Radar target parameter estimation method and device, electronic equipment, medium and product

Abstract

The invention provides a target parameter estimation method and device of a radar, electronic equipment, a medium and a product. The method comprises the following steps: acquiring array element spacing and carrier information of a carrier frequency control array radar; determining a snapshot signal of the target object according to the array element spacing, the carrier offset, the carrier number and the carrier signal receiving offset angle; performing matrix reconstruction according to the snapshot signal to obtain a reconstructed signal covariance matrix; and performing parameter estimation according to the reconstructed signal covariance matrix and an alternating direction multiplier method to obtain single snapshot target parameters of the carrier frequency control array radar on the target object. According to the technical scheme of the invention, the snapshot signal of the target object is determined based on the carrier frequency controlled array radar under the single snapshot, the matrix reconstruction is carried out, then the parameter estimation is carried out according to the reconstructed signal covariance matrix and the alternating direction multiplier method, and the single snapshot target parameter of the carrier frequency controlled array radar on the target object is obtained. The alternating direction multiplier is adopted to solve the single-snapshot target parameter, the problem complexity is reduced, and the precision of the single-snapshot target parameter is improved.

Description

Technical Field

[0001] The present invention relates to the field of radar technology, and in particular to a radar target parameter estimation method, device, electronic equipment, medium and product. Background Art

[0002] Radar target parameter estimation is an important part of radar signal processing. It refers to the process of determining the various physical properties and states of the target by analyzing the echo signals received by the radar.

[0003] At present, in the existing technology, for the estimation of radar single snapshot parameters, sparse recovery methods such as orthogonal matching pursuit and atomic norm minimization are usually used. Among them, the best effect is the gridless sparse recovery method based on atomic norm minimization (ANM), which models the signal recovery problem as a semi-positive definite programming problem and then uses the interior point method to solve it. The existing solution of the semi-positive definite programming problem by the interior point method leads to high computational complexity and long estimated operation time. Summary of the invention

[0004] The present invention provides a radar target parameter estimation method, device, electronic device, medium and product, which are used to solve the defects of high computational complexity and long estimation operation time caused by solving semi-positive definite programming problems by interior point method in the prior art, realize the determination of snapshot signals of target objects based on single snapshot carrier frequency controlled array radar, perform matrix reconstruction based on snapshot signals, obtain reconstructed signal covariance matrix, and then perform parameter estimation based on reconstructed signal covariance matrix and alternating direction multiplier method to obtain single snapshot target parameters of target objects by carrier frequency controlled array radar, adopt alternating direction multiplier to solve single snapshot target parameters, reduce problem complexity and improve the accuracy of single snapshot target parameters.

[0005] The present invention provides a radar target parameter estimation method, comprising the following steps.

[0006] The array element spacing and carrier information of the carrier frequency-controlled array radar are obtained; wherein the array element spacing includes the distance between adjacent array elements set on the carrier frequency-controlled array radar, and the carrier information includes the carrier offset, the number of carriers and the carrier signal receiving offset angle.

[0007] The snapshot signal of the target object is determined based on the array element spacing, carrier offset, number of carriers and carrier signal reception offset angle.

[0008] Matrix reconstruction is performed according to the snapshot signal to obtain the reconstructed signal covariance matrix.

[0009] Parameter estimation is performed based on the reconstructed signal covariance matrix and the alternating direction multiplier method to obtain the single snapshot target parameters of the target object by the carrier frequency controlled array radar.

[0010] According to a target parameter estimation method of a radar provided by the present invention, a snapshot signal of a target object is determined according to array element spacing, carrier offset, carrier number and carrier signal receiving offset angle, including: obtaining a target distance of the target object from a carrier frequency-controlled array radar; determining a distance element parameter according to the target distance, carrier offset, light speed and carrier number; obtaining the number of array elements of the carrier frequency-controlled array radar; determining an angle element parameter according to the number of array elements, array element spacing, carrier signal receiving offset angle and carrier wavelength; and determining a snapshot signal according to the distance element parameter, the angle element parameter and a Gaussian noise matrix.

[0011] According to a target parameter estimation method of a radar provided by the present invention, matrix reconstruction is performed according to snapshot signals to obtain a reconstructed signal covariance matrix, including: format conversion of the snapshot signal to obtain a vectorized snapshot signal; obtaining the number of snapshots of the carrier frequency-controlled array radar; when the number of snapshots is less than or equal to a preset threshold, matrix reconstruction is performed according to the vectorized snapshot signal to obtain a reconstructed signal covariance matrix.

[0012] According to a target parameter estimation method of a radar provided by the present invention, matrix reconstruction is performed according to a vectorized snapshot signal to obtain a reconstructed signal covariance matrix, including: determining a receiving distance frequency according to a carrier offset, a number of carriers and a target distance; determining a receiving angle frequency according to the number of array elements, an array element spacing and a carrier signal receiving offset angle; determining a receiving signal vector according to the receiving distance frequency, the receiving angle frequency and a vectorized snapshot signal; determining a received signal according to the received signal vector; and performing matrix reconstruction on the received signal to obtain a reconstructed signal covariance matrix.

[0013] According to a radar target parameter estimation method provided by the present invention, a received signal is matrix reconstructed to obtain a reconstructed signal covariance matrix, including: matrix reconstructing the received signal to obtain an atomic norm; and formatting the atomic norm to obtain a reconstructed signal covariance matrix.

