High-precision multi-channel phased array radio metrology calibration method and system

Abstract

The present invention relates to a high-precision multi-channel phased array radio metrology calibration method and system. The method: electromagnetic characteristic modeling is performed on N array element channels and antenna covers of a multi-channel phased array antenna to obtain a channel measurement model; electromagnetic field numerical calculation is performed on the multi-channel phased array antenna to obtain an initial error data matrix; the initial error data matrix is ​​mapped to a two-dimensional weight matrix, and the two-dimensional weight matrix is ​​optimally matched and solved to obtain a theoretical calibration coefficient matrix; a vector network analyzer is used to connect a standard gain antenna and a multi-channel phased array antenna, and a far-field scanning measurement is performed on the multi-channel phased array antenna to obtain measured amplitude and phase characteristic data; weighted least squares iterative calculation is performed on the measured amplitude and phase characteristic data and the theoretical calibration coefficient matrix to obtain a target calibration compensation coefficient. The present invention realizes the accurate measurement of the amplitude and phase characteristics of a multi-channel phased array antenna and improves the stability of the calibration process.

Description

Technical Field

[0001] The present invention relates to the technical field of radio metrology calibration, and in particular to a high-precision multi-channel phased array radio metrology calibration method and system. Background Art

[0002] As modern radar and communication systems develop towards high frequency, broadband and multi-function, multi-channel phased array antennas have become key core components. However, in practical applications, phased array antennas have problems such as inconsistent amplitude and phase between channels, wavefront distortion caused by the radome, and mutual coupling effects. These factors seriously affect the performance indicators of phased array antennas. Traditional phased array antenna calibration methods mainly rely on single-channel measurements and empirical models, which cannot effectively deal with the coupling effects between multiple channels, resulting in limited calibration accuracy. At the same time, due to the lack of accurate modeling and compensation methods for the influence of the radome, there is a large deviation between the calibration results and the actual working state.

[0003] At present, phased array antenna calibration technology mainly faces three challenges: first, the problem of accurate modeling of the mutual coupling effects between multiple channels. Traditional electromagnetic field simulation methods have large computational complexity and low efficiency, and it is difficult to meet the modeling needs of large-scale arrays; second, the problem of accurate characterization of the influence of the antenna cover on electromagnetic wave propagation. Existing calculation methods often ignore the non-uniformity and loss characteristics of the antenna cover medium properties; finally, there is a lack of effective multi-source data fusion mechanism, which makes it impossible to optimize the combination of theoretical model calculation results and measured data. Summary of the invention

[0004] The main purpose of the present invention is to provide a high-precision multi-channel phased array radio metrology calibration method and system, which realizes the accurate measurement of the amplitude and phase characteristics of the multi-channel phased array antenna and improves the stability of the calibration process.

[0005] To achieve the above object, the present invention provides a high-precision multi-channel phased array radio metrology calibration method, comprising the following steps:

[0006] The electromagnetic characteristics of the N array element channels and radome of the multi-channel phased array antenna are modeled to obtain a channel measurement model;

[0007] According to the channel measurement model, performing electromagnetic field numerical calculation on the multi-channel phased array antenna to obtain an initial error data matrix;

[0008] Mapping the initial error data matrix to a two-dimensional weight matrix, and performing optimal matching on the two-dimensional weight matrix to obtain a theoretical calibration coefficient matrix;

[0009] A vector network analyzer is used to connect a standard gain antenna and the multi-channel phased array antenna, and a far-field scanning measurement is performed on the multi-channel phased array antenna to obtain measured amplitude and phase characteristic data;

[0010] A weighted least squares iterative calculation is performed on the measured amplitude-phase characteristic data and the theoretical calibration coefficient matrix to obtain a target calibration compensation coefficient.

[0011] The present invention also provides a high-precision multi-channel phased array radio metrology calibration system, comprising:

[0012] A modeling module is used to model the electromagnetic characteristics of N array element channels and antenna covers of a multi-channel phased array antenna to obtain a channel measurement model;

[0013] A calculation module, used for performing electromagnetic field numerical calculation on the multi-channel phased array antenna according to the channel measurement model to obtain an initial error data matrix;

[0014] A solution module, used for mapping the initial error data matrix to a two-dimensional weight matrix, and performing an optimal matching solution on the two-dimensional weight matrix to obtain a theoretical calibration coefficient matrix;

[0015] A measurement module, used to connect a standard gain antenna and the multi-channel phased array antenna using a vector network analyzer, perform far-field scanning measurement on the multi-channel phased array antenna, and obtain measured amplitude and phase characteristic data;

[0016] The iterative module is used to perform weighted least squares iterative calculation on the measured amplitude-phase characteristic data and the theoretical calibration coefficient matrix to obtain a target calibration compensation coefficient.

[0017] In summary, the technical solution provided by the present invention achieves an accurate description of the complex electromagnetic characteristics of a multi-channel phased array antenna by establishing a mathematical model of electromagnetic characteristics including mutual coupling effects and the influence of the antenna cover, and combining the finite element method for high-precision numerical calculations; an optimization method combining the Hungarian algorithm and the KM algorithm is adopted to construct an optimal matching model based on a weight matrix, which effectively improves the calculation accuracy of the calibration coefficients between channels; a multi-source data fusion mechanism combining far-field measurement with theoretical models is established, and the reliability of the calibration parameters is significantly improved through weighted least squares iterative calculation; a high-precision measurement system based on vector network analysis is developed, which realizes the accurate measurement of the amplitude and phase characteristics of a multi-channel phased array antenna; orthogonal transformation and amplitude-phase decoupling technology are adopted to realize independent control of calibration compensation parameters and improve the stability of the calibration process; a complete performance evaluation system is established, and quantitative evaluation of the calibration effect is achieved through systematic testing of parameters such as antenna radiation pattern, gain, and beam pointing. BRIEF DESCRIPTION OF THE DRAWINGS

[0018] Figure 1 It is a schematic diagram of the steps of a high-precision multi-channel phased array radio metrology calibration method in one embodiment of the present invention;

[0019] Figure 2 It is a structural block diagram of a high-precision multi-channel phased array radio metrology calibration system in one embodiment of the present invention.

[0020] The realization of the purpose, functional features and advantages of the present invention will be further explained in conjunction with embodiments and with reference to the accompanying drawings. DETAILED DESCRIPTION

[0021] In order to make the purpose, technical solution and advantages of the present invention more clearly understood, the present invention is further described in detail below in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present invention and are not intended to limit the present invention.

