CN111308412B

CN111308412B - Antenna array correction method and device, computer equipment and storage medium

Info

Publication number: CN111308412B
Application number: CN202010252889.8A
Authority: CN
Inventors: 龙必起
Original assignee: Shenzhen Huazhi Xinlian Technology Co ltd
Current assignee: Shenzhen Huazhi Xinlian Technology Co ltd
Priority date: 2020-04-02
Filing date: 2020-04-02
Publication date: 2021-02-23
Anticipated expiration: 2040-04-02
Also published as: CN111308412A

Abstract

The application relates to a method and a device for correcting an antenna array, computer equipment and a storage medium, wherein after signal source data of the antenna array which is incident to a seven-array-element hexagon from a plurality of time-sharing directions are obtained, a coupling matrix in each signal source data and an amplitude error matrix of the antenna array comprising an amplitude error matrix and a phase error matrix are jointly updated through a preset alternating iteration method to obtain a target coupling matrix and a target amplitude error matrix, newly received signal source data are compensated and corrected according to the target coupling matrix and the target amplitude error matrix, and the obtained compensated and corrected signal source data represent the signal source data which are received after the antenna array error is corrected. The method can effectively carry out combined correction on the errors of the seven-array element hexagonal antenna array.

Description

Antenna array correction method and device, computer equipment and storage medium

Technical Field

The present application relates to the field of signal processing technologies, and in particular, to a method and an apparatus for calibrating an antenna array, a computer device, and a storage medium.

Background

In array signal processing, whether beam forming or direction of arrival estimation is studied, the basis of most algorithms is established in the case of an ideal antenna array.

In actual engineering, due to the change of temperature, the gain of the receiving channel of each array element in the array is different, and the influence of factors such as mutual coupling exists between the array elements, the array has errors such as amplitude error, phase error and mutual coupling error, so that the array processing algorithm is degraded to a certain extent or even fails. At present, when various array errors are corrected, because an error model of the phase errors and the amplitude errors of the array is a diagonal array, the phase errors and the amplitude errors can be corrected together, but because a mutual coupling matrix model in a common array has no special structure and is difficult to process, most of mutual coupling correction algorithms are researched by uniform circular arrays and uniform line arrays, and cannot be subjected to combined correction in the common array, for example, a seven-array-element hexagonal array, and the common correction algorithm based on the uniform circular arrays and the uniform line arrays cannot be directly applied to the seven-array-element hexagonal array.

Therefore, an effective joint correction method is lacking for a seven-element hexagonal antenna array.

Disclosure of Invention

In view of the above, it is necessary to provide a method, an apparatus, a computer device, and a storage medium for correcting an antenna array, which can effectively perform joint correction of errors of a seven-element hexagonal antenna array.

In a first aspect, the present application provides a method for calibrating an antenna array, the method including:

acquiring signal source data which are incident to a seven-array-element hexagonal antenna array from a plurality of time-sharing directions; each signal source data comprises a coupling matrix of the antenna array and a phase amplitude error matrix of the antenna array; the phase amplitude error matrix comprises an amplitude error matrix and a phase error matrix;

performing combined updating on the coupling matrix and the phase amplitude error matrix through a preset alternating iteration method to obtain a target coupling matrix and a target phase amplitude error matrix; the alternating iteration method comprises the steps of converting a coupling matrix and a phase amplitude error matrix into corresponding replacement vectors comprising all elements respectively through a transformation matrix determined by an error model based on a seven-array element hexagonal antenna array;

according to the target coupling matrix and the target phase amplitude error matrix, compensating and correcting newly received signal source data; and the signal source data after compensation correction represents the signal source data received after the antenna array error correction.

In a second aspect, the present application provides a calibration apparatus for an antenna array, the apparatus comprising:

the signal data acquisition module is used for acquiring signal source data which are incident to the seven-array-element hexagonal antenna array from a plurality of time-sharing directions; each signal source data comprises a coupling matrix of the antenna array and a phase amplitude error matrix of the antenna array; the phase amplitude error matrix comprises an amplitude error matrix and a phase error matrix;

the joint updating module is used for carrying out joint updating on the coupling matrix and the phase amplitude error matrix through a preset alternative iteration method to obtain a target coupling matrix and a target phase amplitude error matrix; the alternating iteration method comprises the steps of converting the coupling matrix and the phase amplitude error matrix into corresponding replacement vectors comprising all elements respectively through a transformation matrix determined by an error model based on a seven-array element hexagonal antenna array;

the compensation correction module is used for performing compensation correction on newly received signal source data according to the target coupling matrix and the target phase amplitude error matrix; and the signal source data after compensation correction represents the signal source data received after the antenna array error correction.

In a third aspect, the present application provides a computer device comprising a memory and a processor, the memory storing a computer program, the processor implementing the steps of the method in any of the first aspect embodiments when executing the computer program.

In a fourth aspect, the present application provides a computer-readable storage medium having stored thereon a computer program which, when executed by a processor, performs the steps of the method of any of the embodiments of the first aspect described above.

After signal source data of an antenna array which is incident to a seven-array-element hexagonal antenna array from a plurality of time-sharing directions are obtained, a coupling matrix in each signal source data and a phase-amplitude error matrix of the antenna array comprising an amplitude error matrix and a phase error matrix are jointly updated through a preset alternating iteration method to obtain a target coupling matrix and a target phase-amplitude error matrix, newly received signal source data are compensated and corrected according to the target coupling matrix and the target phase-amplitude error matrix, and the obtained compensated and corrected signal source data represent the signal source data which are received after the antenna array error is corrected. In the method, after a plurality of known signal source data are received, the adopted alternating iteration method comprises the step of respectively converting the coupling matrix and the phase amplitude error matrix into corresponding replacement vectors comprising all elements through a transformation matrix determined based on an error model of the seven-array-element hexagonal antenna array, so that the improved alternating iteration method can be used on the seven-array-element hexagonal antenna array, the errors of the seven-array-element hexagonal antenna array are effectively corrected in a combined mode, and all the errors in the seven-array-element hexagonal array are considered through the combined updating of the coupling matrix and the phase amplitude error matrix, and the errors of the seven-array-element hexagonal array are corrected more comprehensively.

Drawings

Fig. 1 is a diagram illustrating an exemplary embodiment of an antenna array calibration method;

fig. 2 is a flowchart illustrating a calibration method for an antenna array according to an embodiment;

FIG. 2a is a schematic diagram of M narrow-band signals being incident on a seven-array element hexagonal array in a time-sharing manner;

FIG. 3 is a flow chart illustrating a method for calibrating an antenna array according to an embodiment;

FIG. 4 is a flowchart illustrating a method for calibrating an antenna array according to an embodiment;

FIG. 5 is a flow chart illustrating a method for calibrating an antenna array according to an embodiment;

FIG. 6 is a flow chart illustrating a method for calibrating an antenna array according to an embodiment;

FIG. 7 is a flowchart illustrating a method for calibrating an antenna array according to an embodiment;

FIG. 8 is a schematic flow chart of a seven-element hexagonal array active joint calibration method according to an embodiment;

FIG. 9 is a simulation diagram of MUSIC spectrum experiment before and after seven-array element hexagonal array correction;

fig. 10 is a block diagram of a calibration apparatus for an antenna array according to an embodiment.

