Distributed management and control method and system for millimeter wave radar

Abstract

The invention discloses a distributed management and control method and system for a millimeter-wave radar, and the method comprises the steps: determining a corresponding working scene according to a plurality of scene data, the millimeter-wave radar and environment parameters; and determining a distributed management and control system of the millimeter wave radar and the controller according to the working scene, the processing level of the millimeter wave radar and the processing level of the controller of the vehicle, thereby realizing distributed management and control of the millimeter wave radar and the controller. Determining a plurality of to-be-processed data combinations based on the plurality of scene data transmitted by the millimeter wave radar, the target object and the processing space of the controller; determining a plurality of processing results based on the plurality of to-be-processed data combinations, the real-time driving data of the vehicle and the processing logic of the controller; and determining an optimal processing result according to the plurality of processing results, the previous processing data of the vehicle and the driving state of the vehicle, triggering intelligent control of the vehicle based on the optimal processing result, and ensuring multi-level precision control of the millimeter wave radar and the controller under synchronous work.

Description

Technical Field

[0001] The present invention relates to the technical field of millimeter wave radars, and in particular to a distributed control method and system for millimeter wave radars. Background Art

[0002] With the development of science and technology, millimeter-wave radar is applied to intelligent vehicles and detects the external environment. Millimeter-wave radar can be used as a part of intelligent vehicles. In the existing technology, millimeter-wave radar detects the outside world and collects multiple signals. The processing capacity of millimeter-wave radar is limited and it cannot accurately process multiple signals. Summary of the invention

[0003] The purpose of the present invention is to overcome the deficiencies of the prior art. The present invention provides a distributed control method and system for millimeter-wave radar.

[0004] The embodiment of the present invention provides a distributed control method of millimeter wave radar, which is applied to the distributed control scenario of millimeter wave radar;

[0005] The distributed control method of the millimeter wave radar includes:

[0006] When the vehicle is in a driving state, a plurality of digital acquisition signals are determined based on the millimeter wave signal of the millimeter wave radar;

[0007] Determine the corresponding target object according to multiple digital acquisition signals, images taken by the vehicle, and a target detection system;

[0008] Determining a plurality of scene data based on directional detection of target objects and vehicles;

[0009] Determine the corresponding working scene according to multiple scene data, millimeter-wave radar and environmental parameters, and determine the distributed control system of millimeter-wave radar and controller according to the working scene, the processing level of millimeter-wave radar and the processing level of the vehicle controller;

[0010] In the distributed control system of the millimeter-wave radar and the controller, multiple combinations of data to be processed are determined based on multiple scene data transmitted by the millimeter-wave radar, target objects, and the processing space of the controller; multiple processing results are determined based on the multiple combinations of data to be processed, the real-time driving data of the vehicle, and the processing logic of the controller;

[0011] The best processing result is determined based on multiple processing results, the vehicle's previous processing data, and the vehicle's driving status, and the vehicle's intelligent control is triggered based on the best processing result, ensuring multi-level precision control of the millimeter-wave radar and the controller under synchronous operation.

[0012] In addition, an embodiment of the present invention further provides a distributed control system for millimeter wave radar, and the distributed control system for millimeter wave radar includes:

[0013] An acquisition module, used for determining a plurality of digital acquisition signals based on the millimeter wave signal of the millimeter wave radar when the vehicle is in a driving state;

[0014] A target detection module, used to determine the corresponding target object based on multiple digital acquisition signals, images taken by the vehicle and a target detection system;

[0015] A scene module, for determining a plurality of scene data based on directional detection of a target object and a vehicle;

[0016] A distributed control module is used to determine the corresponding working scene according to multiple scene data, millimeter-wave radar and environmental parameters, and determine the distributed control system of the millimeter-wave radar and the controller according to the working scene, the processing level of the millimeter-wave radar and the processing level of the vehicle controller;

[0017] A processing result module is used to determine a plurality of combinations of data to be processed based on a plurality of scene data transmitted by the millimeter-wave radar, a target object, and a processing space of the controller in a distributed control system of the millimeter-wave radar and the controller; and to determine a plurality of processing results based on the plurality of combinations of data to be processed, the real-time driving data of the vehicle, and the processing logic of the controller;

[0018] The intelligent control module is used to determine the best processing result based on multiple processing results, the vehicle's previous processing data and the vehicle's driving status, trigger the vehicle's intelligent control based on the best processing result, and ensure multi-level precision control of the millimeter-wave radar and the controller under synchronous operation.

[0019] In an embodiment of the present invention, through the method in the embodiment of the present invention, when the vehicle is in a driving state, multiple digital acquisition signals are determined based on the millimeter wave signal of the millimeter wave radar; the corresponding target object is determined according to the multiple digital acquisition signals, the image taken by the vehicle and the target detection system; multiple scene data are determined based on the directional detection of the target object and the vehicle; the corresponding working scene is determined according to the multiple scene data, the millimeter wave radar and the environmental parameters, and the distributed control system of the millimeter wave radar and the controller is determined according to the working scene, the processing level of the millimeter wave radar and the processing level of the vehicle's controller, which is compatible with the overall consideration of the working scene, the processing level of the millimeter wave radar and the processing level of the vehicle's controller, and realizes multi-dimensional control of the working scene, the processing level of the millimeter wave radar and the processing level of the vehicle's controller, ensuring the accuracy of the distributed control system of the millimeter wave radar and the controller, thereby realizing the distributed control of the millimeter wave radar and the controller.

[0020] Furthermore, in the distributed control system of the millimeter-wave radar and the controller, multiple combinations of data to be processed are determined based on multiple scene data transmitted by the millimeter-wave radar, target objects and the processing space of the controller; multiple processing results are determined based on the multiple combinations of data to be processed, the real-time driving data of the vehicle and the processing logic of the controller; the best processing result is determined according to the multiple processing results, the previous processing data of the vehicle and the driving status of the vehicle, and the intelligent control of the vehicle is triggered based on the best processing result, and multi-level precision control of the millimeter-wave radar and the controller under synchronous operation is ensured, thereby realizing precise control of the millimeter-wave radar and the controller at different stages, releasing the processing pressure of the millimeter-wave radar, and better applying the computing power of the controller. BRIEF DESCRIPTION OF THE DRAWINGS

[0021] Figure 1 is a flow chart of a distributed control method of a millimeter wave radar in an embodiment of the present invention;

[0022] Figure 2 is a flow chart of S11 in the distributed control method of the millimeter wave radar in the embodiment of the present invention;

[0023] Figure 3 is a flow chart of S12 in the distributed control method of the millimeter wave radar in the embodiment of the present invention;

[0024] Figure 4 is a flow chart of S13 in the distributed control method of the millimeter wave radar in the embodiment of the present invention;

[0025] Figure 5 is a flow chart of S14 in the distributed control method of the millimeter wave radar in the embodiment of the present invention;

[0026] Figure 6 is a flow chart of S15 in the distributed control method of the millimeter wave radar in the embodiment of the present invention;

[0027] Figure 7 is a flow chart of S16 in the distributed control method of the millimeter wave radar in an embodiment of the present invention;

[0028] Figure 8 It is a schematic diagram of the structural composition of the distributed control system of the millimeter wave radar in an embodiment of the present invention. DETAILED DESCRIPTION

[0029] The technical solutions in the embodiments of the present invention will be described clearly and completely below in conjunction with the accompanying drawings in the embodiments of the present invention.

[0030] See also Figures 1 to 8A distributed control method of a millimeter wave radar is applied to a distributed control scenario of a millimeter wave radar; the distributed control method of the millimeter wave radar includes:

[0031] Step S11: when the vehicle is in a driving state, determining a plurality of digital acquisition signals based on the millimeter wave signal of the millimeter wave radar;

[0032] Step S12: determining a corresponding target object according to a plurality of digital acquisition signals, an image captured by the vehicle, and a target detection system;

[0033] Step S13: determining a corresponding target object according to a plurality of digital acquisition signals, an image captured by the vehicle, and a target detection system;

[0034] Step S14: determining a corresponding working scene according to the plurality of scene data, the millimeter-wave radar and the environmental parameters, and determining a distributed control system of the millimeter-wave radar and the controller according to the working scene, the processing level of the millimeter-wave radar and the processing level of the vehicle controller;

[0035] Step S15: In the distributed control system of the millimeter-wave radar and the controller, a plurality of combinations of data to be processed are determined based on a plurality of scene data transmitted by the millimeter-wave radar, the target object, and the processing space of the controller; a plurality of processing results are determined based on the plurality of combinations of data to be processed, the real-time driving data of the vehicle, and the processing logic of the controller;

[0036] Step S16: Determine the best processing result based on multiple processing results, the vehicle's previous processing data and the vehicle's driving status, trigger the vehicle's intelligent control based on the best processing result, and ensure multi-level precision control of the millimeter-wave radar and the controller under synchronous operation.