[0022] Reference Figure 1 This embodiment provides a high-precision multi-channel phased array radio metrology calibration method, comprising the following steps:

[0023] S1, electromagnetic characteristic modeling is performed on N array element channels and antenna cover of the multi-channel phased array antenna to obtain a channel measurement model;

[0024] Among them, according to the structural characteristics of the multi-channel phased array antenna, its transmitting unit and receiving unit are arranged in a two-dimensional planar array to form a spatial distribution matrix of N array element channels with spatial characteristics, and the position relationship and geometric layout of each channel in the array are clarified. Based on the spatial distribution matrix, the electromagnetic field coupling characteristics between adjacent array element channels are calculated, and the N-order S parameter matrix is ​​established by using the S parameter model of network analysis. The electromagnetic field transmission and reflection characteristics between each channel are described, including the mutual coupling effect between array elements and the response to the external environment. At the same time, according to the influence of the antenna cover, the regional grid is divided. The antenna cover is divided into multiple small unit grids, and for each grid unit, its dielectric constant and loss tangent value are numerically discretized to obtain a parameter matrix reflecting the electromagnetic characteristics of the antenna cover. According to the antenna cover characteristic parameter matrix, the propagation path of the electromagnetic wave in the antenna cover is analyzed by finite element analysis using the weak form of the wave equation, and the wavefront distortion propagation function is obtained. This function describes the distortion of the electromagnetic wave after passing through the antenna cover, including important characteristics such as phase delay and waveform change. Combining the N-order S-parameter matrix with the wavefront distortion propagation function, a set of simultaneous equations reflecting the mutual coupling effect of array elements and the comprehensive influence of the radome is constructed. By numerically solving the set of equations, the amplitude and phase distortion coefficient set is obtained, which is a quantitative expression of the amplitude and phase changes of each channel in the antenna system. Based on the amplitude and phase distortion coefficient set, a mathematical expression of electromagnetic characteristics is established to describe the overall propagation characteristics of the multi-channel phased array antenna. This expression comprehensively considers the mutual coupling effect between antenna channels and the influence of the radome on the electromagnetic wave propagation path to form a propagation characteristic model. The overall propagation characteristic model is input into the finite element calculation program, and the corresponding electromagnetic field boundary conditions and excitation source parameters are set to simulate the actual working conditions. By iteratively calculating the model, the steady-state field distribution data of the multi-channel phased array antenna is obtained, reflecting the electromagnetic field characteristics of each channel in a stable state, including the field strength distribution and phase change. Based on the steady-state field distribution data, the weighted superposition method is used to synthesize the radiation pattern of each array element channel. The radiation pattern intuitively reflects the far-field radiation characteristics of the antenna. On this basis, the radiation pattern is associated and mapped with the amplitude and phase distortion coefficient sets to obtain the final channel measurement model.

[0025] S2, according to the channel measurement model, the electromagnetic field numerical calculation of the multi-channel phased array antenna is performed to obtain the initial error data matrix;

[0026] Specifically, according to the array element channel characteristics in the channel measurement model, the scanning angle range and step interval are set for each array element channel. These parameters determine the resolution and angle coverage of the pattern calculation. Based on the set scanning parameters, the pattern of each array element channel is segmented and calculated to obtain an angle sampling data set covering the entire scanning range. The angle sampling data set contains the response information of the array element pattern at each scanning angle, reflecting the distribution of the electromagnetic characteristics of the array element in different directions. Using the angle sampling data set, the gain characteristics of each array element channel at each scanning angle are normalized to obtain a standardized amplitude characteristic matrix. At the same time, according to the wavefront distortion propagation function in the channel measurement model, the phase response of each array element channel is complex operated to obtain a standardized phase characteristic matrix. The standardized amplitude characteristic matrix and the standardized phase characteristic matrix are superimposed in the complex domain to obtain the complex field distribution data of the array element channel. The complex field distribution data contains the comprehensive characteristics of amplitude and phase, and is an important intermediate data for describing the electromagnetic behavior of the array element. In order to analyze the electromagnetic characteristics of the array as a whole, the complex field distribution data is reconstructed according to the array arrangement relationship. The reconstructed field distribution data reflects the overall electromagnetic distribution characteristics of the array in the spatial domain. After the reconstruction is completed, the reconstructed field distribution data is subjected to discrete Fourier transform to convert it from the spatial domain to the frequency domain to obtain frequency domain characteristic data, which more intuitively displays the frequency response of the array element and its amplitude and phase error characteristics. According to the frequency domain characteristic data, the amplitude error and phase error of each array element channel are extracted to form preliminary error data. The extracted error data is normalized to generate an error eigenvector. In order to extract the main influencing factors from the error eigenvector, the principal component analysis method is applied to identify the main error influencing factors through dimensionality reduction calculation, and sort them according to their contribution to the error to form an error weight sequence. The error weight sequence is reorganized into an N×N dimensional matrix according to the array structure. The reorganized error matrix is ​​subjected to singular value decomposition, and the error characteristics are optimized, analyzed and corrected through the singular values ​​and eigenvectors obtained by decomposition. The singular value decomposition process decomposes the error matrix into multiple low-rank components, thereby extracting key error patterns and constructing an initial error data matrix.

[0027] S3, mapping the initial error data matrix to a two-dimensional weight matrix, and solving the optimal matching of the two-dimensional weight matrix to obtain a theoretical calibration coefficient matrix;

[0028] It should be noted that the amplitude and phase data in the initial error data matrix are dimensionally separated, extracted and transformed in the coordinate space to form a visualized two-dimensional plane amplitude and phase distribution diagram. The distribution diagram intuitively reflects the amplitude and phase error characteristics of each array element channel. On this basis, by analyzing each data point in the distribution diagram, the corresponding weight value is assigned according to the magnitude of its amplitude error and phase error to generate the initial weight distribution matrix. The Hungarian algorithm is used to perform linear programming modeling on the initial weight distribution matrix, and an optimization calculation model containing weight coefficients is constructed. The construction of the optimization model aims to find a set of optimal matching relationships by minimizing the weight error, thereby optimizing the calibration results. By incorporating the weight coefficient into the optimization model and mapping the array element channel number and weight distribution to the two-dimensional matrix space, a two-dimensional weight matrix is ​​obtained, which reflects the weight distribution and its optimization relationship between channels in the array. Iterative optimization parameters are set for the two-dimensional weight matrix. By taking the minimum calibration error as a constraint, the KM (Kuhn-Munkres) algorithm is introduced for iterative optimization. The application of the KM algorithm can construct an iterative optimization sequence according to the weight distribution, which continuously approaches the global optimal solution by repeatedly iteratively optimizing the element values ​​in the weight matrix. In the iterative process, a linear programming equation group is constructed based on the optimization sequence, and the equation group is numerically solved to obtain the matching weight coefficient of each array element channel. The channel matching weight coefficient is converted into specific amplitude compensation factor and phase compensation factor. To ensure the independence of the calibration results, the compensation factor is amplitude-phase decoupled to form a set of independent calibration parameter sets. These calibration parameters characterize the amplitude and phase characteristic compensation requirements of each channel respectively. In order to apply the calibration parameters to the overall model of the multi-channel phased array antenna, the independent calibration parameter set is reconstructed. The final theoretical calibration coefficient matrix is ​​formed by combining the amplitude calibration coefficient and the phase calibration coefficient according to the structural relationship of the array and mapping them to the N×N dimensional space.

