CN109696652B - Two-dimensional DOA estimation method and device, equipment and storage medium thereof - Google Patents

Two-dimensional DOA estimation method and device, equipment and storage medium thereof Download PDF

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CN109696652B
CN109696652B CN201910086840.7A CN201910086840A CN109696652B CN 109696652 B CN109696652 B CN 109696652B CN 201910086840 A CN201910086840 A CN 201910086840A CN 109696652 B CN109696652 B CN 109696652B
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相征
徐豪
任鹏
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Xidian University
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Abstract

The invention discloses a two-dimensional DOA estimation method, a device and a storage medium thereof, wherein the method comprises the following steps: acquiring three-linear array parameters; obtaining a signal receiving model of the three-linear array according to the parameters of the three-linear array; obtaining a first signal matrix and a second signal matrix according to a signal receiving model of a three-wire array, obtaining a first eigenvalue and a first eigenvector of the first signal matrix according to the first signal matrix, and obtaining a second eigenvalue of the second signal matrix according to the first eigenvector; and obtaining the azimuth angle and the elevation angle of the two-dimensional DOA according to the first characteristic value and the second characteristic value. According to the invention, the data receiving model of the three-linear array is adopted, the azimuth angle and the elevation angle of the signal source are rapidly paired, and only one of matrixes related to the azimuth angle and the elevation angle is subjected to eigenvalue decomposition without simultaneously performing eigenvalue decomposition, so that the complexity of operation is reduced, and the rapid pairing of the azimuth angle and the elevation angle of the signal source is realized.

Description

Two-dimensional DOA estimation method and device, equipment and storage medium thereof
Technical Field
The invention belongs to the technical field of array signal processing, and particularly relates to a two-dimensional DOA estimation method, a device and equipment thereof, and a storage medium.
Background
Array signal processing is involved in many fields such as communications, radar, and sonar, and one of the basic problems of array signal processing is estimation of the Direction of Arrival (DOA) of a spatial signal.
In practice, the two-dimensional DOA Estimation is divided into two categories, namely the first category is to consider the structure of an array antenna to finish the two-dimensional DOA Estimation, the second category is to consider the method of space-time secondary processing to finish the two-dimensional DOA Estimation, the core of the array antenna processing system for the two-dimensional DOA Estimation is mainly to estimate the elevation angle and the azimuth angle of a Signal source, the array structure commonly used by the array antenna comprises a linear array, an L type array, a circular array, a planar array, a parallel linear array and the like, and the method for processing the Signal comprises a two-dimensional MUSIC (Multiple Signal Classification, SIC) method, a two-dimensional ESPRI (timing Signal parameter correlation techniques, PRISET) method and a two-dimensional propagation method, wherein the two-dimensional MUSIC method is used for searching two-dimensional peaks, the azimuth angle and the azimuth angle are calculated according to the two-dimensional angular propagation data of the Signal sources, the two-dimensional angular propagation parameters are obtained by respectively calculating the elevation angle and the two-dimensional propagation parameters of the elevation angle.
However, the traditional two-dimensional DOA estimation method has the problems of large calculation amount and incapability of quickly matching the azimuth angle and the elevation angle of a signal source.
Disclosure of Invention
In order to solve the above problems in the prior art, the present invention provides a two-dimensional DOA estimation method, and an apparatus, a device, and a storage medium thereof.
The embodiment of the invention provides a two-dimensional DOA estimation method, which comprises the following steps:
acquiring three-linear array parameters;
obtaining a signal receiving model of the three-linear array according to the three-linear array parameters;
obtaining a first signal matrix and a second signal matrix according to the signal receiving model of the three-wire array, obtaining a first eigenvalue and a first eigenvector of the first signal matrix according to the first signal matrix, and obtaining a second eigenvalue of the second signal matrix according to the first eigenvector;
and obtaining the azimuth angle and the elevation angle of the two-dimensional DOA according to the first characteristic value and the second characteristic value.
In one embodiment of the present invention, the signal reception model of the three-wire array is:
X1＝AxS(t)+Nx1(t)
X2＝AxΦxS(t)+Nx2(t)
Y＝AyS(t)+Ny(t)
Z＝AxΦzS(t)+Nz(t)
wherein, X1Is a first received data matrix, X2Is the second received data matrix, Y is the third received data matrix, Z is the fourth received data matrix, S (t) is the received data matrix of the signal source, Nx1Is a first noise matrix, Nx2Is a second noise matrix, NyIs a third noise matrix, NzIs a fourth noise matrix, AxIs a first directional matrix, AyIs a second direction matrix, phixIs a first diagonal matrix, phizIs a second diagonal matrix.