[0037] refer to Figure 2 , in step S11, when the vehicle is in a driving state, a plurality of digital acquisition signals are determined based on the millimeter wave signal of the millimeter wave radar;

[0038] In the specific implementation process of the present invention, the specific steps may be:

[0039] S111: real-time monitoring of vehicle status;

[0040] S112: When the vehicle is in a driving state, the millimeter wave radar detects external objects as the vehicle is driving dynamically;

[0041] S113: collecting millimeter wave signals of the millimeter wave radar based on external detection of the millimeter wave radar;

[0042] S114: Determine a plurality of digital acquisition signals according to signal processing of the millimeter wave signal of the millimeter wave radar.

[0043] In the embodiments of the present application, specifically, through sensors (such as GPS positioning system, speed sensor, acceleration sensor, etc.) and wireless communication equipment (such as vehicle networking technology) installed on the vehicle, key data such as the position, speed, acceleration, direction, etc. of the vehicle are collected in real time. At the same time, combined with technologies such as video monitoring system and radar detection, environmental information and road conditions around the vehicle are obtained. Using advanced algorithms and models (such as machine learning, deep learning, etc.), the collected data is analyzed and processed to accurately identify the current state of the vehicle, including parking state and driving state. The driving state can be further subdivided into normal driving, acceleration, deceleration, turning, etc., to provide more detailed vehicle dynamic information. The identified vehicle status information is displayed in real time in the traffic management system, such as a traffic monitoring screen, mobile phone APP, etc. The display content may include the vehicle's position, speed, state (parking / driving), driving direction, etc., which is convenient for managers and drivers to intuitively understand the vehicle situation.

[0044] At the same time, when the vehicle is in motion, the millimeter-wave radar conducts external detection as the vehicle drives dynamically, and performs real-time detection, so as to facilitate the control of the external environment when the vehicle is driving dynamically, thereby collecting the millimeter-wave signal of the millimeter-wave radar based on the external detection of the millimeter-wave radar, realizing the external detection of the millimeter-wave radar, ensuring the accuracy of the millimeter-wave signal of the millimeter-wave radar, and realizing the dynamic control of the millimeter-wave signal of the millimeter-wave radar.

[0045] Specifically, when the vehicle is in motion, the millimeter-wave radar continuously emits millimeter-wave signals as the vehicle moves, and receives reflected signals. After processing, these signals can generate a detailed image of the vehicle's surroundings, including the position, speed, and movement trajectory of other vehicles, pedestrians, obstacles, etc. Millimeter-wave radar has high-speed data acquisition and processing capabilities and can detect changes in the external environment in real time. This means that the vehicle can quickly respond to emergencies on the road, such as emergency braking, lane changes, or avoiding obstacles.

[0046] Millimeter-wave radar transmits and receives millimeter-wave signals through an antenna array. These signals are reflected back when encountering obstacles, received by the radar and converted into digital data. After processing and analysis, the collected data can extract key information such as the location, speed, and shape of the obstacle. In order to ensure the accuracy of the millimeter-wave signal, the radar system needs to undergo rigorous calibration and testing. In addition, the use of advanced signal processing algorithms and machine learning technology can further improve the accuracy and robustness of the radar's perception of the external environment.

[0047] During driving, the millimeter-wave radar system needs to constantly monitor the quality and stability of the signal. This includes detecting parameters such as signal strength, frequency, and phase to ensure that they meet preset standards and requirements. According to changes in the external environment and changes in the vehicle's driving status, the millimeter-wave radar system can dynamically adjust its transmission power, beam width, scanning frequency and other parameters. This dynamic adjustment helps optimize the radar's detection range and accuracy while reducing unnecessary energy consumption and interference.

[0048] Therefore, multiple digital acquisition signals are determined based on the signal processing of the millimeter-wave signal of the millimeter-wave radar, and the millimeter-wave signal of the millimeter-wave radar is processed, thereby realizing the analysis of the millimeter-wave signal of the millimeter-wave radar, so as to facilitate the overall control of the millimeter-wave signal of the millimeter-wave radar, and ensure the control of multiple digital acquisition signals, so as to facilitate the processing of multiple digital acquisition signals. At this time, the millimeter-wave signal of the millimeter-wave radar is converted into multiple digital acquisition signals under multiple signal processing measures.

[0049] Specifically, millimeter wave radar transmits electromagnetic waves in the millimeter wave band through its antenna system. These waves have the characteristics of strong penetration, good directivity, and high measurement accuracy. When the millimeter wave signal encounters a target (such as a vehicle, pedestrian, obstacle, etc.), part of the signal will be reflected back and received by the radar antenna. The received signal will first undergo preprocessing steps such as amplification and filtering to improve the signal-to-noise ratio and anti-interference ability of the signal. The preprocessed signal will undergo more complex signal processing, such as mixing, demodulation, denoising, spectrum analysis, etc. The purpose of these processing steps is to extract useful information related to the target position, speed, shape, etc. from the received signal. During the signal processing process, the analog signal is converted into a digital signal through an analog-to-digital converter (ADC). These digital signals contain various information about the target, such as distance, speed, angle, etc., forming multiple digital acquisition signals.

[0050] In order to ensure the accuracy and reliability of digital acquisition signals, the system will strictly control these signals. This includes steps such as signal calibration, verification, and redundancy removal to ensure that each signal reflects the true target information. Multiple digital acquisition signals are further processed, such as filtering, smoothing, and interpolation, to improve the accuracy and completeness of the data. These processing measures help eliminate noise, fill data gaps, and enhance the readability and interpretability of signals. The processed multiple digital acquisition signals can be used in various application scenarios, such as intelligent driving assistance, collision warning, automatic parking, etc. These signals provide vehicles with real-time and accurate environmental perception information, which helps to improve driving safety and comfort.

[0051] refer to Figure 3, in step S12, determining the corresponding target object according to the multiple digital acquisition signals, the image captured by the vehicle and the target detection system;

[0052] In the specific implementation process of the present invention, the specific steps may be:

[0053] S121: freeze multiple digital acquisition signals;

[0054] S122: Determine detection data of the millimeter wave radar according to multi-level transformation of multiple digital acquisition signals;

[0055] S123: Associating the millimeter wave radar and the camera, and collecting images taken by the vehicle according to circumferential detection of the camera;

[0056] S124: Correlate the detection data of the millimeter wave radar, the image taken by the vehicle, and the target detection system;

[0057] S125: determining first target information according to the detection data of the millimeter wave radar and the image taken by the vehicle, and determining second target information according to the detection data of the millimeter wave radar and the target detection system;

[0058] S126: Determine a corresponding target object according to the first target information, the second target information, and the millimeter wave radar.

[0059] In an embodiment of the present application, during the signal processing of the millimeter wave radar, the system will first capture and record multiple digital acquisition signals. These signals represent the reflection information of different targets (such as vehicles, pedestrians, obstacles, etc.) in the environment detected by the radar. In order to ensure the accuracy and reliability of these digital acquisition signals, the system will strictly control them. This includes steps such as signal verification, redundancy removal, and error correction to ensure that each signal reflects the true target information.

[0060] Multi-level transformation refers to the process of performing transformations on multiple digital acquisition signals at different levels to extract higher-level information or features. These transformations can include filtering, smoothing, interpolation, feature extraction, etc. In millimeter-wave radar systems, multi-level transformations are usually implemented through digital signal processing algorithms and software. These algorithms gradually transform and process digital acquisition signals according to preset rules and logic. The logical selection of multi-level transformations depends on the application requirements of the radar system and the target detection task. For example, in some cases, the system may need to extract information such as the distance, speed, angle, etc. of the target; in other cases, it may need to identify the type, shape, or behavior pattern of the target.

[0061] After multi-level transformation processing, the system will integrate and analyze the information in multiple digital acquisition signals to determine the detection data of the millimeter wave radar. These detection data usually include key information such as the position, speed, acceleration, shape, size, etc. of the target. Through multi-level transformation processing, the system can eliminate noise and interference in the digital acquisition signal and improve the accuracy and reliability of the data. At the same time, the system will further verify and calibrate the detection data to ensure its accuracy.

