target broadband excitation to obtain a reduced dimension matrix. This reduced dimension matrix contains the excitation information of a part of the array elements in the original virtual dense array, but the number is greatly reduced, thereby reducing the complexity of the subsequent optimization process.

[0104] Next, multiple first target array elements are selected from the dimensionality reduction matrix. These first target array elements are representative array elements selected according to certain criteria. Their excitation will be directly used in the subsequent optimization process. Clustering is performed on the remaining array elements in the dimensionality reduction matrix except the first target array element. Clustering is an unsupervised learning method used to divide data into several groups or clusters so that the data in the same cluster is as similar as possible, while the data between different clusters are as different as possible. Here, clustering is used to group the remaining array elements according to a certain similarity criterion, and the array elements in each group have similar excitation characteristics. Multiple second target array elements are determined based on the clustering results. These second target array elements are representative array elements selected from each cluster, and their excitation will represent the excitation of the array elements in the entire cluster. By selecting the first target array element and the second target array element as the target antenna unit, the density of the array elements in the virtual dense array can be greatly reduced while maintaining the performance of the antenna array, thereby reducing the computational burden of the subsequent optimization process.

[0105] Finally, the first target array element and the second target array element are used as target antenna units for the subsequent antenna array optimization process. This method can effectively reduce the design cost and time and improve the efficiency of the optimization process while ensuring the performance of the antenna array.

[0106] Following the above example, we perform M-point IDFT on the constructed spatial spectrum distribution and truncate the result to N dimensions using a rectangular window to obtain the target broadband excitation of the virtual dense array. It can be rewritten into matrix form W A , with a dimension of N×J, where N is the number of array elements and J is the number of frequency sampling points in the target frequency band. In this embodiment, the broadband excitation matrix W A It is called the amplitude spectrum and is expressed by equation (7):

[0107]

[0108] Obviously, the amplitude spectrum W A It is a rank-deficient matrix with decreasing singular values ​​of size N×J. The PCA algorithm can be used for frequency dimensionality reduction and obtain a dimensionality reduction matrix W that retains the main characteristics of the amplitude spectrum distribution. R , the dimension reduction matrix W R It can be expressed by equation (8) and equation (9):

[0109]

[0110]

[0111] in It is W A The standardized matrix of W A The autocorrelation matrix of corresponds to a J×L matrix consisting of L eigenvectors of the largest L eigenvalues, and L is much smaller than J. Select the amplitude spectrum W A The selection of principal component features satisfies the total cumulative contribution rate 0.6<α<1 and satisfies the condition of formula (10):

[0112]

[0113] After the dimension reduction, the new amplitude spectrum distribution matrix W is obtained. R Finally, the array elements of the densely arranged virtual array are selected to form a new sparsely distributed array, that is, the target non-uniform array.

[0114] First, from the dimension reduction matrix W R Select the first antenna unit from the set S K1 .

[0115] Then, for the remaining set The dimension-reduced amplitude spectrum W can be R according to The matrix consisting of row vectors corresponding to the element subscripts Using clustering algorithms, The array elements in the new cluster are divided into K2 clusters. The array elements contained in the new clusters have similar characteristics: similar amplitude spectrum graphs with frequency transformation.

[0116] For this purpose, the K-means clustering algorithm was selected to perform the above work. The K-means algorithm clusters (N-K1) array elements into K2 clusters. A larger K2 value will make the sum of the distances from the points in each cluster to the centroid smaller, which means that the error between the directional pattern of the final sparse array and the directional pattern of the virtual array is closely related to the value of K2. A larger K2 value will result in a smaller comprehensive error. Therefore, when setting K2 in practice, it should be as large as possible to meet the desired reference directional pattern tolerance. In each cluster, one or several representative array elements closest to the centroid of the cluster will be selected and added to the set S. K2 If the initial virtual array is very dense, the difference between the centroids of the representative elements and clusters will be very small. On the one hand, the initial virtual array can be set to a very large scale to meet the needs of large-scale arrays; on the other hand, too many virtual elements will significantly increase the computational overhead of the amplitude spectrum analysis and element selection stages, which needs to be weighed.

