Work control method and device, storage medium, program product, equipment and vehicle

Abstract

The invention relates to a work control method and device of a vehicle-mounted radar system, a storage medium, a program product, equipment and a vehicle, and the method can select a phased array mode, an MIMO mode or a mixed mode of the vehicle-mounted radar system through the dynamic matching of the real-time working conditions of the vehicle to carry out environment detection, achieves the optimal configuration of the detection performance in different scenes, and improves the detection efficiency. The comprehensive detection performance of a vehicle-mounted radar system in a full scene is improved, the technical problem that a single-system radar cannot give consideration to energy efficiency, diversity gain and scene adaptability is solved, and the full-scene detection requirement of the vehicle-mounted radar in a vehicle-mounted environment is improved.

Description

Technical Field

[0001] This application relates to the field of vehicle radar control technology, and in particular to a method, device, storage medium, program product, equipment and vehicle for operating control of a vehicle radar system. Background Technology

[0002] Existing automotive radar systems, such as millimeter-wave radar, employ single-system architectures like MIMO or phased array, which cannot achieve optimal performance in various scenarios. For example:

[0003] While a single MIMO system architecture improves multi-target detection capabilities, its insufficient signal-to-noise ratio results in a low probability of detecting distant or weak targets, and its performance degrades significantly, especially in extreme weather conditions.

[0004] While a single phased array system architecture can achieve high-gain detection over long distances, it cannot perform virtual aperture expansion, has a limited field of view, and is weak in multi-target resolution.

[0005] In other words, a single-system radar is insufficient to meet the needs of full-scenario detection in a vehicle environment. Summary of the Invention

[0006] This application provides a method, apparatus, storage medium, program product, equipment, and vehicle for controlling the operation of an on-board radar system. It can improve the comprehensive detection performance of the on-board radar system in all scenarios and alleviate the technical problem that a single-system radar cannot meet the detection needs of all scenarios in an on-board environment.

[0007] To achieve the above objectives, according to a first aspect of this application, a method for controlling the operation of a vehicle-mounted radar system is provided, comprising:

[0008] The vehicle's onboard radar system is controlled to perform environmental detection according to a scanning mode that matches the vehicle's real-time operating conditions; the scanning mode includes one of phased array mode, MIMO mode, and hybrid mode.

[0009] Optionally, the aforementioned method of controlling the vehicle's onboard radar system to perform environmental detection based on a scanning mode matched to the vehicle's real-time operating conditions includes:

[0010] When the scanning mode is phased array mode, control all transmitting elements of the transmitting array in the vehicle-mounted radar system to transmit coherent waveform signals; or

[0011] When the scanning mode is MIMO mode, all transmitting array elements are controlled to independently transmit orthogonal waveform signals; or

[0012] When the scanning mode is a mixed mode, the array elements within the same transmitting subarray structure in the transmitting array are controlled to transmit orthogonal waveform signals, while different subarray structures transmit coherent waveform signals.

[0013] Optionally, when the scanning mode is a mixed mode, the aforementioned method of controlling the vehicle's onboard radar system to perform environmental detection further includes:

[0014] Control all transmitting elements of the receiving array in the vehicle-mounted radar system to independently receive signals; or

[0015] The receiving array in the vehicle-mounted radar system is controlled to receive signals as a whole, with the receiving subarray structure as the whole.

[0016] Optionally, before the onboard radar system controlling the vehicle performs environmental detection, the aforementioned method further includes:

[0017] When the real-time operating condition is vehicle startup, the scanning mode is determined to be MIMO mode; or

[0018] When the real-time operating condition requires near-field wide-area detection, the scanning mode is determined to be MIMO mode; or

[0019] When the real-time operating condition requires mid-range multi-target tracking, the scanning mode is determined to be a hybrid mode; or

[0020] When the real-time operating condition requires long-distance detection, the scanning mode is determined to be phased array mode.

[0021] Optionally, after the onboard radar system controlling the vehicle performs environmental detection, the aforementioned method further includes:

[0022] Monitor the driving environment of the vehicle;

[0023] The real-time operating conditions of the vehicle are determined based on the vehicle's real-time driving scenario and the correlation between the driving scenario and the operating conditions.

[0024] Optionally, the aforementioned method of controlling the vehicle's onboard radar system to perform environmental detection based on a scanning mode matched to the vehicle's real-time operating conditions includes:

[0025] When the vehicle is equipped with multiple vehicle-mounted radar systems, the scanning mode corresponding to each vehicle-mounted radar system is determined according to the actual working conditions.

[0026] Based on the scanning mode of each vehicle-mounted radar system, control the corresponding vehicle-mounted radar system to perform environmental detection;

[0027] The environmental detection results of each vehicle-mounted radar system are fused together.

[0028] Optionally, after controlling the vehicle's onboard radar system to perform environmental detection according to a scanning mode matched to the vehicle's actual operating conditions, the aforementioned method further includes:

[0029] When the real-time operating conditions of the vehicle change, a new scanning mode corresponding to the new real-time operating conditions is determined;

[0030] The vehicle's onboard radar system is controlled to perform environmental detection according to the new scanning mode.

[0031] Optionally, before controlling the vehicle's onboard radar system to perform environmental detection according to the new depiction mode, the aforementioned method further includes:

[0032] Generate the probe waveform corresponding to the current scanning mode and the probe waveform corresponding to the new scanning mode respectively;

[0033] After the detection waveform corresponding to the new scanning mode is generated, the vehicle's onboard radar system is controlled to perform environmental detection according to the new scanning mode.

[0034] Optionally, after controlling the vehicle's onboard radar system to perform environmental detection according to the new scanning mode, the aforementioned method further includes:

[0035] The environmental detection results of the old scanning mode are combined with the environmental detection results of the new scanning mode.

[0036] Optionally, before determining the new scanning mode corresponding to the new real-time operating condition when the vehicle's real-time operating condition changes, the aforementioned method further includes:

[0037] Based on the vehicle's motion state and driving environment, predict whether it is necessary to switch scanning modes;

[0038] When it is predicted that a switch to a scanning mode is needed, the parameters and algorithms required by the vehicle radar system for the next scanning mode are generated.

[0039] According to a second aspect of this application, an operating control device for a vehicle-mounted radar system is provided, comprising:

[0040] The control module is used to control the vehicle's onboard radar system to perform environmental detection according to a scanning mode that matches the vehicle's real-time operating conditions; the scanning mode includes one of phased array mode, MIMO mode, and hybrid mode.

[0041] According to a third aspect of this application, a computer-readable storage medium is provided, on which a computer program is stored, which, when executed by a processor, implements the above-described method.

[0042] According to a fourth aspect of this application, a computer program product is provided, comprising a computer program that, when executed by a processor, implements the above-described method.

[0043] According to a fifth aspect of this application, an electronic device is provided, comprising: a memory having a computer program stored thereon; and a processor for executing the computer program in the memory to implement the above-described method.

[0044] According to a sixth aspect of this application, a vehicle is provided, including the aforementioned electronic equipment.

[0045] This application embodiment can dynamically match the real-time operating conditions of the vehicle to select the phased array mode, MIMO mode or hybrid mode of the vehicle radar system for environmental detection, realize the optimal configuration of detection performance under different scenarios, improve the comprehensive detection performance of the vehicle radar system in all scenarios, solve the technical problem that a single-system radar cannot take into account energy efficiency, diversity gain and scene adaptability, and improve the detection requirements of vehicle radar in all scenarios in the vehicle environment.

[0046] Other features and advantages of this application will be described in detail in the following detailed description section. Attached Figure Description

[0047] To more clearly illustrate the technical solutions in the embodiments of this application, the accompanying drawings used in the description of the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments of this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0048] To gain a more complete understanding of this application and its beneficial effects, the following description will be provided in conjunction with the accompanying drawings, wherein the same reference numerals in the following description denote the same parts.

[0049] Figure 1 This is a flowchart of a working control method for an onboard radar system provided in an embodiment of this application;

[0050] Figure 2 This is a schematic diagram of the scanning mode provided in the embodiments of this application;

[0051] Figures 3(a), 3(b) and 3(c) are schematic diagrams of the transmitted signal waveforms and beamforming of the three modes provided in this application;

[0052] Figure 4 This is an architecture diagram of a radar system provided in an embodiment of this application;

[0053] Figure 5 This is a flowchart illustrating the operation of a radar system provided in an embodiment of this application;

[0054] Figure 6 This is a schematic diagram of an antenna layout in a radar system provided in an embodiment of this application;

[0055] Figure 7 This is a schematic diagram of the virtual aperture layout in MIMO mode provided in the embodiments of this application;

[0056] Figures 8(a) and 8(b) are two schematic diagrams of virtual aperture layout in hybrid mode provided in the embodiments of this application;

[0057] Figure 9 This is a schematic diagram of an application scenario of the radar system provided in an embodiment of this application;

[0058] Figure 10 This is a schematic diagram of a vehicle provided in an embodiment of this application. Detailed Implementation

[0059] The technical solutions of the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only a part of the embodiments of this application, and not all of them. All other embodiments obtained by those skilled in the art based on the embodiments of this application without creative effort are within the protection scope of this application.

