Speed ambiguity resolution method of millimeter wave radar, millimeter wave radar and product

Abstract

The invention provides a millimeter-wave radar speed ambiguity resolution method, a millimeter-wave radar and a product, and the method comprises the steps: dividing chirp frequency modulation signals into N chirp groups based on a grouping rule that the distance migration amount and the distance resolution of a target in segmented time meet a preset relation; performing M-order FFT processing on the N chirp groups to obtain a target spectrum data matrix; wherein M is greater than or equal to N; determining a potential target based on the target spectrum data matrix; and determining a corresponding data segment of the potential target in each chirp group, performing speed ambiguity resolution calculation based on the data segment, and determining the real speed of the potential target.

Description

Technical Field

[0001] The present application relates to the field of radar technology, and in particular to a velocity deambiguation method for a millimeter-wave radar, a millimeter-wave radar, and a computer program product. Background Art

[0002] Millimeter-wave radar detects and tracks targets by emitting and receiving electromagnetic waves, and can simultaneously measure the distance, speed, and angle of the target. Compared with cameras and lidars, millimeter-wave radars have good environmental and weather adaptability, and can adapt to application scenarios such as strong light, night, heavy rain, fog, and dust. They have been widely used in vehicle-mounted ADAS (Advanced Driving Assistance System) assisted driving systems and vehicle-mounted AD (Autonomous Driving) automatic driving systems. Through the mutual integration of cameras, lidars, and millimeter-wave radars, the redundancy of intelligent decision-making can be improved, and the high reliability and safety of ADAS assisted driving or AD automatic driving can be achieved.

[0003] Currently, the main frequency band of vehicle-mounted millimeter-wave radar is 77GHz, and the corresponding wavelength is 3.9mm. The target speed measurement range can reach 300km / h. According to the radar speed measurement range formula:

[0004]

[0005] It can be seen that T c <11.7us, where T c is the chirp period. However, this speed measurement range is usually difficult to achieve and speed defuzzification is required to meet the speed measurement requirements. Summary of the invention

[0006] In order to solve the existing technical problems, the present application provides a velocity deambiguation method of a millimeter wave radar for estimating the true velocity of a target based on the range migration effect of the target, a millimeter wave radar and a computer program product.

[0007] In a first aspect, a velocity deambiguation method for a millimeter-wave radar is provided, the method comprising:

[0008] Based on the preset relationship between the range migration amount and the range resolution of the target within the segment time as the grouping rule, the chirp frequency modulation signal is divided into N chirp groups;

[0009] Performing M-order FFT processing on the N chirp groups to obtain a target spectrum data matrix; wherein M≥N;

[0010] determining potential targets based on the target spectrum data matrix;

[0011] Determine the corresponding data segments of the potential target in each of the chirp groups, perform speed defuzzification calculation based on the data segments, and determine the true speed of the potential target.

[0012] In a second aspect, a vehicle-mounted millimeter-wave radar is provided, comprising a millimeter-wave radar processor and a memory, wherein the memory stores a computer program executable by the millimeter-wave radar processor;

[0013] When the computer program is executed by the millimeter-wave radar processor, the speed deambiguation method of the millimeter-wave radar described in any embodiment of the present application is implemented.

[0014] In a third aspect, a computer program product is provided, including a computer program, which, when executed by a processor, implements the velocity deambiguation method of the millimeter-wave radar described in any embodiment of the present application.

[0015] In the speed deambiguation method of the millimeter-wave radar provided in the above embodiment, the target spectrum data is obtained by FFT processing of all chirp frequency modulation signals, and the potential target is extracted by FFT processing of all chirp frequency modulation signals, so that the maximum speed range and SNR of the target will not be lost; all chirp frequency modulation signals are grouped based on the grouping rules, and the speed deambiguation calculation is performed according to the corresponding data segment of the potential target in each chirp group. Since the observation time corresponding to each chirp group is short, the distance migration effect in each chirp group can be ignored. The same column in the same chirp group contains all target information at the same distance, thereby avoiding the problem of target pairing, facilitating the determination of the target ambiguity according to the relative relationship of the target in each group of chirp frequency modulation signals, and helping to improve the estimation accuracy of the real speed of the target.

[0016] The vehicle-mounted millimeter-wave radar and computer program product provided in the above embodiments belong to the same concept as the corresponding millimeter-wave radar speed deambiguation method embodiment, and thus have the same technical effect as the corresponding millimeter-wave radar speed deambiguation method embodiment, and will not be repeated here. BRIEF DESCRIPTION OF THE DRAWINGS

[0017] Figure 1 FIG. 4 is a Fast-slow chirp waveform diagram in one embodiment.

[0018] Figure 2 FIG. 4 is a schematic diagram of a MIMO array in one embodiment.

[0019] Figure 3 FIG. 4 is a schematic diagram of a TDM-MIMO waveform in an embodiment.

[0020] Figure 4Schematic diagram of the amplitude-frequency result after FFT processing in one embodiment.