In an embodiment of the present invention, obtaining a first signal matrix and a second signal matrix according to a signal receiving model of the three-wire array includes:
for the first received data matrix X1The second received data matrix X2Performing cross-correlation processing on the third received data matrix Y and the fourth received data matrix Z to obtain a first cross covariance matrix, a second cross covariance matrix and a third cross covariance matrix;
obtaining a signal matrix according to the first cross covariance matrix, the second cross covariance matrix and the third cross covariance matrix;
obtaining a signal subspace matrix according to the signal matrix;
and obtaining the first signal matrix and the second signal matrix according to the signal subspace matrix.
In an embodiment of the present invention, obtaining a signal subspace matrix according to the signal matrix includes:
singular value decomposition processing is carried out on the signal matrix to obtain a third eigenvalue and a third eigenvector;
and obtaining the signal subspace matrix according to the third eigenvalue and the third eigenvector.
In an embodiment of the present invention, obtaining a first eigenvalue and a first eigenvector of the first signal matrix according to the first signal matrix includes:
and carrying out eigenvalue decomposition processing on the first signal matrix to obtain a first eigenvalue and a first eigenvector.
In an embodiment of the present invention, obtaining the second eigenvalue of the second signal matrix according to the first eigenvector includes:
obtaining a second eigenvector of the second signal matrix according to the first eigenvector;
and obtaining a second eigenvalue of the second signal matrix according to the first eigenvector and the second eigenvector.
In an embodiment of the present invention, obtaining the azimuth angle and the elevation angle of the two-dimensional DOA according to the first eigenvalue and the second eigenvalue comprises:
obtaining the elevation angle of the two-dimensional DOA according to the second characteristic value;
and obtaining the azimuth angle of the two-dimensional DOA according to the first characteristic value and the elevation angle.
Another embodiment of the present invention provides an apparatus for two-dimensional DOA estimation, the apparatus comprising:
the data acquisition module is used for acquiring the three-linear array parameters;
the data model construction module is used for obtaining a signal receiving model of the three-linear array according to the three-linear array parameters;
the data processing module is used for obtaining the first signal matrix and the second signal matrix according to a signal receiving model of the three-wire array, obtaining the first eigenvalue and the first eigenvector of the first signal matrix according to the first signal matrix, and obtaining the second eigenvalue of the second signal matrix according to the first eigenvector;
and the data determining module is used for obtaining the azimuth angle and the elevation angle of the two-dimensional DOA according to the first characteristic value and the second characteristic value.
Yet another embodiment of the present invention provides an electronic device for two-dimensional DOA estimation, which includes a processor, a communication interface, a memory, and a communication bus, wherein the processor, the communication interface, and the memory complete communication with each other via the communication bus;
the memory is used for storing a computer program;
the processor is configured to implement any of the above methods when executing the computer program stored in the memory.
Yet another embodiment of the invention provides a computer-readable storage medium having stored therein a computer program which, when executed by a processor, implements any of the methods described above.
Compared with the prior art, the invention has the beneficial effects that:
1. the invention adopts the data receiving model of the three-linear array to quickly pair the two parameters of the azimuth angle and the elevation angle of the signal source, because the matrixes related to the two parameters of the azimuth angle and the elevation angle do not need to be subjected to eigenvalue decomposition at the same time, only one of the matrixes needs to be subjected to eigenvalue decomposition, and then the eigenvalue of the other matrix is solved by utilizing the characteristic that the eigenvectors of the eigenvalue decomposition of the two matrixes are the same, thereby reducing the complexity of operation and realizing the quick pairing of the two parameters of the azimuth angle and the elevation angle of the signal source.
2. Compared with the traditional double parallel linear array ESPRIT method, the method prevents the azimuth angle and the elevation angle of the signal source from being estimated simultaneously, reduces the probability of failure of the DOA estimation method when the elevation angle is close to 90 degrees, and improves the accuracy of the DOA estimation method.