[0062] Furthermore, the millimeter-wave radar and the camera are associated, and the images taken by the vehicle are collected based on the circumferential detection of the camera. The millimeter-wave radar and the camera are compatible, and the circumferential detection of the camera is fully utilized to collect the images taken by the vehicle, thereby ensuring the accuracy of the images taken by the vehicle.

[0063] Specifically, millimeter-wave radar and cameras are usually integrated together in intelligent driving systems to form a multi-sensor fusion system. This fusion not only improves the perception accuracy of the system, but also enhances its robustness and reliability. Millimeter-wave radar has significant advantages in detection distance, speed, angle, etc. due to its long-range detection, unaffected by light, and strong penetration. Cameras, with their high resolution, rich color and texture information, and the ability to recognize shapes and details, perform well in target recognition, classification, and behavior prediction.

[0064] The camera has a wide field of view and can cover multiple directions around the vehicle. By adjusting the camera's installation position and angle, 360-degree panoramic monitoring can be achieved. The camera captures images around the vehicle in real time and uses image processing algorithms to perform feature extraction, target detection, tracking, and recognition. These processing steps ensure the accuracy and usefulness of the image.

[0065] In order to achieve effective collaboration between millimeter-wave radar and camera, their data needs to be fused and calibrated. This includes steps such as time synchronization, spatial alignment, and data format conversion. Through data fusion, the system can combine the ranging information of the millimeter-wave radar and the image information of the camera to generate more accurate and comprehensive environmental perception results. In order to fully utilize the circumferential detection capabilities of the camera, the system needs to optimize the perception algorithms. These algorithms should be able to accurately identify targets in the image, estimate their position and speed, and match and verify them with the data of the millimeter-wave radar. In order to ensure the accuracy of the images taken by the vehicle, the system needs to calibrate and maintain the camera regularly. In addition, the image processing algorithm also needs to be continuously updated and optimized to adapt to different lighting conditions, weather conditions and road environments.

[0066] Therefore, the detection data of the millimeter-wave radar, the image taken by the vehicle and the target detection system are associated; the first target information is determined according to the detection data of the millimeter-wave radar and the image taken by the vehicle, and the second target information is determined according to the detection data of the millimeter-wave radar and the target detection system; the corresponding target object is determined according to the first target information, the second target information and the millimeter-wave radar, and the first target information, the second target information and the millimeter-wave radar are compatible, and multiple interactions of the first target information, the second target information and the millimeter-wave radar are realized, thereby ensuring the accurate identification of the target object.

[0067] Specifically, millimeter-wave radar can obtain information such as the distance, speed, and angle of the target by emitting millimeter-wave signals and receiving their echoes. These data are highly accurate and real-time, and are an important basis for target recognition. The camera equipped on the vehicle can capture images of the surrounding environment and provide rich visual information. This information includes the shape, color, texture, etc. of the target, which helps to accurately identify and classify the target. The target detection system is usually based on deep learning algorithms and can automatically detect and identify targets in images. This system can process complex image data, extract key features, and output information such as the location and category of the target. In order to achieve accurate target recognition, the detection data of the millimeter-wave radar, the images taken by the vehicle, and the target detection system need to be associated and interacted. This process includes data synchronization, fusion, and calibration to ensure that information from different sources can complement and verify each other. Through multiple interactions, the system can make full use of the ranging advantages of the millimeter-wave radar, the visual information of the camera, and the automatic recognition capabilities of the target detection system to achieve all-round and multi-level perception of the target object.

[0068] Based on the detection data of the millimeter-wave radar and the images taken by the vehicle, the first target information can be determined. This information includes the distance, speed, position, and visual features of the target. Combining the detection data of the millimeter-wave radar and the output results of the target detection system, the second target information can be determined. This information mainly focuses on the category of the target, behavior prediction, and the relationship with other targets. In order to improve the accuracy of target recognition, the first target information and the second target information need to be fused and verified. This process includes steps such as data matching, de-redundancy, and error correction to ensure the accuracy and consistency of the target information.

[0069] Based on the first target information, the second target information and the raw data of the millimeter wave radar, the system can determine the corresponding target object. This process involves comprehensive analysis and judgment of multi-source information to ensure accurate identification of the target object. In order to achieve accurate identification of the target object, the system needs to continuously optimize algorithms and models to improve the efficiency and accuracy of data processing. At the same time, the sensor needs to be calibrated and maintained regularly to ensure the stability and reliability of its performance.

[0070] refer to Figure 4 , in step S13, in the floor cleaning space, the corresponding target object is determined according to the multiple digital acquisition signals, the image taken by the vehicle and the target detection system;

[0071] In the specific implementation process of the present invention, the specific steps may be:

[0072] S131: freeze the target object;

[0073] S132: Collecting the real-time relative relationship between the target object and the vehicle;

[0074] S133: Matching a corresponding directional detection system based on the real-time relative relationship between the target object and the vehicle;

[0075] S134: triggering directional detection of the target object and the vehicle according to the directional detection system;

[0076] S135: Determine a plurality of scene data based on the directional detection of the target object and the vehicle.

[0077] In an embodiment of the present application, the target object is frozen and controlled, and at the same time, the real-time relative relationship between the target object and the vehicle is collected, the real-time relative relationship between the target object and the vehicle is introduced, and the real-time relative relationship between the target object and the vehicle is controlled. At the same time, a corresponding directional detection system is matched based on the real-time relative relationship between the target object and the vehicle, which is compatible with the overall consideration of the real-time relative relationship between the target object and the vehicle, and multiple matches of the real-time relative relationship between the target object and the vehicle are achieved, thereby ensuring the accuracy of the directional detection system and realizing directional detection of the target object by the vehicle.

[0078] Specifically, the intelligent driving system uses sensors such as cameras and millimeter-wave radars to capture target objects in the surrounding environment in real time. When the system identifies a potential target object (such as a vehicle, pedestrian, obstacle, etc.), it will immediately freeze it, that is, lock its key features such as position, shape, and size. Once the target object is frozen, the system will continue to track and monitor it. This includes updating the target object's position information, speed information, and relative relationship with other objects. At the same time, the system will also predict the target object's future motion trajectory based on its behavior pattern so that it can respond in time.

[0079] By integrating multiple sensors (such as cameras, millimeter-wave radars, and lidars), the intelligent driving system can collect the relative relationship between the target object and the vehicle in real time. These relationships include key parameters such as distance, speed difference, angle, and acceleration. Introducing the collected real-time relative relationship into the system can greatly improve the accuracy and reliability of target object recognition. These relationship data provide the system with more comprehensive and three-dimensional environmental perception information, which helps the system make more accurate judgments and decisions.

[0080] According to the real-time relative relationship between the target object and the vehicle, the system will intelligently match the corresponding directional detection system. These systems may include different algorithms, models or processing flows, designed to accurately detect target objects of different types and states. When matching the directional detection system, the system will comprehensively consider all relevant information about the target object, including its position, speed, shape, size, and relative relationship with other objects. This comprehensive and integrated consideration ensures the accuracy and applicability of the directional detection system.

[0081] Therefore, the directional detection of the target object and the vehicle is triggered according to the directional detection system; multiple scene data are determined according to the directional detection of the target object and the vehicle, and the directional detection of the target object and the vehicle is monitored in real time, thereby ensuring the multi-dimensional control of the directional detection of the target object and the vehicle, thereby ensuring the accuracy of multiple scene data.

[0082] Specifically, the directional detection system in the intelligent driving system is built based on data fusion and algorithm processing of multiple sensors (such as cameras, millimeter-wave radars, lidars, etc.). When the system identifies potential interactions between a target object and a vehicle, the directional detection system is triggered. The conditions that trigger directional detection may include changes in parameters such as the distance, speed difference, and acceleration between the target object and the vehicle. The system will determine when to start directional detection based on a preset threshold or algorithm.

[0083] Once the directional detection system is triggered, the system will begin to collect multiple scene data related to the target object and the vehicle. This data may include the position, speed, shape, size of the target object, as well as the vehicle's own status information (such as speed, acceleration, steering angle, etc.). The system will integrate and analyze the collected multi-dimensional data to form a comprehensive understanding of the interaction between the target object and the vehicle. This helps the system make more accurate judgments and decisions.

