WO2015096099A1

WO2015096099A1 - Method and apparatus for estimating angle of arrival, and electronic device

Info

Publication number: WO2015096099A1
Application number: PCT/CN2013/090581
Authority: WO
Inventors: 刘劲楠; 王悦
Original assignee: 华为技术有限公司
Priority date: 2013-12-26
Filing date: 2013-12-26
Publication date: 2015-07-02
Also published as: CN104937856B; CN104937856A

Abstract

The present invention provides a method and an apparatus for estimating an angle of arrival and an electronic device, which are used for solving the technical problem existing in the prior art that larger storage space is needed to store a redundant dictionary. The electronic device, used in an orthogonal frequency division multiplexing communications system, comprises a processor, used for obtaining antenna array measurement results of M array elements, and estimating angles of arrival of K radio signals according to the antenna array measurement results and a redundant dictionary, the redundant dictionary being a partially-discrete Fourier transform matrix, M and K being positive integers.

Description

Method, device and electronic device for estimating angle of arrival

The present invention relates to the field of communications, and in particular, to a method, apparatus, and electronic device for estimating an angle of arrival. Background technique

The use of antenna arrays to measure the angle of arrival of a signal source (DOA) plays an important role in many fields such as radar, communications, sonar, and voice. In the wireless communication, the base station can measure the terminal by measuring the DOA of the terminal signal (ie, the uplink signal), and can also perform the weight selection of the downlink beamforming (Downlink Beam Forming) according to the DO A. Similarly, the terminal can also perform weight selection of Uplink Beam Forming by measuring the DOA of the base station signal (ie, the downlink signal).

In the existing method of estimating DOA based on the compressed sensing algorithm, after generating the redundant dictionary, a large storage space is required to store the redundant dictionary. Summary of the invention

The invention provides a method, a device and an electronic device for estimating an angle of arrival, which are used to solve the technical problem that a storage redundancy dictionary existing in the prior art requires a large storage space.

In a first aspect, the present invention provides an electronic device, which is applied to an Orthogonal Frequency Division Multiplexing (OFDM) communication system, and includes: a processor, configured to obtain an antenna array measurement result of M array elements; and based on the antenna array measurement result and The redundancy dictionary estimates the angle of arrival of the K wireless signals, wherein the redundancy dictionary is a partial discrete Fourier transform matrix, where M and K are both positive integers.

With reference to the first aspect, in a first possible implementation manner, when the M array elements include an array element having at least two dimensions, the processor is specifically configured to: obtain the M array elements respectively An antenna array measurement result of the array elements of each dimension; for each of the array elements, estimating K arrival angles based on the antenna array measurement results and the redundancy dictionary; The K arrival angles of the array elements of the dimensions, and the K arrival angles of the M array elements are estimated.

With reference to the first aspect or the first possible implementation manner, in a second possible implementation manner, the redundancy dictionary is obtained by: uniformly dividing a range of trigonometric function values into N grids; A direction vector of each of the N grids, and the redundant dictionary is composed of N of the direction vectors.

In conjunction with the second possible implementation, in a third possible implementation, the direction vector is determined according to the following formula:

2i 0) = [1 _e j^(!- ^2i/N ) _e (M-1)(1 - 2i/N)]T where is the angle of the i-th grid, » =arccos(l- 2i/ N), i = 0,...,Nl, M«N, N is an integer power of 2.

With reference to the first aspect, and any one of the first possible implementation to the third possible implementation, in a fourth possible implementation, the processor is specifically configured to: The measurement result and the redundancy dictionary are obtained by using the compressed sensing algorithm to obtain a sparse signal matrix, wherein the compressed sensing algorithm includes at least: 计算 calculating a transposed right multiplied first matrix of the redundant dictionary by using a fast Fourier algorithm Operation and/or redundancy dictionary right multiplication of the second matrix operation, the first matrix and the second matrix being a matrix associated with the antenna array measurement results; estimating the angle of arrival based on the sparse signal matrix .

With reference to the fourth possible implementation manner, in a fifth possible implementation, the processor is further configured to:: based on the antenna array measurement result, the redundancy dictionary, and one of the redundancy dictionary The order derivative matrix is obtained by using the compressed sensing algorithm to obtain a sparse signal matrix.

In conjunction with the fifth possible implementation, in a sixth possible implementation, the elements of the first derivative matrix are determined according to the following formula:

B( jj π) = j ^2;r (jj ~^ _c j^(jj-D(i-2ii N)

, N

Where jj is the number of rows of the first derivative matrix, ϋ is the number of columns of the first derivative matrix, jj=0, l,..., Ml, ϋ=0,1,.··,Ν- 1. In combination with the fourth possible implementation to the sixth possible implementation, in a seventh possible implementation, the processor is specifically configured to: expand the first matrix into N Dimension matrix; performing an inverse fast Fourier transform on the N-dimensional matrix and performing fast Fourier shift.

In combination with the fourth possible implementation to the sixth possible implementation, in the eighth possible implementation, the processor is specifically configured to: perform fast fast on the second matrix Inverse transform, obtaining a third matrix; determining an even term in the first M term in the third matrix as an even term of the operation result of the redundant dictionary right multiplied by the second matrix, and The inverted value of the odd term in the first M term in the third matrix is determined to be an odd term of the operation result.

With reference to the first aspect, and the first possible implementation manner to the eighth possible implementation manner, in the ninth possible implementation manner, the electronic device further includes: an antenna array, configured to perform measurement according to Configuring to perform received signal measurement to obtain the antenna array measurement result, wherein the measurement configuration includes at least a combination of one or more of a sparsity degree, a snapshot number, and a number of snapshot bits.

With reference to the first aspect, and the first possible implementation to the eighth possible implementation, in the tenth possible implementation, the electronic device further includes: a receiver, configured to receive The antenna array measures the result, and sends the antenna array measurement result to the processor.

In conjunction with the first aspect, and the first possible implementation to the tenth possible implementation, in an eleventh possible implementation, the electronic device is specifically a terminal or a base station.

In a second aspect, the present invention provides an apparatus for estimating an angle of arrival, which is applied to an Orthogonal Frequency Division Multiplexing (OFDM) communication system, and includes: an antenna array measurement result receiving unit, configured to obtain an antenna array measurement result of M array elements; And an angle estimating unit, configured to estimate an angle of arrival of the K wireless signals based on the antenna array measurement result and the redundancy dictionary, wherein the redundancy dictionary is a partial discrete Fourier transform matrix, and M and K are positive integers.

With reference to the second aspect, in a first possible implementation, when the M array elements include an array element having at least two dimensions, the angle of arrival estimating unit specifically includes: an antenna array measurement result input subunit An antenna array measurement result for respectively obtaining an array element of each of the M array elements; a single dimension angle of arrival calculation subunit, configured for the array element of each dimension, based on the antenna array measurement Results and the redundant dictionary, estimating K angles of arrival; multi-dimensional arrival An angle calculation subunit, configured to calculate the K arrival angles of the M array elements based on K arrival angles of the array elements of each of the dimensions.

