CN115494471A - Method and system for estimating polarization direction of arrival of high-frequency ground wave radar and application - Google Patents

Abstract

The invention belongs to the technical field of high-frequency ground wave radar signal processing, and discloses a method and a system for estimating the polarization direction of arrival of a high-frequency ground wave radar and application of the method and the system. The method comprises the following steps: the method comprises the steps of constructing a polarized space-time frequency distribution matrix based on a cross term to replace a data covariance matrix in a super-resolution algorithm by utilizing the characteristics that the time-frequency cross term of strong and weak signals of the high-frequency ground wave radar contains weak target information and is not easy to submerge in time-frequency noise, carrying out interactive processing on obtained related information, and carrying out polarized direction of arrival estimation on the weak target signals under the background of non-stationary strong signal interference. The estimation success rate of the non-stationary weak signal direction of arrival in the prior art is low and the error is large, the algorithm provided by the invention improves the success rate of low signal-to-noise ratio by about 40% by using a time-frequency analysis cross term, and reduces the estimation error by about 1 degree.

Description

Method, system and application for estimating direction of arrival of polarized wave of high-frequency ground wave radar

technical field

The invention belongs to the technical field of high-frequency ground-wave radar signal processing, and in particular relates to a method, system and application for estimating the direction of arrival of polarized waves of high-frequency ground-wave radar.

Background technique

The estimation performance of polarization direction of arrival of high-frequency ground wave radar is seriously affected by strong signals, and weak target echoes are submerged in clutter, making it difficult to be found. Then how to find the weak target signal in the strong clutter background is the key to improve the performance of high frequency ground wave radar polarized direction of arrival estimation. What are the advantages of HF ground wave radar polarization direction of arrival estimation based on time-frequency cross term? How to extract the time-frequency cross term and how to use the cross term to construct the polarization space-time-frequency distribution matrix for weak target signal DOA estimation? This is a challenging invention subject at home and abroad, and it is also a scientific problem that the present invention mainly expects to solve.

The echo of high-frequency ground wave radar is affected by many factors such as radio frequency interference, ionospheric interference, and sea clutter interference, and is a very complex non-stationary signal. Existing research on direction-of-arrival estimation for high-frequency ground-wave radar is mainly based on the ratio-amplitude direction-finding method of digital beamforming, and the estimation of polarization direction-of-arrival for weak non-stationary signals in the presence of non-stationary strong interference signals still needs further research .

Through the above analysis, the problems and defects in the prior art are:

(1) In the background of non-stationary strong jamming signals, the polarization direction of arrival estimation of weak target signals for high-frequency ground wave radar is an unsolved and very concerned topic. The existing high-frequency ground wave radar direction-of-arrival estimation methods are often the traditional beamforming direction-finding method and the ratio-amplitude direction-finding method based on digital beamforming, which cannot accurately estimate the arrival of weak target signals submerged in the background of non-stationary strong interference signals. direction.

(2) In the estimation of polarization direction of arrival in the prior art, the estimation error is large, so that the practical accuracy of related instruments cannot meet the demand.

Contents of the invention

In order to overcome the problems existing in the related technologies, the disclosed embodiments of the present invention provide a method, system and application for estimating the direction of arrival of polarized waves of high-frequency ground wave radar. Specifically, it relates to a dual-algorithm polarization direction-of-arrival estimation method based on time-frequency cross terms.

The technical solution is as follows: a method for estimating the direction of arrival of polarized waves of high-frequency ground-wave radar, characterized in that, the method for estimating the direction of arrival of polarized waves of high-frequency ground-wave radar utilizes the time-frequency of strong and weak signals of high-frequency ground-wave radar The cross item contains weak target information and is not easy to be submerged in time-frequency noise. A polarization space-time-frequency distribution matrix based on the cross item is constructed to replace the data covariance matrix in the super-resolution algorithm, and the obtained relevant information is interactively processed. And carry out the polarization direction of arrival estimation of weak target signal under the non-stationary strong signal interference background; Specifically include the following steps:

S1, establishing a dual-polarization data vector model;

S2, calculating the polarization space-time-frequency distribution and selecting cross-term time-frequency points;

S3. Construct the polarization space-time-frequency distribution matrix, and use the polarization time-frequency ESPRIT (Polarized Time-Frequency ESPRIT, PTF -ESPRIT) finely estimates the direction of arrival.