[0117] Furthermore, in order to make the selected first target array element more representative, the selection of the first target array element will focus on the following two aspects: one is the energy contribution to the amplitude spectrum, and the other is a smaller FI pattern comprehensive error. The selecting of multiple first target array elements from the reduced dimension matrix includes: determining the contribution score of each array element in the reduced dimension matrix relative to the target broadband excitation, and the FI pattern comprehensive error information corresponding to each array element; selecting multiple first target array elements in the reduced dimension matrix according to the contribution score of each array element and the FI pattern comprehensive error information.

[0118] Specifically, the energy contribution of each array element in the reduced dimension matrix to the target broadband excitation is calculated. At the same time, in order to ensure that the selected first target array element can reconstruct the original pattern as accurately as possible, the FI pattern comprehensive error corresponding to each array element needs to be calculated. This can be achieved by substituting the excitation distribution of each array element into the far-field pattern calculation formula of the antenna array and calculating the error between the obtained pattern and the expected pattern.

[0119] Using the above example, construct the first set based on the selected first target antenna unit is a spectrum containing the reduced-dimensional amplitude spectrum W R The set of K1 array element subscripts with the strongest energy span. The energy span of an array element is defined as the sum of the absolute values ​​of the amplitude of the array element in the amplitude spectrum over the frequency range of the array element across the entire target frequency band. Here, the reduced-dimensional amplitude spectrum matrix is ​​used to calculate the energy span of each array element:

[0120] ε i =||W R (i,:)||2,i=1,…,N

[0121] The maximum value of the virtual array energy span is defined as follows:

[0122] ε max =max(ε i ),i=1,…,N

[0123] Therefore, the set In the process, the array elements with energy span greater than a certain threshold will be selected.

[0124]

[0125] The remaining elements in the virtual array can form a set

[0126]

[0127] Where 0<β<1 is a specified frequency span factor. If β approaches 0, more array elements will be selected from the virtual array, which means that the final sparse array will be very close to the dense virtual array set initially; if β approaches 1, the final target non-uniform array will be composed of the most critical array elements in the virtual array.

[0128] The first target array element selected by the above method in the embodiment of this specification not only has a large energy contribution, but also can reconstruct the original directional pattern more accurately, thereby ensuring the performance of the final antenna array. At the same time, due to the use of dimensionality reduction processing and clustering algorithms, the number of array elements that need to be optimized is greatly reduced, the computational complexity is reduced, and the efficiency of the optimization process is improved.

[0129] Step 108: constructing a target non-uniform array according to the target antenna unit, wherein the target non-uniform array meets a preset antenna radiation condition.

[0130] Specifically, the target antenna unit includes a first target antenna unit and a second target antenna unit, a first set is constructed by the first target antenna unit, a second set is constructed by the second target antenna unit, and a union of the first set and the second set is used as the target non-uniform array. The preset antenna radiation condition refers to the radiation performance that the target non-uniform array is expected to achieve.

[0131] Using the above example, the element subscripts of the selected target non-uniform array can be represented by the set S K To express.

[0132]

[0133] The embodiments of this specification construct a target non-uniform array by selecting key antenna elements in a virtual dense array to meet the preset antenna radiation conditions. In this process, not only the energy contribution of the array element is considered, but also the influence of the array element on the comprehensive error of the pattern is combined to ensure that the performance of the sparse array is close to or even better than the original dense array.

[0134] Furthermore, after constructing the target non-uniform array according to the target antenna unit, it also includes: calculating the target coefficient of the filter corresponding to the target non-uniform array through a convex optimization solution algorithm; and determining the expected waveform corresponding to the target non-uniform array by configuring the filter of the target coefficient.

[0135] Specifically, after determining the target non-uniform array, it is necessary to further design the filter corresponding to each element in the array to ensure that the overall performance of the array meets expectations. In this step, a convex optimization solution algorithm will be used to calculate the target coefficients of the filter corresponding to the target non-uniform array. Convex optimization is a powerful mathematical tool that can find the optimal solution under given constraints.

[0136] Using the above example, through the above steps, the target non-uniform array can be effectively constructed, and the desired waveform can be achieved by optimizing the filter coefficients. This method is not only highly flexible and scalable, but also ensures that the performance of the final array is optimal.

[0137] After designing the reference pattern and sparse array, the SOCP-FIB synthesis technology in equation (11) can be used to optimize the broadband excitation H(f,n).

[0138]

[0139] The FI beamforming problem is actually equivalent to designing a set of FIR filter coefficients so that its frequency response H(f,n) is the same as the element weight value of broadband beamforming at the corresponding discrete frequency point. It can be seen that designing FIR filter coefficients with the desired frequency response is the key to the FI beamforming problem.