[0014] According to a radar target parameter estimation method provided by the present invention, parameter estimation is performed according to a reconstructed signal covariance matrix and an alternating direction multiplier method to obtain a single-snapshot target parameter of a carrier frequency-controlled array radar to a target object, comprising: constructing an augmented Lagrangian function according to the reconstructed signal covariance matrix; updating the augmented Lagrangian function according to the alternating direction multiplier method to obtain matrix parameters; determining a double matrix according to the matrix parameters and the reconstructed signal covariance matrix; performing eigenvalue decomposition on the double matrix to obtain characteristic parameters; and determining the single-snapshot target parameter of the carrier frequency-controlled array radar to the target object according to the characteristic parameters.

[0015] The present invention also provides a target parameter estimation device for a radar, comprising the following modules.

[0016] The information acquisition module is used to obtain the array element spacing and carrier information of the carrier frequency-controlled array radar; wherein the array element spacing includes the distance between adjacent array elements set on the carrier frequency-controlled array radar, and the carrier information includes the carrier offset, the number of carriers and the carrier signal receiving offset angle.

[0017] The signal determination module is used to determine the snapshot signal of the target object according to the array element spacing, carrier offset, number of carriers and carrier signal reception offset angle.

[0018] The matrix reconstruction module is used to perform matrix reconstruction according to the snapshot signal to obtain the reconstructed signal covariance matrix.

[0019] The parameter estimation module is used to perform parameter estimation based on the reconstructed signal covariance matrix and the alternating direction multiplier method to obtain the single-snap target parameters of the carrier frequency-controlled array radar for the target object.

[0020] The present invention also provides an electronic device, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor. When the processor executes the computer program, a target parameter estimation method for any of the above-mentioned radars is implemented.

[0021] The present invention also provides a non-transitory computer-readable storage medium on which a computer program is stored. When the computer program is executed by a processor, the target parameter estimation method of any of the above-mentioned radars is implemented.

[0022] The present invention also provides a computer program product, comprising a computer program, and when the computer program is executed by a processor, the target parameter estimation method of any of the above radars is implemented.

[0023] The present invention provides a radar target parameter estimation method, device, electronic device, medium and product, which obtain the array element spacing and carrier information of the carrier frequency-controlled array radar; wherein the array element spacing includes the distance between adjacent array elements arranged on the carrier frequency-controlled array radar, and the carrier information includes carrier offset, carrier number and carrier signal receiving offset angle; determine the snapshot signal of the target object according to the array element spacing, carrier offset, carrier number and carrier signal receiving offset angle; perform matrix reconstruction according to the snapshot signal to obtain the reconstructed signal covariance matrix; perform parameter estimation according to the reconstructed signal covariance matrix and the alternating direction multiplier method to obtain the single snapshot target parameter of the carrier frequency-controlled array radar for the target object. The technical solution of the present invention is used to solve the defects of high computational complexity and long estimated operation time caused by solving semi-positive definite programming problems by interior point method in the prior art, and realizes determining the snapshot signal of the target object based on the carrier frequency controlled array radar in a single snapshot, and performing matrix reconstruction based on the snapshot signal to obtain the reconstructed signal covariance matrix, and then performing parameter estimation based on the reconstructed signal covariance matrix and the alternating direction multiplier method to obtain the single snapshot target parameters of the carrier frequency controlled array radar for the target object, and using the alternating direction multiplier to solve the single snapshot target parameters, thereby reducing the complexity of the problem and improving the accuracy of the single snapshot target parameters. BRIEF DESCRIPTION OF THE DRAWINGS

[0024] In order to more clearly illustrate the technical solutions in the present invention or the prior art, the following briefly introduces the drawings required for use in the embodiments or the description of the prior art. Obviously, the drawings described below are 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.

[0025] Figure 1 It is a flow chart of the target parameter estimation method of the radar provided by the present invention.

[0026] Figure 2 This is a structural diagram of a multi-carrier frequency control array provided by the present invention.

[0027] Figure 3 Schematic diagram of single snapshot target parameters provided by the present invention.

[0028] Figure 4 It is a schematic diagram of the structure of the target parameter estimation device of the radar provided by the present invention.

[0029] Figure 5 It is a structural schematic diagram of the electronic device provided by the present invention. DETAILED DESCRIPTION

[0030] In order to make the purpose, technical solution and advantages of the present invention clearer, the technical solution of the present invention will be clearly and completely described below in conjunction with the drawings of the present invention. 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.

[0031] Combine the following Figure 1 The target parameter estimation method of the radar provided by the present invention is described. The target parameter estimation method of the radar provided by the present invention can be applicable to the situation of rapid estimation of multiple target parameters of a multi-carrier frequency-controlled radar based on the number of snapshots. The executor of the method can be an electronic device or a target parameter estimation device of the radar arranged in the electronic device. The target parameter estimation device of the radar can be implemented by software, hardware or a combination of both. Figure 1 FIG. 1 is a flow chart of a target parameter estimation method for a radar provided by the present invention, such as Figure 1 As shown, the method includes the following steps 101, 102, 103 and 104.

[0032] Step 101: Obtain array element spacing and carrier information of a carrier frequency-controlled array radar.

