CN114706056A - High-resolution angle measurement method, device and medium for millimeter wave radar based on covariance fitting - Google Patents
High-resolution angle measurement method, device and medium for millimeter wave radar based on covariance fitting Download PDFInfo
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Abstract
The application discloses a method, a device and a medium for measuring a high-resolution angle of a millimeter wave radar based on covariance fitting, wherein the method comprises the following steps: constructing a radar data sampling covariance matrix according to array receiving data; carrying out discrete processing on an interested angle space in the radar data to obtain angle grid points, and constructing a calculation matrix according to the angle grid points; performing iterative computation on the computation matrix according to an alternative multiplier method, and obtaining a spatial spectrum according to a preset iteration termination condition; the spatial spectrum is converted to a target angle. According to the method and the device, the number of signals does not need to be known in advance, the calculation complexity is low, and the requirements of the millimeter wave radar angle measurement on low-complexity and high-resolution algorithms can be effectively met.
Description
Technical Field
The application relates to the field of millimeter wave radars, in particular to a covariance fitting-based millimeter wave radar high-resolution angle measurement method, a covariance fitting-based millimeter wave radar high-resolution angle measurement device and a covariance fitting-based millimeter wave radar high-resolution angle measurement medium.
Background
The millimeter wave radar has wide application in the fields of intelligent driving, indoor detection, intelligent transportation and the like. These applications have a strong demand for high angular resolution. For the millimeter wave radar, the angle resolution performance is limited by the aperture of the antenna, the larger the effective aperture of the antenna is, the higher the resolution is, and on the contrary, the smaller the aperture of the antenna is, the worse the resolution is. In common application fields, the aperture of the antenna cannot be very large, which causes a large contradiction between the limited aperture of the antenna and the requirement of high resolution of the millimeter wave radar angle.
In the related art, the estimation of the angle is realized by using Fast Fourier Transform (FFT), but the resolution performance of the FFT is limited by the rayleigh limit, so that the requirement of high resolution of the angle cannot be met. The classical MUSIC algorithm, although it can achieve angular super-resolution, requires to know the number of targets in advance, and in practice, the determination of the number of targets is always a difficult problem in the field of radar application. In recent years, sparse recovery algorithms without hyper-parameters, such as SPICE and LIKES, developed without hyper-parameters can realize super-resolution of angle dimensions without knowing the number of signals, but the computation complexity is high, so that the computation requirement on a chip is high, and the hardware cost of the radar is increased.
Therefore, the above technical problems of the related art need to be solved.
Disclosure of Invention
The present application is directed to solving one of the technical problems in the related art. Therefore, the embodiment of the application provides a method, a device and a medium for high-resolution angle measurement of a millimeter wave radar based on covariance fitting, and the method, the device and the medium can meet the requirement of the high-resolution angle measurement of the millimeter wave radar based on covariance fitting.
According to an aspect of the embodiments of the present application, a method for high-resolution angle measurement of millimeter wave radar based on covariance fitting is provided, the method including:
constructing a radar data sampling covariance matrix according to array receiving data;
carrying out discrete processing on an interested angle space in the radar data to obtain angle grid points, and constructing a calculation matrix according to the angle grid points;
performing iterative computation on the computation matrix according to an alternative multiplier method, and obtaining a spatial spectrum according to a preset iteration termination condition;
the spatial spectrum is converted to a target angle.
In one embodiment, the sampling covariance matrix is formulated as:
wherein ,
for the sampling covariance matrix, y (T) is the array received data, T is the number of samples, yH(t) is a conjugate transpose of the array received data.
In one embodiment, the constructing a calculation matrix according to the angle lattice point includes:
and constructing a first matrix according to the angle lattice points, wherein the formula of the overcomplete basis matrix is as follows:
B＝[b(θ1)，…，b(θP)]
wherein B is the overcomplete basis matrix, B (θ)p) Is the guide vector on the p-th grid point;
constructing another matrix phi ═ B, IM], wherein ,IMIs an M × M identity matrix.
In one embodiment, the calculation matrix is iteratively calculated according to an alternative multiplier method, and a calculation formula of the iterative calculation includes:
γk+1：＝(Q+ρI)-1[w+ρ(ηk-uk)]
ηk+1：＝Θ(γk+1+uk)
uk+1：＝uk+γk+1-ηk+1
wherein ,γk+1For the spatial spectrum, θ is 0 and γk+1+ukIn (1)Maximum, P + M, I is the unit matrix, the initial value of the iteration
η0 and u0Are all zero vectors.