[0021] Figure 5 Schematic diagram of a radar processing hierarchical structure in one embodiment.

[0022] Figure 6 This is a diagram of optional application scenarios of a velocity deambiguation method for a millimeter-wave radar in one embodiment.

[0023] Figure 7 Schematic diagram of the working principle of a vehicle-mounted millimeter-wave radar in one embodiment.

[0024] Figure 8 Flow chart of a velocity deambiguation method for a millimeter-wave radar in one embodiment.

[0025] Fig. 9 Schematic diagram of the result of FFT processing of chirp.

[0026] Fig.10 The figure is a flow chart of a velocity defuzzification method in an optional specific example.

[0027] Fig.11 for Fig.10 An optional chirp waveform diagram is shown in the specific example.

[0028] Fig.12 for Fig.10 A schematic diagram of chirp grouping in an optional specific example is shown.

[0029] Fig.13 The figure is a working flow chart of the vehicle-mounted millimeter wave radar in one embodiment.

[0030] Fig.14 FIG. 4 is a schematic diagram of the structure of a millimeter wave radar in one embodiment. DETAILED DESCRIPTION

[0031] The technical solution of the present invention is further described in detail below in conjunction with the accompanying drawings and specific embodiments.

[0032] In order to make the purpose, technical solutions and advantages of the present application clearer, the present application will be further described in detail below in conjunction with the accompanying drawings. The described embodiments should not be regarded as limiting the present application. All other embodiments obtained by ordinary technicians in the field without making creative work are within the scope of protection of this application.

[0033] In the following description, the expression "some embodiments" is involved, which describes a subset of all possible embodiments. It should be noted that "some embodiments" may be the same subset or different subsets of all possible embodiments, and may be combined with each other without conflict.

[0034] In the following description, the terms "first, second, third" involved are merely used to distinguish similar objects and do not represent a specific ordering of the objects. It can be understood that "first, second, third" can be interchanged with a specific order or sequence where permitted, so that the embodiments of the present application described herein can be implemented in an order other than that illustrated or described herein.

[0035] In order to solve the speed measurement requirement problem of speed deambiguation of millimeter wave radar, the inventors of this application conducted in-depth research and analysis on the principles and defects of current speed deambiguation algorithms, and mainly divided speed deambiguation algorithms into three categories:

[0036] First, the speed expansion algorithm based on the Chinese remainder theorem

[0037] like Figure 1 As shown in Figure 1, the chirp frequency modulation signal is divided into a fast chirp segment and a slow chirp segment. The speed defuzzification principle of the speed expansion algorithm based on the Chinese remainder theorem is:

[0038] 1.1. Perform FFT in the velocity and distance dimensions on the fast chirp segment to obtain the corresponding distance-velocity map, namely RDM1.

[0039] 1.2. Perform FFT in the speed and distance dimensions on the slow chirp segment to obtain the corresponding distance-speed map, namely RDM2.

[0040] 1.3. When there is only one target, the position of the target on RDM1 is R1 and V1, and the position of the target on RDM2 is R2 and V2.

[0041] 1.4. The radar speed measurement range formula is as follows:

[0042]

[0043] Where T c Corresponding to Figure 1 Tc_1 and Tc_2 in the fast chirp segment, assuming that the maximum speed range is v max1 , the maximum speed measurement range of the slow chirp segment is v max2 . Then according to the constraint m*v max1 +V1=n*v max2 +V2, and m and n are both integers, the true speed of the target can be calculated.

[0044] The drawbacks of this method are:

[0045] 1.1, according to the velocity resolution formula, as follows:

[0046]

[0047] Where T f It is the working time of all chirps used by the speed dimension FFT. Since the fast chirp segment and the slow chirp segment each occupy a part of the working time, the speed resolution is reduced.

[0048] 1.2, since the SNR gain of the velocity dimension FFT is positively correlated with the number of chirps used, this method reduces the SNR gain before detection.

[0049] 1.3, when there are multiple speeds at the same distance, the target speed will be wrongly calculated due to the failure of target registration on the slow chirp and fast chirp.

[0050] Second, the velocity expansion algorithm based on the doppler phase deviation compensation assumption

[0051] The radar adopts TDM-MIMO working mode, such as Figure 2 As shown in the figure, the radar antenna's transmit array and receive array use TDM-MIMO to form a larger virtual array, and its transmit waveform is as follows: Figure 3 The velocity deambiguation principle of the velocity expansion algorithm based on the doppler phase offset compensation assumption is:

[0052] 2.1. Perform distance dimension and speed dimension fft on the data of the four receiving channels corresponding to Tx1.

[0053] 2.2. Perform distance dimension and speed dimension FFT on the data of the four receiving channels corresponding to Tx2.

[0054] 2.3. Assuming that the target position on the RDM of Tx1 is R1 and V1, the points on RDM of 8 receiving channels (4 for Tx1 and 4 for Tx2) can be selected as points on R1 and V1 to form an 8-channel sequence, and its arrangement is the same as Figure 2 The array format is consistent with .

