Signal direction of arrival evaluation method and device, electronic equipment, storage medium and computer program product

Abstract

The invention relates to the technical field of communication, and provides a signal direction of arrival evaluation method and device, electronic equipment, a storage medium and a computer program product, and the method comprises the steps: receiving an uplink signal based on a uniform circular array, and determining downlink control information based on the uplink signal; determining a first correlation matrix and the number of information sources based on the downlink control information and the uplink signal; performing array manifold calculation based on the estimated elevation angle and the estimated azimuth angle to obtain a second correlation matrix set; determining correlation values corresponding to a pre-estimated elevation angle and a pre-estimated azimuth angle according to the first correlation matrix and the second correlation matrix set; and carrying out peak value search according to the number of the information sources and the correlation value to obtain an elevation angle and an azimuth angle of the uplink signal. According to the invention, the evaluation efficiency of the DOA of the LTE uplink signal can be improved by reducing the calculation amount.

Description

Technical Field

[0001] The present application relates to the field of communication technology, and in particular to a signal arrival direction evaluation method, device, electronic device, storage medium and computer program product. Background Art

[0002] The Multiple Signal Classification (MUSIC) algorithm is a landmark algorithm for spatial spectrum estimation, and its emergence has achieved a huge leap in spatial spectrum estimation technology. When using the MUSIC algorithm to calculate the Direction of Arrival (DOA) of the Long Term Evolution (LTE) uplink signal, the array antenna receives the signal data to generate a covariance matrix, decomposes the covariance matrix to obtain the signal subspace and noise subspace, and obtains the angle information of the incoming signal through the orthogonal relationship between the signal direction vector and the noise subspace.

[0003] However, the MUSIC algorithm is currently used to calculate the DOA of the LTE uplink signal. When the azimuth and elevation are calculated simultaneously, the amount of calculation of the MUSIC algorithm is very large, resulting in low efficiency in evaluating the DOA of the LTE uplink signal. Summary of the invention

[0004] The present application aims to solve at least one of the technical problems existing in the related art. To this end, the present application proposes a signal arrival direction evaluation method, device, electronic device, storage medium and computer program product to solve the problem of very large amount of calculation when using the MUSIC algorithm to calculate the DOA of the LTE uplink signal, so as to improve the evaluation efficiency of the DOA of the LTE uplink signal.

[0005] A signal direction of arrival evaluation method according to an embodiment of the first aspect of the present application includes: receiving an uplink signal based on a uniform circular array, and determining downlink control information based on the uplink signal; Determine a first correlation matrix and the number of information sources based on the downlink control information and the uplink signal; Perform array manifold calculation based on the estimated elevation angle and the estimated azimuth angle to obtain a second correlation matrix set; Determining correlation values ​​corresponding to an estimated elevation angle and an estimated azimuth angle according to the first correlation matrix and the second correlation matrix set; A peak search is performed according to the number of information sources and the correlation value to obtain the elevation angle and azimuth angle of the uplink signal.

[0006] According to an embodiment of the present application, performing array manifold calculation based on the estimated elevation angle and the estimated azimuth angle to obtain a second correlation matrix set includes: Obtain a pending elevation angle from the estimated elevation angle; Determine the correlation between the elevation angle to be processed and each azimuth angle in the estimated azimuth angle according to the number of array elements of the uniform circular array and the array element radius of the uniform circular array in combination with the array manifold, and form a second correlation matrix according to the correlation degrees; An unprocessed elevation angle is obtained from the estimated elevation angle as a new elevation angle to be processed, and the process returns to execute the step of determining the correlation between the elevation angle to be processed and each azimuth angle in the estimated azimuth angle according to the number of array elements of the uniform circular array and the array element radius of the uniform circular array in combination with the array manifold, and forming a second correlation matrix from each correlation degree, until all elevation angles in the estimated elevation angle are processed and a second correlation matrix set is formed from each second correlation matrix.

[0007] According to an embodiment of the present application, determining the correlation value corresponding to the estimated elevation angle and the estimated azimuth angle according to the first correlation matrix and the second correlation matrix set includes: Perform convolution operations on the first correlation matrix and each second correlation matrix in the second correlation matrix set to obtain a corresponding number of convolution data; For each convolution data, extraction is performed according to a preset interval to obtain the correlation values ​​of all azimuth angles in the estimated azimuth angle at each elevation angle of the estimated elevation angle.

[0008] According to an embodiment of the present application, performing array manifold calculation based on the estimated elevation angle and the estimated azimuth angle to obtain a second correlation matrix set further includes: Obtain a pending elevation angle from the estimated elevation angle; Evenly divide each azimuth in the estimated azimuth into preset groups; Determine the correlation between the elevation angle to be processed and each azimuth angle in each group of azimuth angles of the estimated azimuth angles according to the number of array elements of the uniform circular array and the array element radius of the uniform circular array in combination with the array manifold, and form a second correlation matrix based on the correlation degrees of each group; An unprocessed elevation angle is obtained from the estimated elevation angle as a new elevation angle to be processed, and the process returns to execute the step of determining the correlation between the elevation angle to be processed and each azimuth angle in each group of azimuth angles of the estimated azimuth angles according to the number of array elements of the uniform circular array and the array element radius of the uniform circular array in combination with the array manifold, and forming a second correlation matrix from each group of correlation degrees until all elevation angles in the estimated elevation angles are processed and a second correlation matrix set is formed from each second correlation matrix.

[0009] According to an embodiment of the present application, determining the correlation values ​​corresponding to the estimated elevation angle and the estimated azimuth angle according to the first correlation matrix and the second correlation matrix set further includes: Determining an intermediate value based on the number of array elements and the number of azimuth angles in each group of azimuth angles; Perform a fast Fourier operation based on the intermediate value and the first correlation matrix to obtain a first matrix; Performing a fast Fourier operation based on the intermediate value and each group of correlation levels in each second correlation matrix of the second correlation matrix set to obtain a corresponding number of second matrices; Performing inverse fast Fourier transform on each second matrix based on the first matrix to obtain a corresponding number of third matrices; For each third matrix, extraction is performed at preset intervals to obtain correlation values ​​of all azimuth angles in each group of azimuth angles of the estimated azimuth angle at each elevation angle of the estimated elevation angle.