In one embodiment, in step S1, the bipolar data vector model is established as:

为对角化矩阵，

为信号极化特征矢量，Among them, x[t] is a dual-polarization data vector, x ^[v] [t] and x ^[h] [t] are vertical component and horizontal component data vectors respectively, A ^[v] (Φ) and A ^[h] (Φ) are vertical component and horizontal component steering matrix respectively, s ^[v] (t) and s ^[h] (t) are vertical signal component and horizontal signal component respectively, n ^[v] (t) and n ^[h] (t) are vertical component and horizontal component additive white noise respectively,

is a diagonalized matrix,

is the signal polarization eigenvector,

q ^[v] = [cos(γ ₁ ),..., cos(γ _N )] ^T , Q ^[v] = diag(q ^[v] ) (2)

Among them, γ is the polarization auxiliary angle, η is the polarization phase difference, correspondingly,

表示第n个信号空间极化联合特征；对于第n个信号，扩展的空间极化联合特征矢量为：Equation (4) is an extended mixing matrix, where φ is the signal incident angle,

Represents the spatial polarization joint feature of the nth signal; for the nth signal, the extended spatial polarization joint feature vector is:

In one embodiment, in step S2, calculating the polarization space-time domain distribution includes: combining the polarization feature, space feature and time-frequency feature of the received signal; The distribution matrix form is:

D _x (t, f) is called the spatially polarized time-frequency distribution (Spatially Polarized Time-Frequency Distribution, SPTFD) matrix, where w is the Gaussian kernel function; ignoring the influence of noise, the spatially polarized time-frequency distribution matrix and the signal time The frequency distribution matrix is related by the following formula:

D _xx (t,f)＝B(Φ)QD _s (t,f)Q ^H B ^H (Φ) (7)

In one embodiment, in step S2, selecting the cross-term time-frequency points includes:

In the SPTFD framework, the time-frequency characteristics of the signal do not overlap; assuming that the signal is composed of _two chirp signals _s1 and s2, the time-frequency distribution matrix of the signal is:

和

为信号自时频分布，

和

为信号交叉时频分布；in,

with

is the self-time-frequency distribution of the signal,

with

is the signal cross time-frequency distribution;

The chirp signal includes the following time-frequency point types:

The first time-frequency point is only related to the signal self-term, and the signal time-frequency distribution matrix has a first-order diagonal mathematical structure;

The second time-frequency point is only related to the signal cross term, and the signal time-frequency distribution matrix is a non-diagonal matrix; their diagonal elements are equal to 0;

The third time-frequency point is related to the self-term and cross-term of the signal, and the signal time-frequency distribution matrix has no obvious algebra-specific structure;

The fourth time-frequency point has nothing to do with the signal self-term and cross-term;

In the polarized DOA estimation of the weak non-stationary signal with strong and weak non-stationary signals by using the spatial polarization time-frequency distribution cross term, the unitary transformation is carried out by using the trace invariance in the second time-frequency point matrix to judge the signal cross term Whether it exists, the specific judgment conditions are:

Among them, {·} means to find the trace of the matrix, ||·|| means to find the norm, and ε means to define the positive and small values.

In one embodiment, in step S3, constructing the polarization space-time-frequency distribution matrix includes:

Construct the direction of arrival of the polarization array vector by combining the SPTFD matrix in the space domain, time-frequency domain and polarization domain;

由于||a^[i](φ)||²＝M，其中M为阵列阵元数，F^H(φ)F(φ)为单位矩阵；从空间极化联合域进行搜索时，定义空间极化矢量为：Spatial property matrix

Since ||a ^[i] (φ)|| ² ＝M, where M is the number of array elements, F ^H (φ)F(φ) is the unit matrix; when searching from the spatial polarization joint domain, define the spatial polarity Convert the vector to:

Among them, the vector c=[c ₁ c ₂ ] ^T is an unknown polarization coefficient unit norm vector; in formula (10), ||F(φ)c||=[c ^H F ^H (φ)F( φ)c] ^1/2 =(c ^H c) ^1/2 =1.

In one embodiment, in step S3, the Polarized Time-Frequency MUSIC (Polarized Time-FrequencyMUSIC, PTF-MUSIC) spatial spectrum is provided by the following function:

Wherein, [] ^-1 is the reciprocal operation, and U _n represents the noise subspace of the SPTFD matrix constructed by the time-frequency points of the intersection term of formula (6);

的最小特征值得到整体的最小特征值；PTF-MUSIC的空间谱为：In formula (11), by finding the matrix

The minimum eigenvalue of the overall minimum eigenvalue is obtained; the spatial spectrum of PTF-MUSIC is:

Among them, λ _min [ ] means to find the minimum eigenvalue; corresponding to each direction of arrival (DOA) of N signals, there are N highest points in the spatial spectrum; the DOA rough estimation result is obtained by PTF-MUSIC.

In one embodiment, in step S3, finely estimating the DOA by cross-term-based polarized time-frequency ESPRIT (PolarizedTime-Frequency ESPRIT, PTF-ESPRIT) includes the following steps: Obtain covariance matrices R ₁₁ and R by SPTFD _22. After the eigendecomposition, the respective signal subspaces are obtained respectively, which are set as E ₁ and E ₂ , and the whole antenna receiving array matrix D _x is decomposed to obtain a signal subspace, denoted by E _x ; decompose E _x into E ₁ and E 2 E ₂ ; E ₁ and E ₂ are both M×N-dimensional matrices, which are respectively composed of eigenvectors corresponding to the larger eigenvalues of R ₁₁ and R ₂₂ , and the two signal subspaces are connected by a non-singular transformation matrix Ψ up, there is:

