A single waveform based millimeter wave radar velocity resolution method and system

Abstract

The application relates to a single-waveform-based millimeter wave radar speed unblurring method, which utilizes the overall speed consistency of a target, performs speed unblurring on multi-point cloud speed clustering of the same target, greatly reduces system complexity and hardware cost, significantly improves the real-time performance and calculation efficiency of the algorithm, and simplifies the algorithm flow and engineering implementation difficulty.

Description

Technical Field

[0001] This invention belongs to the field of millimeter-wave radar technology, and more specifically, relates to a method and system for deambiguing the velocity of millimeter-wave radar based on a single waveform. Background Technology

[0002] With the rapid development of autonomous driving, intelligent transportation, and other fields, deep fusion has been achieved among sensors such as cameras, LiDAR, and millimeter-wave radar. Compared to sensors like LiDAR and cameras, millimeter-wave radar utilizes the Doppler frequency offset effect to achieve high-precision speed measurement, effectively compensating for the shortcomings of sensor speed measurement performance. However, millimeter-wave radar speed measurement has significant technical bottlenecks. Limited by both the hardware performance and waveform design of millimeter-wave radar, the radar cannot collect a large number of chirps in the fast time dimension, resulting in a limited range of Doppler frequencies that can be processed. When the relative speed between the target and the radar exceeds the measurable range, the target vehicle speed measured by the radar becomes blurred. The current mainstream speed de-ambiguation method is AB wave matching. By setting different idle times between the A-wave and B-wave chirps and alternately transmitting the two waveforms, two range-velocity spectra with different speed resolutions are obtained. At this time, the same target is located at different positions in the range-velocity spectra of the AB waves. Conventional solutions use the Chinese Remainder Theorem (CRT) and its improved algorithm to perform AB wave speed matching to obtain the optimal number of speed ambiguity cycles.

[0003] The patent document "A Method and System for Deambiguity of Millimeter-Wave Radar Velocity" (application date: November 26, 2024, publication number: CN119179072A) discloses a method and system for deambiguity of millimeter-wave radar. This patent uses the angle of the target in the AB wave as a constraint condition, and further uses the remainder theorem to perform velocity deambiguity matching based on the angle information. This method transmits two waveforms and performs matching processing on all point clouds, greatly increasing the algorithm's time consumption and hardware overhead, and reducing the algorithm's real-time performance.

[0004] To address the shortcomings of current AB wave deblurring techniques, this invention proposes a velocity deblurring method based on a single waveform. By utilizing the overall velocity consistency of the target, multi-point cloud velocity clustering of the same target is performed for velocity deblurring, which greatly simplifies the velocity deblurring process and reduces algorithm complexity. Summary of the Invention

[0005] This invention provides a method for deambiguing the velocity of millimeter-wave radar based on a single waveform, the method comprising the following steps:

[0006] S1: The millimeter-wave radar transmits and receives chirp signals. After sampling and mixing the raw data, ADC data is obtained. Two-dimensional FFT processing is performed on it to obtain a range-velocity 2D spectrum.

[0007] S2: Perform CFAR processing on the range-velocity 2D spectrogram to detect point cloud targets, and further perform angle measurement processing to obtain range-velocity-angle 3D information;

[0008] S3: Obtain the vehicle's speed using CAN communication or a self-estimated speed algorithm, calculate the projected speed of the vehicle in the target direction, and use the projected speed and radar-measured speed to distinguish between stationary and dynamic targets;

[0009] S4: Based on the speed projection relationship between this vehicle and the target, calculate the actual speed of the dynamic target under different fuzzy circles. If the difference between the actual speed of this vehicle and other dynamic targets within a certain distance range is less than a certain threshold, the two points are successfully matched, and the matching mark is incremented by one.

[0010] S5: Determine the number of speed ambiguity circles based on the maximum number of markers to obtain the target's true speed.

