Method for estimating direction of arrival of time-domain carrier-frequency-free ultra-wideband system

Abstract

The invention particularly relates to a method for estimating the direction of arrival of a time-domain carrier-frequency-free ultra-wideband system. The method comprises the following steps: acquiring carrier-frequency-free ultra-wideband signals of a plurality of signal sources located in a far-field space at a plurality of moments; constructing an output signal matrix according to the receiving antenna array; based on the output signal matrix, obtaining antenna array frequency domain data through Fourier transform, and constructing a frequency domain array receiving matrix of each frequency point; introducing a delay tap, constructing a time delay vector of each frequency point, obtaining pseudo sampling frequency domain array receiving data of each frequency point, performing characteristic decomposition on the pseudo sampling frequency domain array receiving data to obtain a characteristic value of each frequency point, and determining a signal subspace matrix and a noise subspace matrix of each frequency point; setting an angle search range, constructing a pseudo frequency domain direction vector, obtaining spatial spectrum distribution under each frequency point, and summing and superposing the spatial spectrum distribution; and setting a corresponding detection threshold to carry out angle measurement to obtain a signal source incident angle. According to the method, the problem of insufficient resolution of the direction of arrival estimation method of the carrier-frequency-free ultra-wideband system can be solved.

Description

Technical Field

[0001] The present invention relates to the technical field of signal processing, and in particular to a time-domain carrier-free ultra-wideband system direction of arrival estimation method. Background Art

[0002] Since its introduction, the impact pulse system, a member of the ultra-wideband (UWB) family, has seen widespread application due to its advantages, including high range resolution, small close-range blind spots, strong penetration, robust anti-interference capabilities, and low probability of intercept. As a novel UWB system, implementing direction-of-arrival (DOA) estimation in medium- and long-range applications is crucial for its practical application. DOA estimation techniques, which process echo information in complex spaces to determine target angles, are a key research area in array signal processing.

[0003] Due to constraints such as array structure, beamforming (DBF) has become a key research area for DOA estimation. Essentially, DBF is spatial filtering, enhancing signals in specific regions while suppressing signals elsewhere. However, DBF is limited by the Rayleigh limit, making it impossible to distinguish multiple signals within the same beam in space, effectively preventing DOA estimation. Researchers have proposed numerous direction-finding methods that are not subject to Rayleigh constraints, significantly improving the stability and accuracy of DOA estimation. In particular, DOA estimation methods for super-resolution narrowband signal arrays, such as the MUSIC algorithm and the ESPRIT algorithm, are well established. Compared to narrowband signals, DOA estimation in wideband systems is closely related to signal frequency, leaving much room for research in estimation algorithms. Common wideband DOA estimation methods include the coherent signal subspace (CSM) and incoherent subspace (ISM) algorithms.

[0004] The resolution of DOA estimation depends on the array's aperture size, number of elements, and number of snapshots. Impulse pulse systems emit sub-nanosecond pulses with bandwidths exceeding GHz and no carrier frequency information. The echo signals cannot be spectrally separated in the time domain using short-time Fourier transforms (SFTs). Traditional DOA estimation methods used in broadband systems are unusable, and the simplest approach is to use time-domain DBF (Deep Fourier Transformation) for angle measurement. Because it's impossible to infinitely change the physical size and configuration of the array elements, the accuracy and resolution of angle measurements using time-domain DBF are far inferior to those of conventional radars using super-resolution algorithms. Research on DOA estimation in carrier-free ultra-wideband systems is limited.

[0005] It should be noted that the information disclosed in the above background technology section is only used to enhance the understanding of the background of the present invention, and therefore may include information that does not constitute prior art known to ordinary technicians in this field. Summary of the Invention

[0006] The present invention provides a time domain carrier-free ultra-wideband system direction of arrival estimation method, which is used to solve the problem of insufficient resolution of the carrier-free ultra-wideband system direction of arrival estimation method.

[0007] Other features and advantages of the present invention will become apparent from the following detailed description, or may be learned in part by practice of the present invention.

