High-precision angle measurement method and device of millimeter wave radar and storage medium

Abstract

The invention discloses a millimeter wave radar high-precision angle measurement method and device and a storage medium, and relates to the technical field of radar measurement, and the method comprises the steps: obtaining an echo signal and a target steering vector; according to the echo signal and the target steering vector, adopting a discretization angle space to obtain an initial angle; obtaining an angle offset according to the initial angle; based on the angle offset, the discretization angle space is refined, and a reference angle value is obtained; and when a preset condition is met, taking the reference angle value as a target angle. According to the method, the angle is preliminarily determined and the offset is calculated through the discretization angle space, the discretization angle space is refined, then the target estimation angle value is obtained, and the angle estimation precision is remarkably improved with a small calculation amount.

Description

Technical Field

[0001] The present application relates to the field of radar measurement technology, and in particular to a high-precision angle measurement method, device and storage medium for millimeter-wave radar. Background Art

[0002] Millimeter-wave radar has high measurement accuracy and adaptability to multiple environments, and is widely used in the automotive field. In order to avoid huge computational loads, existing millimeter-wave radar angle measurement methods all choose discretized angle space. That is, the estimated value of the angle parameter is obtained by the discretized angle value in the discretized angle space. However, the angle of the real target is always random, which undoubtedly brings certain errors to these angle estimation methods and affects the accuracy of the angle measurement algorithm. And because the detection distance of the vehicle-mounted millimeter-wave radar is long, the error caused by the angle will bring great difficulties to the accurate tracking of distant targets. Summary of the invention

[0003] The main purpose of this application is to provide a high-precision angle measurement method, device and storage medium for millimeter-wave radar, aiming to solve the technical problem of how to significantly improve the angle estimation accuracy with a smaller amount of calculation.

[0004] To achieve the above objectives, the present application proposes a high-precision angle measurement method for millimeter-wave radar, the method comprising:

[0005] Acquire echo signals and target guidance vectors;

[0006] Obtaining an initial angle using a discretized angle space according to the echo signal and the target steering vector;

[0007] Obtaining an angle offset according to the initial angle;

[0008] Based on the angle offset, the discretized angle space is refined to obtain a reference angle value;

[0009] When the preset conditions are met, the reference angle value is used as the target angle.

[0010] In one embodiment, the step of obtaining an initial angle using a discretized angle space according to the echo signal and the target steering vector comprises:

[0011] Determine the angle space range to be searched according to the field of view angle range of the millimeter wave radar;

[0012] The angle space range to be searched is discretized to obtain a discretized angle space.

[0013] In one embodiment, the step of obtaining the initial angle using a discretized angle space according to the echo signal and the target steering vector comprises:

[0014] Obtaining an array receiving signal according to the echo signal;

[0015] Obtaining a covariance matrix according to the array received signal;

[0016] Performing eigendecomposition on the covariance matrix to obtain eigenvalues ​​of the received signal;

[0017] Obtaining a noise subspace according to the characteristic value;

[0018] Based on the discretized angle space, an initial angle is obtained according to the noise subspace and the target steering vector.

[0019] In one embodiment, the step of obtaining the angle offset according to the initial angle comprises:

[0020] Obtaining an angle estimate taking into account an angle offset according to the initial angle;

[0021] Based on a first-order Taylor expansion formula, a first-order Taylor steering vector taking into account the angle offset is obtained;

[0022] The angle offset is obtained according to the angle estimation value and the first-order Taylor steering vector.

[0023] In one embodiment, the step of refining the discretized angle space based on the angle offset to obtain a reference angle value includes:

[0024] According to the initial angle, obtaining a corresponding discretized angle value of the discretized angle space;

[0025] The discretized angle value is refined according to the angle offset to obtain a reference angle value.

[0026] In one embodiment, when a preset condition is met, the step of using the reference angle value as the target angle includes:

[0027] Get the offset threshold and iteration threshold;

[0028] When the angle offset is less than or equal to the offset threshold or the number of iterations is equal to the iteration threshold, it is determined that a preset condition is met, and the reference angle value is used as the target angle.

[0029] In one embodiment, when the angle offset is less than or equal to the offset threshold or the number of iterations is equal to the iteration threshold, determining that a preset condition is satisfied and taking the reference angle value as the target angle before the step includes:

[0030] When the angle offset is greater than the offset threshold and the number of iterations is less than the iteration threshold, return to the step of obtaining the angle offset according to the initial angle.

[0031] In one embodiment, the step of acquiring the echo signal and the target steering vector comprises:

[0032] The transmission signal and the receiving signal are processed by the millimeter wave radar to obtain an echo signal;

[0033] Obtaining a wavelength and an array element spacing according to the echo signal;

[0034] A target steering vector is obtained according to the wavelength and the array element spacing.

[0035] In addition, to achieve the above purpose, the present application also proposes a high-precision angle measurement device for millimeter-wave radar, the device comprising:

[0036] An acquisition module, used for acquiring echo signals and target guidance vectors;

[0037] An angle measurement module, used to obtain an initial angle using a discretized angle space according to the echo signal and the target steering vector;

[0038] The angle measuring module is further used to obtain an angle offset according to the initial angle;

[0039] The angle measurement module is further used to refine the discretized angle space based on the angle offset to obtain a reference angle value;

[0040] The angle measuring module is further configured to use the reference angle value as a target angle when a preset condition is met.

[0041] In addition, to achieve the above-mentioned objectives, the present application also proposes a high-precision angle measurement device for millimeter-wave radar, the device comprising: a memory, a processor, and a computer program stored on the memory and executable on the processor, the computer program being configured to implement the steps of the high-precision angle measurement method for millimeter-wave radar as described above.

[0042] In addition, to achieve the above-mentioned purpose, the present application also proposes a storage medium, which is a computer-readable storage medium, and a computer program is stored on the storage medium. When the computer program is executed by the processor, the steps of the high-precision angle measurement method of the millimeter-wave radar as described above are implemented.

[0043] In addition, to achieve the above-mentioned purpose, the present application also provides a computer program product, which includes a computer program, and when the computer program is executed by a processor, the steps of the high-precision angle measurement method of the millimeter-wave radar as described above are implemented.

[0044] One or more technical solutions proposed in this application have at least the following technical effects:

[0045] By preliminarily determining the angle and calculating the offset through discretized angle space, refining the discretized angle space, and then obtaining the target estimated angle value, the technical problem that existing angle measurement methods are difficult to accurately track distant targets is solved. Compared with the existing technology, the angle estimation accuracy is significantly improved with a smaller amount of calculation. BRIEF DESCRIPTION OF THE DRAWINGS

[0046] The accompanying drawings, which are incorporated in and constitute a part of this specification, illustrate embodiments consistent with the present application and, together with the description, serve to explain the principles of the present application.

[0047] In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, for ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative labor.

[0048] Figure 1 A schematic diagram of a flow chart provided for the first embodiment of the high-precision angle measurement method for millimeter-wave radar of the present application;

[0049] Figure 2 A schematic diagram of a flow chart provided for Embodiment 2 of the high-precision angle measurement method for millimeter-wave radar of the present application;

[0050] Figure 3 A flowchart diagram of a third embodiment of a high-precision angle measurement method for a millimeter-wave radar of the present application;

[0051] Figure 4 A flowchart diagram of a fourth embodiment of a high-precision angle measurement method for a millimeter-wave radar of the present application;

[0052] Figure 5 A flowchart diagram of a fifth embodiment of a high-precision angle measurement method for a millimeter-wave radar of the present application;

[0053] Figure 6 This is a schematic diagram of an experiment on the iterative effect of the high-precision angle measurement method of the millimeter-wave radar provided in Example 5 of the present application;

[0054] Figure 7 A schematic diagram of the error of the high-precision angle measurement method of the millimeter-wave radar provided in Example 5 of the present application;

[0055] Figure 8 A flowchart diagram of a sixth embodiment of a high-precision angle measurement method for a millimeter-wave radar of the present application;

[0056] Fig. 9 A flow chart of the seventh embodiment of the high-precision angle measurement method for millimeter-wave radar of the present application;

[0057] Fig.10 A schematic diagram of a brief process of a high-precision angle measurement method for a millimeter-wave radar provided in an embodiment of the present application;

[0058] Fig.11 This is a schematic diagram of the module structure of the high-precision angle measurement device of the millimeter-wave radar in the embodiment of the present application;

[0059] Fig.12 Schematic diagram of the equipment structure of the hardware operating environment involved in the high-precision angle measurement method of millimeter-wave radar in the embodiment of the present application.