[0011] This invention provides a single-waveform-based millimeter-wave radar velocity deambiguation system, the system comprising:

[0012] Signal receiving unit: Uses millimeter-wave radar to transmit and receive chirp signals, samples and mixes the raw data to obtain ADC data, performs two-dimensional FFT processing on it to obtain a range-velocity 2D spectrum;

[0013] Target detection unit: Performs CFAR processing on the range-velocity 2D spectrogram to detect point cloud targets, and further performs angle measurement processing to obtain range-velocity-angle 3D information;

[0014] Target differentiation unit: The vehicle speed is obtained using CAN communication or self-estimated speed algorithm, and the projected speed of the vehicle in the target direction is calculated; the projected speed and the radar measured speed are used to differentiate between stationary and moving targets;

[0015] Target matching unit: Based on the speed projection relationship between the vehicle and the target, calculate the actual speed of the dynamic target under different fuzzy circles. If the difference between the actual speed of the target and other dynamic targets within a certain distance range is less than a certain threshold, the two points are successfully matched, and the matching mark is incremented by one.

[0016] Velocity estimation unit: Determines the velocity fuzzy circle number based on the maximum number of markers to obtain the target's true velocity.

[0017] An electronic device includes a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor, when executing the computer program, implements the aforementioned single-waveform-based millimeter-wave radar velocity deambiguation method.

[0018] A computer-readable storage medium storing a computer program that, when executed by a processor, implements the above-described single-waveform-based millimeter-wave radar velocity deambiguation method.

[0019] Compared with the prior art, the beneficial effects of the present invention are as follows:

[0020] 1. Significantly reduces system complexity and hardware overhead: This invention only requires transmitting and receiving one waveform. Compared with the traditional scheme that requires alternating transmission and processing of two waveforms (AB wave), it significantly simplifies the waveform scheduling design and hardware implementation complexity of the radar front end, and reduces the system's hardware requirements for data processing bandwidth and storage.

[0021] 2. Significantly improves the real-time performance and computational efficiency of the algorithm: This method abandons the complex process of pairwise matching and remainder theorem solving of the entire point cloud in traditional schemes, and instead utilizes the "overall speed consistency" of the target itself for clustering. This approach greatly reduces the amount of computation, improves the algorithm's running efficiency, and makes it more suitable for dynamic scenarios with high real-time requirements.

[0022] 3. Simplified algorithm flow and engineering implementation difficulty: By utilizing the velocity distribution characteristics of multiple point clouds on the same target for clustering and defuzzification, the logic is more intuitive, avoiding complex cross-waveform matching and angle constraint decision processes. This makes the algorithm development, debugging, and optimization easier, more robust, and easier to deploy and apply in practical systems. Attached Figure Description

[0023] To more clearly illustrate the technical solutions of the embodiments of this application, the drawings used in the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments of this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0024] Figure 1 This is a flowchart of this application;

[0025] Figure 2 This is the single-waveform diagram used in this application;

[0026] Figure 3 This is a model diagram of the radar antenna used in this application;

[0027] Figure 4 This is the physical model diagram of the algorithm in this application. Detailed Implementation

[0028] The embodiments of this application will now be described in detail with reference to the accompanying drawings.

[0029] The following specific examples illustrate the implementation of this application. Those skilled in the art can easily understand other advantages and effects of this application from the content disclosed in this specification. Obviously, the described embodiments are only a part of the embodiments of this application, and not all of them. This application can also be implemented or applied through other different specific embodiments, and the details in this specification can also be modified or changed based on different viewpoints and applications without departing from the spirit of this application. It should be noted that, in the absence of conflict, the following embodiments and features in the embodiments can be combined with each other. Based on the embodiments in this application, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of this application.

[0030] It should be noted that various aspects of embodiments within the scope of the appended claims are described below. It will be apparent that the aspects described herein can be embodied in a wide variety of forms, and any particular structure and / or function described herein is merely illustrative. Based on this application, those skilled in the art will understand that one aspect described herein can be implemented independently of any other aspect, and two or more of these aspects can be combined in various ways. For example, any number and aspects set forth herein can be used to implement the device and / or practice the method. Additionally, this device and / or method can be implemented using structures and / or functionalities other than one or more of the aspects set forth herein.

