Phased array antenna calibration method, device, computer equipment and phased array antenna

Abstract

The present invention relates to the field of antenna calibration and discloses a phased array antenna calibration method, apparatus, computer equipment, and phased array antenna. The method comprises: obtaining array element clustering results associated with the phased array antenna to be calibrated; dividing the phased array antenna to be calibrated into multiple array element groups based on the array element clustering results; obtaining measurement data for each array element group; and calibrating the phased array antenna to be calibrated based on the measurement data. The present invention utilizes a group calibration strategy to significantly improve the calibration efficiency of the phased array antenna and is particularly suitable for phased array systems in large-scale, high-density, and dynamic environments.

Description

Technical Field

[0001] The present invention relates to the field of antenna calibration, and in particular to a phased array antenna calibration method, device, computer equipment and phased array antenna. Background Art

[0002] Phased array antennas are composed of multiple unit channels, each of which integrates microwave components such as radiating elements, phase shifters, and attenuators. Due to differences in manufacturing processes and materials, the performance of components in each channel is difficult to be completely consistent, resulting in amplitude and phase errors that need to be compensated through calibration techniques. Traditional calibration methods rely on external antennas or embedded calibration units to measure parameters such as mutual coupling and scattering. However, these methods have significant limitations: the number of measurements is on the order of kN (N is the number of array elements, k ≥ 1). For large-scale phased arrays (e.g., tens of thousands of elements), calibration can take hours, making it difficult to meet the requirements of efficient production. A new calibration method is urgently needed to improve the correction efficiency of phased array antennas. Summary of the Invention

[0003] Based on this, it is necessary to provide a phased array antenna calibration method, device, computer equipment and phased array antenna to address the above technical problems, so as to improve the correction efficiency of the phased array antenna.

[0004] A phased array antenna calibration method, comprising:

[0005] Obtaining array element clustering results associated with the phased array antenna to be calibrated;

[0006] Dividing the phased array antenna to be calibrated into a plurality of array element groups according to the array element clustering result;

[0007] Acquiring measurement data of each array element group;

[0008] The phased array antenna to be calibrated is calibrated according to the measurement data.

[0009] Optionally, before obtaining the array element clustering result associated with the phased array antenna to be calibrated, the method further includes:

[0010] Acquire historical calibration data associated with the phased array antenna to be calibrated; the historical calibration data includes calibration data of multiple sets of calibrated phased array antennas;

[0011] Clustering is performed on the historical calibration data to obtain the array element clustering result.

[0012] Optionally, clustering the historical calibration data to obtain the array element clustering result includes:

[0013] Preprocessing the historical calibration data to obtain normalized data;

[0014] The normalized data is processed by a hierarchical aggregation algorithm to obtain the array element clustering result.

[0015] Optionally, preprocessing the historical calibration data to obtain normalized data includes:

[0016] removing bad pixels from the historical calibration data to obtain bad pixel-removed data;

[0017] Normalizing the phase data in the bad pixel removed data to generate the normalized data.

[0018] Optionally, removing bad pixels from the historical calibration data to obtain bad pixel-removed data includes:

[0019] The bad pixel removal data is obtained by processing the historical calibration data using a bad pixel evaluation rule; the bad pixel evaluation rule includes:

[0020] For any channel of the mth set of antennas in the historical calibration data I , if exists , then the data of channel 1 is marked as bad data points; wherein, represents the amplitude of the kth frequency point of channel I of the mth set of antennas, Represents the mean value of all channels at frequency k of the mth set of antennas; is the cutoff value.

[0021] Optionally, the cutoff value is three times the variance of the amplitude distribution at frequency point k.

[0022] Optionally, the processing the normalized data by a hierarchical aggregation algorithm to obtain the array element clustering result includes:

[0023] The calibration data of each channel in the normalized data is considered as an independent cluster;

[0024] Calculate all cluster distances;

[0025] Merge the two clusters with the smallest distance to form a cluster set;

[0026] The process of calculating cluster distances and merging clusters is repeated until the phase error in the cluster set is greater than the phase control threshold, and the clustering result with the smallest number of cluster groups whose phase errors are not greater than the phase control threshold is determined as the array element clustering result.

