Vehicle-mounted radar angle measurement method, terminal device and storage medium
By combining fast angle measurement algorithms and high-precision angle measurement algorithms, and utilizing multi-baseline angle measurement and DBF algorithms, the challenges of accuracy and speed in vehicle-mounted radar angle measurement methods have been solved, achieving high-precision and high-speed angle measurement results.
Patent Information
- Authority / Receiving Office
- CN · China
- Patent Type
- Patents(China)
- Current Assignee / Owner
- SEE(XIAMEN)TECH CO LTD
- Filing Date
- 2023-11-06
- Publication Date
- 2026-06-09
Smart Images
Figure CN117368922B_ABST
Abstract
Description
Technical Field
[0001] This invention relates to the field of radar angle measurement, and more particularly to a vehicle-mounted radar angle measurement method, terminal equipment, and storage medium. Background Technology
[0002] With the increasing penetration rate of advanced driver assistance systems (ADAS), radar systems, as a crucial component of ADAS perception, are also seeing a rise in installation rates. Vehicle-mounted radar primarily performs target detection and tracking. Target detection by vehicle-mounted radar mainly involves ranging, speed measurement, and angle measurement. Angle measurement is primarily based on a Multiple Input Multiple Output (MIMO) virtual antenna array and utilizes specific angle measurement algorithms. In advanced driver assistance systems, vehicle-mounted radar angle measurement needs to meet both high accuracy and real-time performance requirements. While maximum likelihood algorithms or subspace angle measurement algorithms offer good performance and high accuracy, their computational complexity poses a significant challenge to real-time systems like vehicle-mounted radar. Conversely, fast angle measurement methods often fail to meet accuracy requirements. Therefore, there is an urgent need for a radar angle measurement method that simultaneously achieves high accuracy and speed. Summary of the Invention
[0003] To address the aforementioned problems, this invention proposes a vehicle-mounted radar angle measurement method, a terminal device, and a storage medium.
[0004] The specific plan is as follows:
[0005] A method for angle measurement using vehicle-mounted radar includes the following steps:
[0006] S1: Calculate the distance and velocity of all target points detected by the radar CFAR;
[0007] S2: Measure the angles of all target points using a fast angle measurement algorithm, and extract the angle measurement errors of each target point obtained during the angle measurement process;
[0008] S3: For target points in the fast angle measurement algorithm where the angle measurement error is less than the angle measurement error threshold, determine whether the target point poses a threat by combining its distance, speed, and angle;
[0009] S4: For target points that pose a threat and target points where the angle measurement error in the fast angle measurement algorithm is greater than or equal to the angle measurement error threshold, the angle of the target point is remeasured using a high-precision angle measurement algorithm, based on the measurement results of the fast angle measurement algorithm.
[0010] S5: Combine the angle measurement error of the target point obtained by the fast angle measurement algorithm with the angle measurement performance of the high-precision angle measurement algorithm to obtain the final angle measurement result.
[0011] Furthermore, the fast angle measurement algorithm employs a multi-baseline angle measurement algorithm, where the angle measurement error is evaluated using the phase ambiguity number error value.
[0012] Furthermore, the high-precision angle measurement algorithm employs the DBF algorithm.
[0013] Furthermore, the radar employs millimeter-wave radar for vehicle-mounted rearward applications.
[0014] Furthermore, the process of determining whether a target point poses a threat in step S3 includes the following steps:
[0015] S301: Determine whether the target point is a moving target based on the vehicle speed, target point detection speed, and angle obtained by the fast angle measurement algorithm. If it is, proceed to step S302; otherwise, determine that the target point does not pose a threat.
[0016] S302: Determine whether the target point's movement direction is toward; if so, proceed to step S303; otherwise, determine that the target point poses no threat.
[0017] S303: Calculate the lateral distance between the target point and the vehicle. If the lateral distance is less than a preset distance threshold, proceed to step S304; otherwise, determine that the target point does not pose a threat.
[0018] S304: Determine whether the target point is a false target. If it is, determine that the target point does not pose a threat; otherwise, determine that the target point poses a threat.