[0031] Additionally, specific details are provided in the following description to facilitate a thorough understanding of the examples. However, those skilled in the art will understand that practice can be carried out without these specific details.

[0032] This specification presents an embodiment of a millimeter-wave radar velocity deambiguation method based on a single waveform. The method includes the following steps:

[0033] S1: The millimeter-wave radar transmits and receives chirp signals. After sampling and mixing the raw data, ADC data is obtained. Two-dimensional FFT processing is performed on it to obtain a range-velocity 2D spectrum.

[0034] S1-1: In the original data sampling, a single real sampling is used. For each single real sampling, the mathematical expression of the mixing signal for a target at a distance of R is:

[0035] Where A is the signal amplitude. Let B be the frequency modulation slope of the chirp signal, B be the signal bandwidth, and T be the effective transmission duration. For carrier frequency, Let be the round-trip time of the electromagnetic wave, 2R be the round-trip distance of the electromagnetic wave, and c be the speed of light. For targets at different distances, the frequency of the mixing signal is proportional to the return delay, and further proportional to the target distance. With a sampling point count of... Sampling frequency Under these conditions, by performing a one-dimensional FFT on the mixed signal, the distance resolution expression can be calculated: .

[0036] S1-2: For a moving target, the target distance can be calculated by using the frequency change of the frequency-modulated signal in the fast time dimension. In the slow time dimension, multiple chirps are collected in one frame, and the phase difference between the various mixing signals of the target caused by the Doppler effect is used to calculate the target's motion speed information.

[0037] In the fast time dimension, a single chirp is processed. Point sampling, in the slow time dimension, for Each chirp is sampled, and the size of its data packet is [size missing]. The matrix is ​​a two-dimensional matrix. First, a distance-dimensional FFT transformation is performed on the matrix, then a velocity-dimensional FFT transformation is performed to obtain the distance-velocity spectrum (RD Map).

[0038] S2: Perform CFAR processing on the range-velocity 2D spectrum to detect point cloud targets. Further perform angle measurement processing to obtain range-velocity-angle 3D information. Let N be the total number of point cloud targets detected after CFAR processing. The CFAR threshold is dynamically solved using the CA-CAFR algorithm. The range of the z-th point cloud target after radar resolution is... The speed is , angle is , denoted as { , , At this point, the radar's target resolution speed is an ambiguity speed.

[0039] The angle measurement process includes:

[0040] S2-1: Assuming the energy value of the detected unit in the RD spectrum is E, the detection threshold for the detected unit in the distance dimension strip is... Where M is the number of single-sided detection units, , These represent the energy of the training units on the left and right sides, respectively. It is an adjustable threshold coefficient;

[0041] S2-2: The detection threshold of the detected unit on the velocity dimension strip. Where M is the number of single-sided detection units, , These represent the training unit energies on the upper and lower sides, respectively. It is an adjustable threshold coefficient;

[0042] S2-3: When there is energy in the detected unit When the cell is considered a real target, the distance and velocity information of the point are recorded, and the corresponding multi-channel complex data is acquired.

[0043] S2-4: Assume the incident angle is... According to geometric relationships, the phase difference caused by the spacing between adjacent antennas satisfy , can be obtained ; DOA estimation is performed using angle-dimensional FFT. FFT processing is performed on the multi-channel complex data of the target that exceeds the CFAR threshold. The direction information of the target signal is mapped to the frequency domain to obtain the angle spectrum. The peak value of the angle spectrum corresponds to the true angle of arrival of the target.

[0044] The radar antenna uses a uniform linear array with 2 transmit and 3 receive elements, and has 6 virtual channels. The spacing between adjacent radar elements is... , The wavelength is the signal wavelength.