[0033] In this step, the array element spacing includes the distance between adjacent array elements set on the carrier frequency controlled array radar, and the carrier information includes the carrier offset, the number of carriers, and the carrier signal receiving offset angle. The carrier information also includes the carrier frequency center of the array element on the carrier frequency controlled array radar, which is not limited in this embodiment.

[0034] Specifically, for a carrier frequency-controlled array radar having a linear array of multiple array elements, the carrier wavelength of the carrier frequency-controlled array radar is obtained, the array element spacing of the carrier frequency-controlled array radar is determined according to the carrier wavelength, and the carrier frequency center, carrier offset, number of carriers and carrier signal reception offset angle corresponding to multiple carriers of multiple array elements on the carrier frequency-controlled array radar are obtained.

[0035] Exemplary, for example, it may be considered that a linear array of a multi-carrier frequency-controlled array radar has multiple array elements, such as M array elements. Figure 2 is a structural diagram of a multi-carrier frequency control array provided by the present invention, such as Figure 2 As shown in the figure, the irregular rectangle on the X-axis represents the array element. There are multiple array elements on the X-axis. The distance between each adjacent array element is the array element spacing. The multi-carriers of each array element are , , …, ,in, , and etc. respectively represent the carrier frequency centers of different carriers, represents the carrier offset, N represents the number of carriers, d represents the array element spacing, Indicates the carrier signal receiving offset angle. The angle between the X-axis and the Y-axis indicates the carrier signal receiving offset angle Array element spacing , It is represented by the carrier wavelength, which is not limited in this embodiment.

[0036] Step 102: Determine a snapshot signal of the target object according to the array element spacing, carrier offset, number of carriers, and carrier signal reception offset angle.

[0037] Specifically, after the array element spacing, carrier offset, number of carriers and carrier signal reception offset angle are obtained, the snapshot signal of the target object is determined according to the array element spacing, carrier offset, number of carriers and carrier signal reception offset angle.

[0038] In a specific implementation, a snapshot signal of a target object is determined based on array element spacing, carrier offset, number of carriers, and carrier signal reception offset angle, including: obtaining a target distance of the target object from a carrier frequency-controlled array radar; determining a distance element parameter based on the target distance, carrier offset, speed of light, and number of carriers; obtaining the number of array elements of the carrier frequency-controlled array radar; determining an angle element parameter based on the number of array elements, array element spacing, carrier signal reception offset angle, and carrier wavelength; and determining a snapshot signal based on the distance element parameter, the angle element parameter, and a Gaussian noise matrix.

[0039] Specifically, suppose there are K target objects located at different locations such as , …, After matched filtering, the receiving end first determines the target distance of the target object from the carrier frequency-controlled array radar, and then determines the distance element parameters according to the target distance, carrier offset, light speed and number of carriers. ,in, represents the set of products of the number of N carriers and 1, Indicates a carrier wave, Indicates the carrier offset, Indicates the target object The corresponding target distance, represents the speed of light, Indicates transposition. Get the number of array elements of the carrier frequency-controlled array radar; determine the angle element parameters according to the number of array elements, array element spacing, carrier signal receiving offset angle and carrier wavelength. ,in, represents the set of products of M array elements and 1, Indicates the target object The corresponding carrier signal receiving offset angle, represents the carrier wavelength, and M represents the number of array elements, i.e., the number of array element antennas. Finally, the snapshot signal is determined based on the distance element parameter, the angle element parameter, and the Gaussian noise matrix. ,in, represents the product of the number of array elements M and the number of carriers N, Represents the total number of target objects, , Indicates The complex reflection coefficient of the target object, Indicates the number of snapshots. Indicates the distance element parameter The transpose of represents the Gaussian noise matrix.

[0040] Step 103: Perform matrix reconstruction according to the snapshot signal to obtain a reconstructed signal covariance matrix.

[0041] In a specific embodiment, matrix reconstruction is performed according to the snapshot signal to obtain a reconstructed signal covariance matrix, including: format conversion of the snapshot signal to obtain a vectorized snapshot signal; obtaining the number of snapshots of the carrier frequency-controlled array radar; when the number of snapshots is less than or equal to a preset threshold, matrix reconstruction is performed according to the vectorized snapshot signal to obtain a reconstructed signal covariance matrix.

[0042] In this step, the number of snapshots refers to the number of single snapshots, and the preset threshold is a preset value for determining the number of snapshots, for example, 1. Determining whether the number of snapshots is less than or equal to the preset threshold is to determine whether the number of snapshots is less than or equal to 1 at this moment. If the number of snapshots is less than or equal to 1, it means that the number of single snapshots is less than or equal to 1, and this embodiment does not limit this.