The present invention will be described in further detail with reference to the accompanying drawings and examples.
Drawings
FIG. 1 is a schematic flow chart of a two-dimensional DOA estimation method according to an embodiment of the present invention;
FIG. 2 is a schematic structural diagram of a three-linear array in a two-dimensional DOA estimation method according to an embodiment of the present invention;
FIG. 3 is a schematic diagram of an apparatus for two-dimensional DOA estimation according to an embodiment of the present invention;
fig. 4 is a schematic structural diagram of an electronic device for two-dimensional DOA estimation according to an embodiment of the present invention.
Detailed Description
The present invention will be described in further detail with reference to specific examples, but the embodiments of the present invention are not limited thereto.
Example one
Referring to fig. 1 and fig. 2, fig. 1 is a schematic flow chart of a two-dimensional DOA estimation method according to an embodiment of the present invention, and fig. 2 is a schematic structural diagram of a three-linear array in the two-dimensional DOA estimation method according to the embodiment of the present invention. The embodiment of the invention provides a two-dimensional DOA estimation method, which comprises the following steps:
step 1, obtaining three-linear array parameters.
Specifically, referring to fig. 2 again, the tri-linear array is divided into three line segments on the x-axis, the y-axis, and the z-axis, and the array element number of each line segment on the x-axis, the y-axis, and the z-axis of the tri-linear array is obtained, where the array element number of the line segment on the x-axis is N, the array element numbers of the line segments on the y-axis and the z-axis are both N-1, the distances between the array elements on the x-axis, the y-axis, and the z-axis are all d, the number of signal sources in the tri-linear array is M, the frequency of the signal source is f, the emission wavelength of the signal source
Figure BDA0001962037890000061
And the receiving data of the signal source in the three-line array is S (t). Wherein, the interference signal noise when each array element receives data is Gaussian white noise with mutual statistical independence, the mean value of the Gaussian white noise is 0, and the variance of the Gaussian white noise is sigma2And the Gaussian noise and the signal source signal are independent.
Preferably, N is 8, M is 3, d is 0.5M and λ is 1M.
And 2, obtaining a signal receiving model of the three-wire array according to the parameters of the three-wire array.
Specifically, the three-wire array is divided into 4 arrays according to the structure of the three-wire array, from the origin, the first N-1 array elements on the x axis are the first array, the last N-1 array elements on the x axis are the second array, the N-1 array elements on the y axis are the third array, and the first N-1 array elements on the x axis are translated towards the z axis to obtain the fourth array. In this embodiment, the received data of the first array, the second array, the third array, and the fourth array may be represented as:
Figure BDA0001962037890000062
wherein, X1For a first received data matrix, representing received data of a first array in a three-wire array, X2Is a second received data matrix representing received data of a second array in the three-wire array, Y is a third received data matrix representing received data of a third array in the three-wire array, Z is a fourth received data matrix representing received data of a fourth array in the three-wire array, S (t) is a received data matrix of signal sources of the three-wire array, N (t)x1Is a first noise matrix, Nx2Is a second noise matrix, NyIs a third noise matrix, NzIs a fourth noise matrix, a first noise matrix Nx1A second noise matrix Nx2A third noise matrix NyA fourth noise matrix NzRespectively representing Gaussian white noise brought by interference signals when the first array, the second array, the third array and the fourth array receive data, wherein the mean values of the Gaussian white noise are all 0, and the variances are all sigma2，AxIs a first directional matrix, in particular a directional matrix of a first array, AyIs a second direction matrix, in particular a direction matrix of a third array, phixFor a first diagonal matrix, in particular a diagonal matrix generated by translating the first array into the second array, phizFor the second diagonal matrix, the first array is translated to the diagonal matrix generated for the fourth array. In this embodiment, the first direction matrix
Figure BDA0001962037890000071
Figure BDA0001962037890000072
Second direction matrix
Figure BDA0001962037890000073
Wherein the content of the first and second substances,
Figure BDA0001962037890000074
for a pitch angle and theta for a pitch angle,
Figure BDA0001962037890000075
Figure BDA0001962037890000076
d is the distance between array elements, and lambda is the emission wavelength of the signal source; first diagonal matrix
Figure BDA0001962037890000077
Second diagonal matrix
Figure BDA0001962037890000078
Figure BDA0001962037890000079
For elevation, θ is depression, and d is the spacing between array elements.
