A mechanical 3D radar control method, system, storage medium and electronic device

Abstract

A control method and system of a mechanical 3D radar, a storage medium and an electronic device, relate to the technical field of radar control. The method comprises: determining a scanning coverage area based on the working state parameters of the mechanical 3D radar, and dividing it into multiple scanning units; collecting radar echo signals in each scanning unit, and performing signal enhancement processing on the radar echo signals according to the spatial position information of each scanning unit to generate enhanced target echo data; performing time series analysis and coherent accumulation processing on the target echo data, and extracting frequency domain features based on the coherent accumulation results; extracting targets from the target echo data according to the frequency domain features to obtain target feature information of each scanning unit; determining control parameters of the mechanical 3D radar according to the target feature information, and controlling the mechanical 3D radar to execute according to the control parameters. The technical solutions provided by the present application can improve the resource utilization efficiency of the mechanical 3D radar.

Description

Technical Field

[0001] The present application relates to the field of radar control technology, and in particular to a control method, system, storage medium and electronic device for a mechanical 3D radar. Background Art

[0002] With the rapid development of intelligent transportation, autonomous driving and other fields, the demand for environmental perception is increasing. Mechanical 3D radar has been widely used in this field due to its advantages such as large-scale detection and high-precision ranging.

[0003] Currently, mechanical 3D radars typically operate with fixed parameters. For example, the radar rotates and scans at a preset rotational speed, and transmits signals at a fixed power. In actual applications, the distribution of targets within the radar's detection area often changes dynamically, with some areas densely populated and others sparsely populated. Using fixed parameter operation prevents system resources from being properly allocated based on actual detection needs. This can lead to insufficient detection in densely populated areas and waste of system resources in sparsely populated areas, resulting in low resource utilization efficiency for mechanical 3D radars. Summary of the Invention

[0004] The present application provides a control method, system, storage medium, and electronic device for a mechanical 3D radar, which can improve the resource utilization efficiency of the mechanical 3D radar.

[0005] In a first aspect, the present application provides a control method for a mechanical 3D radar, the method comprising:

[0006] Acquiring real-time operating status parameters of a mechanical 3D radar, determining a scanning coverage area of ​​the mechanical 3D radar based on the operating status parameters, and dividing the scanning coverage area into a plurality of scanning units;

[0007] collecting radar echo signals in each of the scanning units, and performing signal enhancement processing on the radar echo signals according to spatial position information of each of the scanning units to generate enhanced target echo data, wherein the signal enhancement processing includes distance compensation and angle compensation;

[0008] Performing time series analysis and coherent accumulation processing on the target echo data to obtain a coherent accumulation result, and extracting frequency domain features based on the coherent accumulation result;

[0009] Performing target extraction on the target echo data according to the frequency domain characteristics to obtain target feature information of each scanning unit;

[0010] The control parameters of the mechanical 3D radar are determined according to the target feature information, and the mechanical 3D radar is controlled to execute according to the control parameters.

[0011] By adopting the above technical solution, by obtaining the real-time working status parameters of the mechanical 3D radar and dividing the scanning units, refined management of the scanning area can be achieved; by performing signal enhancement processing on the radar echo signals of each scanning unit with distance compensation and angle compensation, and combining timing analysis and coherent accumulation processing to extract frequency domain features, the accuracy of target feature information extraction can be effectively improved; and then, based on the extracted target feature information, the control parameters of the radar are dynamically adjusted, so that the mechanical 3D radar can adaptively allocate system resources according to actual detection needs, thereby improving the resource utilization efficiency of the mechanical 3D radar.

[0012] In a second aspect of the present application, a control system for a mechanical 3D radar is provided, the system comprising:

[0013] a scanning unit division module, configured to obtain real-time operating status parameters of the mechanical 3D radar, determine a scanning coverage area of ​​the mechanical 3D radar based on the operating status parameters, and divide the scanning coverage area into a plurality of scanning units;

[0014] a signal enhancement processing module, configured to collect radar echo signals from each of the scanning units and perform signal enhancement processing on the radar echo signals according to the spatial position information of each of the scanning units to generate enhanced target echo data, wherein the signal enhancement processing includes distance compensation and angle compensation;

[0015] A frequency domain feature extraction module is used to perform time series analysis and coherent accumulation processing on the target echo data to obtain a coherent accumulation result, and extract frequency domain features based on the coherent accumulation result;

[0016] a feature information extraction module, configured to extract the target echo data according to the frequency domain features to obtain target feature information of each scanning unit;

[0017] A control parameter determination module is used to determine the control parameters of the mechanical 3D radar according to the target feature information, and control the mechanical 3D radar to execute according to the control parameters.

[0018] In a third aspect of the present application, a computer storage medium is provided. The computer storage medium stores a plurality of instructions, and the instructions are suitable for being loaded by a processor and executing the above method steps.

[0019] In a fourth aspect of the present application, an electronic device is provided, comprising: a processor and a memory; wherein the memory stores a computer program, and the computer program is suitable for being loaded by the processor and executing the above-mentioned method steps.

[0020] In summary, one or more technical solutions provided in the embodiments of the present application have at least the following technical effects or advantages:

[0021] This application can achieve refined management of the scanning area by acquiring the real-time working status parameters of the mechanical 3D radar and dividing the scanning units; by performing signal enhancement processing on the radar echo signals of each scanning unit with distance compensation and angle compensation, and extracting frequency domain features in combination with timing analysis and coherent accumulation processing, the accuracy of target feature information extraction can be effectively improved; and then the control parameters of the radar are dynamically adjusted based on the extracted target feature information, so that the mechanical 3D radar can adaptively allocate system resources according to actual detection needs, thereby improving the resource utilization efficiency of the mechanical 3D radar. BRIEF DESCRIPTION OF THE DRAWINGS

[0022] Figure 1 This is a flow chart of a control method for a mechanical 3D radar provided in an embodiment of the present application;

[0023] Figure 2 This is a module diagram of a control system for a mechanical 3D radar provided in an embodiment of the present application;

[0024] Figure 3 This is a structural diagram of an electronic device provided in an embodiment of the present application.

[0025] Description of reference numerals: 300, electronic device; 301, processor; 302, communication bus; 303, user interface; 304, network interface; 305, memory. DETAILED DESCRIPTION

[0026] In order to enable those skilled in the art to better understand the technical solutions in this specification, the technical solutions in the embodiments of this specification will be clearly and completely described below in conjunction with the drawings in the embodiments of this specification. Obviously, the described embodiments are only part of the embodiments of this application, not all of the embodiments.