[0055] 2.4. Since Tx1 and Tx2 do not work at the same time, the time interval is Tc. If the speed of the target is v, there will be a phase difference between the 4 receiving channels of Tx1 and the 4 receiving channels of Tx2. The phase difference is related to the speed v, and the formula is as follows: Formula 3:

[0056]

[0057] 2.5. Assume the target's true speed v r The range is from 0 to 2*v max, the target's speed on the RDM is V1, if the target's real speed is v r =V1, then the phases that need to be compensated for Tx1 and Tx2 can be calculated as follows:

[0058]

[0059] If the target's true velocity is v r =V1+v max , we can calculate the phases that need to be compensated for Tx1 and Tx2 at this time, as shown in Formula 5:

[0060]

[0061] 2.6. Perform azimuth FFT on two 8-element sequences after different phase compensation. The amplitude-frequency results of the two sequences after FFT are as follows: Figure 4 As shown, if the phase compensation value corresponding to the blue amplitude-frequency diagram is as follows:

[0062]

[0063] The actual target speed is V1; if the phase compensation value corresponding to the blue amplitude-frequency graph is, as shown in Formula 7:

[0064]

[0065] Then the real target speed is V1+v max .

[0066] The drawbacks of this method are:

[0067] 2.1, since the SNR gain of the velocity dimension FFT is positively correlated with the number of chirps used, this method reduces the SNR gain before detection;

[0068] 2.2, from the radar speed measurement range formula, as shown in the previous formula 1, the maximum speed measurement range corresponding to a single Tx is reduced.

[0069] 2.3, the extension range of the speed measurement range of this method is limited.

[0070] Third, velocity expansion algorithm based on target tracking hypothesis

[0071] like Figure 5 As shown in the figure, the radar processing process mainly includes analog front end (AFE) receiving data, digital front end (DFE) processing, range-doppler FFT processing, target detection (Detection), target tracking (Tracking), target classification (Classification), and obtaining the target list (Target List).

[0072] The velocity defuzzification principle of the velocity expansion algorithm based on the target tracking hypothesis is:

[0073] Use the information of the currently detected target, mainly including distance, speed (there are several possible speed conditions), and angle, to match it with the existing historical trajectory, and pair several possible speed conditions with the historical trajectory to find the speed value with the best match, which is the real speed of the target.

[0074] The drawbacks of this method are:

[0075] 3.1, there is a problem of target matching. When the target is matched incorrectly, the target velocity solution will be wrong.

[0076] 3.2, when the target has acceleration, the longer the tracking period, the worse the effect.

[0077] In order to solve the defects of the above-mentioned known speed deambiguation algorithm, the inventor of the present application proposed a technical idea of ​​resolving the speed ambiguity of millimeter-wave radar based on the range migration of the target. The chirp frequency modulation signal is divided into N chirp groups by setting a grouping rule based on the preset relationship between the range migration amount of the target within the segment time and the range resolution. The potential target is extracted by performing FFT processing on all chirp frequency modulation signals, which can ensure that the maximum speed range and SNR (Signal-to-Noise Ratio) gain of the target are not lost; the range migration effect within the same group of the chirp signal can be ignored, the tracking period can be reduced, and the target pairing problem can be avoided, which is conducive to improving the estimation accuracy of the target's true speed.

[0078] See also Figure 6 , which is an optional application scenario diagram of the millimeter wave radar speed deambiguation method provided in an embodiment of the present application applied to a vehicle. The vehicle-mounted millimeter wave radar 200 is usually installed on both sides of the front of the vehicle 100. Common installation locations are not limited to Figure 6 The forward position shown also includes the front corner, rear corner and rear corner positions, which are used to detect and perceive the surrounding environment targets (target 1, target 2, target 3).

[0079] See also Figure 7 , is a schematic diagram of the structure of the vehicle-mounted millimeter-wave radar. The vehicle-mounted millimeter-wave radar mainly consists of four functional parts:

[0080] 1) Antenna array, consisting of a transmitting array and a receiving array.

[0081] 2) MRTR (Millimeter-wave Radar Transceiver, millimeter-wave radar transceiver module or chip), millimeter-wave radar transceiver functional module, mainly composed of transmitting components, receiving components and linear frequency modulation local oscillator source components. MRTR generates and transmits the working waveform signal of the millimeter-wave radar, receives and discretely samples the reflected waveform signal of the target, and sends the sampled reflected waveform signal to the MRP (Millimeter-wave Radar Processor) millimeter-wave radar processor.

[0082] 3) MRP (Millimeter-wave Radar Processor), millimeter-wave radar processor, receives the reflected waveform signal from MRTR and performs digital processing to obtain information such as the distance, speed and angle of environmental targets, clusters, identifies and tracks targets, and outputs point cloud-level detection results or target-level detection results. From the main functional division, MRP is mainly composed of distance measurement module, speed measurement module, angle measurement module and target clustering identification and tracking module. The above modules can be implemented through embedded software, FPGA (Field Programmable Gate Array) or AISC (Application Specific Integrated Circuit) application-specific integrated circuits.