And 3, obtaining a first signal matrix and a second signal matrix according to the signal receiving model of the three-wire array, obtaining a first eigenvalue and a first eigenvector of the first signal matrix according to the first signal matrix, and obtaining a second eigenvalue of the second signal matrix according to the first eigenvector.
Step 3.1, obtaining a first signal matrix and a second signal matrix according to the signal receiving model of the three-wire array, comprising:
for the first received data matrix X1A second received data matrix X2Performing cross-correlation processing on the third received data matrix Y and the fourth received data matrix Z to obtain a first cross-covariance matrix and a second cross covariance matrixA difference matrix, a third cross covariance matrix;
obtaining a signal matrix according to the first cross covariance matrix, the second cross covariance matrix and the third cross covariance matrix;
obtaining a signal subspace matrix according to the signal matrix;
and obtaining a first signal matrix and a second signal matrix according to the signal subspace matrix.
Step 3.1.1, for the first received data matrix X1A second received data matrix X2And performing cross-correlation processing on the third received data matrix Y and the fourth received data matrix Z to obtain a first cross covariance matrix, a second cross covariance matrix and a third cross covariance matrix.
Specifically, with the signal reception model of the three-wire array of formula (1), the first reception data matrix X in the signal reception model of the three-wire array is subjected to1A second received data matrix X2Performing cross-correlation processing on the 4 received data matrixes including the third received data matrix Y and the fourth received data matrix Z, and specifically calculating the first received data matrix X1A first cross-covariance matrix R with a third received data matrix Y1Second received data matrix X2A second cross covariance matrix R with a third received data matrix Y2A third cross covariance matrix R of a fourth received data matrix Z and a third received data matrix Y3In this embodiment, the first cross covariance matrix R1A second cross covariance matrix R2A third cross covariance matrix R3Respectively expressed as:
Figure BDA0001962037890000081
wherein, E [. C]Expressing the mathematical expectation of.H denotes the conjugate transpose, Rs＝E[S(t)S(t)H]Is a signal correlation matrix of M × M.
Step 3.1.2, according to the first cross covariance matrix R1A second cross covariance matrix R2A third cross covariance matrix R3And obtaining a signal matrix R.
In particular, a first cross-covariance matrix R is utilized1A second cross covariance matrix R2A third cross covariance matrix R3A signal matrix R is constructed, and in this embodiment, the signal matrix R is specifically represented as:
R＝[R1，R2，R3]T(3)
as can be seen, the dimension of the signal matrix R is 3(N-1) × (N-1).
Step 3.1.3, obtaining a signal subspace matrix U according to the signal matrix Rs。
In this embodiment, a signal subspace matrix U is obtained according to the signal matrix RsThe method comprises the following steps:
performing singular value decomposition processing on the matrix R to obtain a third eigenvalue and a third eigenvector;
obtaining a signal subspace matrix U according to the third eigenvalue and the third eigenvectors。
Further, singular value decomposition processing is performed on the signal matrix R to obtain a third eigenvalue and a third eigenvector.
Specifically, singular value decomposition processing is performed on the signal matrix R by using the singular value decomposition theorem of the matrix, wherein the specific singular value decomposition is expressed as:
R＝U∑VH(4)
wherein, U and VHAnd the matrix is generated by performing singular value decomposition on the signal matrix R respectively, wherein U is a third eigenvector, ∑ is a third diagonal matrix, and the value of the diagonal in the third diagonal matrix is the third eigenvalue of the signal matrix R.
Further, a signal subspace matrix U is obtained according to the third eigenvalue and the third eigenvectors。
Specifically, the third eigenvector U is not directly taken as the signal subspace matrix U in this embodimentsFirst, the third eigenvalues are sorted in ascending order from small to large, eigenvectors corresponding to the first M larger third eigenvalues are obtained from the ascending order, and the eigenvectors corresponding to the M third eigenvalues form a signal subspace UsIn this embodiment, the signalSpace UsExpressed as:
Us＝U(：，1：M) (5)
step 3.1.4, according to the signal subspace matrix UsAnd obtaining a first signal matrix and a second signal matrix.