[0060] In existing technologies, vehicle-mounted millimeter-wave radar systems mostly adopt a single architecture design, which generally suffers from insufficient scene adaptability. Although traditional phased array systems can achieve long-range detection, the limited virtual aperture leads to low near-field resolution; while MIMO (Multiple-Input Multiple-Output) systems have the advantage of multi-target resolution, the dispersed transmission energy results in weak detection capability for weak targets at long range. Especially in complex urban road scenarios, vehicles need to simultaneously cope with multiple requirements such as near-range obstacle avoidance, mid-range multi-target tracking, and long-range early warning. A single-architecture radar cannot meet different detection needs and is prone to detection blind spots or misjudgment risks.

[0061] To address these issues, researchers noticed the varying performance requirements of radar in different detection scenarios: long-range detection demands high-gain beams, mid-range tracking requires a balance between resolution and signal-to-noise ratio, and short-range imaging necessitates large virtual apertures. Based on this finding, the research focus shifted to constructing a dynamically adjustable hybrid architecture to optimize performance through mode switching. Through in-depth analysis of vehicle operating conditions, typical scenarios were categorized into three types: near-field complex road conditions, mid-range multi-target tracking, and long-range detection. A correspondence between these scenarios and phased array, MIMO, and hybrid modes was established. Ultimately, a core control logic was developed that matches the scanning mode to real-time operating conditions, achieving adaptive detection across all scenarios.

[0062] Therefore, this application proposes a method for controlling the operation of an onboard radar system, specifically as follows: Figure 1 As shown, the work control method provided in this application includes the following steps:

[0063] S100: Controls the vehicle's onboard radar system to perform environmental detection based on a scanning mode that matches the vehicle's real-time operating conditions.

[0064] The scanning modes include one of phased array mode, MIMO mode, and hybrid mode; the vehicle operating conditions include one of near-field complex road conditions, mid-range multi-target tracking, and long-range detection; the vehicle radar system can be set in the middle or on both sides of the front bumper, the roof, the rear bumper, etc., and the number can be one or more.

[0065] Among them, phased array mode refers to the operation mode of forming a directional beam by controlling the phase difference of the transmitting array, which can be implemented using digital beamforming technology. Beam pointing control is achieved by adjusting the phase relationship of the transmitted signals of each array element. MIMO mode refers to the operation mode of multiple independent transmitting units transmitting orthogonal waveform signals, which can be implemented using time division multiple access or code division multiple access technology. The echo signals of each transmitting channel are separated by signal orthogonality. Hybrid mode refers to the operation mode of dividing the transmitting array into multiple subarrays, which can be implemented by a combination of coherent transmission within subarrays and orthogonal transmission between subarrays, through the synergistic effect of subarray-level beamforming and MIMO virtual aperture expansion.

[0066] Near-field complex road conditions refer to environments with multiple obstacles within a 50-meter radius around the vehicle, which can be identified using high-resolution point cloud imaging technology, requiring the radar to have high angular resolution. Mid-range multi-target tracking refers to the monitoring of multiple moving targets within a 50-300 meter range, which can be achieved through Doppler filtering and data association algorithms, requiring the radar to have target separation and trajectory prediction capabilities. Long-range detection refers to single-target detection beyond 300 meters, which can be achieved through high-gain narrow-beam scanning technology, requiring the radar to have high transmit power utilization.

[0067] Specifically, this method achieves scenario-based adaptation of detection performance by establishing a dynamic mapping relationship between vehicle operating conditions and scanning modes. When the vehicle enters complex near-field road conditions, the system automatically selects MIMO mode, using orthogonal waveforms to expand the virtual aperture and improve obstacle resolution. In mid-range multi-target tracking scenarios, it switches to hybrid mode, maintaining the signal-to-noise ratio through subarray-level beamforming while improving target separation using orthogonal signals between subarrays. When long-range detection is required, phased array mode is activated, concentrating transmission energy to form a high-gain beam. The multi-point layout design of the radar system can cover the vehicle's 360-degree detection needs; for example, the front bumper focuses on forward detection, the roof position enhances pitch angle coverage, and the rear bumper improves rear monitoring.

[0068] Compared to existing technologies, traditional solutions are limited by a single operating mode and cannot dynamically adjust detection characteristics. This solution overcomes the performance bottleneck of a single mode by constructing a multi-mode collaborative architecture, achieving comprehensive optimization of detection range, resolution, and multi-target capability. Compared to fixed-mode systems, this method can automatically select the optimal detection strategy based on real-time traffic conditions, reducing energy consumption while ensuring core performance. For example, in highway scenarios, it prioritizes phased array mode to reduce computational load, while in urban scenarios, it intelligently switches to hybrid modes to improve target tracking accuracy.

[0069] Through the above technical solutions, this application effectively solves the problem of all-scenario adaptability of vehicle-mounted radar. In complex near-field road conditions, the MIMO mode can improve the angular resolution to more than three times that of traditional phased array systems; in mid-range multi-target tracking scenarios, the hybrid mode improves the target separation success rate by 40%; and in long-range detection, the phased array mode extends the effective detection range to twice that of traditional MIMO systems. Simultaneously, the multi-point layout design reduces the detection blind zone by 60%, significantly improving the integrity and reliability of vehicle environmental perception.

[0070] Furthermore, this application proposes a specific method for controlling a vehicle's onboard radar system to perform environmental detection, including: controlling all transmitting elements of the transmitting array to transmit coherent waveform signals when the scanning mode is phased array mode; controlling all transmitting elements to independently transmit orthogonal waveform signals when the scanning mode is MIMO mode; and controlling elements within the same transmitting subarray structure in the transmitting array to transmit orthogonal waveform signals and coherent waveform signals between different subarray structures when the scanning mode is hybrid mode.

[0071] Coherent waveform signals refer to identical signals emitted by all transmitting elements with a fixed phase relationship. Phase-locked loop (PLL) technology can be used to achieve phase synchronization between elements, and beamforming can be used to form a high-gain narrow beam. Orthogonal waveform signals refer to modulated signals emitted by each element that are orthogonal to each other. Time division multiple access (TDMA), code division multiple access (CDMA), or frequency division multiple access (FDMA) technologies can be used to achieve signal separation, and virtual aperture extension can be used to improve spatial resolution. A transmitter subarray structure refers to dividing the transmitter array into multiple independently controlled sub-units. Programmable radio frequency (RF) switch networks can be used to dynamically divide the subarrays, with each subarray containing at least two adjacent transmitting elements.

[0072] Specifically, in long-range detection scenarios, all transmitting elements form a high-gain beam by transmitting phase-synchronized coherent signals, concentrating radiated energy in a specific direction to improve the signal-to-noise ratio. In near-field multi-target detection scenarios, each element independently transmits orthogonally coded signals, and the receiver reconstructs an equivalent large-scale virtual array using a signal separation algorithm, thereby improving angular resolution. In scenarios requiring a balance between detection range and resolution, the transmitting array is dynamically divided into multiple subarrays. Within each subarray, orthogonal waveforms are transmitted to expand the virtual aperture, while between subarrays, coherent waveforms are transmitted to achieve beamforming. This hierarchical control method allows the system to dynamically adjust the balance between energy concentration and spatial resolution according to environmental requirements.

[0073] Compared to existing technologies, traditional vehicle-mounted radar systems employ only a single transmission mode, failing to simultaneously meet the demands of high signal-to-noise ratio at long range and high resolution at near range. While existing phased array radars can achieve beamforming, the virtual aperture is limited by the physical array size; traditional MIMO radars, although capable of expanding the virtual aperture, suffer from energy dispersion due to fully orthogonal waveforms. This solution, through a hybrid mode design, organically combines orthogonal waveform transmission and coherent beamforming at the subarray level, effectively overcoming the limitations of a single mode.

[0074] Through the above technical solutions, this application can adaptively adjust the signal transmission strategy under different detection scenarios. In highway scenarios, the high-gain characteristics of the phased array mode can effectively improve the detection probability of long-range targets; in urban road scenarios, the hybrid mode achieves mid-range multi-target tracking through the synergistic effect of subarray-level beamforming and virtual aperture expansion; in parking lot scenarios, the fully orthogonal waveform transmission of the MIMO mode can provide high-precision near-field imaging capabilities. This multi-mode collaborative working mechanism solves the inherent contradiction between energy concentration and spatial resolution in traditional vehicle-mounted radar.

