Detection method, control method and device

Abstract

A detection method, a control method and devices can be applied to the fields of automatic driving, intelligent driving or surveying and mapping and the like. The objective of the invention is to improve timeliness of target motion state detection and reduce response time for target motion. The method comprises the following steps: acquiring an echo signal obtained by detecting a first target in a first time unit, determining the relationship between the speed and time of the first target according to the echo signal, and sending first information determined based on the corresponding relationship between the speed and time to a control device, the control device is used for making an accurate and timely response according to the movement condition of the first target. Wherein the first information comprises at least one of the corresponding relation between the speed and the time of the first target, the acceleration information of the first target or the motion state information of the first target. Wherein the acceleration information of the first target is determined according to the corresponding relation between the speed and the time, and the motion state information of the first target is determined according to the acceleration information of the first target.

Description

Technical Field

[0001] This application relates to the field of detection technology, and in particular to a detection method, control method and apparatus. Background Technology

[0002] Environmental perception in intelligent driving vehicles is primarily achieved through sensors such as cameras, millimeter-wave radar, and lidar. Among these, millimeter-wave radar is a sensor that can directly measure the velocity of a target. Current standard interface specifications stipulate that millimeter-wave radar detection of the acceleration information of moving targets is generally based on object-level calculations; specifically, the target's acceleration is calculated from multiple frames of collected data.

[0003] However, the acquisition and processing time for multi-frame data is at least several hundred milliseconds. In actual vehicle driving scenarios, the time from when the vehicle in front suddenly brakes to a complete stop in an emergency is only several hundred milliseconds. The above-mentioned multi-frame processing and calculation method cannot provide a timely response for the vehicle in an emergency, which is not conducive to the safe driving of the vehicle. Summary of the Invention

[0004] This application provides a detection method, control method, and apparatus to improve vehicle driving safety.

[0005] In a first aspect, this application proposes a detection method applied to a detection device, comprising: acquiring an echo signal obtained from detecting a first target within a first time unit, determining the correspondence between the speed and time of the first target based on the echo signal, and sending first information determined based on the correspondence to a control device; wherein the first information includes, but is not limited to: the correspondence between the speed and time of the first target, acceleration information of the first target, or motion state information of the first target; wherein the acceleration information of the first target is determined based on the correspondence between the speed and time of the first target, and the motion state information of the first target is determined based on the acceleration information of the first target.

[0006] In the above scheme, by analyzing the echo signal of the detected target, the correspondence between the target's speed and time is obtained. Based on this correspondence, first information characterizing the target's motion state is determined and sent to the control device for the control device to decide the vehicle's response mode. Compared to traditional schemes that require multiple frames to detect and perceive the target's motion state, the scheme of this application analyzes the echo signal, which can complete the perception of the target's motion state within tens of milliseconds of detection time, improving the timeliness of motion state perception and reducing the response time of the control device to the target's motion state, thus better protecting user safety.

[0007] In one possible implementation, when sending the first information to the control device, the first information can be sent through the detection-level interface of the detection device. The detection device includes a detection-level interface and a target-level interface. In conventional schemes, the target's acceleration, obtained through multi-frame detection of the target, is sent to the control device through the target-level interface. This application analyzes the target's motion state within a single frame of tens of milliseconds of detection time and sends the analysis to the control device through the detection-level interface.

[0008] In one possible implementation, the first objective is determined according to a set rule; or, the first objective is determined based on the distance between the vehicle and other vehicles in the detection environment.

[0009] In the above scheme, the detection device can select the first target to be detected from multiple targets included in the driving environment according to the set rules, or it can adaptively select the first target based on the driving environment, such as selecting a target that is close to the vehicle and poses a threat to the driving safety of the vehicle.

[0010] In one possible implementation, when determining the correspondence between the velocity and time of the first target based on the echo signal, the velocity of the first target at different times can be determined within one frame of the detected echo signal.

[0011] In the above scheme, the detected echo signal of a frame includes echo signals of different time periods within the first time unit, so the speed at different times can be obtained, thereby determining the correspondence between speed and time.

[0012] In one possible implementation, determining the velocity of the first target at different times specifically includes: segmenting the echo signal to obtain multiple sub-echo signals; and determining the velocity of the first target corresponding to each of the multiple echo signals.

[0013] In one possible implementation, determining the velocity of the first target at different times specifically includes: performing sliding window processing on the echo signal to obtain multiple sub-echo signals; and determining the velocity of the first target corresponding to each of the multiple echo signals.

[0014] The above scheme proposes two methods to determine the velocity of the first target at different times: the sub-echo signal can be obtained by sliding window, or the signal can be segmented to obtain the sub-echo signal, and then the velocity can be determined for each sub-echo signal.

[0015] In one possible implementation, the motion state information of the first target includes at least one of the following: uniform motion state, rapidly accelerating motion state, accelerating motion state, rapidly decelerating motion state, or decelerating motion state.

[0016] In one possible implementation, the motion state information of the first target also includes the confidence level of the corresponding motion state. The confidence level of each motion state is used to characterize the degree of confidence that the first target is in each motion state.

[0017] In one possible implementation, the confidence level of the motion state corresponding to the first target is calculated based on the error between the acceleration information of the first target and the set acceleration of the motion state corresponding to the first target.

[0018] In the above scheme, different motion states have different set accelerations. After determining the acceleration of the first target, the confidence level of the first target in each motion state can be determined based on the error between the acceleration of the first target and the set acceleration of each motion state.

[0019] In one possible implementation, the acceleration information of the first target includes the acceleration of the first target and the acceleration error, wherein the acceleration error is determined based on the signal-to-noise ratio of the echo signal; the acceleration and the acceleration error are combined to determine the error between the acceleration of the first target and the set acceleration.

[0020] In the above scheme, the acceleration error obtained from detecting the first target is determined based on the signal-to-noise ratio of the echo signal of the first target, and the acceleration and acceleration error are combined to determine the motion state.

[0021] In one possible implementation, the echo signal includes at least one of the following: the echo signal with the strongest received intensity among the plurality of echo signals received within the first time unit; and the echo signal with the earliest received time among the plurality of echo signals received within the first time unit.

[0022] In the above scheme, the detection device not only selects the target to be detected from the driving environment, but also selects the echo signal used for motion state detection from the echo signals returned by multiple points contained in the target. Among them, the echo signal with high signal strength has a high signal-to-noise ratio and is less affected by interference from other targets; the earlier the reception time, the more likely it is to be the point in the corresponding target that is closest to the vehicle, and the echo signal returned by the closest point is used for motion state detection.

[0023] Secondly, this application proposes a control method applied to a control device, comprising: receiving first information from a detection device, the first information being determined based on an echo signal obtained from detecting a first target within a first time unit; determining the motion state of the first target based on the first information, and controlling a vehicle to avoid the first target based on the motion state of the first target; the first information comprising at least one of the following: a correspondence between the speed of the first target and time, acceleration information of the first target, or motion state information of the first target; wherein the acceleration information of the first target is determined based on the correspondence between the speed of the first target and time, and the motion state information of the first target is determined based on the acceleration information of the first target.

[0024] In one possible implementation, the control device is connected to the detection level interface of the detection device, and the first information is sent by the detection device through the detection level interface.

[0025] In one possible implementation, the first objective is determined according to a set rule; or, the first objective is determined according to the positional relationship between the vehicle and other vehicles in the detection environment.

[0026] In one possible implementation, the motion state information includes at least one of the following: uniform motion state, rapidly accelerating motion state, accelerating motion state, rapidly decelerating motion state, or decelerating motion state.

