Millimeter wave radar beamforming method, apparatus, device, and storage medium

Abstract

The present application relates to the technical field of radar beam shaping, and particularly relates to a millimeter wave radar beam shaping method, device, equipment and storage medium. The method comprises the following steps: transmitting a linear frequency modulation detection waveform based on a millimeter wave radar array and collecting echoes to obtain a multi-path signal layered set; performing multi-path interference analysis based on the spatial coordinates of scatterers to obtain environmental multi-path interference data; performing beam shaping and multi-path interference compensation according to the environmental multi-path interference data to generate first detection beam parameters; and performing sidelobe beam gradual attenuation processing on the first detection beam parameters to output second detection beam parameters. The present application realizes efficient radar multi-path suppression, improves the quality of radar beam shaping, and thus improves detection reliability and stability.

Description

Technical Field

[0001] This invention relates to the field of radar beamforming technology, and in particular to a millimeter-wave radar beamforming method, apparatus, equipment, and storage medium. Background Technology

[0002] In complex application environments, the detection performance of millimeter-wave radar array sensors is often significantly affected by multipath effects. Multipath effects refer to the phenomenon where electromagnetic waves emitted by radar, after being reflected, scattered, or diffracted by the ground, walls, vehicles, equipment casings, etc., reach the receiver through multiple propagation paths. Multipath echoes and direct target echoes superimpose in time, frequency, and spatial dimensions, easily generating false targets, angular offsets, and range estimation errors, severely reducing the detection reliability and stability of the radar system. Existing multipath suppression methods mainly focus on time-domain or frequency-domain signal processing, such as distinguishing multipath signals through range thresholds, filtering algorithms, or Doppler characteristics. These methods are effective when multipath is weak or the environment is relatively simple, but in indoor environments, urban canyons, or high-reflection industrial settings, due to the complex distribution of multipath paths and dense reflection sources, traditional methods struggle to accurately distinguish target echoes from multipath interference, resulting in limited suppression effects. Summary of the Invention

[0003] To address the aforementioned technical problems, this invention proposes a millimeter-wave radar beamforming method, apparatus, device, and storage medium, thereby resolving at least one of the aforementioned technical problems.

[0004] To achieve the above objectives, the present invention provides a millimeter-wave radar beamforming method, comprising the following steps: Step S1: Based on the millimeter-wave radar array, transmit linear frequency modulated detection waveforms and collect echoes to obtain multipath signal hierarchical sets; Step S2: Perform multipath interference analysis based on the spatial coordinates of the scatterer to obtain environmental multipath interference data; Step S3: Perform beamforming and multipath interference compensation based on environmental multipath interference data to generate the first detection beam parameters; Step S4: Perform sidelobe beam attenuation processing on the first probe beam parameters and output the second probe beam parameters.

[0005] This specification provides a millimeter-wave radar beamforming apparatus for performing the millimeter-wave radar beamforming method described above, comprising: The echo acquisition unit is used to transmit linear frequency modulated detection waveforms based on millimeter-wave radar arrays and acquire echoes to obtain multipath signal hierarchical sets. The interference analysis unit is used to perform multipath interference analysis based on the spatial coordinates of the scatterer to obtain environmental multipath interference data. The interference compensation unit is used to perform beamforming and multipath interference compensation based on environmental multipath interference data, and to generate the first detection beam parameters. The attenuation processing unit is used to perform sidelobe beam attenuation processing on the first probe beam parameters and output the second probe beam parameters.

[0006] The present invention also provides a computer device, including a memory and a processor, wherein the memory stores a computer program, and the processor executes the computer program to implement the steps of the millimeter-wave radar beamforming method described in any of the preceding claims.

[0007] The present invention also provides a computer-readable storage medium having a computer program stored thereon, wherein the computer program, when executed by a processor, implements the steps of the millimeter-wave radar beamforming method described in any of the preceding claims.