[0019] Furthermore, in step S4, when the high-precision angle measurement algorithm uses the DBF algorithm, combined with the measurement results of the fast angle measurement algorithm, the method for measuring the angle of the target point using the high-precision angle measurement algorithm is as follows: initially, the number of DBF full pseudospectral calculations is set to 0; when measuring the angle for each target point, firstly, based on the angle of the target point measured by the multi-baseline angle measurement algorithm, the output power of multiple angles within a certain range on both sides of the angle is calculated, and a partial pseudospectrum is generated based on the calculated output power of these angles; it is determined whether the number of peaks in the partial pseudospectrum is less than 1 and the number of DBF full pseudospectrum calculations is less than the preset threshold. If so, a full pseudospectrum with an angle within ±90 degrees is generated, and the number of DBF full pseudospectrum calculations is incremented by 1, and the angle of the target point is obtained based on the full pseudospectrum; otherwise, the angle of the target point is obtained based on the partial pseudospectrum; when obtaining the angle of the target point based on the full pseudospectrum and when obtaining the angle of the target point based on the partial pseudospectrum, the angle of the target point is initially obtained through peak search, and then the angle of the target point is obtained more accurately through interpolation.
[0020] Furthermore, the step size of both the full pseudospectrum and the partial pseudospectrum is less than or equal to 0.5 degrees.
[0021] Furthermore, the specific determination process in step S5 includes the following steps:
[0022] S501: Determine if the number of peaks in the pseudo-spectrum is greater than 0. If yes, proceed to S502; otherwise, select the angle obtained by the fast angle measurement algorithm as the final angle measurement result.
[0023] S502: Determine whether the maximum energy of the pseudo-spectral peak is greater than the first peak energy threshold. If so, select the angle obtained by the high-precision angle measurement algorithm as the final angle measurement result; otherwise, proceed to S503.
[0024] S503: Determine whether the angle measurement error is less than the first angle measurement error threshold. If so, select the angle obtained by the fast angle measurement algorithm as the final angle measurement result; otherwise, select the angle obtained by the high-precision angle measurement algorithm as the final angle measurement result.
[0025] A vehicle-mounted radar angle measurement terminal device includes a processor, a memory, and a computer program stored in the memory and executable on the processor. When the processor executes the computer program, it implements the steps of the method described above in the embodiments of the present invention.
[0026] A computer-readable storage medium storing a computer program that, when executed by a processor, implements the steps of the method described above in the embodiments of the present invention.
[0027] The present invention adopts the above technical solution, which can ensure high angle measurement accuracy of threatening targets and make the entire angle measurement process fast. Attached Figure Description
[0028] Figure 1 The diagram shown is a flowchart of Embodiment 1 of the present invention.
[0029] Figure 2 The diagram shown is a schematic diagram of the phase comparison method for angle measurement in this embodiment.
[0030] Figure 3 The diagram shown is a schematic diagram of multi-baseline angle measurement in this embodiment.
[0031] Figure 4 The diagram shown is a schematic of the beamforming algorithm structure in this embodiment. Detailed Implementation
[0032] To further illustrate the various embodiments, the present invention provides accompanying drawings. These drawings are part of the disclosure of the present invention, primarily used to illustrate the embodiments, and can be used in conjunction with the relevant descriptions in the specification to explain the operating principles of the embodiments. With reference to these drawings, those skilled in the art should be able to understand other possible implementations and the advantages of the present invention.
[0033] The present invention will now be further described in conjunction with the accompanying drawings and specific embodiments.
[0034] Example 1:
[0035] This invention provides a method for angle measurement using vehicle-mounted radar, such as... Figure 1 As shown, the method includes the following steps:
[0036] S1: Calculate the distance and velocity of all target points detected by the radar CFAR.
[0037] In this embodiment, a vehicle-mounted rear-facing 77GHz millimeter-wave radar is used, primarily for detecting targets behind the vehicle. The target points detected by the radar are obtained under constant false alarm rate (CFAR). In radar signal detection, when the intensity of external interference changes, the radar can automatically adjust its sensitivity to keep the false alarm probability constant; this characteristic is called the constant false alarm rate characteristic. CFAR detection is an important component of automatic radar target detection and is the foundation for further target identification.
[0038] In calculating the range and velocity of a target point, a two-dimensional range-Doppler FFT operation can be performed on the radar echo data first, and the range-Doppler energy map can be obtained by incoherently accumulating the two-dimensional FFT operation results of all antennas, thereby improving the signal-to-noise ratio and thus enhancing the radar's ability to detect targets. Then, the number of targets and their range gate and Doppler gate can be determined by the radar's constant false alarm rate. Finally, the range and velocity of the target can be calculated.