[0043] Specifically, after determining the snapshot signal, the format of the snapshot signal is converted to obtain a vectorized snapshot signal. ,in, represents the Gaussian noise matrix The corresponding vectorized Gaussian noise matrix after vectorization is, It means Vectorize it. represents the Kronecker product (an operation between two matrices of arbitrary size, the Kronecker product is a special form of tensor product), Represents the Khatri-Rao product (a tensor product operator, mainly used to calculate the outer product of the column vectors of two tensors or matrices), , Indicates the number of carriers N and the total number of target objects The set of products of Indicates the distance element parameter corresponding to target object 1, Indicates the distance element parameter corresponding to target object 2, Indicates the target object Corresponding distance element parameters. , Indicates the number of array elements M and the total number of target objects The set of products of Indicates the angle element parameter corresponding to target object 1. Indicates the angle element parameter corresponding to target object 2. Indicates the target object The corresponding angle element parameter. represents the set of complex reflection coefficients, , Indicates the total number of target objects The set of products of and 1, represents the complex reflection coefficient corresponding to target object 1, represents the complex reflection coefficient corresponding to the target object 2, Indicates the target object The corresponding complex reflection coefficient, express The transpose of .

[0044] Furthermore, after determining the vectorized snapshot signal, the number of snapshots of the carrier frequency-controlled array radar is obtained; when the number of snapshots is less than or equal to a preset threshold, matrix reconstruction is performed according to the vectorized snapshot signal to obtain a reconstructed signal covariance matrix.

[0045] Specifically, after determining the vectorized snapshot signal, when there is only the number of snapshots, the number of snapshots of the carrier frequency controlled array radar is obtained. When it is equal to 1, the signal covariance matrix ,in, express The conjugate transpose of express When the number of snapshots is less than or equal to a preset threshold, matrix reconstruction is performed according to the vectorized snapshot signal to obtain a reconstructed signal covariance matrix.

[0046] In a specific embodiment, matrix reconstruction is performed according to the vectorized snapshot signal to obtain a reconstructed signal covariance matrix, including: determining the receiving distance frequency according to the carrier offset, the number of carriers and the target distance; determining the receiving angle frequency according to the number of array elements, the array element spacing and the carrier signal receiving offset angle; determining the received signal vector according to the receiving distance frequency, the receiving angle frequency and the vectorized snapshot signal; determining the received signal according to the received signal vector; and performing matrix reconstruction on the received signal to obtain a reconstructed signal covariance matrix.

[0047] Specifically, when the number of snapshots is less than or equal to a preset threshold, in the process of matrix reconstruction according to the vectorized snapshot signal, first, the receiving distance frequency is determined according to the carrier offset, the number of carriers and the target distance. ,in, Indicates the number of a certain carrier, Indicates the target distance, represents the speed of light, represents n carriers, Indicates carrier offset. The receiving angle frequency is determined based on the number of array elements, the array element spacing, and the carrier signal receiving offset angle. , Indicates the number of array elements. Indicates the carrier signal receiving offset angle, represents the carrier wavelength, express Then, when the snapshot data is 1, the initial covariance matrix is ​​determined according to the vectorized snapshot signal. The initial covariance matrix At this time, the initial covariance matrix is ​​not accurate for estimating the subsequent single snapshot target parameters, and the initial covariance matrix needs to be further reconstructed. First, the received signal vector is determined according to the determined receiving distance frequency and receiving angle frequency. The received signal vector can be expressed as a linear combination of K atoms in the atomic set. The received signal vector ,in, , , , Then, the received signal is determined according to the received signal vector; the received signal is matrix reconstructed to obtain the reconstructed signal covariance matrix.

[0048] In a specific implementation, matrix reconstruction is performed on the received signal to obtain a reconstructed signal covariance matrix, including: matrix reconstruction is performed on the received signal to obtain an atomic norm; and format conversion is performed on the atomic norm to obtain a reconstructed signal covariance matrix.

[0049] Specifically, the received signal is determined according to the received signal vector, and the received signal is reconstructed into a matrix to obtain the atomic norm. It can be expressed as formula (1). In formula (1), Indicates the number of elements in the atomic set, i describes the i-th element in the atomic set, represents the complex reflection coefficient corresponding to the i element, express The complex reflection coefficient corresponding to each element.

[0050] (1) In this step, the received signal can be obtained by solving the minimization problem in formula (2).

[0051] (2) In formula (2), represents the norm of 2, represents the phase velocity measure. Formula (2) is equivalent to solving the following formula (3).

[0052] (3) In formula (3), represents a variable to be optimized. represents a complex matrix, express A collection of express The parameter form is a complex matrix Constructed double Toeplitz (long diagonal) matrix. Among them, The construction of is shown in formula (4).

[0053] (4) In formula (4), for any The construction of is shown in formula (5).

[0054] (5) Furthermore, in solving formula (3) If the problem is still difficult, we can convexify formula (1) to obtain formula (6).

[0055] (6) Then, for formula (6), the atomic norm minimization problem is transformed into a semi-positive definite programming problem, minimizing It is equivalent to the semi-positive definite programming problem in formula (7).

[0056] (7) In formula (7), represents the trace of the matrix, Represents the reconstructed signal covariance matrix.

[0057] Step 104: perform parameter estimation based on the reconstructed signal covariance matrix and the alternating direction multiplier method to obtain single-snapshot target parameters of the carrier frequency-controlled array radar for the target object.

[0058] Specifically, after determining the reconstructed signal covariance matrix, the alternating direction method of multipliers (ADMM) is used to perform parameter estimation according to the reconstructed signal covariance matrix and the alternating direction method of multipliers to obtain the single snapshot target parameters of the carrier frequency controlled array radar for the target object.