[0027] A phased array antenna calibration device, comprising:

[0028] A clustering result acquisition module is used to obtain array element clustering results associated with the phased array antenna to be calibrated;

[0029] An array element grouping module is configured to divide the phased array antenna to be calibrated into a plurality of array element groups according to the array element clustering result;

[0030] A measurement data acquisition module, configured to acquire measurement data of each array element group;

[0031] A calibration module is used to calibrate the phased array antenna to be calibrated according to the measurement data.

[0032] A computer device includes a memory, a processor, and computer-readable instructions stored in the memory and executable on the processor. When the processor executes the computer-readable instructions, the phased array antenna calibration method is implemented.

[0033] A phased array antenna is calibrated by any one of the above-mentioned phased array antenna calibration methods.

[0034] The above-described phased array antenna calibration method, apparatus, computer equipment, and storage medium utilize the similarity between calibration data to perform group calibration. The number of groups is much smaller than the number of array channels, reducing the test workload by an order of magnitude. This achieves sparse calibration of phased array antennas and significantly improves antenna calibration efficiency. Furthermore, the number of array element groups is related to phase deviation, enabling different array element groupings to be obtained under different phase deviation requirements, facilitating flexible adjustment of the calibration method. Through the group calibration strategy, the present invention significantly outperforms traditional global calibration methods in terms of efficiency, accuracy, resource utilization, and system robustness, making it particularly suitable for phased array systems operating in large-scale, high-density, and dynamic environments. BRIEF DESCRIPTION OF THE DRAWINGS

[0035] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the following briefly introduces the drawings required for use in the description of the embodiments of the present invention. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative labor.

[0036] Figure 1 is a flow chart of a phased array antenna calibration method according to an embodiment of the present invention;

[0037] Figure 2 is the phase distribution of the mth set of phased array antennas divided into groups of 150 array elements in one embodiment of the present invention;

[0038] Figure 3 is the phase distribution of the mth set of phased array antennas divided into 75 array element groups in one embodiment of the present invention;

[0039] Figure 4is the amplitude distribution of the mth set of phased array antennas divided into 150 array element groups in one embodiment of the present invention;

[0040] Figure 5 is the amplitude distribution of the mth set of phased array antennas divided into 75 array element groups in one embodiment of the present invention;

[0041] Figure 6 is a cluster number-distance relationship diagram of phase array antenna phase data clustering in one embodiment of the present invention;

[0042] Figure 7 This is a schematic diagram of solving unknown quantities using the improved rotating vector method in one embodiment of the present invention. Figure 1 ( Values are 0°, 90°, 180°);

[0043] Figure 8 This is a schematic diagram of solving unknown quantities using the improved rotating vector method in one embodiment of the present invention. Figure 2 ( Values are 0°, 90°, 270°);

[0044] Figure 9 is a structural schematic diagram of a phased array antenna calibration device according to an embodiment of the present invention;

[0045] Figure 10 FIG. 1 is a schematic diagram of a computer device according to an embodiment of the present invention. DETAILED DESCRIPTION

[0046] The following will clearly and completely describe the technical solutions in the embodiments of the present invention in conjunction with the accompanying drawings. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of them. All other embodiments obtained by ordinary technicians in this field based on the embodiments of the present invention without making any creative efforts shall fall within the scope of protection of the present invention.

[0047] In one embodiment, if Figure 1 As shown, a phased array antenna calibration method is provided, including the following steps S10 to S40.

[0048] S10, obtaining an array element clustering result associated with the phased array antenna to be calibrated;

[0049] S20, dividing the phased array antenna to be calibrated into a plurality of array element groups according to the array element clustering result;

[0050] S30, obtaining measurement data of each array element group;

[0051] S40: Calibrate the phased array antenna to be calibrated according to the measurement data.

[0052] It is understandable that the links between the channels of the phased array antenna are similar, and the calibration data is clustered. In this embodiment, the phased array antenna to be calibrated is calibrated using the measurement data of the array element grouping, which can achieve fast calibration with a number far less than the number of channels.