[0045] S3: Obtain the vehicle's speed using CAN communication or a self-estimated speed algorithm, and calculate the projected speed of the vehicle in the target direction; use the projected speed and radar-measured speed to distinguish between stationary and moving targets; specifically including:

[0046] Use CAN communication to obtain the vehicle speed from the vehicle body. The projected velocity of this vehicle in the z-th point cloud direction is Assume the true velocity of the z-th point cloud relative to the Earth coordinate system is... The projection velocity of the point cloud relative to the radar's direction of motion is Among them, the speed of vehicles traveling in the same direction as this vehicle A negative value indicates the speed of travel in opposite directions. The value is positive.

[0047] S4: Based on the speed projection relationship between this vehicle and the target, calculate the true speed of the dynamic target under different ambiguity circles. If the difference between the true speed of this target and other dynamic targets within a certain distance range is less than a certain threshold, the two points are successfully matched, and the matching marker count is incremented by one; assuming the theoretical speed of radar measurement of point clouds is... The maximum speed measurement range of the radar is Specifically, it includes:

[0048] Based on the geometric projection relationship between the vehicle's speed and the target point cloud speed, we have the following formula: ,

[0049] Where n is the velocity ambiguity circle number, and n takes values ​​of -2, -1, 0, 1, 2, representing the maximum unambiguous velocity measurement by the radar. The speed reaches 120 km / h; the velocity of the z-th point cloud target after radar resolution is... , angle is The speed of this vehicle The true velocity of the z-th point cloud relative to the Earth coordinate system is ;

[0050] When the theoretical speed of radar measurement of point clouds When the speed does not exceed the radar's maximum speed measurement range, n=0; the radar measures the speed of the point cloud. ;

[0051] When the theoretical speed of radar measurement of point clouds When the speed exceeds the radar's maximum velocity measurement range, n≠0, and the radar's measurement velocity of the point cloud will become blurred. The measured velocity and the theoretical velocity will satisfy the following relationship: ;

[0052] The velocity threshold for a stationary target is defined; using the above formula, the assumed target velocity relative to the geodetic coordinate system is calculated by traversing different fuzzy cycles. If it exists The target is considered stationary relative to the geodetic coordinate system and is therefore excluded from subsequent calculations, thus reducing the computational load.

[0053] For targets not classified as stationary, they are marked as dynamic point cloud targets. The dynamic point cloud is sorted in ascending order of distance. Assuming point i is selected as the dynamic target, the target's velocity relative to the geodetic coordinate system at fuzzy circle number n is obtained. Typically, a sedan's dimensions are 2m wide and 6m long; therefore, a lateral distance threshold is set. The longitudinal distance threshold is 1.5m. Given a point cloud of 3m, perform traversal calculations on other point clouds. Assuming a selected point j, if the spatial distribution satisfies:

[0054]

[0055]

[0056] We then assume that points i and j may be different point clouds of the same vehicle body in spatial distribution. Assuming that points i and j originate from the same vehicle body, their velocities relative to the Earth's coordinate system must be similar. Therefore, we set a threshold for the velocity difference relative to the Earth's coordinate system, since they belong to the same vehicle body. The speed is 2 m / s, where the distance to the j-th point cloud target calculated by the radar is... , angle is ;

[0057] The velocity of the target relative to the geodetic coordinate system at point j under fuzzy circle number m is calculated by traversing the coordinate system. The relative geodetic coordinate system velocity difference between point i and point j under different fuzzy circle numbers is calculated. ,like If point i and point j belong to the same vehicle body, then the number of successful clusterings of point i when the speed fuzzy circle number is n is considered to be [missing information]. Add 1.

[0058] S5: Determine the velocity fuzzy circle number based on the maximum number of markers to obtain the target's true velocity. This specifically includes: the number of successful clusterings of point i at different velocity fuzzy circle numbers obtained in step S4. If the number of successful clusterings is maximized when the number of fuzzy cycles is n=q, and the number of successful clusterings is greater than 4 points, then... If the value is greater than 4, it is considered that there are multiple targets in the space near point i, all of which meet the speed constraint relationship of the same vehicle body. It is determined that the multiple points have the characteristics of coming from the same vehicle body. When the speed ambiguity circle number of point i is q, the radar measurement speed is real and unambiguous.