[0059] In a specific implementation, parameter estimation is performed based on a reconstructed signal covariance matrix and an alternating direction multiplier method to obtain single-snapshot target parameters of a carrier frequency-controlled array radar for a target object, including: constructing an augmented Lagrangian function based on the reconstructed signal covariance matrix; updating the augmented Lagrangian function based on the alternating direction multiplier method to obtain matrix parameters; determining a double matrix based on the matrix parameters and the reconstructed signal covariance matrix; performing eigenvalue decomposition on the double matrix to obtain characteristic parameters; and determining the single-snapshot target parameters of the carrier frequency-controlled array radar for the target object based on the characteristic parameters.

[0060] Specifically, the alternating direction multiplier method is used to improve the computational efficiency. After the alternating direction multiplier method is introduced, formula (7) can be transformed into formula (8).

[0061] (8) In formula (8), is a regularization parameter, and then the augmented Lagrangian function is constructed by formula (8). The augmented Lagrangian function is shown in formula (9).

[0062] (9) in, is the Lagrange multiplier, represents the matrix norm of the matrix. The matrix norm can be, for example, the Frobenious norm. is a penalty parameter.

[0063] Furthermore, the augmented Lagrangian function is updated according to the alternating direction multiplier method to obtain the matrix parameters. That is, through the ADMM method, the update of formula (9) is divided into three steps to obtain the matrix parameters, which are formula (10), formula (11) and formula (12).

[0064] (10) (11) (12) In formula (10), formula (11) and formula (12), the matrix parameters include and .

[0065] Specifically, the first step is for ( ), first we update the matrix and After dividing into blocks, we obtain formula (13) and formula (14).

[0066] (13) (14) Then, let the The partial derivative of is 0, which determines formula (15).

[0067] (15) The updated Formula (16), the updated Formula (17), the updated is formula (18).

[0068] (16) (17) (18) In formula (16), is a (2M-1)×(2N-1) matrix where the (M,N)th element is 1 and the rest are 0. is a mapping from a MN×MN dimensional matrix to a (2M-1)×(2N-1) dimensional matrix. For example, arrive , the mapping process is as follows.

[0069] Assumption Matrix , the elements of the matrix can be obtained by formula (19).

[0070] (19) Among them, m=-M+1, -M+2,…,M-1 and n=-N+1, -N+2,…,N-1. Returns the (mr, mc)th N×N submatrix of the matrix, where mr = 1, 2, …, M and mc = 1, 2, …, M. Represents the return of the trace of the nth subdiagonal of the input matrix.

[0071] The second step is for , transforming formula (11) into formula (20).

[0072] (20) In order to simplify the calculation, the matrix formula (21) is defined.

[0073] (twenty one) make , g=1,2,…,MN+1. When considering , is solved, and the solution process is shown in formula (22).

[0074] (twenty two) In formula (22), This means that all negative eigenvalues ​​are set to 0.

[0075] The third step is for Update, through formula (12) and formula (14), we get formula (23).

[0076] (twenty three) After the parameters are updated and the updated matrix parameters are obtained, the signal covariance matrix is ​​reconstructed and reconstructed according to the updated matrix parameters. The parameters of the reconstructed signal covariance matrix are updated to obtain an updated double matrix Then, the updated binary matrix is ​​classified by the Multiple Signal Classification (MUSIC) algorithm. Perform eigenvalue decomposition, and the decomposition process is shown in formula (24).

[0077] (twenty four) In formula (24), represents the matrix consisting of all eigenvectors, express The conjugate transpose of . represents a matrix whose diagonal elements consist of eigenvalues. represents the signal subspace, express The conjugate transpose of represents the noise subspace, express The conjugate transpose of . and denote the diagonal matrix composed of large eigenvalues ​​and small eigenvalues ​​respectively. Therefore, the obtained characteristic parameters include the noise subspace , Finally, the single-snap target parameters of the carrier frequency-controlled array radar for the target object are determined according to the characteristic parameters. .

[0078] The advantage of this setting is that the multi-carrier frequency-controlled array radar estimates the distance and angle parameters of multiple targets under a single snapshot, models the problem as an atomic norm minimization problem and solves it, and uses the ADMM algorithm to solve the atomic norm minimization problem. Compared with the traditional MUSIC algorithm, the estimation accuracy is greatly improved, and compared with the atomic norm minimization-convex optimization (AtomicNorm Minimization-Convex Optimization, ANM-CVX) algorithm, the computational complexity of the problem is reduced. It can quickly solve the problem while ensuring high-precision estimation of distance and angle parameters under multiple targets, which has strong practical application significance.

