Distributed array mutual coupling error correction method and system based on auxiliary information source

Abstract

The invention provides a distributed array mutual coupling error correction method and system based on an auxiliary information source, and relates to the field of array signal processing.The method comprises the steps that the auxiliary information source is arranged on the outer side of a distributed array, signals are received, a snapshot sampling signal model and a mutual coupling matrix are constructed, and an objective function of the auxiliary information source is constructed; initializing a quantum arithmetic search mechanism, calculating a fitness value of a quantum operator, updating a quantum rotation angle, and estimating and determining an auxiliary source target angle; and calculating a mutual coupling error matrix and an error correction coefficient. The quantum arithmetic search mechanism has the characteristics of high convergence speed, high convergence precision and the like; a mutual coupling error coefficient of the distributed array is calculated through the auxiliary source target angle, and then a mutual coupling error matrix is obtained; the error correction coefficient of the distributed array can be calculated according to the determined mutual coupling error matrix, then the mutual coupling error of the distributed array is corrected, and the direction finding performance of the corrected distributed array is close to that of an ideal distributed array without the mutual coupling error.

Description

Technical Field

[0001] The present application relates to the technical field of array signal processing, and in particular to a distributed array mutual coupling error correction method and system based on an auxiliary signal source. Background Art

[0002] With the rapid development of 5G technology, antenna distributed array system, as a highly competitive technology, has become an indispensable key technology by fully tapping into spatial channel resources to effectively improve system capacity and reliability and reduce the complexity of interference elimination without the need for additional spectrum resources and transmission power. Antenna distributed array system is a network composed of spatially separated antenna nodes, connected to a common source through a transmission medium, providing wireless services within a geographic area or structure. As an implementation form of multi-antenna system, antenna distributed array system can significantly improve user coverage and communication capacity without increasing spectrum overhead.

[0003] At present, by constructing a suitable distributed array, better direction finding performance can be achieved under the same number of array elements. However, distributed arrays may have various errors, among which mutual coupling error is the most common. When mutual coupling error exists, the direction finding performance of the distributed array will drop sharply or even fail. In the related technology, mutual coupling error correction can be performed on uniform linear arrays based on sparse Bayesian, and mutual coupling error correction can also be performed based on blind source separation. The correction process of antenna mutual coupling error is computationally intensive and is designed for uniform linear arrays, lacking research on distributed arrays. Summary of the invention

[0004] In view of the deficiencies in the prior art, the present application provides a distributed array mutual coupling error correction method and system based on an auxiliary signal source, which solves the problem of technical barriers in the mutual coupling error correction of distributed arrays.

[0005] To achieve the above objectives, the present invention is implemented through the following technical solutions:

[0006] In a first aspect, an embodiment of the present application provides a distributed array mutual coupling error correction method based on an auxiliary information source, the method comprising: arranging an auxiliary information source outside a distributed array whose mutual coupling error is to be corrected, receiving a signal sent by the auxiliary information source through the distributed array, and constructing a snapshot sampling signal model and a mutual coupling matrix; extracting a received signal vector of a uniform subarray in the distributed array, and constructing an objective function of the auxiliary information source for positioning; initializing a preset quantum arithmetic search mechanism, and determining a fitness function of the quantum arithmetic search mechanism based on the objective function, and calculating a fitness value of the quantum operator; executing the quantum arithmetic search mechanism, and selecting a corresponding update strategy according to probability to update a quantum rotation angle of the quantum arithmetic search mechanism to obtain a target rotation angle; according to the target rotation angle, using a simulated quantum rotation gate to update the quantum position of the quantum operator, determining the optimal quantum position and optimal fitness value of the quantum arithmetic search mechanism, so as to estimate and determine the auxiliary source target angle; based on the auxiliary source target angle, calculating the mutual coupling error coefficient and the mutual coupling error matrix of the distributed array; according to the mutual coupling error matrix, determining the error correction coefficient of the distributed array to correct the mutual coupling error of the distributed array.

[0007] According to a first aspect of an embodiment of the present application, an auxiliary information source is arranged outside a distributed array whose mutual coupling error is to be corrected, a signal sent by the auxiliary information source is received through the distributed array, and a snapshot sampling signal model and a mutual coupling matrix are constructed, including: determining a distributed array whose mutual coupling error is to be corrected, the distributed array includes a plurality of uniform arrays, and the plurality of uniform arrays are arranged in a straight line; an auxiliary information source with a narrowband far field is arranged in space, the auxiliary information source is located outside the distributed array, and its signal wave direction is set at an angle to the normal direction of the distributed array; a signal vector of the auxiliary information source is received through the distributed array, and a snapshot sampling signal model and a mutual coupling matrix corresponding to the distributed array are established.

[0008] According to the first aspect of the embodiment of the present application, The snapshot sampling signal model corresponding to the signal vector of the secondary auxiliary source satisfies the expression: Where C represents the mutual coupling matrix of the distributed array, It is The noise vector under the next snapshot obeys the Gaussian distribution. It is The auxiliary source signal vector at the next snapshot, is the maximum number of snapshots; represents the ideal array steering vector of the distributed array and satisfies the expression:

[0009] In the formula, (·) T is the matrix transpose operation, b mrepresents the position of the mth array element relative to the first array element, m∈[2,W], λ represents the wavelength of the auxiliary signal source; Represents the angle between the signal direction of the auxiliary source and the normal direction of the distributed array.

[0010] According to a first aspect of the embodiment of the present application, the aforementioned mutual coupling matrix is ​​a block diagonal matrix and satisfies the expression:

[0011]

[0012] In the formula, the nth matrix on the main diagonal of the matrix is is the sub-coupling matrix corresponding to the ηth sub-array, η∈[1,Z]; the sub-array of the distributed array is a uniform array, and With symmetric Toeplitz characteristics, The qth 1 Row q 2 Elements of a column Satisfies the expression:

[0013]

[0014] In the formula, represents the mutual coupling coefficient vector of the mutual coupling matrix, q 1 and q 2 ∈[1,M η ]; p is the mutual coupling degree of freedom of the distributed array, and the mutual coupling degree of freedom p satisfies: And M η >p-1; is the distance between the first array element of each subarray, d is the array element spacing in all subarrays, and there is no overlapping array element between each subarray. η is the number of array elements in the nth subarray.

[0015] According to a first aspect of an embodiment of the present application, the aforementioned extraction of a received signal vector of a uniform subarray in a distributed array and construction of an objective function of an auxiliary information source for positioning includes: extracting received data of a subarray in a distributed array and calculating a covariance matrix corresponding to the received data; performing eigenvalue decomposition on the covariance matrix to obtain a set of eigenvalues; wherein the eigenvector corresponding to the eigenvalue corresponds to the signal subspace of the received signal vector; based on the characteristic that the noise subspace of the subarray is orthogonal to the actual steering vector of the subarray, constructing an objective function for angle estimation of the auxiliary information source; wherein the objective function does not include a mutual coupling error vector to achieve accurate estimation of the angle of the auxiliary information source.

