A coprime array and a signal angle-of-arrival estimation method

Abstract

The present application discloses a coprime array and a signal arrival angle estimation method, wherein the coprime array includes a first subarray, a second subarray and a third subarray arranged in sequence on a straight line; the first subarray includes array elements, and the array element intervals are respectively; the second subarray includes array elements, and the array element intervals are respectively; the third subarray includes array elements, and the array element intervals are respectively; the adjacent array elements of the first subarray overlap with the second subarray, and the adjacent array elements of the second subarray overlap with the third subarray, wherein,, and are mutually prime. The embodiment of the present application combines three coprime subarrays into a triple extended coprime array to strengthen the coprime constraints between the subarrays, so that the probability of overlapping fuzzy angle sets between multiple subarrays is reduced, and the ambiguity caused by a single snapshot is effectively suppressed, thereby improving the DoA estimation performance, thereby improving the target detection and positioning accuracy of the millimeter wave radar system under a single snapshot condition.

Description

Technical Field

[0001] The present application relates to the technical field of array signal processing, and in particular to a coprime array and a signal arrival angle estimation method. Background Art

[0002] Millimeter-wave radar has become one of the indispensable sensors in the field of autonomous driving due to its excellent all-weather and all-day working capabilities. Especially in the application of on-board point cloud imaging, millimeter-wave radar can generate clear point cloud images through high-resolution range Doppler compression technology, thereby providing accurate distance and speed information for environmental perception. This high-resolution point cloud data is crucial for object detection, tracking, and obstacle avoidance in autonomous driving systems.

[0003] In order to further improve the accuracy of target positioning, angle of arrival (DoA) estimation technology is widely used. DoA technology estimates the target position by analyzing the incident angle of the radar signal, and is one of the important technologies for achieving high-precision point cloud imaging. However, since the vehicle-mounted millimeter-wave radar system needs to process single-snapshot data in real time, and the coprime array is susceptible to ambiguity leakage under single-snapshot conditions, the DoA estimation performance is significantly reduced, which affects the target detection and positioning accuracy of the millimeter-wave radar system under single-snapshot conditions.

[0004] Therefore the prior art still needs to be improved and enhanced. Summary of the invention

[0005] The technical problem to be solved by the present application is to provide a coprime array and a signal arrival angle estimation method in view of the deficiencies of the prior art.

[0006] In order to solve the above technical problems, the first aspect of the present application provides a coprime array, wherein the coprime array includes a first sub-array, a second sub-array and a third sub-array arranged in sequence on a straight line; the first sub-array includes array elements, and the array element spacing is ; The second subarray includes array elements, and the array element spacing is ; The third subarray includes The array elements and the array element intervals are ; The adjacent array elements of the first sub-array overlap with the second sub-array, and the adjacent array elements of the second sub-array overlap with the third sub-array, wherein, , and Two are mutually prime, Indicates a rounding operation.

[0007] The coprime array, wherein the array element positions of the coprime array are:

[0008] ;

[0009] ;

[0010] ;

[0011] in, Indicates the total number of array elements; represents the position sequence of coprime arrays, express The The array element position of the array element, , represents the starting element position of the second subarray, Indicates the starting element position of the third subarray.

[0012] The coprime array, wherein for Far-field incoherent sources from different angles Arriving at the coprime array, the covariance matrix of the coprime array under a single snapshot is:

[0013] ;

[0014] ;

[0015] ;

[0016] ;

[0017] ;

[0018] in, represents the array received signal of the coprime array, express The conjugate of Represents coprime arrays The array manifold matrix, Indicates The steering vector of the source, represents the wavelength, represents the signal amplitude, represents a Gaussian white noise vector, express The conjugate of represents the signal autocorrelation matrix; represents the sum of the cross-correlation matrix between different signals and the signal-noise cross-correlation matrix; represents the noise autocorrelation matrix, Indicates The received signal of a source is express The conjugate of Indicates The distance between the array element and the starting array element, .

[0019] A second aspect of the present application provides a signal arrival angle estimation method, using the coprime array as described above, and the signal arrival angle estimation method specifically includes:

[0020] receiving an array receive signal of the coprime array and acquiring a steering vector matrix of the array receive signal;

[0021] estimating an initial power spectrum of the array received signal based on the array received signal and the steering vector matrix;

[0022] constructing a covariance matrix of the array received signal based on the initial power spectrum, and estimating a signal amplitude corresponding to the steering vector matrix based on the covariance matrix;

[0023] A signal angle of arrival of a signal received by the array is determined based on the signal amplitude.