[0083] The speed deambiguation method of the millimeter wave radar provided in the embodiment of the present application is mainly completed in the MRP speed measurement module. The implementation form, composition mode or module division mode of MRP does not affect the use of the speed deambiguation method of the millimeter wave radar provided in the embodiment of the present application.

[0084] 4) A read-write memory used to store the working data of the millimeter-wave radar, including working parameter data and process data stored in advance.

[0085] It should be noted that the configuration form or composition method of the functional parts of the above-mentioned vehicle-mounted millimeter-wave radar does not affect the use of the speed deambiguation method of the millimeter-wave radar provided in the embodiment of the present application; in terms of application scenarios, the use of the speed deambiguation method of the millimeter-wave radar provided in the embodiment of the present application can be applied to all applications that use electromagnetic waves for target direction finding, and is not limited to vehicle-mounted millimeter-wave radar applications.

[0086] See also Figure 8 , a velocity deambiguation method for a millimeter wave radar provided in an embodiment of the present application, comprising the following steps:

[0087] S101, dividing the chirp frequency modulation signal into N chirp groups based on a grouping rule in which a range migration amount and a range resolution of a target within a segmented time satisfy a preset relationship.

[0088] Range migration refers to the fact that the echo signals of the same target at different time points fall into different units in the range direction due to the relative motion between the radar and the target. Range resolution refers to the minimum distance that the radar can distinguish between two targets in the radar image when other quantities of the two targets, such as direction or speed, are the same but the distances are different. Segmentation time refers to the time corresponding to the length of the chirp group.

[0089] Among them, all chirp frequency modulation signals are equally divided into groups. The number of chirp groups should not be too many, so that the SNR gain of each chirp group is low, so that the amplitude of the signal in the chirp group is greatly affected by noise; the number of chirp groups should not be too few, so that the duration of each chirp group is too long. For high-speed targets, the distance migration in each chirp group cannot be ignored. Based on the preset relationship between the distance migration of the target in the segmented time and the distance resolution as the grouping rule, the chirp frequency modulation signal is divided into N chirp groups. In this way, it can be ensured that the SNR gain of each chirp group is not lost, the amplitude of the signal can be avoided from being affected by noise, and the duration of each chirp group will not be too long. For high-speed targets, the difference in distance migration in each chirp group can be ignored. The same column in the same chirp group contains all target information at the same distance, which reduces the tracking cycle and avoids the problem of target pairing.

[0090] Optionally, the grouping rule is that the distance migration of the target within the segment time t is less than the distance resolution, and the segment time t can be used to determine the length of the chirp group; or the grouping rule is that the distance migration of the target within the segment time t is greater than the product of the distance resolution and the first ratio, and less than the product of the distance resolution and the second ratio; wherein the first ratio is 1 / 3, and the second ratio is 1 / 2; the distance migration is the product of the maximum possible speed of the target and the segment time t. The number of groups is preferably a power of 2.

[0091] In an optional example, assuming that the range resolution of the radar is R_res and the maximum possible speed of the target is Vel_max, then within the segment time t, 1 / 3*R_res <Vel_max*t<1 / 2*R_res。

[0092] S103, performing M-order FFT processing on the N chirp groups to obtain a target spectrum data matrix; wherein M≥N.

[0093] FFT (Discrete Fourier Transform) processing converts the time domain signal to the frequency domain through discrete Fourier processing. The target spectrum data matrix is ​​a two-dimensional data matrix obtained by performing M-order FFT processing on N chirp groups, that is, performing M-order FFT processing on all chirp frequency modulation signals. The horizontal and vertical axes of the data matrix are usually distance and speed.

[0094] S105: Determine potential targets based on the target spectrum data matrix.

[0095] According to the target spectrum data matrix, each point corresponds to a distance and speed. Screening is performed based on the amplitude of each point, and potential targets are screened out based on the positions of points with larger amplitudes.

[0096] It should be noted that the number of potential targets can be one or more. Each potential target corresponds to a coordinate point of the target spectrum data matrix, so each potential target corresponds to a distance and a speed.

[0097] S107, determining corresponding data segments of the potential target in each of the chirp groups, performing speed defuzzification calculation based on the data segments, and determining the real speed of the potential target.

[0098] In the same chirp group, the distance migration of the target can be ignored. In the spectrum data matrix of each chirp group, the same column contains the information of all targets (if any targets exist) at the same distance.

[0099] In the speed deambiguation method of the millimeter-wave radar provided in the above embodiment, the target spectrum data is obtained by FFT processing of all chirp frequency modulation signals, and the potential target is extracted by FFT processing of all chirp frequency modulation signals, so that the maximum speed range and SNR of the target will not be lost; all chirp frequency modulation signals are grouped based on the grouping rules, and the speed deambiguation calculation is performed according to the corresponding data segment of the potential target in each chirp group. Since the observation time corresponding to each chirp group is short, the distance migration effect in each chirp group can be ignored. The same column in the spectrum data matrix corresponding to the same chirp group contains all target information at the same distance, thereby avoiding the problem of target pairing, facilitating the determination of the target ambiguity according to the relative relationship of the target in each group of chirp frequency modulation signals, and helping to improve the estimation accuracy of the real speed of the target.