[0016] According to the first aspect of the embodiment of the present application, the aforementioned initialization of the preset quantum arithmetic search mechanism, and the determination of the fitness function of the quantum arithmetic search mechanism based on the objective function, and the calculation of the fitness value of the quantum operator include: obtaining the preset quantum arithmetic search mechanism and initializing the quantum arithmetic search mechanism; processing the objective function through the initialized quantum algorithm search mechanism to determine the corresponding fitness value.

[0017] In the population of quantum arithmetic search mechanism, the number of quantum operators is recorded as The maximum number of iterations is denoted as T, and the iteration number is denoted as t. At the first iteration, the quantum positions of all quantum operators are initialized to random numbers between [0,1]. At the tth iteration, The quantum position of a quantum operator is and No. The physical position of a quantum operator is denoted by In the formula, δ min and δ max are the lower and upper limits of the search boundary of the quantum arithmetic search mechanism respectively; according to the objective function estimated from the auxiliary source angle, at the tth iteration, The fitness function of a quantum operator satisfies the expression:

[0018]

[0019] Where U N Indicates a smaller M η -1 eigenvalue corresponding to the eigenvector, For U N The corresponding conjugate transposed matrix; For a defined M η ×p-dimensional matrix, M η is the number of array elements in the nth subarray, p is the mutual coupling degree of freedom of the distributed array, For the matrix The conjugate transposed matrix of .

[0020] According to the first aspect of the embodiment of the present application, the aforementioned execution of the quantum arithmetic search mechanism, selecting a corresponding update strategy according to probability to update the quantum rotation angle of the quantum arithmetic search mechanism to obtain the target rotation angle, includes: defining the target variable and a first random number between 0 and 1 , the target variable satisfies: Among them, h 1 and h m The target changes The maximum number of iterations; according to the size relationship between the target variable and the first random number, the quantum operator of the quantum algorithm search mechanism selects the corresponding update strategy to update the quantum rotation angle; when the first random number is smaller than the target variable, the quantum rotation angle update strategy corresponding to the quantum operator satisfies:

[0021]

[0022] When the random number is greater than or equal to the target variable, the quantum rotation angle update strategy corresponding to the quantum operator satisfies:

[0023]

[0024] In the formula, the variable Used to store the quantum position corresponding to the best quantum operator up to the tth iteration, is a second random number uniformly distributed between [0,1], μ is a constant set between (0,1), α is a constant set between (0,10), and ε is a very small positive number to prevent the formula from having extreme points. ω 1 is a constant between (0,1); is a third random number uniformly distributed between [0,1], ω 2 is a constant between (0,1).

[0025] According to the first aspect of the embodiment of the present application, define the variable Used to store the tth iteration The fitness value of a quantum operator is defined as It is used to store the fitness value corresponding to the best quantum operator until the tth iteration. The aforementioned method updates the quantum position of the quantum operator according to the target rotation angle using a simulated quantum rotation gate, determines the optimal quantum position and the optimal fitness value of the quantum arithmetic search mechanism, and estimates and determines the auxiliary source target angle, including the following steps:

[0026] According to the updated target rotation angle, the quantum position of the quantum operator is updated using a simulated quantum rotation gate to obtain the quantum target position; the quantum target position is converted into a physical position, and the fitness value of the quantum operator is calculated and updated; the fitness value of the lth quantum operator in the t+1 generation is In the largest case, if Then Otherwise, When the current number of iterations is equal to the maximum number of iterations T, output the current And by The optimal auxiliary source angle estimation result of the quantum arithmetic search mechanism is obtained, δ min and δmax are respectively the lower and upper limits of the search boundary of the quantum arithmetic search mechanism; when the current number of iterations is less than the maximum number of iterations T, let t=t+1, re-execute the quantum arithmetic search mechanism, and select the corresponding update strategy according to probability to update the quantum rotation angle of the quantum arithmetic search mechanism.

[0027] In a second aspect, an embodiment of the present application provides a distributed array mutual coupling error correction system based on an auxiliary information source, the system comprising: an arrangement and construction module, an extraction and construction module, an initialization module, an execution and update module, an estimation module, a calculation module and a correction module; wherein the arrangement and construction module is used to arrange the auxiliary information source outside the distributed array of the mutual coupling error to be corrected, receive the signal sent by the auxiliary information source through the distributed array, and construct a snapshot sampling signal model and a mutual coupling matrix; the extraction and construction module is used to extract the received signal vector of the uniform subarray in the distributed array, and construct the objective function of the auxiliary information source for positioning; the initialization module is used to initialize the preset quantum arithmetic search mechanism, and determine the quantum arithmetic based on the objective function. The fitness function of the arithmetic search mechanism calculates the fitness value of the quantum operator; the execution update module is used to execute the quantum arithmetic search mechanism, and the corresponding update strategy is selected according to probability to update the quantum rotation angle of the quantum arithmetic search mechanism to obtain the target rotation angle; the estimation module is used to update the quantum position of the quantum operator according to the target rotation angle using a simulated quantum rotation gate, and determine the optimal quantum position and optimal fitness value of the quantum arithmetic search mechanism to estimate and determine the auxiliary source target angle; the calculation module is used to calculate the mutual coupling error coefficient and mutual coupling error matrix of the distributed array based on the auxiliary source target angle; the correction module is used to determine the error correction coefficient of the distributed array according to the mutual coupling error matrix to correct the mutual coupling error of the distributed array.

[0028] In a third aspect, an embodiment of the present application provides an electronic device, comprising: a processor, a memory, and a program stored in the memory and executable on the processor, wherein when the program is executed by the processor, the distributed array mutual coupling error correction method based on an auxiliary signal source in the aforementioned first aspect is implemented.

[0029] In a fourth aspect, an embodiment of the present application provides a computer-readable storage medium, on which a program or instruction is stored. When the program or instruction is executed by a processor, the distributed array mutual coupling error correction method based on an auxiliary signal source in the aforementioned first aspect is implemented.