[0027] In one possible implementation, the motion state information of the first target also includes the confidence level of the motion state corresponding to the first target.

[0028] In one possible implementation, the confidence level of the motion state corresponding to the first target is calculated based on the error between the acceleration information of the first target and the set acceleration of the motion state corresponding to the first target.

[0029] In one possible implementation, the acceleration information of the first target includes the acceleration of the first target and the acceleration error, wherein the acceleration error is determined based on the signal-to-noise ratio of the echo signal; the acceleration and the acceleration error are combined to determine the error between the acceleration of the first target and the set acceleration.

[0030] Thirdly, this application provides a detection device that has the function of implementing the method of the first aspect or any of the designs in the first aspect. For example, the detection device includes modules, units or means for performing the operations involved in the method of the first aspect or any of the designs in the first aspect. The modules, units or means can be implemented by software, or by hardware, or by a combination of software and hardware.

[0031] In one possible implementation, the detection device may include interface circuitry and one or more processors. The one or more processors are coupled to a memory. The memory stores part or all of the necessary computer program or instructions for implementing the functions involved in the method of implementing the first aspect or any of the designs in the first aspect. The one or more processors can execute the computer program or instructions, which, when executed, cause the detection device to implement the method of the first aspect or any of the designs or examples in the first aspect. The interface circuitry is used to implement communication functions within the detection device and / or communication functions between the detection device and other devices or components.

[0032] Fourthly, this application provides a control device that has the function of implementing the method of the second aspect or any of the designs in the second aspect. For example, the control device includes modules, units or means for performing the operations involved in the method of the second aspect or any of the designs in the second aspect. The modules, units or means can be implemented by software, or by hardware, or by a combination of software and hardware.

[0033] In one possible implementation, the control device includes interface circuitry and one or more processors. The one or more processors are coupled to a memory. The memory stores part or all of the necessary computer program or instructions for implementing the functions involved in the method of implementing the second aspect or any of the designs in the second aspect. The one or more processors are executable to carry out the computer program or instructions, causing the control device to implement the methods in the second aspect or any of the designs or examples in the second aspect. The interface circuitry is used to implement communication functions within the control device and / or communication functions between the control device and other devices or components.

[0034] Fifthly, this application provides a detection system, including a detection device and a control device, wherein the detection device is used to perform the method in the first aspect or any possible design of the first aspect; and the control device is used to perform the method in the second aspect or any possible design of the second aspect.

[0035] Sixthly, this application provides a terminal device that includes the detection system described in the fifth aspect, or the detection device described in the third aspect, and / or the control device described in the fourth aspect.

[0036] In a seventh aspect, this application provides a chip including at least one processor and interface circuitry. Further, optionally, the chip may also include a memory, wherein the processor is configured to execute computer programs or instructions stored in the memory, causing the chip to perform the methods in any possible implementation of the first or second aspect described above.

[0037] Eighthly, this application provides a computer-readable storage medium storing a computer program or instructions that, when executed by a detection device, cause the detection device to perform any possible implementation of the first or second aspect described above.

[0038] Ninthly, this application provides a computer program product comprising a computer program or instructions that, when executed by a detection device, cause the detection device to perform any possible implementation of the first or second aspect described above.

[0039] The beneficial effects of any of the designs in the second to ninth aspects mentioned above can be referred to the beneficial effects that the corresponding designs in the first aspect mentioned above can achieve, and this application will not repeat them one by one. Attached Figure Description

[0040] Figure 1 An illustrative diagram shows one possible application scenario of this application;

[0041] Figure 2 An exemplary diagram illustrates the content of information transmitted through a target-level interface.

[0042] Figure 3A An exemplary schematic diagram of the architecture of a possible detection system according to this application is shown;

[0043] Figure 3B An exemplary schematic diagram of the architecture of a possible detection device according to this application is shown;

[0044] Figure 4 An exemplary flowchart of one possible detection method according to this application is shown;

[0045] Figure 5 An exemplary diagram illustrating a possible correspondence between speed and time according to this application is provided.

[0046] Figure 6 An exemplary schematic diagram illustrates one possible format for uploading the first information according to this application;

[0047] Figure 7 An exemplary flowchart of another possible detection method of this application is shown;

[0048] Figure 8 An exemplary flowchart of another possible detection method of this application is shown;

[0049] Figure 9 An exemplary flowchart of another possible detection method of this application is shown;

[0050] Figure 10 An exemplary schematic diagram of a possible structure of a detection device provided in this application is shown;

[0051] Figure 11 An exemplary schematic diagram of another possible structure of the control device provided in this application is shown. Detailed Implementation

[0052] The embodiments of this application will now be described in detail with reference to the accompanying drawings.

[0053] The following provides explanations for some of the terms used in this application. It should be noted that these explanations are for the convenience of those skilled in the art and do not constitute a limitation on the scope of protection claimed in this application.

[0054] (1) Chirp signal: This refers to a signal in which the carrier frequency increases linearly during the pulse duration, also known as a linear frequency modulated signal. Chirp signal is a commonly used detection signal in millimeter-wave radar, with high range resolution and anti-interference capability. When the pulse changes to the low frequency ground, it emits a sound that sounds like the chirping of birds, hence the name "chirp signal".

[0055] (2) Point cloud: This refers to the sampled points obtained after a detection device probes an object. Point cloud data is a set of vectors in a three-dimensional coordinate system. The set of point clouds obtained after a detection device probes and samples the surface of an object can be called a point cloud set. The detection device can simultaneously probe and sample multiple objects, and the resulting set of point cloud data can include point cloud sets corresponding to multiple objects. It should be noted that, in the embodiments of this application, a frame (or single frame) of point cloud data refers to a set of point cloud data acquired and processed at one sampling moment.

[0056] (3) Joint Time-Frequency Analysis (JTFA): Also known as time-frequency analysis, this is a signal processing method that clearly describes the energy density or intensity of a signal at different times and frequencies. By analyzing the time-frequency distribution of a signal, the Doppler frequency at each moment can be obtained. Examples of time-frequency analysis techniques include the Short-Time Fourier Transform (STFT). The Short-Time Fourier Transform, also known as the windowed Fourier Transform, is an effective time-frequency analysis method. Its basic idea is to select a localized time-frequency window function, divide the time-domain signal into multiple fixed-duration time windows on the time axis, perform sliding window processing on the signal, and then perform a Fourier transform on the signal within each time window to obtain the time-varying spectrum of the signal.

[0057] (4) Millimeter-wave radar: This is a type of radar that operates in the millimeter-wave band, typically between 30GHz and 300GHz, with wavelengths of 1-10mm, falling between microwaves and centimeter waves. Compared to centimeter-wave radar, millimeter-wave radar is smaller, easier to integrate, and has higher spatial resolution, making it commonly used in vehicles to assist in autonomous driving. In terms of hardware structure, vehicle-mounted millimeter-wave radar mainly consists of an antenna, a transceiver module, and a signal processing module. The working principle of millimeter-wave radar is as follows: it uses a high-frequency circuit to generate electromagnetic waves with a specific modulation frequency, and transmits and receives electromagnetic waves reflected from the target through an antenna. The parameters of the transmitted and received electromagnetic waves are used to calculate various parameters of the target. It can also simultaneously measure the distance, speed, and azimuth of multiple targets. Distance measurement involves continuously sending millimeter-wave signals to the target, then using a sensor to receive the millimeter waves returning from the object, and obtaining the distance to the target by detecting the round-trip time of the millimeter waves. Velocity measurement is based on the Doppler effect. By calculating the frequency change of the radar wave returning to the receiving antenna, the target's velocity relative to the radar can be obtained. Simply put, the relative velocity is proportional to the frequency change. Azimuth measurement is performed by calculating the phase difference of radar waves reflected from the same target by the antenna array to obtain the target's azimuth angle.