[0100] In some embodiments, S107 includes:

[0101] According to the distance R of the potential target, determining the matching data segments of the potential target in each of the chirp groups, and performing M-order FFT processing on the matching data segments respectively;

[0102] Determine, according to the speed V of the potential target, a matching data point of the potential target in each matching data segment;

[0103] Resolving velocity ambiguity of the potential target based on the matching data points;

[0104] According to the velocity ambiguity and the velocity V, the actual velocity of the potential target is determined.

[0105] According to the target spectrum data matrix obtained by performing M-order FFT processing on all chirp frequency modulation signals, all potential targets are screened out, and the distance R and speed V of each potential target are determined. For each potential target, the matching data segment of the potential target in each chirp group is determined according to the distance R, and then the matching data point of the potential target in the matching data segment is determined in combination with the speed V. According to the matching data points corresponding to the potential target determined based on the chirp frequency modulation signal of each chirp group, the speed ambiguity of the potential target is resolved by using the characteristics of each chirp group for the same potential target.

[0106] In the above embodiment, potential targets are determined by performing FFT processing on all chirp frequency modulation signals, and then a reasonable number of chirp groupings are performed on the chirp frequency modulation signals, and the corresponding data of each potential target in each chirp grouping is determined. Therefore, the relative relationship of the target in each chirp grouping can be used to resolve the speed ambiguity of the target, which can reduce the observation period, effectively retain the maximum speed measurement range, and improve the accuracy of the estimation of the target's true speed.

[0107] In some embodiments, each of the chirp groups is a first two-dimensional data matrix, wherein the abscissa of the first two-dimensional data matrix is ​​the ADC sample and the ordinate is the chirp index;

[0108] Step S103 includes:

[0109] Performing distance FFT processing on the ADC samples in the first two-dimensional data matrix to obtain a second two-dimensional data matrix; the abscissa of the second two-dimensional data matrix is ​​the distance, and the ordinate is the chirp index;

[0110] Perform M-order velocity FFT processing on the second two-dimensional data matrix to obtain a third two-dimensional data matrix; the abscissa of the third two-dimensional data matrix is ​​distance, and the ordinate is velocity.

[0111] See also Fig. 9 In the first two-dimensional data matrix, the horizontal axis is the ADC sample and the vertical axis is the chirp index. The kth row represents all sampling points of the kth chirp. Each point in the first two-dimensional matrix contains information about all targets. In the second two-dimensional data matrix, the horizontal axis is the distance and the vertical axis is the chirp index. Different columns of the second two-dimensional data matrix correspond to different distances, and each chirp in the same column contains information about all targets at that distance (if any targets exist). In the third two-dimensional data matrix, the horizontal axis is the distance and the vertical axis is the speed. When the amplitude of a point in the third two-dimensional data matrix is ​​significantly larger than that of other points, it can be regarded as a potential target at the distance and speed corresponding to the point.

[0112] In the above embodiment, by performing distance dimension FFT and speed dimension FFT processing on N chirp groups, and obtaining a target spectrum data matrix after performing FFT processing on all chirp frequency modulation signals to extract potential targets, it can be ensured that the maximum speed range and SNR of the extracted potential targets will not be lost.

[0113] In some embodiments, in step S107, resolving the velocity ambiguity of the potential target based on the matching data points includes:

[0114] determining, based on the amplitudes of the matching data points, an amplitude ratio of a reference matching data point relative to each of the matching data points;

[0115] The amplitude ratio is fitted with a Sinc function to resolve the velocity ambiguity of the potential target.

[0116] After the potential target is determined, according to the distance R and speed V of the potential target, Fig. 9 As shown in the matrix diagram on the right (the third two-dimensional data matrix), the red box and the green box correspond to two potential targets, and these two potential targets correspond to a distance and speed respectively. Select the first potential target (corresponding to Fig. 9 The red box in the matrix on the right side of the distance R of all chirps (corresponding to Fig. 9 The middle matrix diagram of the second two-dimensional data matrix, a section in the red column of the second two-dimensional data matrix), all of them are processed by M-order FFT. Then extract the matching data points with a speed of V in each section of the FFT processing results, and calculate the amplitude, and record their amplitudes as a1, a2, a3, and a4 respectively. Take a1 as the reference matching data point, divide a1 by a1, a2, a3, and a4 respectively, and obtain the amplitude ratios of the reference matching data point to each matching data point b1, b2, b3, and b4; by fitting b1, b2, b3, and b4 with the sinc function, the speed ambiguity of the potential target is solved, and then the true speed of the potential target is determined based on the speed ambiguity and the speed V.

[0117] It should be noted that, for each potential target among all potential targets, the above steps are respectively processed to determine the true speed of all potential targets respectively.