[0024] The signal arrival angle estimation method, wherein the step of constructing a covariance matrix of the array received signal based on the initial power spectrum and estimating the signal amplitude corresponding to the steering vector matrix based on the covariance matrix specifically includes:

[0025] Constructing a covariance matrix of the array received signal based on the initial power spectrum, and using the covariance matrix as an initial covariance matrix;

[0026] estimating a signal amplitude corresponding to the steering vector matrix based on the initial covariance matrix;

[0027] Constructing a target power spectrum based on the signal amplitude, and constructing a target covariance matrix of the array received signal according to the target power spectrum;

[0028] The target covariance matrix is ​​used as an initial covariance matrix, and the step of estimating the signal amplitude corresponding to the steering vector matrix based on the initial covariance matrix is ​​re-executed until a preset end condition is reached to obtain the signal amplitude corresponding to the steering vector matrix.

[0029] The signal arrival angle estimation method, wherein the end condition is:

[0030] ;

[0031] in, Indicates The estimated signal amplitude, express The estimated signal amplitude, Indicates the preset error threshold.

[0032] The signal arrival angle estimation method, wherein the calculation formula of the signal amplitude is:

[0033] ;

[0034] in, represents the signal amplitude, represents the steering vector matrix, represents the inverse of the covariance matrix, Indicates that the array receives the signal.

[0035] A third aspect of the present application provides a signal arrival angle estimation device, which adopts the coprime array as described above, and the signal arrival angle estimation device specifically includes:

[0036] A receiving module, used for receiving an array receiving signal of the coprime array and obtaining a steering vector matrix of the array receiving signal;

[0037] an estimation module, configured to estimate an initial power spectrum of the array received signal based on the array received signal and the steering vector matrix;

[0038] A construction module, configured to construct a covariance matrix of the array received signal based on the initial power spectrum, and estimate a signal amplitude corresponding to the steering vector matrix based on the covariance matrix;

[0039] A search module is used to determine a signal arrival angle of the array received signal based on the signal amplitude.

[0040] A fourth aspect of the present application provides a computer-readable storage medium, which stores one or more programs. The one or more programs can be executed by one or more processors to implement the steps in any of the signal arrival angle estimation methods described above.

[0041] A fifth aspect of the present application provides a terminal device, comprising: a processor and a memory;

[0042] The memory stores a computer-readable program executable by the processor;

[0043] When the processor executes the computer-readable program, the steps in any of the above-mentioned signal arrival angle estimation methods are implemented.

[0044] Beneficial effect: Compared with the prior art, the present application provides a coprime array and a signal arrival angle estimation method, wherein the coprime array comprises a first subarray, a second subarray and a third subarray arranged in sequence on a straight line; the first subarray comprises array elements, and the array element spacing is ; The second subarray includes array elements, and the array element spacing is ; The third subarray includes The array elements and the array element intervals are ; The adjacent array elements of the first sub-array overlap with the second sub-array, and the adjacent array elements of the second sub-array overlap with the third sub-array, wherein, , and The embodiment of the present application combines three mutually prime subarrays into a triple extended mutually prime array to strengthen the mutual prime constraints between the subarrays, thereby reducing the probability of overlapping blur angle sets between multiple subarrays and effectively suppressing the ambiguity caused by a single snapshot, thereby improving the DoA estimation performance and thus improving the target detection and positioning accuracy of the millimeter wave radar system under a single snapshot condition. BRIEF DESCRIPTION OF THE DRAWINGS

[0045] In order to more clearly illustrate the technical solutions in the embodiments of the present application, the drawings required for use in the description of the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without creative work.

[0046] Figure 1 A schematic diagram of a first sub-array, a second sub-array, and a third sub-array provided in an embodiment of the present application.

[0047] Figure 2 A schematic diagram of a coprime matrix provided in an embodiment of the present application.

[0048] Figure 3 This is a flow chart of a signal angle of arrival estimation method provided in an embodiment of the present application.

[0049] Figure 4 MUSIC spectra of the coprime linear array under different snapshots.

[0050] Figure 5 is the CBF spatial spectrum of different arrays.

[0051] Figure 6 is the root mean square error of the traversal angle VS of the second source.

[0052] Figure 7 is the traversal angle vs success rate of the second information source.