[0058] (5) Frequency Modulated Continuous Wave (FMCW): FMCW technology is a key technology used in radar ranging. Its basic principle is that the transmitted wave is a high-frequency continuous wave, and its frequency changes with time according to a triangular wave law. The received echo frequency follows the same frequency change law as the transmitted wave, but there is a time delay, which leads to a difference in frequency at the same time. By measuring the beat frequency of the two signals, the distance to the target can be obtained. Millimeter-wave radars typically use FMCW waveforms. FMCW waveforms can achieve large bandwidth and long coherence accumulation time, thus possessing high ranging, velocity measurement accuracy, and resolution capabilities. Millimeter-wave radars using FMCW waveforms can also be called FMCW millimeter-wave radars.

[0059] (6) FMCW LiDAR: Combining the signal processing methods of microwave radar with laser technology, FMCW LiDAR achieves multi-dimensional and higher-sensitivity detection by precisely controlling and adjusting the micron-level wavelength of the laser. Specifically, when detecting a target, the FMCW LiDAR emits detection light towards the target in the detection area according to the set detection field of view, receives the local oscillator light and the echo light reflected back from the target object, and outputs the corresponding electrical signal. The signal processing unit then processes the electrical signal to obtain a point cloud map. Through the point cloud map, data such as the target's distance, azimuth, height, velocity, attitude, and shape can be obtained, thereby achieving laser detection.

[0060] The preceding text introduced some of the terms used in this application. The following text introduces the possible application scenarios of this application.

[0061] In one possible implementation, the detection method can be applied to a detection device, which can be mounted on a vehicle. The detection device can be, for example, millimeter-wave radar or lidar. For example, see [reference needed]. Figure 1 The diagram illustrates one possible application scenario of this application. In this scenario, the detection device is installed on the front bumper of the vehicle as an example. However, it should be understood that the detection device can also be installed in any or more of the six directions of the vehicle: front, rear, left, right, up, and down, such as around the headlights, around the rearview mirrors, near the doors, on the rear bumper, behind the windshield, or on the roof, to capture information about the vehicle's surrounding environment. When the detection device is installed behind the windshield, the requirement for no stone collision is lower, it does not affect the vehicle's appearance, and the windshield itself has window heating and defogging functions as well as wiper cleaning functions.

[0062] Taking millimeter-wave radar as an example, the working principle of the detection device is as follows: the detection device emits millimeter waves (such as millimeter waves with a carrier frequency of 77 GHz) into the detection area. If a target exists in the detection area, the target can reflect the received millimeter waves back to the detection device (the reflected millimeter waves can be called echo signals). The detection device processes the echo signals to determine the target's association information. For example, the detection device can use FMCW waveforms, and the signal emitted by the transmitting antenna is a chirp signal. The detection device can perform time-frequency analysis processing on the chirp signal and the echo signal to determine the target information. Another example is that the detection device can acquire physical environment information around the vehicle body in real time or periodically, such as the relative distance (Range), relative speed (Velocity), relative angle (such as horizontal angle (Azimuth Angle)), and elevation angle (Elevation) between the vehicle and other objects, etc. Then, based on the detected physical environment information, it performs target tracking and identification classification, and then combines this with vehicle dynamic information for data fusion. After making reasonable decisions, the system informs or warns the driver through various means such as sound, light, and touch, or intervenes proactively in the vehicle in a timely manner, thereby ensuring the safety and comfort of the driving process and reducing the probability of accidents. Currently, vehicles can utilize millimeter-wave radar to achieve the functions of advanced driver assistance systems (ADAS), such as adaptive cruise control, forward collision warning, blind spot detection, parking aid, and lane change assistance, thus enabling assisted driving or autonomous driving.

[0063] It should be understood that the above application scenarios are merely examples, and the detection device provided in this application can also be applied to other possible scenarios, not limited to those listed above. For example, the detection device can also be installed inside a vehicle for dynamic detection of living targets inside the vehicle. Alternatively, the detection device can also be installed on roadside traffic radar for detecting violations by vehicles passing by on surrounding roads, monitoring the current level of traffic congestion for timely evacuation, or communicating with vehicles to achieve intelligent vehicle-road cooperative communication. Alternatively, the detection device can also be installed on aircraft, such as drones, passenger planes, forest protection aircraft, or aerial survey aircraft, to monitor obstacles in the flight environment for timely avoidance and to reduce accidents. Furthermore, the detection device can also be installed on ships as a shipborne detection device to assist in safe navigation. For example, detection devices can also be applied to terminal devices or installed in components of terminal devices. These terminal devices can be, for example, smart home devices (e.g., for privacy-free detection), smart manufacturing equipment (e.g., for monitoring operational status), robots, or smart transportation equipment. Smart transportation equipment can be, for example, automated guided vehicles (AGVs) or unmanned vehicles. These will not be listed exhaustively here.

[0064] It should be noted that the application scenarios described in this application are for the purpose of more clearly illustrating the technical solutions of this application, and do not constitute a limitation on the technical solutions provided in this application. The above application scenarios can be applied to fields such as autonomous driving, autonomous driving, assisted driving, intelligent driving, connected vehicles, security monitoring, biomedicine, or surveying and mapping (such as 3D mapping).

[0065] As described in the background section, the interface used by the detection device to transmit acceleration is specified in the Object Level, as defined by the International Organization for Standardization (ISO) standard 23150. Information regarding the acceleration-related interface transmissions in the Object Level can be found in [link to relevant documentation]. Figure 2 The content shown. Combined with... Figure 2 The target acceleration can include the projected components of the target acceleration in the x, y, and z dimensions. These three projected components are calculated using the echo signals from at least three frames of probe signals. The target acceleration error can also include the error of the projected components of the target acceleration in the x, y, and z dimensions.

[0066] Typically, millimeter-wave radar frame periods are 30–50 milliseconds. Based on this, the acquisition and processing time for at least three frames of echo signals can reach several hundred milliseconds. In real-world scenarios, if a vehicle in front of you suddenly brakes, the time from the start of braking to a complete stop is usually only a few hundred milliseconds. This time is only enough to acquire at least three frames of echo signals, leaving insufficient time for subsequent analysis. Therefore, traditional target acceleration acquisition methods suffer from large time delays and information distortion, failing to meet the needs of intelligent driving systems for transient perception and timely response to the motion of other vehicles.

[0067] In view of this, this application proposes a detection method. This method analyzes the echo signal obtained from the detected target to determine the correspondence between the target's speed and time, and feeds back relevant information about the target's acceleration to the vehicle's control device. This allows the control device to determine the target's motion state based on this information and respond promptly. Compared to traditional methods that require multiple frames of echo signals to determine the target's acceleration, the method of this application can detect the target's acceleration within one frame of echo signal. Therefore, it can reduce latency, improve the perception of the motion state of other vehicles, and increase the speed of response, thereby improving driving safety.

[0068] The following section will first introduce the system architecture to which the detection method proposed in this application can be applied.