[0039] S2: Measure the angles of all target points using a fast angle measurement algorithm, and extract the angle measurement errors of each target point obtained during the angle measurement process.
[0040] The fast angle measurement algorithm is used for coarse estimation of the target point angle. In this embodiment, the fast angle measurement algorithm adopts the multi-baseline angle measurement algorithm, and the angle measurement error is evaluated by the phase ambiguity number error value.
[0041] The multi-baseline angle measurement algorithm is an improvement on the dual-channel phase method angle measurement. Its essence is to directly measure the angle by utilizing the phase difference between the echoes received by multiple antennas, and it has the characteristics of fast calculation speed.
[0042] In phase-based angle measurement, the baseline length of the two antennas is d, the target azimuth angle is θ, and the transmitted signal is S(t) = exp(j2πf0t). Figure 2 As shown, the echo signals from the two antennas are:
[0043]
[0044] Depend on Figure 2 It can be seen that the path difference ΔR = dsin(θ) corresponds to the phase difference. for:
[0045]
[0046] As shown in the above formula, the larger the baseline length d of the two antennas, the smaller the angle measurement error. However, when d increases to a certain extent, the phase difference... It may exceed 2π, at which point there will be an angle measurement ambiguity problem, that is, one phase difference may correspond to multiple possible angles.
[0047] The multi-baseline angle measurement algorithm can improve angle measurement accuracy without causing angle measurement ambiguity. Its angle measurement principle is as follows: Figure 3 As shown. The short baseline consists of antennas 1 and 2, with an antenna spacing d. 12 It is half a wavelength, and the phase difference is Δφ 12 The long baseline consists of two antennas, 1 and 3, with the antenna spacing generally greater than or equal to one wavelength and a phase difference of Δφ. 13 .
[0048]
[0049]
[0050] Where N is the phase ambiguity number, and ψ∈(-π,π) is the phase difference after long baseline ambiguity.
[0051] Neglecting noise, the phase difference Δφ between antennas is proportional to the antenna spacing, i.e.:
[0052]
[0053]
[0054] The Δφ calculated using the above formula can be used to determine Δφ. 13 The true phase value. Search for the phase ambiguity number N within the possible range of the system, such that Δφ 13 When the deviation between the estimated value and Δφ is less than the set threshold, the phase unwinding is considered complete, i.e., |2πN+ψ-Δφ|<ε.
[0055] The target azimuth angle is calculated based on the phase difference between channels 1 and 3 after phase dewinding. The calculation formula is as follows:
[0056]
[0057] The algorithm principle of multi-baseline angle measurement has been introduced above. The algorithm flow is described below. Let a and b represent the two antenna channels constituting the short baseline, and c and d represent the two antenna channels constituting the long baseline. The multi-baseline angle measurement algorithm flow includes the following steps:
[0058] S101: Calculate the phase difference Δφ of the short baseline.12 Calculate the phase difference ψ of the long baseline. The specific calculation formula is:
[0059]
[0060]
[0061] Where e = b*conj(a), f = d*conj(c), imag(.) represents taking the imaginary part of the complex number, real(.) represents taking the real part of the complex number, and conj(.) represents calculating the conjugate of the complex number.
[0062] S102: Calculate the phase difference Δφ between antennas using formula (6).
[0063] S103: Calculate the difference between the phase difference between antennas and the phase difference of the long baseline. (N1 is a floating-point number here).
[0064] S104: Let N = Round(N1), calculate the phase ambiguity error value ΔN = |N1 - N|.
[0065] The Round(.) function returns a value rounded to the specified number of decimal places. The phase ambiguity error value ΔN represents the degree to which N1 is close to the nearest integer, and also represents the magnitude of the multi-baseline angle measurement error. A smaller ΔN indicates higher angle measurement accuracy, and vice versa.
[0066] S105: Determine whether the phase ambiguity error value ΔN is less than the preset error threshold σ (σ is a small threshold value, which can be set by those skilled in the art according to actual usage requirements). If so, it means that N′ is close enough to an integer, and the phase consistency condition is satisfied, the phase unwinding is completed, and Δφ 13 =2τN+ψ; calculate the azimuth angle of the target using formula (7); otherwise, it is determined that the phase consistency condition is not met and the multi-baseline angle measurement fails.