[0053] Figure 8 This is a principle block diagram of a signal angle of arrival estimation device provided in an embodiment of the present application.

[0054] Fig. 9A functional block diagram of a terminal device provided in an embodiment of the present application. DETAILED DESCRIPTION

[0055] The embodiment of the present application provides a coprime array and a signal angle of arrival estimation method. In order to make the purpose, technical solution and effect of the present application clearer and more specific, the present application is further described in detail with reference to the accompanying drawings and examples. It should be understood that the specific embodiments described here are only used to explain the present application and are not used to limit the present application.

[0056] It will be understood by those skilled in the art that, unless expressly stated, the singular forms "one", "said", and "the" used herein may also include plural forms. It should be further understood that the term "comprising" used in the specification of the present application refers to the presence of the features, integers, steps, operations, elements and / or components, but does not exclude the presence or addition of one or more other features, integers, steps, operations, elements, components and / or groups thereof. It should be understood that when we refer to an element as being "connected" or "coupled" to another element, it may be directly connected or coupled to the other element, or there may be an intermediate element. In addition, the "connection" or "coupling" used herein may include wireless connection or wireless coupling. The term "and / or" used herein includes all or any unit and all combinations of one or more associated listed items.

[0057] It will be understood by those skilled in the art that, unless otherwise defined, all terms (including technical and scientific terms) used herein have the same meaning as those generally understood by those skilled in the art to which this application belongs. It should also be understood that terms such as those defined in general dictionaries should be understood to have meanings consistent with those in the context of the prior art, and will not be interpreted with idealized or overly formal meanings unless specifically defined as here.

[0058] It should be understood that the sequence numbers and sizes of the steps in this embodiment do not mean the order of execution. The execution order of each process is determined by its function and internal logic, and should not constitute any limitation on the implementation process of the embodiment of the present application.

[0059] After research, it was found that millimeter-wave radar has become one of the indispensable sensors in the field of autonomous driving due to its excellent all-weather and all-day working capabilities. Especially in the application of on-board point cloud imaging, millimeter-wave radar can generate clear point cloud images through high-resolution range Doppler compression technology, thereby providing accurate distance and speed information for environmental perception. This high-resolution point cloud data is crucial for functions such as object detection, tracking, and obstacle avoidance in autonomous driving systems.

[0060] In order to further improve the accuracy of target positioning, Direction of Arrival (DoA) estimation technology is widely used. DoA technology estimates the target position by analyzing the incident angle of the radar signal, and is one of the important technologies for achieving high-precision point cloud imaging. In modern radar systems, sparse array structures have received increasing attention due to their larger aperture and higher resolution. Sparse array structures such as coprime arrays and nested arrays can achieve higher DoA resolution while keeping the number of antennas unchanged by reasonably arranging antenna elements. However, in practical applications, since the vehicle-mounted millimeter-wave radar system needs to process single snapshot data in real time, it has a high signal-to-noise ratio (SNR) requirement. The high signal-to-noise ratio requirement makes the existing DoA estimation method affect the accuracy of the vehicle-mounted millimeter-wave radar system that needs to process single snapshot data in real time. This is because the existing coprime array structure and DoA estimation method have the following problems:

[0061] 1. Ambiguity leakage problem: Mutually prime arrays are susceptible to ambiguity leakage under single snapshot conditions, resulting in a significant decrease in DoA estimation performance. Ambiguity leakage mainly comes from the arrangement of different antennas in the array. When the number of snapshots is insufficient, the covariance matrix of the signal cannot be accurately estimated, resulting in unreliable estimation results, which is particularly unfavorable for vehicle-mounted radar systems that only rely on a single snapshot.

[0062] 2. Dependence on multiple snapshots: Most DoA estimation methods rely on multiple snapshots to construct the covariance matrix of the signal to improve estimation accuracy. However, in actual vehicle applications, due to the need for real-time processing, the system can only obtain single snapshot data, resulting in a conflict between the need for multiple snapshots and the need for a single snapshot under high signal-to-noise ratio.

[0063] 3. Limitations of virtual array element generation: More snapshots are required to support accurate generation of virtual array elements. When there are insufficient snapshots, the generated virtual array may not accurately reflect the characteristics of the target signal, resulting in reduced DoA estimation accuracy. In addition, the generation and processing of virtual array elements will also increase the computational burden of the system, which is not conducive to vehicle-mounted radar systems with high real-time requirements.