[0059] Based on the above steps, the velocity ambiguity number q of point i is calculated, and the velocity of point i relative to the radar is set to an unambiguous velocity. Complete the speed deblurring.

[0060] This invention employs a velocity-based defuzzification method based on a single waveform. It utilizes the overall velocity consistency of the same target to cluster multi-point clouds, replacing the complex process of relying on dual-waveform matching and the remainder theorem in the traditional AB-wave scheme. This method significantly reduces the complexity of waveform scheduling and hardware design while maintaining defuzzification performance, substantially improving the algorithm's real-time performance and computational efficiency, and simplifying engineering implementation.

[0061] This invention provides a single-waveform-based millimeter-wave radar velocity deambiguation system, the system comprising:

[0062] Signal receiving unit: Uses millimeter-wave radar to transmit and receive chirp signals, samples and mixes the raw data to obtain ADC data, performs two-dimensional FFT processing on it to obtain a range-velocity 2D spectrum;

[0063] Target detection unit: Performs CFAR processing on the range-velocity 2D spectrogram to detect point cloud targets, and further performs angle measurement processing to obtain range-velocity-angle 3D information;

[0064] Target differentiation unit: The vehicle speed is obtained using CAN communication or self-estimated speed algorithm, and the projected speed of the vehicle in the target direction is calculated; the projected speed and the radar measured speed are used to differentiate between stationary and moving targets;

[0065] Target matching unit: Based on the speed projection relationship between the vehicle and the target, calculate the actual speed of the dynamic target under different fuzzy circles. If the difference between the actual speed of the target and other dynamic targets within a certain distance range is less than a certain threshold, the two points are successfully matched, and the matching mark is incremented by one.

[0066] Velocity estimation unit: Determines the velocity fuzzy circle number based on the maximum number of markers to obtain the target's true velocity.

[0067] An electronic device includes a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor, when executing the computer program, implements the aforementioned single-waveform-based millimeter-wave radar velocity deambiguation method.

[0068] A computer-readable storage medium storing a computer program that, when executed by a processor, implements the above-described single-waveform-based millimeter-wave radar velocity deambiguation method.

[0069] Those skilled in the art will understand that all or part of the processes in the methods of the above embodiments can be implemented by a computer program instructing related hardware. The computer program can be stored in a non-volatile computer-readable storage medium, and when executed, it can include the processes of the embodiments of the above methods. Any references to memory, storage, databases, or other media used in the embodiments provided in this application can include non-volatile and / or volatile memory. Non-volatile memory can include read-only memory (ROM), programmable ROM (PROM), electrically programmable ROM (EPROM), electrically erasable programmable ROM (EEPROM), or flash memory. Volatile memory can include random access memory (RAM) or external cache memory. By way of illustration and not limitation, RAM is available in various forms, such as static RAM (SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), dual data rate SDRAM (DDRSDRAM), enhanced SDRAM (ESDRAM), synchronous link DRAM (SLDRAM), Rambus direct RAM (RDRAM), direct memory bus dynamic RAM (DRDRAM), and memory bus dynamic RAM (RDRAM), etc.

[0070] In this specification, the same or similar parts between the various embodiments can be referred to mutually. Each embodiment focuses on describing the differences from other embodiments. In particular, the descriptions of the embodiments described later are relatively simple, and relevant parts can be referred to the descriptions of the foregoing embodiments.

[0071] The above description is merely a specific embodiment of this application, but the scope of protection of this application is not limited thereto. Any variations or substitutions that can be easily conceived by those skilled in the art within the technical scope disclosed in this application should be included within the scope of protection of this application. Therefore, the scope of protection of this application should be determined by the scope of the claims.