[0008] According to a first aspect of the present invention, a method for estimating direction of arrival of a time-domain carrier-free ultra-wideband system is provided, the method comprising:

[0009] Acquiring carrier-free ultra-wideband signals at multiple times from multiple signal sources located in a far-field space;

[0010] According to the receiving antenna array, an output signal matrix is ​​constructed based on the carrier-free ultra-wideband signal;

[0011] Based on the output signal matrix, obtaining antenna array frequency domain data through Fourier transform;

[0012] Using the antenna array frequency domain data, constructing a frequency domain array receiving matrix for each frequency point;

[0013] Introduce delay taps to construct the delay vector of each frequency point;

[0014] Using the time delay vectors of each frequency point, constructing a pseudo-sampling frequency domain array to receive data at each frequency point;

[0015] Receive data according to the pseudo-sampling frequency domain array of each frequency point, obtain the pseudo-data covariance matrix of each frequency point, and perform eigendecomposition on the pseudo-data covariance matrix to obtain the eigenvalue of each frequency point;

[0016] The number of signal sources is determined based on the eigenvalues ​​of each frequency point, and the signal subspace matrix and the noise subspace matrix of each frequency point are determined;

[0017] Setting an angle search range, constructing a frequency domain direction vector for each frequency point at different angles, and using the delay vector of each frequency point to obtain a pseudo frequency domain direction vector for each frequency point at different angles;

[0018] Performing spectrum peak search using the noise subspace matrix and the pseudo-frequency domain direction vector at each frequency point to obtain the spatial spectrum distribution at each frequency point;

[0019] The spatial spectrum distribution at each frequency point is summed and superimposed, and a corresponding detection threshold is set to perform angle measurement to obtain the incident angle of the signal source.

[0020] In some exemplary embodiments, the output signal matrix may be represented as:

[0021]

[0022] Among them, x m (t) is the data observed by the mth antenna, s n (t) represents the echo signal of the nth target received by the reference array element, n m (t) represents the noise component received by the mth array element; τ mn is the time delay of the echo signal of the nth target received by the mth array element relative to s(t), which is determined by the array structure and the target echo incident angle.

[0023] In some exemplary embodiments, the antenna array frequency domain data may be represented as:

[0024]

[0025] Among them, X m (ω) is x m (t) Frequency domain data after Fourier transformation, S n (ω) is s n (t) Frequency domain data after Fourier transform, For s n (t-τ mn )Frequency domain data after Fourier transformation, N m (ω) is n m (t) Frequency domain data after Fourier transform.

[0026] In some exemplary embodiments, the frequency domain array receiving matrix of each frequency point is expressed as:

[0027]

[0028] Without considering the noise, it can be written in vector form as:

[0029] X0(ω)=A(ω)S(ω)

[0030] in,

[0031] A(ω)=[a1(ω) a2(ω) … a N (ω)] is the direction matrix at each frequency point;

[0032] S(ω)=[S1(ω) S2(ω) … S N (ω)] T is the frequency domain array receiving matrix of each frequency point;

[0033] is the frequency domain direction vector of each frequency point at different angles.

[0034] In some exemplary embodiments, the delay vector of each frequency point is expressed as:

[0035]

[0036] Among them, T d To delay the time, a delay of point L is introduced after each channel.

[0037] In some exemplary embodiments, the pseudo-sampling frequency domain array received data at each frequency point is represented as:

[0038]

[0039] in, is the pseudo snapshot vector, is the Kronecker product.

[0040] In some exemplary embodiments, the pseudo data covariance matrix of each frequency point is expressed as:

[0041]

[0042] in, is the signal feature vector matrix, is the noise feature vector matrix, is the signal eigenvalue diagonal matrix, is the noise eigenvalue diagonal matrix.

[0043] In some exemplary embodiments, the pseudo-frequency domain direction vector of each frequency point is expressed as:

[0044]

[0045] In some exemplary embodiments, the spatial spectrum distribution at each frequency point is expressed as:

[0046]

[0047] According to a second aspect of the present invention, a storage medium is provided, on which a computer program is stored. When the computer program is executed by a processor, the method for estimating the direction of arrival of a time-domain carrier-free ultra-wideband system according to the first aspect is implemented.