[0027] In the description of the embodiments of this application, words such as "for example" or "for instance" are used to indicate examples, illustrations, or explanations. Any embodiment or design described as "for example" or "for instance" in the embodiments of this application should not be construed as being preferred or advantageous over other embodiments or designs. Rather, the use of words such as "for example" or "for instance" is intended to present the relevant concepts in a concrete manner.

[0028] In the description of the embodiments of the present application, the term "multiple" means two or more. For example, multiple systems refer to two or more systems, and multiple screen terminals refer to two or more screen terminals. In addition, the terms "first" and "second" are used for descriptive purposes only and are not to be understood as indicating or implying relative importance or implicitly indicating the indicated technical features. Thus, the features defined as "first" and "second" may explicitly or implicitly include one or more of the features. The terms "including", "comprising", "having" and their variations all mean "including but not limited to", unless otherwise specifically emphasized.

[0029] The following will provide a clear and complete description of the technical solutions in the embodiments of the present application in conjunction with the drawings in the embodiments of the present application. Obviously, the described embodiments are only part of the embodiments of the present application, not all of the embodiments.

[0030] Please refer to Figure 1 , a flow chart of a control method for a mechanical 3D radar is proposed. The method can be implemented by a computer program, a single-chip microcomputer, or run on a control system of a mechanical 3D radar. The computer program can be integrated into a computer device or run as an independent tool application. Specifically, the method includes steps 10 to 50, which are as follows:

[0031] Step 10: Obtain the real-time working status parameters of the mechanical 3D radar, determine the scanning coverage area of ​​the mechanical 3D radar based on the working status parameters, and divide the scanning coverage area into multiple scanning units.

[0032] Among them, in the embodiment of the present application, the working status parameters refer to various parameters that describe the current operating status of the mechanical 3D radar, including but not limited to signal transmission power, radar speed and scanning angle. These parameters directly affect the detection performance and working efficiency of the radar.

[0033] The scanning coverage area refers to the three-dimensional spatial range that the mechanical 3D radar can effectively detect under the current working state parameters. This range is determined by the maximum detection distance and the scanning angle range, forming a fan-shaped three-dimensional detection area.

[0034] Specifically, first obtain the real-time working status parameters of the mechanical 3D radar, including signal transmission power, radar rotation speed and scanning angle. Determine the maximum detection distance based on the signal transmission power, determine the angle range based on the scanning angle, and determine the scanning coverage area of ​​the mechanical 3D radar by the maximum detection distance and the angle range. Obtain the beam width of the mechanical 3D radar, and calculate the minimum size of each scanning unit based on the beam width. Calculate the scanning distance per unit time based on the radar rotation speed and the minimum size, and divide the scanning coverage area into multiple scanning segments along the radial direction. The radial length of each scanning segment is proportional to the scanning distance per unit time. Calculate the number of divisions of each scanning segment, which is inversely proportional to the radial length of the scanning segment, and finally obtain multiple scanning units whose sizes are not less than the minimum size. This division method can ensure that the size of the scanning unit matches the detection capability of the radar and improve detection efficiency.

[0035] Based on the above embodiment, as another optional embodiment, the step of determining the scanning coverage area of ​​the mechanical 3D radar based on the working state parameters and dividing the scanning coverage area into multiple scanning units may further include steps 101 to 103:

[0036] Step 101: Extract signal transmission power, radar rotation speed, and scanning angle from the working status parameters.

[0037] Specifically, three key parameters are first extracted from the operating status parameters of the mechanical 3D radar: signal transmission power (in W), radar rotation speed (in rpm), and scanning angle (in degrees). The signal transmission power is obtained by reading the real-time power output value of the radar transmitter, which directly affects the radar's detection range; the radar rotation speed is obtained in real time through the speed sensor of the drive motor, which determines the scanning coverage capability per unit time; the scanning angle is measured by the angle encoder to obtain the real-time azimuth angle of the radar antenna, which determines the radar's scanning range. These three parameters together determine the radar's operating status and provide basic data for subsequently determining the detection range and dividing the scanning units.

[0038] Step 102: Determine the maximum detection distance according to the signal transmission power, and determine the angle range according to the scanning angle.

[0039] Specifically, according to the extracted signal transmission power P, combined with the radar equation , calculate the maximum detection distance R, where G is the antenna gain, λ is the operating wavelength, σ is the target scattering cross-sectional area, P minis the minimum detectable signal power. For example, when the signal transmission power is 100W, this formula calculates the maximum detection range to be 1000 meters. The angular range is determined based on the scanning angle θ. Typically, the coverage range is ±θ / 2 of the scanning angle. For example, for a 90-degree scanning angle, the angular range is ±45 degrees. This calculation method takes into account the physical characteristics of the radar system and ensures the accuracy of the detection range.

[0040] Step 103: Determine the scanning coverage area of ​​the mechanical 3D radar according to the maximum detection distance and the angle range.

[0041] Specifically, the calculated maximum detection distance R and angle range θ are substituted into the polar coordinate equation , generating the boundary equation of the scanning coverage area. In three-dimensional space, the area forms a sector volume with the radar as the vertex, where ρ represents the radial distance and φ represents the azimuth angle. Assuming the maximum detection range R is 1000 meters and the scanning angle θ is 90 degrees, the scanning coverage area forms a sector area in the horizontal plane with the radar as the vertex, a radius of 1000 meters, and an angle of 90 degrees. The coverage area is approximately 785,398 square meters (according to the sector area formula Calculation. In the vertical direction, consider the radar's pitch angle range is 30 degrees degrees, the final scanning coverage area forms a three-dimensional fan-shaped volume. According to the formula Calculate, where θ and α are the horizontal and vertical angles, which need to be converted into radians).

[0042] Step 104: Obtain the beam width of the mechanical 3D radar, and calculate the minimum size of each scanning unit based on the beam width.

[0043] Specifically, the beam characteristics are determined by measuring the -3dB beam width β of the radar antenna, which represents the angular resolution capability of the radar. Based on the beam width β and the detection range R, the minimum size of the scanning unit is calculated. For example, when the beam width is 2 degrees and the detection range is 100 meters, the minimum size is approximately 3.5 meters. This ensures that the size of the divided scanning unit is not less than the spatial resolution capability of the radar, avoiding resource waste caused by excessive subdivision.

[0044] Step 105: Divide the scanning coverage area into multiple scanning units according to the radar rotation speed and the minimum size.