[0118] In the above embodiment, after determining the potential target, since all chirp frequency modulation signals are divided into N chirp groups, for each segment, the distance migration amount can be ignored, so each segment does not need to consider the impact of distance migration on it, and the chirp used in the speed defuzzification method is the same chirp group, so there is no need to consider the pairing problem of the target, and the observation period can be reduced while effectively retaining the maximum speed measurement range and SNR, thereby improving the accuracy of the estimation of the target's true speed.

[0119] In some embodiments, the velocity deambiguation method of the millimeter wave radar includes:

[0120] Based on different velocity ambiguities and their corresponding amplitude ratios, an ambiguity mapping table is formed;

[0121] The resolving the velocity ambiguity of the potential target based on the matching data points further includes:

[0122] According to the amplitude ratio of the matching data points of the current potential target, a search is performed in the ambiguity mapping table to determine the matching target speed ambiguity.

[0123] Among them, a large number of historical records of fitting amplitude ratios with Sinc functions are used to select typical amplitude ratio values ​​under different ambiguity conditions and store them to form an ambiguity mapping table. In the subsequent speed deambiguation processing, the method of fitting the amplitude ratio of the unknown target with the Sinc function can be replaced by the table lookup method. The amplitude ratios b1, b2, b3, and b4 calculated from the matching data points in the N chirp groups corresponding to the speed V of the unknown target are compared with the values ​​in the ambiguity mapping table to determine the speed ambiguity of the unknown target.

[0124] In an optional example, when the target distance is 45 meters and the true speed is 0 m / s, the target speed determined according to the detection result is 0 m / s, and b1≈b2≈b3≈b4≈1, indicating that the true speed of the target is 0 m / s; when the target distance is 45 meters and the true speed is 56 m / s, the target speed determined according to the detection result is 0 m / s, and b1=1, b2=1.23, b3=2.09, b4=6.70, indicating that there is a speed ambiguity in the target, and the true speed determined by speed deambiguation should be 56 m / s.

[0125] In the above embodiment, by forming an ambiguity mapping table and using a table lookup method to determine the speed ambiguity of the unknown target, it is beneficial to reduce the amount of calculation of the speed deambiguation method of the millimeter wave radar and improve the calculation efficiency.

[0126] In some embodiments, in step S107, determining the actual speed of the potential target according to the speed ambiguity and the speed V includes:

[0127] Based on the following speed calculation formulas, Formula 8 and Formula 9, determine the actual speed of the potential target;

[0128] v=V+k*v max ; (Formula 8)

[0129]

[0130] Among them, v refers to the true speed, k refers to the speed ambiguity, T c refers to the period of the chirp frequency modulation signal, and λ refers to the wavelength of the chirp frequency modulation signal.

[0131] The speed V of the potential target, that is, the speed V calculated by the radar and the maximum speed v measured by the radar max The relationship between the actual speed of the target satisfies the formula shown in formula 8.

[0132] In this way, by determining the velocity ambiguity of the target, the true velocity of the target can be determined.

[0133] In order to have a more comprehensive understanding of the velocity deambiguation method of the millimeter wave radar provided in the embodiment of the present application, please refer to Figures 10 to 12 ,by Figure 2 Taking the structure of the vehicle-mounted millimeter-wave radar shown in the figure as an example, the main working process of the vehicle-mounted millimeter-wave radar and the process of the speed deambiguation method of the millimeter-wave radar are explained.

[0134] Taking the 1T1R FMCW radar system as an example, the radar working waveform is as follows: Fig.11 shown.

[0135] According to the radar waveform parameters, as shown in Table 1 below:

[0136] Serial number matter value 1 Chirp starting frequency 76.5GHz 2 Frequency modulation bandwidth of a single chirp 150MHz 3 Single chirp effective working time 20us 4 Chirp cycle 35us 5 ADC sampling points 128 6 Chirp number 512

[0137] Divide all chirp frequency modulation signals into 4 segments to form N (N=4) chirp groups, such as Fig.12 The velocity defuzzification methods include:

[0138] S11, perform FFT processing on N chirp groups.

[0139] S12, determining the distance R and speed V of the potential target.

[0140] Among them, in steps S11 to S12, the MRP speed measurement module first performs M-order FFT processing on N chirps, where M≥N, and determines the distance R and speed V of the potential target according to the FFT processing results of all chirps.

[0141] S131, select all chirps in the first segment with a distance of R and perform M-order FFT processing.

[0142] S132, select a point with a velocity of V and calculate its amplitude, which is recorded as a1.

[0143] S141, select all chirps in the second segment with a distance of R and perform M-order FFT processing.

[0144] S142, select a point with a velocity of V and calculate its amplitude, which is recorded as a2.

[0145] S151, select all chirps in the third segment with a distance of R and perform M-order FFT processing.

[0146] S152, select a point with a velocity of V and calculate its amplitude, which is recorded as a3.

[0147] S161, select all chirps in the second segment with a distance of R and perform M-order FFT processing.

[0148] S162, select a point with a velocity of V and calculate its amplitude, which is recorded as a4.