[0140] Assume that a FIR filter of length L has an impulse response:

[0141] h=[h(1),…,h(l),…h(L)] T

[0142] The complex frequency response of the filter can be expressed as:

[0143]

[0144] Among them, f s is the sampling frequency, and the sampling period is Δt =1 / f s Assume that the expected frequency response of the FIR filter at frequency f is H d (f), then the error norm between the designed filter and the desired filter can be expressed as:

[0145] δ q =(∫ F λ(f)|e T (f)hH d (f)| q df) 1 / q

[0146] Where F = [0,f s / 2] represents the full frequency band, λ(f) is a non-negative error weighting function, which is used to adjust the fitting tightness of different frequencies. The larger the relative weight, the higher the accuracy of the final filter coefficient at that frequency. When q=∞,1,2, the corresponding error norms are l ∞ norm, l1 norm and l2 norm.

[0147] Discretization of the continuous frequency of the filter, assuming that the sampling points on the frequency are f1,…,f k ,…,f K , where f k ∈F,k=1,2,…K. Assume that the filter is at frequency f k The expected response is H d (f k ). The norm of the frequency response error between the desired filter and the designed filter can be expressed as formula (12):

[0148]

[0149] Where λ=[λ1,…,λ k ,…,λ K ] is a non-negative error weighting factor; the designed filter frequency response is H d =[H d (f1),…,H d (f k ),…,H d (f K )], and the other is the desired frequency response.

[0150] Similar to the continuous case, the optimal filter with different approximation criteria can be obtained by minimizing different norms. The l2 norm formula (13) is used to solve the optimal design problem of FIR filter.

[0151]

[0152] In the formula, F PBIt is the pre-specified target broadband frequency range, which corresponds to the passband in time domain signal processing in the FIR filter. SB is the stopband, and δ0 is the upper limit of the error within the given stopband range. Obviously, this optimization problem can be solved using SOCP, and the CVX algorithm package can efficiently solve this type of optimization problem.

[0153] The present invention divides the solution of the optimal array structure and FIR filter coefficients into two steps. In the first step, the reference pattern and weight spectrum are obtained by iterative Fourier transform of a virtual dense uniform array, and then the key antenna units are determined by weight spectrum analysis. The K-means clustering algorithm is applied to divide the units into different clusters, and the representative array elements of each cluster are selected to form a new non-uniformly spaced array. In the second step, the present invention uses SOCP technology to design the corresponding finite impulse response (FIR) filter coefficients to ensure that the frequency response of the filter is close to the weight of the antenna unit. A new non-uniform array can be obtained while maintaining the FI characteristics of the target pattern, and the comprehensive pattern can be scanned, which has significant advantages in computational cost.

[0154] The specific implementation of the antenna array non-frequency-variant broadband pattern synthesis method based on amplitude spectrum analysis proposed in the embodiments of this specification can be further given by the following simulation examples and results:

[0155] In the simulation example, the proposed method is used in electromagnetic applications to synthesize FI patterns with uniform SLL. It is assumed that the desired broadband pattern in the frequency band f∈[0.4,1.2]GHz maintains the FI characteristics over |θ|≤18°. For the sidelobe region |θ|>18°, the upper bound of the desired SLL is set to Γ SL =-16dB. The initial number of virtual array elements is N = 100, and the element spacing is Δ x =λ u / 8, wave speed c = 3 × 10 8 m / s, each array element is connected to a FIR filter with a length of L = 25. The main lobe beam is constructed using the Chebyshev pattern, and the side lobe is composed of Γ SL Simple setting, β = 0.9, K2 = 5 groups. In each cluster, a representative element closest to the cluster centroid is selected.

[0156] The optimized sparse array layout with a half-wavelength sparsity rate of 60% is as follows: Figure 3 As shown, Figure 3 is a schematic diagram of the array element layout of a target non-uniform linear array of a frequency-invariant antenna array optimization method based on amplitude spectrum analysis provided by another embodiment of the present specification. The FI directional pattern obtained by synthesis is as follows Figure 4 and Figure 5 As shown, Figure 4It is a schematic diagram of spatial spectrum distribution of FI directional pattern containing uniform SLL in a frequency-invariant antenna array optimization method based on amplitude spectrum analysis provided by another embodiment of this specification; Figure 5 Another embodiment of the present specification provides a method for optimizing the arrangement of a frequency-invariant antenna array based on amplitude spectrum analysis, which includes a broadband discrete frequency FI pattern having a uniform SLL.