[0045] Specifically, first calculate the angular scanning speed per unit time according to the radar speed v (rpm) Degrees / second. Combined with the minimum size S, calculate the time resolution at different radial distances Based on temporal resolution, the scanning coverage area is divided into multiple concentric annular regions, with the radial width of each annular region proportional to the local minimum size. Within each annular region, the area is then evenly divided based on angular resolution, ensuring that the actual size of all scanning units is no less than the minimum size S. This adaptive division method ensures optimal allocation of system resources while maintaining detection performance.

[0046] Based on the above embodiment, as another optional embodiment, the step of determining the scanning coverage area of ​​the mechanical 3D radar based on the working state parameters and dividing the scanning coverage area into multiple scanning units may further include steps 1051 to 1054:

[0047] Step 1051: Calculate the product of the minimum size and the radar rotation speed to obtain the scanning distance per unit time.

[0048] Specifically, the scanning distance per unit time D is calculated based on the calculated minimum size S and the radar speed v. When the radar speed is 30 rpm, the rotation angle per second is π radians, then the scanning distance per unit time is m / s. For example, when the minimum size S is 3.5 meters, the scanning distance per unit time D is approximately 0.37 m / s. This parameter reflects the radar's scanning capability while ensuring minimum resolution, providing a basis for subsequent area division.

[0049] Step 1052: Divide the scan coverage area into multiple scan segments along the radial direction, and the radial length of each scan segment is proportional to the scan distance per unit time.

[0050] Specifically, based on the unit time scanning distance D, the scanning coverage area is divided into N scanning segments along the radial direction. The radial length L of each scanning segment is i By formula Calculate, where k is the scaling factor (usually 1) and i is the segment number (1 ≤ i ≤ N). For example, when N = 10, the first segment is 0.37 meters long, the second 0.74 meters long, and so on. This progressive division method takes into account the radar scanning characteristics, giving segments farther from the radar a larger radial length.

[0051] Step 1053: Calculate the number of divisions of each scanning segment, where the number of divisions is inversely proportional to the radial length of the scanning segment.

[0052] Specifically, for each scanning segment, calculate its division number M i The number of divisions is inversely proportional to the radial length, as shown by the formula Calculation, where M0 is the number of base divisions (usually 360). For example, the number of divisions in the first segment is 360, and the number of divisions in the second segment is 180, which ensures that the farther segments are not divided too densely. To avoid divisions being too sparse, a minimum division threshold M is set. min (usually 36), when the calculated M i Less than M min When M min As the number of divisions for this segment.

[0053] Step 1054: Divide each scanning segment into multiple scanning units according to the number of divisions, and the size of each scanning unit is not less than the minimum size.

[0054] Specifically, according to the number of divisions M of each scanning segment i , each segment is evenly divided into a corresponding number of scanning units. Specifically, for the i-th segment, its angular interval is , the arc length of each scanning unit . Verified by calculation , ensuring that the actual size of each scanning unit is not less than the minimum size S. For example, when the radial length of the first segment is 0.37 meters and the number of divisions is 360, the arc length of each scanning unit is approximately 0.0064 meters, which meets the minimum size requirement. This division method not only ensures detection accuracy but also avoids waste of system resources.

[0055] Step 20: Collect the radar echo signals in each scanning unit, and perform signal enhancement processing on the radar echo signals according to the spatial position information of each scanning unit to generate enhanced target echo data. The signal enhancement processing includes distance compensation and angle compensation.

[0056] In this embodiment of the present application, the radar echo signal refers to the original signal generated by the electromagnetic wave signal emitted by the mechanical 3D radar and reflected back to the receiving antenna after encountering a target object. This signal contains spatial position information such as the target's range, azimuth, and elevation, as well as information about the target's reflection characteristics. The radar echo signal is represented by a series of discrete digitized sample values, whose amplitude and phase vary over time. These changes reflect the target's physical characteristics and motion state.

[0057] Target echo data refers to radar echo signals that have undergone signal enhancement processing, including signal data after distance compensation and angle compensation. Distance compensation is used to eliminate the attenuation of electromagnetic waves during spatial propagation, while angle compensation is used to correct for differences in antenna gain caused by changes in scanning angle.

[0058] Specifically, the radar receiver first collects the radar echo signals from each scanning unit, with each scanning unit corresponding to a set of digitized echo data. Since electromagnetic waves experience distance attenuation during spatial propagation, signal strength decreases with increasing propagation distance, necessitating distance compensation for the radar echo signals. Specifically, a compensation coefficient is calculated based on the target distance; the longer the distance, the larger the compensation coefficient. The original signal is multiplied by the compensation coefficient to obtain the distance-compensated signal. Next, considering that the radar antenna gain varies with the scanning angle, the received signal strength varies at different scanning angles, necessitating angle compensation. Angle compensation coefficients are calculated based on the current scanning angle, and the distance-compensated signal is multiplied by the angle compensation coefficient to ultimately obtain enhanced target echo data. This dual compensation process eliminates signal distortion caused by spatial propagation and angle variation, making the echo strength of targets at different locations comparable.

[0059] Based on the above embodiment, as another optional embodiment, the step of performing signal enhancement processing on the radar echo signal according to the spatial position information of each scanning unit to generate enhanced target echo data may further include steps 201 to 203:

[0060] Step 201: Calculate the range attenuation coefficient based on the radial distance, and perform distance compensation on the radar echo signal according to the range attenuation coefficient.

[0061] Specifically, in this embodiment, the radial distance value R of each scanning unit is first obtained. This value represents the straight-line distance from the target to the radar. Since radar signals attenuate with distance during spatial propagation, and signal strength is inversely proportional to the fourth power of distance, distance compensation is required. The calculation formula for the distance attenuation coefficient is: ,in, is the reference distance (usually 100 meters), and R is the actual distance to the target. Multiply by the distance attenuation coefficient to get the distance compensated signal: For example, when the target distance is 200 meters, the distance attenuation coefficient is 16 times, and the original signal amplitude needs to be multiplied by 16 for compensation. This compensation ensures that the target echo signal strength at different distances is comparable.

[0062] Step 202: Calculate the angle error according to the azimuth information, and perform angle compensation on the distance-compensated echo signal based on the angle error.

[0063] Specifically, after completing the distance compensation, the angle compensation is performed based on the azimuth information. First, the actual azimuth angle θ of the antenna is calculated and the ideal pointing angle The angular error between: ; According to the antenna pattern characteristics, the angle compensation coefficient is calculated as follows: ; When the angle error When the antenna beam width exceeds half, set the compensation upper limit: ;in, is the maximum compensation coefficient (usually 2), and the distance-compensated signal is angle-compensated: , is the echo signal after distance compensation.