[0029] S4, using a vector network analyzer to connect the standard gain antenna and the multi-channel phased array antenna, perform far-field scanning measurement on the multi-channel phased array antenna, and obtain measured amplitude and phase characteristic data;

[0030] Specifically, the distance of the measurement space is calculated according to the preset far-field conditions to ensure that the distance between the standard gain antenna and the multi-channel phased array antenna meets the far-field conditions. The calculation of the far-field conditions is based on the radar distance formula ,in is the diameter of the antenna, is the wavelength. The distance calculation result not only determines the size of the measurement space, but also guides the installation position of the standard gain antenna. The standard gain antenna is fixed on the precision displacement platform to ensure that it can move with high precision according to the predetermined path during the scanning process, forming the spatial layout of the standard measurement system. In order to realize the automation and precision of the scanning measurement, the motion trajectory of the precision displacement platform is planned and the scanning measurement path is designed. The planning of the scanning path includes the preset angle range and angle interval, which are determined according to the beam width and measurement accuracy requirements of the antenna. At the same time, the first port of the vector network analyzer is connected to the standard gain antenna through a phase-stable RF cable to ensure the phase stability of the signal transmission. The second port of the vector network analyzer is connected to the N array element channels of the multi-channel phased array antenna through the RF switch matrix to complete the connection of the measurement system. In order to ensure the measurement accuracy, the vector network analyzer is parameterized according to the working frequency band of the multi-channel phased array antenna. The specific parameters include the setting of the center frequency, bandwidth, transmission power level and intermediate frequency bandwidth to ensure that the measurement covers the working frequency range of the antenna and meets the dynamic range requirements of the signal. After completing the instrument configuration, the standard measurement system is calibrated using the THRU calibration and SOLT (Short-Open-Load-Thru) calibration methods. The system error correction term is obtained by collecting the S parameter data between the ports, especially the S11 and S21 parameters. The system error correction term is used to compensate for the amplitude and phase errors introduced by factors such as cables, switch matrices and connectors in the measurement system, thereby improving the accuracy of the measurement. Based on the system error correction term and the planned scanning measurement path, the precision displacement platform is controlled to scan step by step according to the preset angle interval. At each angle position, the S21 parameter data of the vector network analyzer is collected, and the transmission characteristics between the standard gain antenna and the multi-channel phased array antenna are recorded to form the original amplitude and phase data. The S21 parameter data describes the transmission gain and phase changes of the signal and is the key data for the amplitude and phase characteristic measurement. The collected original amplitude and phase data are compensated for the system error to remove the artifacts introduced by the system factors. The compensated data is reconstructed into a three-dimensional data array according to the scanning angle and channel number. The data array is a measurement data cube containing the amplitude and phase information of all channels at different angles. In order to improve the practicality and accuracy of the data, the measured data cube is subjected to amplitude-phase separation and noise reduction processing to separate the amplitude and phase characteristics of each channel. In the noise reduction process, the filtering algorithm or principal component analysis method is used to remove the random noise introduced in the measurement, so as to extract clearer and more accurate amplitude-phase data. Through the above steps, the measured amplitude-phase characteristic data is obtained.

[0031] S5, performing weighted least squares iterative calculation on the measured amplitude and phase characteristic data and the theoretical calibration coefficient matrix to obtain the target calibration compensation coefficient.

[0032] Among them, the measured amplitude and phase characteristic data are normalized to eliminate the deviation introduced by the different signal amplitude ranges in the measurement, and the data is standardized for subsequent calculations. While normalizing, the theoretical calibration coefficient matrix is ​​transformed into a complex domain, and it is converted from the amplitude and phase representation to a complex form, so that it can be directly fused with the normalized measured data. The result of the complex domain transformation and the normalized measured data together constitute the initial fusion data set. The measurement noise in the initial fusion data set is subjected to variance analysis. By calculating the variance of each data point, the distribution characteristics of the noise are quantified, and different weights are assigned to the measurement data according to the size of the variance. The principle of weight assignment is: the larger the noise variance, the smaller the weight; the smaller the noise variance, the higher the weight. The weight distribution forms a data credibility matrix. Based on the data credibility matrix, a weighted least squares objective function is established. In the objective function, the uncertainty of the measurement data and the certainty of the theoretical calibration coefficient are used as optimization parameters, the random measurement error term is introduced, and a hybrid optimization equation group is constructed. On the basis of the hybrid optimization equation group, the objective function is solved by an iterative calculation method. The maximum number of iterations and convergence criteria are set to ensure that the calculation can be completed within a reasonable time and meet the accuracy requirements. In each iteration, the parameter update amount in the gradient direction is calculated by taking the derivative of the hybrid optimization equation group. The gradient descent method is used to continuously adjust the optimization parameters so that the error of the objective function is gradually reduced and an iterative calculation sequence is generated. During the iteration process, each updated parameter falls into the parameter optimization interval, thereby ensuring the stability and accuracy of the calculation. As the iteration proceeds, the convergence analysis of the iterative calculation sequence is performed to determine whether the parameters have reached the optimal solution. Based on the minimum error criterion, the solution with the minimum error is selected as the final calibration compensation parameter. After the calibration compensation parameters are determined, these parameters are grouped according to the number of the array element channel, and the grouped parameters correspond to the amplitude and phase characteristics of each channel respectively. The grouped calibration compensation parameters are amplitude-phase decoupled, and the amplitude and phase are extracted separately to form independent compensation factors. In order to ensure the orthogonality and linear independence of the compensation factors, they are orthogonally transformed. The result of the orthogonal transformation mathematically ensures the orthogonality of the compensation factors and physically avoids the coupling effect between different channels. The results of the orthogonal transformation are mapped to the amplitude and phase control ports of each array element channel to form the target calibration compensation coefficients. These calibration compensation coefficients are directly used to adjust the amplitude and phase characteristics of the phased array antenna, eliminate the performance deviation caused by system errors, and thus achieve high-precision calibration of the antenna.

[0033] The amplitude compensation parameters and phase compensation parameters in the target calibration compensation coefficient are channel matched, and the compensation parameters corresponding to each array element channel are imported into its controller according to the channel number of the multi-channel phased array antenna. This process is completed through the hardware interface and software configuration to form the calibration configuration data of the antenna. The calibration configuration data contains the precise compensation values ​​of all array element channels to ensure that the amplitude and phase state of the antenna meets the theoretical calibration requirements. According to the main lobe beam scanning range of the antenna, the calibration configuration data is assigned according to the preset angle interval, and the amplitude and phase control amount is applied to each array element channel. The assignment operation is implemented through the controller and a complete beam scanning sequence is generated. The beam scanning sequence defines the radiation direction and amplitude and phase distribution of the antenna at different scanning angles, covering the complete scanning range of the antenna main lobe. After the beam scanning sequence is generated, far-field measurements are performed on each beam direction in the sequence. By using measurement equipment such as standard gain antennas and vector network analyzers, the radiation field intensity data of the entire airspace is collected to obtain three-dimensional pattern data. Based on the three-dimensional pattern data, the two-dimensional section data of the antenna E plane and H plane are extracted, corresponding to the radiation characteristics of the antenna on the two main planes. The extracted two-dimensional section data is normalized to obtain a standardized pattern curve, which reflects the relative value of the antenna's radiation intensity. According to the standardized pattern curve, the antenna's main lobe characteristic data is calculated, including key indicators such as half-power beam width, beam pointing, gain and null position. Among them, the half-power beam width defines the angle range of the antenna's main lobe, the beam pointing indicates the maximum radiation direction of the main lobe, the gain reflects the overall radiation capability of the antenna, and the null position describes the distribution of pattern nulls near the main lobe. At the same time, the data of the sidelobe area of ​​the standardized pattern curve is extracted, and the sidelobe characteristic data of the antenna is calculated by analyzing the extreme values ​​of the sidelobe level and the null depth. The sidelobe level indicates the radiation intensity outside the main lobe, while the null depth reflects the antenna's suppression capability in a specific direction. The antenna's main lobe characteristic data and sidelobe characteristic data are compared and analyzed before and after calibration, and the improvement effect of calibration on antenna performance is demonstrated by comparison. Based on these comparison results, a calibration performance evaluation report containing beam performance indicators and calibration accuracy data is generated. The report comprehensively summarizes the antenna performance after calibration, including the improvement of mainlobe gain, improvement of beam pointing accuracy, reduction of sidelobe level and optimization of null depth, and provides quantitative calibration accuracy data and performance improvement effects.