[0157] It can be seen that within the target broadband frequency band of frequency f∈[0.4,1.2]GHz, FNBW satisfies |θ|≤18°, the beamwidth that meets the sidelobe SLL level requirement is |θ|≤17.36°, and the radiation pattern satisfies the Γ set within |θ|>18°. SL , the frequency-invariant factor σ = 0.23 dB, which fully verifies the effectiveness of the proposed method. As the frequency increases, the first zero point also moves inward, but it still meets the requirement of the main lobe beamwidth |θ| ≤ 18°.

[0158] The method provided in the embodiment of this specification is used to design the FIR filter coefficients. The filter coefficient distribution obtained in the end and the expected and designed frequency responses of the FIR filter corresponding to the second array element of the non-uniform array are shown in Figure 5 and Figure 6 , Figure 6 It is a schematic diagram of the distribution of normalized filter coefficients hl,n of a frequency-invariant antenna array optimization method based on amplitude spectrum analysis provided by another embodiment of the present specification; Figure 7 It is a schematic diagram of the expected and designed frequency responses of the FIR filter of the second array element of a frequency-invariant antenna array optimization method based on amplitude spectrum analysis provided by another embodiment of the present specification.

[0159] The embodiments of this specification provide a non-uniform sparse array design method based on dimensionality reduction processing and clustering algorithm, which can effectively reduce the complexity and cost of the antenna array while maintaining or even improving the radiation performance of the antenna array. By selecting key antenna units in a virtual dense array to construct a target non-uniform sparse array, an antenna array that meets specific application requirements can be obtained. And by calculating the coefficients of the corresponding FIR filter, broadband beamforming is achieved, ensuring that the array has stable performance in a wide frequency band.

[0160] Figure 8 This is a flowchart of a method for optimizing the arrangement of a frequency-invariant antenna array based on amplitude spectrum analysis provided by another embodiment of this specification. Figure 8 , the non-frequency-variant antenna array optimization method based on amplitude spectrum analysis is further described 8, which specifically includes the following steps.

[0161] Step 802: Given various parameters of the virtual dense array, various performance parameter indicators of the broadband directional pattern are preset.

[0162] Step 804: Select a suitable starting excitation, use iterative Fourier transform synthesis method to construct the required spatial spectrum distribution, obtain the amplitude spectrum by IDFT, and perform amplitude spectrum analysis.

[0163] Among them, the IDFT (Inverse Discrete Fourier Transform) method is used for the spatial spectrum distribution to obtain the amplitude spectrum, and then the amplitude spectrum is analyzed.

[0164] Step 806: Is it determined whether the energy span is greater than the preset threshold εmax?

[0165] If yes, it means that the energy span is greater than εmax, and step 808 is executed. If no, it means that the energy span is less than εmax, and step 810 is executed. The energy span refers to the energy span of the array element in the reduced dimension matrix obtained after the amplitude spectrum is reduced in dimension.

[0166] Step 808: Construct a first set.

[0167] Add the array elements with energy span greater than εmax to the first set middle.

[0168] Step 810: Construct a second set.

[0169] The remaining elements in the reduced-dimensional matrix whose energy span is less than εmax Perform K-means cluster analysis and obtain the second set based on the analysis results

[0170] Step 812: Perform SOCP-FIB solution on the sparse array to obtain broadband excitation.

[0171] The sparse array is composed of the first set and the second set The sparse array obtained by taking the union has the same meaning as the target non-uniform array in the previous embodiment.

[0172] Step 814: Convex optimization to solve the FIR filter coefficients.

[0173] Each element in the sparse array is connected to a FIR filter.

[0174] Step 816: Output array layout, broadband pattern and filter coefficients.

[0175] The embodiment of this specification constructs a new sparse array based on the original virtual dense array. The sparse array can maintain the radiation performance of the array on the basis of reducing the density, reducing the cost of the communication system and the difficulty of array implementation, and uses SOCP technology to design the corresponding finite impulse response (FIR) filter coefficients to ensure that the frequency response of the filter is close to the weight of the antenna unit. A new non-uniform array can be obtained while maintaining the FI characteristics of the target pattern, and the comprehensive pattern can be scanned, which has a significant advantage in computing cost.