[0084] The directional detection system needs to monitor the interaction between the target object and the vehicle in real time. This requires the system to have a high degree of real-time and accuracy so that it can respond quickly at critical moments. In order to ensure the accuracy of directional detection, the system needs to control the target object and the vehicle from multiple dimensions. This includes continuous monitoring of parameters such as its position, speed, acceleration, and the prediction and analysis of changes in their relative relationship. During real-time monitoring, the system also needs to be able to detect abnormal situations, such as sudden acceleration, deceleration, or lane changes of the target object. Once an abnormal situation is detected, the system will immediately initiate the corresponding processing mechanism to ensure driving safety.

[0085] refer to Figure 5 , S14: determining a corresponding working scene according to a plurality of scene data, the millimeter-wave radar and environmental parameters, and determining a distributed control system of the millimeter-wave radar and the controller according to the working scene, the processing level of the millimeter-wave radar and the processing level of the vehicle controller;

[0086] In the specific implementation process of the present invention, the specific steps may be:

[0087] S141: freeze multiple scene data;

[0088] S142: Collecting environmental parameters based on environmental detection of the vehicle;

[0089] S143: Associating multiple scene data, millimeter wave radars, and environmental parameters, and determining corresponding working scenes according to the multiple scene data, millimeter wave radars, and environmental parameters;

[0090] S144: Freeze the working scene;

[0091] S145: Multiple interactions are performed on the working scene, the processing level of the millimeter wave radar, and the processing level of the vehicle controller;

[0092] S146: Determine a distributed control system of the millimeter-wave radar and the controller based on multiple interactions of the working scenario, the processing level of the millimeter-wave radar, and the processing level of the vehicle's controller.

[0093] At this time, scene data refers to the state information of the vehicle's surrounding environment at a specific time and space, including but not limited to road type, traffic flow, weather conditions, light conditions, etc. The intelligent driving system captures environmental information in real time through sensors (such as cameras, millimeter-wave radars, lidars, etc.) and freezes this information into multiple scene data points. These data points contain rich environmental details and provide a basis for subsequent analysis and processing.

[0094] The system integrates the frozen scene data to form a comprehensive environmental perception map. This helps the system to have a more comprehensive and detailed understanding of the surrounding environment. The introduced scene data is used in multiple modules of the intelligent driving system, such as path planning, obstacle avoidance strategy formulation, vehicle control, etc. These data provide the system with necessary input information to support its intelligent decision-making.

[0095] The intelligent driving system continuously detects the environment around the vehicle through a sensor network. This includes detecting key elements such as road conditions, traffic signs, obstacles, pedestrians, etc. During the detection process, the system collects various environmental parameters, such as weather conditions (sunny, rainy, snowy, etc.), light conditions (day, night, dawn, dusk, etc.), road conditions (dry, slippery, icy, etc.), etc. These parameters are important for the system to understand the current environmental status and predict future environmental changes.

[0096] Furthermore, multiple scene data, millimeter-wave radars and environmental parameters are associated, and the corresponding working scenes are determined based on the multiple scene data, millimeter-wave radars and environmental parameters. This is compatible with the overall consideration of multiple scene data, millimeter-wave radars and environmental parameters, and realizes multi-dimensional control of multiple scene data, millimeter-wave radars and environmental parameters, ensuring the accuracy of the working scenes.

[0097] Specifically, the intelligent driving system uses different sensors (such as cameras, millimeter-wave radars, lidars, etc.) and algorithm modules to capture and process environmental information around the vehicle in real time to form multiple scene data. These data cover multiple dimensions such as road type, traffic conditions, weather conditions, and light conditions. As an important perception sensor, millimeter-wave radar can provide accurate information such as the distance, speed, and angle of the target object. The system combines these radar data with scene data to obtain more comprehensive environmental perception information. In addition to scene data and millimeter-wave radar data, the system also collects environmental parameters such as weather conditions, road conditions, light intensity, etc. through other sensors (such as temperature sensors, humidity sensors, light sensors, etc.) and algorithm modules. These parameters are of great significance for understanding the current environmental state and predicting future environmental changes.

[0098] The system correlates and analyzes multiple scene data, millimeter wave radar data, and environmental parameters to identify current environmental characteristics and potential risks. This includes road type identification, traffic condition analysis, weather condition assessment, and other aspects. Based on the results of data correlation and analysis, the system intelligently determines the current working scenario. These scenarios may include driving on highways, congested urban roads, driving on rural roads, driving in severe weather conditions, etc.

[0099] When determining the working scene, the system fully considers the overall impact of multiple scene data, millimeter wave radar data and environmental parameters. This overall consideration ensures that the system can accurately and comprehensively understand the current environmental status and make corresponding intelligent decisions. The system controls the environment in multiple dimensions, including road types, traffic conditions, weather conditions, light conditions and other aspects. This multi-dimensional control helps the system to more accurately identify potential risks and adopt corresponding obstacle avoidance and driving strategies. Through precise algorithms and models, the system can ensure the accuracy of the working scene. This includes high-precision fusion of multiple data sources, real-time updating of environmental parameters, and dynamic adjustment of working scenes. This accuracy ensures the stability and reliability of the intelligent driving system in complex and changing environments.

[0100] Therefore, the working scene is frozen; multiple interactions are performed on the working scene, the processing level of the millimeter-wave radar, and the processing level of the vehicle's controller; the distributed management and control system of the millimeter-wave radar and the controller is determined based on the multiple interactions of the working scene, the processing level of the millimeter-wave radar, and the processing level of the vehicle's controller, thereby achieving multiple interactions of the working scene, the processing level of the millimeter-wave radar, and the processing level of the vehicle's controller, and ensuring the precise control of the distributed management and control system of the millimeter-wave radar and the controller.

[0101] Specifically, the intelligent driving system first captures and processes information about the vehicle's surroundings in real time by integrating data from multiple sensors (such as cameras, millimeter-wave radars, and lidars) and algorithm modules, thereby defining the current working scenario. The working scenario may include a variety of situations, such as urban congested roads, highway driving, rural road driving, and driving in severe weather conditions.

[0102] The system dynamically adjusts the processing level of the millimeter-wave radar according to the fixed working scene. For example, when driving on the highway, the system may increase the scanning frequency and accuracy of the millimeter-wave radar to better identify the vehicles and obstacles ahead; when driving on rural roads, the scanning frequency may be reduced to reduce unnecessary computing load. At the same time, the system will also adjust the processing level of the vehicle controller according to the working scene. This includes adjusting the vehicle's acceleration, braking, steering and other control strategies to adapt to different road and traffic conditions. For example, in severe weather conditions, the system may increase the safety distance, reduce the speed, and enable specific anti-skid control strategies. The target object information (such as distance, speed, angle, etc.) provided by the millimeter-wave radar is transmitted to the vehicle controller in real time. The controller formulates a corresponding driving strategy based on this information and the current working scene. This interaction ensures that the system can respond to environmental changes in a timely and accurate manner.

[0103] Based on the above multiple interaction processes, the intelligent driving system can determine an accurate millimeter-wave radar and controller distributed control system. This system is designed to achieve collaborative work between different components to ensure driving safety and driving experience. The system can dynamically adjust the processing level and interaction strategy of the millimeter-wave radar and vehicle controller according to changes in the working scene. This dynamic adjustment ensures that the system can always maintain the optimal working state. When determining the distributed control system, the system fully considers factors in multiple dimensions such as the working scene, millimeter-wave radar processing level, and vehicle controller processing level. This multi-dimensional control helps the system to understand the current environmental status more comprehensively and make accurate decisions. Through precise algorithms and models, the system can ensure accurate control of the millimeter-wave radar and controller distributed control system. This includes considerations such as real-time monitoring of each component, error correction, and exception handling.

[0104] At this time, the overall consideration of the working scene, the processing level of the millimeter-wave radar, and the processing level of the vehicle's controller is compatible, and multi-dimensional control of the working scene, the processing level of the millimeter-wave radar, and the processing level of the vehicle's controller is realized, ensuring the accuracy of the distributed control system of the millimeter-wave radar and the controller, thereby realizing the distributed control of the millimeter-wave radar and the controller.