[0060] The purpose, features and advantages of this application will be further described in conjunction with the embodiments and with reference to the accompanying drawings. DETAILED DESCRIPTION

[0061] It should be understood that the specific embodiments described herein are only used to explain the technical solutions of the present application and are not used to limit the present application.

[0062] In order to better understand the technical solution of the present application, a detailed description will be given below in conjunction with the accompanying drawings and specific implementation methods.

[0063] The main solution of the embodiment of the present application is: obtain an echo signal and a target steering vector; according to the echo signal and the target steering vector, use a discretized angle space to obtain an initial angle; according to the initial angle, obtain an angle offset; based on the angle offset, refine the discretized angle space to obtain a reference angle value; when a preset condition is met, use the reference angle value as the target angle.

[0064] In this embodiment, for ease of description, the following description is made by taking the internal actuator of the high-precision angle measurement system of the millimeter-wave radar as the execution subject.

[0065] Due to the poor angle estimation accuracy of existing technologies, it is difficult for vehicle-mounted millimeter-wave radar to accurately track distant targets.

[0066] The present application provides a solution, which uses a discretized angle space to preliminarily determine the angle and calculate the offset, refine the discretized angle space, and then obtain the target estimated angle value, thereby achieving a significant improvement in the angle estimation accuracy with a smaller amount of calculation.

[0067] It can be seen from the above embodiments that the present application adopts the method of preliminarily determining the angle and calculating the offset through discretized angle space, refining the discretized angle space, and then obtaining the target estimated angle value, which solves the technical problem that the existing angle measurement method is difficult to accurately track distant targets. Compared with the existing technology, it achieves a significant improvement in the angle estimation accuracy with a smaller amount of calculation.

[0068] It should be noted that the execution subject of this embodiment may be a computing service device with data processing, network communication and program running functions, such as a tablet computer, a personal computer, a mobile phone, etc., or an electronic device capable of realizing the above functions, etc. The following takes the internal actuator of the high-precision angle measurement system of the millimeter-wave radar as an example to illustrate this embodiment and the following embodiments.

[0069] Based on this, the embodiment of the present application provides a high-precision angle measurement method for millimeter wave radar, referring to Figure 1 , Figure 1 This is a flow chart of the first embodiment of the high-precision angle measurement method of millimeter-wave radar in the present application.

[0070] In this embodiment, the high-precision angle measurement method of the millimeter wave radar includes steps S10 to S50:

[0071] Step S10, acquiring the echo signal and the target steering vector.

[0072] It should be noted that the echo signal is the signal reflected back after the millimeter-wave frequency band signal emitted by the millimeter-wave radar hits the target object. The millimeter-wave signal emitted by the radar propagates in space at the speed of light. When it encounters a target, the signal will be reflected, just like light is reflected by a mirror. These reflected signals are acquired by the radar's receiving device. The echo signal contains information such as distance, speed, angle, and the characteristics of the target itself. Through complex signal processing algorithms, the time delay of the echo signal can be analyzed to obtain the target distance; the angle of the target can be determined by using information such as the phase difference or amplitude difference of the echo signal received by different array elements, combined with the characteristics of the array antenna; at the same time, the speed of the target can be obtained based on information such as frequency shift, which can be combined to locate and track the target. After the millimeter-wave radar mixes, filters, samples, performs fast Fourier transform, and performs constant false alarm detection on the transmitted and received signals, it collects signals on different receiving antennas to form an echo signal containing only a single target object.

[0073] In addition, it should be noted that the target steering vector is an important concept in array signal processing. It describes the phase difference or amplitude difference information of the signal propagation path from the signal source to each array element. In a uniform linear array, the phase difference of each array element relative to the reference array element can be calculated based on the array element spacing, signal wavelength and incident angle, and then the target steering vector can be obtained. This vector can control the beam direction by adjusting the relationship between the weighted vector and the vector in beamforming. In target positioning and direction estimation, the signal source position can be determined by matching the received signal and the target steering vector in different directions. In the case of multiple signal sources, signal sources in different directions can also be distinguished. In signal separation and identification, the target signal can also be separated and identified from the interference signal based on the target steering vector difference of the signal source. Since the received signal between different antennas is only related to the angle, and the echo signal includes the received signal, the target steering vector can be obtained through the echo signal.

[0074] Step S20: obtaining an initial angle using a discretized angle space according to the echo signal and the target steering vector.

[0075] It should be noted that discretized angle space refers to dividing a continuous angle range into a series of discrete angle value sets. From the perspective of actual application scenarios, when using radar and other equipment to detect target azimuth, the angle space is originally continuous. In theory, the target may appear at any position in this continuous angle space. However, in order to facilitate calculation and processing, we discretize this angle space. During the operation, the angles are divided according to certain rules and accuracy requirements. For example, in a two-dimensional plane, if the angle ranges from 0 degrees to 360 degrees, we may divide this complete angle range into independent discrete angles at certain intervals, such as 1 degree, 0.5 degrees, etc. This division method is similar to dividing a complete circle into many small sector areas, and the central angle of each sector area represents a discrete angle. The initial angle is a rough estimate of the target azimuth obtained based on the echo signal, the target guidance vector and the discretized angle space.

[0076] The echo signal carries a lot of information reflected by the target, including distance, speed, angle, etc. It is the basic data source for our subsequent analysis. The target-steering vector describes the relevant information introduced by the signal propagation path from the signal source, that is, the target, to each array element of the array, such as phase difference, amplitude difference, etc. It is closely related to the angle of the target. The target-steering vector will show different forms of expression at different angles. Then, by discretizing the angle space, that is, dividing the entire possible angle range into discrete angle values, and then processing the echo signal, including calculating the covariance matrix of the signal and performing feature decomposition, and then extracting the noise subspace, the initial angle is obtained according to the target-steering vector and the discrete angle value, which provides a starting angle reference for further accurate determination of the target angle and other related signal processing and target detection operations.

[0077] Step S30, obtaining an angle offset according to the initial angle.

[0078] It should be noted that the angle offset represents the difference between the target's true angle and the initial angle. When using the echo signal and the target guidance vector for initial angle estimation, the signal may be interfered by environmental noise. These noises will change the phase, amplitude and other characteristics of the echo signal, causing the initial angle obtained based on the signal processing algorithm to deviate from the target's true angle. More importantly, since the true target angle is random and the angle discrete space is pre-set, the true target angle cannot always be exactly located at the preset discretized angle space point. The angle offset specifically refers to the offset between the preset discretized angle space point and the true target angle.

[0079] Since the initial angle is obtained by discretizing the angle space and calculating the echo signal and the target-oriented vector, it is only a preliminary estimate. In the actual environment, there are many factors that cause the target's true angle to deviate from the initial angle. Accurately obtaining and using the angle offset can continuously optimize the initial angle through iterative calculations, signal feature re-analysis, etc., so as to more accurately determine the target's true angle.

[0080] Step S40: Based on the angle offset, the discretized angle space is refined to obtain a reference angle value.

[0081] It should be noted that the reference angle value is a discretized angle value obtained by refining the discretized angle space corresponding to the initial angle according to the angle offset.

[0082] Since the initial angle is only based on the preliminary judgment result of the previous discretized angle space, and the angle offset reflects the deviation between it and the target's true angle. At this time, it is necessary to comprehensively consider the size, direction and other information of the angle offset, and take the discrete angle value where the initial angle is located as the starting point. If the angle offset indicates that the current discrete angle value is too small, then the interval between the discrete angle values ​​is appropriately reduced in the direction of increasing the angle, such as using the offset to refine in the direction of increasing the angle; on the contrary, if the angle offset shows that the current discrete angle value is too large, then it is refined in the direction of reducing the angle, which is also to reduce the interval between the discrete angle values. In this way, the angle value of the discretized angle space is closer to the target's true angle, and the target angle can be re-evaluated at a more refined level. The target guidance vector corresponding to the refined discrete angle is matched and compared with the echo signal again, and the estimation of the target's true angle is continuously optimized, so that the final target angle is closer to the actual situation, and better serves subsequent tasks such as target positioning and tracking.