[0067] S3: For target points with an angle measurement error less than the angle measurement error threshold, determine whether the target point poses a threat by combining its distance, speed, and angle (obtained by a fast angle measurement algorithm).
[0068] This embodiment involves the following four steps in determining whether a target point poses a threat:
[0069] S301: Determine whether the target point is a moving target based on the vehicle speed, target point detection speed, and angle obtained by the fast angle measurement algorithm. If it is, proceed to step S302; otherwise, determine that the target point does not pose a threat.
[0070] S302: Determine whether the target point's movement direction is towards (this vehicle). If so, proceed to step S303; otherwise, determine that the target point poses no threat.
[0071] S303: Calculate the lateral distance between the target point and the vehicle. If the lateral distance is less than a preset distance threshold, proceed to step S304; otherwise, determine that the target point does not pose a threat.
[0072] S304: Determine whether the target point is a false target. If it is, determine that the target point does not pose a threat; otherwise, determine that the target point poses a threat.
[0073] S4: For target points that pose a threat and target points where the angle measurement error in the fast angle measurement algorithm is greater than or equal to the angle measurement error threshold, the angle of the target point is remeasured using a high-precision angle measurement algorithm, based on the measurement results of the fast angle measurement algorithm.
[0074] In this embodiment, the high-precision angle measurement algorithm adopts the DBF (Digital Beam Forming) algorithm. DBF technology is a technology that has developed along with phased array antenna technology. Its essence is to perform spatial filtering by weighting each array element. Although the radiation pattern of the array antenna is omnidirectional, the output of the array can be adjusted to concentrate the directional gain of the array in one direction after weighted summation. The guiding position that obtains the maximum output power for the desired signal is the direction of arrival estimation.
[0075] In array signal processing methods, an appropriate weighting vector is selected for the array output to compensate for the propagation delay of each array element, so that the array outputs can be superimposed in the same direction in a certain desired direction, thereby enabling the array to generate a main lobe beam in that direction, while generating a smaller response in other directions. By using this method to perform beam scanning of the entire space, the orientation of the signal to be measured in the air can be determined.
[0076] Taking a one-dimensional M-element equidistant linear array as an example, such as Figure 4 As shown, the spatial signal is a narrowband signal, and each channel uses a complex weighting coefficient to adjust the amplitude and phase of that channel.
[0077] The output of the array at this time can be expressed as
[0078] If we use vectors to represent the output of each array element and the weighting coefficients, then we have:
[0079] x(t)=[x1(t) x2(t)…x M (t)] T
[0080] w(θ)=[w1(θ) w2(θ)…w M (θ)] T
[0081] Where x(t) represents the array element output matrix and w(θ) represents the weighting coefficient matrix.
[0082] Therefore, the output of the array can also be represented by a vector as y(t) = w H (θ)x(t), where the superscript H denotes the conjugate transpose.
[0083] To compensate for the time delay between array elements in a certain direction θ to form a main lobe, the weighting coefficient vector of a conventional beamformer in the desired direction can be configured as w(θ) = [1 e -iωt …e -i(M-1)ωt ] T .
[0084] Observing this weighting vector, we find that if there is only one signal in space originating from direction θ, the representation of its direction vector α(θ) is the same as that of this weighting coefficient vector. Therefore, y(t) = w H (θ)x(t)=a H (θ)x(t).
[0085] The output power of a conventional beamformer can then be expressed as:
[0086] P DBF (θ)=E[y(t) 2 ] = w H (θ)Rw(θ)=a H (θ)Ra(θ)
[0087] Within a range of ±90 degrees, the step size is less than or equal to 0.5 degrees, so that the θ value (angle) with the maximum output power P is the angle value of the target, thus ensuring high angle measurement accuracy.
[0088] Since calculating angles using the high-precision DBF algorithm is time-consuming, this embodiment introduces the angle measurement results obtained from the previous multi-baseline angle measurement algorithm to shorten the calculation time. Specifically, the calculated angle values are used to narrow the pseudospectral calculation range and peak search range, thereby significantly reducing the computation time. If this method cannot calculate the angle value, the normal DBF algorithm is used to recalculate the angle to prevent missing valid targets.
[0089] To prevent the use of the normal DBF algorithm to calculate angles for too many target points, this embodiment limits the number of times the DBF algorithm is used to calculate the full pseudospectrum to detect the angles of the target points, thus avoiding excessive computation and time consumption. If the number of target points calculated exceeds this limit, the remaining targets will directly use the angle values obtained by the multi-baseline angle measurement algorithm.