[0030] The present application provides a distributed array mutual coupling error correction method and system based on auxiliary information sources. Compared with the prior art, it has the following beneficial effects:

[0031] The present application is to correct the mutual coupling error of a distributed array. An auxiliary information source is arranged on the outside of the distributed array. There is no need to determine the precise position of the auxiliary information source, which is easy to implement in engineering. By receiving the signal of the auxiliary information source, the received signal vector is extracted and an objective function is constructed to locate the auxiliary information source. The present application updates the quantum position of the quantum operator based on a quantum arithmetic search mechanism, and then determines the optimal quantum position and the optimal fitness value to estimate and determine the auxiliary source target angle. The quantum arithmetic search mechanism has the characteristics of fast convergence speed and high convergence accuracy. The mutual coupling error coefficient of the distributed array is calculated through the auxiliary source target angle, and then the mutual coupling error matrix is ​​obtained. The error correction coefficient of the distributed array can be calculated according to the determined mutual coupling error matrix, and then the mutual coupling error of the distributed array is corrected. The direction finding performance of the corrected distributed array is close to that of an ideal distributed array without mutual coupling error. BRIEF DESCRIPTION OF THE DRAWINGS

[0032] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0033] Figure 1 It is a flow chart of a distributed array mutual coupling error correction method based on an auxiliary signal source provided in an embodiment of the present application;

[0034] Figure 2 yes Figure 1 An exemplary flow chart of S110;

[0035] Figure 3 is a schematic diagram of the layout of a distributed array provided in an embodiment of the present application;

[0036] Figure 4 is a graph of the root mean square error of angle estimation before and after the distributed array error correction and a graph of the root mean square error of angle estimation of the ideal distributed array under different signal-to-noise ratios;

[0037] Figure 5 It is a graph of the root mean square error of angle estimation before and after the distributed array error correction and a graph of the root mean square error of angle estimation of the ideal distributed array under different snapshot numbers of the auxiliary signal source and the unknown signal source;

[0038] Figure 6 It is a structural schematic diagram of a distributed array mutual coupling error correction system based on an auxiliary signal source provided in an embodiment of the present application;

[0039] Figure 7 It is a structural schematic diagram of an electronic device provided in an embodiment of the present application. DETAILED DESCRIPTION

[0040] In order to make the purpose, technical solutions and advantages of the embodiments of the present invention clearer, the technical solutions in the embodiments of the present invention are clearly and completely described. Obviously, the described embodiments are part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0041] It should be noted that, in this article, relational terms such as first and second, etc. are only used to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Moreover, the terms "include", "comprise" or any other variants thereof are intended to cover non-exclusive inclusion, so that a process, method, article or device including a series of elements includes not only those elements, but also other elements not explicitly listed, or also includes elements inherent to such process, method, article or device. In the absence of further restrictions, the elements defined by the sentence "comprise a ..." do not exclude the existence of other identical elements in the process, method, article or device including the elements.

[0042] The embodiments of the present application provide a distributed array mutual coupling error correction method and system based on an auxiliary signal source, thereby solving the problem of technical barriers in the mutual coupling error correction of distributed arrays; and achieving fast and accurate mutual coupling error correction for distributed arrays.

[0043] The technical solution in the embodiment of the present application is to solve the above technical problems, and the overall idea is as follows:

[0044] Antennas are the entrances and exits of wireless communication base station systems. Antennas can transmit signals and support the mobility of terminals. With the rapid development of 5G technology, antenna distributed array systems, as a highly competitive technology, have become an indispensable key technology by fully tapping into spatial channel resources to effectively improve system capacity and reliability and reduce the complexity of interference elimination without the need for additional spectrum resources and transmission power. The antenna distributed array system is a network composed of spatially separated antenna nodes, which are connected to a common source through a transmission medium to provide wireless services within a geographic area or structure. As an implementation form of a multi-antenna system, the antenna distributed array system can significantly improve user coverage and communication capacity without increasing spectrum overhead.

[0045] At present, by constructing a suitable distributed array, better direction finding performance can be achieved under the same number of array elements. However, distributed arrays may have various errors, among which mutual coupling error is the most common. In related technologies, mutual coupling error correction can be performed on uniform linear arrays based on sparse Bayesian or blind source separation. The correction process of antenna mutual coupling error is computationally intensive and is designed for uniform linear arrays. There is a lack of research on distributed arrays. When mutual coupling error exists, the direction finding performance of distributed arrays will drop sharply or even fail. It is of great significance and value to study the mutual coupling error correction method of distributed arrays.

[0046] In order to better understand the above technical solution, the above technical solution will be described in detail below in conjunction with the accompanying drawings and specific implementation methods.

[0047] The following first introduces a distributed array mutual coupling error correction method based on an auxiliary signal source provided in an embodiment of the present application.

[0048] The present application provides a flow chart of a distributed array mutual coupling error correction method based on an auxiliary signal source, as shown in FIG. Figure 1 As shown, the method may include the following steps S110-S170.

[0049] S110, arranging an auxiliary information source outside the distributed array whose mutual coupling error is to be corrected, receiving a signal sent by the auxiliary information source through the distributed array, and constructing a snapshot sampling signal model and a mutual coupling matrix.

[0050] S120, extracting the received signal vector of the uniform sub-array in the distributed array, and constructing the objective function of the auxiliary signal source for positioning.

[0051] S130, initializing a preset quantum arithmetic search mechanism, determining a fitness function of the quantum arithmetic search mechanism based on an objective function, and calculating a fitness value of the quantum operator.

[0052] S140, executing the quantum arithmetic search mechanism, selecting a corresponding update strategy according to probability to update the quantum rotation angle of the quantum arithmetic search mechanism, and obtaining a target rotation angle.

[0053] S150, according to the target rotation angle, using the simulated quantum rotation gate to update the quantum position of the quantum operator, determine the optimal quantum position and optimal fitness value of the quantum arithmetic search mechanism, so as to estimate and determine the auxiliary source target angle.

[0054] S160. Based on the auxiliary source target angle, calculate the mutual coupling error coefficient and mutual coupling error matrix of the distributed array.

[0055] S170. Determine an error correction coefficient of the distributed array according to the mutual coupling error matrix to correct the mutual coupling error of the distributed array.

[0056] The above is a specific implementation method of an embodiment of the present application. It can be understood that the present application is to perform mutual coupling error correction on a distributed array. An auxiliary information source is arranged on the outside of the distributed array. There is no need to determine the precise position of the auxiliary information source, which is easy to implement in engineering. By receiving the signal of the auxiliary information source, the received signal vector is extracted and the objective function is constructed to locate the auxiliary information source; the present application updates the quantum position of the quantum operator based on a quantum arithmetic search mechanism, and then determines the optimal quantum position and the optimal fitness value to estimate and determine the auxiliary source target angle. The quantum arithmetic search mechanism has the characteristics of fast convergence speed and high convergence accuracy; the mutual coupling error coefficient of the distributed array is calculated by the auxiliary source target angle, and then the mutual coupling error matrix is ​​obtained; the error correction coefficient of the distributed array can be calculated according to the determined mutual coupling error matrix, and then the mutual coupling error of the distributed array is corrected. The direction finding performance of the corrected distributed array is close to that of an ideal distributed array without mutual coupling error; the error correction method provided by the present application has high correction accuracy and low computational complexity, and has important practical value.

[0057] In some embodiments, Figure 2 As shown, the auxiliary information source is arranged outside the distributed array of the mutual coupling error to be corrected, the signal sent by the auxiliary information source is received through the distributed array, and a snapshot sampling signal model and a mutual coupling matrix are constructed, that is, S110 can specifically include the following steps:

[0058] S210, determining a distributed array of mutual coupling errors to be corrected, where the distributed array includes a plurality of uniform arrays, and the plurality of uniform arrays are arranged in a straight line.

[0059] S220. Arrange a narrowband far-field auxiliary information source in space. The auxiliary information source is located outside the distributed array, and its signal wave direction is set at an angle to the normal direction of the distributed array.