[0034] In one example, electromagnetic characteristics modeling is performed on N array element channels and a radome of a multi-channel phased array antenna to obtain a channel measurement model, including:

[0035] The transmitting units and receiving units of the multi-channel phased array antenna are arranged in a two-dimensional plane array to obtain a spatial distribution matrix of N array element channels;

[0036] Based on the spatial distribution matrix, the S parameters of the electromagnetic field coupling characteristics between adjacent array element channels are calculated to obtain an N-order S parameter matrix;

[0037] The area of ​​the radome is meshed, and the dielectric constant and loss tangent value of each unit in the mesh are numerically discretized to obtain the characteristic parameter matrix of the radome;

[0038] The weak form of the wave equation is constructed according to the characteristic parameter matrix of the radome, and the propagation path of the electromagnetic wave in the radome is analyzed by finite element method to obtain the wavefront distortion propagation function.

[0039] A set of simultaneous equations is established based on the N-order S-parameter matrix and the wavefront distortion propagation function, and the set of amplitude and phase distortion coefficients is obtained by numerically solving the simultaneous equations.

[0040] Based on the amplitude and phase distortion coefficients, a mathematical expression of electromagnetic characteristics including the mutual coupling effect of antenna channels and the influence of radome is established to obtain the overall propagation characteristic model.

[0041] The overall propagation characteristic model is input into the finite element calculation program, the electromagnetic field boundary conditions and excitation source parameters are set, and iterative calculation is performed to obtain the steady-state field distribution data;

[0042] According to the steady-state field distribution data, the radiation pattern of each array element channel is synthesized by the weighted superposition method, and the radiation pattern is associated with the amplitude and phase distortion coefficient set to obtain the channel measurement model.

[0043] In this example, the transmitting units and receiving units of the multi-channel phased array antenna are arranged in a two-dimensional planar array. Assume that the antenna array consists of The coordinates of each array element on the two-dimensional plane are Indicates that . These coordinates form the spatial distribution matrix of the antenna:

[0044] ;

[0045] in and They are The position of the array elements on the two-dimensional plane. Based on the spatial distribution matrix , calculate the electromagnetic field coupling characteristics between adjacent array elements. The coupling characteristics are expressed as Parameters indicate that It is Array element vs. The scattering parameters of an array element reflect the electromagnetic energy transmission relationship between two array elements. The calculation formula is:

[0046] ;

[0047] in Indicates The incident voltage wave of the array element, Indicates By calculating the reflected voltage wave of each array element , build Step Parameter matrix:

[0048] ;

[0049] This matrix captures the mutual coupling effects between the elements in the array. To account for the effect of the radome, the radome area is meshed into multiple small cells, each with a dielectric constant of and loss tangent The characteristic parameter matrix of the radome is formed after numerical discretization:

[0050] ;

[0051] in is the total number of grid cells, and Respectively The dielectric constant and loss tangent of each unit. Based on the characteristic parameter matrix of the radome , construct the weak form of the wave equation to describe the propagation characteristics of electromagnetic waves in the radome. The basic expression of the weak form of the wave equation is:

[0052] ;

[0053] in is the electromagnetic potential function, is the Laplace operator, is the volume of the grid unit. By using the finite element analysis method, the wave equation is numerically solved to obtain the wavefront distortion propagation function ,in is the spatial coordinate. Combined Parameter Matrix and the wavefront distortion propagation function , establish a set of simultaneous equations that describe the behavior of the entire array. The form of the simultaneous equations is:

[0054] ;

[0055] in Is Parameters and propagation functions The coefficient matrix formed by is the amplitude and phase distortion coefficient vector, is the external excitation vector. By numerically solving this set of equations, we can obtain the amplitude and phase distortion coefficients: , each component of which represents the amplitude and phase deviation of each channel. Based on the amplitude and phase distortion coefficient set , establish an overall propagation characteristic model including array mutual coupling effect and radome influence ,in Indicates the spatial position. This model is input into the finite element calculation program, boundary conditions and excitation source parameters are set, and the steady-state field distribution data is obtained through iterative calculation. , whose expression is:

[0056] ;

[0057] in is the amplitude-phase coefficient of the nth array element, j is the imaginary unit, which represents the imaginary part of the complex number, is the wave vector. Based on the steady-state field distribution data, the radiation pattern of each array element is synthesized using the weighted superposition method. ,in and is the azimuth and elevation angle. After the radiation pattern is associated with the amplitude and phase distortion coefficient set, a channel measurement model is formed to describe the overall electromagnetic characteristics of the multi-channel phased array antenna.

[0058] In one example, according to the channel measurement model, the electromagnetic field numerical calculation is performed on the multi-channel phased array antenna to obtain an initial error data matrix, including:

[0059] The scanning angle range and step interval are set for the array channel in the channel measurement model, and the directional diagram of the array channel is calculated segmentally according to the set scanning parameters to obtain an angle sampling data set;

[0060] Based on the angle sampling data set, the gain characteristics of each array element channel at each scanning angle are normalized to obtain a standardized amplitude characteristic matrix;

[0061] According to the wavefront distortion propagation function in the channel measurement model, complex operations are performed on the phase response of each array element channel to obtain a standardized phase characteristic matrix, and complex domain superposition operations are performed on the standardized amplitude characteristic matrix and the standardized phase characteristic matrix to obtain the complex field distribution data of the array element channel;

[0062] The complex field distribution data of the array element channel is reconstructed according to the array arrangement relationship, and the reconstructed field distribution is subjected to discrete Fourier transform to obtain frequency domain characteristic data. The amplitude error and phase error of each array element channel are extracted according to the frequency domain characteristic data, and the extracted error data are normalized to obtain the error characteristic vector;

[0063] The error eigenvector is subjected to principal component analysis to extract the main error influencing factors, which are sorted according to the degree of influence to obtain the error weight sequence. The error weight sequence is then reorganized into an N×N dimensional matrix form, and the reorganized matrix is ​​subjected to singular value decomposition to obtain the initial error data matrix.

[0064] In this example, the scanning angle range and step interval are set for the array channel in the channel measurement model. Suppose the scanning angle range is , the step interval is , then the scanning angle set is expressed as:

[0065] ;

[0066] in For the Sampling angles, is the number of angle sampling points. According to the set scanning angle set , for each array channel directivity diagram Perform segmented calculations to obtain the angle sampling data set . Indicates The array element is at an angle The directional pattern response below is calculated or simulated by the channel measurement model through formulas, for example:

[0067] ;

[0068] in It is The gain of an array element, is its initial phase deviation, is the angular response function of the directional pattern. Based on the angle sampling data set, the gain characteristics of each array channel at each scanning angle are normalized to eliminate the influence of amplitude deviation. The normalized amplitude characteristic matrix It is expressed as:

[0069] ;

[0070] in is the directional diagram at an angle At the same time, according to the wavefront distortion propagation function in the channel measurement model , perform complex operations on the phase response of each array element channel. Assume ,in is the wavefront phase function, then the phase characteristics of each array element are calculated by superposition:

[0071] ;

[0072] in It is The spatial coordinates of the array elements. The standardized phase characteristic matrix Then:

[0073] ;

[0074] in Represents the matrix norm. The standardized amplitude characteristic matrix And the phase characteristic matrix Perform complex domain superposition operations to obtain the complex field distribution data of the array element channel :

[0075] ;

[0076] The complex field distribution data According to the array arrangement relationship, it is reconstructed into a two-dimensional field distribution matrix, and a discrete Fourier transform is performed to obtain the frequency domain characteristic data. :

[0077] ;

[0078] in and is the frequency domain sampling point. The amplitude error of each array channel is extracted from the frequency domain characteristic data. and phase error , and normalize the extracted error data to form an error feature vector:

[0079] ;

[0080] The error eigenvector Perform principal component analysis to extract the main error influencing factors. Assume the covariance matrix is , then the principal components are obtained by eigenvalue decomposition:

[0081] ;

[0082] in For the eigenvalues, is the corresponding eigenvector. Sort the error influencing factors according to the size of the eigenvalue to obtain the error weight sequence. The error weight sequence is reorganized into Dimensional matrix form , and the matrix Perform singular value decomposition to obtain the initial error data matrix:

[0083] ;

[0084] in and is the unit orthogonal matrix, is a diagonal matrix whose diagonal elements are singular values.