In one embodiment, after iterative computation is performed on the computation matrix according to an alternative multiplier method, iterative computation is stopped when a preset iteration number is met, and a peak value of the spatial spectrum is output.
In one embodiment, the sampling covariance matrix is constructed to perform radar data sampling, and sampled data is represented in the sampling covariance matrix as:
R＝BΓBH+σ2IM＝ΦΠΦH
wherein ,B∈CM×PIs an overcomplete basis matrix, Γ ═ diag { γ ═ d1，…，γp，…，γPDenotes the signal power at the p-th angular grid point.
In one embodiment, the method further comprises:
obtaining a non-negative vector according to a least square fitting formula, and obtaining a target angle according to the position of a non-negative element, wherein the least square fitting formula is as follows:
min γTQγ-2wTγ s.t.γ≥0
where γ is the spatial spectrum, T is the number of samples, Q is the Hadamard product of the matrix, and ω is the column vector composed of diagonal elements.
According to an aspect of the embodiments of the present application, a millimeter wave radar high resolution angle measurement apparatus based on covariance fitting is provided, the apparatus includes:
the sampling module is used for constructing a sampling covariance matrix to sample radar data according to the array receiving data;
the building module is used for carrying out discrete processing on an interested angle space in the radar data to obtain angle grid points and building a calculation matrix according to the angle grid points;
the calculation module is used for carrying out iterative calculation on the calculation matrix according to an alternative multiplier method and obtaining a spatial spectrum according to a preset iteration termination condition;
and the conversion module is used for converting the space spectrum into a target angle.
According to an aspect of the embodiments of the present application, a millimeter wave radar high resolution angle measurement apparatus based on covariance fitting is provided, the apparatus includes:
at least one processor;
at least one memory for storing at least one program;
at least one of the programs when executed by at least one of the processors implements the millimeter wave radar high resolution goniometry method based on covariance fitting as described in previous embodiments.
According to an aspect of the embodiments of the present application, a medium is provided, which stores a program executable by a processor, and the program executable by the processor implements the millimeter wave radar high-resolution angle measurement method based on covariance fitting as described in the foregoing embodiments.
The millimeter wave radar high-resolution angle measurement method, device and medium based on covariance fitting have the advantages that: according to the method, a sampling covariance matrix is constructed to sample radar data according to array receiving data; carrying out discrete processing on an interested angle space in the radar data to obtain angle grid points, and constructing a calculation matrix according to the angle grid points; performing iterative computation on the computation matrix according to an alternative multiplier method, and obtaining a spatial spectrum according to a preset iteration termination condition; and converting the spatial spectrum into a target angle. According to the method and the device, the number of signals does not need to be known in advance, the calculation complexity is low, and the requirements of the millimeter wave radar angle measurement on low-complexity and high-resolution algorithms can be effectively met.
Additional aspects and advantages of the present application will be set forth in part in the description which follows and, in part, will be obvious from the description, or may be learned by practice of the present application.
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In order to more clearly illustrate the technical solutions in the embodiments of the present application, the drawings needed to be used in the description of the embodiments are briefly introduced below, and it is obvious that the drawings in the following description are only some embodiments of the present application, and it is obvious for those skilled in the art to obtain other drawings based on these drawings without creative efforts.
Fig. 1 is a flowchart of a millimeter wave radar high-resolution angle measurement method based on covariance fitting according to an embodiment of the present application;
fig. 2 is a diagram of a target angle estimation result obtained by a millimeter wave radar high-resolution angle measurement method based on covariance fitting according to an embodiment of the present application;
FIG. 3 is a diagram illustrating a target angle estimation result obtained by a conventional FFT method;
fig. 4 is a schematic diagram of a millimeter wave radar high-resolution angle measurement device based on covariance fitting according to an embodiment of the present application;
fig. 5 is another schematic diagram of a millimeter wave radar high-resolution angle measurement device based on covariance fitting according to an embodiment of the present application.
Detailed Description
In order to make the technical solutions better understood by those skilled in the art, the technical solutions in the embodiments of the present application will be clearly and completely described below with reference to the drawings in the embodiments of the present application, and it is obvious that the described embodiments are only partial embodiments of the present application, but not all embodiments. All other embodiments obtained by a person of ordinary skill in the art based on the embodiments in the present application without making any creative effort shall fall within the protection scope of the present application.