[0053] Specifically, the array element clustering results associated with the phased array antenna to be calibrated can be obtained. Clustering can be performed based on historical calibration data to form array element clustering results. Dividing array elements into groups based on the array element clustering results can achieve the purpose of reducing the number of measurement points while ensuring calibration accuracy. In an example, the phased array antenna to be calibrated has N radiating elements and the number of calibration frequency points is K. The array element clustering results can be divided by array element number. According to the array element clustering results, all the radiating elements of the phased array antenna to be calibrated are grouped. The rth array element group can be expressed as , where r is the group number, and the array element clustering results include G, For the The number of array elements in the array element group, , a total of A formation element.

[0054] The measurement data of each array element group can be measured to obtain the phase and amplitude That is to say, through G measurements, the calibration of N radiation units can be achieved.

[0055] In one application example, there are 528 phased array antennas to be calibrated, each containing 752 radiating elements. The measurement frequency ranges from 10.7 GHz to 12.7 GHz, for a total of 12 frequency points. A compact test field is used. Measurement data (microwave signals are generated and measured using a vector network analyzer) is used. The calibration method uses an improved rotating vector method. Using the grouping method described above, calibration data for the mth phased array antenna can be obtained: amplitude data , phase data ,in, m Antenna number, (m=0, 1,…, 527); n is the radiation unit number (same as the channel number), (n=0, 1, ..., 751); k is the frequency point number (K=0, 1, ..., 11). Its amplitude and phase errors are: .

[0056] like Figures 2 to 5 As shown, Figure 2 The phase distribution of the mth phased array antenna divided into 150 array element groups, Figure 3 The phase distribution of the mth phased array antenna divided into 75 array element groups, Figure 4is the amplitude distribution of the mth phased array antenna divided into 150 array element groups, Figure 5 is the amplitude distribution of the mth phased array antenna divided into 75 array element groups, Figures 2 to 5 The vertical axis of is the frequency. Figures 2 to 5 It can be seen that when the number of array element groups is 75, the phase variance is 7.9° and the amplitude variance is 1.34dB. When the number of array element groups is 150, the phase variance is 5.05° and the amplitude variance is 1.19dB.

[0057] This embodiment leverages the similarity between calibration data to perform group calibration. The number of groups is far smaller than the number of array channels, reducing the test workload by an order of magnitude. This enables sparse calibration of phased array antennas, significantly improving calibration efficiency. Furthermore, the number of element groups is related to phase deviation, enabling different element groupings to be achieved under different phase deviation requirements, facilitating flexible adjustment of the calibration method. This embodiment, through its group calibration strategy, significantly outperforms traditional global calibration methods in terms of efficiency, accuracy, resource utilization, and system robustness, making it particularly suitable for phased array systems operating in large-scale, high-density, and dynamic environments.

[0058] Optionally, before step S10, that is, before obtaining the array element clustering result associated with the phased array antenna to be calibrated, the method further includes:

[0059] S11. Acquire historical calibration data associated with the phased array antenna to be calibrated; the historical calibration data includes calibration data of multiple sets of calibrated phased array antennas;

[0060] S12: Clustering the historical calibration data to obtain the array element clustering result.

[0061] Understandably, historical calibration data associated with the phased array antenna to be calibrated can be obtained. This historical calibration data includes calibration data for multiple sets of previously calibrated phased array antennas. In this case, the phased array antenna to be calibrated and the previously calibrated phased array antennas have the same specifications. Clustering the historical calibration data requires a large amount of calibration data. In some examples, the historical calibration data includes more than 100 sets of calibration data.

[0062] Clustering historical calibration data can yield element clustering results. An appropriate clustering algorithm can be selected based on actual needs, such as hierarchical clustering. Hierarchical clustering partitions the dataset at different levels, forming a tree-like clustering structure. In some examples, the AGNE (agglomerative hierarchical clustering) algorithm can be used to cluster historical calibration data. The AGNE algorithm is a bottom-up hierarchical clustering method that initially treats each sample (element) as a separate cluster and then gradually merges the closest clusters until a termination condition is met, such as reaching a preset number of clusters or merging all data points into a single cluster. The resulting element clustering results can be used to group the individual radiating units (element) of a phased array antenna into element groups.