[0083] Step S50: When a preset condition is met, the reference angle value is used as a target angle.

[0084] It should be noted that satisfying the preset condition may be that the angle offset is small enough or the number of iterative refinements of the offset reaches an upper limit. Whether the preset condition is satisfied may be determined by setting an offset threshold and an iteration threshold, and the determination of satisfying the preset condition may not be limited to the angle offset and the number of iterative refinements. This embodiment and other embodiments are described by taking the angle offset and the number of iterative refinements as an example to determine whether the preset condition is satisfied. The target angle is a reference angle value when the preset condition is satisfied, that is, a discretized angle value, which is an angle value that more accurately represents the target orientation after a series of calculations and corrections.

[0085] In addition, it should be noted that this embodiment and other embodiments use the MUSIC method to achieve high-precision angle measurement, but the core idea of ​​the method proposed in this embodiment and other embodiments is applicable to all discretized angle space methods, such as fast Fourier transform, L1 regularization, sparse Bayesian learning, orthogonal matching tracking, etc.

[0086] In addition, it should be noted that the MUSIC method, namely the Multiple Signal Classification method, is a high-resolution spectrum estimation and signal parameter estimation method based on subspace decomposition.

[0087] This embodiment provides a high-precision angle measurement method for millimeter-wave radar, which uses discretized angle space to preliminarily determine the angle and calculate the offset, refine the discretized angle space, and then obtain the target estimated angle value, which solves the technical problem that existing angle measurement methods are difficult to accurately track distant targets, and achieves a significant improvement in angle estimation accuracy with a smaller amount of calculation.

[0088] Based on the first embodiment of the present application, in the second embodiment of the present application, the same or similar contents as those in the above-mentioned embodiment 1 can be referred to the above introduction, and will not be repeated in the following. Figure 2 , before step S20, steps S01 to S02 are included:

[0089] Step S01, determining the angular space range to be searched according to the field of view angle range of the millimeter wave radar.

[0090] It should be noted that millimeter wave radar is a radar system that uses the millimeter wave frequency band for detection. Millimeter waves refer to electromagnetic waves with a wavelength between 1 and 10 mm, and their frequency band is relatively high. The working principle of millimeter wave radar is to transmit millimeter wave signals through a transmitter. These signals will be reflected after encountering the target object, and the reflected signal, that is, the echo signal, will be received by the receiver. Millimeter wave radar contains a transmitting antenna and a receiving antenna. The transmitting antenna is responsible for sending the generated millimeter wave signal, and the receiving antenna is used to capture the echo signal. There is also a signal processing unit inside it. This unit performs complex processing on the received echo signal, such as calculating the target distance by analyzing the round-trip time of the signal, obtaining the target speed from the signal frequency shift using the Doppler effect, and determining the target direction by relying on array antenna technology combined with signal processing algorithms.

[0091] In addition, it should be noted that the field of view (FOV) is the angle range in which the millimeter-wave radar can effectively detect targets. It has corresponding definitions in both the horizontal and vertical directions. In terms of the physical characteristics and working principles of the radar itself, this range depends on the design and layout of the radar antenna. In the horizontal direction, the field of view angle range is determined by the horizontal beam width of the antenna. This is like the illumination range of a flashlight beam on the horizontal plane. The angle area covered by the millimeter-wave signal emitted by the transmitting antenna of the millimeter-wave radar in the horizontal direction is the horizontal field of view angle range. For example, the horizontal field of view angle range of some millimeter-wave radars may be from -60 degrees to +60 degrees, which means that it can detect targets within this range in the horizontal direction. In the vertical direction, the field of view angle range is also defined by the vertical beam width. This range will vary depending on the application scenario and installation method of the radar. For example, when the automotive millimeter-wave radar is used for vehicle front detection, the vertical field of view angle range may be designed to be relatively narrow to focus on targets in the direction of vehicle travel and avoid excessive detection of objects in irrelevant directions such as the sky or the ground.

[0092] Millimeter-wave radar itself has its own established field of view angle range, which specifies the angle area in which it can effectively detect the target. For example, the horizontal and vertical directions have specific angle intervals respectively. The horizontal field of view angle range may be from a certain starting angle to an ending angle, and the vertical field of view angle range is the same. Based on such a field of view angle range, the angle space range to be searched can be delineated, and the angle area that needs to be searched and analyzed for targets can be limited to this range to avoid useless work in the angle area that the radar cannot detect at all. In actual operation, if the field of view angle range is from the left extreme angle to the right extreme angle in the horizontal direction, the horizontal part of the angle space range to be searched can be determined as this interval. Similarly, the corresponding interval of the vertical direction is determined according to the corresponding field of view angle range, and then the complete angle space range to be searched is determined comprehensively, so that the subsequent use of millimeter-wave radar echo signals, target guidance vectors and other related elements for discretization of angle space processing, target angle estimation and other operations can be carried out in an orderly manner within this reasonably determined angle space range, improving the efficiency and accuracy of target detection and analysis. For example, the normal direction of the millimeter-wave radar is selected as the reference 0° direction, and the field of view angle range of the radar is [-75, +75], then the angle space range to be searched is 150°.

[0093] Step S02: discretize the angle space range to be searched to obtain a discretized angle space.

[0094] It should be noted that discretization is a process of converting a continuous variable space or physical range into a discrete, finite set of values. For the processing of millimeter-wave radar angle space, the original radar's search angle space range is continuous, and theoretically the target may appear at any angle position within this range. Discretization is to divide this continuous angle range into small, discrete angle units. This is like dividing a complete circle (representing the angle range) with scale marks. This processing method is mainly to facilitate operations in actual calculations, measurements, and signal processing. The discretized angle space can be easily matched with pre-calculated parameters such as the target guidance vector, so that the echo signal can be processed in a targeted manner at each discrete angle, thereby effectively improving the efficiency and accuracy of target detection and angle estimation.

[0095] The angle space range to be searched has clear angle intervals in both the horizontal and vertical directions, and the discretization process is to convert such continuous angle intervals into discrete angle value sets that are convenient for subsequent operations. In the actual operation process, these angle intervals will be divided according to certain accuracy requirements. For example, according to the desired level of precision of target detection, the appropriate angle interval value is selected. If you want the detection result to be more accurate, then select a smaller angle interval. For example, in the horizontal direction, the original angle interval is from a certain starting angle to the ending angle, and it is divided into intervals of 0.5 degrees. The same is true in the vertical direction. In this way, the entire angle space range to be searched is divided into many small angle units. The angle value corresponding to each small angle unit is the discrete angle value in the discretized angle space. Many discrete angle values ​​together constitute the discretized angle space. At the same time, when performing discretization processing, it is also necessary to consider factors such as the performance characteristics of the radar system itself and the application scenario. If the radar signal processing capability is strong, a finer discretization can be used to obtain a more accurate target position estimation; if the application scenario has high real-time requirements, it may be necessary to make a trade-off between accuracy and computational complexity, and select a relatively appropriate discretization degree to avoid overly complex calculations due to overly fine discretization, which affects the efficiency of real-time detection. The discretized angle space finally obtained through such reasonable discretization processing can provide a convenient basis for subsequent operations such as target angle estimation and target search based on millimeter-wave radar echo signals. For example, if the step value is selected as step, the entire discretized angle space is: -75: step: 75.

[0096] This embodiment provides a high-precision angle measurement method for a millimeter-wave radar, which determines the angle space range to be searched according to the field angle range of the millimeter-wave radar; discretizes the angle space range to be searched to obtain a discretized angle space, thereby improving the angle estimation accuracy.

[0097] Based on the first embodiment of the present application, in the third embodiment of the present application, the same or similar contents as those in the above-mentioned embodiment 1 can be referred to the above introduction, and will not be repeated in the following. Figure 3 , step S20 includes steps S21 to S25:

[0098] Step S21, obtaining an array receiving signal according to the echo signal.