The terms "first," "second," "third," and "fourth," etc. in the description and claims of this application and the accompanying drawings are used for distinguishing between different objects and not for describing a particular order. Furthermore, the terms "include" and "have," as well as any variations thereof, are intended to cover non-exclusive inclusions. For example, a process, method, system, article, or apparatus that comprises a list of steps or elements is not limited to only those steps or elements listed, but may alternatively include other steps or elements not listed, or inherent to such process, method, article, or apparatus.
Reference herein to "an embodiment" means that a particular feature, structure, or characteristic described in connection with the embodiment can be included in at least one embodiment of the application. The appearances of the phrase in various places in the specification are not necessarily all referring to the same embodiment, nor are separate or alternative embodiments mutually exclusive of other embodiments. It is explicitly and implicitly understood by one skilled in the art that the embodiments described herein can be combined with other embodiments.
The millimeter wave radar has wide application in the fields of intelligent driving, indoor detection, intelligent transportation and the like. These applications have a strong demand for high angular resolution. For the millimeter wave radar, the angle resolution performance is limited by the aperture of the antenna, the larger the effective aperture of the antenna is, the higher the resolution is, and on the contrary, the smaller the aperture of the antenna is, the worse the resolution is. In common application fields, the aperture of the antenna cannot be very large, which causes a large contradiction between the limited aperture of the antenna and the requirement of high resolution of the millimeter wave radar angle.
In the related art, the estimation of the angle is realized by using Fast Fourier Transform (FFT), but the resolution performance of the FFT is limited by rayleigh limit, so that it cannot meet the requirement of high resolution of the angle. The classical MUSIC algorithm, although it can achieve angular super-resolution, requires to know the number of targets in advance, and in practice, the determination of the number of targets is always a difficult problem in the field of radar application. In recent years, sparse recovery algorithms without hyper-parameters, such as SPICE and LIKES, developed without hyper-parameters can realize super-resolution of angle dimensions without knowing the number of signals, but the computation complexity is high, so that the computation requirement on a chip is high, and the hardware cost of the radar is increased.
In order to solve the problems, the application provides a millimeter wave radar high-resolution angle measurement method, a millimeter wave radar high-resolution angle measurement device and a millimeter wave radar high-resolution angle measurement medium based on covariance fitting.
For ease of understanding, the description explains the relevant terms:
millimeter wave: millimeter wave (millimeter wave): electromagnetic waves with the wavelength of 1-10 mm are called millimeter waves and are located in the overlapping wavelength range of microwave and far infrared waves, so that the electromagnetic wave has the characteristics of two wave spectrums. The theory and technology of millimeter waves are the extension of microwaves to high frequencies and the development of light waves to low frequencies, respectively.
Millimeter wave radar: millimeter-wave radars are radars that operate in the millimeter wave band (millimeter wave) for detection. Usually, the millimeter wave is in the frequency domain of 30 to 300GHz (with a wavelength of 1 to 10 mm). Millimeter-wave radar has some of the advantages of both microwave and photoelectric radar because the wavelength of millimeter-wave waves is intermediate between microwave and centimeter waves. Compared with the centimeter wave seeker, the millimeter wave seeker has the characteristics of small volume, light weight and high spatial resolution. Compared with optical probes such as infrared, laser and television, the millimeter wave probe has strong capability of penetrating fog, smoke and dust and has the characteristics of all weather (except heavy rainy days) all day long. In addition, the anti-interference and anti-stealth capabilities of the millimeter wave seeker are also superior to those of other microwave seekers. The millimeter wave radar can distinguish and identify very small targets and can identify a plurality of targets simultaneously; the imaging device has the advantages of imaging capability, small size, good maneuverability and concealment and strong survival capability on a battlefield.
Covariance: covariance (Covariance) is used in probability theory and statistics to measure the overall error of two variables. Variance is a special case of covariance, i.e. when the two variables are the same. Covariance represents the error of the sum of two variables, as opposed to the variance representing the error of only one variable. If the two variables have the same trend, i.e. if one of them is greater than its expected value and the other is also greater than its expected value, the covariance between the two variables is positive. If the two variables have opposite trend, i.e. one of them is larger than the expected value of itself and the other is smaller than the expected value of itself, the covariance between the two variables is negative.