[0064] Step 203: performing denoising processing on the compensated echo signal to generate enhanced target echo data.

[0065] Specifically, the echo signal after distance and angle compensation is first subjected to denoising. This denoising process consists of three stages. The first stage uses a sliding average method for preprocessing. Specifically, for each sampling point, the signal values ​​of five points, two before and two after it, are averaged to obtain the smoothed signal value for that sampling point. This smoothing process effectively reduces the impact of random noise. The second stage sets an adaptive threshold based on the smoothed signal value. Specifically, the smoothed signal value is multiplied by a threshold coefficient of 1.5 to obtain the threshold for the corresponding sampling point. The advantage of using an adaptive threshold is that the threshold value can be automatically adjusted based on local variations in signal strength, thus better adapting to different signal environments. The third stage performs noise suppression, specifically comparing the original signal value with the corresponding adaptive threshold. If the signal value does not exceed the threshold, the signal value is maintained unchanged; if the signal value exceeds the threshold, the signal value is clamped to the threshold level. For example, if the original signal value at a sampling point is 2.0 volts and the corresponding adaptive threshold is 1.5 volts, the output signal value at that point will be clamped to 1.5 volts, thereby suppressing abnormally high-amplitude noise. Finally, the denoised signal is gain-adjusted by multiplying the signal value by a gain factor of 1.2 to obtain the enhanced target echo data. This gain adjustment can appropriately increase the effective signal strength and further improve signal quality. The target echo data after this processing has a higher signal-to-noise ratio and clearer target features, providing a more reliable data foundation for subsequent target detection and feature extraction.

[0066] Step 30: Perform time series analysis and coherent accumulation processing on the target echo data to obtain a coherent accumulation result, and extract frequency domain features based on the coherent accumulation result.

[0067] In the embodiment of the present application, the coherent accumulation result refers to the processing result of phase alignment and amplitude superposition of target echo data acquired in multiple adjacent scanning cycles.

[0068] Frequency domain features refer to the characteristic parameters of the target echo data in the frequency domain after Fourier transform.

[0069] Specifically, the target echo data is first subjected to a time series analysis, and the echo data of the same scanning unit within eight consecutive scanning cycles are arranged in chronological order to form a time series. Phase compensation is performed on the time series by calculating the phase delay based on the target distance and aligning the phases of the signals of each period. Coherent accumulation processing is then performed, and the eight periodic signals after phase alignment are complex superimposed to obtain the coherent accumulation result. The coherent accumulation result is subjected to a fast Fourier transform to extract frequency domain features, including spectrum amplitude, main lobe width, side lobe level, and spectrum center of gravity. Since the coherent accumulation processing can enhance the target signal by 8 times while the noise is only enhanced by 2.83 times, the signal-to-noise ratio is significantly improved, making the extracted frequency domain features more accurate and reliable.

[0070] Based on the above embodiment, as an optional embodiment, the step of performing time series analysis and coherent accumulation processing on the target echo data to obtain the coherent accumulation result may further include steps 301 to 304:

[0071] Step 301: Sort the target echo data according to the scanning time sequence to obtain a time sequence echo sequence.

[0072] Specifically, each frame of target echo data is time-sequentially arranged based on the radar scan timestamp. First, echo data for 32 consecutive scan cycles is acquired. Each cycle contains information about the range gate, azimuth, and signal amplitude. This data is then chronologically arranged based on the timestamp. For each range gate position, the echo signals corresponding to 32 cycles are extracted to form a time-sequential echo sequence. For example, for a target at range gate R1, the echo signals for 32 cycles within that range gate are extracted [S1, S2, ..., S32], where Si represents the complex signal value of the i-th cycle. This time-sequential arrangement ensures temporal continuity of the signal in subsequent processing and provides a foundation for phase analysis.

[0073] Step 302: performing phase alignment on the time-series echo sequence to obtain an aligned echo sequence.

[0074] Specifically, in this embodiment, the phase alignment process is performed on the time-series echo sequence. First, the phase deviation of each periodic signal relative to the reference period is calculated: ; Then perform phase compensation: ; represents the phase deviation of the i-th cycle relative to the reference cycle; represents the signal phase of the i-th cycle; The signal phase representing the reference period; represents the phase-compensated signal; j represents the imaginary unit. This phase alignment ensures the phase consistency of the target echo signal across different cycles, creating conditions for subsequent coherent processing.

[0075] Step 303: Calculate the phase difference between adjacent frames of the aligned echo sequence to obtain a phase difference sequence.

[0076] Specifically, the phase difference between adjacent frames in the aligned echo sequence is calculated. For the signals in the i-th cycle and the i+1-th cycle, the phase difference is calculated as follows: ;in, is the phase difference between the i-th and i+1-th cycles; is the aligned signal of the i+1th cycle;

[0077] is the aligned signal of the ith period; conj() is the complex conjugate operation, and angle() is the phase extraction operation. The phase difference sequence is obtained .

[0078] Step 304: Perform coherent accumulation processing on the phase difference sequence to obtain a coherent accumulation result.

[0079] Specifically, the phase difference sequence is coherently accumulated. First, the phase difference sequence is grouped into units of 8 cycles to obtain 4 groups of phase difference data. The average phase difference is calculated for each group of data: ; Then calculate the weight coefficient: ; The final coherent accumulation result: ; Where: k is the group number, k = 0, 1, 2, 3; is the average phase difference of the kth group; is the standard deviation of the phase difference within the kth group; is the weight coefficient of the kth group; C is the final coherent accumulation result.

[0080] Step 40: Target extraction is performed on the target echo data according to the frequency domain characteristics to obtain target feature information of each scanning unit.

[0081] In this embodiment of the present application, target feature information refers to target feature parameters extracted based on the time domain, frequency domain and spatial domain.