[0063] By analyzing historical calibration data, this embodiment can better understand and predict the behavior of the phased array antenna to be calibrated, thereby improving the calibration efficiency and accuracy of the phased array antenna.

[0064] Optionally, step S12, i.e., clustering the historical calibration data to obtain the array element clustering result, includes:

[0065] S121, preprocessing the historical calibration data to obtain normalized data;

[0066] S122: Process the normalized data using a hierarchical aggregation algorithm to obtain the array element clustering result.

[0067] Understandably, the collected historical calibration data can be preprocessed. Preprocessing is a key step in data analysis, ensuring the effectiveness and accuracy of subsequent analysis. Preprocessing includes but is not limited to outlier detection and processing, and phase normalization. Obtaining normalized data after preprocessing can improve the quality of cluster analysis and achieve higher-quality array element clustering results.

[0068] After preprocessing, hierarchical agglomeration algorithms can be applied to the normalized data. Hierarchical agglomeration is a method for constructing a hierarchy of clusters, such as agglomerative hierarchical clustering. Agglomerative hierarchical clustering starts with each sample as a separate cluster and then gradually merges the most similar clusters.

[0069] Specifically, using the hierarchical aggregation algorithm, we can start with a single array element as an independent cluster, and then gradually merge the closest clusters based on the Chebyshev distance. This process can be represented by a dendrogram, and the final cluster division can be determined based on a specific stopping condition (such as the set maximum number of clusters or threshold distance), thereby obtaining the array element clustering result. For example, arbitrarily select the K0th frequency point and perform the data Perform hierarchical aggregation, Where K0 is the selected fixed frequency index, n is the antenna element index (the value range is 0 to N-1, corresponding to N elements), is the calibration data of the K0th frequency point of the ith radiation unit of the mth phased array antenna. Cluster distance metric function , where Chebyshev distance is used. and is the cluster of phased array antenna calibration data. Among them, e belongs to The calibration data points in The calibration data points in .

[0070] In an embodiment, processing normalized data based on a hierarchical aggregation algorithm helps to discover the intrinsic connections between array elements and can help identify array element groups with similar performance characteristics, which is very useful for optimizing the calibration of phased array antennas.

[0071] Optionally, step S121, i.e., preprocessing the historical calibration data to obtain normalized data, includes:

[0072] S1211, removing bad pixels from the historical calibration data to obtain bad pixel-removed data;

[0073] S1212: Normalize the phase data in the bad pixel removed data to generate the normalized data.

[0074] Bad points are generally considered outliers or erroneous data points in historical calibration data. These data deviations may be caused by measurement errors, equipment failures, or other abnormal operating conditions. Bad point removal can be performed on historical calibration data to obtain bad point-free data. Obtaining bad point-free data helps improve the accuracy and reliability of subsequent data clustering.

[0075] After obtaining the bad pixel data, the phase data can be further normalized to generate normalized data. By normalization, all phase data can be made to fall within the interval [0, 360). For example, the phase data can be normalized using the following formula:

[0076] .

[0077] Can be defined , Phase data before normalization, is the normalized phase data.

[0078] This embodiment can clean up the noise in the historical calibration data by removing bad pixels; through phase normalization, more stable and easy-to-analyze normalized data can be obtained, thereby improving the quality of cluster analysis and obtaining better array element clustering results.

[0079] Optionally, step S1211, i.e., removing bad pixels from the historical calibration data to obtain bad pixel-removed data, includes:

[0080] S12111. Process the historical calibration data using a bad pixel evaluation rule to obtain bad pixel removal data. The bad pixel evaluation rule includes:

[0081] For any channel of the mth set of antennas in the historical calibration data I , if exists , then the data of channel 1 is marked as bad data points; wherein, represents the amplitude of the kth frequency point of channel I of the mth set of antennas, Represents the mean value of all channels at frequency k of the mth set of antennas; is the cutoff value.