The principle and the derivation process of the millimeter wave radar high-resolution angle measurement method, the millimeter wave radar high-resolution angle measurement device and the medium based on covariance fitting comprise the following steps: for the angle estimation problem of the millimeter wave radar, consider the following linear model:
y(t)＝Ax(t)+n(t)，t＝1，…，T.
wherein y (t) e CM×1、x(t)∈CK×1And n (t) CM×1Respectively representing an observation vector, a signal and a noise vector;
is the steering vector of the kth target,
is the angle of the kth signal, | ·| non-woven phosphor2A 2-norm representing a vector; m represents the number of actual array elements, T represents the number of samples, and K represents the number of signals. In the model, the assumed noise n (t) is zero mean and σ variance2Complex white gaussian noise and the noise is uncorrelated with the signal.
Under the uncorrelated signal assumption, the covariance matrix of the above formula can be expressed as:
R＝E{y(t)yH(t)}＝ARsAH+σ2IM
wherein Rs＝diag{δ1，…，δk}，
IM、E{·}、(·)HAnd diag {. cndot } represent the M × M unit matrix, mathematical expectation, conjugate transpose, and diagonal matrix, respectively. In actual processing, a sampling covariance matrix is usually used
Instead of R, where the sampling covariance matrix can be expressed as:
based on the principle and the derivation process, the application provides a covariance fitting-based millimeter wave radar high-resolution angle measurement method, as shown in fig. 1, the covariance fitting-based millimeter wave radar high-resolution angle measurement method specifically comprises the following steps:
s101, constructing a radar data sampling covariance matrix according to array receiving data.
In this embodiment, the formula of the sampling covariance matrix adopted in step S101 is:
wherein ,
for the sampling covariance matrix, y (T) is the array received data, T is the number of samples, yH(t) is a conjugate transpose of the array received data.
S102, carrying out discrete processing on the angle space of interest in the radar data to obtain angle grid points, and constructing a calculation matrix according to the angle grid points.
And S103, carrying out iterative computation on the computation matrix according to an alternative multiplier method, and obtaining a spatial spectrum according to a preset iteration termination condition.
And S104, converting the space spectrum into a target angle.
In this embodiment, an interested angle space is discretized into p lattice points, and under a sparse representation framework, a covariance matrix in the above principle can be represented as:
R＝BΓBH+σ2IM＝ΦΠΦH
wherein B∈CM×PIs an overcomplete basis matrix, i.e., its P-th (P ═ 1, …, P) column can be considered as a discrete angle θpA guide vector of a function of, and
Γ＝diag{γ1，…，γp，…，γP}，γp≧ 0 denotes the signal power at the pth lattice point; phi ═ B, IM]，
According to the theory of sparsity characterization, if and only if θp∈{ψkWhen K is 1, …, K, gammap> 0, otherwise gamma p0. That is, by finding the position of the non-zero element in the spatial spectrum gamma, the diagonal can be obtained
Is estimated. It should be explained that the theory of sparse representation is to describe the energy of the signal as much as possible by the minimum number of coefficients. For different types of signals, the distribution of coefficients may be different for different transforms.
In this embodiment, the following weighted covariance fitting problem may be considered:
in the formula | · | non-countingFThe Frobenius norm of the matrix is represented. According to the relationship between the Frobenius norm and the matrix trace, the following can be obtained:
where trace (·) represents the traces of the matrix. Substituting equation (4) into equation (6) yields:
in the formula 
() () represents the Hadamart product of the matrix, w being
A column vector of diagonal elements.
Therefore, the method for obtaining the target angle in the embodiment further includes: obtaining a non-negative vector according to a least square fitting formula, and obtaining a target angle according to the position of a non-negative element, wherein the least square fitting formula is as follows:
min γTQγ-2wTγ s.t.γ≥0
where γ is the spatial spectrum, T is the number of samples, Q is the Hadamard product of the matrix, and ω is the column vector composed of diagonal elements. It should be noted that although there are a large number of solutions to the non-negative least squares problem, their complexity, robustness, and accuracy are not satisfactory in sparse recovery. In the embodiment, an Alternating Direction Multiplier Method (ADMM) is combined, least square fitting is solved, compromise processing can be sought between complexity and robustness, and the complexity is enabled to improve the accuracy of a calculation result within a reasonable level.