[0060] S230, receiving a signal vector of an auxiliary signal source through a distributed array, and establishing a snapshot sampling signal model and a mutual coupling matrix corresponding to the distributed array.

[0061] In the embodiments of this application, please refer to Figure 3 , a narrowband far-field auxiliary signal source is arranged in space, the wavelength of the auxiliary signal source is λ, and the angle between the signal direction of the auxiliary signal source and the array normal is Angle of auxiliary source It does not need to be known precisely. Suppose the distributed array consists of Z uniform arrays, and all uniform arrays are arranged in a straight line; among them, the nth subarray has M ηarray elements, η∈[1,Z], the number of array elements in the entire array is The spacing between the elements in all sub-arrays is d, and Define the distance between the first array elements of each subarray as It is an integer multiple of d, and there is no overlapping array element between each sub-array, o∈[1,Z-1].

[0062] In one example, The snapshot sampling signal model corresponding to the signal vector of the secondary auxiliary source satisfies the expression: Where C represents the mutual coupling matrix of the distributed array, It is The noise vector under the next snapshot obeys the Gaussian distribution. It is The auxiliary source signal vector at the next snapshot, is the maximum number of snapshots; represents the ideal array steering vector of the distributed array and satisfies the expression:

[0063]

[0064] In the formula, (·) T is the matrix transpose operation, b m represents the position of the mth array element relative to the first array element, m∈[2,W], λ represents the wavelength of the auxiliary signal source; Represents the angle between the signal direction of the auxiliary source and the normal direction of the distributed array.

[0065] In some embodiments, the aforementioned mutual coupling matrix is ​​a block diagonal matrix and satisfies the expression:

[0066]

[0067] In the formula, the nth matrix on the main diagonal of the matrix is is the sub-coupling matrix corresponding to the ηth sub-array, η∈[1,Z]; the sub-array of the distributed array is a uniform array, and With symmetric Toeplitz characteristics, The qth 1 Row q 2 Elements of a column Satisfies the expression:

[0068]

[0069] In the formula, represents the mutual coupling coefficient vector of the mutual coupling matrix, q 1 and q2 ∈[1,M η ]; p is the mutual coupling degree of freedom of the distributed array, and the mutual coupling degree of freedom p satisfies: And M η >p-1; is the distance between the first array element of each subarray, d is the array element spacing in all subarrays, and there is no overlapping array element between each subarray. η is the number of array elements in the nth subarray.

[0070] It should be noted that, according to the properties of block matrix multiplication, the l-th auxiliary source snapshot sampling signal model received by the distributed array can be expressed as in, is the array received signal of the nth subarray, is the ideal array steering vector for the nth subarray.

[0071] In some embodiments, the aforementioned extraction of the received signal vector of the uniform sub-array in the distributed array and the construction of the objective function of the auxiliary signal source for positioning, that is, the aforementioned S120 may specifically include the following steps:

[0072] S310: extracting received data of a sub-array in a distributed array, and calculating a covariance matrix corresponding to the received data.

[0073] S320, performing eigenvalue decomposition on the covariance matrix to obtain a set of eigenvalues; wherein the eigenvectors corresponding to the eigenvalues ​​correspond to the signal subspace of the received signal vector.

[0074] S330. Based on the characteristic that the noise subspace of the subarray is orthogonal to the actual steering vector of the subarray, construct an objective function for the auxiliary source for angle estimation; wherein the objective function does not include a mutual coupling error vector to achieve accurate estimation of the auxiliary source angle.

[0075] In the embodiment of the present application, specifically, the present application can extract the received data of the nth subarray in the distributed array. And calculate its covariance matrix No.v 1 Row v 2 The elements of the column can be estimated from the received data of the nth sub-matrix as and They are No.v 1 Row and v 2 Line, v 1 and v 2 ∈[1,M η ],(·) * It is the conjugate operation.

[0076] In the covariance matrix In the process of eigenvalue decomposition, it can be understood that according to the properties of eigenvalue decomposition, Written as Among them, U s is the eigenvector corresponding to the largest eigenvalue, i.e., the signal subspace of the subarray receiving signal, Σ S is the largest eigenvalue; U N It is a smaller M η -1 eigenvalue corresponding to the eigenvector, that is, the noise subspace of the subarray receiving signal; Σ N It is a smaller M η -1 diagonal matrix of eigenvalues.

[0077] It should be noted that, by utilizing the characteristics that the noise subspace of the subarray is orthogonal to the actual steering vector of the subarray, an objective function for angle estimation of the auxiliary source can be constructed; the actual array steering vector of the nth subarray is recorded as It is understandable that due to With symmetric Toeplitz characteristics, we can define an M η ×p-dimensional matrix Will Rewrite as matrix u 1 Row u 2 The elements of a column can be represented as:

[0078]

[0079] in, and They are u 1 elements, uth 1 +u 2 -1 element and u-th element 1 -u 2 +1 element.

[0080] Furthermore, in the embodiment of the present application, it is assumed that the matrix According to the orthogonality of the subarray noise subspace and the actual subarray steering vector, the objective function of the auxiliary source angle estimation can be written as Since the elements in the mutual coupling coefficient vector c are not equal to 0, the objective function of the auxiliary source angle estimation can be equivalently rewritten as Among them, det(·) is a matrix determinant operation; the rewritten objective function does not contain the mutual coupling error vector, based on which, the accurate estimation of the auxiliary source angle can be achieved.

[0081] In some embodiments, the aforementioned initialization of the preset quantum arithmetic search mechanism, and the fitness function of the quantum arithmetic search mechanism is determined based on the objective function, and the fitness value of the quantum operator is calculated, that is, the aforementioned S130 may specifically include the following steps:

[0082] S410: Obtain a preset quantum arithmetic search mechanism, and initialize the quantum arithmetic search mechanism.

[0083] S420, processing the objective function through the initialized quantum algorithm search mechanism to determine the corresponding fitness value.

[0084] In one example, the number of quantum operators in the population of a quantum arithmetic search mechanism is denoted by The maximum number of iterations is denoted by T, and the iteration number is denoted by t. At the first iteration, the quantum positions of all quantum operators are initialized to random numbers between [0,1]. At the tth iteration, The quantum position of a quantum operator is and No. The physical position of a quantum operator is denoted by In the formula, δ min and δ max They are respectively the lower and upper limits of the search boundary of the quantum arithmetic search mechanism.

[0085] In one example, according to the objective function of the auxiliary source angle estimation, at the tth iteration, The fitness function of a quantum operator satisfies the expression:

[0086]

[0087] Where U N Indicates a smaller M η -1 eigenvalue corresponding to the eigenvector, For U N The corresponding conjugate transposed matrix; For a defined M η ×p-dimensional matrix, M η is the number of array elements in the nth subarray, p is the mutual coupling degree of freedom of the distributed array, For the matrix The conjugate transposed matrix of .