[0079] Exemplarily, the present invention estimates the single snapshot target parameters, i.e., distance and angle parameters, of a multi-carrier frequency-controlled array radar for multiple targets under a single snapshot, models the problem as an atomic norm minimization problem and solves it, which greatly reduces the demand for the number of snapshots compared to traditional algorithms. Specifically, the ADMM algorithm is used to solve the atomic norm minimization problem modeled, which greatly reduces the computational complexity compared to the calculation method using the convex optimization CVX method. The computational complexity of the ANM-CVX algorithm using the CVX method is , while the computational complexity of the ANM-ADMM algorithm using the ADMM method in the present invention mainly comes from the eigenvalue decomposition and is ,in represents the number of iterations. Compared with the ANM-ADMM algorithm, the computational complexity is significantly reduced, especially in the case of large-scale arrays. In fact, the average running time of the two algorithms in the same environment is 8.20 seconds and 1.69 seconds respectively. The simulation assumes that the number of array elements M is 12, the number of carriers N is 12, the carrier frequency center is 3 Gigahertz (GHz), the frequency offset is 4 Kilohertz (KHz), the array element spacing d is 0.05m, the regularization parameter is 37, the penalty parameter is 0.03, and the four targets are located at (20 km, 20 degrees), (14 km, 40 degrees), (30 km, 50 degrees), and (5 km, 60 degrees). The 2D-MUSIC algorithm, ANM-CVX algorithm, and ANM-ADMM algorithm are used to estimate the target parameters, and 100 Monte Carlo experiments are performed. Figure 3is a schematic diagram of single-snapshot target parameters provided by the present invention, Figure 3 (a) shows the single snapshot target parameters obtained by using the 2D-MUSIC algorithm to estimate the target parameters; Figure 3 (b) in FIG. 1 is a schematic diagram of a single-shot target parameter obtained by using the ANM-ADMM algorithm to estimate the target parameter in the present invention. Figure 3 As shown, by adopting the ANM-ADMM algorithm in the present invention to estimate the target parameters, the single snapshot target parameters are obtained more accurately.

[0080] The present invention provides a method for estimating target parameters of a radar, which obtains the array element spacing and carrier information of a carrier frequency-controlled array radar; wherein the array element spacing includes the distance between adjacent array elements arranged on the carrier frequency-controlled array radar, and the carrier information includes carrier offset, carrier number and carrier signal receiving offset angle; a snapshot signal of a target object is determined according to the array element spacing, carrier offset, carrier number and carrier signal receiving offset angle; matrix reconstruction is performed according to the snapshot signal to obtain a reconstructed signal covariance matrix; parameter estimation is performed according to the reconstructed signal covariance matrix and an alternating direction multiplier method to obtain a single snapshot target parameter of the carrier frequency-controlled array radar for the target object. The technical solution of the present invention is used to solve the defects of high computational complexity and long estimated operation time caused by solving semi-positive definite programming problems by interior point method in the prior art, and realizes determining the snapshot signal of the target object based on the carrier frequency controlled array radar in a single snapshot, and performing matrix reconstruction based on the snapshot signal to obtain the reconstructed signal covariance matrix, and then performing parameter estimation based on the reconstructed signal covariance matrix and the alternating direction multiplier method to obtain the single snapshot target parameters of the carrier frequency controlled array radar for the target object, and using the alternating direction multiplier to solve the single snapshot target parameters, thereby reducing the complexity of the problem and improving the accuracy of the single snapshot target parameters.

[0081] The target parameter estimation device of the radar provided by the present invention is described below. The target parameter estimation device of the radar described below and the target parameter estimation method of the radar described above can be referred to each other.

[0082] Figure 4 is a schematic diagram of the structure of the target parameter estimation device of the radar provided by the present invention, referring to Figure 4 As shown, the target parameter estimation device 400 of the radar includes: an information acquisition module 401, a signal determination module 402, a matrix reconstruction module 403 and a parameter estimation module 404.

[0083] The information acquisition module 401 is used to obtain the array element spacing and carrier information of the carrier frequency-controlled array radar; wherein the array element spacing includes the distance between adjacent array elements set on the carrier frequency-controlled array radar, and the carrier information includes the carrier offset, the number of carriers and the carrier signal receiving offset angle.

[0084] The signal determination module 402 is used to determine the snapshot signal of the target object according to the array element spacing, the carrier offset, the number of carriers and the carrier signal reception offset angle.

[0085] The matrix reconstruction module 403 is used to perform matrix reconstruction according to the snapshot signal to obtain a reconstructed signal covariance matrix.

[0086] The parameter estimation module 404 is used to perform parameter estimation based on the reconstructed signal covariance matrix and the alternating direction multiplier method to obtain the single snapshot target parameters of the carrier frequency controlled array radar for the target object.

[0087] In an exemplary embodiment, the signal determination module 402 is specifically used to: obtain the target distance of the target object from the carrier frequency-controlled array radar; determine the distance element parameter according to the target distance, carrier offset, speed of light and number of carriers; obtain the number of array elements of the carrier frequency-controlled array radar; determine the angle element parameter according to the number of array elements, array element spacing, carrier signal reception offset angle and carrier wavelength; determine the snapshot signal according to the distance element parameter, angle element parameter and Gaussian noise matrix.

[0088] In an exemplary embodiment, the matrix reconstruction module 403 is specifically used to: convert the format of the snapshot signal to obtain a vectorized snapshot signal; obtain the number of snapshots of the carrier frequency-controlled array radar; and when the number of snapshots is less than or equal to a preset threshold, perform matrix reconstruction according to the vectorized snapshot signal to obtain a reconstructed signal covariance matrix.

[0089] In an exemplary embodiment, the matrix reconstruction module 403 performs matrix reconstruction according to the vectorized snapshot signal to obtain a reconstructed signal covariance matrix, which is specifically used to: determine the receiving distance frequency according to the carrier offset, the number of carriers and the target distance; determine the receiving angle frequency according to the number of array elements, the array element spacing and the carrier signal receiving offset angle; determine the received signal vector according to the receiving distance frequency, the receiving angle frequency and the vectorized snapshot signal; determine the received signal according to the received signal vector; and perform matrix reconstruction on the received signal to obtain a reconstructed signal covariance matrix.