[0085] In one example, the initial error data matrix is ​​mapped to a two-dimensional weight matrix, and the two-dimensional weight matrix is ​​optimally matched to obtain a theoretical calibration coefficient matrix, including:

[0086] The amplitude and phase data in the initial error data matrix are dimensionally separated and coordinate transformed to obtain a two-dimensional plane amplitude and phase distribution diagram, and the data points in the two-dimensional plane amplitude and phase distribution diagram are weighted according to the magnitude of the amplitude and phase errors to obtain an initial weight distribution matrix;

[0087] Based on the Hungarian algorithm, a linear programming model is built for the initial weight distribution matrix, an optimization calculation model including weight coefficients is constructed, and the optimization calculation model is mapped to a two-dimensional matrix space according to the array element channel number to obtain a two-dimensional weight matrix.

[0088] Iterative optimization parameters are set for the two-dimensional weight matrix, and the minimum calibration error is substituted into the KM algorithm as a constraint to obtain an iterative optimization sequence. A linear programming equation group is constructed based on the iterative optimization sequence, and the linear programming equation group is numerically solved to obtain the channel matching weight coefficient.

[0089] The channel matching weight coefficient is converted into an amplitude compensation factor and a phase compensation factor, and the compensation factor is amplitude-phase decoupled to obtain an independent calibration parameter set;

[0090] The independent calibration parameter set is reconstructed, and the amplitude calibration coefficient and the phase calibration coefficient are combined and mapped to the N×N dimensional space to obtain the theoretical calibration coefficient matrix.

[0091] In this example, the dimensions of the amplitude data and phase data in the initial error data matrix are separated. Assume that the initial error data matrix is ,in Indicates Channel pair Complex error value of the channel. Amplitude data matrix and phase data matrix Calculated by the following formula:

[0092] ;

[0093] in express The amplitude value of By separating the amplitude and phase data, a two-dimensional plane amplitude-phase distribution diagram is constructed, using coordinates Represents each data point. The data points in the two-dimensional plane amplitude-phase distribution diagram are weighted according to the magnitude of the amplitude and phase errors. Assuming the weight function Defined as:

[0094]

[0095] in and are the reference values ​​of amplitude and phase, and is the weight factor of amplitude and phase error. The initial weight distribution matrix is ​​generated by the above weight function , whose elements correspond . Based on the Hungarian algorithm, the initial weight distribution matrix Linear programming modeling is performed. The Hungarian algorithm is an optimization method for solving the optimal allocation problem, and its goal is to minimize the total weight error. The optimization objective function is expressed as:

[0096] ;

[0097] in Indicates Is the channel matched to the Channels, with the constraint that each channel can only be assigned to one other channel, i.e.:

[0098] ;

[0099] The above problem is solved by the Hungarian algorithm to obtain the optimal allocation matrix , and map it to the two-dimensional matrix space according to the channel number to generate a two-dimensional weight matrix For the obtained two-dimensional weight matrix , set the iterative optimization parameters, and substitute the minimum calibration error into the KM algorithm (Kuhn-Munkres algorithm) for further optimization. The objective function of iterative optimization is:

[0100] ;

[0101] in is the weight distribution variable vector. By setting the maximum number of iterations and convergence criteria , perform gradient descent optimization on the objective function, and the iterative update rule is:

[0102] ;

[0103] in is the learning rate, is the gradient vector. After the optimization is completed, the channel matching weight coefficient is obtained. The channel matching weight coefficient is converted into an amplitude compensation factor and phase compensation factor , calculated as follows:

[0104] ;

[0105] These compensation factors are decoupled to ensure the independence of amplitude and phase, forming an independent calibration parameter set. The independent calibration parameter set is reconstructed and the amplitude calibration coefficients are converted to and phase calibration coefficients Map to dimensional space. The reconstruction matrix is ​​expressed as:

[0106] ;

[0107] in represents the point-wise multiplication of elements, is the theoretical calibration coefficient matrix.

[0108] In one example, a vector network analyzer is used to connect a standard gain antenna and a multi-channel phased array antenna to perform far-field scanning measurement on the multi-channel phased array antenna to obtain measured amplitude and phase characteristic data, including:

[0109] Perform distance calculation on the measurement space according to the preset far-field conditions to obtain the distance calculation result, and install the standard gain antenna on the precision displacement platform according to the distance calculation result to obtain the standard measurement system space layout;

[0110] The motion trajectory of the precision displacement platform is planned to obtain the scanning measurement path, and the first port of the vector network analyzer is connected to the standard gain antenna through a phase-stable cable, and the second port is connected to the N array element channels of the multi-channel phased array antenna through the RF switch matrix to obtain the connection relationship of the measurement system;

[0111] Configure the parameters of the vector network analyzer according to the working frequency band of the multi-channel phased array antenna, set the center frequency, bandwidth, power level and intermediate frequency bandwidth, obtain the instrument measurement parameters, and perform THRU calibration and SOLT calibration on the standard measurement system based on the instrument measurement parameters, collect S parameter data between ports, and obtain the system error correction items;

[0112] According to the system error correction term and the scanning measurement path, the precision displacement platform is controlled to scan at the preset angle interval, the S21 parameter data is collected, and the original amplitude and phase data are obtained;

[0113] The original amplitude and phase data are compensated for system errors, and the compensated data are reconstructed into a three-dimensional data array according to the angle and channel number to obtain a measurement data cube. The measurement data cube is then subjected to amplitude-phase separation and data noise reduction, and the amplitude and phase characteristics of each channel at different angles are extracted to obtain the measured amplitude and phase characteristic data.