[0088] In some embodiments, the aforementioned execution of the quantum arithmetic search mechanism, selecting a corresponding update strategy according to probability to update the quantum rotation angle of the quantum arithmetic search mechanism, and obtaining the target rotation angle, that is, the aforementioned S140 may specifically include the following steps:

[0089] S510, define target variables and a first random number between 0 and 1 The target variable satisfies: Among them, h l and h m The target variables are The lower and upper limits of h m >h l And h m and h l ∈[0,1]; t is the current iteration number, and T is the maximum number of iterations.

[0090] S520, according to the size relationship between the target variable and the first random number, a corresponding update strategy is selected by the quantum operator of the quantum algorithm search mechanism to update the quantum rotation angle.

[0091] S530: When the first random number is smaller than the target variable, that is, when When , the quantum rotation angle update strategy corresponding to the quantum operator satisfies:

[0092]

[0093] S540, when the random number is greater than or equal to the target variable, that is, when When , the quantum rotation angle update strategy corresponding to the quantum operator satisfies:

[0094]

[0095] In the formula, the variable Used to store the quantum position corresponding to the best quantum operator up to the tth iteration, is a second random number uniformly distributed between [0,1], μ is a constant set between (0,1), α is a constant set between (0,10), and ε is a very small positive number to prevent the formula from having extreme points. ω 1 is a constant between (0,1); is a third random number uniformly distributed between [0,1], ω 2 is a constant between (0,1).

[0096] In some embodiments, the variable Used to store the tth iteration The fitness value of a quantum operator is defined as It is used to store the fitness value corresponding to the best quantum operator until the tth iteration. According to the target rotation angle, the quantum position of the quantum operator is updated using a simulated quantum rotation gate to determine the optimal quantum position and the optimal fitness value of the quantum arithmetic search mechanism to estimate and determine the auxiliary source target angle, that is, the aforementioned S150 may specifically include the following steps:

[0097] S610: According to the updated target rotation angle, the quantum position of the quantum operator is updated using a simulated quantum rotation gate to obtain a quantum target position.

[0098] S620, converting the quantum target position into a physical position, and calculating and updating the fitness value of the quantum operator.

[0099] S630, the fitness value of the lth quantum operator in the t+1 generation In the largest case, if Then Otherwise,

[0100] S640: When the current number of iterations is equal to the maximum number of iterations T, output the current And by The optimal auxiliary source angle estimation result of the quantum arithmetic search mechanism is obtained, δ min and δ max They are respectively the lower and upper limits of the search boundary of the quantum arithmetic search mechanism.

[0101] S650. When the current number of iterations is less than the maximum number of iterations T, set t=t+1, re-execute the quantum arithmetic search mechanism, and select a corresponding update strategy according to probability to update the quantum rotation angle of the quantum arithmetic search mechanism.

[0102] In the embodiments of the present application, specifically, The quantum position update formula of a quantum operator is Convert the updated quantum position of the quantum operator into a physical position Calculate and update the fitness value of the quantum operator

[0103] It can be understood that in the process of iterative processing based on the quantum arithmetic search mechanism, if the fitness value of the lth quantum operator in the t+1 generation is Maximum, if satisfied Then otherwise Determine whether the number of iterations is equal to T. If so, output And by The optimal auxiliary source angle estimation result of the quantum arithmetic search mechanism is obtained, that is, the auxiliary source target angle; if not, set t=t+1 and return to the aforementioned S140 to continue execution.

[0104] In some embodiments, in the process of calculating the mutual coupling error coefficient and the mutual coupling error matrix of the distributed array based on the auxiliary source target angle, that is, in the aforementioned S160, the mutual coupling error coefficient can be calculated based on the estimated auxiliary source precise angle; the final estimated mutual coupling error matrix can be determined according to the mutual coupling error coefficient; the mutual coupling error coefficient satisfies the expression:

[0105]

[0106] Where τ=[1,0,...,0] T is a p×1-dimensional column vector, To estimate the auxiliary source target angle, for The inverse matrix of .

[0107] It should also be noted that the present application has actually verified the technical effect of the distributed array mutual coupling error correction method based on auxiliary signal sources proposed in the present application through experiments.

[0108] Specifically, for the mutual coupling coefficient vector, the mutual coupling degrees of freedom are set to p=3 in all simulations, and the mutual coupling coefficient vector is set to c=[1,0.714+0.438j,0.471+0.594j]; for the quantum arithmetic search mechanism, the parameters are set to: T=150 in all simulations, Search for lower bound δ min =-90, search boundary upper limit δ max =90,h l =0.2,h m =1,α=5,μ=0.5,ε=10 -6 ,ω 1 =ω 2 =0.5.

[0109] exist Figure 4 In the auxiliary signal source angle Set to 20°, the signal-to-noise ratio of the auxiliary source is set to 10dB, and the snapshot of the auxiliary source signal is set to The total number of distributed array elements is W = 20, which is composed of Z = 4 uniform array sub-arrays with equal spacing. The number of elements in each uniform array sub-array is M. η=5, and the uniform subarray spacing is 20d. Three unknown far-field narrowband signals are set, and the incident angles of the signal sources are random values ​​between [-15°, -10°], [-5°, 0°], and [10°, 20°], respectively. The number of snapshots of the unknown signal source is 1000 times. The direction of arrival estimation method adopts the MUSIC method proposed by Schmidt RO in "Multiple emitter location and signal parameter estimation" (1986, 34 (3): 276-280) published in "IEEE Transactions on Antennas and Propagation", and the spectrum peak search step is set to 0.1°. The number of independent repeated experiments of the simulation is 200 times. It can be seen that after the mutual coupling error compensation is performed by the method of the present invention, the direction finding performance of the distributed array is significantly improved, which is close to the direction finding performance of the ideal distributed array.

[0110] exist Figure 5 In the , the auxiliary signal source angle and unknown signal source angle settings are the same as Figure 4 Same, distributed array settings and Figure 4 The signal-to-noise ratio of the auxiliary signal source and the unknown signal source is set to 5dB. Figure 4 Similarly, the number of independent repeated experiments of the simulation is 200. It can be seen that after the mutual coupling error compensation is performed by the method of the present invention, the direction finding performance of the distributed array is significantly improved.

[0111] In some embodiments, the present application provides a distributed array mutual coupling error correction system 700 based on an auxiliary signal source, such as Figure 6 As shown, the system 700 may include the following modules:

[0112] The arrangement and construction module 710 is used to arrange an auxiliary information source outside the distributed array whose mutual coupling error is to be corrected, receive the signal sent by the auxiliary information source through the distributed array, and construct a snapshot sampling signal model and a mutual coupling matrix.

[0113] The extraction and construction module 720 is used to extract the received signal vector of the uniform sub-array in the distributed array and construct the objective function of the auxiliary signal source for positioning.

[0114] The initialization module 730 is used to initialize the preset quantum arithmetic search mechanism, determine the fitness function of the quantum arithmetic search mechanism based on the objective function, and calculate the fitness value of the quantum operator.

[0115] The execution update module 740 is used to execute the quantum arithmetic search mechanism, select a corresponding update strategy according to probability to update the quantum rotation angle of the quantum arithmetic search mechanism, and obtain the target rotation angle.