[0090] To prevent too many target points from using the DBF algorithm to calculate angles, DBF angle measurement is only performed on threatening target points and target points where the phase ambiguity error value in the fast angle measurement algorithm is greater than the error threshold.
[0091] The angle calculation process using the DBF algorithm in this embodiment includes the following steps:
[0092] S401: Initialize and set the weighted vector matrix w(θ) = [1 e -iωt …e -i(M-1)ωt ] T The number of DBF full pseudospectral calculations was 0.
[0093] In the weighted vector matrix w(θ), θ traverses the range of [-90° to +90°].
[0094] The number of DBF full pseudospectral calculations is used to characterize the number of full pseudospectral calculations performed. The number of DBF full pseudospectral calculations only increases when a full pseudospectral calculation is performed.
[0095] S402: Obtain the calibration of the output x(t) of each array element.
[0096] S403: Calculate the array output matrix y(t) based on the weighted vector matrix w(θ) and the array element output matrix x(t).
[0097] S404: Based on the angle measured by the multi-baseline angle measurement algorithm, calculate the output power of multiple angles on both sides of the angle (e.g., 8 angles on each side), and generate a partial pseudo-spectrum based on the calculated output power of these angles (16 angles).
[0098] S405: Calculate the peak values in the pseudo-spectrum (including peak energy (output power) and the corresponding angle).
[0099] S406: Determine whether the number of peaks in a partial pseudo-spectrum is less than 1 and the number of DBF full pseudo-spectrum calculations is less than a preset threshold (set to 3 in this embodiment). If yes, proceed to S407; otherwise, proceed to S408.
[0100] S407: Generate a full pseudospectrum with an angle within ±90° and calculate the peak value in the full pseudospectrum, incrementing the DBF full pseudospectrum calculation count by 1.
[0101] S408: Determine if the number of peaks is greater than 0. If it is, find the largest peak and perform interpolation to obtain the angle of the target point, and return the number of peaks; otherwise, return the number of peaks directly.
[0102] S5: Combine the angle measurement error of the target point obtained by the fast angle measurement algorithm with the angle measurement performance of the high-precision angle measurement algorithm to obtain the final angle measurement result.
[0103] Since, theoretically, the smaller the angle measurement error (phase ambiguity number error), the smaller the error of the fast angle measurement algorithm; and the larger the pseudospectral peak energy, the more reliable the high-precision angle measurement algorithm, this embodiment establishes the following determination process:
[0104] S501: Determine if the number of peaks in the pseudo-spectrum is greater than 0. If yes, proceed to S502; otherwise, select the angle obtained by the fast angle measurement algorithm as the final angle measurement result.
[0105] S502: Determine whether the maximum energy (i.e., output power P) of the pseudo-spectral peak is greater than the first peak energy threshold. If so, select the angle obtained by the high-precision angle measurement algorithm as the final angle measurement result; otherwise, proceed to S503.
[0106] S503: Determine whether the angle measurement error (phase ambiguity number error value) is less than the first angle measurement error threshold. If so, select the angle obtained by the fast angle measurement algorithm as the final angle measurement result; otherwise, select the angle obtained by the high-precision angle measurement algorithm as the final angle measurement result.
[0107] It should be noted that the first peak energy threshold corresponds to the value at which the angle measurement result of the high-precision angle measurement algorithm is at the boundary between good and bad, and the first angle measurement error threshold corresponds to the value at which the angle measurement result of the fast angle measurement algorithm is at the boundary between good and bad. The technical solution in this field can determine the values of these two parameters based on multiple experimental data.
[0108] This invention employs a combination of a fast angle measurement method and a high-precision angle measurement method for angle measurement. The fast angle measurement method is not limited to the multi-baseline method, but can also use the dual-channel phase comparison method, etc. The high-precision angle measurement method is not limited to the DBF algorithm, but can also use Capon, etc. The two methods can work together to measure the target angle.
[0109] Since the multi-baseline method can measure angles quickly while ensuring a certain level of accuracy, it has higher accuracy than conventional fast angle measurement algorithms such as the dual-channel phase comparison method, and is therefore a preferred choice in this embodiment.
[0110] Since the DBF algorithm can calculate the pseudo-spectrum and search for peaks within the selected angle range, and can also improve the accuracy of angle measurement by reducing the step size to increase the number of selected angles within the selected angle range, it is a preferred choice in this embodiment.