In particular, because the M signal sources in the three-wire array are independent of each other, the signal subspace U issThe subspace spanned by the array pattern of the signal matrix R is the same, so that there must be a non-singular matrix T such that:
Figure BDA0001962037890000101
wherein, Us1＝Us(1：M，：)，Us2＝Us(M+1：2M，：)，Us3＝Us(2M + 1: 3M, A is represented by AxAnd
Figure BDA0001962037890000105
and forming a conversion matrix.
Let the first signal matrix Ψx＝T-1ΦxT, second signal matrix ΨZ＝T-1ΦzT, the first signal matrix ΨxSecond signal matrix ΨZSubstituting equation (6), equation (6) can thus be re-expressed as:
Figure BDA0001962037890000102
the first signal matrix Ψ can be obtained by equation (7)xSecond signal matrix ΨZFirst signal matrix ΨxSecond signal matrix ΨZThe concrete expression is as follows:
Figure BDA0001962037890000103
wherein · --1Represents the inverse of.
Step 3.2, according to the first signal matrix psixObtaining a first signal matrix ΨxAnd a first feature vector.
Specifically, the conventional DOA estimation method is to simultaneously perform the first signal matrix Ψ in equation (8)xSecond signal matrix ΨZCarrying out eigenvalue decomposition and solving the elevation angle of DOA
Figure BDA0001962037890000104
And a depression angle θ, but this involves a large amount of calculation. This embodiment does not require the first signal matrix ΨxSecond signal matrix ΨZThe eigenvalue decomposition is performed simultaneously for both matrices, only for the first signal matrix ΨxPerforming eigenvalue decomposition to obtain a first signal matrix ΨxFirst characteristic value V ofxi(i ═ 1, 2.. times, M), a first characteristic value VxiIncluding the azimuth and elevation information of the signal source.
By the first characteristic value VxiThe first characteristic value V can be obtainedxiCorresponding first feature vector Ui(i ═ 1, 2.. times, M), a first eigenvector UiExpressed as:
Ui＝[ui1ui2...uiM]T(9)
wherein u isjiRepresenting a first feature vector UiThe ith vector of the jth eigenvector in (a), T, represents the transpose of the matrix.
The present embodiment is implemented by only mapping the first signal matrix ΨxThe eigenvalue decomposition is carried out, thereby avoiding the situation that the traditional DOA estimation method simultaneously carries out the first signal matrix psixSecond signal matrix ΨZAnd decomposing the characteristic value, thereby reducing the operation complexity of the DOA estimation method, improving the parameter matching speed and realizing the rapid parameter matching.
Step 3.3, according to the first characteristic vector UiTo obtain a second signal matrix ΨZThe second characteristic value of (1).
In this embodiment, the first feature vector U is usediTo obtain a second signal matrix ΨZIncludes:
according to the first feature vector UiTo obtain a second signal matrix ΨZThe second feature vector of (2);
according to the first feature vector UiAnd a second eigenvector, obtaining a second eigenvalue of the second signal matrix.
Further, according to the first feature vector UiTo obtain a second signal matrix ΨZThe second feature vector of (1).
In particular, because the first signal matrix ΨxSecond signal matrix ΨZHaving the same eigenvectors, the second signal matrix Ψ is set in this embodimentZIs a second eigenvector ofzUiThe second eigenvector is ΨZUiCan pass through the first feature vector UiExpressed as:
ΨzUi＝[wi1wi2...wiM]T(10)
wherein, wjiRepresenting the second eigenvector ΨZUiThe ith vector of the jth eigenvector in (a), T, represents the transpose of the matrix.
Further, according to the first feature vector UiAnd a second eigenvector ΨZUiTo obtain a second signal matrix ΨZThe second characteristic value of (1).
Specifically, a first feature vector U is utilizediAnd a second eigenvector ΨZUiSolving for the second signal matrix ΨZSecond characteristic value V ofzi(i ═ 1, 2.., M), the second characteristic value V of the present embodimentziExpressed as:
Figure BDA0001962037890000121
wherein u isikRepresenting a first feature vector UiThe kth vector, w, of the ith feature vectorikRepresenting the second eigenvector ΨZUiThe kth vector of the ith feature vector.