[0008] The specific benefits of this invention are as follows: By employing linear frequency modulation (LFM) to detect waveforms and utilizing its broadband characteristics, millimeter-wave radar achieves high range resolution, effectively distinguishing direct path echoes from multipath reflections in the time or range domains, providing a precise data foundation for subsequent multipath suppression. Multi-channel echo data is synchronously acquired via an array antenna, and combined with range gating and time delay differences, the echo signals are divided into hierarchical sets of multipath signals corresponding to different propagation paths. This ensures the data structure of various multipath signals is distinguishable, avoiding multipath signal aliasing. Angle estimation, time delay estimation, and array pattern analysis are performed on the hierarchical sets of multipath signals to extract the spatial coordinate information of the scattering bodies, enabling precise localization of different multipath reflection sources and preventing misidentification of multipath signals as target echoes. By uniformly modeling parameters such as the spatial coordinates of the scattering body, reflection intensity, and angle of arrival (AoA), an environmental multipath interference dataset is formed, transforming multipath interference from random noise into modelable and predictable structured interference information. Multipath analysis based on the spatial dimension, compared to purely time-domain or frequency-domain methods, can effectively distinguish between real targets and mirror targets / false targets, reducing ranging and angle measurement errors caused by multipath. The array weighting coefficients are optimized based on the target's direction and the distribution of multipath interference in the environment, ensuring the main lobe points towards the target, achieving directional enhancement of target echo energy and improving the signal-to-noise ratio (SNR). Nulls or energy attenuation regions are introduced along the multipath interference direction to reduce the impact of multipath reflection signals on main lobe detection, achieving spatial domain multipath suppression. Multipath interference compensation corrects phase shifts and amplitude distortions caused by environmental reflections, avoiding beamform distortion and improving beamforming stability and accuracy. Gradual attenuation of sidelobes reduces their sensitivity to echoes from non-target directions, further suppressing multipath signals received by sidelobes and reducing false echoes. Gradual attenuation, rather than abrupt truncation, ensures a smooth transition in beam energy distribution, avoiding phase discontinuities or array pattern distortion caused by sudden sidelobe drops. By controlling the energy of the side lobes, the main lobe becomes more concentrated and the level of the side lobes decreases, thereby improving angular resolution and target separation capability. Attached Figure Description

[0009] Figure 1 This is a schematic diagram of the steps of a millimeter-wave radar beamforming method according to the present invention; Figure 2 This is a detailed flowchart illustrating the implementation steps of step S1. Figure 3 This is a flowchart illustrating the detailed implementation steps of step S2. Detailed Implementation

[0010] It should be understood that the specific embodiments described herein are for illustrative purposes only and are not intended to limit the scope of the invention.

[0011] This application provides a millimeter-wave radar beamforming method, apparatus, device, and storage medium. The execution entities of the millimeter-wave radar beamforming method, apparatus, device, and storage medium include, but are not limited to, mechanical equipment, data processing platforms, cloud server nodes, network upload devices, etc., which can be considered as general computing nodes in this application. The data processing platform includes, but is not limited to, at least one of an audio / image management system, an information management system, and a cloud-based data management system.

[0012] Please see Figures 1 to 3 This invention provides a millimeter-wave radar beamforming method, comprising the following steps: Step S1: Based on the millimeter-wave radar array, transmit linear frequency modulated detection waveforms and collect echoes to obtain multipath signal hierarchical sets; Step S2: Perform multipath interference analysis based on the spatial coordinates of the scatterer to obtain environmental multipath interference data; Step S3: Perform beamforming and multipath interference compensation based on environmental multipath interference data to generate the first detection beam parameters; Step S4: Perform sidelobe beam attenuation processing on the first probe beam parameters and output the second probe beam parameters.

[0013] In the embodiments of the present invention, see Figure 1 The diagram below illustrates the steps of a millimeter-wave radar beamforming method according to the present invention. In this example, the steps of the millimeter-wave radar beamforming method include: Step S1: Based on the millimeter-wave radar array, transmit linear frequency modulated detection waveforms and collect echoes to obtain multipath signal hierarchical sets; In this embodiment, the millimeter-wave radar array uses a linear frequency modulated continuous wave (LFM) method to detect space. The array's transmitting antenna radiates an LFM detection waveform towards the target area. The carrier frequency of this waveform is set in the millimeter-wave band, and the frequency modulation bandwidth is set to 2 GHz to achieve centimeter-level range resolution. The single frequency modulation period is set to approximately 50 μs to balance the requirements for detection range and velocity resolution. During spatial propagation, the echo signal undergoes direct reflection from the target and multipath propagation caused by environmental reflectors such as walls and the ground. Various echo signals are simultaneously acquired by multiple receiving channels in the array. The acquired multi-channel echo signals undergo pulse compression and peak extraction processing to obtain the range, energy, and spatial response characteristics corresponding to different propagation paths. Further, combining the spatial geometry of the array channels, propagation path analysis is performed on the echo components. Based on the consistency of energy intensity, propagation distance, and spatial pointing, the echo signal is divided into different levels, such as direct path, primary reflection path, and higher-order multipath, thus forming a structured multipath signal hierarchical set.

[0014] Step S2: Perform multipath interference analysis based on the spatial coordinates of the scatterer to obtain environmental multipath interference data; In this embodiment, by jointly calculating the arrival angle, propagation delay, and energy information of the multipath components, a geometric reflection model is used to inversely estimate the position of the scatterer generating multipath reflection, obtaining the position parameters of the scatterer in the spatial coordinate system. Subsequently, the spatial coordinates of the scatterer are time-series tracked within a continuous radar detection frame period, the occurrence frequency of the multipath component corresponding to each scatterer is statistically analyzed, and its probability distribution characteristics are constructed. Energy variation analysis is performed on the multipath components belonging to the same scatterer, calculating its energy fluctuation amplitude and fluctuation period to characterize the stability of multipath interference in the time and energy dimensions. By comprehensively analyzing information such as occurrence probability, energy fluctuation amplitude, and fluctuation period, environmental multipath interference data including multipath spatial location, stability, and interference intensity is formed.