[0082] Understandably, for any channel of the mth set of antennas in the historical calibration data I , if exists , then the data of channel I is marked as bad data points. represents the amplitude of the kth frequency point of channel I of the mth set of antennas, , K is the number of calibration frequency points, Represents the mean value of all channels at frequency k of the mth set of antennas; is the cutoff value. The bad data point can be Indicates that the data of channel I is not processed. . Cutoff value It can be set according to actual needs.

[0083] In this embodiment, by eliminating amplitude values that have an amplitude difference that is too small from the mean, the clustering efficiency of the historical calibration data is greatly improved.

[0084] Optionally, the cutoff value is three times the variance of the amplitude distribution at frequency point k.

[0085] Understandably, the cutoff value can be set to three times the variance of the amplitude distribution at frequency k. Since the amount of historical calibration data is large, most frequency amplitudes are close to the mean. By selecting a reasonable cutoff value, the calibration data involved in clustering can be greatly reduced, improving clustering accuracy and efficiency.

[0086] Optionally, step S122, i.e., processing the normalized data using a hierarchical aggregation algorithm to obtain the array element clustering result, includes:

[0087] S1221, treating the calibration data of each channel in the normalized data as an independent cluster;

[0088] S1222, calculating all cluster distances;

[0089] S1223. Merge the two clusters with the smallest distance to form a cluster set.

[0090] S1224 , repeat the process of calculating cluster distances and merging clusters until the phase error in the cluster set is greater than the phase control threshold, and determine the clustering result with the smallest number of cluster groups whose phase errors are not greater than the phase control threshold as the array element clustering result.

[0091] Understandably, the normalized data can be processed by a hierarchical aggregation algorithm to obtain the array element clustering result. Here, the hierarchical aggregation algorithm can be an AGNE algorithm. The calibration data of each channel in the normalized data can be regarded as an independent cluster, and then all cluster distances are calculated (cluster distance refers to the distance between two clusters), and the two clusters with the smallest distance are merged to form a cluster set. The process of calculating cluster distances and merging clusters is repeated until the phase error in the cluster set is greater than the phase control threshold. The clustering result with the smallest number of cluster groups whose phase error is not greater than the phase control threshold is determined as the array element clustering result. Here, the phase control threshold can be set according to the actual phase deviation requirement. For example, the phase control threshold .like Figure 6 As shown, Figure 6 The relationship between the number of clusters (i.e., the number of cluster groups) and the distance of the phased array antenna phase data clustering. The phase control threshold determines the cluster distance. Figure 6 It can be seen that there is a negative correlation between cluster distance and the number of cluster groups.

[0092] In this embodiment, a hierarchical merging strategy is adopted with the phase error threshold as the termination condition to ensure that the channel phase error within each cluster is minimized, thereby improving calibration accuracy. The number of cluster groups is controlled based on the phase control threshold, thus balancing the grouping precision and system complexity.

[0093] In some application examples, the historical calibration data of step S11 can be obtained based on the improved rotation vector method. The calibration of the phased array antenna is essentially to obtain the relative amplitude values between the array elements. and phase relative value (The reference object is the full array signal), forming an accurate amplitude and phase distribution, thereby optimizing the beam performance. In other words, the unknown quantity to be solved is the relative value of the amplitude and phase relative value In order to obtain this unknown quantity through the changing cosine curve, the traditional rotating vector method has a sampling point far greater than 2, so the rotating vector method has many redundant measurements.

[0094] In the improved rotation vector method, special channel phase difference ( value) to solve and .like Figure 7-Figure 8 As shown, in the complex plane coordinate system (real part Re is the horizontal axis, imaginary part Im is the vertical axis), the channel to be measured n You can determine it by changing any three angles and , generally choose The values are 0°, 90°, 180° ( Figure 7 ) and 0°, 90°, 270° ( Figure 8 ),by Figure 7 For example, by changing the phase of the channel to be measured, the energy measured is:

[0095] ;

[0096] Where E is the measured energy value; E0 is the amplitude of the full array signal, which is used as a reference benchmark. The independent signal amplitude of the measured channel n reflects the gain characteristics of the channel. is the initial phase of the full array signal (usually the average value or the specified reference channel phase), is the initial phase of the channel n to be measured, including the manufacturing error and temperature drift effect. is the basic term, representing the energy of the original channel to be measured, is the interference cancellation term, which is used to represent the phase reverse compensation of the interference signal (such as noise or reflected wave). is the phase adjustment term, which represents the new state after applying a phase shift Δ to the interference signal. represents the adjusted composite energy. Represents the adjusted resultant energy.