E ₁ Ψ = E ₂ (13)

There is a unique nonsingular transformation matrix T such that:

E ₁ =A ₁ T (14)

E ₂ =A ₁ ΦT (15)

Substituting Equation (14) and Equation (15) into Equation (13), the matrix A is full rank, and we get:

TΨT ^-1 = Φ (16)

Among them, Ψ is a rotation operator, it is obtained that the eigenvalue of Ψ is equal to the diagonal element of Φ, and each column of matrix T is the eigenvector of matrix Ψ; after calculating Ψ first, calculate the value of each signal according to the following formula DOA value, namely θ;

On the basis of the rough estimation in formula (12), compare the results obtained in formula (17) with the rough estimation results, and when the difference is less than 5 degrees, choose the Polarized Time-Frequency ESPRIT (Polarized Time-Frequency ESPRIT, PTF -ESPRIT) fine estimate direction of arrival results.

Another object of the present invention is to provide a high frequency ground wave radar polarized wave direction of arrival estimation

The counting system includes:

A dual-polarization data vector model establishment module is used to establish a dual-polarization data vector model and to calculate the polarization space-time-frequency distribution matrix;

The polarization space-time-frequency distribution calculation and cross-term time-frequency point selection module is used to calculate the polarization space-time-frequency distribution and select cross-term time-frequency points;

The direction of arrival estimation module is used to construct the polarization space-time-frequency distribution matrix, which is roughly estimated by PTF-MUSIC and then finely estimated by PTF-ESPRIT.

Another object of the present invention is to provide a computer device, the computer device includes a memory and a processor, the memory stores a computer program, when the computer program is executed by the processor, the processor executes the The method for estimating the direction of arrival of polarized waves for high-frequency ground-wave radar.

Another object of the present invention is to provide a computer-readable storage medium, which stores a computer program. When the computer program is executed by a processor, the processor executes the high-frequency ground-wave radar polarization direction-of-arrival method. Estimation method.

In combination with all the above-mentioned technical solutions, the advantages and positive effects of the present invention are:

First, in view of the technical problems existing in the above-mentioned prior art and the difficulty of solving the problems, closely combine the technical solution to be protected in the present invention and the results and data in the research and development process, etc., to analyze in detail and profoundly how to solve the technical solution of the present invention Technical problems, some creative technical effects brought about after solving the problems. The specific description is as follows:

The present invention is based on high-frequency ground-wave radar polarized wave direction of arrival estimation and time-frequency analysis methods, that is, to establish a polarized space-time-frequency signal model, using strong and weak signal time-frequency cross items to contain weak target signal information and not easily submerged in time-frequency According to the characteristics of the noise, the polarization space-time-frequency distribution matrix based on the time-frequency cross term is constructed, so that the weak non-stationary signal direction of arrival can be estimated in the non-stationary strong signal interference. The invention provides a new method for estimating the polarization direction of arrival of weak target signals under the background of non-stationary strong signal interference of high-frequency ground wave radar.

Furthermore, when strong and weak signals exist at the same time, weak signals can be estimated through the present invention.

Second, regarding the technical solution as a whole or from the perspective of a product, the technical effects and advantages of the technical solution to be protected by the present invention are specifically described as follows:

The present invention utilizes the characteristic that the time-frequency cross term of strong and weak signals of high-frequency ground wave radar contains weak target information and is not easily submerged in time-frequency noise to realize the polarization direction of arrival estimation of weak target signals under the background of non-stationary strong signal interference. Advantages compared with technology are:

In the prior art, the success rate of DOA estimation for non-stationary weak signals is low and the error is relatively large. The algorithm proposed in the present invention uses the time-frequency analysis cross term to improve the success rate by about 40% when the signal-to-noise ratio is low, and reduces the estimation error by 1 degree. about;

Compared with the traditional polarized direction of arrival estimation algorithm, the algorithm proposed in the present invention not only uses the polarization information, but also combines the time-frequency domain information, and also utilizes the energy of strong signal interference, and then realizes the polarized wave arrival through the cross term. For direction estimation, the success rate at low signal-to-noise ratio has been improved by 20%, and the estimation error has been reduced by about 1 degree.

Description of drawings

The accompanying drawings, which are incorporated in and constitute a part of this specification, illustrate embodiments consistent with the disclosure and together with the description serve to explain the principles of the disclosure.