[0015] Step S3: Perform beamforming and multipath interference compensation based on environmental multipath interference data to generate the first detection beam parameters; In this embodiment, the array beam is designed and optimized in a targeted manner. First, the pointing angle of the main lobe is determined by combining the spatial direction information of the detected target, and the initial phase and amplitude weights of each channel are calculated according to the array structure to maximize the gain of the synthesized beam in the target direction. Subsequently, environmental multipath interference data is introduced to constrain the beam design process. Suppression strategies are applied in spatial directions with high multipath interference probability or large energy fluctuations by adjusting the array channel weights to reduce the beam gain in these directions. This multipath interference compensation process, while ensuring the pointing accuracy of the main lobe, jointly controls the side lobes and the dominant multipath directions, thereby reducing the superposition effect of multipath signals on the target echo.

[0016] Step S4: Perform sidelobe beam attenuation processing on the first probe beam parameters and output the second probe beam parameters.

[0017] In this embodiment, the spatial energy distribution of the beam is further optimized based on the first probe beam parameters, with a focus on implementing gradual attenuation processing for the sidelobe beams. By analyzing the spatial pattern corresponding to the first probe beam parameters, the main lobe region and various levels of sidelobe regions are identified, and the energy distribution along the sidelobe directions is calculated. For directions with relatively high sidelobe energy, a gradual attenuation mechanism is introduced, continuously and smoothly adjusting the corresponding array channel weights to gradually reduce the sidelobe energy rather than abruptly suppressing it, thereby avoiding beam distortion. The gradual attenuation amplitude is set according to the ratio of sidelobe energy to main lobe energy; for example, when the sidelobe energy is higher than the main lobe energy... Apply stronger attenuation at 15dB.

[0018] In this embodiment, see Figure 2 The diagram below illustrates the detailed implementation steps of step S1. In this embodiment, the detailed implementation steps of step S1 include: Based on the linear frequency modulated detection waveform transmitted by the millimeter-wave radar array, environmental echo signals are collected through a multi-channel receiving antenna. The environmental echo signal is subjected to pulse compression and peak detection to extract the peak values ​​of multiple channels; Calculate the energy intensity and geometric relationship of the peak values ​​of the multiple channel signals; Based on the energy intensity and geometric relationship, multipath signal components are analyzed and identified to obtain a multipath signal layer set; the multipath signal layering results include direct paths, primary reflection paths, and higher-order multipaths.

[0019] In this embodiment, the millimeter-wave radar array employs a linear frequency modulated (LFM) continuous wave (CFW) system for space detection. The LFM detection waveform is radiated through a transmitting antenna to cover the area to be detected. The carrier frequency of the LFM detection waveform is set in the millimeter-wave band, with a modulation bandwidth of 2 GHz to achieve centimeter-level range resolution. The duration of a single modulation cycle is set to 50 μs to avoid range ambiguity while maintaining the ranging range. The array receiver consists of multiple receiving antenna channels with known spatial locations, maintaining a fixed spacing between each channel. This spacing is set to half a wavelength to meet the array's spatial sampling conditions. The transmitted waveform is scattered by targets and reflectors in the environment to form echo signals. These echo signals are synchronously acquired through each receiving channel, undergoing down-conversion and sampling processing to obtain multi-channel baseband echo signals. Pulse compression processing is applied to the LFM echo signals within each receiving channel to improve range resolution and enhance effective echo characteristics. The pulse compression is achieved by performing a Fast Fourier Transform (FFT) on the echo signal within the frequency modulation cycle, converting the time-domain signal to the range spectrum domain. The number of transformation points is set to 1024 or 2048 to improve the accuracy of range cell division. Before the spectrum transformation, a window function is applied to the echo signal to reduce sidelobe effects. Subsequently, an adaptive threshold detection method is used for peak detection on the range spectrum. The detection threshold is dynamically adjusted based on the statistical characteristics of neighboring range cells to suppress noise interference.