[0176] Corresponding to the above method embodiment, this specification also provides an embodiment of a non-frequency-variant antenna array optimization arrangement device based on amplitude spectrum analysis, Fig. 9 FIG. 1 is a schematic diagram showing a structure of a non-frequency-variant antenna array optimization arrangement device based on amplitude spectrum analysis provided by an embodiment of the present specification. Fig. 9 As shown, the device comprises:

[0177] The data acquisition module 902 is configured to acquire a virtual dense array composed of a plurality of antenna units and determine initial parameters of the virtual dense array;

[0178] A reference pattern construction module 904 is configured to construct a reference pattern based on the initial parameters, and determine an initial excitation of the reference pattern and expected index parameters of the virtual dense array;

[0179] An array element selection module 906 is configured to construct a spatial spectrum distribution based on the initial excitation and the expected indicator parameter, and select a target antenna element in the virtual dense array according to amplitude spectrum information corresponding to the spatial spectrum distribution;

[0180] The target array construction module 908 is configured to construct a target non-uniform array according to the target antenna unit, wherein the target non-uniform array meets a preset antenna radiation condition.

[0181] Optionally, the data acquisition module includes:

[0182] The classification acquisition submodule is configured to acquire a virtual dense array, determine an initial array pattern, an initial broadband excitation, and a space-time angular frequency corresponding to the virtual dense array; and use the initial array pattern, the initial broadband excitation, and the space-time angular frequency as the initial parameters.

[0183] Optionally, the reference pattern construction module includes:

[0184] A broadband pattern determination submodule, configured to determine an intermediate broadband pattern based on the space-time angular frequency and the initial array pattern;

[0185] A dimensional expansion submodule is configured to sample the space-time angular frequency according to a preset sampling interval to obtain a target number of samples corresponding to the space-time angular frequency, and perform dimension expansion on the initial broadband excitation according to the target number of samples to obtain an expanded broadband excitation;

[0186] A target broadband directional pattern construction submodule is configured to update the intermediate broadband directional pattern according to the extended broadband excitation to obtain a target broadband directional pattern;

[0187] The reference directional pattern construction submodule is configured to construct the reference directional pattern according to the operating frequency of the target broadband directional pattern.

[0188] Optionally, the array element selection module includes:

[0189] An expected data determination submodule, configured to determine an expected sidelobe level and an expected mainlobe FI beamwidth of the initial excitation;

[0190] The sub-band reference pattern determination sub-module is configured to perform dimension expansion on the initial excitation by a zero-filling rule to obtain a target excitation, and to calculate the sub-band reference pattern on the target excitation by using an iterative fast Fourier transform single-frequency synthesis algorithm;

[0191] A sub-band reference pattern correction submodule is configured to correct the sidelobe level and the main lobe FI beamwidth of the sub-band reference pattern according to the expected sidelobe level and the expected main lobe FI beamwidth to obtain a target sub-band reference pattern, wherein the phase of the sub-band reference pattern remains unchanged;

[0192] The spatial spectrum distribution determination submodule is configured to determine a target subband excitation of the target subband reference pattern, and determine the spatial spectrum distribution according to the target subband excitation.

[0193] Optionally, the array element selection module includes:

[0194] A dimensionality reduction processing submodule is configured to perform an inverse Fourier transform on the spatial spectrum distribution to obtain a target broadband excitation corresponding to the virtual dense array, and perform dimensionality reduction processing on the target broadband excitation to obtain a reduced dimensionality matrix;

[0195] A first array element selection submodule is configured to select a plurality of first target array elements from the dimension reduction matrix, perform clustering processing on the remaining array elements in the dimension reduction matrix except the plurality of first target array elements, and determine a plurality of second target array elements according to the clustering result;

[0196] The second array element selection submodule is configured to use the first target array element and the second target array element as target antenna units.

[0197] Optionally, the first array element selection submodule includes:

[0198] An information determination submodule, configured to determine a contribution score of each array element in the dimension reduction matrix relative to the target broadband excitation, and comprehensive error information of the FI pattern corresponding to each array element;

[0199] The array element selection submodule is configured to select a plurality of first target array elements in the dimension reduction matrix according to the contribution score of each array element and the FI directional pattern comprehensive error information.

