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

Abstract

The present application relates to the field of communication technology and provides a signal direction of arrival assessment method, device, electronic device, storage medium and computer program product. The method includes: receiving an uplink signal based on a uniform circular array, determining downlink control information based on the uplink signal; determining a first correlation matrix and the number of signal 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 the estimated elevation angle and the estimated azimuth angle based on the first correlation matrix and the second correlation matrix set; performing a 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. The present application can improve the DOA assessment efficiency of LTE uplink signals by reducing the amount of calculation.

Description

Technical Field

[0001] The present application relates to the field of communication technology, and in particular to a signal direction of arrival 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 development has achieved a significant leap forward in spatial spectrum estimation technology. When using the MUSIC algorithm to calculate the Direction of Arrival (DOA) of Long Term Evolution (LTE) uplink signals, the array antenna receives signal data and generates a covariance matrix. This covariance matrix is ​​decomposed to obtain the signal subspace and noise subspace. The angle information of the incoming signal is obtained through the orthogonal relationship between the signal direction vector and the noise subspace.

[0003] However, the MUSIC algorithm currently used to calculate the DOA of the LTE uplink signal has a very large computational complexity when simultaneously calculating the azimuth and elevation angles, 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 direction of arrival assessment method, device, electronic device, storage medium, and computer program product to solve the problem of very large computational complexity when calculating the DOA of LTE uplink signals using the MUSIC algorithm, thereby improving the DOA assessment efficiency of LTE uplink signals.

[0005] A signal direction of arrival evaluation method according to an embodiment of the first aspect of the present application includes:

[0006] receiving an uplink signal based on a uniform circular array, and determining downlink control information based on the uplink signal;

[0007] Determining a first correlation matrix and a number of information sources based on the downlink control information and the uplink signal;

[0008] Perform array manifold calculation based on the estimated elevation angle and the estimated azimuth angle to obtain a second correlation matrix set;

[0009] determining correlation values ​​corresponding to an estimated elevation angle and an estimated azimuth angle based on the first correlation matrix and the second correlation matrix set;

[0010] A peak search is performed based on the number of information sources and the correlation value to obtain the elevation angle and azimuth angle of the uplink signal.

[0011] According to one 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:

[0012] Obtain a pending elevation angle from the estimated elevation angle;

[0013] determining, based on the number of elements of the uniform circular array and the element radius of the uniform circular array and in combination with an array manifold, a correlation degree between the elevation angle to be processed and each azimuth angle in the estimated azimuth angles, and forming a second correlation matrix based on the correlation degrees;

[0014] An unprocessed elevation angle is obtained from the estimated elevation angle as a new elevation angle to be processed, and the process returns to executing the step of determining, based on the number of elements of the uniform circular array and the element radius of the uniform circular array and in combination with the array manifold, a correlation between the elevation angle to be processed and each azimuth angle in the estimated azimuth angle, 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.

[0015] According to one 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 includes:

[0016] Performing convolution operations on the first correlation matrix and each second correlation matrix in the second correlation matrix set to obtain a corresponding amount of convolution data;

[0017] 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.

[0018] According to one 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:

[0019] Obtain a pending elevation angle from the estimated elevation angle;

[0020] Evenly divide each azimuth angle in the estimated azimuth angle into preset groups;

[0021] determining, based on the number of elements of the uniform circular array and the element radius of the uniform circular array and in combination with the array manifold, a correlation between the elevation angle to be processed and each azimuth angle in each group of estimated azimuth angles, and forming a second correlation matrix based on the correlation degrees of each group;

[0022] An unprocessed elevation angle is obtained from the estimated elevation angle as a new elevation angle to be processed, and the process returns to executing the step of determining, based on the number of elements of the uniform circular array and the element radius of the uniform circular array and in combination with the array manifold, a correlation between the elevation angle to be processed and each azimuth angle in each group of the estimated azimuth angles, and forming a second correlation matrix from each group of correlations, until all elevation angles in the estimated elevation angles are processed and a second correlation matrix set is formed from each second correlation matrix.

[0023] According to one 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:

[0024] determining an intermediate value based on the number of array elements and the number of azimuth angles in each group of azimuth angles;

[0025] Performing a fast Fourier operation on the intermediate value and the first correlation matrix to obtain a first matrix;

[0026] 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;

[0027] Performing an inverse fast Fourier transform on each of the first matrices and each of the second matrices to obtain a corresponding number of third matrices;

[0028] For each third matrix, extraction is performed according to a preset interval 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.