[0010] According to an embodiment of the present application, determining a first correlation matrix and a number of information sources based on the downlink control information and the uplink signal includes: Performing frequency shifting on the uplink signal based on the downlink control information to obtain a frequency shifted signal; filtering the frequency shifted signal to obtain a filtered signal; Extracting information from the filtered signal to obtain extracted information; determining a fourth matrix based on the extracted information; Performing eigenvalue decomposition on the fourth matrix to obtain eigenvalues ​​and eigenvectors; Determining the number of information sources based on the characteristic value; Determine a noise subspace according to the number of information sources and the eigenvector; A first correlation matrix is ​​constructed based on the noise subspace.

[0011] A signal direction of arrival evaluation device according to an embodiment of the second aspect of the present application includes: A first determination module, configured to receive an uplink signal based on a uniform circular array, and determine downlink control information based on the uplink signal; A second determination module, configured to determine a first correlation matrix and a number of information sources based on the downlink control information and the uplink signal; A calculation module, used for performing array manifold calculation based on the estimated elevation angle and the estimated azimuth angle to obtain a second correlation matrix set; A third determination module, configured to determine correlation values ​​corresponding to an estimated elevation angle and an estimated azimuth angle according to the first correlation matrix and the second correlation matrix set; The search module is used to perform peak search according to the number of information sources and the correlation value to obtain the elevation angle and azimuth angle of the uplink signal.

[0012] According to an electronic device of an embodiment of the third aspect of the present application, the electronic device includes a memory, a processor, and a computer program stored in the memory and executable on the processor. When the processor executes the computer program, the signal arrival direction evaluation method described above is implemented.

[0013] According to the storage medium of the fourth aspect embodiment of the present application, the storage medium is a non-transitory computer-readable storage medium, on which a computer program is stored. When the computer program is executed by a processor, it implements any of the signal arrival direction evaluation methods described above.

[0014] A computer program product according to an embodiment of the fifth aspect of the present application includes a computer program, which, when executed by a processor, implements any of the signal arrival direction assessment methods described above.

[0015] The above one or more technical solutions in the embodiments of the present application have at least the following technical effects: When an uplink signal is received based on a uniform circular array, downlink control information is determined based on the uplink signal, so that a first correlation matrix and the number of information sources can be determined based on the downlink control information and the uplink signal; at the same time, array manifold calculation is performed based on the estimated elevation angle and the estimated azimuth angle to obtain a second correlation matrix set; and then, correlation values ​​corresponding to the estimated elevation angle and the estimated azimuth angle can be determined based on the first correlation matrix and the second correlation matrix set; and peak search is further performed based on the number of information sources and the correlation value to obtain the elevation angle and azimuth angle of the uplink signal. By directly using known downlink control information to construct the first correlation matrix, complex autocorrelation calculations on the entire uplink signal are avoided, thereby reducing the amount of calculation; at the same time, for a uniform circular array, when its radius and incident frequency are determined, the corresponding array manifold has been determined, so the second correlation matrix set for array manifold calculation can be performed in advance based on the estimated elevation angle and the estimated azimuth angle and saved for use, and then when the correlation values ​​corresponding to the estimated elevation angle and the estimated azimuth angle are determined based on the first correlation matrix and the second correlation matrix set, the amount of calculation can be effectively reduced, and it is convenient to quickly perform peak search based on the number of signal sources and the correlation value to obtain the elevation angle and azimuth angle of the uplink signal, thereby improving the evaluation efficiency of the DOA of the LTE uplink signal.

[0016] Additional aspects and advantages of the present application will be given in part in the description below, and in part will become apparent from the description below, or will be learned through the practice of the present application. BRIEF DESCRIPTION OF THE DRAWINGS

[0017] In order to more clearly illustrate the technical solutions in the present invention or the prior art, the following briefly introduces the drawings required for use in the embodiments or the description of the prior art. Obviously, the drawings described below are some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0018] Figure 1 It is a flowchart of a signal arrival direction evaluation method provided in an embodiment of the present application.

[0019] Figure 2 It is a schematic diagram of the correlation matrix determination process of the signal arrival direction evaluation method provided in an embodiment of the present application.

[0020] Figure 3 It is a flowchart of using convolution to calculate the correlation values ​​of all azimuth angles at one elevation angle in the signal arrival direction evaluation method provided in an embodiment of the present application.

[0021] Figure 4 It is a flow chart of using FFT to calculate the correlation values ​​of all azimuth angles at one elevation angle in the signal arrival direction evaluation method provided in an embodiment of the present application.

[0022] Figure 5 It is a structural schematic diagram of the electronic device provided by this application. DETAILED DESCRIPTION

[0023] The following is a further detailed description of the implementation of the present application in conjunction with the accompanying drawings and examples. The following examples are used to illustrate the present application but cannot be used to limit the scope of the present application.

[0024] In the description of the embodiments of the present application, it should be noted that the terms "center", "longitudinal", "lateral", "up", "down", "front", "back", "left", "right", "vertical", "horizontal", "top", "bottom", "inside", "outside" and the like indicate positions or positional relationships based on the positions or positional relationships shown in the accompanying drawings, which are only for the convenience of describing the embodiments of the present application and simplifying the description, and do not indicate or imply that the device or element referred to must have a specific orientation, be constructed and operated in a specific orientation, and therefore cannot be understood as limiting the embodiments of the present application. In addition, the terms "first", "second", and "third" are used for descriptive purposes only and cannot be understood as indicating or implying relative importance.

[0025] In the description of the embodiments of the present application, it should be noted that, unless otherwise clearly specified and limited, the terms "connected" and "connection" should be understood in a broad sense, for example, it can be a fixed connection, a detachable connection, or an integral connection; it can be a mechanical connection or an electrical connection; it can be directly connected or indirectly connected through an intermediate medium. For ordinary technicians in this field, the specific meanings of the above terms in the embodiments of the present application can be understood according to specific circumstances.