Fig. 1 is a flow chart of a method for estimating a direction of arrival of a polarized wave of a high-frequency ground wave radar provided by an embodiment of the present invention;

Fig. 2 is a flow chart of the method for estimating the direction of arrival of the polarized wave of the high-frequency ground wave radar provided by Embodiment 1 of the present invention;

Fig. 3 is a flow chart of the method for estimating the direction of arrival of the polarized wave of the high-frequency ground wave radar provided by Embodiment 2 of the present invention;

Fig. 4 is a schematic diagram of a high frequency ground wave radar polarized direction of arrival estimation system provided by an embodiment of the present invention;

FIG. 5 is a schematic diagram of a signal time spectrum provided by an embodiment of the present invention;

FIG. 6 is a cross-item diagram in the time-frequency spectrum provided by an embodiment of the present invention;

FIG. 7 is a cross-term-based polarization time-frequency space spectrogram provided by an embodiment of the present invention;

Fig. 8 is a comparison chart of the estimated success rate between the traditional algorithm provided by the embodiment of the present invention and the algorithm of the present invention;

Fig. 9 is a comparison diagram of the root mean square error between the traditional algorithm provided by the embodiment of the present invention and the algorithm of the present invention;

In the figure: 1. Dual-polarization data vector model building module; 2. Polarization space-time-frequency distribution calculation and cross-term time-frequency point selection module; 3. Direction of arrival estimation module.

detailed description

In order to make the above objects, features and advantages of the present invention more comprehensible, specific implementations of the present invention will be described in detail below in conjunction with the accompanying drawings. In the following description, numerous specific details are set forth in order to provide a thorough understanding of the present invention. However, the present invention can be implemented in many other ways different from those described here, and those skilled in the art can make similar improvements without departing from the connotation of the present invention, so the present invention is not limited by the specific implementation disclosed below.

1. Example of explanation:

As shown in Figure 1, the high-frequency ground-wave radar polarized direction-of-arrival estimation method provided by the embodiment of the present invention uses the high-frequency ground-wave radar strong and weak signal time-frequency cross term to contain weak target information and is not easily submerged in time-frequency noise Based on the characteristics of the cross-term, the polarization space-time-frequency distribution matrix based on the cross term is constructed to replace the data covariance matrix in the super-resolution algorithm (MUSIC and ESPRIT), and the relevant information obtained is interactively processed to realize the weak target under the background of non-stationary strong signal interference. Signal polarization direction of arrival estimation. details as follows:

S101, establishing a dual-polarization data vector model;

S102, calculating the polarization space-time-frequency distribution and selecting cross-term time-frequency points;

S103. Construct a polarization space-time-frequency distribution matrix, roughly estimate by PTF-MUSIC, and then finely estimate DOA by PTF-ESPRIT.

Example 1

As shown in Figure 2, the method for estimating the direction of arrival of the polarized wave of the high-frequency ground wave radar provided by the embodiment of the present invention includes the following steps:

S201, recording and saving the echo data of the high-frequency ground wave radar; performing distance processing on the echo signal;

S202, performing time-frequency analysis on the range gate time series of interest;

S203, extracting the time-frequency intersection item including the weak target signal through an algorithm; the algorithm is formula (9);

S204, constructing a polarization space-time-frequency distribution matrix;

S205. Apply the matrix to the MUSIC algorithm and the ESPRIT algorithm to obtain relevant information; obtain the non-stationary weak signal direction of arrival through information interaction.

Example 2

As shown in FIG. 3 , aiming at the problem of estimating the polarized direction of arrival of a weak target signal in a high-frequency ground-wave radar under a strong clutter background, an embodiment of the present invention provides a method for estimating the polarized direction-of-arrival of a high-frequency ground-wave radar. The core is how to use the characteristic that the time-frequency cross term of strong and weak signals of high-frequency ground wave radar contains weak target information and is not easy to be submerged in time-frequency noise, so as to construct a polarization space-time-frequency distribution matrix for DOA estimation. The basic process is as follows:

S301, establishing a dual-polarization data vector model, which puts the dual-polarization data in the same long vector data model, which facilitates storage and processing of polarization data, and maintains polarization orthogonality. At the same time, the model is also convenient for the subsequent calculation of the polarization space-time-frequency distribution matrix. The specific model is as follows:

为对角化矩阵，

为信号极化特征矢量，in,

is a diagonalized matrix,

is the signal polarization eigenvector,

q ^[v] = [cos(γ ₁ ),..., cos(γ _N )] ^T , Q ^[v] = diag(q ^[v] ) (2)

Correspondingly,

表示第n个信号空间极化联合特征。对于第n个信号，扩展的空间极化联合特征矢量为Equation (4) is the extended mixing matrix,

Denotes the nth signal spatial polarization joint feature. For the nth signal, the expanded spatial polarization joint eigenvector is

Obviously, the dual-polarization array can increase the spatial dimension of the vector.

S302. Calculate the polarization space-time domain distribution: combine the polarization feature, space feature and time-frequency feature of the received signal. The form of the space-time-frequency distribution matrix of the dual-polarization data vector x(t) is as follows:

D _x (t, f) is called a spatially polarized time-frequency distribution (Spatially Polarized Time-Frequency Distribution, SPTFD) matrix. When ignoring the influence of noise, the spatial polarization time-frequency distribution matrix and the signal time-frequency distribution matrix are related by the following formula:

D _xx (t,f)＝B(Φ)QD _s (t,f)Q ^H B ^H (Φ) (7)

S303. Select cross-term time-frequency points: Only when appropriate time-frequency points are considered in the SPTFD matrix can the advantages of the polarization DOA estimation method based on time-frequency cross terms be realized. The key of this method is how to choose the appropriate time-frequency point.