[0029] According to one embodiment of the present application, determining a first correlation matrix and the number of information sources based on the downlink control information and the uplink signal includes:

[0030] performing frequency shifting on the uplink signal based on the downlink control information to obtain a frequency shifted signal;

[0031] filtering the frequency-shifted signal to obtain a filtered signal;

[0032] performing information extraction on the filtered signal to obtain extracted information;

[0033] determining a fourth matrix based on the extracted information;

[0034] Performing eigenvalue decomposition on the fourth matrix to obtain eigenvalues ​​and eigenvectors;

[0035] determining the number of information sources based on the characteristic value;

[0036] Determine a noise subspace according to the number of information sources and the eigenvector;

[0037] A first correlation matrix is ​​constructed based on the noise subspace.

[0038] A signal direction of arrival evaluation device according to an embodiment of the second aspect of the present application includes:

[0039] A first determining module is configured to receive an uplink signal based on a uniform circular array and determine downlink control information based on the uplink signal;

[0040] A second determining module, configured to determine a first correlation matrix and the number of information sources based on the downlink control information and the uplink signal;

[0041] a calculation module, configured to perform array manifold calculation based on the estimated elevation angle and the estimated azimuth angle to obtain a second correlation matrix set;

[0042] a third determining module, configured to 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;

[0043] 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.

[0044] According to an embodiment of the third aspect of the present application, an 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, it implements any of the above-described signal arrival direction evaluation methods.

[0045] 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 the signal arrival direction evaluation method as described in any one of the above.

[0046] According to the computer program product of the fifth aspect of the present application, the computer program includes a computer program, which, when executed by a processor, implements any of the above-mentioned signal arrival direction evaluation methods.

[0047] The above one or more technical solutions in the embodiments of the present application have at least the following technical effects:

[0048] 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. Simultaneously, an array manifold calculation is performed based on the estimated elevation angle and the estimated azimuth angle to obtain a second correlation matrix set. Furthermore, 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. Furthermore, a peak search is 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 is already determined. Therefore, a 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. 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 DOA evaluation efficiency of the LTE uplink signal.

[0049] Additional aspects and advantages of the present application will be given in part in the description below, and in part will become obvious from the description below, or will be learned through practice of the present application. BRIEF DESCRIPTION OF THE DRAWINGS

[0050] In order to more clearly illustrate the technical solutions in the present invention or the prior art, a brief introduction is given below to 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 any creative work.

[0051] Figure 1 4 is a flow chart of a signal direction of arrival evaluation method provided in an embodiment of the present application.

[0052] Figure 2 1 is a flow chart of correlation matrix determination of the signal direction of arrival evaluation method provided in an embodiment of the present application.

[0053] Figure 3 This 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.

[0054] Figure 4 This 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.

[0055] Figure 5 It is a structural diagram of the electronic device provided in this application. DETAILED DESCRIPTION

[0056] The following embodiments of the present invention are described in further detail with reference to the accompanying drawings and examples. The following examples are used to illustrate the present invention, but are not intended to limit the scope of the present invention.

[0057] 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", etc., indicating the orientation or positional relationship, are based on the orientation or positional relationship shown in the accompanying drawings, and 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 operate 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.

[0058] In the description of the embodiments of this application, it should be noted that, unless otherwise specified or limited, the terms "connected" and "connection" should be understood in a broad sense. For example, they can refer to fixed connections, detachable connections, or integral connections; they can refer to mechanical connections or electrical connections; they can refer to direct connections or indirect connections through an intermediate medium. Those skilled in the art will understand the specific meanings of the above terms in the embodiments of this application based on the specific circumstances.

[0059] In the embodiments of the present application, unless otherwise expressly specified or limited, a first feature being "above" or "below" a second feature may mean that the first and second features are in direct contact, or that the first and second features are in indirect contact through an intermediate medium. Furthermore, a first feature being "above," "above," and "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," and "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.

[0060] In the description of this specification, the description with reference to the terms "one embodiment", "some embodiments", "example", "specific example", or "some examples" 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 can be combined in any one or more embodiments or examples in a suitable manner. In addition, those skilled in the art can combine and combine different embodiments or examples described in this specification and the features of different embodiments or examples, unless they are contradictory.