[0069] For example, please see Figure 3A This is a schematic diagram of the architecture of a detection system applicable to an embodiment of this application. The detection system 300 may include a detection device 310 and a control device 320, with the detection device 310 connected to the control device 320. The detection device 310 is deployed on a vehicle, and the deployment method can be found above. Figure 1 The control device 320 can be any device capable of detecting the environment around the vehicle, such as radar, including but not limited to lidar, millimeter-wave radar, microwave radar, and over-the-horizon radar. The control device 320 can be any device capable of controlling the vehicle's motion state; it can be deployed inside or outside the vehicle and connected to it.

[0070] For example, in some examples, the control device 320 may be a control unit in the vehicle, such as the control unit in the vehicle's intelligent driving system, i.e., the intelligent domain controller, or other domain controllers of the vehicle, or it may also be the vehicle control unit (VCU), mobile data center (MDC), etc., where MDC is also known as the intelligent driving computing platform.

[0071] For example, in some examples, the control device 320 can be a control unit outside the vehicle, such as a cloud server or user equipment. User equipment includes, but is not limited to, a user's mobile phone, tablet, or laptop. In some scenarios, to ensure vehicle movement safety, the user equipment needs to connect to the vehicle via a cloud server. Control information sent by the user equipment must be verified by the cloud server before being forwarded to the vehicle for safe movement control.

[0072] Understandably, if the control device 320 is a control unit in the vehicle, then the control device 320 and the detection device 310 can be connected via a wired connection, such as through a controller area network (CAN) bus, a local interconnect network (LIN) bus, or an inter-integrated circuit (I2C) bus. 2 C) Connection via bus, etc., is not limited. Conversely, if the control device 320 is an external control unit, then the control device 320 and the detection device 310 need to be connected wirelessly, such as via wireless local area network (WIFI), cellular network, Bluetooth transmission, global positioning system (GPS), etc., which is also not limited.

[0073] Taking the detection device 310 as an example, which is a millimeter-wave radar, please refer to [link / reference]. Figure 3B This is a schematic diagram of a possible architecture for a detection device provided in an embodiment of this application. The detection device 310 may include a transmitter 3111, a receiver 3112, a monolithic microwave integrated circuit (MMIC) 312, and a microcontroller unit (MCU) 313. As an example, the MMIC 312 may include a signal generator 3121, and sequentially coupled components including a mixer 3122, a low-pass filter 3123, an analog-to-digital converter (ADC) 3124, and a digital signal processor (DSP) 3125. The signal generator 3121 is coupled to both the MCU 313 and the transmitter 3111. The MCU 313 is also coupled to the DSP 3125. The transmitter 3111 is also coupled to the mixer 3122, and the mixer 3122 is also coupled to the receiver 3112.

[0074] Based on this, the following is... Figure 3BThe structure and function of each component shown are described in detail.

[0075] In millimeter-wave radar, the transmitter 3111 can specifically be a transmitting antenna, and the receiver 3112 can specifically be a receiving antenna. Corresponding to the transmitting and receiving antennas, the MMIC 312 can also be configured with a transmitting channel and a receiving channel, with the transmitting antenna connected to the transmitting channel and the receiving antenna connected to the receiving channel. There are several possible combinations of antennas and channels. For example, in one combination, both the transmitting and receiving antennas are located on a printed circuit board (PCB), while the transmitting and receiving channels are both located within the chip, forming an antenna on PCB (AOB). In another combination, both the transmitting and receiving antennas are located within the chip package, and both the transmitting and receiving channels are located within the chip, forming an antenna in package (AIP). Of course, other combinations are also possible, such as the transmitting antenna being located on the printed circuit board and the receiving antenna being located in the chip package, or both the transmitting and receiving channels being located within the chip, etc., which will not be listed here.

[0076] In millimeter-wave radar, the MCU 313 acts as the main control unit, controlling the operation of the MMIC 312. Under the control of the MCU 313, the MMIC 312 interacts with the transmitter 3111 and receiver 3112 to control the transmitter 3111 to transmit a detection signal and the receiver 3112 to receive the echo signal. For example, the MCU 313 can control the signal generator 3121 to generate a detection signal (e.g., millimeter wave). This detection signal can consist of one or more burst packets, each burst packet performing one frame of detection, including multiple chirp signals. This detection signal is transmitted to the detection space via the transmitter 3111. After being reflected and / or scattered by one or more targets in the detection space, the detection signal forms an echo signal, which is received by the receiver 3112 and then transmitted to the mixer 3122.

[0077] Optionally, while transmitting the probe signal, the transmitter 3111 can also synchronously send the probe signal to the mixer 3122 in the MMIC 312. The mixer 3122 can perform mixing processing on the probe signal and the echo signal, such as subtracting the frequency of the probe signal from the frequency of the echo signal and subtracting the phase of the probe signal from the phase of the echo signal to obtain an intermediate frequency (IF) signal. This IF signal is then input to a low-pass filter 3123 for deskewing (which can be considered as filtering out high-frequency components and retaining only mid-to-low-frequency components) to obtain a clean IF signal. This clean IF signal is then discretely sampled by the ADC 3124 and converted into a digital signal, which is then sent to the DSP 3125. The DSP 3125 first performs a one-dimensional Fourier transform on the digital signal from the ADC 3124 to obtain the distribution characteristics of the echo signal in the distance dimension, and then performs a two-dimensional Fourier transform on these distribution characteristics to obtain the distribution characteristics of the echo signal in the velocity dimension, i.e., the velocity change over time. These two distribution characteristics are then transmitted to the MCU 313.

[0078] Furthermore, the MCU 313 can determine the target's correlation information based on relevant information from the echo signal from the MMIC 312. For example, the MCU 313 can determine the target's relative distance based on the distribution characteristics of the echo signal in the distance dimension, and the target's relative velocity based on the distribution characteristics of the echo signal in the velocity dimension. Optionally, relative angles can also be determined, such as the horizontal and pitch angles between the target and the vehicle where the detection device 310 is located. In some scenarios, the MCU 313 can interact with... Figure 2 The target is connected to the control device 320 shown in the figure. By sending the target's association information to the control device 320, the control device 320 can adjust the vehicle's motion state.

[0079] It should be noted that the various components included in the above architecture are merely illustrative. In the actual detection device 310, more or fewer components may be included than those shown in the figure. Furthermore, the components shown or not shown can be combined or divided in any way, and any component can be replaced by other components with equivalent functions. For example, in another example, the MMIC 312 may also include one or more of the following: a low noise amplifier (LNA), a power amplifier (PA), an up-converter, a detector, and a voltage-controlled oscillator. In yet another example, the signal generator 3121 can be replaced by components such as a modulator, a phase shifter, and a switch; the MCU 313 can be replaced by other components with control functions; and the DSP 3125 can be replaced by other components with signal processing capabilities. This application does not impose specific limitations on these aspects.

[0080] based on Figure 3A and Figure 3B The detection scheme proposed in this application will be described in detail below with reference to other accompanying figures.

[0081] In the various embodiments of this application, unless otherwise specified or in case of logical conflict, the terminology and / or descriptions of different embodiments are consistent and can be referenced by each other. The technical features of different embodiments can be combined to form new embodiments according to their inherent logical relationship.

[0082] like Figure 4 The diagram shown is a flowchart of a detection method provided in this application. This detection method can be applied to detection devices and control devices, such as... Figure 3A The detection device 310 and control device 320 are shown. (As shown...) Figure 4 As shown, the method includes the following steps:

[0083] Step 401: The detection device acquires the echo signal obtained from detecting the first target within the first time unit.