With reference to the second aspect or the first possible implementation manner, in a second possible implementation manner, the redundancy dictionary is obtained by: uniformly dividing a range of trigonometric function values into N grids; A direction vector of each of the N grids, and the redundant dictionary is composed of N of the direction vectors.

2i 0) _e (M-1)(1- 2i/N)]T

Where is the angle of the i-th grid, » =arccos(l-2i/ N), i = 0,...,N-l, M«N,

N is an integer power of 2.

With reference to the second aspect, and any one of the first possible implementation to the third possible implementation, in a fourth possible implementation, the angle of arrival estimation unit specifically includes: a sparse signal matrix calculation a subunit, configured to obtain a sparse signal matrix by using the compressed sensing algorithm based on the antenna array measurement result and the redundancy dictionary, where the compressed sensing algorithm includes at least: calculating a redundancy by using a fast Fourier algorithm Transposition of the dictionary by the operation of the first matrix and/or operation of the redundancy dictionary by the operation of the second matrix. The first matrix and the second matrix are matrices related to the measurement results of the antenna array; the estimation subunit And for estimating the angle of arrival based on the sparse signal matrix.

With reference to the fourth possible implementation manner, in a fifth possible implementation, the sparse signal matrix calculation subunit is specifically configured to: determine, according to the antenna array measurement result, the redundancy dictionary, and the redundancy The first derivative matrix of the dictionary is obtained by using the compressed sensing algorithm to obtain a sparse signal matrix.

With reference to the fifth possible implementation manner, in a sixth possible implementation manner, the elements in the first derivative matrix are determined according to the following formula: B( jj ii) : j ^2;r (jj ~ ^ _c j^( jj -i)d-2ii N)

, N

Where jj is the row index of the first derivative matrix, ii is the column index of the first derivative matrix, jj=0, l,..., Ml, ϋ=0,1,. · ·, Ν-1.

With reference to any one of the fourth possible implementation to the sixth possible implementation, in a seventh possible implementation, the sparse signal matrix calculation subunit includes: an extension subunit, The first matrix is expanded into a dimensional matrix; an inverse fast Fourier transform sub-unit is configured to perform an inverse fast Fourier transform on the one-dimensional matrix, and perform a fast Fourier transform shift.

With reference to any one of the fourth possible implementation manner and the sixth possible implementation manner, in the eighth possible implementation manner, the sparse signal matrix calculation subunit, specifically includes: inverse fast Fourier transform a subunit, configured to perform an inverse fast Fourier transform on the second matrix, to obtain a third matrix, and a determining subunit, configured to determine an even term in the preceding item in the third matrix as The redundancy dictionary is right-multiplied by the even term of the operation result of the second matrix, and the inverted value of the odd term in the preceding term in the third matrix is determined as an odd term of the operation result.

With reference to the second aspect, and the first possible implementation manner to the eighth possible implementation manner, in the ninth possible implementation manner, the antenna array measurement result receiving unit is specifically configured to: The measurement configuration performs a received signal measurement to obtain the antenna array measurement result, wherein the measurement configuration includes at least a combination of one or more of a sparsity degree, a snapshot number, and a number of snapshot bits.

With reference to the second aspect, and the first possible implementation manner to the eighth possible implementation manner, in the tenth possible implementation manner, the antenna array measurement result receiving unit is specifically configured to: receive The antenna array measurement result transmitted by the peer device.

In a third aspect, the present invention provides a method for estimating an angle of arrival, which is applied to an Orthogonal Frequency Division Multiplexing (OFDM) communication system, comprising: obtaining an antenna array measurement result of two array elements; based on the antenna array measurement result and redundancy a dictionary, estimating an angle of arrival of the plurality of wireless signals, wherein the redundancy dictionary is a partial discrete Fourier transform matrix, and Μ and Κ are positive integers. With reference to the third aspect, in a first possible implementation manner, when the M array elements include an array element having at least two dimensions, the antenna array measurement result of obtaining the M array elements is specifically as follows: An antenna array measurement result of the array element of each of the M array elements is obtained. The estimating the angle of arrival of the K wireless signals based on the antenna array measurement result and the redundancy dictionary, specifically: An array element of one dimension, estimating K arrival angles based on the antenna array measurement result and the redundancy dictionary; calculating the M array elements based on K arrival angles of the array elements of each dimension Said K arrival angles.

With reference to the third aspect or the first possible implementation manner, in a second possible implementation manner, the redundancy dictionary is obtained by: uniformly dividing a range of trigonometric function values into N grids; A direction vector of each of the N grids, and the redundant dictionary is composed of N of the direction vectors.

^ 0. ) = [1 _e j ⁽¹ - ^{2i / N} ) _e (M-1)(1 - 2i / N) ]T where is the angle of the i-th grid, ^ = arccos(l- 2i / N), i = 0,..., Nl , M « N , N is an integer power of 2.

With reference to the third aspect, and any one of the first possible implementation to the third possible implementation, in a fourth possible implementation, the performing, based on the antenna array measurement result and the redundancy dictionary, Estimating the angle of arrival of the K wireless signals, the method comprising: obtaining the sparse signal matrix by using the compressed sensing algorithm based on the antenna array measurement result and the redundancy dictionary, wherein the compressed sensing algorithm includes at least: The Fourier algorithm calculates the operation of the transposed right-of-first matrix of the redundancy dictionary and/or the operation of the redundant dictionary by the second matrix. The first matrix and the second matrix are measured with the antenna array. a correlation matrix; estimating the angle of arrival based on the sparse signal matrix.

With reference to the fourth possible implementation manner, in a fifth possible implementation, the obtaining, by using the compressed sensing algorithm, a sparse letter based on the antenna array measurement result and the redundancy dictionary The number matrix is specifically: based on the antenna array measurement result, the redundancy dictionary, and a first derivative matrix of the redundancy dictionary, the compressed sensing algorithm is used to obtain a sparse signal matrix.

B( jj ϋ) = j ^{2; γ} " ~ ^ _c j^( jj-D(i-2ii/N)

, N

Where jj is the number of rows of the first derivative matrix, ii is the number of columns of the first derivative matrix, jj=0, l,..., Ml, ϋ=0,1,. · ·,Ν- 1.

Combining the fourth possible implementation manner with the sixth possible implementation manner, in the seventh possible implementation manner, using the fast Fourier algorithm, the transposed matrix of the redundant dictionary is multiplied by the first The matrix specifically includes: expanding the first matrix into a one-dimensional matrix; performing an inverse fast Fourier transform on the one-dimensional matrix, and performing fast Fourier shift.