[0064] In order to solve the above problem, an embodiment of the present application provides a coprime array, wherein the coprime array includes a first sub-array, a second sub-array and a third sub-array arranged in sequence on a straight line; the first sub-array includes array elements, and the array element spacing is ; The second subarray includes array elements, and the array element spacing is ; The third subarray includes The array elements and the array element intervals are ; The adjacent array elements of the first sub-array overlap with the second sub-array, and the adjacent array elements of the second sub-array overlap with the third sub-array, wherein, , and The embodiment of the present application combines three mutually prime subarrays into a triple extended mutually prime array to strengthen the mutual prime constraints between the subarrays, thereby reducing the probability of overlapping blur angle sets between multiple subarrays and effectively suppressing the ambiguity caused by a single snapshot, thereby improving the DoA estimation performance and thus improving the target detection and positioning accuracy of the millimeter wave radar system under a single snapshot condition.

[0065] The application content is further explained below through the description of embodiments in conjunction with the accompanying drawings.

[0066] This embodiment provides a coprime array, such as Figure 1 and Figure 2 As shown, the first sub-array is represented by "△", the second sub-array is represented by "○", and the third sub-array is represented by "◇". The first sub-array includes array elements, and the array element spacing is ; The second subarray includes array elements, and the array element spacing is ; The third subarray includes The array elements and the array element intervals are , , and The first subarray, the second subarray and the third subarray are located on a straight line; the second subarray is located after the first subarray, and the last array element of the first subarray overlaps with the starting array element of the second subarray, that is, the adjacent array elements of the first subarray overlap with the second subarray; the third subarray is located after the second subarray, and the last array element of the second subarray overlaps with the starting array element of the third subarray, that is, the adjacent array elements of the second subarray overlap with the third subarray.

[0067] The embodiment of the present application forms a triple extended coprime array by connecting three subarrays end to end to strengthen the coprime constraints between the subarrays, thereby reducing the probability of overlapping fuzzy angle sets, and thus effectively avoiding directional ambiguity when estimating the directions of multiple signal sources, thereby improving the DoA estimation performance, thereby improving the target detection and positioning accuracy of the millimeter wave radar system under single snapshot conditions.

[0068] Furthermore, the aperture of the first subarray is close to the spatial aperture of the third subarray, and the aperture of the second subarray is close to the aperture of the first subarray (for example, the difference between the aperture of the second subarray and the aperture of the first subarray is within a preset range, etc.). Thus, relative to an array with two subarrays, the additional third subarray does not increase the risk of DoA estimation ambiguity leakage, and the probability of overlap of ambiguity angles of the three subarrays is lower than that of a traditional coprime array with only two subarrays, thereby reducing the probability of overlap of ambiguity angle sets.

[0069] like Figure 1 As shown, the array element positions of the coprime array are:

[0070] ;

[0071] ;

[0072] ;

[0073] in, Indicates the total number of array elements; represents the position sequence of coprime arrays, express The The array element position of the array element, , represents the starting element position of the second subarray, Indicates the starting element position of the third subarray.

[0074] In addition, for the coprime array provided in the embodiment of the present application, in the presence of Far-field incoherent sources from different angles Arriving at the array, the single snapshot array receiving signal is modeled as:

[0075] ;

[0076] in, represents the array received signal of the coprime array, Represents coprime line series The array manifold matrix, Representative The steering vector of the source, is the wavelength; To represent the signal amplitude, represents a Gaussian white noise vector, Indicates The distance between the array element and the starting array element, .to this end, The sample covariance matrix of the received signal of the snapshot array can be expressed as:

[0077] ;

[0078] ;

[0079] ;

[0080] ;

[0081] in, represents the array received signal of the coprime array, express The conjugate of express The conjugate of represents the signal autocorrelation matrix; represents the sum of the cross-correlation matrix between different signals and the signal-noise cross-correlation matrix; represents the noise autocorrelation matrix, Indicates The received signal of a source is express The conjugation of.

[0082] In addition, in the coprime array provided in the embodiment of the present application, since the three sub-arrays of the triple extended coprime array are mutually prime, the fuzzy angles of the same angle in any two of the three sub-arrays do not overlap. , subarray and subarray The blur angle set and There will be no overlap, that is:

[0083] .