Detailed Description

In order to make the objects, technical solutions and advantages of the present application more apparent, the present application is described in further detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative of the present application and are not intended to limit the present application.

Referring to fig. 1, the present application provides an application environment of a calibration method for an antenna array, in which a computer device includes a processor, a memory, a network interface, and a database connected by a system bus. Wherein the processor is configured to provide computational and control capabilities. The memory comprises a nonvolatile storage medium and an internal memory. The non-volatile storage medium stores an operating system, a computer program, and a database. The internal memory provides an environment for the operation of an operating system and computer programs in the non-volatile storage medium. The database of the computer device is used for storing data of a calibration method of the antenna array. The network interface of the computer device is used for communicating with an external terminal through a network connection. The computer program is executed by a processor to implement a method of calibration of an antenna array. It is to be understood that the internal structure of the computer device shown in fig. 1 is an example only and is not intended to be limiting.

In the actual antenna array signal processing, due to the influence of factors such as temperature variation, difference of the receiving channel gain of each array element in the antenna array, mutual coupling between the array elements and the like, many array processing algorithms are degraded to a certain extent or even fail. For example, in the aspect of beam forming, due to mismatching between an actual array manifold and an ideal array manifold caused by array errors, most adaptive beam forming algorithms cannot form a beam in a target direction, and even suppress signals in the target direction; as another example, in estimating the direction of arrival, a phase error of the array may cause the MUSIC algorithm to fail to peak in the correct direction.

For amplitude errors, phase errors, mutual coupling errors and the like of the array, a single error correction algorithm and a combined correction algorithm exist, wherein the single error correction algorithm is a correction algorithm provided for amplitude or phase or mutual coupling, and the combined correction is to correct multiple errors. If it is necessary to correct multiple errors at once, it is easier to combine the phase error and the amplitude error, but in the case of cross-coupling correction, it is difficult to process the errors because the cross-coupling matrix model has no special structure in the general array.

Most of the research of mutual coupling correction algorithms at present is based on uniform circular arrays and uniform linear arrays, because the mutual coupling model of the two arrays can be modeled as a Toeplitz matrix. For example, a seven-element hexagonal array is also more practical, but the common correction algorithm based on uniform circular arrays and uniform linear arrays cannot be directly applied to the seven-element hexagonal array. On the other hand, from the prior knowledge of whether the direction of the signal source is needed, the correction algorithm of the array can be divided into active correction and self-correction, the active correction needs the direction information of the signal source, but the algorithm is simple, the calculated amount is relatively small, the self-correction can achieve real-time correction, but the calculated amount is large, and the local optimal solution is easy to fall into. Therefore, more active correction algorithms are generally used in engineering.

Based on this, the embodiments of the present application provide a method and an apparatus for correcting an antenna array, a computer device, and a storage medium, which can effectively perform joint correction on errors of a seven-element hexagonal antenna array. The following describes in detail the technical solutions of the present application and how the technical solutions of the present application solve the above technical problems by embodiments and with reference to the drawings. The following several specific embodiments may be combined with each other, and details of the same or similar concepts or processes may not be repeated in some embodiments. It should be noted that, in the calibration method for an antenna array provided in the present application, the execution main bodies of fig. 2 to 9 are computer devices, where the execution main bodies of fig. 2 to 9 may also be calibration apparatuses for an antenna array, where the apparatuses may be implemented as part of or all of the computer devices by software, hardware, or a combination of software and hardware.

In order to make the objects, technical solutions and advantages of the embodiments of the present application clearer, the technical solutions in the embodiments of the present application will be clearly and completely described below with reference to the drawings in the embodiments of the present application, and it is obvious that the described embodiments are some embodiments of the present application, but not all embodiments.

In an embodiment, fig. 2 provides a method for correcting an antenna array, where this embodiment relates to a specific process in which a computer device receives, through an array receiving end, a plurality of antenna array signal source data with known directions and time-sharing incidence on a seven-element hexagon, and corrects an array error jointly according to the received signal source data, as shown in fig. 2, the method includes:

s101, signal source data which are incident to a seven-array-element hexagonal antenna array from a plurality of time-sharing directions are obtained; each signal source data comprises a coupling matrix of the antenna array and a phase amplitude error matrix of the antenna array; the phase-amplitude error matrix includes an amplitude error matrix and a phase error matrix.

In practical application, when the antenna array is subjected to joint correction, a correction scenario is simulated in a computer device, wherein the correction scenario refers to fig. 2a, and fig. 2a shows M narrowband signals S_i1,2,3, M, time-sharing incidence 7-array element hexagonal array schematic diagram, wherein Z1... Z7 denotes a 7-array element hexagonal antenna array.

The computer equipment acquires signal source data which are incident to the seven-array-element hexagonal antenna array from a plurality of time-sharing directions based on the correction scene of fig. 2a, wherein each signal source data comprises a coupling matrix of the antenna array and a phase amplitude error matrix of the antenna array; the phase-amplitude error matrix is a combination of the amplitude error matrix and the phase error matrix.

Illustratively, in FIG. 2a, the far field has M narrow-band sources time-sharing the direction of arrival θ_kAnd k is 1,2,3, M is incident on a 7-array element hexagonal array, then for an array receiving end, the received data of the kth signal source can be represented as:

X_k＝C*G*P*a_k*S_k+N_k

wherein, X_kA data matrix of a kth source received by the array is a matrix with dimensions of 7 xL, wherein the fast beat number of L data samples; c is a coupling matrix among array elements with 7 multiplied by 7 dimensions; g is an array amplitude error matrix of 7 multiplied by 7 dimensions; p is an array phase error matrix of 7 x 7 dimensions; a is_kThe array manifold of the kth source is a 7 x 1 dimensional column vector; s_kA signal of a kth source is a row vector with dimension of 1 xL; n is a radical of_kIs white gaussian noise with a mean value of zero, and is a matrix with dimensions of 7 × L.

Further, C, G, P, a_kThe specific form of (b) can be expressed as:

wherein, in the above formula, c_iFor the mutual coupling coefficient between the array elements, c is₁And c₅Are equal to c₂And c₄Are equal but are represented separately for subsequent calculations; wherein, g_iI 1,2, 7 is an amplitude error coefficient of each array element; wherein,

is the phase error coefficient of each array element. Wherein,

the phase difference generated by the ith array element to the kth information source is a seven-array-element hexagon.

As can be seen from the above example, the seven-element hexagonal array receives source data X_kThe matrix comprises a coupling matrix C, an amplitude error matrix G and a phase error matrix P, wherein the amplitude error matrix G and the phase error matrix P are both diagonal matrices, so that the two matrices are collectively called a phase amplitude error matrix Γ G P, and then X is based on the matrix_kThe expression of (c) can be simplified as: x_k＝C*Γ*a_k*S_k+N_kThat is, for the receiving end of the array in the computer device, the kth signal source data of the M received signal source data can be represented as X_k＝C*Γ*a_k*S_k+N_k。

S102, jointly updating the coupling matrix and the phase amplitude error matrix through a preset alternating iteration method to obtain a target coupling matrix and a target phase amplitude error matrix; the alternating iteration method comprises the step of converting the coupling matrix and the phase amplitude error matrix into corresponding replacement vectors comprising all elements of each element respectively through a transformation matrix determined based on an error model of the seven-element hexagonal antenna array.