[0061] It should be noted that the current MUSIC algorithm used to calculate the DOA of LTE uplink signals reduces accuracy in the frequency domain when determining the data correlation matrix if user frequency domain resource allocation is limited. Furthermore, the frequency domain must be reset to zero before transforming other user data to the time domain, which increases the computational complexity. Furthermore, the MUSIC algorithm's peak search is computationally intensive and not easily amenable to hardware parallelization.

[0062] Based on this, the present application proposes a signal direction of arrival assessment method, device, electronic device, storage medium and computer program product.

[0063] Figure 1 FIG. 1 is a flow chart of a signal direction of arrival evaluation method provided in an embodiment of the present application. Figure 1 As shown, the signal direction of arrival evaluation method includes:

[0064] Step 110: Receive an uplink signal based on a uniform circular array, and determine downlink control information based on the uplink signal.

[0065] Step 120: Determine a first correlation matrix and the number of information sources based on the downlink control information and the uplink signal.

[0066] Step 130 : Perform array manifold calculation based on the estimated elevation angle and the estimated azimuth angle to obtain a second correlation matrix set.

[0067] Step 140: Determine correlation values ​​corresponding to the estimated elevation angle and the estimated azimuth angle based on the first correlation matrix and the second correlation matrix set.

[0068] Step 150: 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.

[0069] It should be noted that the execution entity of the signal arrival direction evaluation method provided in the embodiment of the present application can be a server, computer equipment, etc., such as a mobile phone, tablet computer, laptop computer, PDA, vehicle-mounted electronic equipment, wearable device, ultra-mobile personal computer (UMPC), netbook or personal digital assistant (PDA), etc.

[0070] The server or computer device of the present application may be provided with or connected to a signal direction of arrival evaluation device, thereby controlling the signal direction of arrival evaluation device to execute the signal direction of arrival 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.

[0071] In the present application, a uniform circular array may be used to receive uplink signals sent by user equipment. Specifically, the sampling rate of the LTE system may be, for example, 30.72 Mbps, and the corresponding Fast Fourier Transform (FFT) point number is 2048.

[0072] It can be understood that the number N of array elements of the uniform circular array, the radius r of the array element and the signal incident frequency f0 are all known.

[0073] 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, and the user's DCI0 is obtained. DCI0 typically contains information about the modulation method, resource block allocation, power control, etc.

[0074] 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.

[0075] 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.

[0076] Furthermore, the filtered signal is extracted to obtain extraction information.

[0077] According to the extracted information, a correlation matrix can be determined as a first correlation matrix, and the number K of information sources can be determined.

[0078] 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 based on actual scene evaluation, thereby obtaining an estimated elevation angle and an estimated azimuth angle.

[0079] Furthermore, the present application can obtain, by performing array manifold calculation, a correlation matrix of the estimated azimuth angle corresponding to all azimuth angles at each elevation angle of the estimated elevation angle as a second correlation matrix, and form a second correlation matrix set from each second correlation matrix;

[0080] 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 the preset interval to obtain the correlation value with the noise matrix corresponding to all azimuth angles at an elevation angle.

[0081] 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.

[0082] 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.

[0083] 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.

[0084] 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 and respectively serve as second matrices.

[0085] Furthermore, an inverse fast Fourier transform is performed on the first matrix and each second matrix to obtain a corresponding number of matrices which are respectively used as third matrices.

[0086] Furthermore, for each third matrix, extraction is performed according to a preset interval 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.

[0087] 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.

[0088] 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 heap method may be used to find the maximum value among the reciprocals corresponding to the respective correlation values.

[0089] Record the index of the maximum value to obtain the corresponding elevation and azimuth angles.

[0090] 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.

[0091] According to the signal direction of arrival 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 signal sources can be determined based on the downlink control information and the uplink signal; at the same time, an 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 a peak search is further performed based on the number of signal 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 is already determined. Therefore, a 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. 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 DOA evaluation efficiency of the LTE uplink signal.