[0048] According to a third aspect of the present invention, a computer program product is provided, on which a computer program is stored. When the computer program is executed by a processor, the method for estimating the direction of arrival of a time-domain carrier-free ultra-wideband system according to the first aspect is implemented.

[0049] According to a fourth aspect of the present invention, there is provided an electronic device, comprising:

[0050] processor; and

[0051] a memory for storing executable instructions of the processor;

[0052] The processor is configured to implement the time-domain carrier-free ultra-wideband system direction of arrival estimation method described in the first aspect above by executing the executable instructions.

[0053] The embodiment of the present invention provides a time-domain carrier-free ultra-wideband system direction of arrival estimation method. First, carrier-free ultra-wideband signals at multiple times of multiple signal sources located in a far-field space are obtained. Then, an output signal matrix is ​​constructed according to a receiving antenna array. Based on the output signal matrix, frequency domain data of the antenna array is obtained through Fourier transform, and a frequency domain array receiving matrix of each frequency point is constructed. Delay taps are introduced to construct a time delay vector of each frequency point, pseudo-sampled frequency domain array receiving data of each frequency point is obtained, and eigenvalues ​​of each frequency point are obtained by eigendecomposition, and a signal subspace matrix and a noise subspace matrix of each frequency point are determined. An angle search range is set, a pseudo frequency domain direction vector is constructed, and a spatial spectrum distribution at each frequency point is obtained, which is summed and superimposed. Finally, a corresponding detection threshold is set to perform angle measurement to obtain the incident angle of the signal source.

[0054] The carrier-free ultra-wideband system uses carrier-free Gaussian pulses and fully utilizes the angle measurement function of the array antenna. When the echo signal cannot be spectrally separated in the time domain through short-time Fourier transform and the DOA estimation method in the traditional broadband system cannot be used, super-resolution estimation of the direction of arrival is achieved by combining delayed taps and spectral peak summation search.

[0055] It is to be understood that the foregoing general description and the following detailed description are exemplary and explanatory only and are not restrictive of the invention. BRIEF DESCRIPTION OF THE DRAWINGS

[0056] The accompanying drawings are incorporated into and constitute a part of this specification, illustrate embodiments consistent with the present invention, and together with the description, serve to explain the principles of the present invention. Obviously, the drawings described below are only some embodiments of the present invention, and it is clear that those skilled in the art can derive other drawings based on these drawings without inventive effort.

[0057] Figure 1 Schematic diagram of the flow chart of the high-precision time-domain carrier-free ultra-wideband system direction of arrival estimation method of the present invention;

[0058] Figure 2 It is the uniform linear array structure model of the present invention;

[0059] Figure 3 Schematic diagram of a carrier-free Gaussian pulse signal according to the present invention;

[0060] Figure 4 Schematic diagram of original echo data of the present invention;

[0061] Figure 5 is the spatial spectrum distribution result at each frequency point of the present invention;

[0062] Figure 6 is the spatial spectrum distribution result under the summing frequency point of the present invention;

[0063] Figure 7 is the direction of arrival estimation result of the present invention;

[0064] Figure 8 The figure shows the comparison results between the direction of arrival estimation method of the present invention and the DBF angle measurement method. DETAILED DESCRIPTION

[0065] Example embodiments will now be described more fully with reference to the accompanying drawings. However, example embodiments can be embodied in many forms and should not be construed as limited to the examples set forth herein; rather, these embodiments are provided so that this disclosure will be thorough and complete and will fully convey the concepts of the example embodiments to those skilled in the art. The described features, structures, or characteristics may be combined in any suitable manner in one or more embodiments.

[0066] In addition, the accompanying drawings are merely schematic illustrations of the present invention and are not necessarily drawn to scale. Identical reference numerals in the figures denote identical or similar parts, and thus repetitive descriptions thereof will be omitted. Some of the blocks shown in the accompanying drawings are functional entities that do not necessarily correspond to physically or logically separate entities. These functional entities may be implemented in software, in one or more hardware modules or integrated circuits, or in different networks and / or processor devices and / or microcontroller devices.