[0116] The estimation module 750 is used to update the quantum position of the quantum operator using a simulated quantum rotation gate according to the target rotation angle, determine the optimal quantum position and optimal fitness value of the quantum arithmetic search mechanism, and estimate the auxiliary source target angle.

[0117] The calculation module 760 is used to calculate the mutual coupling error coefficient and the mutual coupling error matrix of the distributed array based on the auxiliary source target angle.

[0118] The correction module 770 is used to determine the error correction coefficient of the distributed array according to the mutual coupling error matrix to correct the mutual coupling error of the distributed array.

[0119] According to an embodiment of the present application, any multiple modules among the arrangement construction module 710, the extraction construction module 720, the initialization module 730, the execution update module 740, the estimation module 750, the calculation module 760 and the correction module 770 can be combined into one module for implementation, or any one of the modules can be split into multiple modules. Alternatively, at least part of the functions of one or more of these modules can be combined with at least part of the functions of other modules and implemented in one module.

[0120] In some embodiments, the arrangement construction module 710 may be specifically used to:

[0121] Determine a distributed array of mutual coupling errors to be corrected, the distributed array comprising a plurality of uniform arrays, and the plurality of uniform arrays are arranged in a straight line;

[0122] Arrange a narrowband far-field auxiliary signal source in space, the auxiliary signal source is located outside the distributed array, and its signal wave direction is set at an angle to the normal direction of the distributed array;

[0123] The signal vector of the auxiliary signal source is received through the distributed array, and a snapshot sampling signal model and a mutual coupling matrix corresponding to the distributed array are established.

[0124] In some embodiments, the extraction construction module 720 may be specifically used to:

[0125] Extracting received data of a subarray in a distributed array and calculating a covariance matrix corresponding to the received data;

[0126] Performing eigenvalue decomposition on the covariance matrix to obtain a set of eigenvalues; wherein the eigenvectors corresponding to the eigenvalues ​​correspond to the signal subspace of the received signal vector;

[0127] Based on the characteristic that the noise subspace of the subarray is orthogonal to the actual steering vector of the subarray, an objective function of the auxiliary source for angle estimation is constructed; wherein the objective function does not include the mutual coupling error vector to achieve accurate estimation of the auxiliary source angle.

[0128] In some embodiments, the initialization module 730 may be specifically used to:

[0129] Obtain a preset quantum arithmetic search mechanism and initialize the quantum arithmetic search mechanism;

[0130] The objective function is processed through the initialized quantum algorithm search mechanism to determine the corresponding fitness value.

[0131] In some embodiments, the execution update module 740 can be specifically used to: define the target variable and a first random number between 0 and 1 According to the size relationship between the target variable and the first random number, the quantum operator of the quantum algorithm search mechanism selects the corresponding update strategy to update the quantum rotation angle.

[0132] In some embodiments, the estimation module 750 may be specifically configured to:

[0133] According to the updated target rotation angle, the quantum position of the quantum operator is updated using a simulated quantum rotation gate to obtain the quantum target position;

[0134] Convert the quantum target position into a physical position, calculate and update the fitness value of the quantum operator;

[0135] The fitness value of the lth quantum operator in the t+1 generation is In the largest case, if Then Otherwise,

[0136] When the current number of iterations is equal to the maximum number of iterations T, output the current And by The optimal auxiliary source angle estimation result of the quantum arithmetic search mechanism is obtained, δ min and δ max They are the lower and upper bounds of the search boundary of the quantum arithmetic search mechanism;

[0137] When the current number of iterations is less than the maximum number of iterations T, let t=t+1, re-execute the quantum arithmetic search mechanism, and select the corresponding update strategy according to probability to update the quantum rotation angle of the quantum arithmetic search mechanism.

[0138] Figure 6 Each module in the system shown has the function of implementing each step in the aforementioned distributed array mutual coupling error correction method based on auxiliary information source, and can achieve its corresponding technical effect. For the sake of concise description, it will not be repeated here.

[0139] In some embodiments, the present application provides an electronic device, the structure diagram of the electronic device is as follows Figure 7 shown.

[0140] The electronic device may include a processor 810 and a memory 820 storing computer program instructions.

[0141] Specifically, the processor 810 may include a central processing unit (CPU), or an application specific integrated circuit (ASIC), or may be configured to implement one or more integrated circuits of the embodiments of the present application.

[0142] The memory 820 may include a large capacity memory for data or instructions. By way of example and not limitation, the memory 820 may include a hard disk drive (HDD), a floppy disk drive, a flash memory, an optical disk, a magneto-optical disk, a magnetic tape, or a universal serial bus (USB) drive or a combination of two or more of these. In appropriate cases, the memory 820 may include a removable or non-removable (or fixed) medium. In appropriate cases, the memory 820 may be inside or outside the integrated gateway disaster recovery device. In a specific embodiment, the memory 820 is a non-volatile solid-state memory.

[0143] The memory 820 may include a read-only memory (ROM), a random access memory (RAM), a disk storage medium device, an optical storage medium device, a flash memory device, an electrical, optical or other physical / tangible memory storage device. Therefore, generally, the memory 820 includes one or more tangible (non-transitory) computer-readable storage media (e.g., a memory device) encoded with software including computer executable instructions, and when the software is executed (e.g., by one or more processors), it can perform the operations described in any of the distributed array mutual coupling error correction methods based on auxiliary sources in the above embodiments.

[0144] The processor 810 implements any one of the distributed array mutual coupling error correction methods based on auxiliary information sources in the above embodiments by reading and executing computer program instructions stored in the memory 820 .

[0145] In one example, the electronic device may further include a communication interface 830 and a bus 800. Figure 7 As shown, the processor 810, the memory 820, and the communication interface 830 are connected via a bus 800 and communicate with each other.

[0146] The communication interface 830 is mainly used to implement communication between various modules, devices, units and / or equipment in the embodiments of the present application.

[0147] Bus 800 includes hardware, software or both, and the parts of online data flow billing equipment are coupled to each other. For example, but not limitation, bus may include accelerated graphics port (AGP) or other graphics bus, enhanced industrial standard architecture (EISA) bus, front-end bus (FSB), hypertransport (HT) interconnection, industrial standard architecture (ISA) bus, infinite bandwidth interconnection, low pin count (LPC) bus, memory bus, micro channel architecture (MCA) bus, peripheral component interconnection (PCI) bus, PCI-Express (PCI-X) bus, serial advanced technology attachment (SATA) bus, video electronics standard association local (VLB) bus or other suitable bus or two or more of these combinations. In appropriate cases, bus 800 may include one or more buses. Although the present application embodiment describes and shows a specific bus, the application considers any suitable bus or interconnection.

[0148] In addition, in combination with the distributed array mutual coupling error correction method based on auxiliary information source in the above embodiment, the embodiment of the present application can provide a computer storage medium for implementation. The computer storage medium stores computer program instructions; when the computer program instructions are executed by the processor, any one of the distributed array mutual coupling error correction methods based on auxiliary information source in the above embodiment is implemented.