Claims

1. A single waveform based millimeter wave radar velocity resolution ambiguity method, characterized by, The method includes the following steps: S1: The millimeter-wave radar transmits and receives chirp signals. After sampling and mixing the raw data, ADC data is obtained. Two-dimensional FFT processing is performed on it to obtain a range-velocity 2D spectrum. S2: Perform CFAR processing on the range-velocity 2D spectrogram to detect point cloud targets, and further perform angle measurement processing to obtain range-velocity-angle 3D information; S3: Obtain the vehicle's speed using CAN communication or a self-estimated speed algorithm, calculate the projected speed of the vehicle in the target direction, and use the projected speed and radar-measured speed to distinguish between stationary and dynamic targets; S4: Based on the relationship between the vehicle's speed and the target point cloud velocity projection, calculate the true speed of the dynamic target under different blurring cycles. If the difference between the true speed of the target and other dynamic targets within a certain distance range is less than a certain threshold, the two points are successfully matched, and the clustering success count is incremented by one. Specifically, this includes: Assuming that the radar measures the theoretical speed of the point cloud as , the maximum speed range of the radar is , specifically including: Based on the geometric projection relationship between the vehicle's speed and the target point cloud speed, we have the following formula: , Where n is the velocity ambiguity circle number, and n takes values ​​of -2, -1, 0, 1, 2, representing the maximum unambiguous velocity measurement by the radar. The speed reaches 120 km / h; the velocity of the z-th point cloud target after radar resolution is... , angle is The speed of this vehicle The true velocity of the z-th point cloud relative to the Earth coordinate system is ; When the theoretical speed of radar measurement of point clouds When the speed does not exceed the radar's maximum speed measurement range, n=0; the radar measures the speed of the point cloud. ; When the theoretical speed of radar measurement of point clouds When the speed exceeds the radar's maximum velocity measurement range, n≠0, and the radar's measurement velocity of the point cloud will become blurred. The measured velocity and the theoretical velocity will satisfy the following relationship: ; The velocity threshold for a stationary target is defined; using the above formula, the assumed target velocity relative to the geodetic coordinate system is calculated by traversing different fuzzy cycles. If it exists The target is considered stationary relative to the geodetic coordinate system and is therefore classified as a stationary target, and will not be included in subsequent calculations. For targets not identified as stationary, they are marked as dynamic point cloud targets. The dynamic point cloud is sorted in ascending order of distance. Assuming point i is selected as the dynamic target, the target's velocity relative to the geodetic coordinate system at fuzzy circle number n is obtained. Set the horizontal distance threshold. Vertical distance threshold Perform traversal calculations on other point clouds. Assuming point j is selected, if the spatial distribution satisfies: We then assume that points i and j are different locations within the same vehicle body in terms of spatial distribution; assuming that points i and j originate from the same vehicle body, their velocities relative to the Earth's coordinate system must be similar. We further define them as belonging to the same vehicle body, where the distance calculated from the j-th point cloud target by the radar is... , angle is , The threshold value for the velocity difference relative to the geodetic coordinate system; The velocity of the target relative to the geodetic coordinate system at point j under fuzzy circle number m is calculated by traversing the coordinate system. The relative geodetic coordinate system velocity difference between point i and point j under different fuzzy circle numbers is calculated. ,like If point i and point j belong to the same vehicle body, then the number of successful clusterings of point i when the speed fuzzy circle number is n is considered to be [missing information]. Add 1; S5: Determine the speed fuzzy circle number based on the maximum number of successful clusterings to obtain the target's true speed.