[0082] Specifically, frequency domain feature analysis is performed on the target echo data of each scanning unit to extract complete target feature information. First, a spectral amplitude threshold Vth = 1.5V is set as the target detection threshold. For scanning units that detect a target, feature extraction is performed in the time, frequency, and spatial domains. In the time domain feature extraction stage, the peak amplitude Ap and root mean square amplitude Arms of the echo signal are calculated to obtain the peak-to-average ratio K = Ap / Arms. Simultaneously, the start and end times ts and te of the signal are statistically analyzed to obtain the target echo duration T = te - ts. The echo envelope is analyzed to determine the number of scattering points N and the distribution of their spacing. Next, in the frequency domain feature extraction stage, the Doppler center frequency fc and spectral bandwidth B are calculated, the main lobe width Wm and side lobe level Sl are measured, and the coherent accumulation gain G and phase stability σφ are calculated. Finally, spatial domain feature extraction is performed, recording the target's range R, azimuth angle θ, and elevation angle φ. The target's radial velocity vr and tangential velocity vt are calculated, and the target's range span Dr and azimuth span Da are estimated. This multidimensional feature extraction method can comprehensively describe the target's physical characteristics and motion state. For example, for a vehicle target, a typical feature combination is: peak-to-average ratio of 3.2, number of scattering points 4-6, Doppler frequency 500Hz, and range span of 3 range units. This feature information can be used for subsequent target recognition and tracking. This comprehensive extraction method can obtain complete target feature information, improving the accuracy and reliability of target recognition.

[0083] Based on the above embodiment, as an optional embodiment, the step of performing target extraction on the target echo data according to the frequency domain characteristics to obtain target feature information of each scanning unit may further include steps 401 to 404:

[0084] Step 401: Perform amplitude analysis on the frequency domain features to determine the frequency domain amplitude threshold.

[0085] Specifically, the frequency domain features are analyzed for amplitude to determine the appropriate frequency domain amplitude threshold. First, the frequency domain amplitude mean μ and standard deviation σ for the entire scan area are calculated, and a statistical iteration method is used to determine the threshold. The initial threshold is set to Vth_0 = μ + 2σ. Samples above this threshold are counted and the mean μ1 and standard deviation σ1 are recalculated. The threshold is then updated to Vth_1 = μ1 + 2σ1. This process is repeated until the threshold change is less than 0.1dB or the maximum number of iterations, 10, is reached. The final frequency domain amplitude threshold Vth is used for subsequent target detection. This adaptive threshold determination method dynamically adjusts the detection threshold based on the actual signal environment, ensuring a low false alarm rate while preventing missed detection of real targets.

[0086] Step 402: Target detection is performed on the target echo data according to the frequency domain amplitude threshold to obtain a target candidate area.

[0087] Specifically, target detection is performed on target echo data using a defined frequency domain amplitude threshold Vth. For each scanning cell, the frequency domain amplitude V(i,j) (i,j represents the range gate and azimuth gate numbers, respectively) is calculated. If V(i,j) exceeds Vth, the cell is marked as a potential target. Connected regions are then analyzed for adjacent target points, and connected target points within an eight-neighborhood are grouped as the same target candidate region. To prevent false targets, a minimum target size constraint is imposed: a candidate region must contain at least three adjacent cells to be retained. Finally, the location and range information of all target candidate regions that meet the criteria are output, providing a basis for subsequent target confirmation.

[0088] Step 403: Calculate the phase difference feature value within the target candidate area, where the phase difference feature value is calculated based on the phase change between adjacent frames.

[0089] Specifically, the phase difference feature value is calculated for each target candidate region. First, the phase difference between two adjacent frames of each unit in the candidate region is extracted. , and then calculate the statistical characteristics within the region: ; ; is the complex signal of two adjacent frames, K is the number of points in the candidate area, μφ is the average phase difference, and σφ is the standard deviation of the phase difference. Then the phase difference feature value is .

[0090] Step 404: Target confirmation is performed on the target candidate area according to the phase difference characteristic value to obtain target characteristic information of each scanning unit.

[0091] Specifically, the final target confirmation is performed on the target candidate area based on the phase difference feature value, and the phase difference feature value threshold PSth = 0.6 is set. When the PS of the candidate area is greater than PSth, the real target is confirmed in the area. For the confirmed target area, its target feature information is extracted, including time domain features (signal amplitude, duration), frequency domain features (Doppler frequency, spectrum bandwidth), and spatial domain features (position coordinates, motion parameters). For example, the feature information of a target area may be: peak amplitude 2.5V, Doppler frequency 500Hz, target position (R=100m,θ=30°). This target confirmation method based on phase difference features can effectively distinguish real targets from false targets and improve detection reliability.

[0092] Step 50: Determine control parameters of the mechanical 3D radar according to the target feature information, and control the mechanical 3D radar to execute according to the control parameters.

[0093] Specifically, the following three types of control parameters are adjusted based on the target feature information: First, the signal processing control parameters are adjusted. The scanning unit size parameters are adjusted based on the target distance R: When R < 100m, the range gate width ΔR is set to 2m and the azimuth angle interval Δθ is set to 0.3°; when R ≥ 100m, ΔR is set to 4m and Δθ is set to 0.6°. The coherent processing parameters are adjusted based on the target phase stability σφ: When σφ < 0.2, the number of coherent accumulation frames N is set to 12 frames and the phase compensation coefficient α is set to 0.8; when σφ ≥ 0.2, N is set to 6 frames and α is set to 0.6. The detection threshold parameters are adjusted based on the target peak-to-average ratio K: When K > 3, the amplitude threshold Vth is set to 1.8V and the phase difference threshold PSth is set to 0.7; when K ≤ 3, Vth is set to 1.2V and PSth is set to 0.5.

[0094] Then, the detection processing control parameters were adjusted. When the number of target scattering points was greater than 4, the minimum number of connected units (Nmin) was set to 5, and the maximum region size (Smax) was set to 12. When the number of scattering points was less than 4, Nmin was set to 3, and Smax was set to 8. Furthermore, the phase consistency threshold (σth) was adjusted to 0.3, the confirmation confidence level (Pth) was adjusted to 0.85, the spectrum analysis window length (L) was set to 256, and the feature normalization coefficient (K) was set to 1.5.

[0095] Finally, adjust the system's operating control parameters. Set the scan period based on the target radial velocity vr: when vr > 10 m / s, T = 80 ms; when vr ≤ 10 m / s, T = 120 ms. The sampling rate fs is fixed at 1 MHz, and the processing update rate Ru is set to 10 Hz.

[0096] These optimized control parameters are sent to the mechanical 3D radar execution module in real time, enabling the radar system to adaptively respond to different target characteristics. For example, when detecting high-speed moving targets, the tracking update rate is increased by 40% by shortening the scanning cycle and reducing the number of accumulated frames. When detecting small near-field targets, the target detection probability is increased by 25% by improving spatial resolution and lowering the detection threshold.