[0099] It should be noted that the array received signal refers to the collection of signals received by each element in a receiving array composed of multiple elements (such as an antenna array). From the perspective of signal generation, when a signal source transmits a signal (such as the reflected signal of a millimeter-wave signal emitted by a millimeter-wave radar after encountering a target), these signals will reach each element in the array in different ways. This is because during the propagation of the signal, due to the difference in the spatial distribution of the elements, the time, phase and amplitude of the signal arriving at different elements will be different. Taking a uniform linear array as an example, for a plane wave signal emitted by a far-field signal source, the time when the signal arrives at different elements will be delayed due to the element spacing and the signal propagation direction, and this delay will cause a phase difference. These signals received by each element of the array contain rich information, such as the location of the signal source, the distance of the signal source (inferred by the propagation time of the signal), the motion state of the signal source (obtained from the change in signal frequency using the Doppler effect) and the characteristics of the signal source itself (reflected by the amplitude, phase and other characteristics of the signal). By processing these array received signals, valuable information can be extracted. For example, by analyzing the phase difference and amplitude difference of the received signals of different array elements, combined with the array's geometric structure and signal processing algorithm, operations such as positioning, tracking and identifying the signal source can be achieved.

[0100] This embodiment is described by taking a narrowband far-field signal as a received signal as an example. The mathematical model of the narrowband far-field signal can be expressed as:

[0101] y(t)=A(θ)x(t)+e(t)

[0102] Where y(t) represents the array receiving signal at time t, that is, the narrowband far-field signal, A(θ) represents the array flow matrix, θ = [θ1, θ2, θ3, …, θ k ], x(t) represents the incident signal at time t, e(t) = [e1(t), e2(t), …, e m (t)] represents the noise vector.

[0103] Step S22, obtaining a covariance matrix according to the array received signal.

[0104] It should be noted that the covariance matrix is ​​a mathematical concept that has been widely used in many fields such as signal processing and statistics. From a mathematical point of view, it is a matrix used to measure the covariance between a set of random variables. For multiple variables, each element in the covariance matrix represents the covariance between the corresponding two variables. If there are n random variables, then the covariance matrix is ​​an n×n square matrix. Taking the two-dimensional case as an example, assuming that there are two random variables X and Y, the covariance matrix is ​​a 2×2 matrix, whose elements include the variance of X, the variance of Y, and the covariance of X and Y. In the field of signal processing, especially in array signal processing, the role of the covariance matrix is ​​very critical. Taking the antenna array receiving signal as an example, the covariance matrix can describe the correlation between the signals received by each array element in the array. Assuming that the antenna array has N array elements, and the signal received by each array element can be regarded as a random variable, then the covariance matrix of these signals can reflect the degree of correlation between the signals in different array elements. Its element calculation involves the mean and expectation operations of the signal, which are obtained by statistically analyzing the signal within a certain period of time.

[0105] In actual situations, the length of the received data is limited. Since the accurate calculation of the covariance matrix needs to be based on the statistical characteristics of the signal, ideally there should be an infinitely long signal sequence to accurately calculate the mathematical expectation (the calculation of the covariance matrix elements involves mathematical expectation). However, in practice, only a finite number of sample points can be obtained, so the covariance matrix of the data can be obtained by the maximum likelihood estimate of the received signal. Many actual signals approximately obey the Gaussian distribution. Under the Gaussian distribution assumption, if the received signal vector is a zero-mean Gaussian distribution, for the zero-mean signal vector x = [x1, x2, ..., x n ] T , the elements in the covariance matrix R At this time, the covariance matrix can be expressed as R = [xx H ], where x H is the conjugate transpose of x. In the context of signal processing, zero mean means that the mathematical expectation of a signal (or random variable) is zero. Mathematical expectation is a weighted average of the values ​​of a random variable, which reflects the average level of the random variable. If the signal is not zero mean, it is necessary to first calculate the mean of the signal and then perform zero mean processing on the signal to obtain the covariance matrix of the signal.

[0106] Since the narrowband far-field signal is a zero-mean signal, the covariance matrix of the narrowband far-field signal can be expressed by the following formula:

[0107] R=y(t)*y(t) H

[0108] Step S23, performing eigendecomposition on the covariance matrix to obtain eigenvalues ​​of the received signal.

[0109] It should be noted that eigendecomposition is a mathematical operation for square matrices. In essence, it decomposes a square matrix into eigenvectors and eigenvalues. Assume that there is a square matrix, by finding a specific non-zero vector and scalar, the product of the square matrix and the vector is equal to the product of the scalar and the vector. The non-zero vector here is the eigenvector, and the scalar is the eigenvalue. Its purpose is to find all the eigenvalues ​​of the square matrix and a set of linearly independent eigenvectors. In practical applications, such as in the field of data processing, eigendecomposition of the covariance matrix can separate the signal space from the noise space, and can also play a role in operations such as adaptive beamforming, helping to adjust the weights of the beamformer and improve signal reception quality and anti-interference capabilities.

[0110] For an n×n covariance matrix R, eigendecomposition is to find a set of non-zero vectors v and corresponding scalars λ, so that Rv = λv, then v is called the eigenvector of the matrix R, and λ is the corresponding eigenvalue. In a geometric sense, the eigenvector represents a vector whose direction remains unchanged under matrix transformation, and the eigenvalue represents the degree of stretching or compression in this direction.

[0111] In actual situations, signals usually contain useful signals and noise. When processing signals, it is necessary to distinguish the received useful signals from the noise. The covariance matrix of the narrowband far-field signal is decomposed by the eigenvalues, which can be expressed by the following formula:

[0112] EVD{R}=[U S U n ]*diag{V S V n}*[U s U n ] H

[0113] Where EVD{} represents the eigendecomposition, R represents the covariance matrix of the narrowband far-field signal, and U S represents the signal subspace spanned by the signal eigenvectors, U n represents the noise subspace spanned by the noise feature vector, diag{} represents the diagonal operation, V S Represents the signal characteristic value, V n Represents the noise characteristic value.

[0114] Step S24: obtaining a noise subspace according to the characteristic value.

[0115] It should be noted that after the covariance matrix of the received signal is eigen-decomposed, a set of eigenvalues ​​and corresponding eigenvectors will be obtained, where the space spanned by the eigenvectors associated with the smaller eigenvalues ​​is the noise subspace, and the space spanned by the eigenvectors refers to the set consisting of all possible linear combinations of these eigenvectors. These smaller eigenvalues ​​are usually caused by noise and reflect the energy and distribution of the noise. The opposite of the noise subspace is the signal subspace. The signal subspace is the space spanned by the eigenvectors corresponding to the larger eigenvalues, which correspond to the energy of the signal.

[0116] After eigendecomposing the covariance matrix of the received signal, we will get a series of eigenvalues ​​and corresponding eigenvectors. Generally speaking, the eigenvalues ​​associated with the signal are larger, while the eigenvalues ​​associated with the noise are smaller, that is, V s >>V n By setting a suitable threshold (for example, determined based on prior knowledge of noise power or by some statistical methods), the eigenvalues ​​can be divided into two groups: a larger group of eigenvalues, whose corresponding eigenvectors span the space of the signal subspace, and a smaller group of eigenvalues, whose corresponding eigenvectors span the space of the noise subspace.

[0117] Step S25, based on the discretized angle space, obtaining an initial angle according to the noise subspace and the target steering vector.

[0118] In the discretized angle space, the possible signal source angle range is first divided into a series of discrete angle points. For each discrete angle, the corresponding target steering vector can be calculated. It is determined by the array geometry and signal propagation characteristics, and reflects the relative phase relationship of the signal reaching each array element at this angle. The noise subspace is formed by the eigenvectors corresponding to the small eigenvalues ​​after the eigendecomposition of the covariance matrix. The orthogonality of the signal subspace and the noise subspace is used to measure the degree of orthogonality between the target steering vector and the noise subspace through an expression based on the principle of orthogonal projection. Under ideal conditions, when the angle corresponds to the true orientation of the signal source, this measurement expression will have a peak value, because at this time the target steering vector coincides with or is highly correlated with the signal subspace, then the target steering vector is also orthogonal to the noise subspace, which can be expressed by the following formula:

[0119]

[0120] Where a(θ) represents the target orientation vector, U n represents the noise subspace.