[0067] In view of the shortcomings and deficiencies of the prior art, this example embodiment provides a new high-precision phase time domain carrier-free ultra-wideband system direction of arrival estimation method, referring to Figure 1 As shown, the following steps may be specifically included:

[0068] Step S01: acquiring carrier-free ultra-wideband signals at multiple moments from multiple signal sources located in a far-field space;

[0069] The carrier-free ultra-wideband system is a multi-transmitter and multi-receiver uniform antenna array with an antenna spacing of d and an angle measurement function with an angle measurement range of no more than -80° to 80°;

[0070] Step S02: construct an output signal matrix based on the receiving antenna array, which is expressed as:

[0071]

[0072] Among them, x m(t) is the data observed by the mth antenna, s n (t) represents the echo signal of the nth target received by the reference array element, n m (t) represents the noise component received by the mth array element, τ mn is the time delay of the echo signal of the nth target received by the mth array element relative to s(t), which is determined by the array structure and the target echo incident angle.

[0073] Step S03: Based on the output signal matrix, obtain antenna array frequency domain data through Fourier transform, which is expressed as:

[0074]

[0075] Among them, X m (ω) is x m (t) Frequency domain data after Fourier transformation, S n (ω) is s n (t) Frequency domain data after Fourier transform, For s n (t-τ mn )Frequency domain data after Fourier transformation, N m (ω) is n m (t) Frequency domain data after Fourier transform.

[0076] Step S04: Using the antenna array frequency domain data, construct a frequency domain array receiving matrix for each frequency point, expressed as:

[0077]

[0078] Without considering the noise, it can be written in vector form as:

[0079] X0(ω)=A(ω)S(ω)

[0080] in,

[0081] A(ω)=[a1(ω) a2(ω) … a N (ω)] is the direction matrix at each frequency point;

[0082] S(ω)=[S1(ω) S2(ω) … S N (ω)] T is the frequency domain array receiving matrix of each frequency point;

[0083] is the frequency domain direction vector of each frequency point at different angles.

[0084] Step S05: introduce delay taps to construct the delay vector of each frequency point, expressed as:

[0085]

[0086] Among them, T d To delay the time, a delay of point L is introduced after each channel.

[0087] Step S06: Using the delay vectors of each frequency point, construct a pseudo-sampling frequency domain array receiving data of each frequency point, which is expressed as:

[0088]

[0089] in, is a pseudo snapshot vector, which is a LM×1 dimensional vector; ” is the Kronecker product, defined as:

[0090]

[0091] Step S07: Receive data according to the pseudo-sampling frequency domain array of each frequency point, obtain the pseudo-data covariance matrix of each frequency point, and perform eigendecomposition on it to obtain the eigenvalue of each frequency point; wherein the pseudo-data covariance matrix is ​​expressed as:

[0092]

[0093] Step S08: judging the number of signal sources based on the eigenvalues ​​of each frequency point, and determining the signal subspace matrix and noise subspace matrix of each frequency point;

[0094] Step S09: Set the angle search range, construct the frequency domain direction vector of each frequency point at different angles, and use the delay vector of each frequency point to obtain the pseudo frequency domain direction vector of each frequency point at different angles, expressed as:

[0095]

[0096] Step S10: Use the noise subspace matrix and the pseudo-frequency domain direction vector at each frequency point to perform spectrum peak search to obtain the spatial spectrum distribution at each frequency point, which is expressed as:

[0097]

[0098] Step S11: sum and superimpose the spatial spectrum distribution at each frequency point, which is expressed as:

[0099]

[0100] Set the corresponding detection threshold to perform angle measurement and obtain the incident angle of the signal source.

[0101] Below, each step in this exemplary implementation will be described in more detail with reference to the accompanying drawings and embodiments.