[0026] In the embodiments of the present application, unless otherwise clearly specified and limited, a first feature being "above" or "below" a second feature may mean that the first and second features are in direct contact, or the first and second features are in indirect contact through an intermediate medium. Moreover, a first feature being "above", "above" or "above" a second feature may mean that the first feature is directly above or obliquely above the second feature, or simply means that the first feature is higher in level than the second feature. A first feature being "below", "below" or "below" a second feature may mean that the first feature is directly below or obliquely below the second feature, or simply means that the first feature is lower in level than the second feature.

[0027] In the description of this specification, the description with reference to the terms "one embodiment", "some embodiments", "example", "specific example", or "some examples" etc. means that the specific features, structures, materials or characteristics described in conjunction with the embodiment or example are included in at least one embodiment or example of the embodiments of the present application. In this specification, the schematic representations of the above terms do not necessarily refer to the same embodiment or example. Moreover, the specific features, structures, materials or characteristics described may be combined in any one or more embodiments or examples in a suitable manner. In addition, those skilled in the art may combine and combine the different embodiments or examples described in this specification and the features of the different embodiments or examples, without contradiction.

[0028] It should be noted that the current MUSIC algorithm is used to calculate the DOA of the LTE uplink signal. In the process of determining the data correlation matrix, if the user frequency domain resource allocation is small, the accuracy of the frequency domain calculation is reduced; and it is necessary to first set other user data to zero in the frequency domain and then transform it to the time domain, which will increase the amount of additional calculation. At the same time, the MUSIC algorithm has a large amount of calculation when searching for spectrum peaks, and it is not convenient for hardware parallel implementation.

[0029] Based on this, the present application proposes a signal arrival direction assessment method, device, electronic device, storage medium and computer program product.

[0030] Figure 1 is a flow chart of a signal arrival direction evaluation method provided in an embodiment of the present application, such as Figure 1 As shown, the signal arrival direction evaluation method includes: Step 110: Receive an uplink signal based on a uniform circular array, and determine downlink control information based on the uplink signal.

[0031] Step 120: Determine a first correlation matrix and the number of information sources based on the downlink control information and the uplink signal.

[0032] Step 130, performing array manifold calculation based on the estimated elevation angle and the estimated azimuth angle to obtain a second correlation matrix set.

[0033] Step 140: Determine correlation values ​​corresponding to the estimated elevation angle and the estimated azimuth angle according to the first correlation matrix and the second correlation matrix set.

[0034] Step 150, performing peak search according to the number of information sources and the correlation value to obtain the elevation angle and azimuth angle of the uplink signal.

[0035] It should be noted that the executor of the signal arrival direction evaluation method provided in the embodiment of the present application can be a server, a computer device, etc., such as a mobile phone, a tablet computer, a laptop computer, a PDA, a vehicle-mounted electronic device, a wearable device, an ultra-mobile personal computer (UMPC), a netbook or a personal digital assistant (PDA), etc.

[0036] The server or computer device of the present application may be provided with or connected to a signal arrival direction evaluation device, thereby controlling the signal arrival direction evaluation device to execute the signal arrival direction evaluation method of the present application. The server or computer device of the present application may be connected to or deployed with an LTE system, and may obtain data in the LTE system.

[0037] In the present application, a uniform circular array may be used to receive an uplink signal sent by a user equipment. Specifically, the sampling rate of the LTE system may be, for example, 30.72 MHz, and the corresponding Fast Fourier Transform (FFT) point number is 2048.

[0038] It can be understood that the number of array elements N, the array element radius r and the signal incident frequency f0 of the uniform circular array are all known.

[0039] Furthermore, the present application can modulate and demodulate the uplink signal to extract valid symbols and information. According to the LTE system standard, the format information of the downlink control information (DCI) is parsed and extracted to obtain the user's DCI0. DCI0 usually contains information about modulation mode, resource block allocation, power control, etc.

[0040] Furthermore, the present application can obtain the frequency domain resource configuration corresponding to the user according to the user DCI0, including the frequency domain position rbStart and the number of allocated RBs rbNum.

[0041] Furthermore, the present application can perform frequency shifting on the received uplink signal according to the frequency domain position, determine the filter coefficient according to the number of allocated RBs, and further filter the frequency shifted uplink signal according to the filter coefficient.

[0042] Furthermore, the filtered signal is extracted to obtain extraction information.

[0043] According to the extracted information, a correlation matrix can be determined as the first correlation matrix, and the number K of information sources can be determined.

[0044] Furthermore, the present application can obtain an elevation angle range consisting of multiple elevation angles and an azimuth angle range consisting of multiple azimuth angles in advance according to actual scene evaluation, thereby obtaining an estimated elevation angle and an estimated azimuth angle.

[0045] Furthermore, the present application can obtain the correlation matrix of the estimated azimuth angle corresponding to all azimuth angles at each elevation angle of the estimated elevation angle by performing array manifold calculation as the second correlation matrix, and form a second correlation matrix set from each second correlation matrix; Furthermore, the present application can calculate the convolution of the first correlation matrix C and each second correlation matrix in the second correlation matrix set to obtain the convolved data data, and extract from each data data according to a preset interval to obtain the correlation value of the noise matrix corresponding to all azimuth angles at an elevation angle.

[0046] Then, the reciprocals corresponding to the respective correlation values ​​can be determined, and peak searches are performed on the reciprocals corresponding to the respective correlation values ​​according to the number of information sources. After the search is completed, the elevation angle and azimuth angle of the uplink signal are obtained.

[0047] It should be noted that the present application can also group the azimuth angles in the estimated azimuth angles, and then perform array manifold calculations to obtain the correlation matrix of all azimuth angles corresponding to each group of azimuth angles in the estimated azimuth angles at each elevation angle of the estimated elevation angle as the second correlation matrix, and form a second correlation matrix set from each second correlation matrix.

[0048] Furthermore, the present application may also determine an intermediate value based on the number of array elements and the number of azimuth angles in each group of azimuth angles, and then perform a fast Fourier operation based on the intermediate value and the first correlation matrix to obtain a matrix as the first matrix.