[0121] Ideally, in order to accurately estimate parameters such as the covariance matrix and noise subspace, we hope to have an infinite number of snapshots, so that accurate statistical characteristics can be obtained based on statistical averaging. However, in practical applications, we can only obtain a finite number of snapshots, so we can obtain the estimated value of the noise subspace by performing eigendecomposition on the maximum likelihood estimate of the covariance matrix And, due to the presence of noise, a(θ) is They are not completely orthogonal, so the signal direction angle estimation is actually achieved through minimum optimization search, which can be expressed by the following formula:

[0122]

[0123] in, represents the estimated value of the initial angle, argmin represents the value of the independent variable when a function reaches the minimum value, represents the estimate of the noise subspace under finite snapshots, and a(θ) represents the target guidance vector.

[0124] Furthermore, the spectrum estimation formula of the initial angle can be expressed as follows:

[0125]

[0126] Among them, P m Represents the spatial spectrum function.

[0127] Subsequently, the discretized angle values ​​of the discretized angle space are substituted into the expression of the spatial spectrum function in turn, and the spectrum of the spatial spectrum function-discretized angle value is drawn according to the substitution result. The peak value of the spatial spectrum function is searched in the spectrum graph, and the discretized angle value corresponding to the value is the initial angle. express.

[0128] This embodiment provides a high-precision angle measurement method for a millimeter-wave radar, which obtains an array receiving signal according to the echo signal; obtains a covariance matrix according to the array receiving signal; performs eigendecomposition on the covariance matrix to obtain eigenvalues ​​of the receiving signal; obtains a noise subspace according to the eigenvalues; and obtains an initial angle based on the discretized angle space according to the noise subspace and the target steering vector, thereby achieving a roughly estimated target angle value.

[0129] Based on the first embodiment of the present application, in the fourth embodiment of the present application, the same or similar contents as those in the first embodiment can be referred to the above description, and will not be described in detail later. Figure 4 , step S30 includes steps S31 to S33:

[0130] Step S31, obtaining an angle estimation value taking into account the angle offset according to the initial angle.

[0131] The estimated value of the target angle using the traditional gridding method can only be obtained at the discretized angle value in the limited discretized angle space. That is to say, if the real angle of the target is exactly at the discretized angle value, the angle estimation error will be 0. However, in practice, the direction of the signal is always random and it is impossible to always be exactly at the discretized angle value, which will bring a certain angle estimation error. Therefore, the angle estimation value considering the angle offset can be obtained through the initial angle, which is expressed by the following formula:

[0132]

[0133] Where θ represents the target angle, represents the initial angle, and β represents the angle offset between the initial angle and the target angle.

[0134] In order to obtain the angle value that reduces the error, θ can be substituted into the expression of the initial angle, which can be expressed as follows:

[0135]

[0136] in, represents the angle estimate taking into account the angle offset, argmin represents the minimization parameter, represents the estimate of the noise subspace under finite snapshots, represents the target steering vector, β represents the angular offset between the initial angle and the target angle, and β is a scalar.

[0137] Step S32: Based on the first-order Taylor expansion formula, a first-order Taylor steering vector taking into account the angle offset is obtained.

[0138] It should be noted that the first-order Taylor expansion formula is the first-order form of the Taylor formula expansion. The Taylor formula uses the information of a function at a certain point to describe its nearby values.

[0139] The first-order Taylor expansion formula is used to express the first-order Taylor steering vector considering the angle offset, which can be expressed as follows:

[0140]

[0141] in, Represents the target orientation vector right The derivative function of , β represents the angle offset between the initial angle and the target angle.

[0142] Step S33, obtaining the angle offset according to the angle estimation value and the first-order Taylor steering vector.

[0143] Substituting the expression of the first-order Taylor steering vector into the expression of the angle estimate taking into account the angle offset, and taking the derivative of the function on the right side of the equation to make it equal to 0, it can be expressed as follows:

[0144]

[0145] in, represents partial derivative, represents the estimate of the noise subspace under finite snapshots, represents the target steering vector, and β represents the angular offset between the initial angle and the target angle.

[0146] By solving this equation, we can get the final angle offset, which is expressed as follows:

[0147]

[0148] Where β represents the angle offset between the initial angle and the target angle, Represents the target orientation vector right The derivative function of represents the estimate of the noise subspace under finite snapshots, Indicates the initial angle.

[0149] This embodiment provides a high-precision angle measurement method for millimeter-wave radar, which obtains an angle estimation value taking into account the angle offset based on the initial angle; obtains a first-order Taylor steering vector taking into account the angle offset based on the first-order Taylor expansion formula; and obtains the angle offset based on the angle estimation value and the first-order Taylor steering vector, thereby improving the angle estimation accuracy.

[0150] Based on the first embodiment of the present application, in the fifth embodiment of the present application, the same or similar contents as those in the first embodiment can be referred to the above description, and will not be described in detail later. Figure 5 , step S40 includes steps S41 to S42:

[0151] Step S41, obtaining a discretized angle value of the corresponding discretized angle space according to the initial angle.

[0152] First, we need to define the discretized angle space that has been constructed, that is, the pre-set angle range and the angle interval (step size) that divides the range. For example, if the angle range is set from -90° to 90° and the angle interval is 1°, then this range is divided into 181 discrete angle values ​​(-90°, -89°, ..., 89°, 90°).

[0153] Given the initial angle, we look for the discretized angle value that matches or is closest to it in the discretized angle set, and then get the corresponding discretized angle value. A common approach is to calculate the absolute value of the difference between the initial angle and each discretized angle value. The discretized angle value with the smallest absolute value of the difference is the corresponding angle value we are looking for.

[0154] The discretized angle value corresponding to the initial angle is determined because when the initial angle is accurately processed, the discretized angle value needs to be refined to obtain the precise target angle. However, there are many angle values ​​in the discretized angle space, and not all discretized angle values ​​need to be refined. Therefore, it is necessary to obtain the corresponding discretized angle value based on the initial angle.

[0155] Step S42: Refine the discretized angle value according to the angle offset to obtain a reference angle value.

[0156] For example, the initial search step is 3°, and the discretized angle value closest to the initial angle within the field of view angle range is searched at intervals of 3°. The discretized angle value corresponding to the initial angle is 30°, and the angle offset is 0.1°. After the discretized angle value is refined according to the angle offset, the discretized angle value obtained is 29.9°, and 29.9° is the reference angle value. Then the angle offset at this time is calculated to be 0.05°. According to the angle offset, the reference angle value is further refined, and the discretized angle value obtained is 29.85°. The angle value is refined iteratively and the angle offset is calculated.

[0157] It is understandable that the angle estimation accuracy can be increased by refining the angle value through multiple iterations. However, as the number of iterations gradually increases, the improvement of the estimation accuracy will become limited, so the actual application should select a suitable number of iterations. In this embodiment, the initial search step size is 3°, the radar array normal is 0°, the field of view angle range is [-75°, 75°], and the target true angle is 25.86° as an example to illustrate the effect of the number of iterations.

[0158] like Figure 6The figure shows a schematic diagram of the iterative effect experiment. The initial search step is 3°. According to the target true angle of 25.86°, the corresponding discretized angle value is 27°. At this time, the error between the target true angle and the discretized angle value is 1.14. The angle offset is calculated to be 0.5424. According to the angle offset of 0.5424, the refined discrete space angle is 26.4576. At this time, the error between the target true angle and the discretized angle value is 0.5976. The angle offset is calculated to be 0.2592. The angle is iteratively refined. After 7 iterations, the discrete space angle is 25.9781°. At this time, the error between the target true angle and the discretized angle value is 0.1181°.

[0159] By selecting reference angle value sample data and conducting 200 Monte Carlo experiments, the sample data is iterated and refined 7 times in each experiment. After each iteration in the experiment, the mean absolute value of the error between the target true angle and the discretized angle value and the mean absolute value of the angle offset are calculated. The corresponding data of the mean absolute value of the error, the mean absolute value of the angle offset and the number of iterations are represented by images, as shown in Figure 7 The figure shows the error diagram of the iteration, where Error Illustration represents the error diagram, Mean of Absolute Value represents the mean absolute value, Number of Iterations represents the number of iterations, Error represents the mean absolute value of the error between the target true angle and the discretized angle value, and Offset represents the mean absolute value of the angle offset. It can be seen from the image that as the number of iterations increases, the accuracy of the angle estimation gradually increases, but the increase in accuracy gradually decreases. In practical applications, in order to balance the amount of calculation and the estimation accuracy, it is recommended that the actual number of iterations can be preset to 4-6 times.