In the correction scene, the signals incident to the seven-array hexagonal antenna array in each time-sharing direction are preset signals, and the signal source data X are_kIs known and is a standard signal without array errors, the compensation value needed to compensate each error of the array can be determined by only de-coupling the matrix C, the amplitude error matrix G and the phase error matrix P, i.e. at X_k＝C*Γ*a_k*S_k+N_kThe required solution is the coupling matrix C and the phase amplitude error matrix Γ.

The computer equipment respectively updates the coupling matrix and the phase amplitude error matrix based on the signal source data to solve a target coupling matrix and a target phase amplitude error matrix, and particularly, when the coupling matrix and the phase amplitude error matrix are updated, the computer equipment adopts a preset alternative iteration method to update, wherein the alternative iteration method comprises the steps of respectively converting the coupling matrix and the phase amplitude error matrix into corresponding replacement vectors comprising all elements of the coupling matrix through a transformation matrix determined based on an error model of a seven-array element hexagonal antenna array, namely, firstly converting the coupling matrix into the corresponding replacement vectors comprising all elements of the coupling matrix and converting the phase amplitude error matrix into the corresponding replacement vectors comprising all elements of the phase amplitude error matrix, wherein the understanding is that the error model of the array comprises the coupling model and the phase amplitude error model, the transformation matrix of the transformed coupling matrix is determined based on the coupling model of the array, and the transformation matrix of the transformed phase-amplitude error matrix is naturally determined based on the phase-amplitude error model of the array, and the corresponding relationship will not be described in detail in the following. And then alternately and iteratively solving the replacement vector corresponding to the coupling matrix and the replacement vector corresponding to the amplitude error matrix, finally obtaining a target coupling matrix according to the replacement vector corresponding to the solved coupling matrix, and obtaining a target amplitude error matrix according to the replacement vector corresponding to the solved amplitude error matrix.

In the step, the coupling matrix and the phase amplitude error matrix are jointly updated and solved, and all errors in the seven-array element hexagonal array are considered, so that the errors of the seven-array element hexagonal array are corrected more comprehensively.

S103, compensating and correcting newly received signal source data according to the target coupling matrix and the target phase amplitude error matrix; and the signal source data after compensation correction represents the signal source data received after the antenna array error correction.

Based on the target coupling matrix and the target phase amplitude error matrix obtained in the above steps, compensation correction can be performed on newly received signal source data through the target coupling matrix and the target phase amplitude error matrix. The newly received signal source data is the signal source data containing the array error in the actual engineering, and after the newly received signal source data is compensated and corrected by the target coupling matrix and the target amplitude error matrix, the newly received signal source data is corrected into the signal source data without the array error, and because the array error generally has the influence in the data, the correction of the data is the correction of the influence caused by the array error.

Illustratively, a coupling compensation matrix C-1 corresponding to the target coupling matrix and a phase amplitude compensation matrix Γ -1 corresponding to the target phase amplitude error matrix are calculated, and then the coupling compensation matrix C-1 and the phase amplitude compensation matrix Γ -1 are compensated into subsequent newly received signal data Y to correct the newly received data, i.e., Y_cpstgamma-1C-1Y, and corrected Y_cpstThe signal data is signal data without seven-array element hexagonal array errors.

Compared with the prior art that coupling correction cannot be performed when correcting an array error of a seven-array-element hexagon, this embodiment provides a method for correcting an antenna array, which includes, after signal source data incident to the seven-array-element hexagon antenna array from multiple time-sharing directions is acquired, jointly updating a coupling matrix in each signal source data and an amplitude error matrix of the antenna array including an amplitude error matrix and a phase error matrix by a preset alternating iteration method to obtain a target coupling matrix and a target amplitude error matrix, performing compensation correction on newly received signal source data according to the target coupling matrix and the target amplitude error matrix, and representing the received signal source data after correcting the antenna array error by the obtained signal source data after compensation correction. In the method, after a plurality of known signal source data are received, the adopted alternating iteration method comprises the step of respectively converting the coupling matrix and the phase amplitude error matrix into corresponding replacement vectors comprising all elements through a transformation matrix determined based on an error model of the seven-array-element hexagonal antenna array, so that the improved alternating iteration method can be used on the seven-array-element hexagonal antenna array, the errors of the seven-array-element hexagonal antenna array are effectively corrected in a combined mode, and all the errors in the seven-array-element hexagonal array are considered through the combined updating of the coupling matrix and the phase amplitude error matrix, and the errors of the seven-array-element hexagonal array are corrected more comprehensively.

The following describes a detailed process of jointly updating the coupling matrix and the phase-amplitude error matrix by an alternate iteration method through a specific embodiment, as shown in fig. 3, in an embodiment, the step S102 includes:

s201, acquiring an original optimization function expression based on data of each signal source; the original optimization function expression comprises a coupling matrix, a phase amplitude error matrix and a characteristic vector coefficient matrix.

Wherein, the expression X of each signal source data is obtained_kThe process of solving the coupling matrix and the phase amplitude error matrix can be converted into a process of solving an optimization function comprising the coupling matrix, the phase amplitude error matrix and the characteristic vector coefficient matrix by processing the data matrix. In the original optimization function expression in this step, the optimization function originally representing the preliminary conversion is only to distinguish the states of the optimization function, and is not to limit the optimization function.

Optionally, an embodiment is provided, in which the process of decoupling the matrix and the phase-amplitude error matrix is converted into a process of solving an optimization function, as shown in fig. 4, the step S201 includes:

s301, performing correlation operation on each signal source data to obtain a covariance matrix of each signal source data.

After receiving the data of M signal sources in a time-sharing manner, performing correlation operation on the received data to obtain correlation matrixes thereof, namely obtaining covariance matrixes of the data of the signal sources.

For example, the k-th signal source data X_k＝C*Γ*a_k*S_k+N_kThe covariance matrix corresponding thereto is:

where L is the fast beat number of data samples.

S302, performing characteristic decomposition on each covariance matrix, obtaining a characteristic vector corresponding to the maximum characteristic value in the characteristic values of each covariance matrix, and forming a characteristic vector matrix.

And performing characteristic decomposition on each covariance matrix based on the acquired covariance matrix of each signal source data to obtain all eigenvalues of each covariance matrix, and then selecting the eigenvector corresponding to the largest eigenvalue from each eigenvalue of the covariance matrix to form an eigenvector matrix.

For example, the array receives data X for every source_kJust to data X_kPerforming correlation processing to obtain correlation matrix of the signal

Then, the feature decomposition is carried out on the characteristic vector u, and the characteristic vector u corresponding to the maximum characteristic value is taken out_kForming a 7 xM-dimensional matrix U ═ U by the extracted M eigenvectors₁,u₂,...,u_M]And U is the feature vector matrix.

And S303, acquiring an optimization function expression according to the characteristic vector matrix and the coupling matrix and the phase amplitude error matrix in the data of each signal source.