[0049] Furthermore, a fast Fourier operation is performed based on the intermediate value and each group of correlation levels in each second correlation matrix of the second correlation matrix set to obtain a corresponding number of matrices which are respectively used as second matrices.

[0050] Furthermore, based on the first matrix, inverse fast Fourier transform is performed on each second matrix to obtain a corresponding number of matrices which are respectively used as third matrices.

[0051] Furthermore, for each third matrix, extraction is performed at preset intervals to obtain correlation values ​​of all azimuth angles in each group of azimuth angles of the estimated azimuth angle at each elevation angle of the estimated elevation angle.

[0052] Then, the reciprocals corresponding to the respective correlation values ​​can be determined, and peak searches are performed on the reciprocals corresponding to the respective correlation values ​​according to the number of information sources. After the search is completed, the elevation angle and azimuth angle of the uplink signal are obtained.

[0053] Specifically, when performing peak search on the reciprocals corresponding to the respective correlation values ​​according to the number of information sources, for example, a sorting algorithm or a maximum value heap method may be used to find the maximum value among the reciprocals corresponding to the respective correlation values.

[0054] Record the index of the maximum value to obtain the corresponding elevation and azimuth angles.

[0055] According to the known index, the elevation angle and azimuth angle corresponding to the maximum value are extracted as the elevation angle and azimuth angle of the uplink signal.

[0056] According to the signal arrival direction evaluation method of the embodiment of the present application, when an uplink signal is received based on a uniform circular array, downlink control information is determined based on the uplink signal, so that a first correlation matrix and the number of information sources can be determined based on the downlink control information and the uplink signal; at the same time, array manifold calculation is performed based on the estimated elevation angle and the estimated azimuth angle to obtain a second correlation matrix set; and then, correlation values ​​corresponding to the estimated elevation angle and the estimated azimuth angle can be determined based on the first correlation matrix and the second correlation matrix set; and peak search is further performed based on the number of information sources and the correlation value to obtain the elevation angle and azimuth angle of the uplink signal. By directly using known downlink control information to construct the first correlation matrix, complex autocorrelation calculations on the entire uplink signal are avoided, thereby reducing the amount of calculation; at the same time, for a uniform circular array, when its radius and incident frequency are determined, the corresponding array manifold has been determined, so the second correlation matrix set for array manifold calculation can be performed in advance based on the estimated elevation angle and the estimated azimuth angle and saved for use, and then when the correlation values ​​corresponding to the estimated elevation angle and the estimated azimuth angle are determined based on the first correlation matrix and the second correlation matrix set, the amount of calculation can be effectively reduced, and it is convenient to quickly perform peak search based on the number of signal sources and the correlation value to obtain the elevation angle and azimuth angle of the uplink signal, thereby improving the evaluation efficiency of the DOA of the LTE uplink signal.

[0057] Based on the above embodiment, step 120 may include: Performing frequency shifting on the uplink signal based on the downlink control information to obtain a frequency shifted signal; Filtering the frequency shifted signal to obtain a filtered signal; Extracting information from the filtered signal to obtain extracted information; determining a fourth matrix based on the extracted information; Perform eigenvalue decomposition on the fourth matrix to obtain eigenvalues ​​and eigenvectors; Determine the number of information sources based on the eigenvalues; Determine the noise subspace according to the number of information sources and the eigenvector; A first correlation matrix is ​​constructed based on the noise subspace.

[0058] Specifically, the present application can determine the deviation between the RB allocated to the user and the center frequency of the LTE system according to the frequency domain position rbStart value, and then perform frequency shifting according to the following formula: ; Wherein, rxSig in the formula represents the original received data, i.e., the uplink signal in this application; len represents the subframe data length corresponding to the 30.72M sampling rate; Represents the data after frequency shifting; n represents the antenna number, ranging from 1 to N, where N is the total number of allocated antennas, i.e. the number of array elements; j is the imaginary unit; NFFT is the number of FFT points.

[0059] Furthermore, the present application can determine the low-pass filter coefficient coff according to the number of allocated RBs rbNum, where the filter length is len2, and then the frequency-shifted data is calculated by the following formula: Filter and extract to obtain the extracted information : temp1=conv(coff, (n,:)); temp2=temp1(floor(len2 / 2)+[1:len]); (n,:)=temp2(1:M:len); Among them, conv represents convolution calculation; floor represents rounding down; M represents the decimation multiple.

[0060] Furthermore, using the extracted information Compute the correlation matrix as the fourth matrix: ; Among them, RR represents the correlation matrix with dimension N*N; H represents the conjugate transpose.

[0061] Furthermore, RR is subjected to eigenvalue decomposition to obtain the corresponding eigenvalue D and eigenvector EV.

[0062] Furthermore, the eigenvalues ​​D are sorted, the number of information sources K is determined according to the sorting result, and the noise subspace G is further determined according to the number of information sources K and the eigenvector EV.

[0063] According to the noise subspace G, a correlation matrix is ​​constructed as the first correlation matrix according to the following formula : ; ; Among them, H represents conjugate transpose and T represents transpose.

[0064] The present application utilizes a fast algorithm for frequency shifting and filtering, which can effectively reduce computational complexity and help improve the efficiency of DOA evaluation of LTE uplink signals.

[0065] Based on the above embodiment, step 130 may include: Obtain a pending elevation angle from the estimated elevation angle; According to the number of array elements of the uniform circular array and the array element radius of the uniform circular array, the correlation degree between the elevation angle to be processed and each azimuth angle in the estimated azimuth angle is determined in combination with the array manifold, and a second correlation matrix is ​​formed from each correlation degree; The unprocessed elevation angle is obtained from the estimated elevation angle as a new elevation angle to be processed, and the step of determining the correlation between the elevation angle to be processed and each azimuth angle in the estimated azimuth angle according to the number of array elements of the uniform circular array and the array element radius of the uniform circular array in combination with the array manifold, and forming a second correlation matrix from each correlation degree, until all elevation angles in the estimated elevation angle are processed and a second correlation matrix set is formed from each second correlation matrix.