[0102] Example 1

[0103] In the embodiment of the present invention, a uniform linear array with M elements is considered, and the element spacing is d. In a rectangular coordinate system, it is assumed that the uniform linear array is located on the x-axis, the first element is located at the origin of the coordinate system, and the first element is set as the delay reference point, such as Figure 2 As shown. N far-field narrowband signals are represented by θ={θ1,θ2,…,θ N} is incident on a uniform linear array, θ is the angle between the incident signal and the x-axis. The position vector of m array elements is ((m-1)d,0,0), and the unit wave vector of the incident signal is -(cosθ n ,sinθ n ,0), then the time delay τ of the nth signal when it propagates from the delay reference point to the mth array element mn It can be expressed as:

[0104]

[0105] In the embodiment of the present invention, the carrier-free ultra-wideband system adopts a carrier-free Gaussian pulse, and the transmitted carrier-free Gaussian pulse signal is expressed as:

[0106]

[0107] Where Γ is the pulse shaping factor and is related to the pulse width. In the embodiment, the reflected pulse width of the carrier-free ultra-wideband system is 1 ns, the scanning angle range is -90° to 90°, the sampling rate fs = 6 GHz, the number of antenna elements M = 10, the antenna spacing d = 0.3 m, the number of delay taps L = 10, the delay time Td = 100 / fs, and the transmitted pulse waveform is as follows: Figure 3 shown.

[0108] The specific steps are as follows:

[0109] Step S01: Acquire multiple time instants of carrier-free ultra-wideband signals from multiple signal sources in the far-field space, ie {x 1(t) ,x2(t),…,x M (t)};

[0110] In this embodiment, there are two signal sources in the far field space, namely N=2, with incident angles of 10° and 13° respectively. The original echo is as follows: Figure 4 shown.

[0111] Step S02: construct an output signal matrix based on the receiving antenna array, which is expressed as:

[0112]

[0113] Among them, x m(t) is the data observed by the mth antenna, s n (t) represents the echo signal of the nth target received by the reference array element, n m (t) represents the noise component received by the mth array element, τ mn is the time delay of the echo signal of the nth target received by the mth array element relative to s(t), which is determined by the array structure and the target echo incident angle.

[0114] Step S03: Based on the output signal matrix, obtain the antenna array frequency domain data through Fourier transform, which is expressed as:

[0115]

[0116] Among them, X m (ω) is x m (t) Frequency domain data after Fourier transformation, S n (ω) is s n (t) Frequency domain data after Fourier transform, For s n (t-τ mn )Frequency domain data after Fourier transformation, N m (ω) is n m (t) Frequency domain data after Fourier transform.

[0117] Step S04: Use the antenna array frequency domain data to construct a frequency domain array receiving matrix for each frequency point, which is expressed as:

[0118]

[0119] Without considering the noise, it can be written in vector form as:

[0120] X0(ω)=A(ω)S(ω)

[0121] in,

[0122] A(ω)=[a1(ω) a2(ω) … a N (ω)] is the direction matrix at each frequency point;

[0123] S(ω)=[S1(ω) S2(ω) … S N (ω)] T is the frequency domain array receiving matrix of each frequency point;

[0124] is the frequency domain direction vector of each frequency point at different angles.

[0125] Step S05: introduce delay taps to construct the delay vector of each frequency point, expressed as:

[0126]

[0127] Among them, T d To delay the time, a delay of point L is introduced after each channel.

[0128] Step S06: Using the delay vector of each frequency point, construct a pseudo-sampling frequency domain array to receive data of each frequency point, which is expressed as:

[0129]

[0130] in, is a pseudo snapshot vector, which is a LM×1 dimensional vector; ” is the Kronecker product, defined as:

[0131]

[0132] Step S07: Receive data according to the pseudo-sampling frequency domain array of each frequency point, obtain the pseudo-data covariance matrix of each frequency point, and perform eigendecomposition on it to obtain the eigenvalue of each frequency point; wherein the pseudo-data covariance matrix is ​​expressed as:

[0133]

[0134] in, is the signal feature vector matrix, is the noise feature vector matrix, is the signal eigenvalue diagonal matrix, is the noise eigenvalue diagonal matrix.

[0135] Step S08: judging the number of signal sources based on the eigenvalues ​​of each frequency point, and determining the signal subspace matrix and noise subspace matrix of each frequency point;

[0136] Step S09: Set the angle search range, construct the frequency domain direction vector of each frequency point at different angles, and use the delay vector of each frequency point to obtain the pseudo frequency domain direction vector of each frequency point at different angles, expressed as:

[0137]

[0138] Step S10: Use the noise subspace matrix and the pseudo-frequency domain direction vector at each frequency point to perform spectrum peak search to obtain the spatial spectrum distribution at each frequency point, which is expressed as:

[0139]

[0140] In this embodiment, the spatial spectrum distribution results at each frequency point are as follows: Figure 5 shown.