[0084] Optionally, the first time unit can be set by those skilled in the art based on experience, or it can be customized according to the actual application scenario, or it can be modified by the user. For example, in one example, if the accuracy requirement for motion state adjustment is high, the first time unit can be configured to a relatively small value, such as the time length for the detection device to complete one frame of detection. Conversely, if the requirement for saving computing power and resources is high, the first time unit can be configured to a relatively high value, such as the time length for the detection device to complete two or three frames of detection. Of course, other configuration methods are also possible, and no specific limitation is made.

[0085] Optionally, the first target can be a mobile target in the detection space, such as other motor vehicles, pedestrians, or non-motor vehicles, etc., without any specific limitation.

[0086] For example, assuming the detection device detects one frame of image every 30ms, during the detection process of each frame of image, the detection device can continuously transmit pulse signals into the detection space in the first 10ms, and receive and analyze the echo signals in the last 20ms. The echo signals include the signals reflected or scattered back by the target in the detection space by the pulse signals emitted by this detection device, and may also include interference signals, such as the signals received by this detection device after the detection signals emitted by other detection devices are transmitted to this detection device, or the signals after the echo signals of this detection device or other detection devices are reflected by other objects, etc., without specific limitations here.

[0087] Furthermore, if the first time unit is equal to the time it takes for the detection device to complete one frame of detection, then after receiving the echo signal corresponding to each frame of image, the detection device can not only determine the relevant information of the target based on the echo signal, but also perform the identification in step 402 based on the echo signal to adjust the vehicle's operating state in real time. Alternatively, if the first time unit is equal to the time it takes for the detection device to complete two or more frames of detection, then the detection device will determine the relevant information of the target based on the echo signal corresponding to each frame of image, and will only adjust the vehicle's operating state based on the echo signals of two or more frames of images after receiving them.

[0088] For example, taking the first time unit as equal to the time it takes for the detection device to complete one frame of detection, combined with... Figure 3B When the detection device is a millimeter-wave radar, assuming the duration of one detection frame is 30ms as described above, the MCU313 can control the signal generator 3121 in the MMIC312 to generate a millimeter-wave detection signal within the first 10ms of one detection frame, and transmit the millimeter-wave detection signal through the transmitter 3111. If a first target exists in the detection space, the millimeter-wave detection signal will be reflected or scattered by the first target, thus returning to the millimeter-wave radar. Therefore, the MCU313 controls the receiver 3112 in the MMIC312 to receive the echo signal within the last 20ms, and executes the following step 402.

[0089] Step 402: The detection device determines the relationship between the velocity and time of the first target based on the echo signal.

[0090] Optionally, a detection device is used as Figure 3B Taking the millimeter-wave radar shown as an example, after receiving the echo signal, the receiver 3122 can transmit the echo signal to the mixer 3122. The mixer 3122 mixes the detection signal and the echo signal to obtain an intermediate frequency (IF) signal. Then, the low-pass filter 3123 performs deskewing on the IF signal to obtain a clean IF signal. The clean IF signal is then discretely sampled by the ADC 3124 and converted into a digital signal. Finally, the DSP 3125 determines the velocity-time relationship of the first target based on the digital signal.

[0091] The relationship between the velocity of the first target and time includes the velocity of the first target at each moment within the first time unit. The velocity of the first target at each moment within the first time unit can be calculated in various ways, such as:

[0092] As an example (referred to as Example 1), the DSP 3125 can use time-frequency analysis techniques to process the received digital signal. For example, it can use STFT technology to perform sliding window sampling on the received digital signal to obtain multiple sampled signals. Then, based on the Doppler effect, it can calculate the velocity of the first target corresponding to each sampled signal according to the change in frequency of each sampled signal relative to the frequency of the probe signal. In this way, the velocity of the first target at each moment in the first time unit can be obtained.

[0093] As another example (referred to as Example 2), the DSP 3125 can segment the received digital signal to obtain at least two sub-digital signals (also called sub-echo signals, but presented in digital form). Then, based on the Doppler effect, it calculates the velocity of the first target corresponding to each sub-digital signal according to the frequency change of each sub-digital signal relative to the probe signal. After that, based on the velocities of the first target corresponding to the at least two sub-digital signals respectively, it obtains the velocity of the first target at different times in the first time unit.

[0094] In Example 2 above, the echo signal of the first target includes echo signals reflected from multiple points within the first target. Before analyzing the echo signal of the first target, one echo signal can be selected from the multiple echo signals reflected from the multiple points of the first target, and then analyzed based on that selected echo signal. Alternatively, it can be understood as selecting a target point within the first target and analyzing the correspondence between the velocity and time of the first target based on the echo signal of that target point. In this way, it is not necessary to analyze all the echo signals, thereby speeding up the calculation and saving computational resources.

[0095] The selected echo signal can be the echo signal reflected back from the point closest to the vehicle in the first target. This echo signal can be selected in various ways, such as:

[0096] In one example, the strongest echo signal can be selected from multiple echo signals reflected back by the first target. It can be understood that the closer the point is to the vehicle, the shorter the transmission distance of the signal reflected back by the point, the smaller the signal loss, and the greater the signal strength. Therefore, the strongest echo signal can be considered as the echo signal reflected back by the point in the first target that is closest to the vehicle.

[0097] In another example, the selected echo signal can be the echo signal with the earliest reception time among multiple echo signals reflected back by the first target. The earliest reception time indicates that the target point reflecting the echo signal is the point closest to the vehicle among the first targets. Analyzing the echo signal based on the point closest to the vehicle not only results in less signal loss and easier processing, but also better reflects the safe distance between the vehicle and the first target.

[0098] In another example, the point cloud data of the first target can be used to determine the target point closest to the vehicle among multiple points of the first target. For instance, after receiving multiple echo signals reflected back from the first target, the point cloud data of the first target can be determined based on these echo signals. The point cloud data includes the distance between each point of the first target and the vehicle. Therefore, the target point closest to the vehicle can be selected from the first target based on the point cloud data of the first target.

[0099] Optionally, the relationship between the velocity and time of the first target can be represented in any form, such as a table, graph, formula, database, or stack. Based on this relationship, the velocity of the first target at each moment in the first time unit can be determined. For example, for an image representation, please refer to [link to relevant documentation]. Figure 5 This is a schematic diagram showing the relationship between the velocity and time of a first target. The graph represents the relationship between velocity and time in the form of a curve. By looking up the horizontal axis of the graph and drawing a line parallel to the vertical axis, the intersection of the line with the curve represents the velocity of the first target at the time corresponding to that horizontal axis.

[0100] Step 403: The detection device sends first information to the control device. Correspondingly, the control device receives the first information sent by the detection device.

[0101] Optionally, after determining the correspondence between the speed and time of the first target, the detection device can generate first information based on the correspondence between the speed and time of the first target. The first information may include at least one of the following contents one to three.

[0102] Content 1: The Correspondence Between Speed ​​and Time for the First Target

[0103] Here, after the detection device determines the correspondence between the speed and time of the first target in the manner described in step 402 above, it can directly use this correspondence as the first information, or as part of the first information, and combine it with other information (as described in content two and / or content three below) to generate the first information. The relevant content regarding the correspondence between the speed and time of the first target can be directly referred to in step 402 above, and will not be repeated here.

[0104] Content 2: Acceleration information of the first target

[0105] Optionally, the acceleration information of the first target includes the acceleration of the first target within the first time unit, which can be calculated based on the correspondence between the velocity and time of the first target. For example, in one example, after the detection device determines the correspondence between the velocity and time of the first target in the manner described in step 402 above, it can randomly or according to a set rule select two moments based on the velocity of the first target at each moment within the first time unit, and divide the difference between the velocities at these two moments by the difference between these two moments, using the resulting value as the acceleration of the first target. Alternatively, in another example, the detection device can also calculate an acceleration for every two adjacent moments and use the average or weighted average of the calculated accelerations as the acceleration of the first target. Or, in yet another example, the detection device can also obtain the acceleration of the first target by fitting the least squares method based on the correspondence between velocity and time. And so on, this application does not limit the specific method for determining the acceleration of the first target.