[0149] S17, divide a1 by a1, a2, a3, a4 respectively to obtain b1, b2, b3, b4.

[0150] S18, resolve the velocity ambiguity by fitting b1, b2, b3, b4 with the sinc function.

[0151] Among them, steps S131 to S18 select all chirps in each segment of the distance R of the first potential target, perform M-order FFT processing on them, and find the amplitudes a1, a2, a3, and a4 of the points with a speed of V in the FFT processing results of each segment of the chirp, calculate the corresponding amplitude ratios b1, b2, b3, and b4, and perform speed defuzzification.

[0152] For the remaining potential targets, steps S131 to S18 are repeated to determine the velocity ambiguity of the remaining potential targets and calculate the true velocity.

[0153] The speed deambiguation method provided in the above embodiment estimates the real speed of the target based on the range migration effect of the target, and has at least the following effects:

[0154] First, before extracting the target, FFT is performed on all chirps, so the maximum speed range of the target is v max Compared with the known second-class deambiguation algorithm (the velocity expansion algorithm based on the doppler phase offset compensation assumption), the maximum velocity range v max The velocity resolution is larger than that of the known first-class defuzzification algorithm (the velocity expansion algorithm based on the Chinese remainder theorem); and there is no loss in signal-to-noise ratio compared with the known first-class and second-class defuzzification algorithms.

[0155] Second, all chirps are divided into several parts, which avoids the problem of target matching. At the same time, because the duration of each chirp is shortened, the distance migration effect within each chirp can be ignored. Compared with the known third type of defuzzification algorithm (speed expansion algorithm based on target tracking assumption), there is no need to consider the pairing problem of the target, the tracking period is reduced, and the speed defuzzification accuracy is high.

[0156] Third, the relative relationship of the target amplitude in each chirp is used to fit the sinc function to estimate the step size between the amplitudes, and the ambiguity of the target is determined by determining the size of the step size.

[0157] Among them, the typical workflow of the vehicle-mounted millimeter wave radar using the speed deambiguation method proposed in the embodiment of the present application is as follows: Fig.13 As shown, the following steps are included:

[0158] S211, the vehicle-mounted millimeter-wave radar is powered on and initialized, and the working parameters are read and sent down.

[0159] S212, the vehicle-mounted millimeter-wave radar receives an instruction to start working.

[0160] S213, the millimeter wave radar chip generates a linear frequency modulated continuous wave according to the waveform parameters, and transmits the signal to the transmitting component and the receiving component.

[0161] S214, the millimeter wave radar chip transmits a linear frequency modulated continuous wave through a transmitting antenna array.

[0162] S215, the millimeter wave radar chip receives the echo reflected by the target through the receiving antenna array.

[0163] S216, the millimeter wave radar chip is connected to the received wave for ADC sampling.

[0164] S217, the millimeter wave radar chip performs ranging processing on the ADC data.

[0165] S218, the millimeter wave radar chip performs speed measurement processing on the ranging data.

[0166] S219, the millimeter wave radar chip performs cluster tracking processing on the angle measurement results.

[0167] S220, the millimeter wave radar chip outputs point cloud information or trajectory information.

[0168] S221, the millimeter wave radar chip cyclically implements target detection until the stop working condition is met.

[0169] Among them, the speed deambiguation method proposed in the embodiment of the present application can be executed by the millimeter wave radar chip, and can be specifically completed in step S218.

[0170] On the other hand, please refer to Figure 2 and Fig.14 , a millimeter wave radar is also provided, comprising a millimeter wave radar processor 201 and a memory 202. The memory 202 stores a computer program that can be executed by the millimeter wave radar processor 201; when the computer program is executed by the millimeter wave radar processor 201, the speed deambiguation method of the millimeter wave radar described in any embodiment of the present application is implemented, and the same technical effect can be achieved. To avoid repetition, it will not be repeated here.

[0171] On the other hand, an embodiment of the present application further provides a computer program product, including a computer program. When the computer program is executed by a processor, the speed deambiguation method of the millimeter wave radar of any embodiment of the present application is implemented, and the same technical effect can be achieved. To avoid repetition, it will not be repeated here.

[0172] On the other hand, an embodiment of the present application further provides a computer-readable storage medium, on which a computer program is stored. When the computer program is executed by a processor, the various processes of the above-mentioned millimeter-wave radar speed deambiguation method embodiment are implemented, and the same technical effect can be achieved. To avoid repetition, it will not be repeated here.

[0173] The computer-readable storage medium is, for example, a read-only memory (ROM), a random access memory (RAM), a magnetic disk or an optical disk.

[0174] It should be noted that, in this article, the terms "include", "comprises" or any other variations thereof are intended to cover non-exclusive inclusion, so that a process, method, article or device including a series of elements includes not only those elements, but also other elements not explicitly listed, or also includes elements inherent to such process, method, article or device. In the absence of further restrictions, an element defined by the sentence "comprises a ..." does not exclude the existence of other identical elements in the process, method, article or device including the element.