[0066] Accordingly, based on the above embodiment, step 140 may include: Perform convolution operations on the first correlation matrix and each second correlation matrix in the second correlation matrix set to obtain a corresponding number of convolution data; For each convolution data, extraction is performed according to a preset interval to obtain the correlation values ​​of all azimuth angles in the estimated azimuth angle at each elevation angle of the estimated elevation angle.

[0067] Specifically, this application selects an elevation angle from the estimated elevation angles , according to the number of elements of the uniform circular array and the element radius of the uniform circular array, the relevant matrix C is calculated in combination with the following array manifold: ; in, Indicates the selected elevation angle The correlation degree between the kth azimuth and the estimated azimuth, represents the kth azimuth, Indicates the wavelength corresponding to the signal frequency; ; in, Indicates the selected elevation angle The expansion matrix formed by the correlation degree between the k-th azimuth angle; Select a new azimuth from the estimated azimuths and repeat the above process. After executing the corresponding number of times, the correlation degree of all azimuths under the elevation angle is obtained, and the second correlation matrix C is formed by the correlation degrees under the elevation angle; C= ; Among them, 360 represents the number of azimuth angles. For a uniform circular array, when the radius and incident frequency are determined, the corresponding array manifold has been determined, that is, the C part in the formula is known and can be calculated and saved in advance for use.

[0068] A new elevation angle is selected from the estimated elevation angles and the above process is repeated. After executing the corresponding number of times, a corresponding number of second correlation matrices are obtained, and a second correlation matrix set is formed by each second correlation matrix.

[0069] Further, for each second correlation matrix in the second correlation matrix set, the present application can calculate the second correlation matrix C and the first correlation matrix The convolution is performed to obtain the convolved data data, and the data data is extracted at interval N1 to obtain the correlation value convResult of the noise matrix corresponding to all azimuth angles at an elevation angle. Specifically, there are: N1=N*N; ,C); ; Among them, conv represents convolution calculation.

[0070] The above steps are executed repeatedly to obtain the correlation values ​​corresponding to all elevation angles and all azimuth angles in the estimated azimuth angles: .

[0071] The present application provides a new correlation matrix calculation and a new peak search method, which are convenient for hardware implementation and parallel processing, and help to improve the evaluation efficiency of the DOA of the LTE uplink signal.

[0072] Based on the above embodiment, step 130 may further include: Obtain a pending elevation angle from the estimated elevation angle; Evenly divide each azimuth in the estimated azimuth into preset groups; According to the number of array elements of the uniform circular array and the array element radius of the uniform circular array, the correlation degree between the elevation angle to be processed and each azimuth angle in each group of the estimated azimuth angles is determined in combination with the array manifold, and a second correlation matrix is ​​formed by the correlation degrees of each group; An unprocessed elevation angle is obtained from the estimated elevation angle as a new elevation angle to be processed, and the step of determining the correlation between the elevation angle to be processed and each azimuth angle in each group of azimuth angles of the estimated azimuth angles based on the number of array elements of the uniform circular array and the array element radius of the uniform circular array in combination with the array manifold, and forming a second correlation matrix from each group of correlation degrees, until all elevation angles in the estimated elevation angles are processed and a second correlation matrix set is formed from each second correlation matrix.

[0073] Accordingly, based on the above embodiment, step 140 may further include: Determining an intermediate value based on the number of array elements and the number of azimuth angles in each group of azimuth angles; Perform a fast Fourier operation based on the intermediate value and the first correlation matrix to obtain a first matrix; Performing a fast Fourier operation based on the intermediate value and each group of correlation levels in each second correlation matrix of the second correlation matrix set to obtain a corresponding number of second matrices; Performing inverse fast Fourier transform on each of the second matrices based on the first matrix to obtain a corresponding number of third matrices; For each third matrix, extraction is performed at preset intervals to obtain correlation values ​​of all azimuth angles in each group of azimuth angles of the estimated azimuth angle at each elevation angle of the estimated elevation angle.

[0074] Specifically, the 360 ​​azimuth angles can be divided into N2 groups, each group containing M2 values. Perform FFT operation, the calculation method is as follows: N1=N*N; M2=360 / N2; len2=N1*M2; numFFT = 2^nextpow2(len2); ; Here, numFFT represents the power series of 2 that is larger than N1*M2 and closest to it.

[0075] Select an elevation angle from the estimated elevation angles , according to the number of elements of the uniform circular array and the element radius of the uniform circular array, the relevant matrix C is calculated in combination with the following array manifold: ; ; Select a new set of azimuth angles from each set of azimuth angles and repeat the above process. After executing the corresponding number of times, the correlation degree of all azimuth angles corresponding to each set of azimuth angles at the elevation angle is obtained, and the second correlation matrix C is formed by the correlation degree of each set at the elevation angle; C Among them, for a uniform circular array, when the radius and incident frequency are determined, the corresponding array manifold has been determined, that is, Some are known and can be calculated in advance and saved for use.

[0076] A new elevation angle is selected from the estimated elevation angles and the above process is repeated. After executing the corresponding number of times, a corresponding number of second correlation matrices are obtained, and a second correlation matrix set is formed by each second correlation matrix.

[0077] Further, a fast Fourier transform is performed based on the intermediate value and each group of correlation degrees in each second correlation matrix of the second correlation matrix set to obtain a corresponding number of second matrices; and an inverse fast Fourier transform is performed based on the first matrix and each second matrix to obtain a corresponding number of third matrices; specifically, there are: .

[0078] Further, for each third matrix, extraction is performed at preset intervals to obtain correlation values ​​of all azimuths in each group of azimuths of the estimated azimuth at each elevation of the estimated elevation angle, specifically, there are: ; The above process is executed repeatedly to obtain the relevant values ​​corresponding to all elevation angles and azimuth angles: .

[0079] The present application provides another new correlation matrix calculation and a new peak search method, which is convenient for hardware implementation and parallel processing, and helps to improve the evaluation efficiency of the DOA of the LTE uplink signal.