[0020] The echo energy intensity is calculated based on the peak amplitude information. The energy intensity is represented by the square of the amplitude or the cumulative energy of local distance cells, and the results for each channel are normalized to eliminate amplitude differences between channels. Then, considering the spatial relationship of each receiving antenna channel in the array, the phase difference and amplitude distribution characteristics between the peak values ​​of multiple channels are analyzed to construct an array response model to estimate the incident direction of the echo signal. Angle estimation is performed within a preset angle range, set at ±60°, with an angle resolution of 1°, to obtain the geometric pointing information of the echo in space. Based on the energy intensity characteristics and spatial geometric relationship of the echo signal, multipath propagation components are analyzed and classified. First, echoes are screened based on their energy intensity and stability within continuous processing cycles; echoes with higher energy and stronger directional consistency are identified as direct path components. Then, combining the relationship between the propagation distance increment and the incident angle offset, path analysis is performed on the remaining echoes. Echoes with slightly longer propagation distances and regular angle offsets relative to the direct path are identified as primary reflection paths, while echoes with lower energy, complex propagation paths, and discrete spatial distributions are classified as higher-order multipaths. Through the above analysis process, direct paths, primary reflection paths, and higher-order multipaths are respectively classified into different multipath signal hierarchical sets.

[0021] In this embodiment, see Figure 3 The diagram below illustrates the detailed implementation steps of step S2. In this embodiment, the detailed implementation steps of step S2 include: Multipath signal scattering estimation is performed based on multipath signal hierarchical sets to obtain the spatial coordinates of the scattering body; Define the radar detection frame period; perform time-series tracking sampling of the spatial coordinates of the scatterer based on the radar detection frame period to obtain the frequency of occurrence of the multipath component of the scatterer; Calculate the probability distribution of the occurrence frequency; calculate the multipath components of the multipath signal layer set based on the spatial coordinates of the scatterer to obtain the energy fluctuation amplitude and fluctuation period of the scatterer; Multipath interference analysis is performed based on the probability distribution, energy fluctuation amplitude, and fluctuation period to obtain environmental multipath interference data.

[0022] In this embodiment, based on the obtained multipath signal hierarchical set, scattering characteristic analysis and spatial inversion calculations are performed on multipath components at different levels to estimate the spatial coordinates of the scatterers that generate multipath reflections. The multipath signal hierarchical set includes direct paths, primary reflection paths, and higher-order multipaths, with each path retaining corresponding distance, incident angle, and energy information. By jointly processing the propagation distance and incident angle parameters of the primary reflection path and higher-order multipaths, and combining the geometric constraints of millimeter-wave propagation, a reflection path inversion model is constructed, mapping the echo path to the spatial location of the potential scatterer. Based on the estimated echo propagation distance and array angle, the geometric reflection model is used to back-calculate the scatterer's position, thereby obtaining the coordinate representation of the scatterer in two-dimensional or three-dimensional space. For multiple echo paths of the same scatterer appearing in different multipath layers, spatial clustering is used to merge them, reducing path estimation errors and improving the stability of scatterer positioning. A radar detection frame period is defined to describe the time scale of spatial information updates during continuous radar sensing; the frame period can be set to 50 ms to 100 ms to achieve a balance between temporal resolution and computational load. Subsequently, using the detection frame period as a time reference, the spatial coordinates of the scatterer obtained in step one are continuously sampled and tracked in a temporal sequence. Within each detection frame, the coordinates of the scatterer corresponding to the multipath signal layer set are matched and updated to determine whether each scatterer is activated by the corresponding multipath component in the current frame. By counting the number of times the same scatterer is detected in multiple consecutive detection frames, the occurrence frequency of the multipath component corresponding to that scatterer is calculated. The occurrence frequency is used to reflect the stability and persistence characteristics of the scatterer in the time dimension. Scatterers with higher frequencies usually correspond to environmental reflectors with stable structures and fixed positions, while scatterers with lower frequencies may originate from sporadic reflections or weak multipath paths.

[0023] By normalizing the occurrence frequency, the probability of each scatterer being activated by multipath components within a given time window is calculated, thus forming a multipath occurrence probability distribution to characterize the contribution of different scatterers to multipath formation in the environment. Subsequently, combined with the spatial coordinate information of the scatterers, energy analysis is performed on multipath components belonging to the same scatterer in a hierarchical manner. The energy intensity change sequence of the corresponding multipath component is extracted within consecutive detection frames, and the difference between its maximum and minimum energy values ​​is calculated to obtain the energy fluctuation amplitude. By analyzing the time interval characteristics of energy changes, the energy fluctuation period is estimated. The energy fluctuation amplitude reflects the strength and instability of the multipath signal, while the fluctuation period characterizes the temporal variation of multipath interference. Multipath components are weighted according to the occurrence probability distribution; multipaths with higher occurrence probabilities are identified as stable multipath interference, while those with lower occurrence probabilities are identified as random or occasional interference. Subsequently, combining the characteristics of energy fluctuation amplitude and fluctuation period, the influence of different types of multipath interference is quantitatively analyzed. Multipath components with larger energy fluctuation amplitudes and shorter fluctuation periods are considered to have stronger interference effects on beamforming and angle estimation. By integrating the above analysis results, an environmental multipath disturbance dataset is formed that includes multipath type, spatial location, temporal stability, and energy perturbation characteristics.