To improve the accuracy of DOA estimation, the present embodimentExample to find the second characteristic value VziIs expressed as:
Figure BDA0001962037890000122
in the present embodiment, the second characteristic value V is obtained by equations (11) to (12)ziRealize the parameter matching which is actually the azimuth angle theta and the elevation angle of the same signal source
Figure BDA0001962037890000123
The signal source is in one-to-one correspondence, so that the specific direction of the signal source in the three-dimensional space can be estimated, and if the azimuth angle theta and the elevation angle theta are solved in the pairing process
Figure BDA0001962037890000124
If the signals do not belong to the same signal source, the pairing of the parameters fails, and finally the direction of the signal source cannot be correctly estimated. The conventional DOA estimation method is to determine the first signal matrix Ψ in equation (8)xSecond signal matrix ΨZThe two matrixes carry out eigenvalue decomposition simultaneously, parameter pairing can be achieved, and the calculation amount is large. The DOA estimation method of this embodiment is to decompose the eigenvalues of only one of the matrices, and the DOA estimation method of this embodiment is to decompose the first signal matrix ΨxPerforming eigenvalue decomposition and then using the first signal matrix ΨxSecond signal matrix ΨZThe two matrixes have the characteristic of the same eigenvector, so that the azimuth angle theta and the elevation angle of a signal source in DOA estimation are ensured
Figure BDA0001962037890000131
The information is in one-to-one correspondence, automatic pairing of the parameters is achieved, and the most important is that the operand is small, and rapid pairing of the parameters is achieved.
Step 4, obtaining the azimuth angle theta and the elevation angle of the two-dimensional DOA according to the first characteristic value and the second characteristic value
Figure BDA0001962037890000132
In this embodiment, the azimuth angle θ and the elevation angle of the two-dimensional DOA are obtained according to the first characteristic value and the second characteristic value
Figure BDA0001962037890000133
The method comprises the following steps:
according to the second characteristic value, obtaining the elevation angle of the two-dimensional DOA
Figure BDA0001962037890000134
According to the first characteristic value and the upward viewing angle
Figure BDA0001962037890000135
The azimuth angle θ of the two-dimensional DOA is obtained.
Specifically, the second characteristic value V is obtained by equation (12)ziBy the first signal matrix ΨxDetermining a first characteristic value VxiThe azimuth angle theta and the elevation angle of the signal source of this embodiment
Figure BDA0001962037890000136
Expressed as:
Figure BDA0001962037890000137
as can be seen from equation (13), the second characteristic value V is used in the present embodimentziThe distance d between the array elements is equal to the elevation angle of the signal source
Figure BDA0001962037890000138
First of all an individual estimation is carried out and then a first characteristic value VxiThe spacing d between the array elements and the determined elevation angle
Figure BDA0001962037890000139
An estimate of the azimuth angle theta of the signal source is made.
This embodiment is because the second characteristic value VziIncluding only the elevation angle of each signal source
Figure BDA00019620378900001310
Information does not contain azimuth angle theta information, so the parameter matching method based on the three-linear array can firstly match the elevation angle
Figure BDA00019620378900001311
The estimation is carried out independently without considering the estimation error of the azimuth angle, so that the effectiveness of the traditional DOA estimation method for estimating the two-dimensional angle of arrival of the signal source is improved, and the problem that the traditional DOA estimation method fails when the elevation angle approaches 90 degrees is solved, wherein the azimuth angle theta and the elevation angle theta of the signal source are equal to the elevation angle theta
Figure BDA00019620378900001312
Collectively referred to as two-dimensional angles of arrival.
In summary, in the embodiment, the data receiving model of the three-linear array is adopted, and compared with the conventional dual-parallel-linear-array ESPRIT method, the azimuth angle θ and the elevation angle of the signal source are prevented
Figure BDA0001962037890000141
Meanwhile, estimation is carried out, the probability of failure of the DOA estimation method when the elevation angle is close to 90 degrees is reduced, and therefore the accuracy of the DOA estimation method is improved; in the embodiment, a data receiving model of a three-wire array is adopted, and the azimuth angle theta and the elevation angle of a signal source are measured
Figure BDA0001962037890000142
The two parameters are paired quickly because there is no need to pair the parameters relating to azimuth theta and elevation
Figure BDA0001962037890000143
The two matrices of the two parameters are subjected to eigenvalue decomposition simultaneously, only one of the two matrices needs to be subjected to eigenvalue decomposition, then the eigenvalues of the other matrix are solved by using the same eigenvector of the eigenvalue decomposition of the two matrices, so that the complexity of the operation is reducedxSecond signal matrix ΨZ。
Referring to fig. 3, fig. 3 is a schematic structural diagram of a two-dimensional DOA estimation apparatus according to an embodiment of the present invention. Another embodiment of the present invention provides an apparatus for two-dimensional DOA estimation, the apparatus comprising:
the data acquisition module is used for acquiring the parameters of the three-linear array;
the data model construction module is used for obtaining a signal receiving model of the three-linear array according to the parameters of the three-linear array;
the data processing module is used for obtaining a first signal matrix and a second signal matrix according to a signal receiving model of the three-wire array, obtaining a first eigenvalue and a first eigenvector of the first signal matrix according to the first signal matrix, and obtaining a second eigenvalue of the second signal matrix according to the first eigenvector;
and the data determining module is used for obtaining the azimuth angle and the elevation angle of the two-dimensional DOA according to the first characteristic value and the second characteristic value.