Specifically, in this embodiment, the constructing a calculation matrix according to the angle lattice includes: and constructing a first matrix according to the angle lattice points, wherein the formula of the overcomplete basis matrix is as follows:
B＝[b(θ1)，…，b(θP)]
wherein B is the overcomplete basis matrix, B (θ)p) Is the guide vector on the p-th grid point; constructing another matrix phi ═ B, IM], wherein ,IMIs an M × M identity matrix.
In step S103 of this embodiment, the calculation matrix is iteratively calculated according to an alternative multiplier method, and a calculation formula of the iterative calculation includes:
γk+1：＝(Q+ρI)-1[w+ρ(ηk-uk)]
ηk+1：＝Θ(γk+1+uk)
uk+1：＝uk+γk+1-ηk+1
wherein ,γk+1for the spatial spectrum, θ is 0 and γk+1+ukP + M, I is the unit matrix, the initial value of the iteration
η0 and u0Are all zero vectors.
In this embodiment, after iterative computation is performed on the computation matrix according to an alternative multiplier method, iterative computation is stopped when a preset iteration number is satisfied, and a peak value of the spatial spectrum is output. The preset iteration times can be set by technicians independently, and can be changed according to actual needs, and the more the iteration times are in a reasonable range, the more accurate the calculation of the target angle is.
In this embodiment, the sampling covariance matrix is constructed to perform radar data sampling, and data obtained by sampling is represented in the sampling covariance matrix as:
R＝BΓBH+σ2IM＝ΦΠΦH
wherein ,B∈CM×PIs an overcomplete basis matrix, Γ ═ diag { γ ═ d1，…，γp，…，γPDenotes the signal power at the p-th angular grid point.
For the effect of the millimeter wave radar high-resolution angle measurement method based on covariance fitting provided by the present application, as shown in fig. 2 and fig. 3, fig. 2 is a target angle estimation result graph obtained by the millimeter wave radar high-resolution angle measurement method based on covariance fitting provided by the embodiment of the present application, and fig. 3 is a target angle estimation result graph obtained by a conventional FFT method. In one experiment, the distance between the two corner reflectors is about 2.8 meters, the transverse distance (namely the azimuth angle) between the two corner reflectors is 0.8 meter, the radar is a millimeter wave radar working at 77GHz, 4 equivalent array elements are totally arranged, and the distance between the array elements is 0.5 times of the wavelength. Under the present experimental conditions, the azimuth angles of the two corner reflectors are separated by about 0.49 rayleigh limits. The azimuth angle estimation results obtained by the method and the traditional FFT method are respectively shown in the application, and the comparison and analysis of the figure 2 and the figure 3 show that in the same transverse distance experiment, the method can realize super-resolution angle estimation, and the resolution performance of the method is obviously superior to that of the traditional FFT method. Therefore, the method and the device do not need to know the number of signals in advance, have low calculation complexity, and can effectively meet the requirements of millimeter wave radar angle measurement on low-complexity and high-resolution algorithms.
In addition, as shown in fig. 4, the present application further provides a millimeter wave radar high resolution angle measurement device based on covariance fitting, including: a sampling module 401, configured to construct a radar data sampling covariance matrix according to the array received data; a constructing module 402, configured to perform discrete processing on an angle space of interest in the radar data to obtain angle grid points, and construct a calculation matrix according to the angle grid points; a calculating module 403, configured to perform iterative calculation on the calculation matrix according to an alternative multiplier method, and obtain a spatial spectrum according to a preset iteration termination condition; a conversion module 404, configured to convert the spatial spectrum into a target angle.
In addition, as shown in fig. 5, the present application further provides a millimeter wave radar high resolution angle measurement device based on covariance fitting, the device includes:
at least one processor 501;
at least one memory 502, said memory 502 for storing at least one program;
at least one of the programs when executed by at least one of the processors 501 implements the millimeter wave radar high resolution goniometry method based on covariance fitting as described in previous embodiments.
The contents in the above method embodiments are all applicable to the apparatus, the functions of the apparatus are the same as those in the above method embodiments, and the advantageous effects achieved by the apparatus are also the same as those achieved by the above method embodiments.
The present application also provides a medium storing a program executable by a processor, and the program executable by the processor realizes the millimeter wave radar high-resolution angle measurement method based on covariance fitting as described in the foregoing embodiments when executed by the processor.
Similarly, the contents in the foregoing method embodiments are all applicable to this medium embodiment, the functions specifically implemented by this medium embodiment are the same as those in the foregoing method embodiment, and the advantageous effects achieved by this medium embodiment are also the same as those achieved by the foregoing method embodiment.