[0024] In this embodiment, the specific steps for estimating multipath signal scattering based on multipath signal hierarchical sets to obtain the spatial coordinates of the scatterer are as follows: The spatial angle of arrival information of multipath components is calculated based on the multipath signal hierarchical set to obtain the multipath angle of arrival set; Calculate the multipath signal propagation time and the direct path signal propagation time based on the multipath signal hierarchical set; The propagation delay is calculated based on the propagation time of the multipath signal and the propagation time of the direct path signal to obtain the propagation delay difference. Calculate the spatial proximity relationship of the multipath arrival angle set; Based on the propagation delay difference and spatial proximity, the backscatterer is estimated to obtain the spatial coordinates of the scatterer.

[0025] In this embodiment, based on the obtained multipath signal hierarchical set, the spatial angle of arrival information of various multipath components is calculated and summarized to form a multipath angle of arrival set. The multipath signal hierarchical set includes direct paths, primary reflection paths, and higher-order multipaths, each corresponding to a specific range position, energy intensity, and array channel response characteristics. By utilizing the spatial distribution relationship of multiple receiving channels in the millimeter-wave radar array, the phase difference and amplitude distribution of the same multipath component on different channels are jointly analyzed to construct an array spatial response model, and the incident direction is estimated within a preset angle search range. The angle search range is typically set to... The angle resolution is set to 1° or less, with a range of 60° to +60°, to ensure the accuracy and stability of multipath angle estimation. For the same multipath component, angle estimation results obtained in multiple range cells or multiple processing cycles are fused using consistency constraints to obtain a stable angle of arrival estimate. Based on the range information of each echo component in the multipath signal hierarchical set, the propagation time of the multipath signal and the corresponding direct path signal are calculated. The propagation time is obtained by converting the echo round-trip propagation distance to the electromagnetic wave propagation speed. Based on the range cell index obtained after pulse compression, combined with the frequency modulation parameters and range resolution of the millimeter-wave signal, the propagation distance corresponding to each multipath component is converted into propagation time. For the direct path signal, its propagation time corresponds to the shortest propagation path between the target or scatterer and the radar array, typically represented by the shortest distance and strongest energy echo component; while the propagation time of the multipath signal includes the additional reflection path length, representing a longer propagation distance.

[0026] For each multipath component, the direct path component with the closest spatial pointing relationship is selected as the reference path, and the corresponding propagation delay difference is calculated by the difference in their propagation times. This propagation delay difference is typically on the order of nanoseconds to microseconds, and its magnitude is directly related to the length of the reflection path. To improve the stability of the delay calculation, the propagation delay difference results obtained in multiple consecutive processing cycles are statistically averaged or filtered to suppress the jitter caused by measurement noise. The additional distance of the reflection path relative to the direct path is determined based on the propagation delay difference, and combined with the spatial direction corresponding to the arrival angle, this additional path is mapped to the possible scatterer location region. By intersecting and constraining the inversion results of multiple multipath components within the same spatially adjacent set, the spatial coordinates of the scatterer are determined. To improve the reliability of the estimation results, the consistency of the scatterer coordinates obtained in multiple consecutive processing cycles can be screened, retaining only the estimation results with small positional changes.

[0027] In this embodiment, the specific steps of step S3 are as follows: Target information is identified based on radar detection commands; the target information includes distance, speed, and spatial direction. Adaptive beamforming is performed based on the detected target information to obtain initial waveform parameters; Multipath interference compensation is performed on the initial waveform parameters based on environmental multipath interference data to generate the first detection beam parameters.

[0028] In this embodiment, the target to be detected is analyzed and identified based on the input radar detection command to determine the target information set for beamforming. The radar detection command includes parameter constraints related to target search or tracking. By analyzing the command, the target's area of ​​interest and detection priority are clarified. Subsequently, the target is jointly identified and confirmed by combining the range spectrum, velocity spectrum, and spatial angle information obtained from radar echo processing, thereby extracting the target's corresponding range, radial velocity, and spatial direction parameters. The range information is determined by the peak position of the echo signal in the range dimension, the velocity information is obtained through Doppler frequency shift analysis, and the spatial direction information is estimated based on the array channel response relationship. Based on the identified target information, the transmit and receive beams of the millimeter-wave radar array are adaptively adjusted to form a main lobe pointing towards the target and suppress energy in non-target directions. According to the target's spatial direction parameters, the phase and amplitude weights of each channel of the array are calculated to maximize the gain of the synthesized beam in the target direction. Combined with the target's range and velocity information, waveform parameters are jointly designed, including beam pointing angle, beamwidth, and waveform modulation-related parameters, thereby reducing energy radiation in irrelevant areas while meeting target resolution requirements. Based on the obtained environmental multipath interference data, the initial waveform parameters are corrected and compensated to reduce the impact of multipath interference on the detection beam. The environmental multipath interference data includes the spatial distribution, temporal stability, and energy perturbation characteristics of multipath interference. By correlating this data with the initial waveform parameters, the angular ranges and beam sidelobe directions susceptible to multipath interference are identified. Subsequently, the beam weight and pointing angle in the initial waveform parameters are adjusted. While maintaining the main lobe aligned with the detection target direction, the direction of multipath interference is suppressed or its weight is weakened, thereby reducing the superposition effect of multipath energy.