[0092] Based on the above embodiment, step 120 may include:

[0093] performing frequency shifting on the uplink signal based on the downlink control information to obtain a frequency shifted signal;

[0094] Filtering the frequency-shifted signal to obtain a filtered signal;

[0095] Extracting information from the filtered signal to obtain extracted information;

[0096] determining a fourth matrix based on the extracted information;

[0097] Perform eigenvalue decomposition on the fourth matrix to obtain eigenvalues ​​and eigenvectors;

[0098] Determine the number of information sources based on the eigenvalues;

[0099] Determine the noise subspace according to the number of information sources and the eigenvector;

[0100] A first correlation matrix is ​​constructed based on the noise subspace.

[0101] 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:

[0102] ;

[0103] In the formula, rxSig 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; Indicates the data after frequency shifting; n is 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.

[0104] 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 can be calculated using the following formula: Perform filtering and extraction to obtain extraction information :

[0105] temp1=conv(coff, (n,:));

[0106] temp2=temp1(floor(len2 / 2)+[1:len]);

[0107] (n,:)=temp2(1:M:len);

[0108] Among them, conv represents convolution calculation; floor represents rounding down; M represents the decimation multiple.

[0109] Furthermore, using the extracted information Compute the correlation matrix as the fourth matrix:

[0110] ;

[0111] Where RR represents the correlation matrix with dimension N*N; H represents the conjugate transpose.

[0112] Furthermore, eigenvalue decomposition is performed on RR to obtain the corresponding eigenvalue D and eigenvector EV.

[0113] 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.

[0114] According to the noise subspace G, a correlation matrix is ​​constructed as the first correlation matrix according to the following formula :

[0115] ;

[0116] ;

[0117] Where H represents conjugate transpose and T represents transpose.

[0118] This application uses a fast algorithm for frequency shifting and filtering, which can effectively reduce the computational complexity and help improve the efficiency of DOA evaluation of LTE uplink signals.

[0119] Based on the above embodiment, step 130 may include:

[0120] Obtain a pending elevation angle from the estimated elevation angle;

[0121] Determining the degree of correlation between the elevation angle to be processed and each azimuth angle in the estimated azimuth angles based on the number of elements in the uniform circular array and the radius of the elements in the uniform circular array in combination with the array manifold, and forming a second correlation matrix based on the respective correlation degrees;

[0122] An unprocessed elevation angle is obtained from the estimated elevation angle as a new elevation angle to be processed, and the process returns to executing the step of determining the correlation between the elevation angle to be processed and each azimuth angle in the estimated azimuth angle based on the number of elements and the 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.

[0123] Accordingly, based on the above embodiment, step 140 may include:

[0124] Performing 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;

[0125] 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.

[0126] Specifically, this application selects an elevation angle from the estimated elevation angles , according to the number of elements and the radius of the uniform circular array, the relevant matrix C is calculated in combination with the following array manifold:

[0127] ;

[0128] in, Indicates the selected elevation angle The degree of correlation between the k-th azimuth and the estimated azimuth, represents the kth azimuth, Indicates the wavelength corresponding to the signal frequency;

[0129] ;

[0130] in, Indicates the selected elevation angle The expansion matrix formed by the correlation degree between the k-th azimuth angle;

[0131] Select a new azimuth from the estimated azimuths and repeat the above process for a corresponding number of times to obtain the correlation of all azimuths at the elevation angle, and form a second correlation matrix C based on the correlations at the elevation angle.

[0132] C= ;

[0133] Here, 360 represents the number of azimuth angles. For a uniform circular array, when the radius and incident frequency are determined, the corresponding array manifold is already determined, that is, the C part in the formula is known and can be calculated and saved in advance for use.

[0134] A new elevation angle is selected from the estimated elevation angles and the above process is repeated. After executing the above process a 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.

[0135] Furthermore, 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 intervals N1 to obtain the correlation values ​​convResult of the noise matrix corresponding to all azimuth angles at an elevation angle. Specifically, there are:

[0136] N1=N*N;

[0137] ,C);

[0138] ;

[0139] Among them, conv represents convolution calculation.

[0140] Repeat the above steps to obtain the correlation values ​​corresponding to all elevation angles and all azimuth angles in the estimated azimuth angles:

[0141] .

[0142] This application provides a new correlation matrix calculation and a new peak search method, which facilitates hardware implementation and parallel processing, and helps to improve the efficiency of DOA evaluation of LTE uplink signals.