The invention analyzes the weak non-stationary signal DOA estimation problem based on the space-time polarization frequency distribution cross item under strong non-stationary signal interference. In the SPTFD framework, the time-frequency characteristics of signals should not overlap highly. The time-frequency distribution matrix of the signal is:

These two signals are chirp signals. Analyze the following four time-frequency point types. The first type of time-frequency point is only related to the signal self-term, and the signal time-frequency distribution matrix has a first-order diagonal mathematical structure. The second time-frequency point is only related to the signal cross term, and the signal time-frequency distribution matrix is a non-diagonal matrix. Their diagonal elements are approximately equal to 0. The third time-frequency point is related to the self-term and cross-term of the signal, and the signal time-frequency distribution matrix has no obvious algebraic specific structure. The fourth time-frequency point has nothing to do with the self-term and cross-term of the signal.

The diagonal and off-diagonal mathematical structures of the first and second time-frequency bins are often broken when signals are mixed. The first, second, and third time-frequency points are of great significance to DOA estimation. The fourth ones should be discarded as they serve no purpose in this case.

In the embodiment of the present invention, the polarization DOA estimation is performed on weak non-stationary signals with strong and weak non-stationary signals at the same time by using the spatial polarization time-frequency distribution cross term. Because in the second time-frequency point, there is a highly prominent first-order off-diagonal matrix algebraic structure. Use the trace invariance in the matrix to perform unitary transformation to judge whether the signal cross term exists. The specific judgment conditions are as follows:

Among them, {·} means to find the trace of the matrix, ||·|| means to find the norm, and ε means to define the positive and small values. When the signal is almost drowned in the noise, the SPTFDs of the average cross term further mitigate the noise effect.

S304, roughly estimate the direction of arrival (Direction of Arrival, DOA) by TF-MUSIC: In order to improve the spatial resolution of signals with good time-frequency characteristics, time-frequency multiple signal classification (Time-frequency Multiple Signal Classification, TF-MUSIC) is proposed .

In the embodiment of the present invention, MUSIC is applied to the polarized array, and the direction of arrival of the polarized array vector is mainly found by combining the SPTFD matrix in the spatial domain, the time-frequency domain and the polarized domain.

由于||a^[i](φ)||²＝M，F^H(φ)F(φ)为单位矩阵。从空间极化联合域进行搜索时，定义空间极化矢量为：Considering the spatial property matrix

Since ||a ^[i] (φ)|| ² =M, F ^H (φ)F(φ) is an identity matrix. When searching from the spatial polarization joint domain, the spatial polarization vector is defined as:

Wherein, the vector c=[c ₁ c ₂ ] ^T is an unknown polarization coefficient unit norm vector. In formula (10), ∥F(φ)c‖＝[c ^H F ^H (φ)F(φ)c] ^1/2 ＝(c ^H c) ^1/2 ＝1.

Polarized Time-Frequency MUSIC (Polarized Time-Frequency MUSIC, PTF-MUSIC) spatial spectrum is provided by the following functions:

Among them, U _n represents the noise subspace of the SPTFD matrix constructed by the cross-term time-frequency points of formula (6).

的最小特征值得到整体的最小特征值，该方法可以对矩阵进行简单的特征分解，从而避免在极化区域进行大量的运算。这样，可以将PTF-MUSIC的空间谱描述为：In the embodiment of the present invention, time-frequency points of cross items are selected. In formula (11), by finding the matrix

The minimum eigenvalue of the overall minimum eigenvalue is obtained. This method can perform a simple eigendecomposition of the matrix, thereby avoiding a large number of calculations in the polarized region. In this way, the spatial spectrum of PTF-MUSIC can be described as:

Among them, λ _min [·] means to solve the minimum eigenvalue. Corresponding to each direction of arrival (Direction of Arrival, DOA) of the N signals, there are N highest points in the spatial spectrum. That is, the DOA rough estimation result is obtained through PTF-MUSIC.

S305, finely estimate the direction of arrival (Direction of Arrival, DOA) by the Polarized Time-Frequency ESPRIT (Polarized Time-Frequency ESPRIT, PTF-ESPRIT) algorithm based on the cross term: obtain the covariance matrix R ₁₁ and R ₂₂ through SPTFD, the characteristic After decomposing, respective signal subspaces can be obtained, which are set as E ₁ and E ₂ , and the whole antenna receiving array matrix D _x can be decomposed to obtain a signal subspace, denoted by E _x . Since the structure of the antenna array remains unchanged, E _x can be decomposed into E ₁ and E ₂ . Both E ₁ and E ₂ are M×N dimensional matrices, they are composed of the eigenvectors corresponding to the larger eigenvalues of R ₁₁ and R ₂₂ respectively, because the two sub-arrays have the same structure, only the phase difference is different, so the two The signal subspaces can be connected by a non-singular transformation matrix Ψ, as follows:

E ₁ Ψ = E ₂ (13)

Thus there must be a unique non-singular transformation matrix T such that:

E ₁ =A ₁ T (14)

E ₂ =A ₁ ΦT (15)

Substituting formula (14) and formula (15) into formula (13), and assuming that the matrix A is full rank, we can get:

TΨT ^-1 = Φ (16)

Among them, Ψ is a rotation operator, it can be obtained that the eigenvalue of Ψ is equal to the diagonal elements of Φ, and each column of matrix T is the eigenvector of matrix Ψ. Therefore, as long as Ψ can be obtained first, the DOA value of each signal can be obtained according to the following formula.