2. The millimeter-wave radar velocity deambiguation method based on a single waveform according to claim 1, characterized in that, Step S1 specifically includes: S1-1: In the original data sampling, a single real sampling is used. For each single real sampling, the mathematical expression of the mixing signal for a target at a distance of R is: ; Where A is the signal amplitude. Let B be the frequency modulation slope of the chirp signal, B be the signal bandwidth, and T be the effective transmission duration. For carrier frequency, Let √(2R) be the round-trip time of the electromagnetic wave, 2R be the round-trip distance of the electromagnetic wave, and c be the speed of light. For targets at different distances, the frequency of the mixing signal is proportional to the return delay, and further proportional to the target distance. With a sampling point count of... Sampling frequency Under these conditions, a one-dimensional FFT is performed on the mixed signal to calculate the distance resolution expression: ; S1-2: For a moving target, the target distance can be calculated by using the frequency change of the frequency-modulated signal in the fast time dimension. In the slow time dimension, multiple chirps are collected in one frame, and the phase difference between the various mixing signals of the target caused by the Doppler effect is used to calculate the target's motion speed information. In the fast time dimension, a single chirp is processed. Point sampling, in the slow time dimension, for Each chirp is sampled, and the size of its data packet is [size missing]. The matrix is ​​a two-dimensional matrix; the matrix is ​​first subjected to a distance-dimensional FFT transformation, and then to a velocity-dimensional FFT transformation to obtain the distance-velocity spectrum RD spectrum.

3. The millimeter-wave radar velocity deambiguation method based on a single waveform according to claim 1, characterized in that, The angle measurement process in step S2 specifically includes: S2-1: Assume the energy value of the detected unit in the RD spectrum is E, and the detection threshold of the detected unit in the distance dimension strip is... Where M is the number of single-sided detection units, , These represent the energy of the training units on the left and right sides, respectively. It is an adjustable threshold coefficient; S2-2: The detection threshold of the detected unit on the velocity dimension strip. Where M is the number of single-sided detection units, , These represent the training unit energies on the upper and lower sides, respectively. It is an adjustable threshold coefficient; S2-3: When there is energy in the detected unit When the cell is considered a real target, its distance and velocity information are recorded, and the corresponding multi-channel complex data is acquired. S2-4: Assume the incident angle is... According to geometric relationships, the phase difference caused by the spacing between adjacent antennas satisfy , can be obtained ; DOA estimation is performed using angle-dimensional FFT. FFT processing is performed on the multi-channel complex data of the target that exceeds the CFAR threshold. The direction information of the target signal is mapped to the frequency domain to obtain the angle spectrum. The peak value of the angle spectrum corresponds to the true angle of arrival of the target. The radar antenna uses a uniform linear array with 2 transmit and 3 receive elements, and has 6 virtual channels. The spacing between adjacent radar elements is [missing information]. , The wavelength is the signal wavelength.

4. The millimeter-wave radar velocity deambiguation method based on a single waveform according to claim 3, characterized in that, Let N be the total number of point cloud targets detected after CFAR processing. The CFAR threshold is dynamically calculated using the CA-CAFR algorithm. The distance to the z-th point cloud target after radar processing is... The speed is , angle is , denoted as { , , At this point, the radar's target resolution speed is an ambiguity speed.

5. The millimeter-wave radar velocity deambiguation method based on a single waveform according to claim 4, characterized in that, Step S3 specifically includes: Use CAN communication to obtain the vehicle speed from the vehicle body. The projected velocity of this vehicle in the z-th point cloud direction is Assume the true velocity of the z-th point cloud relative to the geodetic coordinate system is... The projection velocity of the point cloud relative to the radar's direction of motion is Among them, the speed of vehicles traveling in the same direction as this vehicle A negative value indicates the speed of travel in opposite directions. The value is positive.

6. The millimeter-wave radar velocity deambiguation method based on a single waveform according to claim 1, characterized in that, Step S5 specifically includes: Based on the number of successful clusterings of point i under different speed fuzzy cycle numbers obtained in step S4 If the number of successful clusterings is n=q when the number of fuzzy circles is n=q, and the number of successful clusterings is greater than 4, then... If the value is greater than 4, it is considered that there are multiple targets in the space near point i, all of which meet the speed constraint relationship of the same vehicle body. It is determined that the multiple points have the characteristics of coming from the same vehicle body. When the speed ambiguity circle number of point i is q, the radar measurement speed is real and unambiguous. Based on the above steps, the velocity ambiguity number q of point i is calculated, and the velocity of point i relative to the radar is set to an unambiguous velocity. Complete the speed deblurring.