[0141] Step S11: sum and superimpose the spatial spectrum distribution at each frequency point, which is expressed as:

[0142] SP MUSIC =∑P MUSIC (ω i ,θ)

[0143] Set the corresponding detection threshold to perform angle measurement and obtain the incident angle of the signal source.

[0144] In this embodiment, the spatial spectrum distribution results at each frequency point are summed, such as Figure 6 The summation result is shown in Figure 6 , the detection threshold is set to -3dB. As can be seen from the figure, the number of angles that meet the detection threshold is 2, and the angles are 10° and 13° respectively, which are consistent with the initial setting values ​​of the simulation.

[0145] As a comparison of technical effects, it can be combined with existing technologies for reference. Figure 8 The time domain DBF angle measurement simulation results using the simulation parameters of Example 1 are shown in Figure 2. Figure 7 In comparison, the angles of the two signal sources are limited by the Rayleigh limit and cannot be distinguished, which makes them unsuitable for use scenarios requiring super-resolution angle measurement.

[0146] In summary, the carrier-free ultra-wideband system uses carrier-free Gaussian pulses and fully utilizes the angle measurement function of the array antenna. When the echo signal cannot be spectrally separated in the time domain through short-time Fourier transform and the DOA estimation method in the traditional broadband system cannot be used, super-resolution estimation of the direction of arrival is achieved by combining delayed taps and spectral peak summation search. This solves the problems of the direction of arrival estimation method in the traditional broadband system being unusable and the inability of time-domain DBF angle measurement to break through the Rayleigh limit.

[0147] The flowcharts and block diagrams in the accompanying drawings illustrate the possible implementation architecture, functions and operations of the systems, methods and computer program products according to various embodiments of the present invention. In this regard, each box in the flowchart or block diagram can represent a module, program segment, or a part of code, and the above-mentioned module, program segment, or a part of code contains one or more executable instructions for implementing the specified logical function. It should also be noted that in some alternative implementations, the functions marked in the box can also occur in an order different from that marked in the accompanying drawings. For example, two boxes represented in succession can actually be executed substantially in parallel, and they can sometimes be executed in the opposite order, depending on the functions involved. It should also be noted that each box in the block diagram or flowchart, and the combination of boxes in the block diagram or flowchart, can be implemented with a dedicated hardware-based system that performs the specified function or operation, or can be implemented with a combination of dedicated hardware and computer instructions.

[0148] The units involved in the embodiments of the present invention may be implemented in software or hardware, and the units described may also be provided in a processor. In some cases, the names of these units do not limit the units themselves.

[0149] It should be noted that, as another aspect, the present application also provides a storage medium, which can be included in an electronic device; or it can exist independently without being installed in the electronic device. The above storage medium carries one or more programs, and when the above one or more programs are executed by an electronic device, the electronic device implements the method described in the following embodiments. For example, the electronic device can implement the following Figure 1 The individual steps of the method are shown.

[0150] In one embodiment, the present application provides a computer program product, including a computer program, which implements the steps in the above-mentioned method embodiments when executed by a processor.

[0151] Furthermore, the above-described figures are merely illustrative of the processes included in the method according to exemplary embodiments of the present invention and are not intended to be limiting. It is readily understood that the processes illustrated in the above-described figures do not indicate or limit the temporal order of these processes. Furthermore, it is readily understood that these processes may be executed synchronously or asynchronously, for example, in multiple modules.

[0152] Other embodiments of the present invention will readily occur to those skilled in the art after considering the specification and practicing the invention herein. This application is intended to cover any variations, uses, or adaptations of the present invention that follow the general principles of the invention and include common knowledge or customary techniques in the art not disclosed herein. The description and examples are to be considered as exemplary only, with the true scope and spirit of the invention being indicated by the claims.