[0097] Based on the above embodiment, as another optional embodiment, the step of determining the control parameters of the mechanical 3D radar according to the target feature information may further include steps 501 to 506:

[0098] Step 501: Calculate the target density weight of each scanning area according to the target distribution density in the target feature information.

[0099] Specifically, we perform density analysis on target feature information and calculate the target density weight of each scanning area. First, we divide the entire detection space into M×N scanning areas, each of which is 100m×30°. For the (i, j)th scanning area, we count the number of targets n(i, j) in it and calculate the target density of this area: ρ(i,j) is the target density of the (i,j)th region (individuals / km²); n(i,j) is the number of targets in the region, and S(i,j) is the area of ​​the region (km²). Then calculate the target density weight: Where w(i,j) is the normalized target density weight, ranging from [0,1]. This weight calculation method based on target distribution can reflect the target density in different areas.

[0100] Step 502: Calculate a rotation speed adjustment coefficient based on a ratio of a target density weight to a preset reference weight.

[0101] Specifically, the speed adjustment coefficient is calculated based on the target density weight. First, the preset base weight w0=0.5 is set, and then the weight ratio of each area is calculated: ; Calculate the speed adjustment coefficient based on the weight ratio: ; Among them, r(i,j) is the weight ratio; kv is the speed adjustment coefficient;

[0102] is the adjustment factor, with a value of 0.5; is the average value of the weight ratios of all regions.

[0103] Step 503: Determine the radar rotation speed and the scanning distance per unit time according to the rotation speed adjustment coefficient.

[0104] Specifically, the radar speed and the scanning distance per unit time are determined based on the speed adjustment coefficient according to the following formula. The radar speed calculation formula is: ; Scanning distance per unit time: Where: v is the adjusted radar speed (rpm); v0 is the reference speed, set to 30 rpm; R is the nominal scanning radius (m); L is the scanning distance per unit time (m / s).

[0105] Step 504: Calculate the transmit power adjustment coefficient based on the echo amplitude mean in the target feature information.

[0106] Specifically, the echo amplitude data in the target feature information is processed to calculate the transmit power adjustment coefficient. First, the mean echo amplitude of all targets is extracted: ; Calculate the transmit power adjustment coefficient: ; Where: Aavg is the average echo amplitude; Ak is the echo amplitude of the kth target; kp is the transmit power adjustment coefficient; Aref is the reference amplitude value, set to 1V.

[0107] Step 505: Determine the radar transmission power and maximum detection range based on the transmission power adjustment coefficient.

[0108] Specifically, the radar transmit power and maximum detection range are determined based on the transmit power adjustment coefficient. The radar transmit power is calculated as: ; Maximum detection distance: ; Where: P is the adjusted transmit power (W); P0 is the reference transmit power, set to 100W; Rmax is the maximum detection distance (m); R0 is the reference detection distance, set to 200m.

[0109] Step 506: The radar rotation speed, transmission power and maximum detection distance are used as control parameters of the mechanical 3D radar.

[0110] Specifically, the calculated radar speed v, transmit power P, and maximum detection distance Rmax are used as control parameters of the mechanical 3D radar. The system packages these parameters into control instructions: ; sent to the radar execution module for real-time adjustments. For example, when detecting a high-density target area (w(i,j)=0.8), the system automatically reduces the rotation speed to 24rpm and increases the transmit power to 150W, extending the maximum detection range to 245m, enabling detailed scanning and enhanced detection of densely populated target areas.

[0111] See Figure 2 , is a schematic diagram of a module of a control system of a mechanical 3D radar provided in an embodiment of the present application, wherein the system includes:

[0112] a scanning unit division module, configured to obtain real-time operating status parameters of the mechanical 3D radar, determine a scanning coverage area of ​​the mechanical 3D radar based on the operating status parameters, and divide the scanning coverage area into a plurality of scanning units;

[0113] a signal enhancement processing module, configured to collect radar echo signals from each of the scanning units and perform signal enhancement processing on the radar echo signals according to the spatial position information of each of the scanning units to generate enhanced target echo data, wherein the signal enhancement processing includes distance compensation and angle compensation;

[0114] A frequency domain feature extraction module is used to perform time series analysis and coherent accumulation processing on the target echo data to obtain a coherent accumulation result, and extract frequency domain features based on the coherent accumulation result;

[0115] a feature information extraction module, configured to extract the target echo data according to the frequency domain features to obtain target feature information of each scanning unit;

[0116] A control parameter determination module is used to determine the control parameters of the mechanical 3D radar according to the target feature information, and control the mechanical 3D radar to execute according to the control parameters.

[0117] Optionally, the scanning unit division module is further used to extract signal transmission power, radar rotation speed and scanning angle from the working status parameters;

[0118] Determine the maximum detection distance according to the signal transmission power, and determine the angle range according to the scanning angle;

[0119] determining a scanning coverage area of ​​the mechanical 3D radar according to the maximum detection distance and the angle range;

[0120] Obtaining a beam width of the mechanical 3D radar, and calculating a minimum size of each scanning unit based on the beam width;

[0121] The scanning coverage area is divided into a plurality of scanning units according to the radar rotation speed and the minimum size.

[0122] Optionally, the scanning unit division module is further configured to calculate the product of the minimum size and the radar rotation speed to obtain a scanning distance per unit time;

[0123] Dividing the scanning coverage area into a plurality of scanning segments along a radial direction, wherein the radial length of each scanning segment is proportional to the scanning distance per unit time;

[0124] Calculating the number of divisions of each scanning segment, wherein the number of divisions is inversely proportional to the radial length of the scanning segment;

[0125] Each of the scanning sections is divided into a plurality of scanning units according to the number of divisions, and a size of each of the scanning units is not less than the minimum size.

[0126] Optionally, the signal enhancement processing module is further configured to calculate a range attenuation coefficient based on the radial distance, and perform distance compensation on the radar echo signal according to the range attenuation coefficient;

[0127] Calculating an angle error according to the azimuth information, and performing angle compensation on the distance-compensated echo signal based on the angle error;

[0128] The compensated echo signal is denoised to generate enhanced target echo data.

[0129] Optionally, the frequency domain feature extraction module is further configured to sort the target echo data according to a scanning time sequence to obtain a time sequence echo sequence;

[0130] performing phase alignment on the time-series echo sequence to obtain an aligned echo sequence;

[0131] Calculating the phase difference between adjacent frames of the aligned echo sequence to obtain a phase difference sequence;

[0132] Performing coherent accumulation processing on the phase difference sequence to obtain a coherent accumulation result.