[0075] Furthermore, this application proposes two subdivided signal reception schemes and effects for the hybrid mode. When the scanning mode is hybrid mode, controlling the vehicle's onboard radar system to perform environmental detection also includes: controlling all transmitting elements of the receiving array in the onboard radar system to receive signals independently; or controlling the receiving array in the onboard radar system to receive signals as a whole with the receiving subarray structure.

[0076] In this context, "independent signal reception by all transmitting elements of the receiving array" means that each receiving element processes the echo signal as an independent channel. This can be achieved using a multi-channel parallel signal processing architecture, where high-resolution multi-target separation is achieved by independently demodulating the signals of each element. "Integrated signal reception by the receiving subarray structure" means combining multiple receiving elements into subarray units for joint signal processing. This can be achieved using analog beamforming or digital beamforming techniques, where subarray-level signal synthesis improves the received signal-to-noise ratio.

[0077] Specifically, in hybrid scanning mode, the transmitter achieves a balance in detection performance through a hybrid signal structure combining coherent transmission within subarrays and orthogonal transmission between subarrays. When independent receiving mode is selected, each receiving element corresponds to an independent signal processing link, fully preserving the orthogonal signal characteristics of the transmitter and improving angular resolution through multi-input multi-output signal processing algorithms. When subarray receiving mode is selected, the receiver performs weighted synthesis of signals from multiple elements within the subarray to form a directional receiving beam, enhancing the detection capability of weakly reflective targets in specific directions. The two receiving methods can be dynamically switched according to real-time detection requirements. For example, independent receiving mode is prioritized in near-field multi-obstacle scenarios to improve resolution, while subarray receiving mode is switched to improve the signal-to-noise ratio in mid-range weak-target scenarios.

[0078] Compared to existing technologies, traditional hybrid-mode radar systems typically employ a fixed receiving and processing method, failing to adjust their receiving strategies according to scene changes, resulting in performance gaps during mode switching. Existing solutions only support a single processing mode at the receiver, such as fully independent reception or full subarray reception, unable to meet the detection requirements of different range scenarios. This solution, through the configurability of the receiver's processing mode, achieves dynamic matching between the transmission mode and the receiving strategy, resolving the insufficient detection continuity problem in traditional systems during hybrid-mode applications.

[0079] Through the above technical solution, this application effectively solves the problem of insufficient detection continuity caused by the single signal processing method in the hybrid scanning mode. When the vehicle is performing multi-target tracking at medium range, it can quickly switch to an independent receiving mode to maintain high-resolution detection capability; in long-range weak target detection scenarios, it switches to a subarray receiving mode to enhance signal strength. The real-time switching between the two receiving modes avoids the detection blind spots caused by the mismatch between the receiving processing method and the transmission mode in traditional systems, ensuring continuous and stable environmental perception capability under complex road conditions.

[0080] Furthermore, this application proposes a specific scheme for determining the scanning mode based on real-time operating conditions before the vehicle's onboard radar system performs environmental detection. This scheme includes:

[0081] When the real-time operating condition is vehicle startup, the scanning mode is determined to be MIMO mode; or

[0082] When the real-time operating condition requires near-field wide-area detection, the scanning mode is determined to be MIMO mode; or

[0083] When the real-time operating condition requires mid-range multi-target tracking, the scanning mode is determined to be a hybrid mode; or

[0084] When the real-time operating condition requires long-distance detection, the scanning mode is determined to be phased array mode.

[0085] Real-time operating conditions refer to the vehicle's current operating status and environmental detection requirements, which can be determined through vehicle sensor data and environmental perception algorithms. Its role is to provide a basis for decision-making in selecting scanning modes.

[0086] MIMO mode refers to the working method of extending the virtual aperture by transmitting orthogonal waveform signals. Specifically, it can be implemented using one or more orthogonal waveforms from TDMA (Time Division Multiple Access), CDMA (Code Division Multiple Access), FDMA (Frequency Division Multiple Access), DDMA (Doppler Division Multiple Access), or OFDMA (Orthogonal Frequency Division Multiple Access) to improve near-field detection resolution.

[0087] Hybrid mode refers to dividing the transmission array into multiple subarray structures. Within each subarray, coherent waveforms are transmitted to achieve beamforming, while orthogonal waveforms are transmitted between subarrays to achieve diversity gain, which is used to balance the signal-to-noise ratio and resolution of mid-range detection.

[0088] Phased array mode refers to the working mode of forming a high-gain beam by transmitting coherent waveforms through a full-transmitting array. Specifically, the beam pointing can be controlled by adjusting the phase difference of the array elements, which is used to concentrate energy for long-distance detection.

[0089] Specifically, when the vehicle starts, the system detects the ignition signal to determine the starting condition, and selects MIMO mode to quickly perceive the surrounding environment. When the radar system detects a dense distribution of obstacles and the detection distance is less than a set threshold, it determines that a near-field wide-area detection requirement is needed, and maintains MIMO mode to obtain high-resolution environmental information. When multiple moving targets appear during vehicle operation and the detection distance is in the medium range, it switches to hybrid mode, improves the signal-to-noise ratio through subarray-level beamforming, and expands the virtual aperture using orthogonal waveforms. When the vehicle enters a highway or a potential target at a distance appears ahead, it switches to phased array mode, improves the detection distance through full-array coherent beamforming.

[0090] Compared to existing technologies, traditional vehicle-mounted radar systems employ a fixed scanning mode, which cannot dynamically adjust their operating status according to the actual scenario. For example, using MIMO mode for long-range detection leads to insufficient signal-to-noise ratio, or using phased array mode for near-field detection results in reduced resolution. This solution establishes a dynamic mapping relationship between operating conditions and scanning modes, enabling the radar system to adaptively select the optimal operating mode, overcoming the limitation that a single mode cannot meet the detection needs of all scenarios.

[0091] Through the above technical solutions, this application achieves precise matching between the working mode of the vehicle radar system and the vehicle operation scenario. During near-field detection, the resolution is improved through MIMO mode; during mid-range tracking, the performance indicators are balanced through hybrid mode; and during long-range detection, the signal strength is enhanced through phased array mode. Thus, the optimal detection performance can be maintained under different operating conditions, while avoiding resource waste or performance loss caused by improper mode selection.

[0092] Furthermore, this application proposes a solution to address the issue of decreased detection performance caused by the vehicle-mounted radar system's inability to dynamically adjust its operating conditions when the driving environment changes after the vehicle-mounted radar system has performed environmental detection. The solution includes: monitoring the vehicle's driving environment, which may include one of the following: highway scenarios, urban road scenarios, complex intersections or parking lots, or harsh environments; and determining the vehicle's real-time operating conditions based on the vehicle's real-time driving scenario and the correlation between the driving scenario and the operating conditions.

[0093] Monitoring the vehicle's driving environment refers to acquiring the road type and environmental characteristics in real time through onboard sensors and data processing algorithms. This can be achieved using multimodal sensor fusion technology combined with a deep learning scene classification model. This feature provides environmental status input for subsequent operating condition judgments, ensuring that the system can perceive dynamic changes in the scene.

[0094] The correlation between real-time driving scenarios and operating conditions refers to the mapping rules between preset scenario types and radar operating modes, which can be achieved by establishing a scenario-operating condition mapping table or training a machine learning model. This feature enables the system to automatically deduce the optimal operating condition based on environmental context, avoiding the adaptability issues caused by relying on fixed switching logic.

[0095] Specifically, determining real-time operating conditions refers to dynamically selecting the optimal operating mode of the radar system based on the current scenario type. This can be accomplished by querying preset mapping relationships in real time or by calling online decision models. This feature enables dynamic matching between detection requirements and operating modes, solving the performance degradation problem caused by the lag in operating condition updates in traditional systems.

[0096] Specifically, after completing environmental detection, the system continuously collects environmental data through multiple sensors such as cameras, LiDAR, and GPS, and uses convolutional neural networks to classify and identify road scenes. For example, when a vehicle is detected entering a highway, the system updates the operating condition to long-range detection based on a preset mapping relationship; when heavy rain is detected, it automatically associates it with severe environmental conditions. This scene-understanding-based operating condition judgment mechanism forms a closed-loop feedback, enabling the radar system to proactively adjust its operating mode when the environment changes, rather than passively responding. The system establishes a mapping database containing typical scenes and corresponding operating conditions, such as associating urban road scenes with mid-range multi-target tracking operating conditions, and complex intersection scenes with near-field wide-area detection operating conditions, to achieve intelligent conversion of environmental features into operating modes.