[0084] In addition, since the fuzzy position of the angle on the sparse uniform linear array is uniformly distributed in the frequency domain, for any angle ,like In the The fuzzy angle set in the sub-array is In the There are two overlapping fuzzy angles in the fuzzy angle set of the sub-matrix and , then for , there is a common blur angle in the two sub-arrays , and for any angle , subarray and subarray The blur angle set and There will be no overlap. Therefore, for any two directions, the blur angle sets generated by different sub-arrays have at most one overlapping angle, that is.

[0085] .

[0086] Furthermore, if two directions have overlapping blur angles in two sub-arrays, then the overlapping angles will not overlap with the blur angles in the remaining sub-arrays:

[0087] ;

[0088] in, .

[0089] Therefore, the probability of overlapping fuzzy angle sets between multiple subarrays is reduced in the triple extended coprime array composed of three groups of coprime subarrays compared to the coprime array composed of only two subarrays. This enables the triple extended coprime array to effectively avoid directional ambiguity when estimating the directions of multiple signal sources, thereby showing higher direction estimation accuracy in practical applications.

[0090] It is worth noting that the coprime array mentioned in the embodiment of the present application directly performs DoA processing based on a single snapshot signal, and does not rely on other sparse arrays based on multi-snap virtual array elements. Therefore, the coprime array directly processes the physical array elements, and the data dimension is smaller than the virtual array element method; and the coprime array can be directly used for single snapshot DoA estimation, which is more in line with the requirements of actual engineering (the on-board point cloud imaging processes a single snapshot high signal-to-noise ratio signal after two-dimensional compression).

[0091] Based on the above coprime array, the present application embodiment provides a signal arrival angle estimation method, such as Figure 3 As shown, the signal arrival angle estimation method specifically includes:

[0092] S10, receiving an array receiving signal of the coprime array, and obtaining a steering vector matrix of the array receiving signal;

[0093] S20, estimating an initial power spectrum of the array received signal based on the array received signal and the steering vector matrix;

[0094] S30, constructing a covariance matrix of the array received signal based on the initial power spectrum, and estimating a signal amplitude corresponding to the steering vector matrix based on the covariance matrix;

[0095] S40: Determine the signal arrival angle of the array received signal based on the signal amplitude.

[0096] Specifically, in step S10, the array receiving signal of the mutually prime array is the echo signal of the mutually prime array. Assume that Far-field incoherent sources from different angles Arriving at the coprime array, the array receiving signal of the coprime array is:

[0097] ;

[0098] in, represents the array received signal of the coprime array, Represents coprime line series The array manifold matrix, Representative The steering vector of the source, is the wavelength; To represent the signal amplitude, represents a Gaussian white noise vector, Indicates The distance between the array element and the starting array element, .

[0099] After the array receiving signal is obtained, a steering vector matrix is ​​constructed based on the array receiving signal. Specifically, when using IAA (Iterative Adaptive Approach) for DoA estimation, first set The interference matrix of a source is:

[0100] ;

[0101] in, represents mathematical expectation.

[0102] Secondly, build about The weighted least squares cost function of :

[0103] ;

[0104] ;

[0105] Again, the closed-form solution obtained by minimizing the least squares cost function is:

[0106] ;

[0107] Then the Substituting the interference matrix of each source into the closed-form solution, the closed-form solution can be simplified according to the matrix inversion theorem as follows:

[0108] ;

[0109] in, Represents the inverse matrix of the covariance matrix of the array receive signal.

[0110] To this end, the steering vector matrix It can be a diagonal matrix with the source's steering vector as the diagonal element, that is, the steering vector matrix Can be

[0111] .

[0112] Further, in step S20, after the array receive signal and the steering vector matrix are acquired, the initial power spectrum of the array receive signal may be estimated, wherein the initial power spectrum may be estimated by CBF (Conventional Beam Forming), that is, the initial power spectrum is:

[0113] ;

[0114] in, represents the initial power spectrum, Represents the steering vector matrix The conjugation of.

[0115] Further, in step S30, after the initial power spectrum is obtained, a covariance matrix of the array received signal is constructed based on the initial power spectrum, wherein the relationship between the covariance matrix and the power spectrum is:

[0116] ;

[0117] in, represents the covariance matrix, represents the power spectrum, which is a diagonal matrix with the main diagonal elements given by composition.

[0118] To this end, after obtaining the initial power spectrum and the steering vector matrix, the covariance matrix can be determined according to the steering vector matrix and the initial power spectrum, and then the signal amplitude can be obtained according to the covariance matrix, where the corresponding relationship between the signal amplitude and the covariance matrix can be:

[0119] ;

[0120] in, Indicates the signal amplitude.