On the basis of the rough estimate in formula (12), the result obtained in formula (17) is compared with the rough estimate result, and the PTF-ESPRIT result is selected when the difference between the two is within 5 degrees.

Example 3

As shown in Figure 4, the high frequency ground wave radar polarized wave direction of arrival estimation method provided by the embodiment of the present invention

Dual-polarization data vector model establishment module 1, used for establishing dual-polarization data vector model, and used for the calculation of polarization space-time-frequency distribution matrix;

The calculation of polarization space-time-frequency distribution and cross-term time-frequency point selection module 2 is used to calculate the polarization space-time-frequency distribution and select cross-term time-frequency points;

The direction of arrival estimation module 3 is used to construct the polarization space-time-frequency distribution matrix, which is roughly estimated by PTF-MUSIC and then finely estimated by PTF-ESPRIT.

In the above-mentioned embodiments, the descriptions of each embodiment have their own emphases, and for parts that are not detailed or recorded in a certain embodiment, refer to the relevant descriptions of other embodiments.

The information interaction and execution process between the above-mentioned devices/units are based on the same idea as the method embodiment of the present invention, and its specific functions and technical effects can be found in the method embodiment section, and will not be repeated here.

Those skilled in the art can clearly understand that for the convenience and brevity of description, only the division of the above-mentioned functional units and modules is used for illustration. In practical applications, the above-mentioned functions can be assigned to different functional units, Completion of modules means that the internal structure of the device is divided into different functional units or modules to complete all or part of the functions described above. Each functional unit and module in the embodiment may be integrated into one processing unit, or each unit may exist separately physically, or two or more units may be integrated into one unit, and the above-mentioned integrated units may adopt hardware It can also be implemented in the form of software functional units. In addition, the specific names of the functional units and modules are only for the convenience of distinguishing each other, and are not used to limit the protection scope of the present invention. For the specific working process of the units and modules in the above system, reference may be made to the corresponding process in the foregoing method embodiments, and details will not be repeated here.

2. Application examples:

Application example 1

An embodiment of the present invention provides a computer device, which includes: at least one processor, a memory, and a computer program stored in the memory and operable on the at least one processor, and the processor executes the The steps in any of the above method embodiments are implemented when the computer program is described.

Application example 2

An embodiment of the present invention also provides a computer-readable storage medium, where a computer program is stored in the computer-readable storage medium, and when the computer program is executed by a processor, the steps in the foregoing method embodiments can be implemented.

Application example 3

The embodiment of the present invention also provides an information data processing terminal, the information data processing terminal is used to provide a user input interface to implement the steps in the above-mentioned method embodiments when the information data processing terminal is implemented on an electronic device, the information data Processing terminals are not limited to mobile phones, computers, and switches.

Application example 4

An embodiment of the present invention also provides a server, which is configured to provide a user input interface to implement the steps in the foregoing method embodiments when executed on an electronic device.

Application example 5

An embodiment of the present invention provides a computer program product. When the computer program product is run on an electronic device, the electronic device can realize the steps in the foregoing method embodiments when executed.

If the integrated unit is realized in the form of a software function unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the present invention realizes all or part of the processes in the methods of the above-mentioned embodiments, which can be completed by instructing related hardware through computer programs. The computer program can be stored in a computer-readable storage medium. The computer program When executed by a processor, the steps in the above-mentioned various method embodiments can be realized. Wherein, the computer program includes computer program code, and the computer program code may be in the form of source code, object code, executable file or some intermediate form. The computer-readable medium may at least include: any entity or device capable of carrying computer program codes to a photographing device/terminal device, a recording medium, a computer memory, a read-only memory (Read-Only Memory, ROM), a random access memory ( RandomAccessMemory, RAM), electrical carrier signals, telecommunication signals, and software distribution media. Such as U disk, mobile hard disk, magnetic disk or optical disk, etc.