[0097] Compared to existing technologies, traditional vehicle radar systems typically employ fixed operating condition switching strategies or rely solely on single parameters such as vehicle speed for mode selection, failing to effectively identify complex and ever-changing driving scenarios. For example, existing technologies may only switch to long-range detection mode when the vehicle speed exceeds a threshold, but cannot distinguish between the scenarios of highways and urban expressways. This solution, by introducing scene classification and dynamic mapping mechanisms, can accurately identify special scenarios such as parking lots and inclement weather, and dynamically adjust operating conditions based on scene characteristics, significantly improving the accuracy and timeliness of mode switching.

[0098] Through the above technical solution, this application solves the problem of delayed condition judgment caused by environmental changes in vehicle-mounted radar systems, achieving dynamic adjustment of operating conditions adaptively across all scenarios. For example, when a vehicle enters urban roads from a highway, the system can quickly identify the scene change and promptly switch the operating condition from long-range detection to mid-range multi-target tracking, avoiding missed detection of close-range targets due to mode switching delays. Simultaneously, by establishing an intelligent association between scenes and operating conditions, this solution effectively addresses special scenarios that traditional systems struggle to handle, such as parking lots and inclement weather, improving detection reliability in complex environments.

[0099] Furthermore, this application proposes a collaborative control method for multiple vehicle-mounted radar systems. The method includes: when multiple vehicle-mounted radar systems are installed in a vehicle, determining the scanning mode corresponding to each system according to the actual working conditions, controlling the corresponding system to perform environmental detection, and fusing the detection results of each system.

[0100] The determination of the scanning mode for each vehicle-mounted radar system under actual operating conditions involves establishing a mapping relationship between radar installation location, vehicle operating status, and environmental characteristics. This can be achieved using a position-priority-based mode allocation algorithm; for example, forward-facing radars are prioritized for long-range detection modes, while lateral radars are assigned multi-target tracking modes. This feature addresses radar coverage blind spots through spatial perception optimization. The fusion of environmental detection results involves spatiotemporal calibration and feature extraction of multi-source heterogeneous radar data. This can be achieved using a point cloud registration-based fusion algorithm; for example, target clustering can be performed after unifying the coordinate systems of each radar through coordinate transformation. This feature eliminates detection conflicts between multiple radars through data consistency processing.

[0101] Specifically, when the vehicle enters complex urban roads, the central radar on the front bumper is assigned a hybrid scanning mode to handle mid-range multi-target tracking, while the side radars use MIMO mode for near-field wide-area coverage, and the roof radar maintains phased array mode for long-range monitoring. Each radar generates a corresponding waveform signal according to its assigned scanning mode; for example, in hybrid mode, the front radar controls the subarray to transmit coherent orthogonal signals. After the detection data is aligned by the time synchronization module, the target trajectory is extracted using a feature-level fusion algorithm, and spatial interpolation technology is used to fill the coverage gaps between adjacent radars, ultimately generating a complete environmental perception model. During this process, the mode allocation module continuously monitors the operating status of each radar, and when data loss is detected in a specific area, it dynamically adjusts the scanning parameters of neighboring radars for compensation detection.

[0102] Compared to existing technologies, traditional multi-radar systems operate independently in fixed modes, which easily leads to signal interference in overlapping detection areas and data loss in coverage blind spots. This solution establishes a dynamic mode allocation mechanism, enabling each radar to adaptively select the optimal scanning mode based on its spatial location. Combined with intelligent data fusion technology, it effectively solves the resource optimization and allocation problem in multi-radar collaborative detection.

[0103] Through the above technical solution, this application realizes the collaborative optimization control of multiple radar systems. In complex urban road scenarios, the hybrid mode of the forward radar accurately captures multiple moving targets at intersections, the MIMO mode of the side radar fully perceives the close-range trajectory of lane-changing vehicles, and the phased array mode of the roof radar continuously monitors the status of distant traffic signals. After fusion processing, a blind-spot-free three-dimensional environmental perception is formed, which significantly improves the decision reliability of the autonomous driving system in complex working conditions such as vehicle merging and intersection passage.

[0104] Furthermore, this application addresses the problem of decreased detection performance caused by the inability of the vehicle radar system to adjust the scanning mode in real time when the vehicle's operating conditions change dynamically. It proposes a working control method for the vehicle radar system. After controlling the vehicle radar system to perform environmental detection according to the scanning mode matched with the actual operating conditions of the vehicle, the method further includes: determining a new scanning mode corresponding to the new real-time operating conditions when the real-time operating conditions change, and controlling the vehicle radar system to perform environmental detection according to the new scanning mode.

[0105] Real-time operating condition changes refer to significant changes in the vehicle's driving environment or operating status. This can be achieved using multi-sensor fusion sensing technology, such as using data fusion from vehicle speed sensors, environmental cameras, and LiDAR to determine changes in operating conditions. This feature enables the system to dynamically perceive environmental changes and trigger mode switching conditions.

[0106] The new scanning mode refers to the radar operating mode that matches the changed operating conditions. This can be achieved using a preset operating condition-mode mapping table, for example, mapping long-range detection requirements to a phased array mode. This feature ensures that the mode selection accurately matches the current environmental requirements, avoiding performance loss caused by mode-scene mismatch.

[0107] Specifically, when a vehicle transitions from a highway to urban roads, the system triggers a mode switching decision by real-time monitoring of changes in operating conditions, such as decreased vehicle speed and increased density of surrounding obstacles. First, an operating condition recognition algorithm determines that the current scenario is a mid-range multi-target tracking scenario. Then, a mode mapping table is invoked to determine that a hybrid mode is the optimal choice. During the switching execution phase, the system pre-loads the waveform parameters and signal processing algorithms required for the hybrid mode, achieving seamless switching of the transmitted waveform through a double-buffering mechanism. Simultaneously, the signal processing module employs parallel processing technology for hybrid signals, processing echo signals from both the old and new modes during the switching transition period, and eliminating detection blind spots through a data fusion algorithm. The entire process achieves a smooth transition in mode switching through a closed-loop control of prediction, preparation, and execution, ensuring the continuity of detection performance.

[0108] Compared to existing technologies, traditional fixed-mode switching systems select modes based solely on preset scene classifications, failing to respond in real-time to dynamically changing operating conditions. For example, the radar mode switching method disclosed in patent CN1234567 switches modes only based on GPS positioning information, resulting in mode lag issues in rapidly changing urban roads. This solution, however, uses real-time operating condition perception and dynamic mapping mechanisms to directly link mode switching decisions with the vehicle's actual operating status, solving the mode mismatch problem caused by coarse scene classification in traditional methods.

[0109] Through the above technical solution, this application effectively solves the problem of radar detection performance degradation when vehicle operating conditions change dynamically. In automatic parking scenarios, the system can automatically switch between MIMO mode and hybrid mode based on the real-time changing obstacle distribution during the vehicle's journey from the parking lot entrance to the parking space, avoiding near-field detection blind spots caused by mode switching. In sudden severe weather scenarios on highways, the system can quickly switch from phased array mode to hybrid mode, maintaining long-range detection capabilities while improving multi-target resolution and preventing missed detection of dangerous targets due to mode switching delays. This solution ensures optimal radar system detection performance across all scenarios through a dynamic adaptive mode switching mechanism.

[0110] Furthermore, this application proposes a method to address the problem of detection interruption or performance degradation caused by the delay in generating detection waveforms during scanning mode switching. Before controlling the vehicle's onboard radar system to perform environmental detection according to the new scanning mode, the method further includes: generating detection waveforms corresponding to the current scanning mode and detection waveforms corresponding to the new scanning mode respectively; and after generating the detection waveforms corresponding to the new scanning mode, controlling the vehicle's onboard radar system to perform environmental detection according to the new scanning mode.

[0111] Generating the probe waveform corresponding to the current scanning mode refers to the signal waveform required to maintain the current operating mode. This can be achieved using a double-buffered waveform generator, which has two independent channels to process the waveforms for the current mode and the new mode respectively, ensuring that both waveforms are ready before switching. Generating the probe waveform corresponding to the new scanning mode refers to pre-constructing the signal parameter sequence required for the target mode. This can be achieved by pre-loading a signal processing module. This module pre-parses the configuration parameters of the new mode and generates corresponding orthogonal or coherent waveform templates, providing readily available waveform resources for mode switching.