[0111] In this embodiment of the invention, evaluation parameters of the angle measurement results need to be provided for the fast angle measurement method, which serves as a prerequisite for whether to continue using the high-precision angle measurement method. In addition, evaluation parameters of the high-precision angle measurement method also need to be provided, which serve as the basis for judging the final angle measurement results after the two methods have been used for detection.
[0112] The embodiments of the present invention use a combination of fast angle measurement algorithm and high-precision angle measurement algorithm to measure the angle of the target point. This avoids the problem that the accuracy is not high enough when using only fast angle measurement algorithm, and solves the problem that the time consumed when using only high-precision angle measurement algorithm. It can simultaneously achieve high accuracy and high speed.
[0113] Example 2:
[0114] The present invention also provides a vehicle-mounted radar angle measurement terminal device, including a memory, a processor, and a computer program stored in the memory and executable on the processor. When the processor executes the computer program, it implements the steps in the method embodiment described above in Embodiment 1 of the present invention.
[0115] Furthermore, as an executable solution, the vehicle-mounted radar angle measurement terminal device can be a computing device such as an on-board computer or a cloud server. The vehicle-mounted radar angle measurement terminal device may include, but is not limited to, a processor and a memory. Those skilled in the art will understand that the above-described composition of the vehicle-mounted radar angle measurement terminal device is merely an example and does not constitute a limitation on the vehicle-mounted radar angle measurement terminal device. It may include more or fewer components than described above, or combine certain components, or different components. For example, the vehicle-mounted radar angle measurement terminal device may also include input / output devices, network access devices, buses, etc., and this embodiment of the invention does not limit this.
[0116] Furthermore, as an executable solution, the processor can be a Central Processing Unit (CPU), or other general-purpose processors, digital signal processors (DSPs), application-specific integrated circuits (ASICs), field-programmable gate arrays (FPGAs), or other programmable logic devices. The general-purpose processor can be a microprocessor or any conventional processor. This processor is the control center of the vehicle-mounted radar angle measurement terminal equipment, connecting all parts of the equipment via various interfaces and lines.
[0117] The memory can be used to store the computer programs and / or modules. The processor implements various functions of the vehicle-mounted radar angle measurement terminal device by running or executing the computer programs and / or modules stored in the memory and calling the data stored in the memory. The memory may mainly include a program storage area and a data storage area. The program storage area may store the operating system and at least one application program required for a function; the data storage area may store data created based on the use of the mobile phone, etc. In addition, the memory may include high-speed random access memory and may also include non-volatile memory, such as hard disk, RAM, plug-in hard disk, smart media card (SMC), secure digital (SD) card, flash card, at least one disk storage device, flash memory device, or other volatile solid-state storage device.
[0118] The present invention also provides a computer-readable storage medium storing a computer program, which, when executed by a processor, implements the steps of the method described in the embodiments of the present invention.
[0119] If the modules / units integrated in the vehicle-mounted radar angle measurement terminal equipment are implemented as software functional units and sold or used as independent products, they can be stored in a computer-readable storage medium. Based on this understanding, all or part of the processes in the methods of the above embodiments of the present invention can also be implemented by a computer program instructing related hardware. The computer program can be stored in a computer-readable storage medium, and when executed by a processor, it can implement the steps of the various method embodiments described above. The computer program includes computer program code, which can be in the form of source code, object code, executable files, or certain intermediate forms. The computer-readable medium can include: any entity or device capable of carrying the computer program code, a recording medium, a USB flash drive, a portable hard drive, a magnetic disk, an optical disk, a computer memory, a read-only memory (ROM), a random access memory (RAM), and a software distribution medium, etc.
[0120] Although the invention has been specifically shown and described in conjunction with preferred embodiments, those skilled in the art should understand that various changes in form and detail may be made to the invention without departing from the spirit and scope of the invention as defined in the appended claims, all of which shall be within the scope of protection of the invention.