In alternative embodiments, the functions/acts noted in the block diagrams may occur out of the order noted in the operational illustrations. For example, two blocks shown in succession may, in fact, be executed substantially concurrently, or the blocks may sometimes be executed in the reverse order, depending upon the functionality/acts involved. Furthermore, the embodiments presented and described in the flowcharts of the present application are provided by way of example in order to provide a more thorough understanding of the technology. The disclosed methods are not limited to the operations and logic flows presented herein. Alternative embodiments are contemplated in which the order of various operations is changed and in which sub-operations described as part of larger operations are performed independently.
Furthermore, although the present application is described in the context of functional modules, it should be understood that, unless otherwise stated to the contrary, one or more of the functions and/or features may be integrated in a single physical device and/or software module, or one or more functions and/or features may be implemented in separate physical devices or software modules. It will also be appreciated that a detailed discussion regarding the actual implementation of each module is not necessary for an understanding of the present application. Rather, the actual implementation of the various functional modules in the apparatus disclosed herein will be understood within the ordinary skill of an engineer, given the nature, function, and internal relationship of the modules. Accordingly, those skilled in the art can, using ordinary skill, practice the present application as set forth in the claims without undue experimentation. It is also to be understood that the specific concepts disclosed are merely illustrative of and not intended to limit the scope of the application, which is defined by the appended claims and their full scope of equivalents.
The functions, if implemented in the form of software functional units and sold or used as a stand-alone product, may be stored in a computer readable storage medium. Based on such understanding, the technical solution of the present application or portions thereof that substantially contribute to the prior art may be embodied in the form of a software product stored in a storage medium and including instructions for causing a computer device (which may be a personal computer, a server, or a network device) to execute all or part of the steps of the method according to the embodiments of the present application. And the aforementioned storage medium includes: a U-disk, a removable hard disk, a Read-Only Memory (ROM), a Random Access Memory (RAM), a magnetic disk or an optical disk, and other various media capable of storing program codes.
The logic and/or steps represented in the flowcharts or otherwise described herein, e.g., an ordered listing of executable instructions that can be considered to implement logical functions, can be embodied in any computer-readable medium for use by or in connection with an instruction execution system, apparatus, or device, such as a computer-based system, processor-containing system, or other system that can fetch the instructions from the instruction execution system, apparatus, or device and execute the instructions. For the purposes of this description, a "computer-readable medium" can be any means that can contain, store, communicate, propagate, or transport the program for use by or in connection with the instruction execution system, apparatus, or device.
More specific examples (a non-exhaustive list) of the computer-readable medium would include the following: an electrical connection (electronic device) having one or more wires, a portable computer diskette (magnetic device), a Random Access Memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber device, and a portable compact disc read-only memory (CDROM). Additionally, the computer-readable medium could even be paper or another suitable medium upon which the program is printed, as the program can be electronically captured, via for instance optical scanning of the paper or other medium, then compiled, interpreted or otherwise processed in a suitable manner if necessary, and then stored in a computer memory.
It should be understood that portions of the present application may be implemented in hardware, software, firmware, or a combination thereof. In the above embodiments, the various steps or methods may be implemented in software or firmware stored in memory and executed by a suitable instruction execution system. For example, if implemented in hardware, as in another embodiment, any one or combination of the following techniques, which are known in the art, may be used: a discrete logic circuit having a logic gate circuit for implementing a logic function on a data signal, an application specific integrated circuit having an appropriate combinational logic gate circuit, a Programmable Gate Array (PGA), a Field Programmable Gate Array (FPGA), or the like.
In the foregoing description of the specification, reference to the description of "one embodiment/example," "another embodiment/example," or "certain embodiments/examples," etc., means that a particular feature, structure, material, or characteristic described in connection with the embodiment or example is included in at least one embodiment or example of the application. In this specification, schematic representations of the above terms do not necessarily refer to the same embodiment or example. Furthermore, the particular features, structures, materials, or characteristics described may be combined in any suitable manner in any one or more embodiments or examples.
While embodiments of the present application have been shown and described, it will be understood by those of ordinary skill in the art that: numerous changes, modifications, substitutions and variations can be made to the embodiments without departing from the principles and spirit of the application, the scope of which is defined by the claims and their equivalents.