[0090] In an exemplary embodiment, the matrix reconstruction module 403 performs matrix reconstruction on the received signal to obtain a reconstructed signal covariance matrix, and is specifically used to: perform matrix reconstruction on the received signal to obtain an atomic norm; and perform format conversion on the atomic norm to obtain a reconstructed signal covariance matrix.

[0091] In an exemplary embodiment, the parameter estimation module 404 is specifically used to: construct an augmented Lagrangian function according to the reconstructed signal covariance matrix; update the augmented Lagrangian function according to the alternating direction multiplier method to obtain matrix parameters; determine a double matrix according to the matrix parameters and the reconstructed signal covariance matrix; perform eigenvalue decomposition on the double matrix to obtain characteristic parameters; and determine a single snapshot target parameter of the carrier frequency-controlled array radar for the target object according to the characteristic parameters.

[0092] The device of this embodiment can be used to execute the method of any embodiment in the radar target parameter estimation method side embodiment. Its specific implementation process and technical effects are similar to those in the radar target parameter estimation method side embodiment. For details, please refer to the detailed description in the radar target parameter estimation method side embodiment, which will not be repeated here.

[0093] Figure 5 is a schematic diagram of the structure of the electronic device provided by the present invention, such as Figure 5 As shown, the electronic device may include: a processor 510, a communication interface 520, a memory 530 and a communication bus 540, wherein the processor 510, the communication interface 520 and the memory 530 communicate with each other through the communication bus 540. The processor 510 may call the logic instructions in the memory 530 to execute the target parameter estimation method of the radar, which includes: obtaining the array element spacing and carrier information of the carrier frequency controlled array radar; wherein the array element spacing includes the distance between adjacent array elements set on the carrier frequency controlled array radar, and the carrier information includes the carrier offset, the number of carriers and the carrier signal receiving offset angle; determining the snapshot signal of the target object according to the array element spacing, the carrier offset, the number of carriers and the carrier signal receiving offset angle; performing matrix reconstruction according to the snapshot signal to obtain the reconstructed signal covariance matrix; performing parameter estimation according to the reconstructed signal covariance matrix and the alternating direction multiplier method to obtain the single snapshot target parameter of the carrier frequency controlled array radar for the target object.

[0094] In addition, the logic instructions in the above-mentioned memory 530 can be implemented in the form of a software functional unit and can be stored in a computer-readable storage medium when it is sold or used as an independent product. Based on such an understanding, the technical solution of the present invention, in essence, or the part that contributes to the prior art or the part of the technical solution, can be embodied in the form of a software product, and the computer software product is stored in a storage medium, including a number of instructions for a computer device (which can be a personal computer, a server, or a network device, etc.) to perform all or part of the steps of the methods of each embodiment of the present invention. The aforementioned storage medium includes: U disk, mobile hard disk, read-only memory (ROM, Read-Only Memory), random access memory (RAM, Random Access Memory), disk or optical disk, etc. Various media that can store program codes.

[0095] On the other hand, the present invention also provides a computer program product, which includes a computer program. The computer program can be stored on a non-transitory computer-readable storage medium. When the computer program is executed by a processor, the computer can execute the radar target parameter estimation method provided by the above methods, which includes: obtaining the array element spacing and carrier information of the carrier frequency-controlled array radar; wherein the array element spacing includes the distance between adjacent array elements set on the carrier frequency-controlled array radar, and the carrier information includes carrier offset, carrier number and carrier signal receiving offset angle; determining the snapshot signal of the target object according to the array element spacing, carrier offset, carrier number and carrier signal receiving offset angle; performing matrix reconstruction according to the snapshot signal to obtain the reconstructed signal covariance matrix; performing parameter estimation according to the reconstructed signal covariance matrix and the alternating direction multiplier method to obtain the single snapshot target parameter of the carrier frequency-controlled array radar for the target object.

[0096] On the other hand, the present invention also provides a non-transitory computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, is implemented to execute the target parameter estimation method of the radar provided by the above-mentioned methods, the method comprising: obtaining the array element spacing and carrier information of the carrier frequency-controlled array radar; wherein the array element spacing includes the distance between adjacent array elements arranged on the carrier frequency-controlled array radar, and the carrier information includes the carrier offset, the number of carriers and the carrier signal receiving offset angle; determining the snapshot signal of the target object according to the array element spacing, the carrier offset, the number of carriers and the carrier signal receiving offset angle; performing matrix reconstruction according to the snapshot signal to obtain the reconstructed signal covariance matrix; performing parameter estimation according to the reconstructed signal covariance matrix and the alternating direction multiplier method to obtain the single snapshot target parameters of the carrier frequency-controlled array radar for the target object.

[0097] The device embodiments described above are merely illustrative, wherein the units described as separate components may or may not be physically separated, and the components displayed as units may or may not be physical units, that is, they may be located in one place, or they may be distributed on multiple network units. Some or all of the modules may be selected according to actual needs to achieve the purpose of the scheme of this embodiment. Ordinary technicians in this field can understand and implement it without paying creative labor.