[0106] Furthermore, optionally, the acceleration information of the first target may include not only the acceleration of the first target within the first time unit, but also the acceleration error of the first target within the first time unit. This acceleration error can be determined based on the signal-to-noise ratio of the echo signal of the first target. For example, when the detection device is... Figure 3B In the millimeter-wave radar shown, the echo signal becomes a relatively clean signal after being filtered by low-pass filter 323. Based on this relatively clean signal and the original echo signal input to low-pass filter 323, the signal-to-noise ratio (SNR) can be determined. Then, by consulting the set correspondence between the SNR and acceleration error, the acceleration error corresponding to that SNR can be obtained. This acceleration error is then used as the acceleration error of the first target in the first time unit. The set correspondence between the SNR and acceleration error can be set by those skilled in the art based on experience, or it can be pre-calibrated; no specific limitation is made.

[0107] Understandably, when the first information includes the acceleration information of the first target, the detection device can use the acceleration information of the first target as the first information, or as part of the first information, and combine it with other information (the above content one and / or the following content three) to generate the first information.

[0108] Content 3: Motion status information of the first target.

[0109] Optionally, after the detection device determines the correspondence between the velocity and time of the first target in the manner described in step 402 above, it can first refer to the introduction in content 2 above to calculate the acceleration information of the first target in the first time unit based on the velocity at each moment in the first time unit, and then determine the motion state information of the first target based on the acceleration information of the first target in the first time unit.

[0110] The motion state information of the first target includes its motion state, which may include, but is not limited to: uniform motion, rapid acceleration, accelerated motion, rapid deceleration, or deceleration. Different motion states can have different preset acceleration ranges; for example, the preset acceleration range for uniform motion is [-0.5 m / s²]. 2 0.5m / s 2 The acceleration range for accelerated motion is set to [0.5 m / s²]. 2 5m / s 2 ].

[0111] Therefore, if the acceleration information of the first target only contains the acceleration of the first target, the detection device can query the correspondence between the preset motion state and the set acceleration range based on the acceleration of the first target, determine the set acceleration range in which the acceleration is located, and take the motion state corresponding to the set acceleration range as the motion state of the first target. For example, when the acceleration of the first target is 0.25 m / s² 2 When the acceleration is found to be within the set acceleration range of uniform motion, it can be determined that the first target is in uniform motion.

[0112] Alternatively, if the acceleration information of the first target includes both the target's acceleration and acceleration error, the detection device can first combine the acceleration and acceleration error to obtain a reference acceleration range. Then, it can query the correspondence between the preset motion state and the set acceleration range to determine the set acceleration range in which the reference acceleration range falls, and use the motion state corresponding to this set acceleration range as the motion state of the first target. For example, the set acceleration range for uniform motion is [-0.5 m / s²]. 2 0.5m / s 2 The acceleration range for accelerated motion is set to [0.5 m / s²]. 2 5m / s 2 For example, assuming the acceleration of the first target is 1 m / s² 2 The acceleration error is ±0.6 m / s². 2 The reference acceleration range is [0.4 m / s²]. 2 1.6m / s 2As can be seen, after combining acceleration and acceleration error, most of the acceleration in the reference acceleration range falls within the set acceleration range of the accelerated motion state. Therefore, the motion state of the first target can be determined to be the accelerated motion state.

[0113] Optionally, the motion state information of the first target may include not only the motion state of the first target but also the confidence level of the motion state. The confidence level of the motion state characterizes the degree of certainty that the first target belongs to a certain motion state, and the confidence level is determined based on acceleration and acceleration error. For example, continuing the above example, the set acceleration range for uniform motion is [-0.5 m / s²]. 2 0.5m / s 2 The acceleration range for accelerated motion is set to [0.5 m / s²]. 2 5m / s 2 The acceleration of the first target is 1 m / s². 2 The acceleration error is ±0.6 m / s². 2 After combining acceleration and acceleration error, the probability statistical distribution shows that a portion of the data falls within the set acceleration range for uniform motion, and another portion falls within the set acceleration range for accelerated motion. Based on the data distributed within these two ranges, the confidence level for determining that the first target is in uniform motion can be 10%, the confidence level for being in accelerated motion can be 90%, and the confidence level for other motion states is 0%. It should be noted that the values ​​in the above example are merely illustrative.

[0114] As described above, the first information can be at least one of the contents one through three mentioned above. Therefore, which contents one through three are specifically reported by the detection device to the control device can be determined according to pre-configured rules or pre-issued instructions from the detection device. For example, consider the case where the detection device pre-issues instructions to report the first information content:

[0115] Before sending the first information to the control device, the detection device can also obtain pre-issued instructions from the control device and determine the content of the first information to be reported based on the instructions. For example, if the pre-issued instruction from the control device instructs the detection device to directly report the correspondence between speed and time, then after determining the correspondence between the speed and time of the first target, the detection device can send it directly to the control device as the first information. As another example, if the instruction from the control device instructs the reporting of acceleration information, then after determining the correspondence between the speed and time of the first target, the detection device also needs to determine the acceleration information of the first target based on the speed-time correspondence, and then report it to the control device as the first information. Yet another example, if the instruction from the control device instructs the reporting of motion state information, then after determining the acceleration information of the first target, the detection device also needs to further determine the motion state information of the first target based on the acceleration information, and then report it to the control device as the first information.

[0116] For example, the instructions pre-issued by the control device or the rules pre-configured in the detection device can be determined based on the interface bandwidth between the control device and the detection device, or the computing resources of the detection device. For instance, when the detection device has sufficient computing resources, the control device can instruct (or configure) the detection device to report motion status information. Furthermore, if the interface bandwidth between the detection device and the control device is sufficient, the control device can instruct (or configure) the detection device to report the correspondence between speed and time (because the correspondence between speed and time involves a large amount of data).

[0117] Furthermore, since the first message sent in different scenarios may contain different content, different content can also be sent in different formats to facilitate the control device's differentiation. For example, see... Figure 6 This demonstrates different upload formats for the initial information. In one example, the detection device can directly upload information such as... Figure 6 The content of the first information shown, for example, when the first information is acceleration information, can directly upload the specific values ​​of acceleration and acceleration error. Alternatively, in another example, when uploading the first information, the detection device can also upload information such as... Figure 6 The first information's representation field, for example, when the first information is a motion state, the detection device can also obtain the representation fields corresponding to different preset motion states, and then upload the representation field corresponding to the motion state of the first target to the control device. Compared with the previous method, this method can save bandwidth between the control device and the detection device.

[0118] Below, in conjunction with Figure 6 The following details the upload formats for different types of primary information:

[0119] For example, such as Figure 6 As shown, when the first information is the content mentioned above, that is, when the first information is the correspondence between speed and time, the first information has no characterization field. The content of the uploaded first information can be found in the description in step 402 above, for example, it can be uploaded in the form of a table, image, or formula.