[0114] In this example, the distance to the measurement space is calculated based on the far-field condition of the antenna. The far-field condition satisfies the formula:

[0115] ;

[0116] in To measure distance, is the maximum physical size of the antenna (i.e., array aperture), is the working wavelength, is the speed of light, is the working frequency of the antenna. According to the calculation results, the standard gain antenna is fixed on the precision displacement platform and keeps the above calculated distance with the multi-channel phased array antenna under test. The platform accurately controls the position and angle of the standard gain antenna during measurement to form the spatial layout of the standard measurement system. The motion trajectory of the precision displacement platform is planned to generate a scanning measurement path. Assume that the measurement path covers a range of , the angle step interval is , then the set of scanning angles contained in the path is:

[0117] ;

[0118] The scanning path is the trajectory of the standard gain antenna swinging in sequence at these angles on the precision displacement platform. After the layout and path planning are completed, connect the measurement system. Connect the first port of the vector network analyzer (VNA) to the standard gain antenna through a phase-stable cable to ensure the phase consistency of the signal transmission. Connect the second port of the VNA to the The array element channels form a complete measurement system connection relationship. According to the working frequency band of the multi-channel phased array antenna, the vector network analyzer is configured with parameters. Set the center frequency ,bandwidth , power level and IF bandwidth After these parameters are configured, perform THRU and SOLT calibration on the measurement system and collect the THRU calibration is used to eliminate the insertion loss between ports, while SOLT (Short-Open-Load-Thru) calibration can compensate for the errors introduced by RF cables, connectors and switch matrices. The resulting system error correction term Contains magnitude and phase errors, such as:

[0119] ;

[0120] in is the amplitude error, is the phase error. According to the system error correction term and scanning measurement path obtained by calibration, the precision displacement platform is controlled to scan at the preset angle interval to collect Parameter data. For scanning angle , collected The parameter data is:

[0121] ;

[0122] in and Respectively represent Channels at angle The amplitude and phase response at the point. The collected original amplitude and phase data need to be compensated for the system error, and the correction formula is:

[0123] ;

[0124] The compensated data is based on the scanning angle and channel number Reconstruct into a three-dimensional data array to form a measurement data cube :

[0125] ;

[0126] For the measurement data cube , perform amplitude-phase separation and data noise reduction. The amplitude data and phase data are extracted as follows:

[0127] ;

[0128] In order to eliminate high-frequency noise in the measurement, a moving average filter is used to reduce the noise of the amplitude and phase data. The filtering formula is:

[0129] ;

[0130] in is the window size. Extract the amplitude and phase characteristics of each channel at different angles and record them as measured amplitude and phase characteristic data .

[0131] In one example, a weighted least squares iterative calculation is performed on the measured amplitude and phase characteristic data and the theoretical calibration coefficient matrix to obtain the target calibration compensation coefficient, including:

[0132] The measured amplitude and phase characteristic data are normalized, and the theoretical calibration coefficient matrix is ​​transformed into the complex domain to obtain the initial fusion data set;

[0133] Perform variance analysis on the measurement noise in the initial fusion data set, assign weights to the measurement data according to the variance, and obtain the data credibility matrix;

[0134] A weighted least square objective function is established based on the data credibility matrix, and deterministic constraints and random measurements are used as optimization parameters to obtain a hybrid optimization equation set.

[0135] Iterative calculation is performed based on the hybrid optimization equation group, the maximum number of iterations and the convergence criterion are set, the parameter optimization interval is obtained, and the hybrid optimization equation group is differentiated according to the parameter optimization interval, and the parameter update amount is calculated using the gradient descent method to obtain the iterative calculation sequence;

[0136] The convergence analysis of the iterative calculation sequence is performed, and the optimal solution is selected based on the minimum error criterion to obtain the calibration compensation parameters. The calibration compensation parameters are grouped according to the channel numbers to obtain the grouped parameters, and the amplitude and phase decoupling of the grouped parameters is performed to obtain independent compensation factors.

[0137] The independent compensation factors are orthogonally transformed to obtain orthogonal transformation results, and the orthogonal transformation results are mapped to the amplitude and phase control ports of each array element channel to obtain the target calibration compensation coefficients.

[0138] In this example, the measured amplitude-phase characteristic data is normalized to eliminate the dimension difference and unify the data range. Assume that the measured amplitude-phase characteristic data is ,in Indicates the channel number, represents the scanning angle, then the amplitude data and phase data They are:

[0139] ;

[0140] After normalization, the amplitude data and phase data are:

[0141] ;

[0142] At the same time, the theoretical calibration coefficient matrix Perform complex domain transformation and express it as:

[0143] ;

[0144] in is the theoretical amplitude coefficient, is the theoretical phase coefficient. The normalized measured data is combined with the theoretical calibration coefficient to generate the initial fusion data set:

[0145] ;

[0146] The variance analysis of the measurement noise in the initial fusion data set is performed to quantify the distribution characteristics of the noise. The variance under is:

[0147] ;

[0148] in is the number of repeated measurements, Angle The weight function is defined as follows:

[0149] ;

[0150] After weight assignment, the data credibility matrix is ​​formed Based on the data credibility matrix , establish the weighted least squares objective function. Let the true calibration coefficient be , then the objective function is:

[0151] ;

[0152] In the objective function, Emphasize high-confidence data and weaken low-confidence data. Combine the physical constraints of measurement noise and calibration coefficients to establish a hybrid optimization equation set:

[0153] ;

[0154] Iterate the hybrid optimization equations and set the maximum number of iterations and convergence criterion The initial calibration parameters are , the update formula is:

[0155] ;

[0156] in is the learning rate, is the gradient of the objective function. The specific form of the gradient is:

[0157] ;

[0158] During the iteration process, according to the convergence criterion Determine whether the optimal solution is reached. After convergence, the calibration compensation parameters are obtained. The calibration compensation parameters are grouped by channel number, and the amplitude compensation factor and phase compensation factor They are:

[0159] ;

[0160] The compensation factor is orthogonally transformed to ensure amplitude and phase decoupling. The orthogonal transformation formula is:

[0161] ;

[0162] in is the orthogonal transformation matrix. The transformation result is mapped to the amplitude and phase control ports of each array element channel to form the target calibration compensation coefficient.

[0163] In one example, the high precision multi-channel phased array radio metrology calibration method further includes:

[0164] Channel matching is performed on the amplitude compensation parameters and phase compensation parameters in the target calibration compensation coefficients, and the compensation parameters are imported into the controller of each array element channel in the multi-channel phased array antenna based on the channel number to obtain calibration configuration data;

[0165] Assign the calibration configuration data according to the angle interval within the main lobe beam scanning range, apply amplitude and phase control to each array element channel, and obtain a beam scanning sequence;

[0166] Perform far-field measurement on each beam direction in the beam scanning sequence, collect radiation field intensity data in the entire airspace, obtain three-dimensional pattern data, extract two-dimensional section data of the E plane and H plane based on the three-dimensional pattern data, normalize the two-dimensional section data, and obtain a standardized pattern curve;

[0167] Calculate the half-power beam width, beam pointing, gain and zero point position according to the standardized radiation pattern curve to obtain the antenna main lobe characteristic data;

[0168] Extract data from the sidelobe area of ​​the standardized pattern curve, perform extreme value statistics of the sidelobe level and the null depth, and obtain antenna sidelobe characteristic data;

[0169] The antenna main lobe characteristic data and the antenna side lobe characteristic data are compared before and after calibration to generate a calibration performance evaluation report containing beam performance indicators and calibration accuracy data.