[0133] Optionally, the feature information extraction module is further configured to perform amplitude analysis on the frequency domain feature to determine a frequency domain amplitude threshold;

[0134] Performing target detection on the target echo data according to the frequency domain amplitude threshold to obtain a target candidate area;

[0135] Calculating a phase difference feature value within the target candidate area, where the phase difference feature value is calculated based on a phase change between adjacent frames;

[0136] Target confirmation is performed on the target candidate area according to the phase difference characteristic value to obtain target characteristic information of each scanning unit.

[0137] Optionally, the control parameter determination module is further configured to calculate a target density weight of each scanning area according to the target distribution density in the target feature information;

[0138] Calculating a speed adjustment coefficient based on a ratio of the target density weight to a preset reference weight;

[0139] Determine the radar rotation speed and the scanning distance per unit time according to the rotation speed adjustment coefficient;

[0140] Calculate the transmission power adjustment coefficient based on the echo amplitude mean in the target feature information;

[0141] Determining the radar transmission power and the maximum detection distance based on the transmission power adjustment coefficient;

[0142] The radar rotation speed, the transmission power and the maximum detection distance are used as control parameters of the mechanical 3D radar.

[0143] It should be noted that the above embodiments provide systems that implement their functions using only the division of the above functional modules as an example. In actual applications, the above functions can be assigned to different functional modules as needed, that is, the internal structure of the device can be divided into different functional modules to complete all or part of the functions described above. In addition, the system and method embodiments provided in the above embodiments are based on the same concept. The specific implementation process is detailed in the method embodiment and will not be repeated here.

[0144] An embodiment of the present application also provides a computer storage medium, which can store multiple instructions. The instructions are suitable for being loaded by a processor and executing a control method for a mechanical 3D radar of the above embodiment. The specific execution process can be found in the specific description of the above embodiment and will not be repeated here.

[0145] Please refer to Figure 3 The present application also discloses an electronic device. Figure 3 The electronic device 300 may include: at least one processor 301 , at least one network interface 304 , a user interface 303 , a memory 305 , and at least one communication bus 302 .

[0146] The communication bus 302 is used to implement the connection and communication between these components.

[0147] The user interface 303 may include a display screen (Display) and a camera (Camera). Optionally, the user interface 303 may also include a standard wired interface and a wireless interface.

[0148] The network interface 304 may optionally include a standard wired interface or a wireless interface (such as a WI-FI interface).

[0149] The processor 301 may include one or more processing cores. Using various interfaces and circuits, the processor 301 connects to various components within the server. It executes instructions, programs, code sets, or instruction sets stored in the memory 305, as well as accesses data stored in the memory 305, to perform various server functions and process data. Optionally, the processor 301 may be implemented using at least one of the following hardware forms: a digital signal processing (DSP), a field-programmable gate array (FPGA), or a programmable logic array (PLA). The processor 301 may integrate one or a combination of a central processing unit (CPU), a graphics processing unit (GPU), and a modem. The CPU primarily processes the operating system, user interface, and application programs; the GPU is responsible for rendering and drawing content displayed on the display screen; and the modem handles wireless communications. It is understood that the modem may not be integrated into the processor 301 but implemented as a separate chip.

[0150] Among them, the memory 305 may include a random access memory (RAM) or a read-only memory (Read-Only Memory). Optionally, the memory 305 includes a non-transitory computer-readable storage medium. The memory 305 can be used to store instructions, programs, codes, code sets or instruction sets. The memory 305 may include a program storage area and a data storage area, wherein the program storage area may store instructions for implementing an operating system, instructions for at least one function (such as a touch function, a sound playback function, an image playback function, etc.), instructions for implementing the above-mentioned various method embodiments, etc.; the data storage area may store data involved in the above-mentioned various method embodiments, etc. The memory 305 may also optionally be at least one storage device located away from the aforementioned processor 301. Refer to Figure 3 The memory 305 as a computer storage medium may include an operating system, a network communication module, a user interface module, and an application program for a control method of a mechanical 3D radar.

[0151] exist Figure 3In the electronic device 300 shown, the user interface 303 is mainly used to provide an input interface for the user and obtain the data input by the user; and the processor 301 can be used to call an application program for a mechanical 3D radar control method stored in the memory 305. When executed by one or more processors 301, the electronic device 300 executes one or more methods in the above embodiments. It should be noted that for the aforementioned method embodiments, for the sake of simplicity of description, they are all expressed as a series of action combinations, but those skilled in the art should know that this application is not limited to the order of the actions described, because according to this application, certain steps can be performed in other orders or simultaneously. Secondly, those skilled in the art should also know that the embodiments described in the specification are all preferred embodiments, and the actions and modules involved are not necessarily required for this application.

[0152] In the above embodiments, the description of each embodiment has its own focus. For parts that are not described in detail in a certain embodiment, reference can be made to the relevant descriptions of other embodiments.

[0153] In the several embodiments provided in this application, it should be understood that the disclosed devices can be implemented in other ways. For example, the device embodiments described above are merely schematic, such as the division of units, which is only a logical function division. In actual implementation, there may be other division methods, such as multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed can be through some service interface, and the indirect coupling or communication connection of devices or units can be electrical or other forms.

[0154] Units described as separate components may or may not be physically separate, and components shown as units may or may not be physical units, that is, they may be located in one place or distributed across multiple network units. Some or all of these units may be selected to achieve the purpose of this embodiment according to actual needs.

[0155] In addition, the functional units in the various embodiments of the present application may be integrated into a single processing unit, or each unit may exist physically separately, or two or more units may be integrated into a single unit. The aforementioned integrated units may be implemented in the form of hardware or software functional units.

[0156] The integrated unit, if implemented in the form of a software function unit and sold or used as an independent product, can be stored in a computer readable memory. Based on such understanding, the technical solutions of the present application essentially or say the part that contributes to the prior art or the whole or part of the technical solutions can be embodied in the form of a software product. The computer software product is stored in a memory and includes a plurality of instructions for causing a computer device (which can be a personal computer, a server or a network device, etc.) to execute all or part of the steps of the embodiments of the present application. The aforementioned memory includes: a U disk, a mobile hard disk, a magnetic disk or an optical disk, and various media that can store program codes.

[0157] The above are only exemplary embodiments of the present disclosure, and cannot limit the scope of the present disclosure. That is, any equivalent changes and modifications made in accordance with the teachings of the present disclosure are still within the scope of the present disclosure. Other embodiments of the present disclosure will be readily apparent to those skilled in the art upon considering the specification and practicing the true principles of the present disclosure.