[0120] For example, such as Figure 6 As shown, when the first information is Content Two above, that is, when the first information is acceleration information, the first information also does not have a characterization field. Referring to the introduction in Content Two above, acceleration information can include acceleration and acceleration error. When the acceleration information only includes the acceleration of the first target, after determining the acceleration of the first target, the detection device can directly upload the acceleration value. For example, referring to the example above, the acceleration of the first target is 1 m / s². 2 At that time, the content of the first piece of information uploaded is 1m / s 2 When the acceleration information includes the acceleration and acceleration error of the first target, the detection device can directly upload the acceleration value and the acceleration error value. For example, referring to the example above, the uploaded first information could be 1 m / s². 2 and ±0.6m / s 2 .

[0121] For example, such as Figure 6 As shown, when the first information is the third item mentioned above, that is, when the first information is motion state information, it can specifically include the motion state of the first target and the motion state confidence level. The motion state of the first target can have a pre-defined representation field, while the motion state confidence level has no representation field and can be directly uploaded as a value. Figure 6 The representation fields corresponding to the various motion states shown are merely examples, and this application does not limit the values ​​of the fields. When the motion state information only includes the motion state of the first target, after determining the motion state, the value corresponding to the motion state can be uploaded to the control device. For example, when the motion state is uniform motion, the detection device can upload the value "0" to the control device, representing that the first target is in uniform motion. When the motion state information includes the motion state of the first target and the motion state confidence level, the detection device can upload the representation fields of each motion state, as well as the corresponding motion state confidence level value. For example, it can be uploaded in the form of an array as shown in the following example:

[0122] (0-10%), (1-0%), (2-90%), (3-0%), (4-0%).

[0123] Optionally, when the detection device sends the first information to the control device, it can do so through the detection level interface of the detection device. This detection level interface can be one of the existing interfaces in the detection level of the detection device, or it can be a newly added interface in the detection level specifically for transmitting the first information; there is no limitation on this. Correspondingly, the control device is connected to this detection level interface of the detection device. Therefore, the control device can receive the first information from the detection device through this detection level interface.

[0124] 404, The control device determines the motion state of the first target based on the first information.

[0125] Here, when the contents of the first information are different, the control device determines the motion state of the first target in different ways based on the first information. Specifically, this includes, but is not limited to, the following situations one to five.

[0126] In scenario one, when the first information includes content one, content two, and content three from step 403 above, in one possible implementation, the control device can directly determine the motion state of the first target based on content three.

[0127] Alternatively, in another possible implementation, to improve the accuracy of the determined motion state, the control device can also re-determine the motion state information of the first target based on Content 2. The specific determination process is the same as that of the detection device determining the motion state based on acceleration information, as described in Content 3 above. Alternatively, to further improve the accuracy of the motion state, after determining the motion state information of the first target based on Content 2, the control device can also combine it with Content 2 from the detection device to determine the motion state of the first target. For example, combining... Figure 4 The content uploaded by the detection device includes (0-10%), (1-40%), (2-50%), (3-0%), and (4-0%), among which the confidence levels of the rapid acceleration motion state and the acceleration motion state are relatively high. The motion state information determined by the control device based on content two includes (0-0%), (1-30%), (2-70%), (3-0%), and (4-0%). Combining the two yields: (0-5%), (1-35%), (2-60%), (3-0%), and (4-0%). It can be seen that after combining the motion state information actually calculated by the control device with the content three sent by the detection device, the confidence level of the acceleration motion state is significantly higher than that of the rapid acceleration motion state. Therefore, the motion state of the first target can be determined to be the acceleration motion state. It should be noted that the combination method shown in the above example is only an example, and other combination methods such as weighted average can also be used. This application does not limit the combination method.

[0128] Alternatively, in another possible implementation, the control device may first redetermine the acceleration information of the first target based on the received content one, and then determine the motion state information of the first target based on the acceleration information. The process of determining the acceleration information can be found in the description in content two above, and the process of determining the motion state information can be found in the description in content three above, and will not be repeated here. For example, the control device may directly use the redetermined motion state information, or it may, as described in the previous possible implementation, combine the redetermined motion state information with content three from the detection device to determine the motion state of the first target.

[0129] Alternatively, after re-determining the acceleration information of the first target based on the received content one, the control device can combine the re-determined acceleration information with content two from the detection device to determine the motion state information of the first target. For example, content two uploaded by the detection device might be: 1 m / s². 2 and ±0.6m / s 2 The control device calculated Content 2 based on Content 1 as: 1.2 m / s 2 and ±0.6m / s 2 The result after combining is: 1.1 m / s 2 and ±0.6m / s 2 Furthermore, the control device can determine the motion state information of the first target based on the acceleration information obtained after combination.

[0130] Scenario 2: When the first information includes both content one and content two from step 403 above, the control device can determine the motion state of the first target based on the received content two. The specific determination process can be found in the description in content three above. Alternatively, the control device can first redetermine the acceleration information of the first target based on the received content one, and then further determine the motion state of the first target based on the redetermined acceleration information. Or, the control device can first redetermine the acceleration information of the first target based on the received content one, then combine the received content two with the redetermined acceleration information, and determine the motion state of the first target based on the combined acceleration information.

[0131] Scenario 3: When the first information only includes the content from step 403 above, the control device can first calculate the acceleration of the first target based on the first information. Further, the control device determines the motion state of the first target based on the set acceleration range within which the acceleration falls. Alternatively, after calculating the acceleration of the first target based on the correspondence between the target's velocity and time, the control device can obtain the acceleration error of the first target from the detection device and combine the acceleration and acceleration error to determine the motion state of the first target. Or, after calculating the acceleration of the first target, the control device can also obtain the signal-to-noise ratio of the echo signal of the first target from the detection device, determine the corresponding acceleration error based on the signal-to-noise ratio, and combine the acceleration and acceleration error to determine the motion state of the first target.

[0132] Scenario 4: When the first information only includes content two from step 403 above, the control device can determine the motion state of the first target based on the acceleration information. For example, when the acceleration information of the first target only includes the acceleration of the first target, the control device can obtain different set acceleration ranges for different motion states, and thus determine the motion state of the first target based on the set acceleration range in which the first target's acceleration falls. As another example, when the acceleration information of the first target includes both the acceleration and acceleration error of the first target, the control device can combine the acceleration and acceleration error to determine the acceleration range in which the target falls, thereby determining the motion state of the first target.

[0133] Scenario 5: When the first information only includes content 3 in step 403 above, the control device can directly obtain the motion state of the first target based on the first information.

[0134] Step 405: The control device makes a corresponding decision on the motion state of the vehicle based on the motion state of the first target.

[0135] Optionally, if the control device detects that the current motion state of the vehicle relative to the motion state of the first target poses a risk of collision with the first target, it can adjust the motion state of the vehicle to avoid a collision and improve driving safety.

[0136] For example, if the first target is detected to be the vehicle in front of the vehicle, and the first target is in a state of rapid deceleration, the control device can control the vehicle to decelerate in order to reduce the risk of collision between the vehicle and the first target.

[0137] For example, if the first target is a pedestrian and the first target is in a state of rapid deceleration, the control device can control the vehicle to decelerate in order to avoid a collision.

[0138] For example, if the first target is detected to be the vehicle in front of the vehicle, and the first target is in a state of rapid deceleration, the control device can control the vehicle to decelerate in order to reduce the risk of collision between the vehicle and the first target.

[0139] There are many other possible application scenarios, which will not be listed here.

[0140] Based on the above Figure 7 The control scheme shown can send information reflecting the target's motion state to the control device based on the echo signal obtained from the detected target. This allows the control device to adjust the vehicle's motion state in a timely manner when there is a driving risk, ensuring vehicle safety. Compared to traditional schemes that require multiple frames to detect and perceive the target's motion state, the scheme in this application can complete the perception of the target's motion state within one frame of detection time, improving the timeliness of motion state perception and reducing the response time of the control device to the target's motion state, thus better protecting user safety.