The above embodiments are only used to illustrate the technical solutions of the present application, and not to limit the same; although the present application has been described in detail with reference to the foregoing embodiments, it should be understood by those of ordinary skill in the art that: the technical solutions described in the foregoing embodiments may still be modified, or some technical features may be equivalently replaced; and such modifications or substitutions do not depart from the spirit and scope of the corresponding technical solutions in the embodiments of the present application.
Claims (10)
1. The millimeter wave radar high-resolution angle measurement method based on covariance fitting is characterized by comprising the following steps of:
constructing a radar data sampling covariance matrix according to array receiving data;
carrying out discrete processing on an interested angle space in the radar data to obtain angle grid points, and constructing a calculation matrix according to the angle grid points;
performing iterative computation on the computation matrix according to an alternative multiplier method, and obtaining a spatial spectrum according to a preset iteration termination condition;
the spatial spectrum is converted to a target angle.
2. The millimeter wave radar high-resolution angle measurement method based on covariance fitting according to claim 1, wherein the formula of the radar data sampling covariance matrix is as follows:
wherein ,
for the sampling covariance matrix, y (T) is the array received data, T is the number of samples, yH(t) is a conjugate transpose of the array received data.
3. The millimeter wave radar high-resolution angle measurement method based on covariance fitting according to claim 1, wherein the constructing a calculation matrix according to the angle lattice points comprises:
and constructing a first matrix according to the angle lattice points, wherein the formula of the overcomplete basis matrix is as follows:
B＝[b(θ1)，…，b(θP)]
wherein B is the overcomplete basis matrix, B (θ)p) Is a firstSteering vectors at p grid points;
constructing another matrix phi ═ B, IM], wherein ,IMIs an M × M identity matrix.
4. The millimeter wave radar high-resolution angle measurement method based on covariance fitting according to claim 1, wherein iterative computation is performed on the computation matrix according to an alternative multiplier method, and a computation formula of the iterative computation comprises:
γk+1：＝(Q+ρI)-1[w+ρ(ηk-uk)]
ηk+1：＝Θ(γk+1+uk)
uk+1：＝uk+γk+1-ηk+1
wherein ,γk+1For the spatial spectrum, θ is 0 and γk+1+ukP + M, I is the unit matrix, the initial value of the iteration
η0 and u0Are all zero vectors.
5. The millimeter wave radar high-resolution angle measurement method based on covariance fitting according to claim 4, wherein after iterative computation is performed on the computation matrix according to an alternative multiplier method, the iterative computation is stopped when a preset iteration number is met, and a peak value of the spatial spectrum is output.
6. The millimeter wave radar high-resolution angle measurement method based on covariance fitting according to claim 1, wherein a radar data sampling covariance matrix is constructed, and sampled data is represented in the sampling covariance matrix as:
R＝BΓBH+σ2IM＝ΦΠΦH
wherein ,B∈CM×PIs an overcomplete basis matrix, Γ ═ diag { γ ═ d1，…，γp，…，γPDenotes the signal power at the p-th angle grid point.
7. The millimeter wave radar high-resolution angle measurement method based on covariance fitting, according to claim 1, further comprising:
obtaining a non-negative vector according to a least square fitting formula, and obtaining a target angle according to the position of a non-negative element, wherein the least square fitting formula is as follows:
minγTQγ-2wTγs.t.γ≥0
where γ is the spatial spectrum, T is the number of samples, Q is the Hadamard product of the matrix, and ω is the column vector composed of diagonal elements.
8. Millimeter wave radar high-resolution angle measurement device based on covariance fitting, its characterized in that, the device includes:
the sampling module is used for constructing a radar data sampling covariance matrix according to the array receiving data;
the building module is used for carrying out discrete processing on an interested angle space in the radar data to obtain angle grid points and building a calculation matrix according to the angle grid points;
the calculation module is used for carrying out iterative calculation on the calculation matrix according to an alternative multiplier method and obtaining a spatial spectrum according to a preset iteration termination condition;
and the conversion module is used for converting the space spectrum into a target angle.
9. Millimeter wave radar high-resolution angle measurement device based on covariance fitting, its characterized in that, the device includes:
at least one processor;
at least one memory for storing at least one program;
at least one of the programs when executed by at least one of the processors implements the covariance fitting-based millimeter wave radar high-resolution goniometry method of any one of claims 1-7.
10. A medium storing a program executable by a processor, the program being executed by the processor to implement the covariance fitting-based millimeter wave radar high-resolution goniometry method as recited in any one of claims 1 to 7.
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