[0097] Take Δ as 0°, 90° and 180° respectively and measure the corresponding energy values and .

[0098] We can get the equation: ;

[0099] in,

[0100] ;

[0101] A is an orthogonal basis matrix based on the Δ value, which is used to simplify the solution of the equation.

[0102] Vector P represents the power value measured under three phase switching , reflecting the energy change of the composite signal. Calibration requires determining the amplitude ratio of each channel relative to the entire array. , compensating for manufacturing tolerances and mutual coupling effects. Determine channel phase deviation for phase shifter compensation.

[0103] Solving the above equations we can get and , and so on, the normalized amplitude and phase of each channel of the entire array can be obtained. By this method, the entire antenna array needs to be measured 2N+1 times to complete the calibration of all channels. In an example, if the kth frequency point of the mth antenna is calibrated, then .

[0104] It should be understood that the size of the serial numbers of the steps in the above embodiments does not mean the order of execution. The execution order of each process should be determined by its function and internal logic, and should not constitute any limitation on the implementation process of the embodiments of the present invention.

[0105] In one embodiment, a phased array antenna calibration device is provided, which corresponds one-to-one to the phased array antenna calibration method in the above embodiment. Figure 9 As shown, the phased array antenna calibration device includes:

[0106] A clustering result acquisition module 10 is configured to acquire an array element clustering result associated with the phased array antenna to be calibrated;

[0107] An array element grouping module 20 is configured to divide the phased array antenna to be calibrated into a plurality of array element groups according to the array element clustering result;

[0108] A measurement data acquisition module 30, configured to acquire measurement data of each array element group;

[0109] The calibration module 40 is configured to calibrate the phased array antenna to be calibrated according to the measurement data.

[0110] Optionally, the clustering result acquisition module 10 further includes:

[0111] A historical data acquisition unit, configured to acquire historical calibration data associated with the phased array antenna to be calibrated; the historical calibration data includes calibration data of multiple sets of calibrated phased array antennas;

[0112] A clustering unit is used to cluster the historical calibration data to obtain the array element clustering result.

[0113] Optionally, the clustering unit includes:

[0114] A preprocessing unit, configured to preprocess the historical calibration data to obtain normalized data;

[0115] The hierarchical clustering unit is used to process the normalized data through a hierarchical aggregation algorithm to obtain the array element clustering result.

[0116] Optionally, the pre-processing unit includes:

[0117] a bad pixel removal unit, configured to remove bad pixels from the historical calibration data to obtain bad pixel removal data;

[0118] The normalization unit is used to normalize the phase data in the bad pixel removal data to generate the normalized data.

[0119] Optionally, the bad pixel removal unit is further configured to:

[0120] The bad pixel removal data is obtained by processing the historical calibration data using a bad pixel evaluation rule; the bad pixel evaluation rule includes:

[0121] For any channel of the mth set of antennas in the historical calibration data I , if exists , then the data of channel 1 is marked as bad data points; wherein, represents the amplitude of the kth frequency point of channel I of the mth set of antennas, Represents the mean value of all channels at frequency k of the mth set of antennas; is the cutoff value.

[0122] Optionally, the cutoff value is three times the variance of the amplitude distribution at frequency point k.

[0123] Optionally, the hierarchical clustering unit includes:

[0124] determining an independent cluster unit for treating the calibration data of each channel in the normalized data as an independent cluster;

[0125] Cluster distance calculation unit, used to calculate all cluster distances;

[0126] The merging unit is used to merge the two clusters with the smallest distance to form a cluster set;

[0127] The clustering result determination unit is configured to repeatedly calculate the cluster distance and merge the clusters until the phase error in the cluster set is greater than the phase control threshold, and determine the clustering result with the smallest number of cluster groups whose phase error is not greater than the phase control threshold as the array element clustering result.