Go toAnd step two, acquiring an optimization function expression based on the obtained characteristic vector matrix and the coupling matrix and the phase amplitude error matrix in the signal source data. By way of example, will

Further developed as follows:

and to R_kBy performing the feature decomposition, the following can be obtained:

wherein v is₁Is R_kMaximum eigenvalue va₁Corresponding feature vectors, since here are correlation matrices of a single signal, v₁Open space, i.e. signal space, i.e. v₁The opened space and C Γ a_kThe open space being the same space, i.e. v₁May be formed of C Γ a_kAnd (4) linear representation. We will refer to v for the k signal₁Is proposed to be changed into u_kThen it is possible to obtain: c Γ a_k＝λ_k*u_kFurther, we can continue to derive C Γ a U Λ, where a is the transmit signal source whose far field is time-shared from M directions, and the array manifold a of the M known direction sources_i1,2, M, forming a 7 xm-dimensional matrix a ═ a₁,a₂,...,a_M]And Λ is a eigenvector coefficient matrix, which is an M × M diagonal matrix,

wherein,

wherein λ_iIs the i-th element, f, on the diagonal of the diagonal matrix Λ_iThe matrix F is a column vector of the ith column, and F ═ C × Γ × a, so that it can be solved in an optimization manner, that is:

here J is the optimization function, and the expression is the expression of the transformed original optimization function.

In the embodiment, after the received signal source data is converted into the correlation matrix, and then processed into the expression of the original optimization function according to the correlation matrix, the problem of solving the coupling matrix and the phase amplitude error matrix is converted into how to solve the optimization function, so that the process of solving the coupling matrix and the phase amplitude error matrix is simplified.

S202, respectively updating the current coupling matrix, the current amplitude error matrix and the current eigenvector coefficient matrix to obtain a current updated coupling matrix, a current updated amplitude error matrix and a current updated eigenvector coefficient matrix.

The step is based on the process of performing combined update on the coupling matrix and the phase amplitude error matrix by adopting an alternating iterative algorithm after converting the problem of solving the coupling matrix and the phase amplitude error matrix into the original optimization function, and specifically, the alternating idea is as follows: when the coupling matrix C is updated, the phase amplitude error matrix gamma and the eigenvector coefficient matrix lambda are assumed to be known; when the phase amplitude error matrix gamma is updated, the coupling matrix C and the eigenvector coefficient matrix lambda are assumed to be known; when updating the eigenvector coefficient matrix Λ, the coupling matrix C and the phase amplitude error matrix Γ are assumed to be known.

The idea of iteration is to cyclically and alternately update, before the start of the alternate iteration, each iteration parameter needs to be initialized, for example, let the iteration number k be 1, set a very small iteration termination constant e (e.g. 0.0001), set the coupling matrix C and the amplitude error matrix Γ as unit matrices, and initialize the eigenvector coefficient matrix Λ with the initialized C and Γ, where it needs to be noted that, because the formula of the elements in Λ is

f_iThe matrix F is a column vector of the ith column, and F is C Γ A, so when initializing Λ, the initialized C and Γ are substituted into an optimization function J, and the C and Γ are taken

Then solved to obtain lambda_iThen, the optimization function J is introduced to initialize the optimization function value to obtain J₀。

After initializing each iteration parameter, respectively updating the current coupling matrix, the current phase amplitude error matrix and the current eigenvector coefficient matrix, wherein the current refers to any one time of a cyclic updating process, and the current updated coupling matrix, the current updated phase amplitude error matrix and the current updated eigenvector coefficient matrix are obtained after updating. For any update process, refer to the description in the following embodiments, which will not be described herein again.

And S203, substituting the currently updated coupling matrix, the currently updated phase amplitude error matrix and the currently updated eigenvector coefficient matrix into the original optimization function expression to obtain the current function value of the original optimization function expression.

And substituting the updated coupling matrix, the amplitude error matrix and the eigenvector coefficient matrix into the original optimization function expression based on the obtained current updated coupling matrix, the current updated amplitude error matrix and the current updated eigenvector coefficient matrix to obtain the current function value of the original optimization function expression.

For example, if the current time is the kth time, the updated C, Γ, and Λ are substituted into the original optimization function, and the current function value obtained is J_k。

And S204, if the error between the current function value and the last function value of the original optimization function expression is smaller than a preset threshold value, determining the current updated coupling matrix as a target coupling matrix and determining the current updated phase amplitude error matrix as a target phase amplitude error matrix.

And after the current function value is obtained, comparing the current function value with the function value of the optimization function in the last updating, if the difference value between the current function value and the function value of the optimization function in the last updating is smaller than a preset threshold value, determining that the iteration process can be ended, determining the current updated coupling matrix as a target coupling matrix and determining the updated phase amplitude error matrix as a target phase amplitude error matrix.

For example, if the current time is the k-th time, the current function value is J_kThen the last time of the k-th time is k-1 times, and the function value of the optimization function of k-1 times is J_k-1，d_k＝J_k-J_k-1If d is_kIf the iteration constant is less than the preset iteration constant e, determining to obtain a final target coupling matrix and a target phase amplitude error matrix, and if d is less than the preset iteration constant e, determining to obtain a final target coupling matrix and a final target phase amplitude error matrix_kAnd if the iteration constant is larger than the preset iteration constant e, returning to update the coupling matrix, the phase amplitude error matrix and the characteristic vector coefficient matrix in the next round. In the embodiment, the target coupling matrix and the target phase amplitude error matrix are obtained through iterative updating, so that the updating results of the coupling matrix and the phase amplitude error matrix are more accurate.

In one embodiment, the process of alternately updating the coupling matrix, the phase amplitude error matrix, and the eigenvector coefficient matrix at any one time is described below. It should be noted that, in this embodiment, all the current states are only used to refer to the stage of the cyclic update, for example, the current update may be performed when the K-th update is performed, and the current update may also be performed when the K + 1-th update is performed.

In this embodiment, the transformation matrix determined by the error model based on the seven-element hexagonal antenna array is divided into a first transformation matrix and a second transformation matrix, where the first transformation matrix represents a transformation matrix including a coupling matrix corresponding to all elements of the coupling matrix, and the second transformation matrix represents a transformation matrix including a phase-amplitude error matrix corresponding to all elements of the phase-amplitude error matrix; correspondingly, the converted replacement vector is also divided into a first replacement vector corresponding to the coupling matrix and a second replacement vector corresponding to the amplitude error matrix.

As shown in fig. 5, the step S202 includes:

s401, substituting the current phase amplitude error matrix and the current eigenvector coefficient matrix into a first optimization function expression converted according to a first transformation matrix to obtain a current updated coupling matrix; the first transformation matrix is used to convert the coupling matrix into a first replacement vector comprising all elements of the coupling matrix.

The step is a process of updating the coupling matrix, and the known phase amplitude error matrix and the characteristic vector coefficient matrix are still data which are not updated at the present time because the coupling matrix is updated first on the assumption that the phase amplitude error matrix and the characteristic vector coefficient matrix are known.

Specifically, the current phase amplitude error matrix and the current eigenvector coefficient matrix are substituted into a first optimization function expression converted according to a first transformation matrix, and a first replacement vector in the first optimization function expression is solved, so that the current updated coupling matrix is obtained.

For example, if the current time is the k-th time, then the coupling matrix, the amplitude error matrix, and the eigenvector coefficient matrix are each C before the k-th update_k、Γ_k、Λ_kAt the time of updating C_kThe known phasor error matrix and eigenvector coefficient matrix are then Γ_kAnd Λ_kI.e. Γ_kAnd Λ_kSubstituting the first optimized function expression into the first optimized function expression to solve a first replacement vector, and obtaining the current updated coupling matrix.