[0143] Based on the above embodiment, step 130 may further include:

[0144] Obtain a pending elevation angle from the estimated elevation angle;

[0145] Evenly divide each azimuth angle in the estimated azimuth angle into preset groups;

[0146] Determining the correlation between the elevation angle to be processed and each azimuth angle in each group of estimated azimuth angles based on the number of elements and the element radius of the uniform circular array and the array manifold, and forming a second correlation matrix based on the correlation degrees of each group;

[0147] An unprocessed elevation angle is obtained from the estimated elevation angle as a new elevation angle to be processed, and the process returns to executing the step of determining the correlation between the elevation angle to be processed and each azimuth angle in each group of estimated azimuth angles based on the number of elements and the element radius of the uniform circular array and the array manifold, and forming a second correlation matrix from each group of correlations, until all elevation angles in the estimated elevation angles are processed and a second correlation matrix set is formed from each second correlation matrix.

[0148] Accordingly, based on the above embodiment, step 140 may further include:

[0149] Determine an intermediate value based on the number of array elements and the number of azimuth angles in each group of azimuth angles;

[0150] Perform a fast Fourier operation based on the intermediate value and the first correlation matrix to obtain a first matrix;

[0151] 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;

[0152] Performing inverse fast Fourier transform on the first matrix and each second matrix to obtain a corresponding number of third matrices;

[0153] For each third matrix, extraction is performed according to a preset interval 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.

[0154] Specifically, the 360 ​​azimuth angles can be divided into N2 groups, each group contains M2 values, and the first correlation matrix Perform FFT operation, the calculation method is as follows:

[0155] N1=N*N;

[0156] M2=360 / N2;

[0157] len2=N1*M2;

[0158] numFFT=2^nextpow2(len2);

[0159] ;

[0160] Here, numFFT represents the power series of 2 that is larger than N1*M2 and closest to it.

[0161] Select an elevation angle from the estimated elevation angles , according to the number of elements and the radius of the uniform circular array, the relevant matrix C is calculated in combination with the following array manifold:

[0162] ;

[0163] ;

[0164] Select a new set of azimuth angles from each set of azimuth angles and repeat the above process for a corresponding number of times to obtain the correlation degrees of all azimuth angles corresponding to each set of azimuth angles at the elevation angle, and form a second correlation matrix C based on the correlation degrees of each set at the elevation angle;

[0165] C

[0166] Among them, for a uniform circular array, when the radius and incident frequency are determined, the corresponding array manifold is determined, that is, Some are known and can be calculated and saved in advance.

[0167] A new elevation angle is selected from the estimated elevation angles and the above process is repeated. After executing the above process a 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.

[0168] Furthermore, a fast Fourier transform is performed on each correlation level of each second correlation matrix in the second correlation matrix set based on the intermediate value to obtain a corresponding number of second matrices; and an inverse fast Fourier transform is performed on each second matrix based on the first matrix to obtain a corresponding number of third matrices; specifically, there are:

[0169] .

[0170] Furthermore, for each third matrix, extraction is performed according to a preset interval 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. Specifically, there are:

[0171]

[0172] ;

[0173] The above process is executed repeatedly to obtain the corresponding correlation values ​​of all elevation angles and azimuth angles:

[0174] .

[0175] This application provides another new correlation matrix calculation and a new peak search method, which facilitates hardware implementation and parallel processing, and helps to improve the efficiency of DOA evaluation of LTE uplink signals.

[0176] Figure 2 FIG. 1 is a flow chart showing a correlation matrix determination process of a signal direction of arrival evaluation method provided in an embodiment of the present application. Figure 2 As shown, in one embodiment, the present application can determine user frequency domain resources based on DCI0 (i.e., the aforementioned frequency domain resource configuration), and then frequency shift the data (i.e., the uplink signal) based on the user RB starting position (i.e., the aforementioned frequency domain position rbStart). Simultaneously, filter coefficients are calculated based on the number of user RBs (i.e., the aforementioned allocated RB number rbNum). The filter coefficients are then used to filter the frequency-shifted data, and the filtered data is further extracted, and the extracted data is used to calculate a correlation matrix.