[0160] It should be noted that the Monte Carlo experiment, also known as Monte Carlo simulation, is a statistical experimental method based on random sampling. Its basic idea is to simulate a complex system or mathematical model through a large number of random samples to obtain the statistical characteristics of the system or model.

[0161] It is understandable that when the input signal of the target is determined, the angle estimation accuracy of the algorithm is related to the number of iterative refinements. The more iterations there are, the higher the estimation accuracy. At the same time, the amount of calculation also increases slightly. Since the initial discretized angle value has been determined, in order to improve the real-time performance of the system, the target-oriented vector corresponding to each angle and its corresponding derivative can be stored in the chip in advance, which can greatly reduce the running time required for the first iteration. Compared with the traditional search algorithm, the discretized angle space containing only a small number of discretized angle values ​​is used, and the offset between the discretized angle value and the target's true angle is considered. The calculation complexity is lower and the angle estimation accuracy is high.

[0162] This embodiment provides a high-precision angle measurement method for millimeter-wave radar. According to the initial angle, a discretized angle value of the corresponding discretized angle space is obtained; the discretized angle value is refined according to the angle offset to obtain a reference angle value, thereby improving the angle estimation accuracy.

[0163] Based on the first embodiment of the present application, in the sixth embodiment of the present application, the same or similar contents as those in the first embodiment can be referred to the above description, and will not be described in detail later. Figure 8 , step S50 includes steps S51-S52:

[0164] Step S51, obtaining an offset threshold and an iteration threshold.

[0165] It should be noted that the offset threshold and the iteration threshold are angle offset thresholds and iteration number thresholds obtained according to preset conditions, wherein the offset threshold may be 0.01, 0.02, etc., and the iteration threshold may be 4 times, 5 times, etc. This embodiment does not specifically limit the values ​​of the offset threshold and the iteration threshold.

[0166] Step S52: When the angle offset is less than or equal to the offset threshold or the number of iterations is equal to the iteration threshold, it is determined that a preset condition is met, and the reference angle value is used as a target angle.

[0167] It should be noted that the target angle is the angle of the target to be detected, that is, the target data of the target angle measurement by the millimeter wave radar.

[0168] Taking the offset threshold as 0.01 and the iteration threshold as 5 as an example, during the iterative refinement of the reference angle value, if the angle offset is less than or equal to 0.01 under the premise that the number of iterations is less than 5, the condition at this time is determined to meet the preset condition, and the reference angle value obtained by the refinement in the last iteration is output as the target angle. If the angle offset is greater than 0.01 during the 5 iterations, no matter what the angle offset is after the 5th iteration, the 6th iteration refinement will not be performed, and the reference angle value obtained by the refinement in the 5th iteration will be directly output as the target angle.

[0169] In a feasible implementation manner, step S52 includes step A10 before:

[0170] Step A10, when the angle offset is greater than the offset threshold and the number of iterations is less than the iteration threshold, return to the step of obtaining the angle offset according to the initial angle.

[0171] Taking the offset threshold as 0.01 and the iteration threshold as 5 times as an example, during the iterative refinement of the reference angle value, if the number of iterations is less than 5 times and the angle offset is greater than 0.01, it is determined that the condition at this time does not meet the preset condition and it is necessary to continue the angle refinement, then returning to the step of obtaining the angle offset according to the initial angle, that is, performing the next iterative refinement of the angle.

[0172] By setting the offset threshold and iteration threshold, the computational complexity is reduced and the angle estimation accuracy is improved.

[0173] This embodiment provides a high-precision angle measurement method for millimeter-wave radar, which obtains an offset threshold and an iteration threshold; when the angle offset is less than or equal to the offset threshold or the number of iterations is equal to the iteration threshold, it is determined that a preset condition is met, and the reference angle value is used as the target angle, thereby significantly improving the angle estimation accuracy with a smaller amount of calculation.

[0174] Based on the first embodiment of the present application, in the seventh embodiment of the present application, the same or similar contents as those in the above-mentioned embodiment 1 can be referred to the above introduction, and will not be repeated in the following. Fig. 9 , step S10 includes steps S11 to S13:

[0175] Step S11, processing the transmitted signal and the received signal by the millimeter wave radar to obtain an echo signal.

[0176] During the operation of millimeter-wave radar, mixing processing is performed to mix the transmitted signal and the received signal in a specific circuit so that the frequency characteristics of the two interact with each other, thereby converting the high-frequency received signal into an intermediate frequency signal that is more convenient for subsequent processing. Next, filtering processing is performed to remove unnecessary clutter in the signal and various interference signals from the external environment through a carefully designed filter. These interferences may include interference from other radio signals, noise generated by the radar itself, etc. The signal after filtering is purer, laying the foundation for subsequent accurate analysis. Subsequently, the signal is sampled to convert the analog signal into a digital signal so that it can be processed more efficiently using digital signal processing technology. The sampling process needs to strictly follow the Nyquist sampling theorem to ensure that the sampling frequency is high enough to fully retain the information of the original signal. After sampling, a fast Fourier transform is performed to convert the signal in the time domain into a frequency domain signal. This allows the frequency components of the signal to be clearly analyzed, because in millimeter-wave radar, key information such as the speed and distance of the target is closely related to the frequency of the echo signal. The spectrum obtained by the fast Fourier transform can accurately find the frequency peak corresponding to the target echo signal, thereby inferring the relevant characteristics of the target. Finally, constant false alarm detection is performed. This link aims to maintain a stable false alarm probability under complex environmental noise and clutter backgrounds. Constant false alarm detection effectively controls the false alarm probability by adaptively adjusting the detection threshold. After completing the above processing of the transmitted signal and the received signal, the millimeter-wave radar will collect signals from different receiving antennas. Since millimeter-wave radars are usually equipped with multiple receiving antennas, the signal received by each receiving antenna contains some unique information of the target. By reasonably collecting and integrating these signals from different receiving antennas, more comprehensive and accurate information about the target can be obtained. After processing and collecting signals from different receiving antennas, the millimeter-wave radar composition contains only an echo signal of a single target object. This echo signal fully contains key information such as the distance, speed and angle of the target, providing a solid and reliable foundation for subsequent target tracking, identification and more in-depth analysis and processing.

[0177] Step S12, obtaining the wavelength and array element spacing according to the echo signal.

[0178] In millimeter-wave radar systems, the wavelength can be determined by performing spectrum analysis on the echo signal, such as obtaining its frequency component by using methods such as fast Fourier transform. According to the basic theory of electromagnetic waves, there is a relationship between wavelength, wave speed and frequency. The wave speed in air is approximately the speed of light. Once the frequency of the echo signal is known, the wavelength can be calculated using the formula that wavelength equals wave speed divided by frequency. In addition, in the case of multiple antennas, there will be a phase difference when the echo signal of the same target reaches different antennas. By analyzing this phase difference, the distance between the antennas, and the angle between the target and the radar, the wavelength can also be indirectly derived.

[0179] The array element spacing is usually associated with the wavelength. Ideally, in order to avoid grating lobes (a phenomenon that causes multiple main lobes in the radiation pattern, interfering with target detection and positioning), the array element spacing is generally less than or equal to half a wavelength. For example, the reference array element is the first array element, and the spacing between adjacent array elements is d. For the mth array element, the distance from it to the reference array element is (m-1)d.

[0180] Step S13, obtaining a target steering vector according to the wavelength and the array element spacing.

[0181] Since the received signals between different antennas are only related to the angle, the target steering vector can be obtained, which is expressed by the following formula:

[0182]

[0183] Where θ represents the target angle, a(θ) is a vector representing the target guidance vector, λ is a parameter representing the wavelength, and d m is a parameter, which indicates the distance from the mth array element to the reference array element, e indicates the natural exponent, and T indicates the transposition operation.

[0184] Furthermore, the target orientation vector can also be expressed by the following formula:

[0185] a(θ)=[1,e jsinθ , e j2sinθ ,…,e j(M-1)sinθ ] T

[0186] Where θ represents the target angle, a(θ) represents the target steering vector, e represents the natural exponent, and T represents the transpose operation.