Combining the fourth possible implementation manner with the sixth possible implementation manner, in the eighth possible implementation manner, using the fast Fourier algorithm to use the redundant dictionary to multiply the operation of the second matrix, Specifically, the method includes: performing an inverse fast Fourier transform on the second matrix to obtain a third matrix; determining an even term in the preceding term in the third matrix as the redundancy dictionary, and multiplying the redundant matrix An even term of the operation result of the two matrices, and an inverse value of the odd term in the preceding term in the third matrix is determined as an odd term of the operation result.

With reference to the third aspect, and any one of the first possible implementation to the eighth possible implementation, in the ninth possible implementation, before the obtaining the array measurement flaw, the method further The method includes: obtaining the antenna array measurement result according to the measurement configuration, wherein the measurement configuration includes at least a combination of one or more of a sparsity degree, a snapshot number, and a number of snapshot bits.

With reference to the third aspect, and any one of the first possible implementation manner to the eighth possible implementation manner, in the tenth possible implementation manner, the obtaining the array measurement result is specifically: receiving by the opposite end The antenna array measurement result sent by the device. The beneficial effects of the invention:

The present invention provides an electronic device, which is applied to an Orthogonal Frequency Division Multiplexing (OFDM) communication system, the electronic device includes: a processor, configured to obtain antenna array measurement results of M array elements and measure scar and redundancy based on the antenna array a dictionary, estimating an angle of arrival of the K wireless signals, wherein the redundant dictionary used herein is a partial discrete Fourier transform matrix, that is, the redundant dictionary has a discrete Fourier transform factor, then, the complex By using a part of the complete discrete Fourier transform matrix in the orthogonal frequency division multiplexing communication system, the redundant dictionary is stored without consuming additional storage space, so the storage redundancy dictionary existing in the prior art is effectively solved. The technical problem of large storage space saves system resources. DRAWINGS

1 is a functional block diagram of an electronic device according to an embodiment of the present invention;

2A-2B are functional block diagrams of an electronic device according to another embodiment of the present invention;

3 is a schematic structural diagram of a uniform linear array according to an embodiment of the present invention;

4 is a schematic structural view of an L-shaped array according to an embodiment of the present invention;

FIG. 5 is a schematic diagram showing a relationship between a spatial angle and a direction angle according to an embodiment of the present invention; FIG.

6 is a functional block diagram of an apparatus for estimating an angle of arrival in an embodiment of the present invention;

7 is a flow chart of a method of estimating an angle of arrival in an embodiment of the present invention. detailed description

The embodiment of the present application solves the technical problem that a storage redundancy dictionary needs a large storage space in the prior art by providing a method, a device, and an electronic device for estimating an angle of arrival.

The technical solution in the embodiment of the present application solves the problem that a storage redundancy dictionary needs to have a large storage space. The general idea is as follows:

The present invention provides an apparatus for estimating an angle of arrival, which is applied to an Orthogonal Frequency Division Multiplexing (OFDM) communication system, the apparatus comprising: an angle of arrival estimation unit for obtaining antenna array measurement results of M array elements and based on an antenna array Measurement results and redundant dictionary, estimating the angle of arrival of K wireless signals, The redundant dictionary used here is a partial discrete Fourier transform matrix, that is to say, the redundant dictionary has a discrete Fourier transform factor, and then the multiplexed frequency division multiplexing communication system can be multiplexed. A part of the complete discrete Fourier transform matrix does not need to consume additional storage space to store the redundant dictionary. Therefore, the technical problem of requiring a large storage space for the storage redundancy dictionary existing in the prior art is effectively solved, and the storage is saved. space.

The technical solutions of the present invention are described in detail below with reference to the accompanying drawings and specific embodiments. It is understood that the specific features of the embodiments and the embodiments of the present invention are the detailed description of the technical solutions of the present invention. In the case of no conflict, the technical features of the embodiments of the present invention and the embodiments may be combined with each other.

The present invention provides an electronic device, which may be any node in an Orthogonal Frequency Division Multiplexing (OFDM) communication system, such as a terminal, a base station, and of course, other wireless communication devices. This application does not specifically limit it.

Please refer to FIG. 1. FIG. 1 is a functional block diagram of an electronic device for estimating an angle of arrival according to an embodiment of the present invention. The electronic device includes: a processor 10, configured to obtain an antenna array measurement result of the M array elements; and an angle of arrival of the K wireless signals based on the antenna array measurement result and the redundancy dictionary, where the redundancy dictionary is partially discrete A Fourier transform matrix, where M and K are both positive integers.

Optionally, the electronic device may further include a transceiver 20 and a memory 30. If the electronic device is a terminal, the display unit, the WIFI module, the I/O interface, and the like may also be included.

In practical applications, the above antenna array measurement result is obtained by measuring the wireless signal received by the antenna array, and then there are the following two cases.

In the first case, the antenna array measurement result is obtained by the electronic device itself. At this time, as shown in FIG. 2A, the electronic device further includes: an antenna array 11a, configured to perform a received signal measurement according to the measurement configuration to obtain an antenna array measurement result.

Specifically, the antenna array 11a and the processor 10 are disposed in the same device. Then, after receiving the wireless signal transmitted by the signal source, the antenna array 11a measures the signal according to the measurement configuration, and generates an antenna array measurement result, and then The result is sent to the processor 10. Of course, the antenna array 11a may only have the function of receiving signals, and when the antenna array 11a receives the wireless signal, it sends it The measurement processor is sent to the electronic device to generate an antenna array measurement result, and the result is sent to the processor 10.

In this embodiment, the antenna array 11a may be a one-dimensional antenna array, such as a linear array of uniform hooks, or a multi-dimensional antenna array, such as a two-dimensional L-shaped array, which is not specifically limited in the present application. The above measurement configuration includes at least a combination of one or more of sparsity, number of snapshots, and number of snapshot bits per snapshot.

Further, if the antenna array 11a and the processor 10 are both disposed in the same electronic device, the above-mentioned measurement configuration can be determined by the electronic device without being sent by other devices.

In the second case, the antenna array measurement result is measured and sent by the peer device. At this time, as shown in FIG. 2B, the electronic device further includes: a receiver lib, configured to receive the antenna array measurement result, and measure the antenna array. The result is sent to the processor.

Specifically, the antenna array and the processor 10 are disposed in different devices, that is, the antenna device is disposed on the opposite device, and after the antenna array measures the wireless signal received by the antenna array and obtains the antenna array measurement result, The measurement result is sent to the electronic device and received by the receiver lib, which in turn is sent to the processor 10.

Further, if the antenna array and the processor 10 are respectively disposed in the terminal and the base station, the measurement configuration is sent by the base station to the terminal or negotiated with the base station, and after the terminal completes the measurement and generates the antenna array measurement score, the terminal It is sent to the base station, received by the receiver lib on the base station and sent to the processor 10. If the antenna array is disposed on the base station, and the processor 10 is disposed on the terminal, the base station may transmit the measurement configuration determined by the terminal or negotiate with the terminal, and send the antenna array measurement result to the receiver lib on the terminal, and It is forwarded to the processor 10 by the receiver lib.