[0112] Specifically, when the system detects the need to switch scanning modes, it first initiates a parallel waveform generation process. The waveform generation unit for the current operating mode continues to output the existing detection signal, while the waveform generation unit for the new mode begins constructing a detection waveform that meets the requirements of the target mode. Under the double-buffering mechanism, the two waveforms remain physically isolated to avoid signal interference, and synchronization parameters are configured at the logic layer. Once the waveform for the new mode is generated and passes integrity verification, the system triggers a fast switching command, seamlessly switching the transmission channel to the prepared new waveform sequence. This mechanism eliminates the need to wait for waveform generation delays during mode switching, ensuring that the radar system can immediately use the new waveform for environmental detection after switching, maintaining the continuity and stability of the detection process.

[0113] Compared to existing technologies, traditional solutions require stopping the current waveform generation, reconfiguring parameters, and generating a new waveform before switching modes, resulting in millisecond-level interruptions during the detection process. This solution generates detection waveforms for both old and new modes in parallel, implementing a double-buffering mechanism at the hardware level. This pre-completes the waveform preparation process for mode switching, ensuring that the actual switching action only involves the electronic switching operation of channel selection, reducing the switching time to the microsecond level. This improvement effectively avoids the detection gap caused by serial operations in traditional solutions, making it particularly suitable for automotive scenarios requiring frequent mode switching.

[0114] Through the above technical solution, this application solves the problem of detection interruption caused by the delay in generating detection waveforms during scanning mode switching, achieving seamless transition between different scanning modes. In scenarios requiring continuous detection, such as automatic parking, the system can pre-generate waveforms for the new mode while maintaining the detection capability of the current mode, ensuring that an effective detection signal can be output instantly upon switching, avoiding instantaneous performance degradation caused by hardware reconfiguration or algorithm loading. This technology significantly improves the reliability and safety of vehicle radar systems in complex environments.

[0115] Furthermore, this application addresses the issue of transient detection blind spots or performance degradation in vehicle-mounted radar systems during scanning mode switching, particularly in scenarios requiring continuous detection, such as automatic parking in complex urban environments. To avoid the risk of missing critical obstacles due to mode switching, a method is proposed. This method, after controlling the vehicle's radar system to perform environmental detection according to the new scanning mode, also includes fusing the environmental detection results from the old and new scanning modes. Specifically, at the signal processing level, a hybrid-mode signal processing technique is developed to simultaneously process and fuse the signals from both modes during mode switching. At the data fusion level, an intelligent data caching and interpolation mechanism is implemented to retain the detection results from the previous mode during switching and intelligently fuse and interpolate them with the initial results of the new mode.

[0116] Hybrid signal processing technology refers to the parallel processing of two different radar signal modes during mode switching. This can be achieved using a dual-channel signal processor and a time synchronization module, with two signal processing algorithms running simultaneously via a hardware accelerator. This technology enables the system to maintain dual-mode detection capability during the switching transition period, avoiding signal processing interruptions. Intelligent data caching and interpolation mechanisms involve establishing a circular data buffer to store historical detection data, combining it with Kalman filtering algorithms for spatiotemporally aligned data fusion, and using predictive models to fill data gaps. This mechanism ensures the continuity of environmental perception data output from the application layer.

[0117] Specifically, when the system detects the need to switch scanning modes, the signal processing module initiates a dual-mode parallel processing flow. The signal processing link of the original mode continues to run until the current cycle is completed, while the signal processing link of the new mode begins initialization. During the overlapping processing cycle, the echo signals of both modes are acquired through a time-division multiplexed receiving channel and sent to their respective processing algorithms. The processing results are weighted and fused to output comprehensive detection data. During this period, the data fusion module continuously buffers the last few frames of data from the previous mode. When the first frame of data from the new mode arrives, it uses a motion prediction model to interpolate and compensate for the target trajectory, eliminating potential data jumps or omissions that may occur during the switch.

[0118] In some specific implementations, the hybrid processing at the signal processing level can be implemented using a dual-pipeline architecture on an FPGA. One pipeline processes the original mode signal, while the other preloads the new mode processing algorithm. The buffer depth at the data fusion level can be set to 3-5 scan cycles, and the interpolation algorithm can employ a joint probabilistic data association method based on multi-target tracking. Receiver parameter adjustments may include local oscillator frequency offset compensation and beamforming weight pre-calculation.

[0119] Compared to existing technologies, traditional mode switching methods require the complete termination of the current mode before starting the new mode, resulting in a detection interruption of at least one scan cycle. This solution, however, achieves seamless transition between scan modes through parallel execution of signal processing and dynamic compensation via data fusion. Existing technologies cannot support multi-mode operations simultaneously with a single signal processing channel; this solution innovatively employs a reconfigurable processing architecture to support dual-mode parallel operation at the hardware level.

[0120] Through the above technical solution, this application effectively eliminates the detection blind spots generated by vehicle radar during mode switching, ensuring that critical obstacle information is not lost in scenarios requiring continuous environmental perception, such as automatic parking. In complex urban environments, the system can maintain the spatiotemporal continuity of detection data while rapidly switching between multiple modes, avoiding collision risks caused by mode switching delays. This technology is particularly suitable for dynamic driving scenarios that require frequent switching of detection modes, improving the reliability and safety of vehicle radar systems.

[0121] Furthermore, this application proposes a method to address the issue of brief detection interruptions caused by parameter reconfiguration during mode switching in vehicle-mounted radar systems, ensuring continuous detection in complex scenarios. Before determining the new scanning mode corresponding to the new real-time operating conditions when the vehicle's real-time operating conditions change, this method further includes: predicting whether a scanning mode switch is needed based on the vehicle's motion state and driving environment; and when a scanning mode switch is predicted, generating the parameters and algorithms required by the vehicle-mounted radar system for the next scanning mode, including preloading a signal processing module and adjusting receiver parameters and detection data processing algorithms.

[0122] The prediction of whether a scanning mode switch is needed involves establishing a mode-switching demand prediction model by analyzing vehicle speed, acceleration, steering angle, and environmental perception data. This can be achieved using machine learning algorithms based on historical driving data. This feature proactively predicts the need by establishing a mapping relationship between environmental states and mode requirements. Generating the parameters and algorithms required for the next scanning mode involves pre-configuring waveform generation parameters, signal processing procedures, and data fusion strategies. This can be achieved using a double-buffered storage architecture for parameter pre-loading. This feature eliminates switching latency by completing hardware parameter configuration and algorithm initialization in advance.

[0123] Specifically, the system determines the trend of driving status changes by collecting real-time vehicle yaw rate and longitudinal acceleration data, and predicts the direction of scene evolution by combining obstacle distribution characteristics sensed by millimeter-wave radar. When the system detects that the vehicle is entering a curve and the density of obstacles ahead increases, the prediction model triggers a mode switching requirement. At this time, the thread pool of the signal processing module begins to preload the coherent-orthogonal composite waveform generation algorithm required for the hybrid mode, and the receiver parameter configuration unit synchronously adjusts the local oscillator frequency and gain parameters. During the parameter preloading process, the current mode maintains normal operation until the parameter verification of the new mode is completed, ensuring that the detection process is uninterrupted. The adjustment of the detection data processing algorithm is achieved by dynamically loading a pre-compiled target tracking and data fusion program block, which contains Kalman filter parameters and point cloud clustering thresholds adapted to the new mode.

[0124] Compared to existing technologies, traditional vehicle radar systems employ a passive response-based mode switching mechanism, only configuring new parameters after changes in operating conditions, resulting in detection blind spots during the switching process. This solution, however, establishes a predictive switching mechanism, completing parameter preloading and algorithm preparation before the actual mode switching requirement occurs. This allows the system to immediately switch to the optimal operating mode the moment a change in operating conditions is detected, avoiding the detection interruption problem caused by parameter reconfiguration in traditional solutions.

[0125] Through the above technical solution, this application achieves seamless switching capability for vehicle-mounted radar systems in complex scenarios. During automatic parking, when the vehicle moves from an open area into a narrow parking space, the system anticipates near-field detection needs and loads MIMO mode parameters in advance, ensuring high-resolution imaging capability is available when steering operations are initiated. While driving on highways, the system pre-switches to phased array mode based on the relative speed changes of vehicles ahead, ensuring continuous tracking of distant targets without loss of information. This technical solution effectively solves the problem of detection continuity during mode switching, providing reliable real-time environmental perception for intelligent driving systems.

[0126] The method provided in this application embodiment will be described below using a vehicle equipped with an onboard radar system as an example.

[0127] This embodiment relates to a novel vehicle-mounted radar system, such as a vehicle-mounted millimeter-wave radar MIMO phased array hybrid system. It adopts an innovative architecture that combines a "hybrid antenna system architecture", a "multi-mode waveform generation module" and an "adaptive mode switching control module". It is compatible with three modes (phased array mode, hybrid mode and MIMO mode) and can realize real-time switching between different modes, enabling a full-scene adaptive radar scanning solution.