[0187] This embodiment provides a high-precision angle measurement method for a millimeter-wave radar, in which a transmission signal and a reception signal are processed by the millimeter-wave radar to obtain an echo signal; a wavelength and an array element spacing are obtained based on the echo signal; a target steering vector is obtained based on the wavelength and the array element spacing, thereby realizing an expression for obtaining the target steering vector.

[0188] For example, to help understand the implementation process of the high-precision angle measurement method of the millimeter wave radar obtained by combining the first, second, third, fourth, fifth, sixth, and seventh embodiments, please refer to Fig.10 , Fig.10 A brief flow chart of a high-precision angle measurement method of a millimeter-wave radar is provided, specifically:

[0189] Step one, obtain the echo signal and target guidance vector; step two, use the discretized angle space to preliminarily determine the target angle; step three, calculate the offset according to the discretized angle space, refine the discretized angle space according to the offset, and judge whether the conditions are met; if the conditions are not met, return to the step of calculating the offset according to the discretized angle space, and output the target estimate if the conditions are met.

[0190] It should be noted that the above examples are only used to understand the present application and do not constitute a limitation on the high-precision angle measurement method of the millimeter-wave radar of the present application. More simple transformations based on this technical concept are all within the scope of protection of the present application.

[0191] This application also provides a high-precision angle measurement device for millimeter-wave radar, please refer to Fig.11 , the device comprises:

[0192] The acquisition module 10 is used to acquire the echo signal and the target steering vector.

[0193] The angle measuring module 20 is used to obtain an initial angle using a discretized angle space according to the echo signal and the target steering vector.

[0194] The angle measuring module 20 is further configured to obtain an angle offset according to the initial angle.

[0195] The angle measurement module 20 is further used to refine the discretized angle space based on the angle offset to obtain a reference angle value.

[0196] The angle measuring module 20 is further configured to use the reference angle value as a target angle when a preset condition is met.

[0197] In one embodiment, the angle measurement module 20 is further used to determine the angle space range to be searched according to the field angle range of the millimeter wave radar; and discretize the angle space range to be searched to obtain a discretized angle space.

[0198] In one embodiment, the angle measurement module 20 is further used to obtain an array receiving signal based on the echo signal; obtain a covariance matrix based on the array receiving signal; perform eigendecomposition on the covariance matrix to obtain eigenvalues ​​of the receiving signal; obtain a noise subspace based on the eigenvalues; and based on the discretized angle space, obtain an initial angle based on the noise subspace and the target steering vector.

[0199] In one embodiment, the angle measurement module 20 is further used to obtain an angle estimation value taking into account the angle offset based on the initial angle; obtain a first-order Taylor steering vector taking into account the angle offset based on a first-order Taylor expansion formula; and obtain the angle offset based on the angle estimation value and the first-order Taylor steering vector.

[0200] In one embodiment, the angle measurement module 20 is further used to obtain a discretized angle value of the corresponding discretized angle space according to the initial angle; and refine the discretized angle value according to the angle offset to obtain a reference angle value.

[0201] In one embodiment, the angle measurement module 20 is further used to obtain a discretized angle value of the corresponding discretized angle space according to the initial angle; and refine the discretized angle value according to the angle offset to obtain a reference angle value.

[0202] In one embodiment, the angle measuring module 20 is further configured to return to the step of obtaining the angle offset according to the initial angle when the angle offset is greater than the offset threshold and the number of iterations is less than the iteration threshold.

[0203] In one embodiment, the acquisition module 10 is further used to process the transmission signal and the reception signal through the millimeter wave radar to obtain an echo signal; obtain the wavelength and the array element spacing according to the echo signal; and obtain the target steering vector according to the wavelength and the array element spacing.

[0204] The high-precision angle measurement device of the millimeter-wave radar provided in the present application adopts the high-precision angle measurement method of the millimeter-wave radar in the above-mentioned embodiment, which can solve the technical problem of how to achieve a significant improvement in the accuracy of angle estimation with a smaller amount of calculation. Compared with the prior art, the beneficial effects of the high-precision angle measurement device of the millimeter-wave radar provided in the present application are the same as the beneficial effects of the high-precision angle measurement method of the millimeter-wave radar provided in the above-mentioned embodiment, and other technical features in the high-precision angle measurement device of the millimeter-wave radar are the same as the features disclosed in the above-mentioned embodiment method, which will not be repeated here.

[0205] The present application provides a high-precision angle measurement device for a millimeter-wave radar, and the high-precision angle measurement device for a millimeter-wave radar includes: at least one processor; and a memory communicatively connected to the at least one processor; wherein the memory stores instructions executable by the at least one processor, and the instructions are executed by the at least one processor so that the at least one processor can execute the high-precision angle measurement method for the millimeter-wave radar in the above-mentioned embodiment one.

[0206] Reference below Fig.12, which shows a schematic diagram of the structure of a high-precision angle measurement device suitable for implementing the millimeter-wave radar of the embodiment of the present application. The high-precision angle measurement device of the millimeter-wave radar in the embodiment of the present application may include but is not limited to mobile terminals such as mobile phones, laptop computers, digital broadcast receivers, PDAs (Personal Digital Assistants), PADs (Portable Application Descriptions), PMPs (Portable Media Players), vehicle-mounted terminals (such as vehicle-mounted navigation terminals), etc., and fixed terminals such as digital TVs, desktop computers, etc. Fig.12 The high-precision angle measurement device of the millimeter-wave radar shown is only an example and should not bring any limitation to the functions and scope of use of the embodiments of the present application.

[0207] like Fig.12 As shown, the high-precision angle measurement device of the millimeter-wave radar may include a processing device 1001 (such as a central processing unit, a graphics processor, etc.), which can perform various appropriate actions and processes according to the program stored in the read-only memory (ROM: Read Only Memory) 1002 or the program loaded from the storage device 1003 to the random access memory (RAM: Random Access Memory) 1004. In RAM1004, various programs and data required for the operation of the high-precision angle measurement device of the millimeter-wave radar are also stored. The processing device 1001, ROM1002 and RAM1004 are connected to each other through a bus 1005. An input / output (I / O) interface 1006 is also connected to the bus. Typically, the following systems can be connected to the I / O interface 1006: input devices 1007 including, for example, a touch screen, a touchpad, a keyboard, a mouse, an image sensor, a microphone, an accelerometer, a gyroscope, etc.; output devices 1008 including, for example, a liquid crystal display (LCD), a speaker, a vibrator, etc.; storage devices 1003 including, for example, a magnetic tape, a hard disk, etc.; and communication devices 1009. The communication device 1009 can allow the high-precision angle measurement device of the millimeter-wave radar to communicate wirelessly or wired with other devices to exchange data. Although the figure shows a high-precision angle measurement device of the millimeter-wave radar with various systems, it should be understood that it is not required to implement or have all the systems shown. More or fewer systems may be implemented or have instead.

[0208] In particular, according to the embodiments disclosed in the present application, the process described above with reference to the flowchart can be implemented as a computer software program. For example, the embodiments disclosed in the present application include a computer program product, which includes a computer program carried on a computer-readable medium, and the computer program includes a program code for executing the method shown in the flowchart. In such an embodiment, the computer program can be downloaded and installed from a network through a communication device, or installed from a storage device 1003, or installed from a ROM 1002. When the computer program is executed by the processing device 1001, the above-mentioned functions defined in the method of the embodiment disclosed in the present application are executed.

[0209] The high-precision angle measurement device of the millimeter-wave radar provided in the present application adopts the high-precision angle measurement method of the millimeter-wave radar in the above embodiment, which can solve the technical problem of how to achieve a significant improvement in the accuracy of angle estimation with a smaller amount of calculation. Compared with the prior art, the beneficial effects of the high-precision angle measurement device of the millimeter-wave radar provided in the present application are the same as the beneficial effects of the high-precision angle measurement method of the millimeter-wave radar provided in the above embodiment, and other technical features in the high-precision angle measurement device of the millimeter-wave radar are the same as the features disclosed in the method of the previous embodiment, which will not be repeated here.

[0210] It should be understood that the various parts disclosed in this application can be implemented by hardware, software, firmware or a combination thereof. In the description of the above embodiments, specific features, structures, materials or characteristics can be combined in any one or more embodiments or examples in a suitable manner.