[0149] It should be clear that the present application is not limited to the specific configuration and processing described above and shown in the figures. For the sake of simplicity, a detailed description of the known method is omitted here. In the above embodiments, several specific steps are described and shown as examples. However, the method process of the present application is not limited to the specific steps described and shown, and those skilled in the art can make various changes, modifications and additions, or change the order between the steps after understanding the spirit of the present application.

[0150] The functional blocks shown in the above block diagram can be implemented as hardware, software, firmware or a combination thereof. When implemented in hardware, it can be, for example, an electronic circuit, an application specific integrated circuit (ASIC), appropriate firmware, a plug-in, a function card, etc. When implemented in software, the elements of the present application are programs or code segments that are used to perform the required tasks. The program or code segment can be stored in a machine-readable medium, or transmitted on a transmission medium or a communication link by a data signal carried in a carrier wave. "Machine-readable medium" can include any medium capable of storing or transmitting information. Examples of machine-readable media include electronic circuits, semiconductor memory devices, ROM, flash memory, erasable ROM (EROM), floppy disks, CD-ROMs, optical disks, hard disks, optical fiber media, radio frequency (RF) links, etc. The code segment can be downloaded via a computer network such as the Internet, an intranet, etc.

[0151] It should also be noted that the exemplary embodiments mentioned in this application describe some methods or systems based on a series of steps or devices. However, this application is not limited to the order of the above steps, that is, the steps can be performed in the order mentioned in the embodiment, or in a different order from the embodiment, or several steps can be performed simultaneously.

[0152] Aspects of the present disclosure are described above with reference to the flowchart and / or block diagram of the method, device (system) and computer program product according to the embodiment of the present disclosure. It should be understood that each box in the flowchart and / or block diagram and the combination of each box in the flowchart and / or block diagram can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, or other programmable data processing device to produce a machine so that these instructions executed by the processor of the computer or other programmable data processing device enable the implementation of the function / action specified in one or more boxes of the flowchart and / or block diagram. Such a processor can be, but is not limited to, a general-purpose processor, a special-purpose processor, a special application processor, or a field programmable logic circuit. It can also be understood that each box in the block diagram and / or flowchart and the combination of boxes in the block diagram and / or flowchart can also be implemented by dedicated hardware that performs a specified function or action, or can be implemented by a combination of dedicated hardware and computer instructions.

[0153] In summary, compared with the prior art, this application has the following beneficial effects:

[0154] 1. In order to correct the mutual coupling error of a distributed array, the present application arranges an auxiliary information source outside the distributed array, receives the signal of the auxiliary information source, extracts the received signal vector and constructs an objective function to locate the auxiliary information source; the mutual coupling error correction method for a distributed array provided by the present application does not need to determine the precise position of the auxiliary information source and is easy to implement in engineering.

[0155] 2. This application updates the quantum position of the quantum operator based on the quantum arithmetic search mechanism, and then determines the optimal quantum position and the optimal fitness value to estimate the auxiliary source target angle. The quantum arithmetic search mechanism has the characteristics of fast convergence speed and high convergence accuracy, low computational complexity, and important practical value.

[0156] 3. The present application calculates the mutual coupling error coefficient of the distributed array through auxiliary source target angles, and then obtains a mutual coupling error matrix; the error correction coefficient of the distributed array can be calculated according to the determined mutual coupling error matrix, and then the mutual coupling error of the distributed array is corrected. The direction finding performance of the corrected distributed array is close to that of an ideal distributed array without mutual coupling error.

[0157] The above embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit the same. Although the present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that the technical solutions described in the aforementioned embodiments may still be modified, or some of the technical features may be replaced by equivalents. However, these modifications or replacements do not deviate the essence of the corresponding technical solutions from the spirit and scope of the technical solutions of the embodiments of the present invention.

Claims

1. A distributed array mutual coupling error correction method based on auxiliary information source, characterized in that: include: Arranging an auxiliary information source outside the distributed array of the mutual coupling error to be corrected, receiving the signal sent by the auxiliary information source through the distributed array, and constructing a snapshot sampling signal model and a mutual coupling matrix; Extracting a received signal vector of a uniform subarray in the distributed array, and constructing an objective function of the auxiliary source for positioning; Initializing a preset quantum arithmetic search mechanism, determining a fitness function of the quantum arithmetic search mechanism based on the objective function, and calculating a fitness value of the quantum operator; Executing the quantum arithmetic search mechanism, and selecting a corresponding update strategy according to probability to update the quantum rotation angle of the quantum arithmetic search mechanism to obtain a target rotation angle; According to the target rotation angle, the quantum position of the quantum operator is updated using a simulated quantum rotation gate, and the optimal quantum position and optimal fitness value of the quantum arithmetic search mechanism are determined to estimate and determine the auxiliary source target angle; Based on the auxiliary source target angle, calculating the mutual coupling error coefficient and the mutual coupling error matrix of the distributed array; According to the mutual coupling error matrix, an error correction coefficient of the distributed array is determined to correct the mutual coupling error of the distributed array.

2. The distributed array mutual coupling error correction method based on auxiliary information source according to claim 1, characterized in that: The method comprises arranging an auxiliary information source outside the distributed array of the mutual coupling error to be corrected, receiving a signal sent by the auxiliary information source through the distributed array, and constructing a snapshot sampling signal model and a mutual coupling matrix, including: Determine a distributed array of mutual coupling errors to be corrected, wherein the distributed array includes a plurality of uniform arrays, and the plurality of uniform arrays are arranged in a straight line; Arranging a narrowband far-field auxiliary information source in space, the auxiliary information source is located outside the distributed array, and its signal wave direction is set at an angle to the normal direction of the distributed array; Receiving the signal vector of the auxiliary information source through the distributed array, establishing a snapshot sampling signal model and a mutual coupling matrix corresponding to the distributed array; Among them, The snapshot sampling signal model corresponding to the signal vector of the secondary auxiliary source satisfies the expression: Where C represents the mutual coupling matrix of the distributed array, It is The noise vector under the next snapshot obeys the Gaussian distribution. It is The auxiliary source signal vector at the next snapshot, is the maximum number of snapshots; represents the ideal array steering vector of the distributed array and satisfies the expression: In the formula, (·) T is the matrix transpose operation, b m represents the position of the mth array element relative to the first array element, m∈[2,W], λ represents the wavelength of the auxiliary signal source; Represents the angle between the signal arrival direction of the auxiliary information source and the normal direction of the distributed array.