The following is an example in which the antenna array is a uniform linear array as an example.

Please refer to Figure 3, which is a schematic diagram of the structure of a uniform linear array. The antenna array has M array elements, the distance between the two elements is d, and the angle of the wireless signal to each element is (9, where < is the angle between the direction of arrival of the signal and the direction of the antenna array.

It should be noted that the redundant dictionary is a partial discrete Fourier transform matrix, where the discrete Fourier transform factor is a Fourier transform factor in OFDM in the multiplexed electronic device, so that the electronic device can construct redundancy offline. Dictionary, without the need to store the Fourier factor in the redundant dictionary, It is only necessary to call the stored Fourier factor of OFDM at the time of use, saving system resources.

First, the above redundant dictionary is constructed offline.

In the first step, the range of trigonometric values is evenly divided into N grids.

For example, if the function value interval [-1, 1] of the cosine function at 0° ~ 180° is evenly divided into N parts, that is, N meshes are formed, then the cosine value corresponding to the i-th mesh is 1- 2i/N, i = 0, 1, ..., Nl, the angle corresponding to the i-th grid is = arccos(l - 2 /N ).

In practical applications, if the angle of arrival is defined as the angle between the direction of arrival of the signal and the normal direction of the antenna array, the redundant dictionary described above can be represented by the sine function of the angle. Similarly, the sine function value is at -90. ~90. The upper function value interval [-1, 1] is evenly divided into N parts, that is, N meshes are formed. Then, the sine value corresponding to the i-th grid is -l + 2i/N, i = 0,1,..., Nl, and the angle corresponding to the i-th grid is θ, = arcsin(-l + 2i / N).

In a specific implementation, a person skilled in the art can set a redundancy dictionary by a cosine function or a redundant dictionary by a sine function, which is not specifically limited in the present application. In this embodiment, a redundant dictionary is constructed by a cosine function as an example.

In the second step, the direction vector of each of the N grids is calculated, and the N direction vectors form a redundancy dictionary.

Specifically, the direction vector is first obtained for the angle corresponding to each of the N grids, wherein the direction vector of the i-th grid is as shown in the formula (1).

2i 0.) = [1 _e ⁽¹ - ^2i/N ) _e j (M-1) (1 - 2i/N)]T In the above equation, the angle of the i-th grid is ^{= £} ^ ^{∞ 8 ( 1} - ^21/1 ^) , i = 0,l,...,Nl,

M«N.

Next, the calculated N direction vectors are formed into a redundancy dictionary, as shown in equation (2).

A = [a(6( ₎ ), a(6i), ..., a(3⁄4. ₁ )] ₍₂₎ In the present embodiment, N is an integer power of 2, at this time, discrete Fourier The transform factor becomes the FFT (Fast Fourier Transformation) factor. Thus, the redundant dictionary used by processor 10 for angle of arrival estimation is constructed. At this time, memory 20 stores the Fourier transform factor in OFDM and the redundant dictionary described above.

Next, the processor 10 begins to estimate the angle of arrival.

In the first step, the processor 10 can obtain a sparse signal matrix using a compressed sensing algorithm based on the antenna array measurement results and the redundancy dictionary.

For example, a pessimistic algorithm-based compressed sensing algorithm is used to input the redundant dictionary A, the array measurement result Y, that is, the received signal matrix, and the sparsity K, that is, the number of angles to be estimated, and the recovered sparse signal matrix is calculated. X, where the set of locations of non-zero elements in X is T.

Here, SOMP (Simultaneous orthogonal Match Pursuit) is taken as an example to obtain sparse recovery through continuous iteration:

Step 1: Initialize. Let the residual r=Y, T=0.

Step 2: Iterate the calculation to get the X that satisfies the condition.

a. Match the correlation, that is, use the transposed matrix of the redundant dictionary A to multiply the residual r in step 1, as shown in equation (3).

U = A'.r ( 3 ) b, position tracking, returns the subscript of the line with the largest absolute value in U, ie: t = arg _max |u _i |. c, update the location set T, that is, take the union of Τ and t, and replace the original with the result

T.

d. Take the corresponding T column in the matrix and obtain A _k , that is, A _k =AIT.

e. Estimate the value update, that is, find the pseudo inverse matrix of A _k and multiply Y by right to obtain the estimated value X.

f. Residual update, that is, using the estimated value X obtained above, update the residual according to equation (4)^

r = Y- AX (4) After obtaining the updated residual r by the above steps a~f, substituting the updated r into step a, and then performing step 1?~ sequentially iterative, wherein the number of iterations must be greater than or equal to K, such that until the number of iterations reaches the maximum number of iterations and the Frobenius norm of the r matrix is less than a threshold, such as lx 10- ⁵ , the iteration is stopped, at this time, the estimated value X obtained by step e, Restoring for sparse signals Matrix.

It should be noted that, in the above calculation process, the transposed matrix of A appearing in step a is multiplied by r, that is, the first matrix, and A is right multiplied by X in step f, that is, the second matrix, at N In the case of an integer power of 2, it can be calculated using the Fast Fourier algorithm.

For example, if the transpose matrix of A is multiplied by r, we can first expand r into an N-dimensional matrix, then perform an inverse FFT transformation, and finally perform an FFT shift to obtain U in step a. For another example, if A is multiplied by X, the FFT inverse transform can be performed on the second matrix X to obtain a third matrix, that is, an FFT inverse transform matrix of X. Then, an even term in the first M term in the third matrix is obtained. And determining an even term of the operation result of the redundancy dictionary A by the second matrix X, and determining an inverse value of the odd term in the first M term in the third matrix as an odd term of the operation result.

In the second step, after the processor 10 obtains the sparse signal matrix, the angle of arrival can be estimated based on the sparse signal matrix.

Specifically, if the position of the non-zero element is on the grid, then the non-zero element row of the sparse signal matrix obtained by the first step is subscripted as i, and its angle of arrival is ar _CC0S (l- 2i / N).

In another embodiment, in the first step, the positions of some non-zero elements in the recovered sparse signal matrix may not be on the grid, then, in order to obtain the positions of these non-grid elements, when performing the compressed sensing algorithm SBI-SVD, Sparsity Bayesian Inference-Singular Value Decomposition, Off- Grid Direction of Arrival Estimation Using Sparse Bayesian Inferenc, IEEE Transaction on Signal Processing, vol, 61, No l, Janary, 2013), or Simultaneous Orthogonal Match Pursuit-Last Squared, An alternating descent algorithm for the off-grid DOA estimation problem with sparsity constraints, EUSIPCO, 2012) to obtain a sparse signal matrix. In addition to the redundant dictionary, the first derivative matrix of the redundant dictionary is used to obtain the sparse signal matrix.