[0170] In this example, the compensation coefficients are calibrated according to the target , extract amplitude compensation parameters and phase compensation parameters , which respectively represent the The amplitude and phase compensation values ​​of each channel are calculated as follows:

[0171] ;

[0172] The extracted parameters are compared with the channel number of the antenna To match, and Import the controller of each array channel in the multi-channel phased array antenna to form calibration configuration data. The calibration configuration data includes the amplitude and phase control information of each array channel after calibration. According to the main lobe beam scanning range of the antenna, the calibration configuration data is assigned according to the preset angle interval. Assume that the scanning range is , the angle interval is , then the scanning angle set is:

[0173] ;

[0174] in For each angle , apply amplitude and phase control according to the calibration configuration data to generate a beam scanning sequence:

[0175] ;

[0176] in It is the phase step amount, which is used to change the scanning direction. After the beam scanning sequence is generated, each beam direction in the sequence is measured in the far field, and the radiation field intensity data of the entire airspace is collected to obtain the three-dimensional directional pattern data. ,in and Represents azimuth and elevation respectively. The measurement of three-dimensional directional pattern data is completed by far-field test equipment, and the measurement data is expressed as:

[0177] ;

[0178] in is the amplitude distribution of the radiation field, is the phase distribution. Extract the two-dimensional cross-sectional data of the E plane (electric field surface) and the H plane (magnetic field surface) from the three-dimensional directional pattern data. These two cross-sectional data represent the radiation characteristics of the antenna on the two main cross sections. Assume that the E plane corresponds to Plane, H plane corresponding Plane, the section data is:

[0179] ;

[0180] The extracted two-dimensional section data is normalized to obtain the standardized direction pattern curve:

[0181] ;

[0182] Based on the standardized radiation pattern curve, the main lobe characteristic data of the antenna is calculated. The half-power beam width HPBW is calculated by finding the angle range corresponding to the -3dB point of the radiation pattern curve:

[0183] ;

[0184] Beam pointing is the position of the main lobe maximum value, gain is the maximum value of the directional pattern curve. The zero point position corresponds to the intersection of the directional pattern curve:

[0185] ;

[0186] For data extraction in the sidelobe region, the sidelobe level (SLL) is defined as the maximum radiation intensity outside the main lobe:

[0187] ;

[0188] The null depth is the minimum value of the radiation intensity drop from the main lobe to the side lobe of the pattern curve. Compare the antenna main lobe characteristic data and side lobe characteristic data obtained by the above calculations before and after calibration. Generate a calibration performance evaluation report, which includes beam performance indicators (such as gain, beam width, side lobe level, etc.) and calibration accuracy data (such as main lobe pointing error, changes in side lobe suppression capability, etc.). The calibration effect is intuitively displayed through charts and data analysis.

[0189] Reference Figure 2 This embodiment provides a high-precision multi-channel phased array radio metrology calibration system, including:

[0190] Modeling module 1, used for modeling electromagnetic characteristics of N array element channels and antenna cover of the multi-channel phased array antenna to obtain a channel measurement model;

[0191] The calculation module 2 is used to perform electromagnetic field numerical calculation on the multi-channel phased array antenna according to the channel measurement model to obtain an initial error data matrix;

[0192] A solution module 3 is used to map the initial error data matrix to a two-dimensional weight matrix, and perform an optimal matching solution on the two-dimensional weight matrix to obtain a theoretical calibration coefficient matrix;

[0193] The measurement module 4 is used to connect the standard gain antenna and the multi-channel phased array antenna using a vector network analyzer, perform far-field scanning measurement on the multi-channel phased array antenna, and obtain measured amplitude and phase characteristic data;

[0194] Iteration module 5 is used to perform weighted least squares iterative calculation on the measured amplitude and phase characteristic data and the theoretical calibration coefficient matrix to obtain the target calibration compensation coefficient.

[0195] In this embodiment, for the specific implementation of each unit in the above system embodiment, please refer to the above method embodiment, which will not be repeated here.

[0196] It should be noted that, in this article, the terms "include", "comprises" or any other variations thereof are intended to cover non-exclusive inclusion, so that a process, system, article or method including a series of elements includes not only those elements, but also includes other elements not explicitly listed, or also includes elements inherent to such process, system, article or method. In the absence of further restrictions, an element defined by the sentence "comprises a ..." does not exclude the presence of other identical elements in the process, system, article or method including the element.

[0197] The above description is only a preferred embodiment of the present invention, and does not limit the patent scope of the present invention. Any equivalent structure or equivalent process transformation made by using the contents of the present invention specification and drawings, or directly or indirectly applied in other related technical fields, are also included in the patent protection scope of the present invention.

Claims

1. A high-precision multi-channel phased array radio metrology calibration method, characterized in that: The following steps are involved: The electromagnetic characteristics of the N array element channels and radome of the multi-channel phased array antenna are modeled to obtain a channel measurement model; According to the channel measurement model, performing electromagnetic field numerical calculation on the multi-channel phased array antenna to obtain an initial error data matrix; Mapping the initial error data matrix to a two-dimensional weight matrix, and performing optimal matching on the two-dimensional weight matrix to obtain a theoretical calibration coefficient matrix; A vector network analyzer is used to connect a standard gain antenna and the multi-channel phased array antenna, and a far-field scanning measurement is performed on the multi-channel phased array antenna to obtain measured amplitude and phase characteristic data; A weighted least squares iterative calculation is performed on the measured amplitude-phase characteristic data and the theoretical calibration coefficient matrix to obtain a target calibration compensation coefficient.

2. The high-precision multi-channel phased array radio metrology calibration method according to claim 1, characterized in that: The electromagnetic characteristic modeling of N array element channels and a radome of the multi-channel phased array antenna is performed to obtain a channel measurement model, including: The transmitting units and receiving units of the multi-channel phased array antenna are arranged in a two-dimensional plane array to obtain a spatial distribution matrix of N array element channels; Performing S parameter calculation on the electromagnetic field coupling characteristics between adjacent array element channels based on the spatial distribution matrix to obtain an N-order S parameter matrix; The area of ​​the radome is meshed, and the dielectric constant and loss tangent value of each unit in the mesh are numerically discretized to obtain the characteristic parameter matrix of the radome; A weak form of the wave equation is constructed according to the characteristic parameter matrix of the radome, and a finite element analysis is performed on the propagation path of the electromagnetic wave in the radome to obtain a wavefront distortion propagation function; Establishing a set of simultaneous equations based on the N-order S-parameter matrix and the wavefront distortion propagation function, and numerically solving the set of simultaneous equations to obtain a set of amplitude and phase distortion coefficients; Based on the amplitude and phase distortion coefficient set, a mathematical expression of electromagnetic characteristics including the mutual coupling effect of antenna channels and the influence of the radome is established to obtain an overall propagation characteristic model; Inputting the overall propagation characteristic model into a finite element calculation program, setting electromagnetic field boundary conditions and excitation source parameters, performing iterative calculations, and obtaining steady-state field distribution data; According to the steady-state field distribution data, a weighted superposition method is used to synthesize the radiation pattern of each array element channel, and the radiation pattern is associated and mapped with the amplitude and phase distortion coefficient set to obtain a channel measurement model.

3. The high-precision multi-channel phased array radio metrology calibration method according to claim 2, characterized in that: The method of performing electromagnetic field numerical calculation on the multi-channel phased array antenna according to the channel measurement model to obtain an initial error data matrix includes: Setting a scanning angle range and a step interval for the array channel in the channel measurement model, performing segmented calculations on the directional diagram of the array channel according to the set scanning parameters, and obtaining an angle sampling data set; Based on the angle sampling data set, the gain characteristic of each array element channel at each scanning angle is normalized to obtain a standardized amplitude characteristic matrix; According to the wavefront distortion propagation function in the channel measurement model, a complex operation is performed on the phase response of each array element channel to obtain a standardized phase characteristic matrix, and a complex domain superposition operation is performed on the standardized amplitude characteristic matrix and the standardized phase characteristic matrix to obtain complex field distribution data of the array element channel; Reconstructing the complex field distribution data of the array element channel according to the array arrangement relationship, performing discrete Fourier transform on the reconstructed field distribution to obtain frequency domain characteristic data, extracting the amplitude error and phase error of each array element channel according to the frequency domain characteristic data, normalizing the extracted error data, and obtaining an error feature vector; The error characteristic vector is subjected to principal component analysis to extract the main error influencing factors, and they are sorted according to the degree of influence to obtain an error weight sequence, and the error weight sequence is reorganized into an N×N dimensional matrix form, and the reorganized matrix is ​​subjected to singular value decomposition to obtain an initial error data matrix.