The device for estimating two-dimensional DOA provided by the embodiment of the invention can execute the method embodiment, and the implementation principle and the technical effect are similar, and are not described herein again.
Referring to fig. 4, fig. 4 is a schematic structural diagram of an electronic device for two-dimensional DOA estimation according to an embodiment of the present invention. Yet another embodiment of the present invention provides an electronic device for two-dimensional DOA estimation, which includes a processor, a communication interface, a memory, and a communication bus, wherein the processor, the communication interface, and the memory complete communication with each other through the communication bus;
a memory for storing a computer program;
a processor for executing the computer program stored in the memory, the computer program when executed by the processor performing the steps of:
acquiring three-linear array parameters;
obtaining a signal receiving model of the three-linear array according to the parameters of the three-linear array;
obtaining a first signal matrix and a second signal matrix according to a signal receiving model of a three-wire array, obtaining a first eigenvalue and a first eigenvector of the first signal matrix according to the first signal matrix, and obtaining a second eigenvalue of the second signal matrix according to the first eigenvector;
and obtaining the azimuth angle and the elevation angle of the two-dimensional DOA according to the first characteristic value and the second characteristic value.
The electronic device for two-dimensional DOA estimation provided by the embodiment of the invention can execute the method embodiment, and the implementation principle and the technical effect are similar, and are not described herein again.
Yet another embodiment of the present invention provides a computer-readable storage medium having stored thereon a computer program which, when executed by a processor, performs the steps of:
acquiring three-linear array parameters;
obtaining a signal receiving model of the three-linear array according to the parameters of the three-linear array;
obtaining a first signal matrix and a second signal matrix according to a signal receiving model of a three-wire array, obtaining a first eigenvalue and a first eigenvector of the first signal matrix according to the first signal matrix, and obtaining a second eigenvalue of the second signal matrix according to the first eigenvector;
and obtaining the azimuth angle and the elevation angle of the two-dimensional DOA according to the first characteristic value and the second characteristic value.
The computer-readable storage medium provided in the embodiment of the present invention may implement the above method embodiments, and its implementation principle and technical effect are similar, which are not described herein again.
The foregoing is a more detailed description of the invention in connection with specific preferred embodiments and it is not intended that the invention be limited to these specific details. For those skilled in the art to which the invention pertains, several simple deductions or substitutions can be made without departing from the spirit of the invention, and all shall be considered as belonging to the protection scope of the invention.