[0121] In addition, after estimating the signal amplitude, the signal arrival angle can be estimated directly according to the estimated signal amplitude, or the covariance matrix can be reconstructed based on the estimated signal amplitude, and then the signal amplitude can be updated based on the reconstructed covariance matrix. Based on this, constructing the covariance matrix of the array received signal based on the initial power spectrum, and estimating the signal amplitude corresponding to the steering vector matrix based on the covariance matrix specifically includes:

[0122] Constructing a covariance matrix of the array received signal based on the initial power spectrum, and using the covariance matrix as an initial covariance matrix;

[0123] estimating a signal amplitude corresponding to the steering vector matrix based on the initial covariance matrix;

[0124] Constructing a target power spectrum based on the signal amplitude, and constructing a target covariance matrix of the array received signal according to the target power spectrum;

[0125] The target covariance matrix is ​​used as an initial covariance matrix, and the step of estimating the signal amplitude corresponding to the steering vector matrix based on the initial covariance matrix is ​​re-executed until a preset end condition is reached to obtain the signal amplitude corresponding to the steering vector matrix.

[0126] Specifically, the signal amplitude corresponding to the steering vector matrix is ​​the last signal amplitude until the preset end condition is reached. The end condition is preset, and can be a preset number threshold, or the difference between the signal amplitudes of two adjacent estimates is less than a preset difference threshold, etc. In the embodiment of the present application, the end condition is that the difference between the signal amplitudes of two adjacent estimates is less than the preset difference threshold, that is, the end condition is:

[0127] ;

[0128] in, Indicates The estimated signal amplitude, express The estimated signal amplitude, Indicates the preset error threshold.

[0129] Further, in step S40, after the signal amplitude is obtained, a power spectrum is determined based on the signal amplitude, and then a spectrum peak search is performed on the power spectrum to obtain the signal arrival angle.

[0130] In summary, this embodiment provides a signal arrival angle estimation method, the method comprising receiving the array receiving signal of the coprime array, and obtaining the steering vector matrix of the array receiving signal; estimating the initial power spectrum of the array receiving signal based on the array receiving signal and the steering vector matrix; constructing the covariance matrix of the array receiving signal based on the initial power spectrum, and estimating the signal amplitude corresponding to the steering vector matrix based on the covariance matrix; determining the signal arrival angle of the array receiving signal based on the signal amplitude. The embodiment of the present application adopts a coprime array composed of three subarrays to receive echo information, and then estimates the signal arrival angle based on the array receiving signal of the coprime array, which improves the ambiguity problem caused by the cross-correlation components of multi-source signals in a single snapshot scenario, thereby achieving high-precision DoA estimation.

[0131] In addition, in order to verify the cause of the ambiguity in DoA estimation of the coprime array under a single snapshot and the effectiveness of the proposed improved coprime array for single snapshot DoA estimation, the embodiments of the present application also analyze and verify the cause of the ambiguity of the coprime linear array and the extended coprime linear array, as well as the effectiveness of the improved coprime array proposed in this article.

[0132] Experiment 1: Blur leakage experiment

[0133] Consider two far-field sources arriving from 0° and 20° respectively. and The coprime line series, signal-to-noise ratio is 20dB, and the MUSIC (Multiple Signal Classification) spectrum under different snapshots is estimated. The results are as follows Figure 4 As shown in Figure 2, it can be seen that under the condition of sufficient snapshots, the coprime linear array can perform unambiguous DoA estimation. When the number of snapshots is only 2, it can be observed that The fuzzy leakage phenomenon caused by this phenomenon is the existence of a pseudo peak with a height close to the true spectral peak.

[0134] Experiment 2: Blur suppression experiment

[0135] In order to investigate the effect of improving the coprime array on suppressing blur leakage, the sizes of the two uniform subarrays of the coprime array and the extended coprime array are set to and , the sizes of the three uniform subarrays of the improved coprime array are set to , and , the signal-to-noise ratio is 20dB. The experimental results are as follows Figure 5As shown, the traditional coprime array and the extended coprime array have two angle blurs and incorrectly estimate the angle of the true value. However, the spatial spectrum of the coprime array (denoted as the proposed array) proposed in the embodiment of the present application does not have angle blur and accurately forms a spectrum peak at the true value. Therefore, the proposed array can effectively suppress the angle blur caused by the coprime array due to a single snapshot.