3. Evidence of the relevant effects of the embodiment:

Under the premise background of the application of the high-frequency ground wave radar polarized wave direction of arrival estimation method provided by the embodiment of the present invention, when the signal-to-noise ratio is high, the calculation accuracy of PTF-ESPRIT is high, and when the signal-to-noise ratio is low, PTF-MUSIC The subspace orthogonality of is easy to reflect. Therefore, firstly, PTF-MUSIC ensures that the approximate range of the weak signal angle is estimated, and then PTF-ESPRIT further fine-tunes the estimation. details as follows:

The simulation analysis conditions are as follows: the normalized frequency of strong interference is 0.2-0.4; the normalized frequency of weak signal is 0-0.2; the signal-to-noise ratio is -4dB, and the signal-to-interference ratio is -7dB. It can be seen from Figure 5 that the time-frequency self-items of weak signals are submerged in noise and cannot be directly extracted and used. Using this patented method to extract cross items, as shown in FIG. 6 . The polarization direction of arrival estimation based on the time-frequency point of the cross term is shown in Fig. 7. This figure shows the estimation results of a certain PTF-ESPRIT and PTF-MUSIC. To verify the stability of the algorithm, see Fig. 8 and 9. Figure 8 shows the comparison of the estimated success rate between the traditional algorithm and the algorithm of the present invention. The success rate is greatly improved when the SNR is low, and the success rate remains stable and high when the SNR is high. On the premise of ensuring the success rate, analyze the root mean square error of the algorithm, as shown in Figure 9, it ensures a stable root mean square error at low signal-to-noise ratio, and has a smaller root mean square error at high signal-to-noise ratio error.

From the above theoretical analysis and simulation analysis, it can be seen that this patent algorithm uses PTF-MUSIC to first estimate the approximate range of DOA of weak signals to ensure the success rate of estimation; The rough estimation result of , ensures the estimation accuracy on the basis of improving the success rate.

The above is only a preferred specific implementation of the present invention, but the protection scope of the present invention is not limited thereto. Any person familiar with the technical field is within the technical scope disclosed in the present invention Any modifications, equivalent replacements and improvements made within the spirit and principles shall fall within the protection scope of the present invention.

Claims (10)

1. A high frequency ground wave radar polarized wave direction of arrival estimation method is characterized in that the method utilizes the fact that the time-frequency cross term of the high frequency ground wave radar strong and weak signals contains weak target information and is difficult to be submerged in the time-frequency noise Features, constructing a polarization space-time-frequency distribution matrix based on cross-terms to replace the data covariance matrix in the super-resolution algorithm, interactively processing the obtained relevant information, and performing polarization detection of weak target signals under the background of non-stationary strong signal interference Direction estimation; specifically includes the following steps: S1, establishing a dual-polarization data vector model; S2, calculating the polarization space-time-frequency distribution and selecting cross-term time-frequency points; S3. Construct the polarization space-time-frequency distribution matrix, and use the polarization time-frequency MUSIC to roughly estimate the direction of arrival, and then use the polarization time-frequency ESPRIT based on the cross term to finely estimate the direction of arrival. 2. the high-frequency ground wave radar polarized wave direction of arrival estimation method according to claim 1 is characterized in that, in step S1, the dual-polarization data vector model is set up as:

Among them, x[t] is a dual-polarization data vector, x ^[v] [t] and x ^[h] [t] are vertical component and horizontal component data vectors respectively, A ^[v] (Φ) and A ^[h] (Φ) are vertical component and horizontal component steering matrix respectively, s ^[v] (t) and s ^[h] (t) are vertical signal component and horizontal signal component respectively, n ^[v] (t) and n ^[h] (t) are vertical component and horizontal component additive white noise respectively,

is a diagonalized matrix,

is the signal polarization eigenvector; q ^[v] = [cos(γ ₁ ),..., cos(γ _N )] ^T , Q ^[v] = diag(q ^[v] ) (2)

Among them, γ is the polarization auxiliary angle, η is the polarization phase difference, correspondingly,

Equation (4) is an extended mixing matrix, where φ is the signal incident angle,

Represents the spatial polarization joint feature of the nth signal. For the nth signal, the extended spatial polarization joint feature vector is:

3. The method for estimating the polarization direction of arrival of high-frequency ground wave radar according to claim 1, wherein in step S2, calculating the polarization space-time-frequency distribution comprises: combining the polarization characteristics and spatial characteristics of the received signal Combined with time-frequency features; the space-time-frequency distribution matrix form of the dual-polarization data vector x(t) is:

D _x (t, f) is called the spatial polarization time-frequency distribution matrix, where w is the Gaussian kernel function; ignoring the influence of noise, the spatial polarization time-frequency distribution matrix and the signal time-frequency distribution matrix are related by the following formula: D _xx (t,f)=B(Φ)QD _s (t,f)Q ^H B ^H (Φ) (7). 4. the high-frequency ground wave radar polarized wave direction of arrival estimation method according to claim 1, is characterized in that, in step S2, choosing cross-term time-frequency point comprises: In the SPTFD framework, the time-frequency characteristics of the signal do not overlap; assuming that the signal is composed of _two chirp signals _s1 and s2, the time-frequency distribution matrix of the signal is:

in,

with

is the self-time-frequency distribution of the signal,

with

is the signal cross time-frequency distribution; The chirp signal includes the following time-frequency point types: The first time-frequency point is only related to the signal self-term, and the signal time-frequency distribution matrix has a first-order diagonal mathematical structure; The second time-frequency point is only related to the signal cross term, and the signal time-frequency distribution matrix is a non-diagonal matrix; their diagonal elements are equal to 0; The third time-frequency point is related to the self-term and cross-term of the signal, and the signal time-frequency distribution matrix has no obvious algebra-specific structure; The fourth time-frequency point has nothing to do with the signal self-term and cross-term; In the polarized DOA estimation of the weak non-stationary signal with strong and weak non-stationary signals by using the spatial polarization time-frequency distribution cross term, the unitary transformation is carried out by using the trace invariance in the second time-frequency point matrix to judge the signal cross term Whether it exists, the specific judgment conditions are:

Among them, {·} means to find the trace of the matrix, ||·|| means to find the norm, and ε means to define the positive and small values. 5. the method for estimating the direction of arrival of polarized wave of high-frequency ground wave radar according to claim 1 is characterized in that, in step S3, constructing the polarization space-time-frequency distribution matrix comprises: Construct the direction of arrival of the polarization array vector by combining the SPTFD matrix in the space domain, time-frequency domain and polarization domain; Spatial property matrix

Since ||a ^[i] (φ)‖ ² = M, where M is the number of array elements, F ^H (φ)F(φ) is the identity matrix; when searching from the spatial polarization joint domain, define the spatial polarization The vector is:

Among them, the vector c=[c ₁ c ₂ ] ^T is an unknown polarization coefficient unit norm vector; in formula (10), |F(φ)c||=[c ^H F ^H (φ)F(φ )c] ^1/2 = (c ^H c) ^1/2 = 1. 6. the high-frequency ground wave radar polarized direction of arrival estimation method according to claim 1 is characterized in that, in step S3, the polarized time-frequency MUSIC spatial spectrum is provided by the following function:

Wherein, [] ^-1 is the reciprocal operation, and U _n represents the noise subspace of the SPTFD matrix constructed by the time-frequency points of the intersection term of formula (6); In formula (11), by finding the matrix

The minimum eigenvalue of the overall minimum eigenvalue is obtained; the spatial spectrum of PTF-MUSIC is:

Among them, λ _min [ ] means to find the minimum eigenvalue; corresponding to each direction of arrival (DOA) of N signals, there are N highest points in the spatial spectrum; the DOA rough estimation result is obtained by PTF-MUSIC. 7. the high frequency ground wave radar polarized direction of arrival estimation method according to claim 1, is characterized in that, in step S3, by the polarization time-frequency ESPRIT based on cross-term fine estimation direction of arrival comprises the following steps: The covariance matrices R ₁₁ and R ₂₂ are obtained through SPTFD, and the respective signal subspaces are obtained after eigendecomposition, which are set to E ₁ and E ₂ , and the entire antenna receiving array matrix D _x is decomposed to obtain a signal subspace, and E _x Decompose E _x into E ₁ and E ₂ ; both E ₁ and E ₂ are M×N-dimensional matrices, which are composed of eigenvectors corresponding to the larger eigenvalues of R ₁₁ and R ₂₂ respectively, and the two signals The subspaces are connected by a non-singular transformation matrix Ψ, which has: E ₁ Ψ = E ₂ (13) There is a unique nonsingular transformation matrix T such that: E ₁ =A ₁ T (14) E ₂ =A ₁ ΦT (15) Substituting Equation (14) and Equation (15) into Equation (13), the matrix A is full rank, and we get: TΨT ^-1 = Φ (16) Among them, Ψ is a rotation operator, it is obtained that the eigenvalue of Ψ is equal to the diagonal element of Φ, and each column of matrix T is the eigenvector of matrix Ψ; after calculating Ψ first, calculate the value of each signal according to the following formula DOA value, namely θ;

On the basis of the rough estimation in formula (12), compare the results obtained in formula (17) with the rough estimation results, and when the difference is less than 5 degrees, choose the Polarized Time-Frequency ESPRIT (Polarized Time-Frequency ESPRIT, PTF -ESPRIT) fine estimate direction of arrival results. 8. A system for realizing the method for estimating the direction of arrival of the polarized wave of high-frequency ground wave radar as claimed in any one of claims 1-7, wherein the system for estimating the direction of arrival of the polarized wave of the high-frequency ground wave radar comprises: A dual-polarization data vector model establishment module (1), used for establishing a dual-polarization data vector model, and for calculating the polarization space-time-frequency distribution matrix; The polarization space-time-frequency distribution calculation and cross-term time-frequency point selection module (2) is used to calculate the polarization space-time-frequency distribution and select cross-term time-frequency points; The direction of arrival estimation module (3) is used to construct the polarization space-time-frequency distribution matrix, which is roughly estimated by PTF-MUSIC and then finely estimated by PTF-ESPRIT. 9. A computer device, characterized in that, the computer device comprises a memory and a processor, the memory stores a computer program, and when the computer program is executed by the processor, the processor performs claim 1 - The method for estimating the direction of arrival of polarized waves of high-frequency ground wave radar described in any one of 7. 10. A computer-readable storage medium, storing a computer program, when the computer program is executed by a processor, the processor is made to perform the high-frequency ground wave radar polarized wave according to any one of claims 1-7. A method for estimating the direction of arrival.

Images