[0200] Optionally, the frequency-invariant antenna array optimization arrangement device based on amplitude spectrum analysis further includes:

[0201] A filter coefficient solving module is configured to calculate the target coefficients of the filter corresponding to the target non-uniform array by a convex optimization solving algorithm;

[0202] The expected model determination submodule is configured to determine the expected waveform corresponding to the target non-uniform array by configuring the filter of the target coefficients.

[0203] The above is a schematic scheme of a non-frequency-variant antenna array optimization arrangement device based on amplitude spectrum analysis of this embodiment. It should be noted that the technical scheme of the non-frequency-variant antenna array optimization arrangement device based on amplitude spectrum analysis and the technical scheme of the non-frequency-variant antenna array optimization arrangement method based on amplitude spectrum analysis belong to the same concept. For details not described in detail in the technical scheme of the non-frequency-variant antenna array optimization arrangement device based on amplitude spectrum analysis, please refer to the description of the technical scheme of the non-frequency-variant antenna array optimization arrangement method based on amplitude spectrum analysis.

[0204] Fig.10 The block diagram of a computing device 1000 according to an embodiment of the present specification is shown. The components of the computing device 1000 include but are not limited to a memory 1010 and a processor 1020. The processor 1020 is connected to the memory 1010 via a bus 1030, and the database 1050 is used to store data.

[0205] The computing device 1000 also includes an access device 1040 that enables the computing device 1000 to communicate via one or more networks 1060. Examples of these networks include a public switched telephone network (PSTN), a local area network (LAN), a wide area network (WAN), a personal area network (PAN), or a combination of communication networks such as the Internet. The access device 1040 may include one or more of any type of network interface (e.g., a network interface card (NIC)) of wired or wireless, such as an IEEE 802.11 wireless local area network (WLAN) wireless interface, a world-wide interoperability for microwave access (Wi-MAX) interface, an Ethernet interface, a universal serial bus (USB) interface, a cellular network interface, a Bluetooth interface, and a near field communication (NFC).

[0206] In one embodiment of the present specification, the above components of the computing device 1000 and Fig.10 Other components not shown in the figure may also be connected to each other, for example, via a bus. It should be understood that Fig.10 The computing device structure block diagram shown is only for the purpose of illustration, and is not intended to limit the scope of this specification. Those skilled in the art can add or replace other components as needed.

[0207] The computing device 1000 may be any type of stationary or mobile computing device, including a mobile computer or mobile computing device (e.g., a tablet computer, a personal digital assistant, a laptop computer, a notebook computer, a netbook, etc.), a mobile phone (e.g., a smart phone), a wearable computing device (e.g., a smart watch, smart glasses, etc.), or other types of mobile devices, or a stationary computing device such as a desktop computer or a personal computer (PC). The computing device 1000 may also be a mobile or stationary server.

[0208] The processor 1020 is used to execute the following computer program / instruction, which, when executed by the processor, implements the steps of the above-mentioned frequency-invariant antenna array optimization method based on amplitude spectrum analysis.

[0209] Each embodiment in this specification is described in a progressive manner, and the same or similar parts between the embodiments can be referred to each other, and each embodiment focuses on the differences from other embodiments. In particular, for the computing device embodiment, since it is basically similar to the embodiment of the non-frequency-variant antenna array optimization method based on amplitude spectrum analysis, the description is relatively simple, and the relevant parts can be referred to the partial description of the embodiment of the non-frequency-variant antenna array optimization method based on amplitude spectrum analysis.

[0210] An embodiment of the present specification also provides a computer-readable storage medium storing a computer program / instruction, which, when executed by a processor, implements the steps of the above-mentioned method for optimizing the arrangement of a frequency-invariant antenna array based on amplitude spectrum analysis.

[0211] Each embodiment in this specification is described in a progressive manner, and the same or similar parts between the embodiments can be referred to each other, and each embodiment focuses on the differences from other embodiments. In particular, for the computer-readable storage medium embodiment, since it is basically similar to the embodiment of the non-frequency-variant antenna array optimization method based on amplitude spectrum analysis, the description is relatively simple, and the relevant parts can be referred to the partial description of the embodiment of the non-frequency-variant antenna array optimization method based on amplitude spectrum analysis.

[0212] An embodiment of the present specification also provides a computer program product, including a computer program / instruction, which, when executed by a processor, implements the steps of the above-mentioned method for optimizing the arrangement of a frequency-invariant antenna array based on amplitude spectrum analysis.