[0136] Experiment 3: Blur Angle Distribution

[0137] The subarray sizes of the coprime linear array and the extended coprime linear array are both set to and The DoA of two far-field sources in space is estimated. The DoA of the first source is fixed at 0°, and the DoA of the second source is traversed from -90° to 90° with an interval of 0.5°. Monte Carlo experiment. The root mean square error between the DoA estimate and the true value is:

[0138] ;

[0139] Will A Monte Carlo experiment is defined as a success. Figure 6 From (a) and (b) in the figure, we can see that the DoA estimation of the second source fails at multiple angles, which shows that the DoA fuzzy overflow phenomenon is common in traditional coprime arrays and extended coprime arrays under single snapshot. Figure 6 In (c), the proposed array is estimated only at angles close to And the failure of the second source when the angle coincides with the first source verifies the robustness and effectiveness of the proposed array in suppressing blur overflow. Figure 7 The DoA estimation success rate of each array in the , further verifies the stability of the proposed array DoA estimation.

[0140] Based on the above signal arrival angle estimation method, this embodiment provides a signal arrival angle estimation device, which adopts the above coprime array, such as Figure 8 As shown, the signal arrival angle estimation device specifically includes:

[0141] A receiving module 100, configured to receive an array receiving signal of the coprime array and obtain a steering vector matrix of the array receiving signal;

[0142] An estimation module 200, configured to estimate an initial power spectrum of the array received signal based on the array received signal and the steering vector matrix;

[0143] A construction module 300, configured to construct a covariance matrix of the array received signal based on the initial power spectrum, and estimate a signal amplitude corresponding to the steering vector matrix based on the covariance matrix;

[0144] The search module 400 is configured to determine the signal arrival angle of the array received signal based on the signal amplitude.

[0145] Based on the above-mentioned signal arrival angle estimation method, this embodiment provides a computer-readable storage medium, which stores one or more programs. The one or more programs can be executed by one or more processors to implement the steps in the signal arrival angle estimation method as described in the above-mentioned embodiment.

[0146] Based on the above signal arrival angle estimation method, the present application also provides a terminal device, such as Fig. 9 As shown, it includes at least one processor 20; a display screen 21; and a memory 22, and may also include a communications interface 23 and a bus 24. The processor 20, the display screen 21, the memory 22, and the communications interface 23 may communicate with each other through the bus 24. The display screen 21 is configured to display a preset user guide interface in the initial setting mode. The communications interface 23 may transmit information. The processor 20 may call the logic instructions in the memory 22 to execute the method in the above embodiment.

[0147] In addition, the logic instructions in the memory 22 can be implemented in the form of software functional units and can be stored in a computer-readable storage medium when sold or used as an independent product.

[0148] The memory 22 is a computer-readable storage medium that can be configured to store software programs, computer executable programs, such as program instructions or modules corresponding to the methods in the embodiments of the present disclosure. The processor 20 executes functional applications and data processing by running the software programs, instructions or modules stored in the memory 22, that is, implementing the methods in the above embodiments.

[0149] The memory 22 may include a program storage area and a data storage area, wherein the program storage area may store an operating system and at least one application required for a function; the data storage area may store data created according to the use of the terminal device, etc. In addition, the memory 22 may include a high-speed random access memory and may also include a non-volatile memory. For example, a variety of media that can store program codes, such as a USB flash drive, a mobile hard disk, a read-only memory (ROM), a random access memory (RAM), a disk or an optical disk, may also be a transient storage medium.

[0150] In addition, the specific process of loading and executing the multiple instruction processors in the above-mentioned storage medium and the terminal device has been described in detail in the above-mentioned method, and will not be described one by one here.

[0151] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present application, rather than to limit it. Although the present application has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the aforementioned embodiments, or make equivalent replacements for some of the technical features therein. However, these modifications or replacements do not deviate the essence of the corresponding technical solutions from the spirit and scope of the technical solutions of the embodiments of the present application.