For example, referring to equations (1) and (2), elements in the first-order inverse matrix of the redundancy dictionary may be as shown in equation (5). B(jj jj) two j 2 ( ϋ ~ ^ _c j^( jj -i)d-2ii )

(5) where jj is the number of rows of the first derivative matrix, ϋ is the number of columns of the first derivative matrix, jj=0, 1 , ..., Μ-1, ii=0,l,...,Nl .

Correspondingly, in the second step, since the position i of the non-zero element of the sparse signal matrix and the compensation value Δ can be obtained by the above SBI-SVD or SOMP-LS algorithm, the angle of arrival is arccos (l-2). (i+diag(A)) /N).

Of course, there are many algorithms for restoring the sparse signal matrix in practical applications, which are not specifically limited in this application, wherein, as long as the redundant dictionary is transposed, the right multiplied by the first matrix or the redundant dictionary is right multiplied by the second matrix, The processing speed of the processor 10 is improved by using the FFT fast algorithm described above.

The estimation of the angle of arrival of the one-dimensional antenna array is achieved by the above steps, and in practical applications, the M array elements may include array elements having at least two dimensions, that is, the antenna array has at least two dimensions. The following is an example in which the antenna array is a two-dimensional array, such as an L-shaped antenna array.

Please refer to FIG. 4, which is a schematic structural diagram of an L-shaped antenna array. Assuming that the antenna array has M array elements, the processor 10 is configured to obtain antenna array measurement results of the array elements of each of the M array elements respectively; for each array element, the antenna array is used to measure the flaws and redundancy. The remainder dictionary, estimated K arrival angles; based on the K arrival angles of the array elements of each dimension, the K arrival angles of the M array elements are estimated.

Specifically, the processor 10 obtains a first dimension, such as an antenna array measurement result of the array element in the horizontal direction, and a second dimension, such as an antenna measurement result of the vertical direction array element, where the antenna array of each dimension The measurement results were obtained by the following procedure.

First, the device with the antenna array divides the antenna array into two independent one-dimensional homogenous linear arrays, and estimates the spatial angles α and β of each uniform linear array respectively, as shown in Fig. 5, and Fig. 5 is a spatial angle. Schematic diagram of the relationship with the direction angle.

Next, sparseness indicates that the antenna receives the signal and the spatial angles α, β. For example, the horizontal direction, that is, the X-axis antenna receiving signal is: Υ _χ = ΑΧ _χ + Ε _χ , and the vertical direction, that is, the antenna on the y-axis The received signal is: Y _y = AX _y + E _y , where A is the redundant dictionary, X _x , X _y is the sparse representation of the signal on the X-axis, y-axis array elements, that is, the sparse signal matrix. Y _x is a received signal matrix representing the array elements on the X-axis, Y _y is the received signal matrix of the array elements on the y-axis, and E _x , E _y are the noise matrices of the signals on the X-axis and y-axis array elements, respectively.

In the third step, we use the algorithm of compressed sensing to estimate cos a, cos β according to Y _x , A, K, and Y _y , A, K respectively. That is, the method for estimating the angle of arrival by using the one-dimensional antenna array for the antenna arrays in two dimensions, that is, using the methods in one or more of the above embodiments to obtain Χ _χ and X _{y respectively} , then, according to X _x Position of non-zero data in i _x , get coso

= l-2i _x / N, the same, according to the position of non-zero data X _y of i _y, is obtained _{cos β = l-2i y /} N. Of course, both i _x and i _y can be vectors.

In another embodiment, the same algorithm as the one-dimensional antenna array, for the case where the non-zero elements are not on the grid, the processor 10 is based on Υ _χ , Α, Β, Κ, and Y _y , A, B , K , respectively. , where Β is the first derivative matrix of Α, using the algorithm of compressed sensing, according to the position ^ and ^ of the non-zero data in x _x , obtain cos« = l-2 (i _x +diag(Ax))/N Similarly, according to the positions i _y and Ay of the non-zero data in X _y , _COSy 9 = _{l_2} (i _y +diag(Ay))/N is obtained. Of course, both i _x and i _y can be vectors.

Finally, in order to match the elements in cos α and cos β , an angle matching algorithm, such as fitting to implement an inverse trigonometric function, is used to calculate the angle of arrival.

For example, the horizontal angle / : / = arctan(cos β I cos a) .

Vertical angle

.

It is known that the electronic device in the one or more embodiments is applied to an Orthogonal Frequency Division Multiplexing (OFDM) communication system, and the electronic device includes: a processor, configured to obtain an antenna array measurement result of the M array elements and Estimating the angle of arrival of the K wireless signals based on the antenna array measurement results and the redundancy dictionary, wherein the redundant dictionary used herein is a partial discrete Fourier transform matrix, that is, The redundant dictionary has a discrete Fourier transform factor, and then a part of the complete discrete Fourier transform matrix in the orthogonal frequency division multiplexing communication system can be multiplexed without consuming additional storage space for storing the redundant dictionary. Therefore, the technical problem that the storage redundancy dictionary existing in the prior art requires a large storage space is effectively solved, and system resources are saved.

Based on the same inventive concept, the present invention also provides an apparatus for estimating an angle of arrival. The apparatus is applied to an OFDM communication system, and the apparatus can be disposed on any node of the communication system, as shown in FIG. 6, FIG. A functional block diagram of the apparatus for estimating the angle of arrival in this embodiment. The device includes: an antenna array measurement result receiving unit 61, configured to obtain antenna array measurement results of M array elements; an arrival angle estimation unit 62, configured to estimate arrival of K wireless signals based on antenna array measurement results and a redundancy dictionary An angle, where the redundancy dictionary is a partial discrete Fourier transform matrix, and M and K are positive integers.

Further, when the antenna array measurement result is obtained by the device where the device is located, the antenna array measurement result receiving unit 61 is specifically configured to: obtain the antenna array measurement result by performing the received signal measurement according to the measurement configuration, where the foregoing measurement configuration includes at least sparseness One or more of the number of the metrics, the number of snapshots, and the number of the Snapshots may include other parameters, which are not specifically limited in this application.

Further, when the antenna array measurement result is obtained by the peer device of the device where the device is located, the antenna array measurement result receiving unit 61 is specifically configured to: receive the antenna array measurement result sent by the peer device.

In an actual application, the antenna array may be a one-dimensional antenna array or a multi-dimensional antenna array. When the M array elements include array elements having at least two dimensions, the angle of arrival estimating unit 62 may include: an antenna array. The measurement result input subunit is used to respectively obtain antenna array measurement results of the array elements of each of the M array elements; the single dimension angle of arrival calculation subunit is used for the array elements of each dimension, based on the antenna array measurement result And a redundant dictionary, estimating K arrival angles; a multi-dimensional arrival angle calculation sub-unit for calculating K arrival angles of M array elements based on K arrival angles of the array elements of each dimension.