7. A millimeter-wave radar velocity deambiguation system based on a single waveform, the system comprising: Signal receiving unit: Uses millimeter-wave radar to transmit and receive chirp signals, samples and mixes the raw data to obtain ADC data, performs two-dimensional FFT processing on it to obtain a range-velocity 2D spectrum; Target detection unit: Performs CFAR processing on the range-velocity 2D spectrogram to detect point cloud targets, and further performs angle measurement processing to obtain range-velocity-angle 3D information; Target differentiation unit: The vehicle speed is obtained using CAN communication or self-estimated speed algorithm, and the projected speed of the vehicle in the target direction is calculated; the projected speed and the radar measured speed are used to differentiate between stationary and moving targets; Target matching unit: Based on the speed projection relationship between the vehicle and the target, calculates the true speed of the dynamic target under different fuzzy circles. If the difference between the true speed of the target and other dynamic targets within a certain distance range is less than a certain threshold, the two points are successfully matched, and the clustering success count is incremented by one; specifically including: Assume the theoretical speed of radar measurement of point clouds is The maximum speed measurement range of the radar is Specifically, it includes: Based on the geometric projection relationship between the vehicle's speed and the target point cloud speed, we have the following formula: , Where n is the velocity ambiguity circle number, and n takes values ​​of -2, -1, 0, 1, 2, representing the maximum unambiguous velocity measurement by the radar. The speed reaches 120 km / h; the velocity of the z-th point cloud target after radar resolution is... , angle is The speed of this vehicle The true velocity of the z-th point cloud relative to the Earth coordinate system is ; When the theoretical speed of radar measurement of point clouds When the speed does not exceed the radar's maximum speed measurement range, n=0; the radar measures the speed of the point cloud. ; When the theoretical speed of radar measurement of point clouds When the speed exceeds the radar's maximum velocity measurement range, n≠0, and the radar's measurement velocity of the point cloud will become blurred. The measured velocity and the theoretical velocity will satisfy the following relationship: ; The velocity threshold for a stationary target is defined; using the above formula, the assumed target velocity relative to the geodetic coordinate system is calculated by traversing different fuzzy cycles. If it exists The target is considered stationary relative to the geodetic coordinate system and is therefore classified as a stationary target, and will not be included in subsequent calculations. For targets not identified as stationary, they are marked as dynamic point cloud targets. The dynamic point cloud is sorted in ascending order of distance. Assuming point i is selected as the dynamic target, the target's velocity relative to the geodetic coordinate system at fuzzy circle number n is obtained. If the size of the car is 2m wide and 6m long, set a lateral distance threshold. The longitudinal distance threshold is 1.5m. Given a point cloud of 3m, perform traversal calculations on other point clouds. Assuming a selected point j, if the spatial distribution satisfies: We then assume that points i and j are point clouds of different locations on the same vehicle body in terms of spatial distribution; assuming that points i and j originate from the same vehicle body, their velocities relative to the Earth's coordinate system must be similar. We set a threshold for the velocity difference relative to the Earth's coordinate system, since they belong to the same vehicle body. The speed is 2 m / s, where the distance to the j-th point cloud target calculated by the radar is... , angle is , The threshold value for the velocity difference relative to the geodetic coordinate system; The velocity of the target relative to the geodetic coordinate system at point j under fuzzy circle number m is calculated by traversing the coordinate system. The relative geodetic coordinate system velocity difference between point i and point j under different fuzzy circle numbers is calculated. ,like If point i and point j belong to the same vehicle body, then the number of successful clusterings of point i when the speed fuzzy circle number is n is considered to be [missing information]. Add 1; Velocity estimation unit: Determines the velocity fuzzy circle number based on the maximum number of successful clusterings to obtain the target's true velocity.

8. An electronic device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor, when executing the computer program, implements a single-waveform-based millimeter-wave radar velocity deambiguation method as described in any one of claims 1 to 6.

9. A computer-readable storage medium storing a computer program that, when executed by a processor, implements a single-waveform-based millimeter-wave radar velocity deambiguation method as described in any one of claims 1 to 6.

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