Claims (4)

1. A two-dimensional DOA estimation method, comprising:
acquiring three-linear array parameters;
obtaining a signal receiving model of the three-wire array according to the parameters of the three-wire array, wherein the signal receiving model of the three-wire array is as follows:
Figure FDA0002515932540000011
wherein, X1Is a first received data matrix, X2Is the second received data matrix, Y is the third received data matrix, Z is the fourth received data matrix, S (t) is the received data matrix of the signal source, Nx1Is a first noise matrix, Nx2Is a second noise matrix, NyIs a third noise matrix, NzIs a fourth noise matrix, AxIs a first directional matrix, AyIs a second direction matrix, phixIs a first diagonal matrix, phizIs a second diagonal matrix;
obtaining a first signal matrix and a second signal matrix according to the signal receiving model of the three-wire array, performing eigenvalue decomposition processing on the first signal matrix to obtain a first eigenvalue and a first eigenvector of the first signal matrix, and obtaining a second eigenvalue of the second signal matrix according to the first eigenvector, wherein,
obtaining a first signal matrix and a second signal matrix according to the signal receiving model of the three-wire array, comprising:
for the first received data matrix X1The second received data matrix X2Performing cross-correlation processing on the third received data matrix Y and the fourth received data matrix Z to obtain a first cross covariance matrix, a second cross covariance matrix and a third cross covariance matrix;
obtaining a signal matrix according to the first cross covariance matrix, the second cross covariance matrix and the third cross covariance matrix;
obtaining a signal subspace matrix according to the signal matrix, including:
singular value decomposition processing is carried out on the signal matrix to obtain a third eigenvalue and a third eigenvector;
obtaining the signal subspace matrix according to the third eigenvalue and the third eigenvector;
obtaining the first signal matrix and the second signal matrix according to the signal subspace matrix;
obtaining a second eigenvalue of the second signal matrix according to the first eigenvector, including:
obtaining a second eigenvector of the second signal matrix according to the first eigenvector;
obtaining a second eigenvalue of the second signal matrix according to the first eigenvector and the second eigenvector;
obtaining an azimuth angle and an elevation angle of the two-dimensional DOA according to the first characteristic value and the second characteristic value, comprising:
obtaining the elevation angle of the two-dimensional DOA according to the second characteristic value;
and obtaining the azimuth angle of the two-dimensional DOA according to the first characteristic value and the elevation angle.
2. An apparatus for two-dimensional DOA estimation, the apparatus comprising:
the data acquisition module is used for acquiring the parameters of the three-linear array;
the data model construction module is used for obtaining a signal receiving model of the three-wire array according to the parameters of the three-wire array, and the signal receiving model of the three-wire array is as follows:
Figure FDA0002515932540000031
wherein, X1Is a first received data matrix, X2Is the second received data matrix, Y is the third received data matrix, Z is the fourth received data matrix, S (t) is the received data matrix of the signal source, Nx1Is a first noise matrix, Nx2Is a second noise matrix, NyIs a third noise matrix, NzIs a fourth noise matrix, AxIs a first directional matrix, AyIs a second direction matrix, phixIs a first diagonal matrix, phizIs a second diagonal matrix;
a data processing module, configured to obtain a first signal matrix and a second signal matrix according to the signal receiving model of the three-wire array, perform eigenvalue decomposition on the first signal matrix to obtain a first eigenvalue and a first eigenvector of the first signal matrix, and obtain a second eigenvalue of the second signal matrix according to the first eigenvector, where,
obtaining a first signal matrix and a second signal matrix according to the signal receiving model of the three-wire array, comprising:
for the first received data matrix X1The second received data matrix X2Performing cross-correlation processing on the third received data matrix Y and the fourth received data matrix Z to obtain a first cross covariance matrix, a second cross covariance matrix and a third cross covariance matrix;
obtaining a signal matrix according to the first cross covariance matrix, the second cross covariance matrix and the third cross covariance matrix;
obtaining a signal subspace matrix according to the signal matrix, including:
singular value decomposition processing is carried out on the signal matrix to obtain a third eigenvalue and a third eigenvector;
obtaining the signal subspace matrix according to the third eigenvalue and the third eigenvector;
obtaining the first signal matrix and the second signal matrix according to the signal subspace matrix;
obtaining a second eigenvalue of the second signal matrix according to the first eigenvector, including:
obtaining a second eigenvector of the second signal matrix according to the first eigenvector;
obtaining a second eigenvalue of the second signal matrix according to the first eigenvector and the second eigenvector;
a data determining module, configured to obtain an azimuth angle and an elevation angle of the two-dimensional DOA according to the first characteristic value and the second characteristic value, including:
obtaining the elevation angle of the two-dimensional DOA according to the second characteristic value;
and obtaining the azimuth angle of the two-dimensional DOA according to the first characteristic value and the elevation angle.
3. An electronic device for two-dimensional DOA estimation, comprising a processor, a communication interface, a memory and a communication bus, wherein the processor, the communication interface and the memory communicate with each other via the communication bus;
the memory is used for storing a computer program;
the processor, when executing the computer program stored on the memory, implementing the method of claim 1.
4. A computer-readable storage medium, in which a computer program is stored which, when being executed by a processor, carries out the method of claim 1.
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