[0080] Figure 2 is a schematic diagram of a correlation matrix determination process of a signal arrival direction evaluation method provided in an embodiment of the present application, such as Figure 2 As shown, in one embodiment, the present application can determine the user frequency domain resources (i.e., the above frequency domain resource configuration) according to DCI0, and then frequency shift the data (i.e., the uplink signal) according to the user RB starting position (i.e., the above frequency domain position rbStart), and calculate the filter coefficient according to the number of user RBs (i.e., the above allocated RB number rbNum). Then, the filter coefficient can be used to filter the frequency shifted data, and the filtered data can be further extracted, and the extracted data can be used to calculate the correlation matrix.

[0081] Figure 3 is a flow chart of using convolution to calculate the correlation values ​​of all azimuth angles at one elevation angle in the signal arrival direction estimation method provided in an embodiment of the present application, such as Figure 3 As shown, in one embodiment, the present application can select an elevation angle and an azimuth angle, calculate the array manifold matrix A, and further calculate the extended matrix B of the matrix A. Determine whether the azimuth angle traversal is completed, if not, select a new azimuth angle and then perform the above calculation steps, and if so, output the manifold extended matrix C corresponding to all azimuth angles. Further perform convolution calculation on the matrix C and the noise subspace correlation matrix G to obtain the convolution result data, extract the convolution result data, and obtain the correlation values ​​of all azimuth angles at an elevation angle.

[0082] Figure 4 FIG. 1 is a flow chart of using FFT to calculate the correlation values ​​of all azimuth angles at one elevation angle in the signal arrival direction evaluation method provided in an embodiment of the present application, such as Figure 4 As shown, in one embodiment, an elevation angle is selected and the azimuth angles are grouped. Further, a group of azimuth angles is taken out, and an azimuth angle is selected from the group, and the array manifold matrix A is calculated, and the extended matrix B of the matrix A is further calculated. It is determined whether the azimuth angles in the group have been traversed. If not, a new azimuth angle is selected from the group and the above calculation steps are performed. If so, the extended matrix C of the manifold corresponding to all azimuth angles in the group is output. Further, the matrix C and the noise subspace correlation matrix G are FFT-calculated to obtain the result data, and the result data is extracted to obtain the correlation values ​​of all azimuth angles in one elevation angle and one group of azimuth angles. It is further determined whether all the groups have been traversed. If not, a new group of azimuth angles is taken out and the above processing process is performed. If so, the correlation values ​​corresponding to all elevation angles and azimuth angles are output.

[0083] The signal arrival direction evaluation device provided by the present application is described below. The signal arrival direction evaluation device described below and the signal arrival direction evaluation method described above can be referenced to each other.

[0084] Furthermore, the present application also provides a signal direction of arrival evaluation device.

[0085] The signal arrival direction evaluation device comprises: A first determination module, configured to receive an uplink signal based on a uniform circular array, and determine downlink control information based on the uplink signal; A second determination module, configured to determine a first correlation matrix and a number of information sources based on the downlink control information and the uplink signal; A calculation module, used for performing array manifold calculation based on the estimated elevation angle and the estimated azimuth angle to obtain a second correlation matrix set; A third determination module, configured to determine correlation values ​​corresponding to an estimated elevation angle and an estimated azimuth angle according to the first correlation matrix and the second correlation matrix set; The search module is used to perform peak search according to the number of information sources and the correlation value to obtain the elevation angle and azimuth angle of the uplink signal.

[0086] The signal arrival direction evaluation device of the present application determines downlink control information based on the uplink signal when an uplink signal is received based on a uniform circular array, so that a first correlation matrix and the number of information sources can be determined based on the downlink control information and the uplink signal; at the same time, array manifold calculation is performed based on the estimated elevation angle and the estimated azimuth angle to obtain a second correlation matrix set; and then, correlation values ​​corresponding to the estimated elevation angle and the estimated azimuth angle can be determined based on the first correlation matrix and the second correlation matrix set; and peak search is further performed based on the number of information sources and the correlation value to obtain the elevation angle and azimuth angle of the uplink signal. By directly using known downlink control information to construct the first correlation matrix, complex autocorrelation calculations on the entire uplink signal are avoided, thereby reducing the amount of calculation; at the same time, for a uniform circular array, when its radius and incident frequency are determined, the corresponding array manifold has been determined, so the second correlation matrix set for array manifold calculation can be performed in advance based on the estimated elevation angle and the estimated azimuth angle and saved for use, and then when the correlation values ​​corresponding to the estimated elevation angle and the estimated azimuth angle are determined based on the first correlation matrix and the second correlation matrix set, the amount of calculation can be effectively reduced, and it is convenient to quickly perform peak search based on the number of signal sources and the correlation value to obtain the elevation angle and azimuth angle of the uplink signal, thereby improving the evaluation efficiency of the DOA of the LTE uplink signal.

[0087] In one embodiment, the second determining module is specifically configured to: Performing frequency shifting on the uplink signal based on the downlink control information to obtain a frequency shifted signal; filtering the frequency shifted signal to obtain a filtered signal; Extracting information from the filtered signal to obtain extracted information; determining a fourth matrix based on the extracted information; Performing eigenvalue decomposition on the fourth matrix to obtain eigenvalues ​​and eigenvectors; Determining the number of information sources based on the characteristic value; Determine a noise subspace according to the number of information sources and the eigenvector; A first correlation matrix is ​​constructed based on the noise subspace.

[0088] In one embodiment, the calculation module is specifically used for: Obtain a pending elevation angle from the estimated elevation angle; Determine the correlation between the elevation angle to be processed and each azimuth angle in the estimated azimuth angle according to the number of array elements of the uniform circular array and the array element radius of the uniform circular array in combination with the array manifold, and form a second correlation matrix according to the correlation degrees; An unprocessed elevation angle is obtained from the estimated elevation angle as a new elevation angle to be processed, and the process returns to execute the step of determining the correlation between the elevation angle to be processed and each azimuth angle in the estimated azimuth angle according to the number of array elements of the uniform circular array and the array element radius of the uniform circular array in combination with the array manifold, and forming a second correlation matrix from each correlation degree, until all elevation angles in the estimated elevation angle are processed and a second correlation matrix set is formed from each second correlation matrix.