[0105] Specifically, the intelligent driving system first captures and analyzes the information of the vehicle's surrounding environment in real time by integrating data from multiple sensors (such as cameras, millimeter-wave radars, lidars, etc.), thereby freezing the current working scene. These scenes may include driving on highways, congested urban roads, rural roads, driving in severe weather conditions, etc. The system needs to be able to accurately identify and classify these scenes to provide a basis for subsequent processing level adjustments. According to the frozen working scene, the system dynamically adjusts the processing level of the millimeter-wave radar. This includes adjusting the radar's scanning frequency, resolution, target recognition algorithm and other parameters to optimize the radar's ability to capture and process environmental information. For example, when driving on a highway, the system may increase the radar's scanning frequency and resolution to better identify vehicles and obstacles ahead; while when driving on rural roads, it may reduce the scanning frequency to reduce unnecessary computing load and energy consumption. At the same time, the system also needs to adjust the vehicle controller's processing level according to the working scene. This includes adjusting the controller's control strategy, response time, execution accuracy and other parameters to ensure that the vehicle can make correct driving decisions based on the current environment. For example, in severe weather conditions, the system may increase the safety distance, reduce the vehicle speed, and enable specific anti-skid control strategies; in congested urban roads, it may adopt a more intelligent following strategy to reduce congestion and accident risks.

[0106] In the process of realizing the millimeter-wave radar and controller distributed control system, the system needs to realize information fusion and collaborative work among multiple components. This includes data fusion between millimeter-wave radar and other sensors such as cameras and lidar, as well as information interaction and collaborative control between radar and controller. Through information fusion, the system can understand the current environmental status more comprehensively and make more accurate decisions; through collaborative work, the system can achieve complementary advantages and efficient cooperation among different components. In order to ensure the accuracy of the millimeter-wave radar and controller distributed control system, the system needs to use accurate algorithms and models for data processing and decision making. This includes using advanced filtering algorithms to denoise and filter radar data, using deep learning algorithms to accurately identify and classify target objects, and using optimization algorithms to dynamically adjust and optimize control strategies.

[0107] refer to Figure 6 , S15: In the distributed control system of the millimeter-wave radar and the controller, a plurality of combinations of data to be processed are determined based on a plurality of scene data transmitted by the millimeter-wave radar, a target object, and a processing space of the controller; a plurality of processing results are determined based on the plurality of combinations of data to be processed, the real-time driving data of the vehicle, and the processing logic of the controller;

[0108] In the specific implementation process of the present invention, the specific steps may be:

[0109] S151: Distributed control system of millimeter wave radar and controller;

[0110] S152: In the distributed control system of the millimeter-wave radar and the controller, a plurality of scene data transmitted by the millimeter-wave radar is collected. At this time, the plurality of scene data transmitted by the millimeter-wave radar includes scene data that exceeds the processing capability of the millimeter-wave radar.

[0111] S153: Associating a plurality of scene data transmitted by the millimeter wave radar, the target object, and the processing space of the controller;

[0112] S154: performing multiple interactions on the multiple scene data, target objects, and processing spaces of the controller transmitted by the millimeter wave radar, and performing multiple interactions on the multiple scene data, target objects, and processing spaces of the controller according to the multiple scene data, target objects, and processing spaces of the controller transmitted by the millimeter wave radar;

[0113] S155: Associating a plurality of to-be-processed data combinations, the real-time driving data of the vehicle, and the processing logic of the controller;

[0114] S156: Determine multiple processing results according to multiple combinations of data to be processed, the real-time driving data of the vehicle, and the processing logic of the controller.

[0115] In an embodiment of the present application, a distributed control system of a millimeter-wave radar and a controller is fixed, and a distributed control system of a millimeter-wave radar and a controller is introduced to control the distributed control system of a millimeter-wave radar and a controller.

[0116] Specifically, the distributed control system of millimeter-wave radar and controller usually consists of multiple millimeter-wave radar sensors, domain controllers, and related communication and data processing modules. The system aims to achieve comprehensive perception and intelligent control of the vehicle's surrounding environment through distributed layout and collaborative work. As a high-precision sensor, the millimeter-wave radar is responsible for transmitting and receiving millimeter-wave signals to detect information such as the distance, speed, and orientation of surrounding objects. These sensors are usually distributed in different positions such as the front, back, left, and right of the vehicle to provide all-round environmental perception capabilities. As the core processing unit of the system, the domain controller is responsible for receiving data from multiple millimeter-wave radars and performing tasks such as fusion calculation, target tracking, behavior prediction, and decision-making. The domain controller is connected to the millimeter-wave radar through a high-speed communication interface to ensure real-time transmission and processing of data. This module is responsible for realizing communication and data exchange between the millimeter-wave radar and the domain controller, as well as functions such as data preprocessing and post-processing. It uses efficient communication protocols and data formats to ensure the accuracy and reliability of data.

[0117] Using advanced data fusion algorithms, data from different millimeter-wave radars are fused to improve the accuracy and completeness of environmental perception. Millimeter-wave radars are calibrated regularly to ensure data consistency and accuracy between sensors. Advanced algorithms and models are used to track and predict the behavior of detected targets in real time to identify potential dangers and opportunities in advance. Based on the predicted behavior results of the target, the vehicle's driving strategy and the controller's control parameters are dynamically adjusted. Based on the fused data and target tracking results, the domain controller formulates the best driving strategy and control parameters.

[0118] At the same time, in the distributed management and control system of the millimeter-wave radar and the controller, multiple scene data transmitted by the millimeter-wave radar are collected. At this time, the multiple scene data transmitted by the millimeter-wave radar contain scene data that exceeds the processing capability of the millimeter-wave radar, which fully utilizes the processing capability of the millimeter-wave radar, and manages the scene data that exceeds the processing capability of the millimeter-wave radar, ensuring the accurate processing of the scene data that exceeds the processing capability of the millimeter-wave radar.

[0119] Specifically, the millimeter-wave radar continuously scans the surrounding environment and generates raw data containing multi-dimensional information such as distance, speed, and direction. The system collects these raw data in real time and performs preliminary format conversion and preprocessing for subsequent processing. The system evaluates the processing capabilities of the millimeter-wave radar in real time, including processing speed, data accuracy, algorithm efficiency, etc. Based on the evaluation results, the system can identify which scene data may exceed the processing capabilities of the radar. For scene data within the processing capabilities of the millimeter-wave radar, the system directly uses the radar's built-in algorithm for processing. For scene data that exceeds the processing capabilities, the system takes additional processing measures, such as using more powerful algorithms, increasing computing resources, or performing distributed processing.

[0120] Develop and apply more efficient algorithms to improve data processing speed and accuracy. Use machine learning or deep learning techniques to continuously optimize and adaptively adjust algorithms. Dynamically allocate computing resources, such as adding CPUs, GPUs, or dedicated processing units to cope with high-load scenarios. Implement resource load balancing to ensure real-time and stability of data processing. Divide data into multiple subtasks and process them in parallel on multiple processors or nodes. Ensure the consistency and accuracy of distributed processing through efficient communication protocols and data synchronization mechanisms. Cache data that exceeds processing capacity and wait for computing resources to be idle before processing. Preprocess data before processing, such as downsampling, filtering, or feature extraction, to reduce the amount of calculation and improve processing efficiency. Monitor abnormal conditions in the data processing process in real time to detect and handle faults in a timely manner. Implement fault recovery mechanisms to ensure that the system can quickly resume normal operation when a fault occurs.

[0121] Therefore, multiple scene data, target objects and processing spaces of the controller transmitted by the millimeter-wave radar are associated; multiple interactions are performed on the processing spaces of the multiple scene data, target objects and processing spaces of the controller transmitted by the millimeter-wave radar; and based on the multiple scene data, target objects and processing spaces of the controller transmitted by the millimeter-wave radar, multiple interactions of the processing spaces of the multiple scene data, target objects and processing spaces of the controller transmitted by the millimeter-wave radar are realized.

[0122] Specifically, the millimeter-wave radar transmits the collected multi-scenario data to the controller in real time. The controller receives and parses the data and extracts key information about the target object, such as position, speed, acceleration, etc. Based on the processing results, the controller sends control instructions to the actuator to realize the intelligent driving of the vehicle. The controller uses advanced algorithms to process the data transmitted by the millimeter-wave radar and identify the target object. The target object is continuously tracked and its status information is updated in real time. The vehicle's driving strategy is adjusted according to the dynamic changes of the target object. When processing data, the controller will consider its own processing capabilities and resource limitations. Through reasonable task scheduling and resource allocation, it ensures that the data transmitted by the millimeter-wave radar can be processed in a timely manner. At the same time, the controller will dynamically adjust its processing space according to the processing results to meet the needs of different scenarios.