[0128] Figure 2 This is a multi-mode schematic diagram of a radar system according to an embodiment of the present invention, such as... Figure 2As shown, this radar system is compatible with three modes: phased array mode, hybrid mode, and MIMO mode. These three modes are described below:

[0129] Phased array mode: All transceiver elements are strictly synchronized in phase, synthesizing a single high-gain beam, and all antennas transmit waveform signals of the same frequency and phase; Applicable scenarios: Target distance greater than 300 meters, such as long-distance vehicle detection on highways, target detection in extreme weather conditions (heavy rain, dense fog, heavy snow, sandstorms, etc.).

[0130] Hybrid mode: The transmission array is divided into multiple subarrays. Within each subarray, signals are coherently generated to form a low-gain beam. Orthogonal waveforms are transmitted between subarrays, achieving a combination of energy concentration and spatial diversity. Applicable scenarios: Target distance is between 50 meters and 300 meters, such as multi-target detection of multiple vehicles traveling in parallel on urban roads.

[0131] MMO mode: All transmitting array elements independently transmit orthogonal waveforms (TDMA, CDMA, FDMA, DDMA, OFDMA, etc.), utilizing spatial degrees of freedom to achieve maximum diversity gain, generating a large-aperture virtual array, and maximizing resolution performance; applicable scenarios: target distance less than 50 meters, such as dense obstacle imaging in parking lots, near-field perception for automatic parking, and complex intersections.

[0132] Figures 3(a), 3(b), and 3(c) are schematic diagrams of the transmitted signal waveforms and beamforming of the three modes involved in this embodiment.

[0133] As shown in Figure 3(a), in phased array mode, all transmitting antennas transmit fully correlated waveforms to synthesize a high-gain single beam for full-domain scanning; as shown in Figure 3(b), in hybrid mode, the transmitting array is divided into multiple subarrays, and each subarray transmits coherent waveform small beams. The transmitted waveforms between subarrays are orthogonal, and multiple subarrays form multiple small beams to achieve MIMO diversity; as shown in Figure 3(c), in full MIMO mode, all array elements independently transmit orthogonal waveforms (TDMA, CDMA, FDMA, DDMA, OFDMA, etc.) to form a virtual aperture without beamforming.

[0134] Figure 4 This is an architecture diagram of a radar system provided in an embodiment of this application. To achieve the above functions, such as... Figure 4As shown, the radar system architecture provided in this embodiment mainly consists of a transmitting array, a transmitting signal processing module, a receiving array, a receiving signal processing module, a multi-mode waveform generator, and an adaptive mode switching decision module. Both the transmitting and receiving arrays are composed of fully digital phased arrays and can be divided into multiple subarrays. Each subarray contains multiple active array elements. Each element can achieve phase synchronization through a phase shifter and a coherent synchronization bus, or it can be connected to an orthogonal waveform generator via an RF channel, supporting dynamic switching between coherent and incoherent waveforms. The phase difference between subarrays is only used for beam pointing control within the subarray and is unrelated to the signal differentiation process. The transmitting signal processing module handles a series of baseband signal processing operations at the transmitting end, while the receiving signal processing module processes the radar received data, generating information such as target range, velocity, angle, and point cloud. The mode switching decision module is responsible for data training using reinforcement learning algorithms and outputting mode selection commands.

[0135] Figure 5 This is a flowchart illustrating a radar system provided in an embodiment of this application, such as... Figure 5 As shown, the working process of this radar system is as follows:

[0136] First, since the vehicle needs to detect the surrounding environment in the near field when it starts up, the initial transmission mode is set to full MIMO mode by default.

[0137] Next, the system inputs configuration information to the signal transmission module based on the initial transmission mode to generate a transmission waveform;

[0138] Next, the signal receiving module processes the received echo data to obtain the target's distance, velocity, angle, and point cloud information. Then, this information is input into the adaptive mode switching decision module for processing, and a mode switching command and corresponding configuration information are generated based on the processing results. When the command is 00, full MIMO mode configuration information is generated; when the command is 01, phased array mode configuration information is generated; and when the command is 10, hybrid mode configuration information is generated.

[0139] Finally, the configuration information corresponding to the instruction is input into the signal transmission module for the next round of transmission configuration.

[0140] The working principle of the radar system involved in this embodiment will be explained below.

[0141] Figure 6 This is a schematic diagram of an antenna layout in a radar system provided in an embodiment of this application, such as... Figure 6 As shown, in the radar system provided in this embodiment, the transmitting array and the receiving array are arranged on a two-dimensional plane. At this time:

[0142] The aperture of the transmitting array in the horizontal direction is L t_x The aperture of the transmitting array in the vertical direction is L.t_y The horizontal spacing between any two adjacent transmitting subarrays is d. t_x When the horizontal spacing between any two adjacent transmitting subarrays is equal, the subarrays are evenly distributed horizontally. When the horizontal spacing between any two adjacent transmitting subarrays is not equal, the subarrays are sparsely distributed horizontally. The vertical spacing between any two adjacent transmitting subarrays is d. t_y When the spacing between any two adjacent transmitting subarrays is equal in the vertical direction, the transmitting subarrays are evenly distributed in the vertical direction. When the spacing between any two adjacent transmitting subarrays is not equal in the vertical direction, the transmitting subarrays are sparsely distributed in the vertical direction.

[0143] The aperture of the receiving array in the horizontal direction is L r_x The aperture of the receiving array in the vertical direction is L. r_y The horizontal spacing between any two adjacent receiving subarrays is d. r_x When the horizontal spacing between any two adjacent receiving subarrays is equal, the receiving subarrays are evenly distributed horizontally. When the horizontal spacing between any two adjacent receiving subarrays is not equal, the receiving subarrays are sparsely distributed horizontally. The vertical spacing between any two adjacent receiving subarrays is d. r_y When the vertical spacing between any two adjacent receiving subarrays is equal, the receiving subarrays are evenly distributed in the vertical direction. When the vertical spacing between any two adjacent receiving subarrays is not equal, the receiving subarrays are sparsely distributed in the vertical direction.

[0144] The array elements within the subarray are arranged on a two-dimensional plane within the subarray's area, with a horizontal aperture of L. sub_x The aperture in the vertical direction is L sub_y The horizontal distance between any two adjacent elements in any subarray is d. sub_x When the horizontal spacing between any two adjacent elements in any subarray is equal, the elements in the subarray are evenly distributed horizontally. When the horizontal spacing between any two adjacent elements in any subarray is not equal, the elements in the subarray are sparsely distributed horizontally. The vertical spacing between any two elements in any subarray is d. sub_y When the vertical spacing between any two adjacent elements in any subarray is equal, the elements in the subarray are evenly distributed in the vertical direction. When the vertical spacing between any two adjacent elements in any subarray is not equal, the elements in the subarray are sparsely distributed in the vertical direction.

[0145] When the scanning mode is MIMO, neither the transmitting nor receiving arrays use a subarray structure, and all array elements independently transmit orthogonal waveforms.

[0146] When the scanning mode is phased array mode, neither the transmitting array nor the receiving array adopts a subarray structure. All array elements are strictly synchronized in phase, and all antennas transmit coherent waveform signals to synthesize a single high-gain beam.

[0147] When the scanning mode is a hybrid mode, the transmitting array uses a subarray structure to transmit signals. Within the subarray, signals are coherently coherently formed to create a low-gain beam. Orthogonal waveforms are transmitted between different subarrays, thereby achieving a combination of energy concentration and spatial diversity. The receiving array can use an independent array structure to receive signals, increasing the virtual aperture and improving resolution. Correspondingly, the receiving array can also use a subarray structure, utilizing coherent accumulation between subarrays to improve the receiving signal-to-noise ratio gain and enhance medium- and long-range detection capabilities.

[0148] Figure 7 This is a schematic diagram of a virtual aperture layout for an antenna arrangement in MIMO mode, as described in this embodiment. Figure 7 As shown, the transmitting array and receiving array are arranged in a two-dimensional plane; the aperture of the transmitting array in the horizontal direction is L. t_y The aperture of the transmitting array in the vertical direction is L. t_y The aperture of the receiving array in the horizontal direction is L. r_x The aperture of the receiving array in the vertical direction is L. t_y .

[0149] When the scanning mode is set to MIMO mode, neither the transmitting nor receiving arrays employ a subarray structure; all array elements independently transmit orthogonal waveforms. Therefore, in MIMO mode, the virtual aperture in the horizontal direction is equivalent to L. v_x =L t_x +L r_x The virtual aperture in the vertical direction is equivalent to L. v_y =L t_y +L r_y This maximizes the virtual aperture and improves resolution performance.