[0128] The specific definitions of the phased array antenna calibration device can be found in the definitions of the phased array antenna calibration method above and will not be repeated here. Each module in the aforementioned phased array antenna calibration device can be implemented in whole or in part through software, hardware, or a combination thereof. Each of these modules can be embedded in or independent of a processor in a computer device in hardware form, or stored in a computer device memory in software form, so that the processor can call and execute the corresponding operations of each of these modules.

[0129] In one embodiment, a computer device is provided. The computer device may be a server, and its internal structure diagram may be as follows: Figure 10 As shown. The computer device includes a processor, a memory, a network interface and a database connected via a system bus. The processor of the computer device is used to provide computing and control capabilities. The memory of the computer device includes a readable storage medium and an internal memory. The readable storage medium stores an operating system, computer-readable instructions and a database. The internal memory provides an environment for the operation of the operating system and computer-readable instructions in the readable storage medium. The database of the computer device is used to store data involved in the phased array antenna calibration method. The network interface of the computer device is used to communicate with an external terminal via a network connection. When the computer-readable instructions are executed by the processor, a phased array antenna calibration method is implemented. The readable storage medium provided in this embodiment includes a non-volatile readable storage medium and a volatile readable storage medium.

[0130] In one embodiment, a computer device is provided, comprising a memory, a processor, and computer-readable instructions stored in the memory and executable on the processor. When the processor executes the computer-readable instructions, the following steps are implemented:

[0131] Obtaining array element clustering results associated with the phased array antenna to be calibrated;

[0132] Dividing the phased array antenna to be calibrated into a plurality of array element groups according to the array element clustering result;

[0133] Acquiring measurement data of each array element group;

[0134] The phased array antenna to be calibrated is calibrated according to the measurement data.

[0135] In one embodiment, a phased array antenna is provided, and the phased array antenna is calibrated by any one of the above-mentioned phased array antenna calibration methods.

[0136] In one embodiment, one or more computer-readable storage media storing computer-readable instructions are provided. The computer-readable storage media provided in this embodiment include non-volatile computer-readable storage media and volatile computer-readable storage media. The computer-readable storage media store computer-readable instructions that, when executed by one or more processors, implement the following steps:

[0137] Obtaining array element clustering results associated with the phased array antenna to be calibrated;

[0138] Dividing the phased array antenna to be calibrated into a plurality of array element groups according to the array element clustering result;

[0139] Acquiring measurement data of each array element group;

[0140] The phased array antenna to be calibrated is calibrated according to the measurement data.

[0141] Those skilled in the art will understand that all or part of the processes in the above-mentioned embodiment methods can be implemented by instructing related hardware through computer-readable instructions. The computer-readable instructions can be stored in a non-volatile readable storage medium or a volatile readable storage medium. When the computer-readable instructions are executed, they can include the processes of the embodiments of the above-mentioned methods. Among them, any reference to memory, storage, database or other media used in the embodiments provided in this application may include non-volatile and / or volatile memory. Non-volatile memory may include read-only memory (ROM), programmable ROM (PROM), electrically programmable ROM (EPROM), electrically erasable programmable ROM (EEPROM) or flash memory. Volatile memory may include random access memory (RAM) or external cache memory. By way of illustration and not limitation, RAM is available in many forms such as static RAM (SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), double data rate SDRAM (DDRSDRAM), enhanced SDRAM (ESDRAM), Synchronous Link DRAM (SLDRAM), Rambus direct RAM (RDRAM), direct memory bus dynamic RAM (DRDRAM), and memory bus dynamic RAM (RDRAM), etc.

[0142] Those skilled in the art will clearly understand that for the sake of convenience and brevity of description, only the division of the above-mentioned functional units and modules is used as an example. In actual applications, the above-mentioned functions can be distributed and completed by different functional units and modules as needed, that is, the internal structure of the device can be divided into different functional units or modules to complete all or part of the functions described above.