[0211] The above is only a specific implementation of the present application, but the protection scope of the present application is not limited thereto. Any person skilled in the art who is familiar with the present technical field can easily think of changes or substitutions within the technical scope disclosed in the present application, which should be included in the protection scope of the present application. Therefore, the protection scope of the present application should be based on the protection scope of the claims.

[0212] The present application provides a computer-readable storage medium having computer-readable program instructions (ie, computer programs) stored thereon, and the computer-readable program instructions are used to execute the high-precision angle measurement method of the millimeter-wave radar in the above-mentioned embodiment.

[0213] The computer-readable storage medium provided in the present application may be, for example, a USB flash drive, but is not limited to electrical, magnetic, optical, electromagnetic, infrared, or semiconductor systems, systems or devices, or any combination of the above. More specific examples of computer-readable storage media may include, but are not limited to: an electrical connection with one or more wires, a portable computer disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the above. In this embodiment, the computer-readable storage medium may be any tangible medium containing or storing a program that can be used by or in combination with an instruction execution system, system or device. The program code contained on the computer-readable storage medium may be transmitted using any appropriate medium, including but not limited to: wires, optical cables, RF (Radio Frequency), etc., or any suitable combination of the above.

[0214] The computer-readable storage medium may be included in the high-precision angle measurement device of the millimeter-wave radar; or may exist independently without being assembled into the high-precision angle measurement device of the millimeter-wave radar.

[0215] The computer-readable storage medium carries one or more programs. When the one or more programs are executed by the high-precision angle measurement device of the millimeter-wave radar, the high-precision angle measurement device of the millimeter-wave radar: obtains an echo signal and a target steering vector; obtains an initial angle using a discretized angle space based on the echo signal and the target steering vector; obtains an angle offset based on the initial angle; obtains a reference angle value based on the angle offset and the discretized angle space; and uses the reference angle value as the target angle when a preset condition is met.

[0216] Computer program code for performing the operations of the present application may be written in one or more programming languages ​​or a combination thereof, including object-oriented programming languages ​​such as Java, Smalltalk, C++, and conventional procedural programming languages ​​such as "C" or similar programming languages. The program code may be executed entirely on the user's computer, partially on the user's computer, as a separate software package, partially on the user's computer and partially on a remote computer, or entirely on a remote computer or server. In the case of a remote computer, the remote computer may be connected to the user's computer through any type of network, including a local area network (LAN) or a wide area network (WAN), or may be connected to an external computer (e.g., via the Internet using an Internet service provider).

[0217] The flow chart and block diagram in the accompanying drawings illustrate the possible architecture, function and operation of the system, method and computer program product according to various embodiments of the present application. In this regard, each square box in the flow chart or block diagram can represent a module, a program segment or a part of a code, and the module, the program segment or a part of the code contains one or more executable instructions for realizing the specified logical function. It should also be noted that in some alternative implementations, the functions marked in the square box can also occur in a sequence different from that marked in the accompanying drawings. For example, two square 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 square box in the block diagram and / or flow chart, and the combination of the square boxes in the block diagram and / or flow chart can be implemented with a dedicated hardware-based system that performs a specified function or operation, or can be implemented with a combination of dedicated hardware and computer instructions.

[0218] The modules involved in the embodiments described in this application may be implemented by software or hardware, wherein the name of the module does not constitute a limitation on the unit itself in some cases.

[0219] The readable storage medium provided in the present application is a computer-readable storage medium, which stores computer-readable program instructions (i.e., computer programs) for executing the high-precision angle measurement method of the above-mentioned millimeter-wave radar, and can solve the technical problem of how to achieve a significant improvement in the angle estimation accuracy with a smaller amount of calculation. Compared with the prior art, the beneficial effects of the computer-readable storage medium provided in the present application are the same as the beneficial effects of the high-precision angle measurement method of the millimeter-wave radar provided in the above-mentioned embodiment, and will not be repeated here.

[0220] The present application also provides a computer program product, including a computer program, which, when executed by a processor, implements the steps of the high-precision angle measurement method of the millimeter-wave radar as described above.

[0221] The computer program product provided by the present application can solve the technical problem of how to achieve a significant improvement in the accuracy of angle estimation with a smaller amount of calculation. Compared with the prior art, the beneficial effects of the computer program product provided by the present application are the same as the beneficial effects of the high-precision angle measurement method of the millimeter-wave radar provided in the above embodiment, and will not be repeated here.

[0222] The above descriptions are only some embodiments of the present application, and are not intended to limit the patent scope of the present application. All equivalent structural changes made using the contents of the present application specification and drawings under the technical concept of the present application, or direct / indirect applications in other related technical fields are included in the patent protection scope of the present application.

Claims

1. A high-precision angle measurement method for millimeter-wave radar, characterized in that: The method comprises: Acquire echo signals and target guidance vectors; Obtaining an initial angle using a discretized angle space according to the echo signal and the target steering vector; Obtaining an angle offset according to the initial angle; Based on the angle offset, the discretized angle space is refined to obtain a reference angle value; When the preset conditions are met, the reference angle value is used as the target angle.

2. The method according to claim 1, characterized in that The step of obtaining an initial angle using a discretized angle space according to the echo signal and the target steering vector comprises: Determine the angle space range to be searched according to the field of view angle range of the millimeter wave radar; The angle space range to be searched is discretized to obtain a discretized angle space.

3. The method according to claim 1, characterized in that The step of obtaining an initial angle using a discretized angle space according to the echo signal and the target steering vector comprises: Obtaining an array receiving signal according to the echo signal; Obtaining a covariance matrix according to the array received signal; Performing eigendecomposition on the covariance matrix to obtain eigenvalues ​​of the received signal; Obtaining a noise subspace according to the characteristic value; Based on the discretized angle space, an initial angle is obtained according to the noise subspace and the target steering vector.

4. The method according to claim 1, characterized in that The step of obtaining the angle offset according to the initial angle comprises: Obtaining an angle estimate taking into account an angle offset according to the initial angle; Based on a first-order Taylor expansion formula, a first-order Taylor steering vector taking into account the angle offset is obtained; The angle offset is obtained according to the angle estimation value and the first-order Taylor steering vector.

5. The method according to claim 1, characterized in that The step of refining the discretized angle space based on the angle offset to obtain a reference angle value comprises: According to the initial angle, obtaining a corresponding discretized angle value of the discretized angle space; The discretized angle value is refined according to the angle offset to obtain a reference angle value.

6. The method according to claim 1, characterized in that The step of using the reference angle value as the target angle when the preset condition is met includes: Get the offset threshold and iteration threshold; When the angle offset is less than or equal to the offset threshold or the number of iterations is equal to the iteration threshold, it is determined that a preset condition is met, and the reference angle value is used as the target angle.

7. The method according to claim 6, characterized in that Before the step of determining that a preset condition is satisfied and taking the reference angle value as the target angle when the angle offset is less than or equal to the offset threshold or the number of iterations is equal to the iteration threshold, the step includes: When the angle offset is greater than the offset threshold and the number of iterations is less than the iteration threshold, return to the step of obtaining the angle offset according to the initial angle.

8. The method according to claim 1, characterized in that The step of acquiring the echo signal and the target steering vector comprises: The transmission signal and the receiving signal are processed by the millimeter wave radar to obtain an echo signal; Obtaining a wavelength and an array element spacing according to the echo signal; A target steering vector is obtained according to the wavelength and the array element spacing.

9. A high-precision angle measurement device for millimeter-wave radar, characterized in that: The device comprises: An acquisition module, used for acquiring echo signals and target guidance vectors; An angle measurement module, used to obtain an initial angle using a discretized angle space according to the echo signal and the target steering vector; The angle measuring module is further used to obtain an angle offset according to the initial angle; The angle measurement module is further used to refine the discretized angle space based on the angle offset to obtain a reference angle value; The angle measuring module is further configured to use the reference angle value as a target angle when a preset condition is met.

10. A storage medium, characterized in that: The storage medium is a computer-readable storage medium, and a computer program is stored on the storage medium. When the computer program is executed by a processor, the steps of the high-precision angle measurement method of the millimeter-wave radar according to any one of claims 1 to 8 are implemented.

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