[0213] The above is a schematic scheme of a computer program product of this embodiment. It should be noted that the technical scheme of the computer program product and the technical scheme of the above-mentioned non-frequency-variant antenna array optimization method based on amplitude spectrum analysis belong to the same concept, and the details not described in detail in the technical scheme of the computer program product can be referred to the description of the technical scheme of the above-mentioned non-frequency-variant antenna array optimization method based on amplitude spectrum analysis.

[0214] The above is a description of a specific embodiment of the specification. Other embodiments are within the scope of the appended claims. In some cases, the actions or steps recorded in the claims can be performed in an order different from that in the embodiments and still achieve the desired results. In addition, the processes depicted in the drawings do not necessarily require the specific order or continuous order shown to achieve the desired results. In some embodiments, multitasking and parallel processing are also possible or may be advantageous.

[0215] The computer instructions include computer program codes, which may be in source code form, object code form, executable files or some intermediate forms, etc. The computer-readable medium may include: any entity or device capable of carrying the computer program code, recording medium, USB flash drive, mobile hard disk, magnetic disk, optical disk, computer memory, read-only memory (ROM), random access memory (RAM), electric carrier signal, telecommunication signal and software distribution medium, etc. It should be noted that the content contained in the computer-readable medium may be appropriately increased or decreased according to the requirements of patent practice. For example, in some regions, according to patent practice, computer-readable media do not include electric carrier signals and telecommunication signals.

[0216] It should be noted that, for the above-mentioned method embodiments, for the sake of simplicity of description, they are all expressed as a series of action combinations, but those skilled in the art should be aware that the embodiments of this specification are not limited by the order of the actions described, because according to the embodiments of this specification, some steps can be performed in other orders or simultaneously. Secondly, those skilled in the art should also be aware that the embodiments described in the specification are all preferred embodiments, and the actions and modules involved are not necessarily required by the embodiments of this specification.

[0217] In the above embodiments, the description of each embodiment has its own emphasis. For parts that are not described in detail in a certain embodiment, reference can be made to the relevant descriptions of other embodiments.

[0218] The preferred embodiments of this specification disclosed above are only used to help explain this specification. The optional embodiments do not describe all the details in detail, nor do they limit the invention to only the specific implementation methods described. Obviously, many modifications and changes can be made according to the content of the embodiments of this specification. This specification selects and specifically describes these embodiments in order to better explain the principles and practical applications of the embodiments of this specification, so that technicians in the relevant technical field can well understand and use this specification. This specification is only limited by the claims and their full scope and equivalents.

Claims

1. A method for optimizing the layout of a frequency-invariant antenna array based on amplitude spectrum analysis, characterized in that: include: Acquire a virtual dense array composed of multiple antenna units, and determine initial parameters of the virtual dense array, wherein the initial parameters include an initial array pattern, an initial broadband excitation, and a space-time angular frequency; Constructing a reference pattern based on the initial parameters, and determining an initial excitation of the reference pattern and expected index parameters of the virtual dense array; Constructing a spatial spectrum distribution based on the initial excitation and the expected index parameter, and selecting a target antenna unit in the virtual dense array according to amplitude spectrum information corresponding to the spatial spectrum distribution; constructing a target non-uniform array according to the target antenna unit, wherein the target non-uniform array satisfies a preset antenna radiation condition; The constructing a reference directional pattern based on the initial parameters comprises: Determining an intermediate broadband pattern based on the space-time angular frequency and the initial array pattern; Sampling the space-time angular frequency according to a preset sampling interval to obtain a target number of samples corresponding to the space-time angular frequency, and dimensionally expanding the initial broadband excitation according to the target number of samples to obtain an extended broadband excitation; Update the intermediate broadband directional pattern according to the extended broadband excitation to obtain a target broadband directional pattern; The reference directional pattern is constructed according to the operating frequency of the target broadband directional pattern.

2. The method according to claim 1, characterized in that The step of obtaining a virtual dense array formed by a plurality of antenna units and determining initial parameters of the virtual dense array includes: Acquire a virtual dense array, and determine an initial array pattern, an initial broadband excitation, and a space-time angular frequency corresponding to the virtual dense array; The initial array pattern, the initial broadband excitation and the space-time angular frequency are used as the initial parameters.