[0177] Figure 3 FIG. 1 is a flow chart of using convolution to calculate the correlation values ​​of all azimuth angles at one elevation angle in the signal direction of arrival estimation method provided in an embodiment of the present application. 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 expansion matrix B of matrix A. It is determined whether the azimuth angle traversal is complete. If not, a new azimuth angle is selected and the above calculation steps are performed. If so, the manifold expansion matrix C corresponding to all azimuth angles is output. Matrix C is further convolved with the noise subspace correlation matrix G to obtain the convolution result data. The convolution result data is extracted to obtain the correlation values ​​of all azimuth angles at a certain elevation angle.

[0178] Figure 4 FIG. 1 is a flow chart of a method for estimating the direction of arrival of a signal using FFT to calculate the correlation values ​​of all azimuth angles at one elevation angle in an embodiment of the present application. Figure 4As 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. The matrix C and the noise subspace correlation matrix G are further FFT-calculated to obtain the result data, and the result data is extracted to obtain the correlation values ​​of all azimuth angles in a group of azimuth angles for an elevation angle. 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.

[0179] The signal direction of arrival estimation device provided in the present application is described below. The signal direction of arrival estimation device described below and the signal direction of arrival estimation method described above can be referenced to each other.

[0180] Furthermore, the present application also provides a signal direction of arrival evaluation device.

[0181] The signal direction of arrival evaluation device comprises:

[0182] A first determining module is configured to receive an uplink signal based on a uniform circular array and determine downlink control information based on the uplink signal;

[0183] A second determining module, configured to determine a first correlation matrix and the number of information sources based on the downlink control information and the uplink signal;

[0184] a calculation module, configured to perform array manifold calculation based on the estimated elevation angle and the estimated azimuth angle to obtain a second correlation matrix set;

[0185] a third determining module, configured to determine correlation values ​​corresponding to the estimated elevation angle and the estimated azimuth angle based on the first correlation matrix and the second correlation matrix set;

[0186] 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.

[0187] The signal direction of arrival evaluation device of the present application determines downlink control information based on the uplink signal when receiving an uplink signal based on a uniform circular array, so that a first correlation matrix and the number of signal 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 signal 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 is already determined. Therefore, a 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. 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 DOA evaluation efficiency of the LTE uplink signal.

[0188] In one embodiment, the second determining module is specifically configured to:

[0189] performing frequency shifting on the uplink signal based on the downlink control information to obtain a frequency shifted signal;

[0190] filtering the frequency-shifted signal to obtain a filtered signal;

[0191] performing information extraction on the filtered signal to obtain extracted information;

[0192] determining a fourth matrix based on the extracted information;

[0193] Performing eigenvalue decomposition on the fourth matrix to obtain eigenvalues ​​and eigenvectors;

[0194] determining the number of information sources based on the characteristic value;

[0195] Determine a noise subspace according to the number of information sources and the eigenvector;

[0196] A first correlation matrix is ​​constructed based on the noise subspace.

[0197] In one embodiment, the calculation module is specifically configured to:

[0198] Obtain a pending elevation angle from the estimated elevation angle;

[0199] determining, based on the number of elements of the uniform circular array and the element radius of the uniform circular array and in combination with an array manifold, a correlation degree between the elevation angle to be processed and each azimuth angle in the estimated azimuth angles, and forming a second correlation matrix based on the correlation degrees;

[0200] An unprocessed elevation angle is obtained from the estimated elevation angle as a new elevation angle to be processed, and the process returns to executing the step of determining, based on the number of elements of the uniform circular array and the element radius of the uniform circular array and in combination with the array manifold, a correlation between the elevation angle to be processed and each azimuth angle in the estimated azimuth angle, 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.

[0201] In one embodiment, the third determining module is specifically configured to:

[0202] Performing convolution operations on the first correlation matrix and each second correlation matrix in the second correlation matrix set to obtain a corresponding amount of convolution data;

[0203] 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.

[0204] In one embodiment, the calculation module is further configured to:

[0205] Obtain a pending elevation angle from the estimated elevation angle;

[0206] Evenly divide each azimuth angle in the estimated azimuth angle into preset groups;

[0207] determining, based on the number of elements of the uniform circular array and the element radius of the uniform circular array and in combination with the array manifold, a correlation between the elevation angle to be processed and each azimuth angle in each group of estimated azimuth angles, and forming a second correlation matrix based on the correlation degrees of each group;

[0208] An unprocessed elevation angle is obtained from the estimated elevation angle as a new elevation angle to be processed, and the process returns to executing the step of determining, based on the number of elements of the uniform circular array and the element radius of the uniform circular array and in combination with the array manifold, a correlation between the elevation angle to be processed and each azimuth angle in each group of the estimated azimuth angles, and forming a second correlation matrix from each group of correlations, until all elevation angles in the estimated elevation angles are processed and a second correlation matrix set is formed from each second correlation matrix.