Further, the redundant dictionary is obtained by: uniformly dividing a range of trigonometric values into N meshes; calculating a direction vector of each of the N meshes, and composing a redundancy dictionary by the N direction vectors. Specifically, the direction vector is determined according to the formula (1), then the redundant dictionary is as public Formula (2) is shown.

Further, the angle-of-arrival estimation unit 62 may include: a sparse signal matrix calculation sub-unit, configured to obtain a sparse signal matrix by using a compressed sensing algorithm based on the antenna array measurement result and the redundancy dictionary, wherein the compressed sensing algorithm includes at least: The Fourier algorithm calculates the operation of the transposed right-of-first matrix of the redundant dictionary and/or the operation of the redundant dictionary by the second matrix. The first matrix and the second matrix are matrices related to the antenna array measurement results; Unit, used to estimate the angle of arrival based on the sparse signal matrix.

In another embodiment, the non-zero element is not on the grid, and the sparse signal matrix calculation sub-unit is specifically configured to: based on the antenna array measurement result, the redundancy dictionary, and the first derivative matrix of the redundancy dictionary, using a compressed sensing algorithm Obtain a sparse signal matrix. Specifically, the elements in the first derivative matrix are as shown in equation (5).

Further, the sparse signal matrix calculation subunit specifically includes: an extended subunit for expanding the first matrix into an N-dimensional matrix; and an inverse fast Fourier transform sub-unit for performing an inverse fast Fourier transform on the N-dimensional matrix And perform a fast Fourier transform shift.

Further, the sparse signal matrix calculation subunit specifically includes: an inverse fast Fourier transform subunit, configured to perform an inverse fast Fourier transform on the second matrix to obtain a third matrix; and determine a subunit for using the third matrix The even term in the first M term in the middle is determined as the even term of the operation result of the redundant dictionary by the second matrix, and the inverse value of the odd term in the first M term in the third matrix is determined as the operation result Odd items.

Various changes and specific examples in the electronic device in the foregoing embodiments are also applicable to the device in this embodiment. Through the foregoing detailed description of the electronic device, those skilled in the art can clearly understand the implementation method of the device in this embodiment. Therefore, for the sake of brevity of the manual, it will not be described in detail here.

Based on the same inventive concept, the present invention provides a method for estimating an angle of arrival, which is applied to any node in an Orthogonal Frequency Division Multiplexing (OFDM) communication system, and may be applied to a terminal or a base station, which is not specifically limited in this application. .

Please refer to Figure 7, which includes:

S101: Obtain an antenna array measurement score of M array elements; S102: Estimating the angle of arrival of the K wireless signals based on the antenna array measurement result and the redundancy dictionary, wherein the redundancy dictionary is a partial discrete Fourier transform matrix, and M and K are positive integers.

In this embodiment, S101 can have two embodiments. First, the antenna array measurement result is obtained by the node through the antenna array set by the node. Then, the S101 may be: performing the received signal measurement according to the measurement configuration to obtain the antenna array measurement result, where the measurement configuration includes at least the sparsity degree, A combination of one or more of the number of snapshots and the number of snapshot bits per snapshot. Second, the antenna array measurement result is sent by the peer device provided with the antenna array. Then, the S101 may be: receiving the antenna array measurement result sent by the peer device.

Optionally, when M array elements include array elements having at least two dimensions, S101 may be: obtaining antenna array measurement results of array elements of each of M array elements respectively; based on antenna array measurement results and redundancy The remainder dictionary, estimating the angle of arrival of the K wireless signals, specifically includes: estimating the K arrival angles based on the antenna array measurement results and the redundancy dictionary for each dimension element; K arrivals based on the array elements of each dimension Angle, calculate the K arrival angles of M elements.

Further, the redundancy dictionary in one or more of the above embodiments may be obtained by: uniformly dividing a range of trigonometric values into N grids; calculating a direction vector of each of the N grids, and The N direction vectors form a redundant dictionary. Specifically, the direction vector is as shown in the formula (1), and the corresponding redundancy dictionary is as shown in the formula (2).

Further, S102 may include: obtaining a sparse signal matrix by using a compressed sensing algorithm based on the antenna array measurement result and the redundancy dictionary, wherein the compressed sensing algorithm includes at least: using a fast Fourier algorithm to calculate a transposed right multiplication of the redundancy dictionary The operation of a matrix and/or the operation of the redundancy dictionary by the second matrix. The first matrix and the second matrix are matrices related to the antenna array measurement results; based on the sparse signal matrix, the angle of arrival is estimated.

In another embodiment, for the estimated non-zero element not on the grid, S102 may be: obtaining a sparse signal matrix by using a compressed sensing algorithm based on the antenna array measurement result, the redundancy dictionary, and the first derivative matrix of the redundancy dictionary. . Specifically, the elements of the first derivative matrix are as shown in equation (6).

For the transposed matrix of the redundant dictionary using the fast Fourier algorithm in the above one or more embodiments, the first matrix is first expanded into an N-dimensional matrix, and then the N-dimensional matrix is further advanced. The fast Fourier transform is performed and fast Fourier shift is performed.

For the operation of the fast Fourier algorithm in the above one or more embodiments, the second matrix is inversely transformed by the second dictionary, and the third matrix is obtained by first performing the inverse fast Fourier transform on the second matrix. Determining an even term of the first M term in the third matrix as an even term of the operation result of the redundancy dictionary right by the second matrix, and inverting the inverse of the odd term in the first M term in the third matrix, Determine the odd number of entries as the result of the operation.

Of course, in the actual application, there is also an algorithm for recovering the sparse signal matrix, which is not specifically limited in this application, wherein, as long as the redundancy dictionary is transposed, the right matrix is first multiplied by the first matrix or the redundant dictionary is right multiplied by the second matrix. , the above FFT fast algorithm can be used to improve the processing speed.

The various variations and specific examples in the electronic device in the foregoing embodiments are also applicable to the method for estimating the angle of arrival of the present embodiment. Through the foregoing detailed description of the electronic device, those skilled in the art can clearly understand that in this embodiment. The method of estimating the angle of arrival method is therefore not described in detail for the sake of brevity of the description.

The technical solution in the foregoing embodiment of the present application has at least the following technical effects or advantages: Since the electronic device in the one or more embodiments is applied to an Orthogonal Frequency Division Multiplexing (OFDM) communication system, the electronic device includes: a processor, configured to obtain an antenna array measurement result of the array element and estimate an angle of arrival of the plurality of wireless signals based on the antenna array measurement result and the redundancy dictionary, where the redundant dictionary used herein is a partial discrete Fourier The leaf transformation matrix, that is to say, the redundant dictionary has a discrete Fourier transform factor, then a part of the complete discrete Fourier transform matrix in the orthogonal frequency division multiplexing communication system can be multiplexed without consuming additional The storage space is used to store the redundancy dictionary. Therefore, the technical problem that the storage redundancy dictionary existing in the prior art requires a large storage space is effectively solved, and system resources are saved.