[0029] In this embodiment, the specific steps of step S4 are as follows: Identifying the main lobe beam and side lobe beams based on probe beam parameters; Calculate the energy distribution value of the sidelobe beam; Based on the energy distribution value, a gradual attenuation process is performed to output the second detection beam parameters; Real-time radar detection is performed based on the second detection beam parameters, and the actual echo signal is monitored; adaptive fine-tuning is performed based on the actual echo signal, and the results are fed back to the millimeter-wave radar array in real time.

[0030] In this embodiment, the spatial energy distribution characteristics of the beam are analyzed based on the generated probe beam parameters to distinguish between the main lobe beam and the side lobe beam. The probe beam parameters include information such as array channel weights, phase distribution, and beam pointing angle. By spatially mapping these parameters, a complete beam pattern can be obtained. Based on the concentration and pointing characteristics of the energy distribution in the beam pattern, the direction of the energy peak is first determined. The beam region corresponding to this direction is identified as the main lobe beam, and its angle range is typically centered on the peak direction, extending to both sides by a certain angular width, for example, ±3° to ±6°, to cover the uncertainty of the target direction. Besides the main lobe region, the beam energy distribution in other directions is identified as the side lobe beam, including near and far side lobes. After identifying the main lobe and side lobe beams, the energy distribution within the side lobe beam region is quantitatively calculated to assess its potential impact on detection performance. The energy distribution value is obtained by statistically analyzing the array output energy within the side lobe beam coverage angle range, specifically including the relative energy intensity of each angular direction within the side lobe region and the overall energy accumulation level. To improve the stability of energy assessment, sidelobe energy can be accumulated or averaged over multiple consecutive detection cycles, thereby reducing the impact of transient fluctuations. The sidelobe energy distribution value not only reflects the overall energy magnitude of the sidelobes but also the degree of energy diffusion in space, such as whether it is concentrated in a specific direction or exhibits a wide-angle distribution. Based on the magnitude of the sidelobe energy distribution value, the array channel weights in the corresponding directions are reduced according to a preset attenuation curve. A larger attenuation amplitude is applied to sidelobe directions with higher energy, and a smaller attenuation amplitude is applied to sidelobe directions with lower energy, thus creating a smooth energy transition effect. The attenuation parameter can be set with reference to the ratio of sidelobe energy to main lobe energy; for example, when the sidelobe energy exceeds the main lobe energy... An attenuation mechanism is activated at 15 dB. This gradual attenuation updates the array channel weights and phase distribution, generating second detection beam parameters optimized for sidelobes, resulting in a more spatially concentrated beam. Continuous radar detection is performed based on these second detection beam parameters to acquire actual echo signals under the current environment. Real-time monitoring and analysis enable adaptive fine-tuning of the beam parameters. The actual echo signals include target echoes and residual multipath echo information. Analysis of the echo signal's range distribution, angular stability, and energy variations evaluates the effectiveness of the current detection beam parameters. When a decrease in echo energy in the main lobe direction or an abnormal increase in echo energy in the side lobe direction is detected, the adaptive fine-tuning mechanism is triggered, making minor adjustments to the array channel weights and phase parameters to restore main lobe gain and further suppress sidelobe leakage. This fine-tuning process uses the second detection beam parameters as a reference and is continuously updated through a closed-loop feedback mechanism, allowing the beam shape to dynamically optimize with environmental changes.

[0031] In this embodiment, the specific steps of performing real-time radar detection based on the second detection beam parameters and monitoring the actual echo signal, performing adaptive fine-tuning processing based on the actual echo signal, and feeding back to the millimeter-wave radar array in real time are as follows: Real-time radar detection is performed based on the parameters of the second detection beam, and the actual echo signal is monitored; The signal-to-noise ratio, energy concentration, and spatial distribution stability of the actual echo signal are calculated to obtain the stable value of the echo signal. The stability value of the echo signal is compared and analyzed based on a preset signal stability threshold. When the stability value of the echo signal is detected to be greater than the preset signal stability threshold, the parameters of the second detection beam are adaptively fine-tuned and fed back to the millimeter-wave radar array in real time.