[0209] In one embodiment, the third determining module is further configured to:

[0210] determining an intermediate value based on the number of array elements and the number of azimuth angles in each group of azimuth angles;

[0211] Performing a fast Fourier operation on the intermediate value and the first correlation matrix to obtain a first matrix;

[0212] 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;

[0213] Performing an inverse fast Fourier transform on each of the first matrices and each of the second matrices to obtain a corresponding number of third matrices;

[0214] For each third matrix, extraction is performed according to a preset interval 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.

[0215] Figure 5 An example of a physical structure diagram of an electronic device is shown below. 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 via the communication bus 540. The processor 510 may call 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;

[0216] Determining a first correlation matrix and a number of information sources based on the downlink control information and the uplink signal;

[0217] Perform array manifold calculation based on the estimated elevation angle and the estimated azimuth angle to obtain a second correlation matrix set;

[0218] determining correlation values ​​corresponding to an estimated elevation angle and an estimated azimuth angle based on the first correlation matrix and the second correlation matrix set;

[0219] A peak search is performed based on the number of information sources and the correlation value to obtain the elevation angle and azimuth angle of the uplink signal.

[0220] In addition, the logical 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 sold or used as an independent product. Based on this understanding, the technical solution of the present application, or the part that contributes to the relevant technology, or the part of the technical solution, can be embodied in the form of a software product. The computer software product is stored in a storage medium and includes several instructions for enabling a computer device (which can be a personal computer, server, or network device, etc.) to execute 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 code.

[0221] In another aspect, an embodiment of the present application further provides a non-transitory computer-readable storage medium having a computer program stored thereon. When the computer program is executed by a processor, the method provided in 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;

[0222] Determining a first correlation matrix and a number of information sources based on the downlink control information and the uplink signal;

[0223] Perform array manifold calculation based on the estimated elevation angle and the estimated azimuth angle to obtain a second correlation matrix set;

[0224] determining correlation values ​​corresponding to an estimated elevation angle and an estimated azimuth angle based on the first correlation matrix and the second correlation matrix set;

[0225] A peak search is performed based on the number of information sources and the correlation value to obtain the elevation angle and azimuth angle of the uplink signal.

[0226] In another aspect, an embodiment of the present application further provides a computer program product having a computer program stored thereon, wherein when the computer program is executed by a processor, the method provided in 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;

[0227] Determining a first correlation matrix and a number of information sources based on the downlink control information and the uplink signal;

[0228] Perform array manifold calculation based on the estimated elevation angle and the estimated azimuth angle to obtain a second correlation matrix set;

[0229] determining correlation values ​​corresponding to an estimated elevation angle and an estimated azimuth angle based on the first correlation matrix and the second correlation matrix set;

[0230] A peak search is performed based on the number of information sources and the correlation value to obtain the elevation angle and azimuth angle of the uplink signal.

[0231] The device embodiments described above are merely illustrative. The units described as separate components may or may not be physically separate, and the components shown as units may or may not be physical units, i.e., they may be located in one location or distributed across multiple network units. Some or all of the modules may be selected based on actual needs to achieve the objectives of the present embodiment. Persons of ordinary skill in the art will be able to understand and implement the present invention without inventive effort.

[0232] Through the description of the above embodiments, those skilled in the art will clearly understand that each embodiment can be implemented using software plus a necessary general-purpose hardware platform, or of course, hardware. Based on this understanding, the essence of the above technical solution, or the portion that contributes to the relevant technology, can be embodied in the form of a software product. This computer software product can be stored in a computer-readable storage medium, such as ROM / RAM, a magnetic disk, or an optical disk, and includes a number of instructions for causing a computer device (such as a personal computer, server, or network device) to execute the methods described in each embodiment or certain portions of the embodiments.