Those skilled in the art will appreciate that embodiments of the present invention can be provided as a method, system, or computer program product. Accordingly, the present invention may take the form of an entirely hardware embodiment, an entirely software embodiment, or a combination of software and hardware. Moreover, the invention can be embodied in the form of one or more computer program products embodied on a computer usable storage medium (including but not limited to disk storage, CD-ROM, optical storage, etc.) in which computer usable program code is embodied. The present invention has been described with reference to flowchart illustrations and/or block diagrams of methods, apparatus (system), and computer program products according to embodiments of the invention. It will be understood that each flow and/or block of the flowchart illustrations and/or FIG. These computer program instructions can be provided to a processor of a general purpose computer, special purpose computer, embedded processor, or other programmable data processing device to produce a machine for the execution of instructions for execution by a processor of a computer or other programmable data processing device. Means for implementing the functions specified in one or more of the flow or in a block or blocks of the flow chart.

The computer program instructions can also be stored in a computer readable memory that can direct a computer or other programmable data processing device to operate in a particular manner, such that the instructions stored in the computer readable memory produce an article of manufacture comprising the instruction device. The apparatus implements the functions specified in one or more blocks of a flow or a flow and/or block diagram of the flowchart.

These computer program instructions can also be loaded onto a computer or other programmable data processing device such that a series of operational steps are performed on a computer or other programmable device to produce computer-implemented processing for execution on a computer or other programmable device. The instructions provide steps for implementing the functions specified in one or more of the flow or in a block or blocks of a flow diagram.

It is apparent that those skilled in the art can make various modifications and variations to the invention without departing from the spirit and scope of the invention. Thus, it is intended that the present invention cover the modifications and variations of the inventions

Claims

Rights request

1. An electronic device used in an orthogonal frequency division multiplexing communication system, characterized by comprising: a processor, used to obtain antenna array measurement results of M array elements; based on the antenna array measurement results and redundancy The redundant dictionary estimates the angle of arrival of K wireless signals, where the redundant dictionary is a partial discrete Fourier transform matrix, where M and K are both positive integers.

2. The electronic device according to claim 1, wherein when the M array elements include array elements with at least two dimensions, the processor is specifically configured to: obtain the M arrays respectively. The antenna array measurement results of the array elements of each dimension in the element; For the array elements of each dimension, estimate K angles of arrival based on the antenna array measurement results and the redundant dictionary; Based on each of the dimensions K arrival angles of the array elements, estimate the K arrival angles of the M array elements.

3. The electronic device according to claim 1 or 2, characterized in that, the redundant dictionary is obtained by: dividing the range of trigonometric function values evenly into N grids; calculating among the N grids The direction vector of each grid, and the redundant dictionary is composed of N direction vectors.

4. The electronic device according to claim 3, characterized in that the direction vector is determined according to the following formula:

_Ά θ ) = [1 e ^j " ⁽¹ " ^{2i )} _e (M- 1)(1- 2i / N) ]T where, is the angle of the i-th grid, ^ = arccos(l-2i / N),i = 0,..., N - l , M « N , N is an integer power of 2.

5. The electronic device according to any one of claims 1 to 4, characterized in that the processor is specifically configured to: use the compressed sensing algorithm based on the antenna array measurement results and the redundant dictionary. Obtain a sparse signal matrix, wherein the compressed sensing algorithm at least includes: using the fast Fourier algorithm to calculate the transposed right multiplication of the first matrix of the redundant dictionary and/or the operation of right multiplication of the redundant dictionary by the second matrix. The first matrix and the second matrix are matrices related to the antenna array measurement results; based on the sparse signal matrix, the angle of arrival is estimated.

6. The electronic device according to claim 5, wherein the processor is specifically In: based on the antenna array measurement result, the redundant dictionary, and the first-order derivative matrix of the redundant dictionary, using the compressed sensing algorithm to obtain a sparse signal matrix.

7. The electronic device according to claim 6, wherein the elements of the first-order derivative matrix are determined according to the following formula:

Among them, jj is the number of rows of the first-order derivative matrix, ϋ is the number of columns of the first-order derivative matrix, jj=0,l,...,M-l, ii=0,l,...,N-l„

8. The electronic device according to any one of claims 5 to 7, characterized in that the processor is specifically used to: expand the first matrix into an N-dimensional matrix; perform fast processing on the N-dimensional matrix. Inverse Fourier transform and fast Fourier shift.

9. The electronic device according to any one of claims 5 to 7, wherein the processor is specifically configured to: perform an inverse fast Fourier transform on the second matrix to obtain a third matrix; The even-numbered items in the first M items in the third matrix are determined as the even-numbered items of the operation result of the second matrix right multiplied by the redundant dictionary, and the even-numbered items in the first M items in the third matrix are The inverted value of the odd term is determined as the odd term of the operation result.

10. The electronic device according to any one of claims 1 to 9, characterized in that, the electronic device further includes: an antenna array, used to perform received signal measurement according to the measurement configuration to obtain the antenna array measurement result, wherein, The measurement configuration at least includes a combination of one or more of sparsity, number of snapshots, and bit number of each snapshot.

11. The electronic device according to any one of claims 1 to 9, characterized in that the electronic device further includes: a receiver, configured to receive the antenna array measurement results, and transmit the antenna array measurement results to sent to the processor.

12. The electronic device according to claims 1 to 11, characterized in that the electronic device is specifically a terminal or a base station.

13. A device for estimating the angle of arrival, used in orthogonal frequency division multiplexing communication systems, characterized by: to, including:

The antenna array measurement result receiving unit is used to obtain the antenna array measurement results of M array elements; the arrival angle estimation unit is used to estimate the arrival angle of K wireless signals based on the antenna array measurement results and the redundant dictionary, where, The redundant dictionary is a partial discrete Fourier transform matrix, M and

K is a positive integer.

14. The device according to claim 13, wherein when the M array elements include array elements with at least two dimensions, the angle of arrival estimation unit specifically includes:

The antenna array measurement result input subunit is used to obtain the antenna array measurement results of the array elements of each dimension among the M array elements;

A single-dimensional angle of arrival calculation subunit, used for estimating K angles of arrival for the array elements of each dimension based on the antenna array measurement results and the redundant dictionary;

A multi-dimensional arrival angle calculation subunit is used to calculate the K arrival angles of the M array elements based on the K arrival angles of the array elements in each dimension.

15. The device according to claim 13 or 14, characterized in that the redundant dictionary is obtained by: dividing the range of trigonometric function values evenly into N grids; calculating each of the N grids The direction vector of a grid, and the redundant dictionary is composed of N number of the direction vectors.