Optionally, an implementation manner of the step S401 is provided, as shown in fig. 6, the implementation manner includes:

s501, converting the coupling matrix of the original optimization function expression into a first replacement vector according to the first transformation matrix to obtain a first optimization function expression.

Firstly, converting the coupling matrix of the original optimization function expression into a first replacement vector according to a first transformation matrix to obtain a first optimization function expression.

For example, the original optimization function is expressed as

The first transformation matrix transforms the coupling matrix into a first replacement vector, and then

The coupling matrix C in (1) is converted into a first replacement vector to obtain a first optimization function expression.

And S502, substituting the current phase amplitude error matrix and the current characteristic vector coefficient matrix into the first optimization function expression to solve a first replacement vector.

S503, determining the current updated coupling matrix according to the first replacement vector.

For example, the current phasor error matrix and the current eigenvector coefficient matrix are Γ_kAnd Λ_kWill gamma_kAnd Λ_kAnd substituting the first optimization function expression to solve a first replacement vector, and obtaining all elements in the coupling matrix C one by one according to the solved first replacement vector because the first replacement vector contains all elements in the coupling matrix C, thereby obtaining the updated coupling matrix C.

Optionally, a first transformation matrix is provided, the product of the first transformation matrix and the first replacement vector being equal to the product of the coupling matrix and the one-dimensional column vector, the first transformation matrix being a diagonal matrix, and the diagonal elements comprising all elements of the one-dimensional column vector.

Wherein, the first transformation matrix is set as:

through T₁(x) Can realize that C x T₁(x) C, wherein C is a coupling matrix; x is the coupling-dimension column vector, which is an arbitrary 7 x 1 dimension column vector; c is a first replacement vector, and c ═ c₁,c₂,c₃,0,c₄,c₅]^TThe first replacement vector C contains all the elements in the coupling matrix C; t is₁(x) In x_1:6A column vector consisting of the first 6 elements coupling a one-dimensional column vector x; x is the number of₇Is the 7 th element coupled to a dimensional column vector x, which is a scalar; wherein, T₂(x_1:6) Equivalence T₂(y)，T₂The expression of (y) is: t is₂(y)＝T₂₁(y)+T₂₂(y)+T₂₃(y)+T₂₄(y) wherein:

wherein [ T (y)]_ijThe corresponding element of the ith row and the jth column of the matrix T is represented, i.e., i, j is the row-column index of the matrix T.

At the same time, let V ═ U ═ Λ ═ V ═ Λ₁,v₂,...,v_M],B＝Γ*A＝[b₁,b₂,...,b_M]Then pass through T₁(x) After transforming the original optimization function, the resulting first optimization function expression can be written as:

by passing

Can be solved out

And then an updated coupling matrix C can be obtained.

As can be seen from the above, the first replacement vector c ═ c₁,c₂,c₃,0,c₄,c₅]^TIncludes a coupling matrix

So that the coupling matrix C can be obtained by solving the first replacement vector

In the embodiment, the C matrix which needs to be optimized and solved for 7 × 7 elements originally can be converted into the first replacement vector C vector for solving 6 elements based on the special structure of C, so that the calculation amount of the optimization algorithm is greatly reduced, and the feasibility of the algorithm is improved.

S402, substituting the current updated coupling matrix and the current eigenvector coefficient matrix into a second optimization function expression converted according to a second transformation matrix to obtain a current updated phase-amplitude error matrix; the second transformation matrix is used to convert the phase amplitude error matrix into a second replacement vector comprising all elements of the phase amplitude error matrix.

The step is a process of updating the phase amplitude error matrix, because the coupling matrix is updated for the first time in the previous step, and then the phase amplitude error matrix in the step is updated, when the phase amplitude error matrix is updated, the coupling matrix and the eigenvector coefficient matrix are assumed to be known, and because the coupling matrix is updated in the front, the known coupling matrix is the coupling matrix obtained after the updating of the step and the non-updated eigenvector coefficient matrix.

Specifically, the coupling matrix obtained after the current update and the current eigenvector coefficient matrix which is not updated are substituted into a second optimization function expression converted according to a second transformation matrix, and a second replacement vector in the second optimization function expression is solved, so that the current updated phase amplitude error matrix is obtained.

For example, if the current time is the k-th time, then the coupling matrix, the amplitude error matrix, and the eigenvector coefficient matrix are each C before the k-th update_k、Γ_k、Λ_kAt the time of updating gamma_kWhen the known coupling matrix is updated C_k' and Λ before update_kC to be updated_k' and Λ before update_kSubstituting the obtained result into a second optimization function expression to obtain a second replacement vector, and obtaining the current updated phase amplitude error matrix gamma_k'。

Optionally, an implementation manner of the step S402 is provided, as shown in fig. 7, the implementation manner includes:

s601, converting the phase amplitude error matrix of the original optimization function expression into a second replacement vector according to a second transformation matrix to obtain a second optimization function expression.

And firstly, converting the phase amplitude error matrix of the original optimization function expression into a second replacement vector according to a second transformation matrix to obtain a second optimization function expression.

For example, the original optimization function is expressed as

The second transformation matrix transforms the coupling matrix into a second replacement vector, and then

And the amplitude error matrix gamma in the step (1) is converted into a second replacement vector to obtain a second optimization function expression.

And S602, substituting the current updated coupling matrix and the current characteristic vector coefficient matrix into a second optimization function expression, and solving a second replacement vector.

And S603, determining the current updated phase amplitude error matrix according to the second replacement vector.

For example, the updated coupling matrix is C_k' and the current eigenvector coefficient matrix is Λ_kMixing C with_k' and Λ_kSubstituting a second optimization function expression to obtain a second replacement vector, wherein the second replacement vector comprises all elements in the phase amplitude error matrix gamma, so that all elements in the phase amplitude error matrix gamma can be obtained one by one according to the solved second replacement vector, and the updated phase amplitude error matrix gamma is obtained_k'。

Optionally, a product of the second transformation matrix and the second replacement vector is equal to a product of the amplitude error matrix and the amplitude one-dimensional column vector, the second transformation matrix is a diagonal matrix, and diagonal elements of the diagonal matrix include all elements of the amplitude one-dimensional column vector.

Wherein, let the second transformation matrix be T₃，T₃A conversion of a 7 x 7-element Γ matrix into a 7-element column vector γ ═ diag (Γ) can be achieved]. The method specifically comprises the following steps: gamma alpha_i＝T₃(a_i) Gamma, wherein, T₃(a_i) Is a vector a_i＝[a_i1,a_i2,...,a_i7]^TA matrix of transformations wherein

Is also a 7 × 7 dimensional diagonal matrix, and the diagonal elements are vectors a_iAll of the elements of (a). Thus, passing through T₃(a_i) Second transformed original optimization functionThe optimization function expression is:

by passing

To obtain

And then an updated value of the phase amplitude error matrix gamma is obtained.

Similarly, the Γ matrix which originally needs to be optimized and solved for 7 × 7 elements can be converted into a second replacement vector γ vector for solving for 7 elements, which greatly reduces the calculation amount of the optimization algorithm and improves the feasibility of the algorithm.