[0153] It should be understood that the present invention is not limited to the exact construction described above and shown in the drawings and that various modifications and variations can be made without departing from the scope thereof, which is limited only by the appended claims.

Claims

1. A method for estimating the direction of arrival of a time-domain carrier-free ultra-wideband system, characterized in that: The transmission waveform of the carrier-free ultra-wideband system is a carrier-free Gaussian pulse, and the method includes: Acquiring carrier-free ultra-wideband signals at multiple times from multiple signal sources located in a far-field space; According to the receiving antenna array, an output signal matrix is ​​constructed based on the carrier-free ultra-wideband signal; Based on the output signal matrix, obtaining antenna array frequency domain data through Fourier transform; Using the antenna array frequency domain data, constructing a frequency domain array receiving matrix for each frequency point; Introduce delay taps to construct the delay vector of each frequency point; Using the time delay vectors of each frequency point, constructing a pseudo-sampling frequency domain array to receive data at each frequency point; Receive data according to the pseudo-sampling frequency domain array of each frequency point, obtain the pseudo-data covariance matrix of each frequency point, and perform eigendecomposition on the pseudo-data covariance matrix to obtain the eigenvalue of each frequency point; The number of signal sources is determined based on the eigenvalues ​​of each frequency point, and the signal subspace matrix and the noise subspace matrix of each frequency point are determined; Setting an angle search range, constructing a frequency domain direction vector for each frequency point at different angles, and using the delay vector of each frequency point to obtain a pseudo frequency domain direction vector for each frequency point at different angles; Performing spectrum peak search using the noise subspace matrix and the pseudo-frequency domain direction vector at each frequency point to obtain the spatial spectrum distribution at each frequency point; The spatial spectrum distribution at each frequency point is summed and superimposed, and a corresponding detection threshold is set to perform angle measurement to obtain the incident angle of the signal source.

2. The method according to claim 1, characterized in that The output signal matrix can be expressed as: Among them, x m (t) is the data observed by the mth antenna, s n (t) represents the echo signal of the nth target received by the reference array element, n m (t) represents the noise component received by the mth array element; τ mn is the time delay of the echo signal of the nth target received by the mth array element relative to s(t), which is determined by the array structure and the target echo incident angle.

3. The method according to claim 2, characterized in that The antenna array frequency domain data can be expressed as: Among them, X m (ω) is x m (t) Frequency domain data after Fourier transformation, S n (ω) is s n (t) Frequency domain data after Fourier transform, For s n (t-τ mn )Frequency domain data after Fourier transformation, N m (ω) is n m (t) Frequency domain data after Fourier transform.

4. The method according to claim 3, characterized in that The frequency domain array receiving matrix of each frequency point is expressed as: Without considering the noise, it can be written in vector form as: X0(ω)=A(ω)S(ω) in, A(ω)=[a1(ω) a2(ω) … a N (ω)] is the direction matrix at each frequency point; S(ω)=[S1(ω) S2(ω) … S N (ω)] T is the frequency domain array receiving matrix of each frequency point; is the frequency domain direction vector of each frequency point at different angles.

5. The method according to claim 4, characterized in that The delay vector of each frequency point is expressed as: Among them, T d To delay the time, a delay of point L is introduced after each channel.

6. The method according to claim 5, characterized in that The pseudo-sampling frequency domain array receiving data of each frequency point is expressed as: in, is the pseudo snapshot vector, is the Kronecker product.

7. The method according to claim 6, characterized in that The pseudo data covariance matrix of each frequency point is expressed as: in, is the signal feature vector matrix, is the noise feature vector matrix, is the signal eigenvalue diagonal matrix, is the noise eigenvalue diagonal matrix.

8. The method according to claim 7, characterized in that The pseudo-frequency domain direction vector of each frequency point is expressed as:

9. The method according to claim 1, characterized in that The spatial spectrum distribution at each frequency point is expressed as:

10. An electronic device, characterized in that: include: processor; as well as a memory for storing executable instructions of the processor; The processor is configured to execute the time-domain carrier-free ultra-wideband system direction of arrival estimation method according to any one of claims 1 to 9 by executing the executable instructions.

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