[0123] Through multiple interactions, close cooperation between the millimeter-wave radar and the controller is achieved. The system's perception and response speed to the surrounding environment are improved. The vehicle can maintain safe driving in complex and changing road environments. Through reasonable task scheduling and resource allocation, resource waste and idleness are avoided. The overall performance and energy efficiency of the system are improved. Multiple interactions enable the system to detect and recover in time when a fault occurs. The reliability and stability of the system are improved. Multiple interactions enable the system to adapt to the needs of different scenarios. Whether it is a congested urban road section or a highway, the system can provide accurate perception and control capabilities.

[0124] Furthermore, multiple combinations of data to be processed, real-time driving data of the vehicle, and processing logic of the controller are associated; multiple processing results are determined based on the multiple combinations of data to be processed, real-time driving data of the vehicle, and processing logic of the controller, which is compatible with overall consideration of multiple combinations of data to be processed, real-time driving data of the vehicle, and processing logic of the controller, and realizes multi-dimensional control of multiple combinations of data to be processed, real-time driving data of the vehicle, and processing logic of the controller, ensuring the accuracy of multiple processing results, so as to facilitate subsequent management and control of multiple processing results.

[0125] Specifically, the system first identifies and classifies multiple combinations of data to be processed, which may come from sensors such as millimeter-wave radar, cameras, GPS, etc. According to the type and characteristics of the data, the system matches it with the processing logic of the controller to ensure that the data can be correctly parsed and processed. The vehicle's real-time driving data, such as speed, acceleration, steering angle, etc., are collected in real time and integrated into the processing flow. These data are combined with the controller's motion control logic to generate precise driving instructions. The controller dynamically adjusts its processing logic based on changes in the combination of real-time driving data and data to be processed. For example, when an obstacle is detected ahead, the controller may increase the weight of the obstacle tracking algorithm to improve the accuracy of obstacle avoidance.

[0126] Before the data enters the processing logic, the system pre-processes and verifies it to ensure the accuracy and completeness of the data. This includes operations such as data cleaning, denoising, and format conversion. The system uses advanced algorithms and models to optimize the processing logic to improve processing speed and accuracy. For example, deep learning technology is used to improve the accuracy of the target recognition algorithm. The system evaluates the processing results from multiple dimensions, including time efficiency, space efficiency, accuracy, etc. The accuracy of the processing results is further verified by comparing with other sensor data or historical data. The system has fault tolerance and exception handling capabilities, and can continue to operate in the event of data loss, sensor failure, etc. Through backup plans or degradation strategies, ensure that the system can provide reliable processing results under various conditions.

[0127] refer to Figure 7 , S16: determining the best processing result according to the multiple processing results, the previous processing data of the vehicle and the driving state of the vehicle, triggering the intelligent control of the vehicle based on the best processing result, and ensuring the multi-level precision control of the millimeter wave radar and the controller under synchronous operation;

[0128] In the specific implementation process of the present invention, the specific steps may be:

[0129] S161: freeze multiple processing results;

[0130] S162: associating a plurality of processing results, previous processing data of the vehicle, and a driving state of the vehicle, and performing multiple interactions on the plurality of processing results, previous processing data of the vehicle, and the driving state of the vehicle;

[0131] S163: Determine the best processing result based on multiple interactions of multiple processing results, previous processing data of the vehicle, and the driving state of the vehicle;

[0132] S164: triggering intelligent control of the vehicle based on the best processing result, and monitoring the intelligence level of the vehicle in real time;

[0133] S165: Dynamically manage the vehicle's intelligence level and ensure multi-level precision control of the millimeter-wave radar and controller working synchronously.

[0134] At this time, multiple processing results are frozen, and multiple processing results, the vehicle's previous processing data, and the vehicle's driving status are introduced, thereby associating multiple processing results, the vehicle's previous processing data, and the vehicle's driving status, and performing multiple interactions on the multiple processing results, the vehicle's previous processing data, and the vehicle's driving status, thereby realizing multiple interactions on multiple processing results, the vehicle's previous processing data, and the vehicle's driving status.

[0135] Specifically, the multi-interaction mechanism refers to the process of correlating and comprehensively analyzing multiple processing results, the vehicle's previous processing data, and the vehicle's driving status. This process involves the collection, integration, analysis, and utilization of data, aiming to improve the accuracy and reliability of the intelligent driving system.

[0136] Collect multiple processing results in real time, which may come from different sensors or algorithm modules, such as millimeter wave radar, camera, GPS, etc. Obtain the vehicle's previous processing data, including historical driving records, fault records, maintenance records, etc. Monitor the vehicle's driving status in real time, such as speed, acceleration, steering angle, braking status, etc. Integrate multiple processing results to form a comprehensive data set. Associate the vehicle's previous processing data with the current driving status to form a comparison between history and reality. Use advanced algorithms and models to conduct in-depth analysis of the integrated data. Identify patterns, trends, and anomalies in the data to extract useful information. Adjust the decision logic and control strategy of the intelligent driving system based on the analysis results. Use the analysis results to optimize the vehicle's driving route, speed, and safety.

[0137] By comprehensively analyzing multiple processing results and the vehicle's driving status, the system can more accurately judge the current environment and make corresponding decisions. Using the vehicle's past processing data, the system can identify potential problems and take measures in advance, thereby improving the reliability of the system. By continuously adjusting and optimizing decision logic and control strategies, the system can gradually adapt to different driving environments and conditions, thereby improving overall performance.

[0138] During driving, the system can detect obstacles in real time and plan obstacle avoidance routes. Through multiple interactive mechanisms, the system can more accurately determine the location and speed of obstacles, thereby ensuring the accuracy and safety of obstacle avoidance. The system can plan the optimal driving route based on real-time traffic information and vehicle status. Through multiple interactive mechanisms, the system can comprehensively consider multiple factors (such as road conditions, weather, vehicle performance, etc.) to provide more accurate navigation suggestions. During parking, the system can detect parking spaces in real time and control the vehicle to park. Through multiple interactive mechanisms, the system can more accurately determine the size and location of parking spaces, thereby ensuring the accuracy and safety of parking.

[0139] Therefore, the best processing result is determined based on multiple processing results, the vehicle's previous processing data, and multiple interactions of the vehicle's driving status; the vehicle's intelligent control is triggered based on the best processing result, and the vehicle's intelligence level is monitored in real time; the vehicle's intelligence level is dynamically managed and controlled, and multi-level precision control of the millimeter-wave radar and controller is ensured under synchronous operation, achieving precise control of the millimeter-wave radar and controller at different stages, releasing the processing pressure of the millimeter-wave radar, and better applying the computing power of the controller.

[0140] Specifically, the system collects multiple processing results in real time, which may come from different sensors (such as millimeter-wave radar, cameras, etc.) and algorithm modules. At the same time, the system also obtains the vehicle's previous processing data and current driving status. Using advanced algorithms and models, the system performs multiple interactive analyses on the collected data. This includes correlation analysis, trend prediction, anomaly detection, etc. between data. Through comprehensive analysis, the system selects the best one or several from multiple processing results. The best processing result is based on a comprehensive judgment of the current environment, vehicle status and past experience.

[0141] Based on the determined optimal processing result, the system triggers the vehicle's intelligent control mechanism. This may include automatic braking, steering adjustment, speed control and other operations. The system monitors the vehicle's intelligence level in real time, which is usually determined by evaluating the vehicle's autonomous driving capabilities in the current environment. The intelligence level may change dynamically due to factors such as environment, road conditions, weather, etc.

[0142] According to the intelligence level of real-time monitoring, the system dynamically adjusts the strategy and control parameters of intelligent driving. For example, in complex or dangerous environments, the system may reduce the intelligence level and increase the frequency of human intervention. When the millimeter-wave radar and the controller work synchronously, the system achieves multi-level precision control. This means that the system can maintain high-precision perception, decision-making and control capabilities at different stages.

[0143] The system reduces the processing pressure of the millimeter-wave radar through reasonable task allocation and optimization. For example, some data processing and analysis tasks are transferred to the controller for execution. The controller uses its powerful computing power to handle complex algorithms and decision-making tasks. This improves the overall performance and response speed of the system.

[0144] In the embodiment of the present invention, for the radar system, the radar system dynamically allocates signal processing tasks according to the actual road conditions. When encountering complex road scenes or ultra-long-distance road detection, the radar's own computing power cannot meet the signal processing requirements. The radar only performs part of the signal processing work, and the domain controller completes part of the signal processing work. This can provide higher computing power for radar signal processing to improve target detection performance.