And S403, substituting the currently updated coupling matrix and the currently updated phase amplitude error matrix into the original optimization function expression to obtain a currently updated eigenvector coefficient matrix.

This step is a process of updating the eigenvector coefficient matrix, because the coupling matrix and the phase amplitude error matrix have been updated previously, the known coupling matrix and phase amplitude error matrix are the updated coupling matrix and the updated phase amplitude error matrix.

Specifically, the eigenvector coefficient matrix is updated, the updated coupling matrix and the updated amplitude error matrix are substituted into the original optimization function expression, and the current updated eigenvector coefficient matrix is obtained.

For example, the coupling matrix is updated to C_k' the updated phase amplitude error matrix is gamma_k', will C_k'and' gamma_kSubstituting the parameters into the original optimization function expression to obtain an updated eigenvector coefficient matrix Lambda^k。

In this embodiment, when the coupling matrix C is updated, it is assumed that the phase amplitude error matrix Γ and the eigenvector coefficient matrix Λ are known; when the phase amplitude error matrix gamma is updated, the coupling matrix C and the eigenvector coefficient matrix lambda are assumed to be known; when the eigenvector coefficient matrix lambda is updated, the coupling matrix C and the phase amplitude error matrix gamma are assumed to be known, and the coupling matrix, the phase amplitude error matrix and the eigenvector coefficient matrix are sequentially and alternately updated, so that the updated coupling matrix, the updated phase amplitude error matrix and the updated eigenvector coefficient matrix are effectively obtained.

In addition, a method for calibrating an antenna array is provided, as shown in fig. 8, the embodiment includes:

s1, emitting M signals from different directions in a time-sharing manner;

s2, respectively solving the M signal source data received by the array to obtain the relevant arrays, and respectively extracting the eigenvectors corresponding to the maximum eigenvalues to form an eigenvector coefficient matrix;

s3, initializing iteration parameters including iteration times k, a coupling matrix C, a phase amplitude error matrix gamma, a characteristic vector coefficient matrix lambda, an iteration termination value e and an optimization function value J₀；

S4, using the first transformation matrix T₁(x) By C x T₁(x) C, converting C into rear C, substituting gamma and lambda into an optimization function to solve, and obtaining an updated coupling matrix C';

s5, using a second transformation matrix T₃(a_i) By Γ a_i＝T₃(a_i) Gamma, converting gamma into gamma, and substituting C 'and lambda into an optimization function to solve to obtain an updated amplitude error matrix gamma';

s6, substituting the updated coupling matrix C ' and the updated phase amplitude error matrix gamma ' into an optimization function to obtain an updated eigenvector coefficient matrix lambda ';

s7, substituting the updated coupling matrix C ', the updated phase amplitude error matrix gamma ' and the updated eigenvector coefficient matrix lambda ' into the optimization function to obtain the value J of the optimization function_kAnd calculate J_kValue J of last optimization function_k-1Difference d of_k；

S8, judgment d_kIf the value is less than the iteration termination value e, executing S9 if the value is greater than the iteration termination value e, and executing S4 if the value is not greater than the iteration termination value e;

and S9, terminating the iteration, and saving the obtained C 'and gamma' so as to compensate the new data received subsequently and obtain the data without array errors.

The implementation principle and technical effect of the steps in the calibration method for an antenna array provided in the foregoing embodiment are similar to those in the foregoing embodiments of the calibration method for an antenna array, and are not described herein again.

In addition, as shown in fig. 9, based on the antenna array calibration method, a MUSIC simulation diagram before and after calibration of a seven-element hexagonal array is provided. Wherein, the simulation conditions adopted by the simulation are as follows:

coefficient of coupling matrix c₁,c₂,c₃,c₄,c₅]Are respectively [1,0.2111+0.1947i, -0.1013+0.1052i,0.2111+0.1947i,1]；

The diagonal elements of the amplitude error matrix and the phase error matrix are respectively:

[1.0721,0.9876,1.2113,0.7532,1.4013,1.2512,1.1654],

exp(i*[-12.0784,-18.8656,12.7204,-16.5237,-5.8732,6.4587.-10.7364])。

when active correction is performed, the incidence directions of the 7 time-sharing correction sources are respectively [20 °,30 °,40 °,50 °,60 °,70 °,80 °.

The fast sampling beat number L is 256 and the SNR is 35dB, which is used to verify that the source angle is 63 before and after correction.

After simulation is performed based on the simulation conditions, as can be seen from the simulation result shown in fig. 9, before the calibration is not performed, the MUSIC spectrum hardly forms a peak value at a correct direction angle, and the height of the spectrum peak is only 0.2931dB, so that when an array error exists, the MUSIC algorithm completely fails; after the antenna array correction method provided by the application is used for correcting, the MUSIC spectrum can form a peak value in the correct direction, and the peak value reaches 53.32dB, so that the antenna array correction method provided by the application is high in feasibility.

It should be understood that although the various steps in the flow charts of fig. 2-8 are shown in order as indicated by the arrows, the steps are not necessarily performed in order as indicated by the arrows. The steps are not performed in the exact order shown and described, and may be performed in other orders, unless explicitly stated otherwise. Moreover, at least some of the steps in fig. 2-8 may include multiple steps or multiple stages, which are not necessarily performed at the same time, but may be performed at different times, which are not necessarily performed in sequence, but may be performed in turn or alternately with other steps or at least some of the other steps.

In one embodiment, as shown in fig. 10, there is provided an antenna array calibration apparatus, including: a signal data acquisition module 10, a joint update module 11 and a compensation correction module 12, wherein:

the signal data acquisition module 10 is configured to acquire signal source data that is incident to the seven-element hexagonal antenna array from multiple time-sharing directions; each signal source data comprises a coupling matrix of the antenna array and a phase amplitude error matrix of the antenna array; the phase amplitude error matrix comprises an amplitude error matrix and a phase error matrix;

the joint updating module 11 is configured to jointly update the coupling matrix and the phase amplitude error matrix by using a preset alternative iteration method to obtain a target coupling matrix and a target phase amplitude error matrix; the alternating iteration method comprises the steps of converting a coupling matrix and a phase amplitude error matrix into corresponding replacement vectors comprising all elements respectively through a transformation matrix determined by an error model based on a seven-array element hexagonal antenna array;

the compensation correction module 12 is configured to perform compensation correction on newly received signal source data according to the target coupling matrix and the target phase amplitude error matrix; and the signal source data after compensation correction represents the signal source data received after the antenna array error correction.

In one embodiment, the joint update module 11 includes:

the function unit is used for acquiring an original optimization function expression based on the data of each signal source; the original optimization function expression comprises a coupling matrix, a phase amplitude error matrix and a characteristic vector coefficient matrix;

the updating unit is used for respectively updating the current coupling matrix, the current phase amplitude error matrix and the current eigenvector coefficient matrix by an alternative iteration method to obtain a current updated coupling matrix, a current updated phase amplitude error matrix and a current updated eigenvector coefficient matrix;

the function value determining unit is used for substituting the currently updated coupling matrix, the currently updated phase amplitude error matrix and the currently updated characteristic vector coefficient matrix into the original optimization function expression to obtain a current function value of the original optimization function expression;

and the iteration judgment unit is used for determining the current updated coupling matrix as a target coupling matrix and determining the current updated amplitude error matrix as a target amplitude error matrix if the error between the current function value and the last function value of the original optimization function expression is smaller than a preset threshold value.