[0098] Through the description of the above implementation methods, those skilled in the art can clearly understand that each implementation method can be implemented by means of software plus a necessary general hardware platform, and of course, can also be implemented by hardware. Based on this understanding, the above technical solution is essentially or the part that contributes to the prior art can be embodied in the form of a software product, and the computer software product can be stored in a computer-readable storage medium, such as ROM / RAM, a disk, an optical disk, etc., including a number of instructions for a computer device (which can be a personal computer, a server, or a network device, etc.) to execute the methods described in each embodiment or some parts of the embodiments.

[0099] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit it. Although the present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the aforementioned embodiments, or make equivalent replacements for some of the technical features therein. 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 radar target parameter estimation method, characterized in that: include: Acquire the array element spacing and carrier information of the carrier frequency-controlled array radar; wherein the array element spacing includes the distance between adjacent array elements set on the carrier frequency-controlled array radar, and the carrier information includes carrier offset, carrier number and carrier signal receiving offset angle; Determine a snapshot signal of a target object according to the array element spacing, the carrier offset, the number of carriers, and the carrier signal reception offset angle; Perform matrix reconstruction according to the snapshot signal to obtain a reconstructed signal covariance matrix; Parameter estimation is performed according to the reconstructed signal covariance matrix and the alternating direction multiplier method to obtain single-snapshot target parameters of the target object by the carrier frequency-controlled array radar.

2. The target parameter estimation method of radar according to claim 1, characterized in that: The determining the snapshot signal of the target object according to the array element spacing, the carrier offset, the number of carriers and the carrier signal reception offset angle includes: Acquire the target distance between the target object and the carrier frequency-controlled array radar; Determine a distance element parameter according to the target distance, the carrier offset, the speed of light, and the number of carriers; Obtaining the number of array elements of the carrier frequency-controlled array radar; Determine an angle element parameter according to the number of array elements, the array element spacing, the carrier signal reception offset angle and the carrier wavelength; The snapshot signal is determined according to the distance element parameter, the angle element parameter and a Gaussian noise matrix.

3. The target parameter estimation method of radar according to claim 2, characterized in that: The performing matrix reconstruction according to the snapshot signal to obtain a reconstructed signal covariance matrix includes: Performing format conversion on the snapshot signal to obtain a vectorized snapshot signal; Obtaining the number of snapshots of the carrier frequency-controlled array radar; When the number of snapshots is less than or equal to a preset threshold, matrix reconstruction is performed according to the vectorized snapshot signal to obtain the reconstructed signal covariance matrix.

4. The target parameter estimation method of radar according to claim 3, characterized in that: The performing matrix reconstruction according to the vectorized snapshot signal to obtain the reconstructed signal covariance matrix includes: Determine a receiving distance frequency according to the carrier offset, the number of carriers and the target distance; Determine a receiving angle frequency according to the number of array elements, the array element spacing and the carrier signal receiving offset angle; Determine a received signal vector according to the received distance frequency, the received angle frequency and the vectorized snapshot signal; Determine a received signal according to the received signal vector; Perform matrix reconstruction on the received signal to obtain the reconstructed signal covariance matrix.

5. The target parameter estimation method of radar according to claim 4, characterized in that: The performing matrix reconstruction on the received signal to obtain the reconstructed signal covariance matrix includes: Performing matrix reconstruction on the received signal to obtain an atomic norm; The atomic norm is formatted to obtain the reconstructed signal covariance matrix.

6. The target parameter estimation method of radar according to claim 1, characterized in that: The step of performing parameter estimation according to the reconstructed signal covariance matrix and the alternating direction multiplier method to obtain a single snapshot target parameter of the target object by the carrier frequency controlled array radar includes: Constructing an augmented Lagrangian function according to the reconstructed signal covariance matrix; The augmented Lagrangian function is updated according to the alternating direction multiplier method to obtain matrix parameters; Determining a dual matrix according to the matrix parameters and the reconstructed signal covariance matrix; Performing eigenvalue decomposition on the binary matrix to obtain eigenvalue parameters; The single snapshot target parameter of the carrier frequency controlled array radar for the target object is determined according to the characteristic parameter.

7. A target parameter estimation device for a radar, characterized in that: include: An information acquisition module, used to acquire the array element spacing and carrier information of the carrier frequency-controlled array radar; wherein the array element spacing includes the distance between adjacent array elements set on the carrier frequency-controlled array radar, and the carrier information includes carrier offset, carrier number and carrier signal receiving offset angle; A signal determination module, configured to determine a snapshot signal of a target object according to the array element spacing, the carrier offset, the number of carriers, and the carrier signal reception offset angle; A matrix reconstruction module, used for performing matrix reconstruction according to the snapshot signal to obtain a reconstructed signal covariance matrix; The parameter estimation module is used to perform parameter estimation based on the reconstructed signal covariance matrix and the alternating direction multiplier method to obtain the single-snapshot target parameters of the carrier frequency-controlled array radar for the target object.

8. An electronic device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein: When the processor executes the computer program, the target parameter estimation method of the radar according to any one of claims 1 to 6 is implemented.

9. A non-transitory computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the target parameter estimation method of the radar according to any one of claims 1 to 6 is implemented.

10. A computer program product, comprising a computer program, characterized in that When the computer program is executed by a processor, the target parameter estimation method of the radar according to any one of claims 1 to 6 is implemented.

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