[0145] Control the radar signal processing process. The radar RF front end generates millimeter wave signals. The millimeter waves propagate in the air, hit obstacles and are reflected back to be received by the RF front end, mixed, amplified, and sampled by the analog-to-digital converter to form an intermediate frequency digital sampling signal. The radar signal processor performs the first fast Fourier transform on the intermediate frequency digital sampling signal to obtain a one-dimensional range spectrum. The radar signal processor performs the second fast Fourier transform on the one-dimensional range spectrum to obtain a two-dimensional range-velocity spectrum.

[0146] The radar signal processor performs target detection on the two-dimensional range-velocity spectrum according to a certain threshold, obtains the original target information, and outputs N1 groups of original target information; the radar signal processor calculates the N1 groups of original target information to obtain the speed, distance, horizontal and / or vertical angle, reflection intensity, and radar point cloud of N2 targets; the radar signal processor performs clustering, classification, and tracking calculations on the radar point cloud containing N2 targets to obtain N3 target tracks, and outputs the target tracks to the domain controller;

[0147] At this time, when the radar determines that the required detection accuracy and / or detection range of the current scene exceeds the computing power of the radar's own signal processor, the radar sends a message to the domain controller, requesting the domain controller to allocate computing power to participate in radar signal processing. The signal processor inside the radar completes S1 to S4, and sends the original target information to the domain controller through the vehicle bus connecting the radar and the domain controller. The domain controller completes S5 to S6 to form the target track and perform subsequent fusion, decision-making, and control. The algorithm for executing S5 and S6 in the domain controller can be different from the algorithm for executing S5 and S6 in the radar. Considering that the domain controller has greater computing power and memory, the domain controller can run algorithms with higher accuracy, higher resolution, and more targets.

[0148] The radar determines that the detection accuracy and / or detection range exceeds the radar's own signal processor computing power according to any one, any two, or all of the following conditions: the number of target original information groups N1 is continuously equal to the maximum number of target original information groups allowed by the radar or higher than a certain limit value, such as 80% of the maximum number of target original information groups within a certain time T1; the number of radar point cloud targets N2 is continuously equal to the maximum number of radar point cloud targets allowed by the radar or higher than a certain limit value, such as 80% of the maximum number of radar point cloud targets within a certain time T2; the number of target tracks N3 is continuously equal to the maximum number of target tracks allowed by the radar or higher than a certain limit value, such as 80% of the maximum number of target tracks within a certain time T3;

[0149] Applying for domain controller computing power for millimeter wave radar:

[0150] S11, millimeter-wave radar A sends information to the domain controller through the vehicle bus, requesting the domain controller to allocate computing power to the radar for signal processing; S12, the domain controller receives the request for computing power allocation from millimeter-wave radar A, and the domain controller determines whether it is reasonable to allocate computing power to millimeter-wave radar A based on the current vehicle position and direction of travel, and whether there are requests from other millimeter-wave radars; if so, S13, the domain controller sends a message to millimeter-wave radar A, agreeing to the request sent by radar A; S14, millimeter-wave radar A receives the message from the domain controller, switches the radar waveform, improves the radar detection resolution and / or detection range, increases the maximum number of target original information groups allowed by the radar, and sends the target original information to the domain controller through the vehicle bus; stops calculating the radar point cloud and target track to save computing power and memory;

[0151] The domain controller receives the original target information sent by the millimeter-wave radar A, executes the algorithm to calculate the radar points S15 within the detection area of ​​the millimeter-wave radar A, and determines that the millimeter-wave radar A no longer needs the computing power of the domain controller for signal processing based on the current vehicle position and travel direction, as well as the number of targets and / or point clouds within the detection area of ​​the millimeter-wave radar. The domain controller sends a message to the millimeter-wave radar A, commanding the radar to return to normal working mode;

[0152] If not, S16, the domain controller sends a message to the millimeter-wave radar A to reject the request of the millimeter-wave radar A; S17, the millimeter-wave radar A receives the message sent by the domain controller and is not allowed to request the allocation of computing power for a period of time;

[0153] The domain controller determines the vehicle's position based on the navigation map and the direction of travel based on the navigation route, thereby flexibly allocating radar signal processing power:

[0154] When the vehicle is about to change lanes to the right, in order to prevent the vehicle behind in the right lane from approaching the vehicle quickly and rear-ending it, the domain controller sends instructions to the right rear corner radar to expand the detection range and improve the detection accuracy, and allocates the domain controller's computing power to process the original target information sent by the right rear corner radar; in order to save computing power, the domain controller can ignore the left lane information.

[0155] When the vehicle is about to change lanes to the left, in order to prevent the vehicle behind in the left lane from approaching the vehicle quickly and rear-ending it, the domain controller sends a command to the left rear corner radar, asking it to expand its detection range, improve detection accuracy, and allocate computing power to process the original target information sent by the left rear corner radar. In order to save computing power, the domain controller can ignore the right lane information.

[0156] When a vehicle turns right at an intersection, in order to prevent vehicles crossing from the left from hitting the vehicle, the domain controller sends instructions to the left front corner radar to expand the detection range, improve the detection accuracy, and allocate computing power to process the original target information sent by the left front corner radar;

[0157] When a vehicle goes straight through an intersection or turns left at an intersection, in order to prevent vehicles crossing from the left or right sides from hitting the vehicle, the domain controller sends instructions to the left front corner radar and the right front corner radar to expand the detection range and improve the detection accuracy, and allocates computing power to process the original target information sent by the left front corner radar and the right front corner radar; in order to save computing power, the domain controller can ignore the information sent by the left rear corner radar and the right rear corner radar;

[0158] When the vehicle is in a mixed area of ​​people and vehicles such as parking lots, underground garages, schools, and communities, and the vehicle is moving forward, in order to prevent the vehicle from hitting pedestrians and / or stationary objects, the domain controller sends instructions to the front radar, left front corner radar, and right front corner radar to improve the detection accuracy, and allocates computing power to process the original target information sent by the front radar, left front corner radar, and right front corner radar; in order to save computing power, the domain controller can ignore the information sent by the left rear corner radar and the right rear corner radar;

[0159] When the vehicle is in a mixed area such as a parking lot, underground garage, school, or community, and the vehicle is moving backward, in order to prevent the vehicle from hitting pedestrians and / or stationary objects, the domain controller sends instructions to the left rear corner radar and the right rear corner radar to improve the detection accuracy and allocate computing power to process the original target information sent by the left rear corner radar and the right rear corner radar; in order to save computing power, the domain controller can ignore the information sent by the front radar, the left front radar, and the right front corner radar;

[0160] See also Figure 8 , Figure 8 It is a schematic diagram of the structural composition of the distributed control system of the millimeter wave radar in an embodiment of the present invention.

[0161] like Figure 8 As shown, a distributed control system of a millimeter wave radar, the distributed control system of the millimeter wave radar includes:

[0162] The acquisition module 21 is used to determine a plurality of digital acquisition signals based on the millimeter wave signal of the millimeter wave radar when the vehicle is in a driving state;

[0163] A target detection module 22, used to determine a corresponding target object according to a plurality of digital acquisition signals, an image captured by the vehicle and a target detection system;

[0164] A scene module 23, used to determine a corresponding target object according to a plurality of digital acquisition signals, an image captured by the vehicle and a target detection system;

[0165] A distributed control module 24 is used to determine a corresponding working scene according to a plurality of scene data, the millimeter-wave radar and environmental parameters, and to determine a distributed control system of the millimeter-wave radar and the controller according to the working scene, the processing level of the millimeter-wave radar and the processing level of the vehicle controller;

[0166] The processing result module 25 is used to determine a plurality of data combinations to be processed based on a plurality of scene data transmitted by the millimeter-wave radar, a target object and a processing space of the controller in the distributed control system of the millimeter-wave radar and the controller; and to determine a plurality of processing results based on the plurality of data combinations to be processed, the real-time driving data of the vehicle and the processing logic of the controller;

[0167] The intelligent control module 26 is used to determine the best processing result based on multiple processing results, the vehicle's previous processing data and the vehicle's driving status, and trigger the vehicle's intelligent control based on the best processing result, and ensure multi-level precision control of the millimeter wave radar and the controller under synchronous operation.