16. The device according to claim 15, characterized in that the direction vector is determined according to the following formula:

^ = [1 _e i^(l-2i) _e j^(Ml)(l-2i/ N) -|T where, is the angle of the i-th grid, 6»i = arccos(l— 2i / N), i = 0,..., N— 1, M « N, N is an integer power of 2.

17. The device according to any one of claims 13 to 16, characterized in that the angle of arrival estimation unit specifically includes:

A sparse signal matrix calculation subunit, configured to use the compressed sensing algorithm to obtain a sparse signal matrix based on the antenna array measurement results and the redundant dictionary, wherein the compressed sensing algorithm at least includes: using fast Fourier Algorithm calculates the operational sum of the transposed right multiplication of the first matrix of the redundant dictionary/ Or the operation of right multiplying the redundant dictionary by the second matrix. The first matrix and the second matrix are matrices related to the measurement results of the antenna array;

An estimation subunit, configured to estimate the angle of arrival based on the sparse signal matrix.

18. The device according to claim 17, wherein the sparse signal matrix calculation subunit is specifically configured to: based on the antenna array measurement results, the redundant dictionary and the first order of the redundant dictionary Derivative matrix, using the compressed sensing algorithm to obtain a sparse signal matrix.

19. The device according to claim 18, wherein the elements in the first-order derivative matrix are determined according to the following formula:

B(jj jj) = j ^2;Γ (ϋ — l) _c (jj- ιχι— 2ίί/Ν) where, jj is the row subscript of the first-order derivative matrix, ii is the column of the first-order derivative matrix Subscript, jj=0,l,...,Ml, ϋ=0, 1, · · ·, Ν-1.

20. The device according to any one of claims 17 to 19, characterized in that the sparse signal matrix calculation subunit specifically includes:

Expansion subunit, used to expand the first matrix into an N-dimensional matrix;

The inverse fast Fourier transform subunit is used to perform inverse fast Fourier transform on the N-dimensional matrix and perform fast Fourier transform shift.

21. The device according to any one of claims 17 to 19, characterized in that the sparse signal matrix calculation subunit specifically includes:

An inverse fast Fourier transform subunit, used to perform an inverse fast Fourier transform on the second matrix to obtain the third matrix;

Determining subunit, used to determine the even-numbered items in the first M items in the third matrix as the even-numbered items of the operation result of the redundant dictionary right multiplied by the second matrix, and convert the third matrix The inverted value of the odd term among the first M terms in is determined as the odd term of the operation result.

22. The device according to any one of claims 13 to 21, characterized in that the antenna array measurement result receiving unit is specifically used to: measure received signals according to the measurement configuration to obtain the antenna array Column measurement results, wherein the measurement configuration at least includes a combination of one or more of sparsity, the number of snapshots, and the number of bits of each snapshot.

23. The device according to any one of claims 13 to 21, characterized in that the antenna array measurement result receiving unit is specifically used to: receive the antenna array measurement result sent by the peer device.

24. A method for estimating the angle of arrival, applied in orthogonal frequency division multiplexing communication systems, which is characterized by:

Obtain the antenna array measurement results of M array elements;

Based on the antenna array measurement results and the redundant dictionary, the arrival angles of K wireless signals are estimated, where the redundant dictionary is a partial discrete Fourier transform matrix, and M and K are positive integers.

25. The method of claim 24, wherein when the M array elements include array elements with at least two dimensions, obtaining the antenna array measurement results of the M array elements is specifically: respectively Obtain the antenna array measurement results of the array elements of each dimension among the M array elements;

The method of estimating the angle of arrival of K wireless signals based on the antenna array measurement results and the redundant dictionary specifically includes:

For the array elements of each dimension, estimate K angles of arrival based on the antenna array measurement results and the redundant dictionary;

Based on the K arrival angles of the array elements in each dimension, calculate the K arrival angles of the M array elements.

26. The method according to claim 24 or 25, characterized in that the redundant dictionary is obtained in the following way:

Divide the range of trigonometric function values evenly into N grids;

The direction vector of each grid in the N grids is calculated, and the redundant dictionary is composed of the N direction vectors.

27. The method of claim 26, wherein the direction vector is determined according to the following formula:

α Ί Λ _ Π XI— 2i / N) ^

Among them, is the angle of the i-th grid, ^ = arccos(l-2i / N), i = 0,..., N - l, M « N, N is an integer power of 2.

28. The method according to any one of claims 24 to 29, wherein estimating the angle of arrival of K wireless signals based on the antenna array measurement results and the redundant dictionary specifically includes:

Based on the antenna array measurement results and the redundant dictionary, the compressed sensing algorithm is used to obtain a sparse signal matrix, wherein the compressed sensing algorithm at least includes: using the fast Fourier algorithm to calculate the transposed right of the redundant dictionary The operation of multiplying the first matrix and/or the operation of right-multiplying the redundant dictionary by the second matrix. The first matrix and the second matrix are matrices related to the measurement results of the antenna array;

Based on the sparse signal matrix, the angle of arrival is estimated.

29. The method of claim 28, wherein the compressed sensing algorithm is used to obtain a sparse signal matrix based on the antenna array measurement results and the redundant dictionary, specifically: based on the antenna array The measurement results, the redundant dictionary and the first-order derivative matrix of the redundant dictionary are used to obtain a sparse signal matrix using the compressed sensing algorithm.

30. The method of claim 29, wherein the elements of the first-order derivative matrix are determined according to the following formula:

Among them, jj is the number of rows of the first-order derivative matrix, ii is the number of columns of the first-order derivative matrix, jj=0,l,...,M-l, ii=0,l,...,N-l„

31. The method according to any one of claims 28 to 30, characterized in that the fast Fourier algorithm is used to right-multiply the first matrix by the transpose matrix of the redundant dictionary, specifically including:

Expand the first matrix into an N-dimensional matrix;

The N-dimensional matrix is subjected to inverse fast Fourier transform and fast Fourier shift.

32. The method according to any one of claims 28 to 30, characterized in that the fast Fourier algorithm is used to right-multiply the second matrix with the redundant dictionary, specifically including:

Perform an inverse fast Fourier transform on the second matrix to obtain a third matrix; Determine the even-numbered items in the first M items in the third matrix as the even-numbered items of the operation result of the redundant dictionary right multiplied by the second matrix, and add the first M items in the third matrix to The inverted value of the odd term is determined as the odd term of the operation result.

33. The method according to any one of claims 24 to 32, characterized in that, obtaining the array measurement result specifically includes: performing received signal measurement according to the measurement configuration to obtain the antenna array measurement result, wherein, the measurement The configuration includes at least a combination of one or more of sparsity, number of snapshots, and number of bits per snapshot.

34. The method according to any one of claims 24 to 32, wherein the obtaining the array measurement result specifically includes: receiving the antenna array measurement result sent by the peer device.