[0032] In this embodiment, a continuous radar detection process is performed based on the generated second detection beam parameters, causing the detection beam to radiate spatially according to the optimized pointing angle, array weight, and phase distribution. The second detection beam parameters have been processed to suppress sidelobe energy, and its main lobe direction is aligned with the current detection target or key sensing area. During the detection process, the echo signal acquired in each detection cycle is continuously monitored. The echo signal contains the target direct echo and residual multipath echo components. By acquiring and aligning the echo signal in multiple consecutive detection cycles, a time-continuous echo data sequence is formed to reflect the changes in detection effect under the current beam parameters. The signal-to-noise ratio (SNR) of the echo signal is calculated. By comparing the target echo energy with the background noise energy, an SNR index reflecting the clarity of the echo is obtained. Its value is usually expressed in decibels and is used to measure the enhancement effect of the detection beam on the target echo. Next, the concentration of echo energy is calculated. By analyzing the proportion of energy in the main lobe direction to the total echo energy, the effectiveness of energy concentration in the desired direction is evaluated. The higher the energy concentration, the smaller the sidelobe leakage and multipath interference. The spatial distribution stability of the echo signal is evaluated again. By comparing the consistency of the echo angle distribution and energy distribution over multiple consecutive detection cycles, the amplitude of spatial distribution variation is calculated to reflect the stability of the echo in the spatial dimension.

[0033] A pre-set signal stability threshold is used to measure whether the detection state meets the stability requirements. This threshold is set based on the detection accuracy requirements and environmental complexity, and is used to distinguish between stable detection states and states that require further optimization. The stable echo signal value obtained in step two is compared with the signal stability threshold. When the stable echo signal value is found to be greater than the preset threshold, it is determined that the current detection beam has good stability and reliability, but there is still room for further optimization. At this time, an adaptive fine-tuning mechanism is triggered. Without destroying the main lobe pointing and the overall beam shape, the array weight and phase distribution in the parameters of the second detection beam are slightly adjusted to further enhance the main lobe energy concentration and suppress the residual multipath effect. The fine-tuning process adopts a gradual adjustment method to avoid fluctuations in detection performance caused by sudden parameter changes, and the updated beam parameters are fed back to the millimeter-wave radar array in real time, so that the detection beam can continuously adapt to environmental changes.

[0034] In this embodiment, a millimeter-wave radar beamforming apparatus is provided for performing the millimeter-wave radar beamforming method as described above, including: The echo acquisition unit is used to transmit linear frequency modulated detection waveforms based on millimeter-wave radar arrays and acquire echoes to obtain multipath signal hierarchical sets. The interference analysis unit is used to perform multipath interference analysis based on the spatial coordinates of the scatterer to obtain environmental multipath interference data. The interference compensation unit is used to perform beamforming and multipath interference compensation based on environmental multipath interference data, and to generate the first detection beam parameters. The attenuation processing unit is used to perform sidelobe beam attenuation processing on the first probe beam parameters and output the second probe beam parameters.

[0035] The present invention also provides a computer device, including a memory and a processor, wherein the memory stores a computer program, and the processor executes the computer program to implement the steps of the millimeter-wave radar beamforming method described in any of the preceding claims.

[0036] The present invention also provides a computer-readable storage medium having a computer program stored thereon, wherein the computer program, when executed by a processor, implements the steps of the millimeter-wave radar beamforming method described in any of the preceding claims.

[0037] Therefore, the embodiments should be considered as exemplary and non-limiting in all respects, and the scope of the invention is defined by the appended claims rather than the foregoing description. Thus, all variations falling within the meaning and scope of the equivalents of the application are intended to be included within the invention.

[0038] The above description is merely a specific embodiment of the present invention, enabling those skilled in the art to understand or implement it. Various modifications to these embodiments will be readily apparent to those skilled in the art, and the general principles defined herein are implemented in other embodiments without departing from the spirit or scope of the invention. Therefore, the present invention is not to be limited to the embodiments shown herein, but is to be accorded the widest scope consistent with the principles and novel features of the invention herein.

Claims

1. A millimeter-wave radar beamforming method, characterized in that, Includes the following steps: Step S1: Based on the millimeter-wave radar array, transmit linear frequency modulated detection waveforms and collect echoes to obtain multipath signal hierarchical sets; Step S2: Perform multipath interference analysis based on the spatial coordinates of the scatterer to obtain environmental multipath interference data; Step S3: Perform beamforming and multipath interference compensation based on environmental multipath interference data to generate the first detection beam parameters; Step S4: Perform sidelobe beam attenuation processing on the first probe beam parameters and output the second probe beam parameters.