[0175] Through the description of the above implementation methods, those skilled in the art can clearly understand that the above-mentioned embodiment methods can be implemented by means of software plus a necessary general hardware platform, and of course by hardware, but in many cases the former is a better implementation method. Based on such an understanding, the technical solution of the present invention, or the part that contributes to the prior art, can be embodied in the form of a software product, which is stored in a storage medium (such as ROM / RAM, a magnetic disk, or an optical disk), and includes a number of instructions for a terminal (which can be a mobile phone, a computer, a server, or a network device, etc.) to execute the methods described in each embodiment of the present invention.

[0176] The above are only specific implementations of the present application, but the protection scope of the present application is not limited thereto. Any technician familiar with the 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.

Claims

1. A velocity deambiguation method for millimeter wave radar, characterized in that: The method comprises: Based on the preset relationship between the range migration amount and the range resolution of the target within the segment time as the grouping rule, the chirp frequency modulation signal is divided into N chirp groups; Performing M-order FFT processing on the N chirp groups to obtain a target spectrum data matrix; wherein M≥N; determining potential targets based on the target spectrum data matrix; Determine the corresponding data segments of the potential target in each of the chirp groups, perform speed defuzzification calculation based on the data segments, and determine the true speed of the potential target.

2. The velocity deambiguation method of millimeter wave radar according to claim 1, characterized in that: The determining of the corresponding data segments of the potential target in each of the chirp groups, performing speed defuzzification calculation based on the data segments, and determining the real speed of the potential target includes: According to the distance R of the potential target, determining the matching data segments of the potential target in each of the chirp groups, and performing M-order FFT processing on the matching data segments respectively; Determine, according to the speed V of the potential target, a matching data point of the potential target in each matching data segment; Resolving velocity ambiguity of the potential target based on the matching data points; According to the velocity ambiguity and the velocity V, the actual velocity of the potential target is determined.

3. The velocity deambiguation method of millimeter wave radar according to claim 2, characterized in that: Each of the chirp groups is a first two-dimensional data matrix, wherein the abscissa of the first two-dimensional data matrix is ​​the ADC sample and the ordinate is the chirp index; The method of performing M-order FFT processing on the N chirp groups to obtain a target spectrum data matrix includes: Performing distance FFT processing on the ADC samples in the first two-dimensional data matrix to obtain a second two-dimensional data matrix; the abscissa of the second two-dimensional data matrix is ​​the distance, and the ordinate is the chirp index; Perform M-order velocity FFT processing on the second two-dimensional data matrix to obtain a third two-dimensional data matrix; the abscissa of the third two-dimensional data matrix is ​​distance, and the ordinate is velocity.

4. The velocity deambiguation method of millimeter wave radar according to claim 2, characterized in that: Resolving the velocity ambiguity of the potential target based on the matching data points includes: determining, based on the amplitudes of the matching data points, an amplitude ratio of a reference matching data point relative to each of the matching data points; The amplitude ratio is fitted with a Sinc function to resolve the velocity ambiguity of the potential target.

5. The velocity deambiguation method of millimeter wave radar according to claim 4, characterized in that: Also includes: Based on different velocity ambiguities and their corresponding amplitude ratios, an ambiguity mapping table is formed; The resolving the velocity ambiguity of the potential target based on the matching data points further includes: According to the amplitude ratio of the matching data points of the current potential target, a search is performed in the ambiguity mapping table to determine the matching target speed ambiguity.

6. The velocity deambiguation method of millimeter wave radar according to claim 2, characterized in that: Determining the true speed of the potential target according to the speed ambiguity and the speed V includes: Based on the following speed calculation formula, determine the actual speed of the potential target; v=V+k*v max ; Among them, v refers to the true speed, k refers to the speed ambiguity, T c refers to the period of the chirp frequency modulation signal, and λ refers to the wavelength of the chirp frequency modulation signal.

7. The velocity deambiguation method of millimeter wave radar according to claim 1, characterized in that: The grouping rule is that the distance migration of the target within the segment time t is less than the distance resolution, and the length of the chirp grouping is determined according to the segment time t.

8. The velocity deambiguation method of millimeter wave radar according to claim 1, characterized in that: The grouping rule is that the distance migration of the target within the segment time t is greater than the product of the distance resolution and the first ratio, and less than the product of the distance resolution and the second ratio; Wherein, the first ratio is 1 / 3, and the second ratio is 1 / 2; The distance migration amount is the product of the maximum possible speed of the target and the segment time t.

9. A millimeter wave radar, characterized in that: The invention comprises a millimeter wave radar processor and a memory, wherein the memory stores a computer program executable by the millimeter wave radar processor; When the computer program is executed by the millimeter-wave radar processor, the speed deambiguation method of the millimeter-wave radar according to any one of claims 1 to 8 is implemented.

10. A computer program product, comprising a computer program, characterized in that When the computer program is executed by a processor, the speed deambiguation method of the millimeter-wave radar according to any one of claims 1 to 8 is implemented.

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