[0143] The embodiments described above are only used to illustrate the technical solutions of the present invention, rather than to limit the same. Although the present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the aforementioned embodiments, or make equivalent replacements for some of the technical features therein. These modifications or replacements do not deviate the essence of the corresponding technical solutions from the spirit and scope of the technical solutions of the various embodiments of the present invention, and should all be included in the scope of protection of the present invention.

Claims

1. A phased array antenna calibration method, characterized in that: include: Obtaining array element clustering results associated with the phased array antenna to be calibrated; Dividing the phased array antenna to be calibrated into a plurality of array element groups according to the array element clustering result; Acquiring measurement data of each array element group; calibrating the phased array antenna to be calibrated according to the measurement data; Before obtaining the array element clustering result associated with the phased array antenna to be calibrated, the method further includes: Acquire historical calibration data associated with the phased array antenna to be calibrated; the historical calibration data includes calibration data of multiple sets of calibrated phased array antennas; The historical calibration data is clustered using a hierarchical aggregation algorithm to obtain the array element clustering result.

2. The phased array antenna calibration method according to claim 1, wherein: The clustering of the historical calibration data to obtain the array element clustering result includes: Preprocessing the historical calibration data to obtain normalized data; The normalized data is processed by a hierarchical aggregation algorithm to obtain the array element clustering result.

3. The phased array antenna calibration method according to claim 2, wherein: The preprocessing of the historical calibration data to obtain normalized data includes: removing bad pixels from the historical calibration data to obtain bad pixel-removed data; Normalizing the phase data in the bad pixel removed data to generate the normalized data.

4. The phased array antenna calibration method according to claim 3, wherein: The step of removing bad pixels from the historical calibration data to obtain bad pixel-removed data includes: The bad pixel removal data is obtained by processing the historical calibration data using a bad pixel evaluation rule; the bad pixel evaluation rule includes: For any channel of the mth set of antennas in the historical calibration data I , if exists , then the data of channel 1 is marked as bad data points; wherein, represents the amplitude of the kth frequency point of channel I of the mth set of antennas, Represents the mean value of all channels at frequency k of the mth set of antennas; is the cutoff value.

5. The phased array antenna calibration method according to claim 4, wherein: The cutoff value is three times the variance of the amplitude distribution at frequency point k.

6. The phased array antenna calibration method according to claim 2, wherein: The step of processing the normalized data by a hierarchical aggregation algorithm to obtain the array element clustering result includes: The calibration data of each channel in the normalized data is considered as an independent cluster; Calculate all cluster distances; Merge the two clusters with the smallest distance to form a cluster set; The process of calculating cluster distances and merging clusters is repeated until the phase error in the cluster set is greater than the phase control threshold, and the clustering result with the smallest number of cluster groups whose phase errors are not greater than the phase control threshold is determined as the array element clustering result.

7. A phased array antenna calibration device, characterized in that: include: A clustering result acquisition module is used to obtain the array element clustering results associated with the phased array antenna to be calibrated; An array element grouping module is configured to divide the phased array antenna to be calibrated into a plurality of array element groups according to the array element clustering result; A measurement data acquisition module, configured to acquire measurement data of each array element group; a calibration module, configured to calibrate the phased array antenna to be calibrated according to the measurement data; The clustering result acquisition module further includes: A historical data acquisition unit is configured to acquire historical calibration data associated with the phased array antenna to be calibrated; the historical calibration data includes calibration data of multiple sets of calibrated phased array antennas; The clustering unit is configured to cluster the historical calibration data using a hierarchical aggregation algorithm to obtain the array element clustering result.

8. A computer device comprising a memory, a processor, and computer-readable instructions stored in the memory and executed on the processor, wherein: When the processor executes the computer-readable instructions, the phased array antenna calibration method according to any one of claims 1 to 6 is implemented.

9. A phased array antenna, characterized in that: The phased array antenna is calibrated by the phased array antenna calibration method according to any one of claims 1 to 6.

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