2. The millimeter-wave radar beamforming method according to claim 1, characterized in that, The specific steps of step S1 are as follows: Based on the linear frequency modulated detection waveform transmitted by the millimeter-wave radar array, environmental echo signals are collected through a multi-channel receiving antenna. The environmental echo signal is subjected to pulse compression and peak detection to extract the peak values ​​of multiple channels; Calculate the energy intensity and geometric relationship of the peak values ​​of the multiple channel signals; Based on the energy intensity and geometric relationship, multipath signal components are analyzed and identified to obtain a multipath signal layer set; the multipath signal layering results include direct paths, primary reflection paths, and higher-order multipaths.

3. The millimeter-wave radar beamforming method according to claim 1, characterized in that, The specific steps of step S2 are as follows: Multipath signal scattering estimation is performed based on multipath signal hierarchical sets to obtain the spatial coordinates of the scattering body; Define the radar detection frame period; perform time-series tracking sampling of the spatial coordinates of the scatterer based on the radar detection frame period to obtain the frequency of occurrence of the multipath component of the scatterer; Calculate the probability distribution of the frequency of occurrence; Based on the spatial coordinates of the scatterer, the multipath components of the multipath signal layer set are calculated to obtain the energy fluctuation amplitude and fluctuation period of the scatterer. Multipath interference analysis is performed based on the probability distribution, energy fluctuation amplitude, and fluctuation period to obtain environmental multipath interference data.

4. The millimeter-wave radar beamforming method according to claim 3, characterized in that, The specific steps for estimating multipath signal scattering based on multipath signal hierarchical sets to obtain the spatial coordinates of the scatterer are as follows: The spatial angle of arrival information of multipath components is calculated based on the multipath signal hierarchical set to obtain the multipath angle of arrival set; Calculate the multipath signal propagation time and the direct path signal propagation time based on the multipath signal hierarchical set; The propagation delay is calculated based on the propagation time of the multipath signal and the propagation time of the direct path signal to obtain the propagation delay difference. Calculate the spatial proximity relationship of the multipath arrival angle set; Based on the propagation delay difference and spatial proximity, the backscatterer is estimated to obtain the spatial coordinates of the scatterer.

5. The millimeter-wave radar beamforming method according to claim 1, characterized in that, The specific steps of step S3 are as follows: Target information is identified based on radar detection commands; the target information includes distance, speed, and spatial direction. Adaptive beamforming is performed based on the detected target information to obtain initial waveform parameters; Multipath interference compensation is performed on the initial waveform parameters based on environmental multipath interference data to generate the first detection beam parameters.

6. The millimeter-wave radar beamforming method according to claim 1, characterized in that, The specific steps of step S4 are as follows: Identifying the main lobe beam and side lobe beams based on probe beam parameters; Calculate the energy distribution value of the sidelobe beam; Based on the energy distribution value, a gradual attenuation process is performed to output the second detection beam parameters; Real-time radar detection is performed based on the parameters of the second detection beam, and the actual echo signal is monitored; The actual echo signal is adaptively fine-tuned and fed back to the millimeter-wave radar array in real time.

7. The millimeter-wave radar beamforming method according to claim 6, characterized in that, The specific steps of performing real-time radar detection based on the second detection beam parameters and monitoring the actual echo signal, and performing adaptive fine-tuning processing based on the actual echo signal and feeding it back to the millimeter-wave radar array in real time are as follows: Real-time radar detection is performed based on the parameters of the second detection beam, and the actual echo signal is monitored; The signal-to-noise ratio, energy concentration, and spatial distribution stability of the actual echo signal are calculated to obtain the stable value of the echo signal. The stability value of the echo signal is compared and analyzed based on a preset signal stability threshold. When the stability value of the echo signal is detected to be greater than the preset signal stability threshold, the parameters of the second detection beam are adaptively fine-tuned and fed back to the millimeter-wave radar array in real time.

8. A millimeter-wave radar beamforming device, characterized in that, For performing the millimeter-wave radar beamforming method as described in claim 1, comprising: The echo acquisition unit is used to transmit linear frequency modulated detection waveforms based on millimeter-wave radar arrays and acquire echoes to obtain multipath signal hierarchical sets. The interference analysis unit is used to perform multipath interference analysis based on the spatial coordinates of the scatterer to obtain environmental multipath interference data. The interference compensation unit is used to perform beamforming and multipath interference compensation based on environmental multipath interference data, and to generate the first detection beam parameters. The attenuation processing unit is used to perform sidelobe beam attenuation processing on the first probe beam parameters and output the second probe beam parameters.

9. A computer device comprising a memory and a processor, wherein the memory stores a computer program, characterized in that, When the processor executes the computer program, it implements the steps of the millimeter-wave radar beamforming method according to any one of claims 1 to 7.

10. A computer-readable storage medium having a computer program stored thereon, characterized in that, When the computer program is executed by the processor, it implements the steps of the millimeter-wave radar beamforming method according to any one of claims 1 to 7.

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