3. The method according to claim 1, characterized in that The constructing of a spatial spectrum distribution based on the initial excitation and the expected index parameter comprises: Determining the desired sidelobe level and the desired mainlobe FI beamwidth of the initial excitation; The initial excitation is dimensionally expanded by a zero-filling rule to obtain a target excitation, and a sub-band reference pattern is calculated by an iterative fast Fourier transform single-frequency synthesis algorithm for the target excitation; According to the expected sidelobe level and the expected mainlobe FI beamwidth, the sidelobe level and the mainlobe FI beamwidth of the subband reference pattern are corrected to obtain a target subband reference pattern, wherein the phase of the subband reference pattern remains unchanged; A target sub-band excitation of the target sub-band reference pattern is determined, and the spatial spectrum distribution is determined according to the target sub-band excitation.

4. The method according to claim 1, characterized in that: The selecting a target antenna unit in the virtual dense array according to the amplitude spectrum information corresponding to the spatial spectrum distribution includes: Performing an inverse Fourier transform on the spatial spectrum distribution to obtain a target broadband excitation corresponding to the virtual dense array, and performing dimensionality reduction processing on the target broadband excitation to obtain a dimensionality reduction matrix; Selecting a plurality of first target array elements from the dimension reduction matrix, performing clustering processing on the remaining array elements in the dimension reduction matrix except the plurality of first target array elements, and determining a plurality of second target array elements according to the clustering result; The first target array element and the second target array element are used as target antenna units.

5. The method according to claim 4, characterized in that The selecting a plurality of first target array elements from the dimension reduction matrix comprises: Determine the contribution score of each array element in the dimension reduction matrix relative to the target broadband excitation, and the comprehensive error information of the FI pattern corresponding to each array element; According to the contribution score of each array element and the comprehensive error information of the FI pattern, a plurality of first target array elements are selected in the dimension reduction matrix.

6. The method according to claim 1, characterized in that After constructing the target non-uniform array according to the target antenna unit, the method further includes: Calculate the target coefficients of the filter corresponding to the target non-uniform array by a convex optimization solution algorithm; The expected waveform corresponding to the target non-uniform array is determined by configuring the filter of the target coefficients.

7. A frequency-invariant antenna array optimization device based on amplitude spectrum analysis, characterized in that: include: A data acquisition module is configured to acquire a virtual dense array composed of a plurality of antenna units and determine initial parameters of the virtual dense array, wherein the initial parameters include an initial array pattern, an initial broadband excitation, and a space-time angular frequency; A reference pattern construction module is configured to construct a reference pattern based on the initial parameters, and determine an initial excitation of the reference pattern and expected index parameters of the virtual dense array; An array element selection module is configured to construct a spatial spectrum distribution based on the initial excitation and the expected indicator parameter, and select a target antenna unit in the virtual dense array according to amplitude spectrum information corresponding to the spatial spectrum distribution; a target array construction module, configured to construct a target non-uniform array according to the target antenna unit, wherein the target non-uniform array satisfies a preset antenna radiation condition; The reference pattern construction module comprises: A broadband pattern determination submodule, configured to determine an intermediate broadband pattern based on the space-time angular frequency and the initial array pattern; A dimensional expansion submodule is configured to sample the space-time angular frequency according to a preset sampling interval to obtain a target number of samples corresponding to the space-time angular frequency, and perform dimension expansion on the initial broadband excitation according to the target number of samples to obtain an expanded broadband excitation; A target broadband directional pattern construction submodule is configured to update the intermediate broadband directional pattern according to the extended broadband excitation to obtain a target broadband directional pattern; The reference directional pattern construction submodule is configured to construct the reference directional pattern according to the operating frequency of the target broadband directional pattern.

8. A computing device, characterized in that include: Memory and processor; The memory is used to store computer programs / instructions, and the processor is used to execute the computer programs / instructions. When the computer program / instructions are executed by the processor, the steps of the method for optimizing the arrangement of a non-frequency-variant antenna array based on amplitude spectrum analysis as described in any one of claims 1 to 6 are implemented.

9. A computer-readable storage medium storing a computer program / instruction, characterized in that: When the computer program / instruction is executed by a processor, the steps of the method for optimizing the arrangement of a frequency-invariant antenna array based on amplitude spectrum analysis as described in any one of claims 1 to 6 are implemented.

10. A computer program product comprising a computer program / instructions, characterized in that When the computer program / instruction is executed by a processor, the steps of the method for optimizing the arrangement of a frequency-invariant antenna array based on amplitude spectrum analysis as described in any one of claims 1 to 6 are implemented.

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