3. The distributed array mutual coupling error correction method based on auxiliary information source according to claim 2, characterized in that: The mutual coupling matrix is ​​a block diagonal matrix and satisfies the expression: In the formula, the nth matrix on the main diagonal of the matrix is is the sub-coupling matrix corresponding to the ηth sub-array, η∈[1,Z]; the sub-array of the distributed array is a uniform array, and With symmetric Toeplitz characteristics, The element in row q1 and column q2 of Satisfies the expression: In the formula, represents the mutual coupling coefficient vector of the mutual coupling matrix, q1 and q2∈[1,M η ]; p is the mutual coupling degree of freedom of the distributed array, and the mutual coupling degree of freedom p satisfies: And M η >p-1; is the distance between the first array element of each subarray, d is the array element spacing in all subarrays, and there is no overlapping array element between each subarray. η is the number of array elements in the nth subarray.

4. The distributed array mutual coupling error correction method based on auxiliary information source according to any one of claims 1 to 3, characterized in that: The extracting the received signal vector of the uniform sub-array in the distributed array and constructing the objective function of the auxiliary information source for positioning includes: Extracting received data of a subarray in a distributed array, and calculating a covariance matrix corresponding to the received data; Performing eigenvalue decomposition on the covariance matrix to obtain a set of eigenvalues; wherein the eigenvectors corresponding to the eigenvalues ​​correspond to the signal subspace of the received signal vector; Based on the characteristic that the noise subspace of the subarray is orthogonal to the actual steering vector of the subarray, an objective function of the auxiliary information source for angle estimation is constructed; wherein the objective function does not include a mutual coupling error vector to achieve accurate estimation of the auxiliary information source angle.

5. The distributed array mutual coupling error correction method based on auxiliary information source according to any one of claims 1 or 2, characterized in that: The step of initializing a preset quantum arithmetic search mechanism, determining a fitness function of the quantum arithmetic search mechanism based on the objective function, and calculating a fitness value of a quantum operator includes: Obtaining a preset quantum arithmetic search mechanism and initializing the quantum arithmetic search mechanism; Processing the objective function through the initialized quantum algorithm search mechanism to determine the corresponding fitness value; Among them, in the population of the quantum arithmetic search mechanism, the number of quantum operators is recorded as The maximum number of iterations is denoted by T, and the iteration number is denoted by t. At the first iteration, the quantum positions of all quantum operators are initialized to random numbers between [0,1]. At the tth iteration, The quantum position of a quantum operator is and No. The physical position of a quantum operator is denoted by In the formula, δ min and δ max They are the lower and upper bounds of the search boundary of the quantum arithmetic search mechanism; According to the objective function of the auxiliary source angle estimation, at the tth iteration, The fitness function of a quantum operator satisfies the expression: Where U N Indicates a smaller M η -1 eigenvalue corresponding to the eigenvector, For U N The corresponding conjugate transposed matrix; For a defined M η ×p-dimensional matrix, M η is the number of array elements in the nth subarray, p is the mutual coupling degree of freedom of the distributed array, For the matrix The conjugate transposed matrix of .

6. The distributed array mutual coupling error correction method based on auxiliary information source according to any one of claims 1 to 3, characterized in that: The step of executing the quantum arithmetic search mechanism and selecting a corresponding update strategy according to probability to update the quantum rotation angle of the quantum arithmetic search mechanism to obtain a target rotation angle includes: Define the target variable and a first random number between 0 and 1 The target variable satisfies: Among them, h l and h m The target variables are The lower and upper limits of h m >h l And h m and h l ∈[0,1]; t is the current iteration number, T is the maximum number of iterations; According to the size relationship between the target variable and the first random number, a corresponding update strategy is selected by the quantum operator of the quantum algorithm search mechanism to update the quantum rotation angle; When the first random number is less than the target variable, the quantum rotation angle update strategy corresponding to the quantum operator satisfies: When the random number is greater than or equal to the target variable, the quantum rotation angle update strategy corresponding to the quantum operator satisfies: In the formula, the variable Used to store the quantum position corresponding to the best quantum operator up to the tth iteration, is a second random number uniformly distributed between [0,1], μ is a constant set between (0,1), α is a constant set between (0,10), and ε is a very small positive number to prevent the formula from having extreme points. ω1 is a constant between (0,1); is a third random number uniformly distributed between [0,1], and ω2 is a constant between (0,1).

7. The distributed array mutual coupling error correction method based on auxiliary information source according to any one of claims 1 to 3, characterized in that: Defining variables Used to store the tth iteration The fitness value of a quantum operator is defined as Used to store the fitness value corresponding to the best quantum operator until the tth iteration; The method of updating the quantum position of the quantum operator using a simulated quantum rotation gate according to the target rotation angle, determining the optimal quantum position and the optimal fitness value of the quantum arithmetic search mechanism to estimate and determine the auxiliary source target angle includes: According to the updated target rotation angle, the quantum position of the quantum operator is updated using a simulated quantum rotation gate to obtain a quantum target position; Converting the quantum target position into a physical position, and calculating and updating the fitness value of the quantum operator; The fitness value of the lth quantum operator in the t+1 generation is In the largest case, if Then Otherwise, When the current number of iterations is equal to the maximum number of iterations T, output the current And by The optimal auxiliary source angle estimation result of the quantum arithmetic search mechanism is obtained, δ min and δ max They are the lower and upper bounds of the search boundary of the quantum arithmetic search mechanism; When the current number of iterations is less than the maximum number of iterations T, let t=t+1, re-execute the quantum arithmetic search mechanism, and select a corresponding update strategy according to probability to update the quantum rotation angle of the quantum arithmetic search mechanism.

8. A distributed array mutual coupling error correction system based on auxiliary information source, characterized in that: include: An arrangement and construction module is used to arrange an auxiliary information source outside the distributed array of the mutual coupling error to be corrected, receive the signal sent by the auxiliary information source through the distributed array, and construct a snapshot sampling signal model and a mutual coupling matrix; An extraction and construction module, used to extract the received signal vector of the uniform sub-array in the distributed array and construct the objective function of the auxiliary information source for positioning; An initialization module, used to initialize a preset quantum arithmetic search mechanism, determine a fitness function of the quantum arithmetic search mechanism based on the objective function, and calculate a fitness value of the quantum operator; An execution update module is used to execute the quantum arithmetic search mechanism, select a corresponding update strategy according to probability to update the quantum rotation angle of the quantum arithmetic search mechanism, and obtain a target rotation angle; An estimation module is used to update the quantum position of the quantum operator using a simulated quantum rotation gate according to the target rotation angle, determine the optimal quantum position and optimal fitness value of the quantum arithmetic search mechanism, so as to estimate and determine the auxiliary source target angle; A calculation module, used for calculating the mutual coupling error coefficient and the mutual coupling error matrix of the distributed array based on the auxiliary source target angle; The correction module is used to determine the error correction coefficient of the distributed array according to the mutual coupling error matrix to correct the mutual coupling error of the distributed array.

9. An electronic device, characterized in that: include: A processor, a memory, and a program stored in the memory and executable on the processor, wherein when the program is executed by the processor, the distributed array mutual coupling error correction method based on an auxiliary information source as described in any one of claims 1 to 7 is implemented.

10. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores a program or instruction, and when the program or instruction is executed by the processor, the distributed array mutual coupling error correction method based on the auxiliary information source as described in any one of claims 1 to 7 is implemented.

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