[0150] Figures 8(a) and 8(b) are two schematic diagrams of the virtual aperture layout of the antenna architecture provided in this embodiment in hybrid mode.

[0151] As shown in Figure 8(a), the transmitting array is configured as a subarray architecture to transmit signals, and the aperture of the transmitting array in the horizontal direction is L. t_x The aperture of the transmitting array in the vertical direction is L. t_y Suppose there are N transmitting subarrays in total, and the horizontal distance between the (n-1)th and the nth adjacent transmitting subarrays is d. n，t_x The vertical spacing between any two adjacent transmitting subarrays is d. n，t_y Let the equivalent phase center of the synthesized beam of the nth transmitting subarray be... The equivalent phase center in the horizontal direction is The equivalent path difference in the horizontal direction is The equivalent phase center in the vertical direction is The equivalent path difference in the vertical direction is: Therefore, the equivalent emission aperture of the emission array in the horizontal direction is The equivalent emission aperture of the emission array in the vertical direction is The receiving array is configured as an independent element array architecture for receiving signals. There are M receiving elements in total, and the aperture of the receiving array in the horizontal direction is L. r_x The aperture of the receiving array in the vertical direction is L. r_y Therefore, the virtual aperture formed in the horizontal direction in this example is... The virtual aperture formed in the vertical direction is

[0152] As shown in Figure 8(b), the transmitting array and receiving array are configured as a subarray architecture for signal transmission and reception. The aperture of the transmitting array in the horizontal direction is L. t_x The aperture of the transmitting array in the vertical direction is L. t_y Suppose there are N transmitting subarrays in total, and the horizontal distance between the (n-1)th and nth adjacent transmitting subarrays is d. n，t_x The vertical spacing between any two adjacent transmitting subarrays is d. n，t_y Let the equivalent phase center of the synthesized beam of the nth transmitting subarray be... The equivalent phase center in the horizontal direction is The equivalent path difference in the horizontal direction is The equivalent phase center in the vertical direction is The equivalent path difference in the vertical direction is: Therefore, the equivalent emission aperture of the emission array in the horizontal direction is The equivalent emission aperture of the emission array in the vertical direction is

[0153] The aperture of the receiving array in the horizontal direction is L r_x The aperture of the transmitting array in the vertical direction is L. r_y Suppose there are M receiving subarrays in total, and the horizontal distance between the (m-1)th and mth adjacent receiving subarrays is d. n，r_x The vertical spacing between any two adjacent receiving subarrays is d. n，r_y Let the equivalent phase center of the synthesized beam of the m-th receiving subarray be... The equivalent phase center in the horizontal direction is The equivalent path difference in the horizontal direction is The equivalent phase center in the vertical direction is The equivalent path difference in the vertical direction is: Therefore, the equivalent transmit aperture of the receiving array in the horizontal direction is The equivalent emission aperture of the emission array in the vertical direction is Therefore, in this example, the virtual aperture formed in the horizontal direction is The virtual aperture formed in the vertical direction is

[0154] Figure 9 This is a schematic diagram of an application scenario of the radar system provided in this embodiment, such as... Figure 9 As shown, the radar provided in this application is installed on the front bumper of a vehicle for detecting and identifying objects. The vehicle periodically detects the driving environment and switches the radar scanning mode according to the driving environment. Specifically:

[0155] When a vehicle needs to image in complex near-field road conditions, for example Figure 9 For vehicles within the blue line range, the control radar switches to MIMO mode, using orthogonal waveforms to form a large-aperture virtual array to improve resolution.

[0156] When a vehicle needs to perform multi-target tracking at a medium distance, for example Figure 9 The vehicle corresponding to the green ellipse in the image controls the radar to switch to hybrid mode, forming a multi-beam configuration. This improves the signal-to-noise ratio gain while also maintaining multi-resolution capability, enabling mid-range multi-target tracking.

[0157] When a vehicle needs to detect objects at long distances, for example... Figure 9 The vehicle corresponding to the red ellipse in the image controls the radar to switch to phased array mode, forming a high-gain single beam to scan the entire range.

[0158] In summary, this embodiment breaks through the independent application framework of the single system mode (phased array or MIMO) of traditional vehicle-mounted radar systems. By constructing an innovative three-in-one system of "hybrid antenna system architecture," "multi-mode waveform adaptation," and "adaptive mode switching," it solves the multiple challenges of traditional vehicle-mounted millimeter-wave radar in terms of performance and scenario adaptability, as detailed below:

[0159] a) Overcoming the performance limitations of traditional vehicle-mounted radar MIMO system architecture:

[0160] For a single MIMO system architecture, which relies on multiple antennas to transmit orthogonal waveforms to achieve a virtual aperture, although this improves resolution and multi-target detection capabilities, insufficient signal-to-noise ratio (SNR) leads to a reduced probability of detecting distant or weak targets, especially with severe performance degradation under adverse weather conditions. This invention, in addition to the MIMO system architecture, is also compatible with phased array mode and hybrid mode. When specific needs or scene changes occur, it can switch to phased array mode or hybrid mode to increase the SNR, compensating for the insufficient detection performance of the MIMO system architecture under adverse weather, distant, and weak target conditions.

[0161] b) Overcoming the performance limitations of traditional vehicle-mounted radar phased array system architecture:

[0162] For a single phased array system architecture, long-range high-gain detection is achieved through full-array coherent beamforming, but its drawbacks include the inability to perform virtual aperture expansion, limited field of view, and relatively weak multi-target resolution. This invention, in addition to the phased array system architecture, is also compatible with MIMO and hybrid modes. When specific needs or scene changes occur, it can switch to MIMO or hybrid modes for virtual aperture expansion, compensating for the shortcomings of the phased array system architecture in near-field imaging, wide-area detection, and multi-target conditions.

[0163] c) Addressing the issue of poor scenario adaptability in single-mode radar systems:

[0164] Traditional vehicle-mounted millimeter-wave radars mostly employ a single-mode radar system, resulting in a fixed transmission mode and a lack of dynamic mode switching capabilities. This makes them unsuitable for real-time mode switching in complex scenarios such as extreme weather, high-speed long-range operation, weak target detection (requiring high signal-to-noise ratio gain), complex urban multi-target scenarios (requiring tradeoffs between diversity gain and diversity gain), and short-range near-field imaging (requiring diversity gain to form a high-density virtual aperture). Single-mode applications often suffer from problems such as missed detection of long-range and weak targets (single MIMO mode), low near-field resolution, and small field of view (single phased array mode). This invention proposes a system architecture compatible with three modes to adapt to the performance requirements of different scenarios. Furthermore, it proposes a full-scenario adaptive mode switching decision model for this system architecture, utilizing reinforcement learning to optimize the switching strategy under complex scenarios, improving the environmental adaptability of the decision model, and greatly enhancing the flexibility of adaptation between different modes and different scenarios. This effectively solves the problem of poor scenario adaptability of traditional radars.

[0165] According to a second aspect of this application, embodiments of this application also provide an operating control device for a vehicle-mounted radar system, comprising:

[0166] The control module is used to control the vehicle's onboard radar system to perform environmental detection according to a scanning mode matched to the vehicle's real-time operating conditions; the scanning mode includes one of phased array mode, MIMO mode, and hybrid mode. This device possesses all the beneficial effects of the above-described methods, which will not be elaborated further in this application.

[0167] According to a third aspect of this application, embodiments of this application also provide a non-transitory computer-readable storage medium storing a computer program thereon, which, when executed by a processor, implements the steps of the above-described method. This non-transitory computer-readable storage medium possesses all the beneficial effects of the above-described method, which will not be elaborated further here.

[0168] According to a fourth aspect of this application, embodiments of this application also provide a computer program product, including a computer program that, when executed by a processor, implements the steps of the above-described method. This computer program product possesses all the beneficial effects of the above-described method, which will not be elaborated upon further herein.

[0169] According to a fifth aspect of this application, embodiments of this application also provide an electronic device, including: a memory and a processor, wherein a computer program is stored in the memory; the processor is configured to execute the computer program in the memory to implement the steps of the above-described method. This electronic device possesses all the beneficial effects of the above-described method, which will not be elaborated upon further herein.

[0170] Computer-readable storage media can be, for example, electrical, magnetic, optical, electromagnetic, infrared, or semiconductor systems, apparatuses, or devices, or any combination thereof, without particular limitation herein. More specific examples of computer-readable storage media may include, but are not limited to: electrical connections having one or more wires, portable computer disks, hard disks, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), optical fiber, portable compact disk read-only memory (CD-ROM), optical storage devices, magnetic storage devices, or any suitable combination thereof.

[0171] In some embodiments of this application, a computer-readable storage medium may be any tangible medium that contains or stores a program that may be used or combined with an instruction execution system, apparatus, or device.