[0233] Finally, it should be noted that the above embodiments are intended only to illustrate the present application and are not intended to limit the present application. Although the present application has been described in detail with reference to the embodiments, it should be understood by those skilled in the art 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 direction of arrival 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; Determining a first correlation matrix and a 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 based on the first correlation matrix and the second correlation matrix set; Performing a peak search based on the number of information sources and the correlation value to obtain the elevation angle and azimuth angle of the uplink signal; 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; determining, based on the number of elements of the uniform circular array and the element radius of the uniform circular array and in combination with an array manifold, a correlation degree between the elevation angle to be processed and each azimuth angle in the estimated azimuth angles, and forming a second correlation matrix based on 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 executing the step of determining, based on the number of elements of the uniform circular array and the element radius of the uniform circular array and in combination with the array manifold, a correlation between the elevation angle to be processed and each azimuth angle in the estimated azimuth angle, 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.

2. The signal direction of arrival evaluation method according to claim 1, wherein: The determining, based on the first correlation matrix and the second correlation matrix set, correlation values ​​corresponding to the estimated elevation angle and the estimated azimuth angle includes: Performing convolution operations on the first correlation matrix and each second correlation matrix in the second correlation matrix set to obtain a corresponding amount 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.

3. The signal direction of arrival evaluation method according to claim 1, wherein: The array manifold calculation is performed based on the estimated elevation angle and the estimated azimuth angle to obtain a second correlation matrix set, further comprising: Obtain a pending elevation angle from the estimated elevation angle; Evenly divide each azimuth angle in the estimated azimuth angle into preset groups; determining, based on the number of elements of the uniform circular array and the element radius of the uniform circular array and in combination with the array manifold, a correlation between the elevation angle to be processed and each azimuth angle in each group of estimated azimuth angles, and forming 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 executing the step of determining, based on the number of elements of the uniform circular array and the element radius of the uniform circular array and in combination with the array manifold, a correlation between the elevation angle to be processed and each azimuth angle in each group of the estimated azimuth angles, and forming a second correlation matrix from each group of correlations, until all elevation angles in the estimated elevation angles are processed and a second correlation matrix set is formed from each second correlation matrix.

4. The signal direction of arrival evaluation method according to claim 3, wherein: The determining, based on 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; Performing a fast Fourier operation 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 an inverse fast Fourier transform on each of the first matrices and each of the second matrices to obtain a corresponding number of third matrices; For each third matrix, extraction is performed according to a preset interval 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.

5. The signal direction of arrival evaluation method according to claim 1, wherein: The determining, based on the downlink control information and the uplink signal, a first correlation matrix and the number of information sources 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; performing information extraction on 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.

6. A signal direction of arrival evaluation device, characterized in that: include: A first determining module is configured to receive an uplink signal based on a uniform circular array and determine downlink control information based on the uplink signal; A second determining module, configured to determine a first correlation matrix and the number of information sources based on the downlink control information and the uplink signal; a calculation module, configured to perform array manifold calculation based on the estimated elevation angle and the estimated azimuth angle to obtain a second correlation matrix set; a third determining module, configured to 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; A search module, configured to perform a peak search based on the number of information sources and the correlation value to obtain the elevation angle and azimuth angle of the uplink signal; The calculation module is specifically configured to obtain an elevation angle to be processed from the estimated elevation angles; determine, based on the number of elements in the uniform circular array and the element radius of the uniform circular array, in combination with an array manifold, a degree of correlation between the elevation angle to be processed and each azimuth angle in the estimated azimuth angles, and form a second correlation matrix from each degree of correlation; obtain an unprocessed elevation angle from the estimated elevation angles as a new elevation angle to be processed, and return to the step of determining, based on the number of elements in the uniform circular array and the element radius of the uniform circular array, in combination with an array manifold, a degree of correlation between the elevation angle to be processed and each azimuth angle in the estimated azimuth angles, and forming a second correlation matrix from each degree of correlation, until all elevation angles in the estimated elevation angles are processed and a second correlation matrix set is formed from each second correlation matrix.

7. 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 direction of arrival estimation method according to any one of claims 1 to 5 is implemented.

8. A storage medium, wherein the storage medium is a non-transitory computer-readable storage medium and stores a computer program, wherein: When the computer program is executed by a processor, the signal direction of arrival estimation method according to any one of claims 1 to 5 is implemented.

9. A computer program product comprising a computer program, characterized in that When the computer program is executed by a processor, the signal direction of arrival estimation method according to any one of claims 1 to 5 is implemented.

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