4. The high-precision multi-channel phased array radio metrology calibration method according to claim 3 is characterized in that: The initial error data matrix is ​​mapped to a two-dimensional weight matrix, and the two-dimensional weight matrix is ​​optimally matched and solved to obtain a theoretical calibration coefficient matrix, including: Performing dimension separation and coordinate transformation on the amplitude and phase data in the initial error data matrix to obtain a two-dimensional plane amplitude and phase distribution diagram, and assigning weights to the data points in the two-dimensional plane amplitude and phase distribution diagram according to the magnitude of the amplitude and phase errors to obtain an initial weight distribution matrix; Based on the Hungarian algorithm, a linear programming model is performed on the initial weight distribution matrix to construct an optimization calculation model including weight coefficients, and the optimization calculation model is mapped to a two-dimensional matrix space according to the array element channel number to obtain a two-dimensional weight matrix; Iterative optimization parameters are set for the two-dimensional weight matrix, the minimum calibration error is substituted into the KM algorithm as a constraint condition to obtain an iterative optimization sequence, and a linear programming equation group is constructed according to the iterative optimization sequence, and the linear programming equation group is numerically solved to obtain a channel matching weight coefficient; Converting the channel matching weight coefficient into an amplitude compensation factor and a phase compensation factor, performing amplitude-phase decoupling on the compensation factor, and obtaining an independent calibration parameter set; The independent calibration parameter set is subjected to matrix reconstruction, and the amplitude calibration coefficient and the phase calibration coefficient combination are mapped to an N×N dimensional space to obtain a theoretical calibration coefficient matrix.

5. The high-precision multi-channel phased array radio metrology calibration method according to claim 4, characterized in that: The method of using a vector network analyzer to connect a standard gain antenna and the multi-channel phased array antenna to perform far-field scanning measurement on the multi-channel phased array antenna to obtain measured amplitude and phase characteristic data includes: Performing distance calculation on the measurement space according to preset far-field conditions to obtain a distance calculation result, and installing a standard gain antenna on a precision displacement platform according to the distance calculation result to obtain a standard measurement system spatial layout; The motion trajectory of the precision displacement platform is planned to obtain a scanning measurement path, and the first port of the vector network analyzer is connected to the standard gain antenna through a phase-stable cable, and the second port is connected to the N array element channels of the multi-channel phased array antenna through a radio frequency switch matrix to obtain a measurement system connection relationship; According to the working frequency band of the multi-channel phased array antenna, the vector network analyzer is configured with parameters, the center frequency, bandwidth, power level and intermediate frequency bandwidth are set, and the instrument measurement parameters are obtained; based on the instrument measurement parameters, the standard measurement system is THRU calibrated and SOLT calibrated, and S parameter data between ports is collected to obtain system error correction items; According to the system error correction term and the scanning measurement path, the precision displacement platform is controlled to scan at a preset angle interval, and S21 parameter data is collected to obtain original amplitude and phase data; The original amplitude and phase data are compensated for system errors, and the compensated data are reconstructed into a three-dimensional data array according to the angle and channel number to obtain a measurement data cube. The measurement data cube is subjected to amplitude and phase separation and data noise reduction, and the amplitude and phase characteristics of each channel at different angles are extracted to obtain the measured amplitude and phase characteristic data.

6. The high-precision multi-channel phased array radio metrology calibration method according to claim 5, characterized in that: The step of performing weighted least squares iterative calculation on the measured amplitude-phase characteristic data and the theoretical calibration coefficient matrix to obtain a target calibration compensation coefficient includes: Normalizing the measured amplitude and phase characteristic data, and performing complex domain transformation on the theoretical calibration coefficient matrix to obtain an initial fusion data set; Performing variance analysis on the measurement noise in the initial fusion data set, assigning weights to the measurement data according to the variance, and obtaining a data credibility matrix; A weighted least square objective function is established based on the data credibility matrix, and deterministic constraints and random measurements are used as optimization parameters to obtain a hybrid optimization equation group; Iterative calculation is performed based on the hybrid optimization equation group, a maximum number of iterations and a convergence criterion are set, a parameter optimization interval is obtained, and a derivative operation is performed on the hybrid optimization equation group according to the parameter optimization interval, and a parameter update amount is calculated using a gradient descent method to obtain an iterative calculation sequence; Performing convergence analysis on the iterative calculation sequence, selecting the optimal solution based on the minimum error criterion to obtain calibration compensation parameters, grouping the calibration compensation parameters according to channel numbers to obtain grouped parameters, performing amplitude-phase decoupling on the grouped parameters to obtain independent compensation factors; An orthogonal transformation is performed on the independent compensation factor to obtain an orthogonal transformation result, and the orthogonal transformation result is mapped to the amplitude and phase control port of each array element channel to obtain a target calibration compensation coefficient.

7. The high-precision multi-channel phased array radio metrology calibration method according to claim 6, characterized in that: The high-precision multi-channel phased array radio metrology calibration method further comprises: Channel matching is performed on the amplitude compensation parameter and the phase compensation parameter in the target calibration compensation coefficient, and the compensation parameter is imported into the controller of each array element channel in the multi-channel phased array antenna based on the channel number to obtain calibration configuration data; Assigning the calibration configuration data according to the angle interval within the main lobe beam scanning range, applying amplitude and phase control amounts to each array element channel, and obtaining a beam scanning sequence; Performing far-field measurement on each beam direction in the beam scanning sequence, collecting radiation field intensity data of the entire airspace, obtaining three-dimensional pattern data, extracting two-dimensional section data of the E plane and the H plane based on the three-dimensional pattern data, normalizing the two-dimensional section data, and obtaining a standardized pattern curve; Calculating the half-power beam width, beam pointing, gain and zero point position according to the standardized pattern curve to obtain antenna main lobe characteristic data; Extracting data from the sidelobe region of the standardized pattern curve, performing extreme value statistics of the sidelobe level and the null depth, and obtaining antenna sidelobe characteristic data; The antenna main lobe characteristic data and the antenna side lobe characteristic data are compared before and after calibration to generate a calibration performance evaluation report including beam performance indicators and calibration accuracy data.

8. A high-precision multi-channel phased array radio metrology calibration system, characterized in that: For implementing the steps of the method according to any one of claims 1 to 7, the system comprises: A modeling module is used to model the electromagnetic characteristics of N array element channels and antenna covers of a multi-channel phased array antenna to obtain a channel measurement model; A calculation module, used for performing electromagnetic field numerical calculation on the multi-channel phased array antenna according to the channel measurement model to obtain an initial error data matrix; A solution module, used for mapping the initial error data matrix to a two-dimensional weight matrix, and performing an optimal matching solution on the two-dimensional weight matrix to obtain a theoretical calibration coefficient matrix; A measurement module, used to connect a standard gain antenna and the multi-channel phased array antenna using a vector network analyzer, perform far-field scanning measurement on the multi-channel phased array antenna, and obtain measured amplitude and phase characteristic data; The iterative module is used to perform weighted least squares iterative calculation on the measured amplitude-phase characteristic data and the theoretical calibration coefficient matrix to obtain a target calibration compensation coefficient.

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