[0158] The present application is intended to cover any variations, uses or adaptive changes of the present disclosure that follow the general principles of the present disclosure and include common knowledge or conventional technical means in the technical field of the present disclosure not described in the present disclosure. The specification and examples are only considered as exemplary.

Claims

1. A control method for a mechanical 3D radar, characterized in that: The method comprises: Acquiring real-time operating status parameters of a mechanical 3D radar, determining a scanning coverage area of ​​the mechanical 3D radar based on the operating status parameters, and dividing the scanning coverage area into a plurality of scanning units; collecting radar echo signals in each of the scanning units, and performing signal enhancement processing on the radar echo signals according to spatial position information of each of the scanning units to generate enhanced target echo data, wherein the signal enhancement processing includes distance compensation and angle compensation; Performing time series analysis and coherent accumulation processing on the target echo data to obtain a coherent accumulation result, and extracting frequency domain features based on the coherent accumulation result; Performing target extraction on the target echo data according to the frequency domain characteristics to obtain target feature information of each scanning unit; The control parameters of the mechanical 3D radar are determined according to the target feature information, and the mechanical 3D radar is controlled to execute according to the control parameters.

2. The control method of the mechanical 3D radar according to claim 1, characterized in that: The determining of the scanning coverage area of ​​the mechanical 3D radar based on the working state parameter and dividing the scanning coverage area into a plurality of scanning units includes: Extract signal transmission power, radar speed and scanning angle from working status parameters; Determine the maximum detection distance according to the signal transmission power, and determine the angle range according to the scanning angle; determining a scanning coverage area of ​​the mechanical 3D radar according to the maximum detection distance and the angle range; Obtaining a beam width of the mechanical 3D radar, and calculating a minimum size of each scanning unit based on the beam width; The scanning coverage area is divided into a plurality of scanning units according to the radar rotation speed and the minimum size.

3. The control method of the mechanical 3D radar according to claim 2, characterized in that: The step of dividing the scanning coverage area into a plurality of scanning units according to the radar rotation speed and the minimum size includes: Calculating the product of the minimum size and the radar rotation speed to obtain a scanning distance per unit time; Dividing the scanning coverage area into a plurality of scanning segments along a radial direction, wherein the radial length of each scanning segment is proportional to the scanning distance per unit time; Calculating the number of divisions of each scanning segment, wherein the number of divisions is inversely proportional to the radial length of the scanning segment; Each of the scanning sections is divided into a plurality of scanning units according to the number of divisions, and a size of each of the scanning units is not less than the minimum size.

4. The control method of the mechanical 3D radar according to claim 1, characterized in that: The spatial position information includes radial distance and azimuth information, and the performing signal enhancement processing on the radar echo signal according to the spatial position information of each scanning unit to generate enhanced target echo data includes: calculating a distance attenuation coefficient based on the radial distance, and performing distance compensation on the radar echo signal according to the distance attenuation coefficient; Calculating an angle error according to the azimuth information, and performing angle compensation on the distance-compensated echo signal based on the angle error; The compensated echo signal is denoised to generate enhanced target echo data.

5. The control method of the mechanical 3D radar according to claim 1, characterized in that: The target echo data is subjected to time series analysis and coherent accumulation processing to obtain a coherent accumulation result, including: Sorting the target echo data according to a scanning time sequence to obtain a time sequence echo sequence; performing phase alignment on the time-series echo sequence to obtain an aligned echo sequence; Calculating the phase difference between adjacent frames of the aligned echo sequence to obtain a phase difference sequence; Performing coherent accumulation processing on the phase difference sequence to obtain a coherent accumulation result.

6. The control method of the mechanical 3D radar according to claim 1, characterized in that: The target extraction is performed on the target echo data according to the frequency domain characteristics to obtain target feature information of each scanning unit, including: Performing amplitude analysis on the frequency domain features to determine a frequency domain amplitude threshold; Performing target detection on the target echo data according to the frequency domain amplitude threshold to obtain a target candidate area; Calculating a phase difference feature value within the target candidate area, where the phase difference feature value is calculated based on a phase change between adjacent frames; Target confirmation is performed on the target candidate area according to the phase difference characteristic value to obtain target characteristic information of each scanning unit.

7. The control method of the mechanical 3D radar according to claim 1, characterized in that: The determining of the control parameters of the mechanical 3D radar according to the target feature information includes: Calculating the target density weight of each scanning area according to the target distribution density in the target feature information; Calculating a speed adjustment coefficient based on a ratio of the target density weight to a preset reference weight; determining the radar rotation speed according to the rotation speed adjustment coefficient; Calculate the transmission power adjustment coefficient based on the echo amplitude mean in the target feature information; Determining the radar transmission power and the maximum detection distance based on the transmission power adjustment coefficient; The radar rotation speed, the radar transmission power and the maximum detection distance are used as control parameters of the mechanical 3D radar.

8. A control system for a mechanical 3D radar, characterized in that: The system comprises: a scanning unit division module, configured to obtain real-time operating status parameters of the mechanical 3D radar, determine a scanning coverage area of ​​the mechanical 3D radar based on the operating status parameters, and divide the scanning coverage area into a plurality of scanning units; a signal enhancement processing module, configured to collect radar echo signals from each of the scanning units and perform signal enhancement processing on the radar echo signals according to the spatial position information of each of the scanning units to generate enhanced target echo data, wherein the signal enhancement processing includes distance compensation and angle compensation; A frequency domain feature extraction module is used to perform time series analysis and coherent accumulation processing on the target echo data to obtain a coherent accumulation result, and extract frequency domain features based on the coherent accumulation result; a feature information extraction module, configured to extract the target echo data according to the frequency domain features to obtain target feature information of each scanning unit; A control parameter determination module is used to determine the control parameters of the mechanical 3D radar according to the target feature information, and control the mechanical 3D radar to execute according to the control parameters.

9. A computer-readable storage medium, characterized in that The computer-readable storage medium stores a plurality of instructions, and the instructions are suitable for being loaded by a processor and executing the method according to any one of claims 1 to 7.

10. An electronic device, characterized in that: The electronic device comprises a processor, a memory, a user interface and a network interface, wherein the memory is used to store instructions, the user interface and the network interface are used to communicate with other devices, and the processor is used to execute the instructions stored in the memory so that the electronic device executes the method according to any one of claims 1 to 7.

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