[0089] In one embodiment, the third determination module is specifically configured to: Perform convolution operations on the first correlation matrix and each second correlation matrix in the second correlation matrix set to obtain a corresponding number of convolution data; For each convolution data, extraction is performed according to a preset interval to obtain the correlation values ​​of all azimuth angles in the estimated azimuth angle at each elevation angle of the estimated elevation angle.

[0090] In one embodiment, the calculation module is further configured to: Obtain a pending elevation angle from the estimated elevation angle; Evenly divide each azimuth in the estimated azimuth into preset groups; Determine the correlation between the elevation angle to be processed and each azimuth angle in each group of azimuth angles of the estimated azimuth angles according to the number of array elements of the uniform circular array and the array element radius of the uniform circular array in combination with the array manifold, and form a second correlation matrix based on the correlation degrees of each group; An unprocessed elevation angle is obtained from the estimated elevation angle as a new elevation angle to be processed, and the process returns to execute the step of determining the correlation between the elevation angle to be processed and each azimuth angle in each group of azimuth angles of the estimated azimuth angles according to the number of array elements of the uniform circular array and the array element radius of the uniform circular array in combination with the array manifold, and forming a second correlation matrix from each group of correlation degrees until all elevation angles in the estimated elevation angles are processed and a second correlation matrix set is formed from each second correlation matrix.

[0091] In one embodiment, the third determining module is further configured to: Determining an intermediate value based on the number of array elements and the number of azimuth angles in each group of azimuth angles; Perform a fast Fourier operation based on the intermediate value and the first correlation matrix to obtain a first matrix; Performing a fast Fourier operation based on the intermediate value and each group of correlation levels in each second correlation matrix of the second correlation matrix set to obtain a corresponding number of second matrices; Performing inverse fast Fourier transform on each second matrix based on the first matrix to obtain a corresponding number of third matrices; For each third matrix, extraction is performed at preset intervals to obtain correlation values ​​of all azimuth angles in each group of azimuth angles of the estimated azimuth angle at each elevation angle of the estimated elevation angle.

[0092] Figure 5 An example of a physical structure diagram of an electronic device is shown in FIG. Figure 5 As shown, the electronic device may include: a processor 510, a communication interface 520, a memory 530 and a communication bus 540, wherein the processor 510, the communication interface 520 and the memory 530 communicate with each other through the communication bus 540. The processor 510 may call the logic instructions in the memory 530 to execute the following method: receiving an uplink signal based on a uniform circular array, and determining downlink control information based on the uplink signal; Determine a first correlation matrix and the number of information sources based on the downlink control information and the uplink signal; Perform array manifold calculation based on the estimated elevation angle and the estimated azimuth angle to obtain a second correlation matrix set; Determining correlation values ​​corresponding to an estimated elevation angle and an estimated azimuth angle according to the first correlation matrix and the second correlation matrix set; A peak search is performed according to the number of information sources and the correlation value to obtain the elevation angle and azimuth angle of the uplink signal.

[0093] In addition, the logic instructions in the above-mentioned memory 530 can be implemented in the form of a software functional unit and can be stored in a computer-readable storage medium when it is sold or used as an independent product. Based on this understanding, the technical solution of the present application can be essentially or partly embodied in the form of a software product that contributes to the relevant technology. The computer software product is stored in a storage medium, including several instructions to enable a computer device (which can be a personal computer, a server, or a network device, etc.) to perform all or part of the steps of the method described in each embodiment of the present application. The aforementioned storage medium includes: U disk, mobile hard disk, read-only memory (ROM, Read-Only Memory), random access memory (RAM, Random Access Memory), disk or optical disk and other media that can store program codes.

[0094] In another aspect, an embodiment of the present application further provides a non-transitory computer-readable storage medium having a computer program stored thereon, and when the computer program is executed by a processor, the method provided by each of the above embodiments is implemented, for example, including: receiving an uplink signal based on a uniform circular array, and determining downlink control information based on the uplink signal; Determine a first correlation matrix and the number of information sources based on the downlink control information and the uplink signal; Perform array manifold calculation based on the estimated elevation angle and the estimated azimuth angle to obtain a second correlation matrix set; Determining correlation values ​​corresponding to an estimated elevation angle and an estimated azimuth angle according to the first correlation matrix and the second correlation matrix set; A peak search is performed according to the number of information sources and the correlation value to obtain the elevation angle and azimuth angle of the uplink signal.

[0095] In another aspect, an embodiment of the present application further provides a computer program product having a computer program stored thereon, and when the computer program is executed by a processor, the method provided by each of the above embodiments is implemented, for example, including: receiving an uplink signal based on a uniform circular array, and determining downlink control information based on the uplink signal; Determine a first correlation matrix and the number of information sources based on the downlink control information and the uplink signal; Perform array manifold calculation based on the estimated elevation angle and the estimated azimuth angle to obtain a second correlation matrix set; Determining correlation values ​​corresponding to an estimated elevation angle and an estimated azimuth angle according to the first correlation matrix and the second correlation matrix set; A peak search is performed according to the number of information sources and the correlation value to obtain the elevation angle and azimuth angle of the uplink signal.

[0096] The device embodiments described above are merely illustrative, wherein the units described as separate components may or may not be physically separated, and the components displayed as units may or may not be physical units, that is, they may be located in one place, or they may be distributed on multiple network units. Some or all of the modules may be selected according to actual needs to achieve the purpose of the scheme of this embodiment. Ordinary technicians in this field can understand and implement it without paying creative labor.

[0097] Through the description of the above implementation methods, those skilled in the art can clearly understand that each implementation method can be implemented by means of software plus a necessary general hardware platform, and of course, can also be implemented by hardware. Based on this understanding, the above technical solution is essentially or the part that contributes to the relevant technology can be embodied in the form of a software product, and the computer software product can be stored in a computer-readable storage medium, such as ROM / RAM, a disk, an optical disk, etc., including a number of instructions for a computer device (which can be a personal computer, a server, or a network device, etc.) to execute the methods described in each embodiment or some parts of the embodiment.