[0168] In addition, the distributed control method and system of the millimeter-wave radar provided in the embodiments of the present invention are introduced in detail above. Specific examples are used herein to illustrate the principles and implementation methods of the present invention. The description of the above embodiments is only used to help understand the method of the present invention and its core idea; for those skilled in the art, according to the ideas of the present invention, there will be changes in the specific implementation methods and application scopes. In summary, the content of this specification should not be understood as limiting the present invention.

Claims

1. A distributed control method for millimeter wave radar, characterized in that: Applied to distributed control scenarios of millimeter wave radar; The distributed control method of the millimeter wave radar includes: When the vehicle is in a driving state, a plurality of digital acquisition signals are determined based on the millimeter wave signal of the millimeter wave radar; Determine the corresponding target object according to multiple digital acquisition signals, images taken by the vehicle, and the target detection system; Determining a plurality of scene data based on directional detection of target objects and vehicles; Determine the corresponding working scene according to multiple scene data, millimeter-wave radar and environmental parameters, and determine the distributed control system of millimeter-wave radar and controller according to the working scene, the processing level of millimeter-wave radar and the processing level of the vehicle controller; In the distributed control system of the millimeter-wave radar and the controller, multiple combinations of data to be processed are determined based on multiple scene data transmitted by the millimeter-wave radar, target objects, and the processing space of the controller; multiple processing results are determined based on the multiple combinations of data to be processed, the real-time driving data of the vehicle, and the processing logic of the controller; The best processing result is determined based on multiple processing results, the vehicle's previous processing data, and the vehicle's driving status, and the vehicle's intelligent control is triggered based on the best processing result, ensuring multi-level precision control of the millimeter-wave radar and the controller under synchronous operation.

2. The distributed control method of millimeter wave radar according to claim 1, characterized in that: The method of determining a plurality of digital acquisition signals based on the millimeter wave signal of the millimeter wave radar when the vehicle is in a driving state includes: Real-time monitoring of vehicle status; When the vehicle is in motion, the millimeter-wave radar detects external objects as the vehicle moves dynamically; Collecting millimeter wave signals of the millimeter wave radar based on external detection of the millimeter wave radar; A plurality of digital acquisition signals are determined according to signal processing of a millimeter wave signal of a millimeter wave radar.

3. The distributed control method of millimeter wave radar according to claim 2, characterized in that: The method of determining the corresponding target object according to the plurality of digital acquisition signals, the image captured by the vehicle and the target detection system includes: Freeze multiple digital acquisition signals; Determine the detection data of the millimeter wave radar according to the multi-level transformation of the plurality of digital acquisition signals; Associating the millimeter wave radar and the camera, and collecting images taken by the vehicle based on the circumferential detection of the camera; Correlate the detection data of the millimeter wave radar, the images taken by the vehicle, and the target detection system; Determine the first target information according to the detection data of the millimeter wave radar and the image taken by the vehicle, and determine the second target information according to the detection data of the millimeter wave radar and the target detection system; The corresponding target object is determined according to the first target information, the second target information and the millimeter wave radar.

4. The distributed control method of millimeter wave radar according to claim 3, characterized in that: The determining of a plurality of scene data based on the directional detection of the target object and the vehicle includes: Freeze the target object; Collect the real-time relative relationship between the target object and the vehicle; A directional detection system based on the real-time relative relationship between the target object and the vehicle; Trigger directional detection of target objects and vehicles based on the directional detection system; A plurality of scene data are determined based on the directional detection of the target object and the vehicle.

5. The distributed control method of millimeter wave radar according to claim 4, characterized in that: The method of determining a corresponding working scene according to a plurality of scene data, a millimeter-wave radar and environmental parameters, and determining a distributed control system of the millimeter-wave radar and the controller according to the working scene, the processing level of the millimeter-wave radar and the processing level of the vehicle controller includes: Freeze multiple scene data; Collecting environmental parameters based on vehicle environmental detection; Associating multiple scene data, millimeter-wave radars, and environmental parameters, and determining corresponding working scenes according to the multiple scene data, millimeter-wave radars, and environmental parameters; Freeze the working scene; Multiple interactions between the working scenario, the processing level of the millimeter wave radar, and the processing level of the vehicle's controller; The distributed control system of the millimeter-wave radar and the controller is determined based on multiple interactions of the working scenario, the processing level of the millimeter-wave radar, and the processing level of the vehicle's controller.

6. The distributed control method of millimeter wave radar according to claim 5, characterized in that: In the distributed control system of the millimeter wave radar and the controller, a plurality of combinations of data to be processed are determined based on a plurality of scene data transmitted by the millimeter wave radar, a target object, and a processing space of the controller; Based on a combination of multiple data to be processed, the real-time driving data of the vehicle and the processing logic of the controller, multiple processing results are determined, including: Distributed control system of millimeter-wave radar and controller; In the distributed control system of the millimeter-wave radar and the controller, multiple scene data transmitted by the millimeter-wave radar are collected. At this time, the multiple scene data transmitted by the millimeter-wave radar contain scene data that exceeds the processing capability of the millimeter-wave radar; Correlate multiple scene data, target objects and controller processing space delivered by millimeter wave radar; Multiple interactions are performed on multiple scene data, target objects and processing spaces of the controller transmitted by the millimeter-wave radar, and based on the multiple scene data, target objects and processing spaces of the controller transmitted by the millimeter-wave radar.

7. The distributed control method of millimeter wave radar according to claim 6, characterized in that: In the distributed control system of the millimeter wave radar and the controller, a plurality of combinations of data to be processed are determined based on a plurality of scene data transmitted by the millimeter wave radar, a target object, and a processing space of the controller; Determining multiple processing results based on multiple combinations of data to be processed, real-time driving data of the vehicle, and processing logic of the controller also includes: Associating multiple data combinations to be processed, real-time driving data of the vehicle, and processing logic of the controller; A plurality of processing results are determined according to a plurality of combinations of data to be processed, real-time driving data of the vehicle and a processing logic of the controller.

8. The distributed control method of millimeter wave radar according to claim 7, characterized in that: The method determines the best processing result based on multiple processing results, the vehicle's previous processing data, and the vehicle's driving status, triggers the vehicle's intelligent control based on the best processing result, and ensures multi-level precision control of the millimeter-wave radar and the controller under synchronous operation, including: Freeze multiple processing results; Associating multiple processing results, previous processing data of the vehicle, and the driving status of the vehicle, and performing multiple interactions on the multiple processing results, previous processing data of the vehicle, and the driving status of the vehicle; The best processing result is determined based on multiple interactions of multiple processing results, past processing data of the vehicle, and the driving state of the vehicle.

9. The distributed control method of millimeter wave radar according to claim 8, characterized in that: The method further includes determining the best processing result based on multiple processing results, the previous processing data of the vehicle and the driving state of the vehicle, triggering the intelligent control of the vehicle based on the best processing result, and ensuring the multi-level precision control of the millimeter wave radar and the controller under synchronous operation, and further includes: Trigger intelligent control of the vehicle based on the best processing results and monitor the vehicle's intelligence level in real time; Dynamically manage the vehicle's intelligence level and ensure multi-level precision control of the millimeter-wave radar and controller working synchronously.

10. A distributed control system for millimeter wave radar, characterized in that: The distributed control system of the millimeter wave radar is applied to the distributed control method of the millimeter wave radar as claimed in any one of claims 1 to 9, and the distributed control system of the millimeter wave radar includes: An acquisition module, used for determining a plurality of digital acquisition signals based on the millimeter wave signal of the millimeter wave radar when the vehicle is in a driving state; A target detection module, used to determine the corresponding target object based on multiple digital acquisition signals, images taken by the vehicle and a target detection system; A scene module, for determining a plurality of scene data based on directional detection of a target object and a vehicle; A distributed control module is used to determine the corresponding working scene according to multiple scene data, millimeter-wave radar and environmental parameters, and determine the distributed control system of the millimeter-wave radar and the controller according to the working scene, the processing level of the millimeter-wave radar and the processing level of the vehicle controller; A processing result module is used to determine a plurality of combinations of data to be processed based on a plurality of scene data transmitted by the millimeter-wave radar, a target object, and a processing space of the controller in a distributed control system of the millimeter-wave radar and the controller; and to determine a plurality of processing results based on the plurality of combinations of data to be processed, the real-time driving data of the vehicle, and the processing logic of the controller; The intelligent control module is used to determine the best processing result based on multiple processing results, the vehicle's previous processing data and the vehicle's driving status, trigger the vehicle's intelligent control based on the best processing result, and ensure multi-level precision control of the millimeter-wave radar and the controller under synchronous operation.

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