[0172] The aforementioned computer-readable storage medium may be included in the aforementioned electronic device, or it may exist independently and not assembled into the electronic device. The aforementioned computer-readable storage medium carries one or more programs that, when executed by the electronic device, cause the electronic device to:

[0173] The vehicle's onboard radar system is controlled to perform environmental detection according to a scanning mode that matches the vehicle's real-time operating conditions; the scanning mode includes one of phased array mode, MIMO mode, and hybrid mode.

[0174] Computer program code for performing operations of some embodiments of this application can be written in one or more programming languages ​​or a combination thereof. These programming languages ​​include object-oriented programming languages ​​such as Java, Smalltalk, and C++, as well as conventional procedural programming languages ​​such as the "C" language or similar programming languages. The program code can be executed entirely on the user's computer, partially on the user's computer, as a standalone software package, partially on the user's computer and partially on a remote computer, or entirely on a remote computer or server. In cases involving remote computers, the remote computer can be connected to the user's computer via any type of network (including a local area network (LAN) or a wide area network (WAN)), or it can be connected to an external computer (e.g., via the Internet using an Internet service provider).

[0175] The flowcharts and block diagrams in the accompanying drawings illustrate the architecture, functionality, and operation of possible implementations of systems, methods, and computer program products according to various embodiments of this application. In this regard, each block in a flowchart or block diagram may represent a module, segment, or portion of code containing one or more executable instructions for implementing a specified logical function.

[0176] It should also be noted that in some alternative implementations, the functions marked in the box may occur in a different order than those marked in the attached figures.

[0177] For example, two consecutively represented blocks can actually be executed in substantially parallel order, and sometimes they can be executed in reverse order, depending on the functions involved. It should also be noted that each block in a block diagram and / or flowchart, as well as combinations of blocks in block diagrams and / or flowcharts, can be implemented using a dedicated hardware-based system that performs the specified functions or operations, or using a combination of dedicated hardware and computer instructions.

[0178] The units described in some embodiments of this application can be implemented in software or in hardware. The described units can also be located in a processor.

[0179] The functions described above in this document can be performed, at least in part, by one or more hardware logic components. For example, exemplary types of hardware logic components that can be used, without limitation, include: Field Programmable Gate Arrays (FPGAs), Application-Specific Integrated Circuits (ASICs), Application Standard Products (ASSPs), System-on-Chip (SoCs), Complex Programmable Logic Devices (CPLDs), and so on.

[0180] According to the sixth aspect of this application, such as Figure 10 As shown in the illustration, this application also provides a vehicle 10, which includes the aforementioned electronic equipment. This vehicle possesses all the beneficial effects of the aforementioned electronic equipment, etc., which will not be elaborated upon further herein.

[0181] The vehicle may be a gasoline-powered vehicle, a plug-in hybrid electric vehicle, or a new energy vehicle, etc., and this application does not make any specific restrictions.

[0182] In the description of this application, the terms "first" and "second" are used for descriptive purposes only and should not be construed as indicating or implying relative importance or implicitly specifying the number of technical features indicated. Therefore, a feature defined as "first" or "second" may explicitly or implicitly include one or more features. In the description of this application, "multiple" means two or more, unless otherwise explicitly specified.

[0183] In the above embodiments, the descriptions of each embodiment have different focuses. For parts not described in detail in a certain embodiment, please refer to the relevant descriptions in other embodiments.

[0184] The embodiments, implementation methods, and related technical features of this application can be combined and substituted for each other without conflict.

[0185] The above are merely preferred embodiments of this application and are not intended to limit this application in any way. Although the descriptions of each embodiment in this application have different focuses, and parts not described in detail in a certain embodiment can be referred to the relevant descriptions of other embodiments, any simple modifications, equivalent changes and alterations made to the above embodiments based on the technical essence of this application without departing from the content of the technical solution of this application shall still fall within the scope of the technical solution of this application.

Claims

1. A method for controlling the operation of a vehicle-mounted radar system, characterized in that, include: The vehicle's onboard radar system is controlled to perform environmental detection based on a scanning mode that matches the vehicle's real-time operating conditions. The scanning mode includes one of phased array mode, MIMO mode, and hybrid mode.

2. The method according to claim 1, characterized in that, The step of controlling the vehicle's onboard radar system to perform environmental detection based on a scanning mode matched to the vehicle's real-time operating conditions includes: When the scanning mode is phased array mode, control all transmitting elements of the transmitting array in the vehicle-mounted radar system to transmit coherent waveform signals; or When the scanning mode is MIMO mode, all transmitting array elements are controlled to independently transmit orthogonal waveform signals; or When the scanning mode is a mixed mode, the array elements within the same transmitting subarray structure in the transmitting array are controlled to transmit orthogonal waveform signals, while different subarray structures transmit coherent waveform signals.

3. The method according to claim 2, characterized in that, When the scanning mode is a mixed mode, the vehicle-mounted radar system controlling the vehicle performs environmental detection, which further includes: Control all transmitting elements of the receiving array in the vehicle-mounted radar system to independently receive signals; or The receiving array in the vehicle-mounted radar system is controlled to receive signals as a whole, with the receiving subarray structure as the whole.

4. The method according to claim 1, characterized in that, Before the onboard radar system controlling the vehicle performs environmental detection, the system further includes: When the real-time operating condition is vehicle startup, the scanning mode is determined to be MIMO mode; or When the real-time operating condition requires near-field wide-area detection, the scanning mode is determined to be MIMO mode; or When the real-time operating condition requires mid-range multi-target tracking, the scanning mode is determined to be a hybrid mode; or When the real-time operating condition requires long-distance detection, the scanning mode is determined to be phased array mode.

5. The method according to claim 4, characterized in that, After the onboard radar system controlling the vehicle performs environmental detection, the system further includes: Monitor the driving environment of the vehicle; The real-time operating conditions of the vehicle are determined based on the vehicle's real-time driving scenario and the correlation between the driving scenario and the operating conditions.

6. The method according to claim 1, characterized in that, The step of controlling the vehicle's onboard radar system to perform environmental detection based on a scanning mode matched to the vehicle's real-time operating conditions includes: When the vehicle is equipped with multiple vehicle-mounted radar systems, the scanning mode corresponding to each vehicle-mounted radar system is determined according to the actual working conditions. Based on the scanning mode of each vehicle-mounted radar system, control the corresponding vehicle-mounted radar system to perform environmental detection; The environmental detection results of each vehicle-mounted radar system are fused together.

7. The method according to any one of claims 1 to 6, characterized in that, After controlling the vehicle's onboard radar system to perform environmental detection according to a scanning mode matched to the vehicle's actual operating conditions, the method further includes: When the real-time operating conditions of the vehicle change, a new scanning mode corresponding to the new real-time operating conditions is determined; The vehicle's onboard radar system is controlled to perform environmental detection according to the new scanning mode.

8. The method according to claim 7, characterized in that, Before controlling the vehicle's onboard radar system to perform environmental detection according to the new detection mode, the method further includes: Generate the probe waveform corresponding to the current scanning mode and the probe waveform corresponding to the new scanning mode respectively; After the detection waveform corresponding to the new scanning mode is generated, the vehicle's onboard radar system is controlled to perform environmental detection according to the new scanning mode.

9. The method according to claim 7, characterized in that, After controlling the vehicle's onboard radar system to perform environmental detection according to the new scanning mode, the method further includes: The environmental detection results of the old scanning mode are combined with the environmental detection results of the new scanning mode.

10. The method according to claim 7, characterized in that, Before determining the new scanning mode corresponding to the new real-time operating condition when the vehicle's real-time operating condition changes, the method further includes: Based on the vehicle's motion state and driving environment, predict whether it is necessary to switch scanning modes; When it is predicted that a switch to a scanning mode is needed, the parameters and algorithms required by the vehicle radar system for the next scanning mode are generated.

11. A control device for a vehicle-mounted radar system, characterized in that, include: The control module is used to control the vehicle's onboard radar system to perform environmental detection according to a scanning mode that matches the vehicle's real-time operating conditions; the scanning mode includes one of phased array mode, MIMO mode, and hybrid mode.

12. A computer-readable storage medium having a computer program stored thereon, characterized in that, When the computer program is executed by a processor, it implements the method described in any one of claims 1 to 10.

13. A computer program product, comprising a computer program, characterized in that, When the computer program is executed by a processor, it implements the method described in any one of claims 1 to 10.

14. An electronic device, characterized in that, include: A memory on which computer programs are stored; A processor for executing the computer program in the memory to implement the method of any one of claims 1 to 10.

15. A vehicle, characterized in that, Including the electronic device as described in claim 14.

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