In one embodiment, the update unit includes:

the coupling matrix updating unit is used for substituting the current phase amplitude error matrix and the current eigenvector coefficient matrix into a first optimization function expression converted according to a first transformation matrix to obtain a current updated coupling matrix; the first transformation matrix is used for converting the coupling matrix into a first replacement vector comprising all elements of the coupling matrix;

the phase amplitude error matrix updating unit is used for substituting the currently updated coupling matrix and the current eigenvector coefficient matrix into a second optimization function expression converted according to a second transformation matrix to obtain a currently updated phase amplitude error matrix; the second transformation matrix is used for converting the phase amplitude error matrix into a second replacement vector comprising all elements of the phase amplitude error matrix;

and the eigenvector coefficient matrix updating unit is used for substituting the currently updated coupling matrix and the currently updated phase amplitude error matrix into the original optimization function expression to obtain the currently updated eigenvector coefficient matrix.

In an embodiment, the coupling matrix updating unit is specifically configured to obtain a first transformation matrix; converting the coupling matrix of the original optimization function expression into a first replacement vector according to the first transformation matrix to obtain a first optimization function expression; substituting the current phase amplitude error matrix and the current characteristic vector coefficient matrix into a first optimization function expression to solve a first replacement vector; and determining the current updated coupling matrix according to the first replacement vector.

In an embodiment, the phase-amplitude error matrix updating unit is specifically configured to obtain a second transformation matrix; converting the phase amplitude error matrix of the original optimization function expression into a second replacement vector according to a second transformation matrix to obtain a second optimization function expression; substituting the current updated coupling matrix and the current characteristic vector coefficient matrix into a second optimization function expression to solve a second replacement vector; and determining the current updated phase amplitude error matrix according to the second replacement vector.

In one embodiment, the product of the first transformation matrix and the first replacement vector is equal to the product of the coupling matrix and the coupling one-dimensional column vector, the first transformation matrix is a diagonal matrix, and diagonal elements of the diagonal matrix include all elements of the coupling one-dimensional column vector.

In one embodiment, the first transformation matrix is:

through T₁(x) Can realize that C x T₁(x) C, wherein C is a coupling matrix; x is a coupling-dimension column vector which is an arbitrary 7 x 1 dimension column vector; c is a first replacement vector, and c ═ c₁,c₂,c₃,0,c₄,c₅]The first replacement vector C contains all the elements in the coupling matrix C; t is₁(x) In x_1:6A column vector consisting of the first 6 elements coupling a one-dimensional column vector x; x is the number of₇Is the 7 th element coupled to a dimensional column vector x, which is a scalar;

wherein, T₂(x_1:6) Equivalence T₂(y)，T₂The expression of (y) is:

T₂(y)＝T₂₁(y)+T₂₂(y)+T₂₃(y)+T₂₄(y) wherein:

wherein [ T (y)]_ijThe corresponding element in the ith row and the jth column of the matrix T is shown.

In one embodiment, the product of the second transformation matrix and the second replacement vector is equal to the product of the amplitude error matrix and the amplitude one-dimensional column vector, the second transformation matrix is a diagonal matrix, and diagonal elements of the diagonal matrix include all elements of the amplitude one-dimensional column vector.

In one embodiment, the function unit includes:

the matrix conversion subunit is used for carrying out correlation operation on the signal source data to obtain a covariance matrix of the signal source data;

the characteristic vector subunit is used for performing characteristic decomposition on each covariance matrix to obtain a characteristic vector corresponding to the largest characteristic value in the characteristic values of each covariance matrix to form a characteristic vector matrix;

and the function determining subunit is used for acquiring the optimization function expression according to the characteristic vector matrix and the coupling matrix and the phase amplitude error matrix in the data of each signal source.

The implementation principle and technical effect of the calibration apparatus for all antenna arrays provided in the above embodiments are similar to those of the calibration method for antenna arrays, and are not described herein again.

For specific limitations of the calibration apparatus for the antenna array, reference may be made to the above limitations of the calibration method for the antenna array, which are not described herein again. The modules in the calibration apparatus of the antenna array may be implemented in whole or in part by software, hardware, and a combination thereof. The modules can be embedded in a hardware form or independent from a processor in the computer device, and can also be stored in a memory in the computer device in a software form, so that the processor can call and execute operations corresponding to the modules.

In one embodiment, a computer device is provided, which may be a terminal, the internal structure of which may be as described above in fig. 1. The computer device includes a processor, a memory, a communication interface, a display screen, and an input device connected by a system bus. Wherein the processor of the computer device is configured to provide computing and control capabilities. The memory of the computer device comprises a nonvolatile storage medium and an internal memory. The non-volatile storage medium stores an operating system and a computer program. The internal memory provides an environment for the operation of an operating system and computer programs in the non-volatile storage medium. The communication interface of the computer device is used for carrying out wired or wireless communication with an external terminal, and the wireless communication can be realized through WIFI, an operator network, NFC (near field communication) or other technologies. The computer program is executed by a processor to implement a method of calibration of an antenna array. The display screen of the computer equipment can be a liquid crystal display screen or an electronic ink display screen, and the input device of the computer equipment can be a touch layer covered on the display screen, a key, a track ball or a touch pad arranged on the shell of the computer equipment, an external keyboard, a touch pad or a mouse and the like.

Those skilled in the art will appreciate that the architecture shown in fig. 1 is merely a block diagram of some of the structures associated with the disclosed aspects and is not intended to limit the computing devices to which the disclosed aspects apply, as particular computing devices may include more or less components than those shown, or may combine certain components, or have a different arrangement of components.

In one embodiment, a computer device is provided, comprising a memory and a processor, the memory having a computer program stored therein, the processor implementing the following steps when executing the computer program:

The implementation principle and technical effect of the computer device provided by the above embodiment are similar to those of the above method embodiment, and are not described herein again.

In one embodiment, a computer-readable storage medium is provided, having a computer program stored thereon, which when executed by a processor, performs the steps of:

The implementation principle and technical effect of the computer-readable storage medium provided by the above embodiments are similar to those of the above method embodiments, and are not described herein again.

It will be understood by those skilled in the art that all or part of the processes of the methods of the embodiments described above can be implemented by hardware instructions of a computer program, which can be stored in a non-volatile computer-readable storage medium, and when executed, can include the processes of the embodiments of the methods described above. Any reference to memory, storage, database or other medium used in the embodiments provided herein can include at least one of non-volatile and volatile memory. Non-volatile Memory may include Read-Only Memory (ROM), magnetic tape, floppy disk, flash Memory, optical storage, or the like. Volatile Memory can include Random Access Memory (RAM) or external cache Memory. By way of illustration and not limitation, RAM can take many forms, such as Static Random Access Memory (SRAM) or Dynamic Random Access Memory (DRAM), for example.

The technical features of the above embodiments can be arbitrarily combined, and for the sake of brevity, all possible combinations of the technical features in the above embodiments are not described, but should be considered as the scope of the present specification as long as there is no contradiction between the combinations of the technical features.