Claims

1. A signal arrival angle estimation method, characterized in that: A coprime array is used, and the coprime array directly processes the physical array elements to estimate the single snapshot DoA; the signal arrival angle estimation method specifically includes: receiving an array receive signal of a mutually prime array, and obtaining a steering vector matrix of the array receive signal; estimating an initial power spectrum of the array received signal based on the array received signal and the steering vector matrix; constructing a covariance matrix of the array received signal based on the initial power spectrum, and estimating a signal amplitude corresponding to the steering vector matrix based on the covariance matrix; determining a signal angle of arrival of a signal received by the array based on the signal amplitude; The coprime array includes a first sub-array, a second sub-array and a third sub-array arranged in sequence on a straight line; the first sub-array includes array elements, and the array element spacing is ; The second subarray includes array elements, and the array element spacing is ; The third subarray includes The array elements and the array element intervals are ; The adjacent array elements of the first sub-array overlap with the second sub-array, and the adjacent array elements of the second sub-array overlap with the third sub-array, wherein, , and Two are mutually prime, Indicates a rounding operation.

2. The signal arrival angle estimation method according to claim 1, characterized in that: The array element positions of the coprime array are: in, Indicates the total number of array elements; represents the position sequence of coprime arrays, Indicates The array element position of the array element, , represents the starting element position of the second subarray, Indicates the starting element position of the third subarray.

3. The signal arrival angle estimation method according to claim 2, characterized in that: for Far-field incoherent sources from different angles Arriving at the coprime array, the covariance matrix of the coprime array under a single snapshot is: in, represents the array received signal of the coprime array, express The conjugate of Represents coprime arrays The array manifold matrix, Indicates The steering vector of the source, represents the wavelength, represents the signal amplitude, represents a Gaussian white noise vector, express The conjugate of represents the signal autocorrelation matrix; represents the sum of the cross-correlation matrix between different signals and the signal-noise cross-correlation matrix; represents the noise autocorrelation matrix, Indicates The received signal of a source is express The conjugate of Indicates The distance between the array element and the starting array element, .

4. The signal arrival angle estimation method according to claim 1, characterized in that: The constructing a covariance matrix of the array received signal based on the initial power spectrum, and estimating a signal amplitude corresponding to the steering vector matrix based on the covariance matrix specifically includes: Constructing a covariance matrix of the array received signal based on the initial power spectrum, and using the covariance matrix as an initial covariance matrix; estimating a signal amplitude corresponding to the steering vector matrix based on the initial covariance matrix; Constructing a target power spectrum based on the signal amplitude, and constructing a target covariance matrix of the array received signal according to the target power spectrum; The target covariance matrix is ​​used as an initial covariance matrix, and the step of estimating the signal amplitude corresponding to the steering vector matrix based on the initial covariance matrix is ​​re-executed until a preset end condition is reached to obtain the signal amplitude corresponding to the steering vector matrix.

5. The signal arrival angle estimation method according to claim 4, characterized in that: The end conditions are: in, Indicates The estimated signal amplitude, express The estimated signal amplitude, Indicates the preset error threshold.

6. The signal arrival angle estimation method according to claim 1, characterized in that: The calculation formula of the signal amplitude is: in, represents the signal amplitude, represents the steering vector matrix, represents the inverse of the covariance matrix, Indicates that the array receives the signal.

7. A signal arrival angle estimation device, characterized in that: A coprime array is used, and the coprime array directly processes the physical array elements to estimate the single snapshot DoA; the signal arrival angle estimation device specifically includes: A receiving module, used for receiving an array receiving signal of the coprime array and obtaining a steering vector matrix of the array receiving signal; an estimation module, configured to estimate an initial power spectrum of the array received signal based on the array received signal and the steering vector matrix; A construction module, configured to construct a covariance matrix of the array received signal based on the initial power spectrum, and estimate a signal amplitude corresponding to the steering vector matrix based on the covariance matrix; A search module, configured to determine a signal arrival angle of the array received signal based on the signal amplitude; The coprime array includes a first sub-array, a second sub-array and a third sub-array arranged in sequence on a straight line; the first sub-array includes array elements, and the array element spacing is ; The second subarray includes array elements, and the array element spacing is ; The third subarray includes The array elements and the array element intervals are ; The adjacent array elements of the first sub-array overlap with the second sub-array, and the adjacent array elements of the second sub-array overlap with the third sub-array, wherein, , and Two are mutually prime, Indicates a rounding operation.

8. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores one or more programs, and the one or more programs can be executed by one or more processors to implement the steps in the signal arrival angle estimation method according to any one of claims 1 to 6.

9. A terminal device, characterized in that: include: Processor and memory; The memory stores a computer-readable program executable by the processor; When the processor executes the computer-readable program, the steps in the signal arrival angle estimation method according to any one of claims 1 to 6 are implemented.

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