[0098] Finally, it should be noted that the above implementation modes are only used to illustrate the present application, rather than to limit the present application. Although the present application is described in detail with reference to the embodiments, a person skilled in the art should understand that various combinations, modifications or equivalent substitutions of the technical solutions of the present application do not depart from the spirit and scope of the technical solutions of the present application.

Claims

1. A signal arrival direction evaluation method, characterized in that: include: receiving an uplink signal based on a uniform circular array, and determining downlink control information based on the uplink signal; Determine a first correlation matrix and the number of information sources based on the downlink control information and the uplink signal; Perform array manifold calculation based on the estimated elevation angle and the estimated azimuth angle to obtain a second correlation matrix set; Determining correlation values ​​corresponding to an estimated elevation angle and an estimated azimuth angle according to the first correlation matrix and the second correlation matrix set; A peak search is performed according to the number of information sources and the correlation value to obtain the elevation angle and azimuth angle of the uplink signal.

2. The signal arrival direction evaluation method according to claim 1, characterized in that: The array manifold calculation is performed based on the estimated elevation angle and the estimated azimuth angle to obtain a second correlation matrix set, including: Obtain a pending elevation angle from the estimated elevation angle; Determine the correlation between the elevation angle to be processed and each azimuth angle in the estimated azimuth angle according to the number of array elements of the uniform circular array and the array element radius of the uniform circular array in combination with the array manifold, and form a second correlation matrix according to the correlation degrees; An unprocessed elevation angle is obtained from the estimated elevation angle as a new elevation angle to be processed, and the process returns to execute the step of determining the correlation between the elevation angle to be processed and each azimuth angle in the estimated azimuth angle according to the number of array elements of the uniform circular array and the array element radius of the uniform circular array in combination with the array manifold, and forming a second correlation matrix from each correlation degree, until all elevation angles in the estimated elevation angle are processed and a second correlation matrix set is formed from each second correlation matrix.

3. The signal arrival direction evaluation method according to claim 2, characterized in that: The determining, according to the first correlation matrix and the second correlation matrix set, correlation values ​​corresponding to the estimated elevation angle and the estimated azimuth angle comprises: Perform convolution operations on the first correlation matrix and each second correlation matrix in the second correlation matrix set to obtain a corresponding number of convolution data; For each convolution data, extraction is performed according to a preset interval to obtain the correlation values ​​of all azimuth angles in the estimated azimuth angle at each elevation angle of the estimated elevation angle.

4. The signal arrival direction evaluation method according to claim 1, characterized in that: The array manifold calculation is performed based on the estimated elevation angle and the estimated azimuth angle to obtain a second correlation matrix set, and further includes: Obtain a pending elevation angle from the estimated elevation angle; Evenly divide each azimuth in the estimated azimuth into preset groups; Determine the correlation between the elevation angle to be processed and each azimuth angle in each group of azimuth angles of the estimated azimuth angles according to the number of array elements of the uniform circular array and the array element radius of the uniform circular array in combination with the array manifold, and form a second correlation matrix according to the correlation degrees of each group; An unprocessed elevation angle is obtained from the estimated elevation angle as a new elevation angle to be processed, and the process returns to execute the step of determining the correlation between the elevation angle to be processed and each azimuth angle in each group of azimuth angles of the estimated azimuth angles according to the number of array elements of the uniform circular array and the array element radius of the uniform circular array in combination with the array manifold, and forming a second correlation matrix from each group of correlation degrees until all elevation angles in the estimated elevation angles are processed and a second correlation matrix set is formed from each second correlation matrix.

5. The signal arrival direction evaluation method according to claim 4, characterized in that: The determining, according to the first correlation matrix and the second correlation matrix set, correlation values ​​corresponding to the estimated elevation angle and the estimated azimuth angle further includes: Determining an intermediate value based on the number of array elements and the number of azimuth angles in each group of azimuth angles; Perform a fast Fourier operation based on the intermediate value and the first correlation matrix to obtain a first matrix; Performing a fast Fourier operation based on the intermediate value and each group of correlation levels in each second correlation matrix of the second correlation matrix set to obtain a corresponding number of second matrices; Performing inverse fast Fourier transform on each second matrix based on the first matrix to obtain a corresponding number of third matrices; For each third matrix, extraction is performed at preset intervals to obtain correlation values ​​of all azimuth angles in each group of azimuth angles of the estimated azimuth angle at each elevation angle of the estimated elevation angle.

6. The signal arrival direction evaluation method according to claim 1, characterized in that: The determining, based on the downlink control information and the uplink signal, a first correlation matrix and the number of information sources comprises: Performing frequency shifting on the uplink signal based on the downlink control information to obtain a frequency shifted signal; filtering the frequency shifted signal to obtain a filtered signal; Extracting information from the filtered signal to obtain extracted information; determining a fourth matrix based on the extracted information; Performing eigenvalue decomposition on the fourth matrix to obtain eigenvalues ​​and eigenvectors; Determining the number of information sources based on the characteristic value; Determine a noise subspace according to the number of information sources and the eigenvector; A first correlation matrix is ​​constructed based on the noise subspace.

7. A signal arrival direction evaluation device, characterized in that: include: A first determination module, configured to receive an uplink signal based on a uniform circular array, and determine downlink control information based on the uplink signal; A second determination module, configured to determine a first correlation matrix and a number of information sources based on the downlink control information and the uplink signal; A calculation module, used for performing array manifold calculation based on the estimated elevation angle and the estimated azimuth angle to obtain a second correlation matrix set; A third determination module, configured to determine correlation values ​​corresponding to an estimated elevation angle and an estimated azimuth angle according to the first correlation matrix and the second correlation matrix set; The search module is used to perform peak search according to the number of information sources and the correlation value to obtain the elevation angle and azimuth angle of the uplink signal.

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

9. A storage medium, the storage medium being a non-transitory computer-readable storage medium, on which a computer program is stored, characterized in that: When the computer program is executed by a processor, the signal arrival direction evaluation method according to any one of claims 1 to 6 is implemented.

10. A computer program product, comprising a computer program, characterized in that When the computer program is executed by a processor, the signal arrival direction evaluation method according to any one of claims 1 to 6 is implemented.

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