The above-mentioned embodiments only express several embodiments of the present application, and the description thereof is more specific and detailed, but not construed as limiting the scope of the invention. It should be noted that, for a person skilled in the art, several variations and modifications can be made without departing from the concept of the present application, which falls within the scope of protection of the present application. Therefore, the protection scope of the present patent shall be subject to the appended claims.

Claims

1. A method for calibrating an antenna array, the method comprising:

acquiring signal source data which are incident to a seven-array-element hexagonal antenna array from a plurality of time-sharing directions; each signal source data comprises a coupling matrix of the antenna array and a phase amplitude error matrix of the antenna array; the phase-amplitude error matrix comprises an amplitude error matrix and a phase error matrix;

jointly updating the coupling matrix and the phase amplitude error matrix through a preset alternating iteration method to obtain a target coupling matrix and a target phase amplitude error matrix; the alternating iteration method comprises the steps of converting the coupling matrix and the phase amplitude error matrix into corresponding replacement vectors comprising all elements respectively through a transformation matrix determined by an error model based on a seven-array element hexagonal antenna array; the transformation matrix comprises a first transformation matrix determined based on an error model of a seven-element hexagonal antenna array; the first transformation matrix is used for converting the coupling matrix into a first replacement vector comprising all elements of the coupling matrix; the first replacement vector is used to determine the target coupling matrix;

wherein the coupling matrix C satisfies C x T₁(x) C; the x is any coupling-dimensional column vector of 7 x 1 dimensions; the c is the first replacement vector, and c ═ c₁,c₂,c₃,0,c₄,c₅]^TThe first replacement vector C contains all elements in the coupling matrix C; the T is₁(x) For the first transformation matrix

Said x_1:6A column vector consisting of the first 6 elements in said x; said x₇Is the 7 th element in the coupled one-dimensional column vector x and is a scalar;

2. The method of claim 1, wherein jointly updating the coupling matrix and the phase amplitude error matrix by a preset alternating iteration method to obtain a target coupling matrix and a target phase amplitude error matrix comprises:

acquiring an original optimization function expression based on the signal source data; the original optimization function expression comprises a coupling matrix, a phase amplitude error matrix and a characteristic vector coefficient matrix;

respectively updating the current coupling matrix, the current phase amplitude error matrix and the current eigenvector coefficient matrix by the alternative iteration method to obtain a current updated coupling matrix, a current updated phase amplitude error matrix and a current updated eigenvector coefficient matrix;

substituting the current updated coupling matrix, the current updated phase amplitude error matrix and the current updated eigenvector coefficient matrix into the original optimization function expression to obtain a current function value of the original optimization function expression;

and if the error between the current function value and the last function value of the original optimization function expression is smaller than a preset threshold value, determining the current updated coupling matrix as the target coupling matrix and determining the current updated amplitude error matrix as the target amplitude error matrix.

3. The method of claim 2, wherein the updating the current coupling matrix, the current amplitude error matrix, and the current eigenvector coefficient matrix by the alternating iteration method to obtain the current updated coupling matrix, the current updated amplitude error matrix, and the current updated eigenvector coefficient matrix respectively comprises:

substituting the current phase amplitude error matrix and the current eigenvector coefficient matrix into a first optimization function expression converted according to a first transformation matrix to obtain the current updated coupling matrix;

substituting the current updated coupling matrix and the current eigenvector coefficient matrix into a second optimization function expression converted according to a second transformation matrix to obtain the current updated phase-amplitude error matrix; the second transformation matrix is used for converting the phase amplitude error matrix into a second replacement vector comprising all elements of the phase amplitude error matrix;

and substituting the currently updated coupling matrix and the currently updated phase amplitude error matrix into the original optimization function expression to obtain the currently updated eigenvector coefficient matrix.

4. The method of claim 3, wherein the step of substituting the current phasor error matrix and the current eigenvector coefficient matrix into a first optimization function expression transformed according to a first transformation matrix to obtain the current updated coupling matrix comprises:

converting the coupling matrix of the original optimization function expression into the first replacement vector according to the first transformation matrix to obtain the first optimization function expression;

substituting the current phase amplitude error matrix and the current characteristic vector coefficient matrix into the first optimization function expression to solve the first replacement vector;

and determining the current updated coupling matrix according to the first replacement vector.

5. The method of claim 3, wherein the step of substituting the current updated coupling matrix and the current eigenvector coefficient matrix into a second optimization function expression transformed according to a second transformation matrix to obtain the current updated phase-amplitude error matrix comprises:

converting the amplitude error matrix of the original optimization function expression into the second replacement vector according to the second transformation matrix to obtain a second optimization function expression;

substituting the current updated coupling matrix and the current characteristic vector coefficient matrix into the second optimization function expression to solve the second replacement vector;

and determining the current updated phase amplitude error matrix according to the second replacement vector.

6. The method according to any of claims 3-5, wherein the product of the first transformation matrix and the first replacement vector is equal to the product of the coupling matrix and a coupling-dimensional column vector, the first transformation matrix is a diagonal matrix, and diagonal elements of the diagonal matrix comprise all elements of the coupling-dimensional column vector;

the product of the second transformation matrix and the second replacement vector is equal to the product of the amplitude error matrix and the amplitude one-dimensional column vector, the second transformation matrix is a diagonal matrix, and diagonal elements of the diagonal matrix include all elements of the amplitude one-dimensional column vector.

7. The method according to any one of claims 2-5, wherein said obtaining an optimization function expression based on each of said signal source data comprises:

performing correlation operation on the signal source data to obtain a covariance matrix of the signal source data;

performing characteristic decomposition on each covariance matrix to obtain a characteristic vector corresponding to the maximum characteristic value in the characteristic values of each covariance matrix to form a characteristic vector matrix;

and acquiring the optimization function expression according to the characteristic vector matrix and the coupling matrix and the phase amplitude error matrix in the signal source data.

8. An apparatus for calibrating an antenna array, the apparatus comprising:

the signal data acquisition module is used for acquiring signal source data which are incident to the seven-array-element hexagonal antenna array from a plurality of time-sharing directions; each signal source data comprises a coupling matrix of the antenna array and a phase amplitude error matrix of the antenna array; the phase-amplitude error matrix comprises an amplitude error matrix and a phase error matrix;

the joint updating module is used for carrying out joint updating on the coupling matrix and the phase amplitude error matrix through a preset alternative iteration method to obtain a target coupling matrix and a target phase amplitude error matrix; the alternating iteration method comprises the steps of converting the coupling matrix and the phase amplitude error matrix into corresponding replacement vectors comprising all elements respectively through a transformation matrix determined by an error model based on a seven-array element hexagonal antenna array; the transformation matrix comprises a first transformation matrix determined based on an error model of a seven-element hexagonal antenna array; the first transformation matrix is used for converting the coupling matrix into a first replacement vector comprising all elements of the coupling matrix; the first replacement vector is used to determine the target coupling matrix;

the compensation correction module is used for carrying out compensation correction on newly received signal source data according to the target coupling matrix and the target phase amplitude error matrix; and the signal source data after compensation correction represents the signal source data received after the error correction of the antenna array.

9. A computer device comprising a memory and a processor, the memory storing a computer program, characterized in that the processor, when executing the computer program, implements the steps of the method of any of claims 1 to 7.

10. A computer-readable storage medium, on which a computer program is stored, which, when being executed by a processor, carries out the steps of the method of any one of claims 1 to 7.