Claims
1. A method for angle measurement using vehicle-mounted radar, characterized in that, Includes the following steps: S1: Calculate the distance and velocity of all target points detected by the radar CFAR; S2: Measure the angles of all target points using a fast angle measurement algorithm, and extract the angle measurement errors of each target point obtained during the angle measurement process; S3: For target points in the fast angle measurement algorithm where the angle measurement error is less than the angle measurement error threshold, determine whether the target point poses a threat by combining its distance, speed, and angle; S4: For target points that pose a threat and for target points where the angle measurement error in the fast angle measurement algorithm is greater than or equal to the angle measurement error threshold, the angle of the target point is remeasured using a high-precision angle measurement algorithm, based on the measurement results of the fast angle measurement algorithm. When the high-precision angle measurement algorithm uses the DBF algorithm, the method for measuring the angle of the target point using the high-precision angle measurement algorithm, based on the measurement results of the fast angle measurement algorithm, is as follows: Initially, the number of DBF full pseudo-spectrum calculations is set to 0. When measuring the angle of each target point, firstly, based on the angle of the target point measured by the multi-baseline angle measurement algorithm, the output power of multiple angles on both sides of the angle is calculated, and a partial pseudo-spectrum is generated based on the calculated output power of these angles. It is determined whether the number of peaks in the partial pseudo-spectrum is less than 1 and the number of DBF full pseudo-spectrum calculations is less than the preset threshold. If so, a full pseudo-spectrum with an angle within the range of ±90 degrees is generated, and the number of DBF full pseudo-spectrum calculations is incremented by 1. The angle of the target point is obtained based on the full pseudo-spectrum. Otherwise, the angle of the target point is obtained based on a portion of the pseudospectral data; Both when obtaining the angle of the target point based on the full pseudospectrum and when obtaining the angle of the target point based on a partial pseudospectrum, the angle of the target point is initially obtained through peak search, and then the angle of the target point is obtained more accurately through interpolation. S5: The final angle measurement result is obtained by combining the angle measurement error of the target point obtained by the fast angle measurement algorithm with the angle measurement performance of the high-precision angle measurement algorithm. The specific determination process includes the following steps: S501: Determine if the number of peaks in the pseudo-spectrum is greater than 0. If yes, proceed to S502; otherwise, select the angle obtained by the fast angle measurement algorithm as the final angle measurement result. S502: Determine whether the maximum energy of the pseudo-spectral peak is greater than the first peak energy threshold. If so, select the angle obtained by the high-precision angle measurement algorithm as the final angle measurement result; otherwise, proceed to S503. S503: Determine whether the angle measurement error is less than the first angle measurement error threshold. If so, select the angle obtained by the fast angle measurement algorithm as the final angle measurement result; otherwise, select the angle obtained by the high-precision angle measurement algorithm as the final angle measurement result.
2. The vehicle-mounted radar angle measurement method according to claim 1, characterized in that: The fast angle measurement algorithm uses a multi-baseline angle measurement algorithm, where the angle measurement error is evaluated using the phase ambiguity number error value.
3. The vehicle-mounted radar angle measurement method according to claim 1, characterized in that: The high-precision angle measurement algorithm uses the DBF algorithm.
4. The vehicle-mounted radar angle measurement method according to claim 1, characterized in that: The radar uses millimeter-wave radar for vehicle-mounted rearward applications.
5. The vehicle-mounted radar angle measurement method according to claim 1, characterized in that: Step S3, which determines whether a target point poses a threat, includes the following steps: S301: Determine whether the target point is a moving target based on the vehicle speed, target point detection speed, and angle obtained by the fast angle measurement algorithm. If it is, proceed to step S302; otherwise, determine that the target point does not pose a threat. S302: Determine whether the target point's movement direction is toward; if so, proceed to step S303; otherwise, determine that the target point poses no threat. S303: Calculate the lateral distance between the target point and the vehicle. If the lateral distance is less than a preset distance threshold, proceed to step S304; otherwise, determine that the target point does not pose a threat. S304: Determine whether the target point is a false target. If it is, determine that the target point does not pose a threat; otherwise, determine that the target point poses a threat.
6. The vehicle-mounted radar angle measurement method according to claim 1, characterized in that: The step size for both the full pseudospectrum and the partial pseudospectrum is less than or equal to 0.5 degrees.
7. A vehicle-mounted radar angle measurement terminal device, characterized in that: It includes a processor, a memory, and a computer program stored in the memory and running on the processor, wherein the processor executes the computer program to implement the steps of the method as described in any one of claims 1 to 6.
8. A computer-readable storage medium storing a computer program, characterized in that: When the computer program is executed by a processor, it implements the steps of the method as described in any one of claims 1 to 6.