[0141] Understandably, the above content only introduces the detection and avoidance of the primary target in a self-driving environment. The primary target can be any target in the self-driving environment, a user-configured target, or a target indicated by the control device.

[0142] For example, when the primary target is any target in the vehicle's driving environment, the detection device can simultaneously detect all targets in the driving environment and send the primary information corresponding to all targets to the control device. Based on the primary information corresponding to all targets, if the control device determines that a certain target poses a collision risk to the vehicle, it can adjust the vehicle's motion state to avoid a collision. Here, "all targets" can refer to all movable objects in the vehicle's driving environment, including but not limited to motor vehicles, pedestrians, or non-motorized vehicles.

[0143] For example, when the primary target is a user-configured target, if the user configures the detection to only detect vehicles, the detection device can detect all targets in the vehicle's driving environment. After detection, it filters out vehicle-type targets from all targets and sends the first information corresponding to the vehicle-type targets to the control device. Based on the first information corresponding to the vehicle-type targets, if the control device determines that a certain vehicle poses a collision risk to the vehicle, it can adjust the vehicle's motion state to avoid a collision.

[0144] For example, when the primary target is the target indicated by the control device, the control device can send a set rule to the detection device, which then selects the primary target based on this rule. For instance, the detection device can detect all targets in the vehicle's driving environment. After detection, it filters out the target indicated by the control device from all targets according to the set rule sent by the control device and sends the primary information corresponding to the indicated target to the control device. For example, if the set rule indicates to focus on targets in the vehicle's lane, the detection device, based on this rule, can select targets within a certain range in front of the vehicle and within a certain range behind the vehicle as the primary targets, and send the primary information corresponding to the primary targets to the control device to prevent sudden deceleration of vehicles in front of the vehicle or sudden acceleration of vehicles behind the vehicle from affecting the vehicle's driving safety.

[0145] The following is based on Figure 8 This paper provides a detailed description of the detection method for scenarios where targets are selected based on predefined rules. This detection method may include steps 701 to 706.

[0146] Step 701: The detection device transmits a detection signal into the detection space and receives the echo signal.

[0147] For example, the detection device can periodically transmit detection signals into the detection space and receive echo signals.

[0148] Step 702: The detection device determines the position information of each target in the detection space based on the echo signal.

[0149] Here, the detection device can first perform frequency mixing processing on the echo signal and the detection signal to obtain an intermediate frequency signal, then perform deskewing processing and mode conversion processing on the intermediate frequency signal to obtain a digital signal, and finally perform a one-dimensional Fourier transform on the digital signal to obtain the distance between the digital signal and the target. Thus, based on the distance and the azimuth angle of the received echo signal, the position information of all targets in the detection space can be obtained.

[0150] Optionally, if the detection space contains multiple targets, the echo signal will contain signals reflected or scattered by multiple targets. Therefore, the detection device can determine the position information of multiple targets in the detection space.

[0151] Step 703: The detection device receives the setting rules sent by the control device.

[0152] Here, the rules can be sent to the detection device in advance, such as being configured in the detection device by the control device when the vehicle leaves the factory, or they can be instructed to the detection device by the control device when the user has a request, or they can be sent to the detection device by the control device every time the detection device is powered on, etc., which will not be listed here.

[0153] Step 704: The detection device selects the target to be detected from the targets in the detection space according to the set rules and the position information of each target in the detection space.

[0154] Here, the detection device can first determine the area to be detected according to the set rules, and then, based on the position information of each target in the detection space, take the target located in the area to be detected as the target to be detected.

[0155] For example, if a rule is set to focus on targets within the same lane, the detection device can, according to this rule, define the area within a set distance directly in front of and behind the vehicle as the detection zone. Then, based on the position information of each target in the detection space, targets whose coordinates fall exactly within the detection zone are selected as the next targets. Since the selection is based on the areas directly in front and behind, the targets to be detected are those located in the same lane as the vehicle, and these targets will have the greatest impact on the vehicle's driving.

[0156] Step 705: The detection device determines the relationship between the speed and time of the target based on the echo signal of the target.

[0157] It is understood that the target to be detected may include one or more. When there are multiple targets to be detected, the detection device performs the processing shown in step 402 above for each target to obtain the correspondence between the velocity and time of each target. The specific processing flow can be found in step 402 above, and will not be repeated here.

[0158] Step 706: The detection device sends the first information to the control device.

[0159] Here, the detection device can generate first information based on one or more of the velocity-time correspondence, acceleration information, and motion state information of all targets to be detected, and then send it to the control device to save communication overhead. Alternatively, the detection device can also generate a first information based on one or more of the velocity-time correspondence, acceleration information, and motion state information of each target to be detected, and then send it to the control device, so that the control device can more specifically adjust the vehicle's motion state for each target to be detected. The specific process for generating the first information can be found in step 403 above, and will not be repeated here.

[0160] Understandably, when there are multiple targets to be detected, the control device can adjust the vehicle's motion state based on the relevant information of all the targets to ensure that the vehicle does not collide with any of the targets.

[0161] In some scenarios, the primary target can also be a target adaptively selected by the detection device based on the driving environment. In other words, the detection device can also select a target to be detected based on its own detection results of all targets in the vehicle's surrounding environment, so that the control device can adjust the vehicle's motion state with reference to the target selected by the detection device.

[0162] The following is based on Figure 4 This paper details a detection method for a scenario where the detection device adaptively selects the target to be detected. The method includes the following steps 801 to 804.

[0163] Step 801: The detection device transmits a detection signal into the detection space and receives the echo signal.

[0164] For example, the detection device can periodically transmit detection signals into the detection space and receive echo signals.

[0165] Step 802: The detection device determines each target in the detection space based on the echo signal.

[0166] Step 803: The detection device adaptively selects the target to be detected from various targets in the detection space based on the driving environment.

[0167] Here, the detection device can select the target to be detected in several ways based on the driving environment. For example:

[0168] As an alternative approach, the detection device can select targets close to the vehicle in the driving environment as targets to be detected, based on driving safety considerations. For example, a distance threshold can be set to identify targets, and targets within the threshold distance can be selected. The distance between the target and the vehicle can be determined in various ways. For instance, the detection device can determine the distance to each target based on the time of transmitting the detection signal and the time of receiving the echo signal corresponding to each target. Alternatively, the detection device can obtain the distance to each target from the point cloud data of each target. And so on, without further listing.

[0169] As another option, since the lanes for intelligent driving are already planned, the environment adaptive selection can also select targets within the lane where the vehicle is located as the targets to be detected, such as vehicles in front of the vehicle or vehicles behind the vehicle.

[0170] Of course, it is important to know that the method of selecting targets based on environmental adaptation is not limited to the scheme described above; the scheme described above is only an example.

[0171] Step 804: The detection device determines the relationship between the speed and time of the target based on the echo signal of the target.

[0172] For example, the target to be detected may include one or more targets. When there are multiple targets, the detection device can determine the correspondence between velocity and time for each target. For example, the process of determining the correspondence between velocity and time can be found above. Figure 9 The relevant details in step 402 will not be repeated here.

[0173] Step 805: The detection device sends the first information to the control device.

[0174] For example, when there are multiple targets to be detected, the detection device can generate a first piece of information based on one or more of the correspondence between the velocity and time, acceleration information, and motion state information of each target, and send it to the control device. Alternatively, the detection device can generate a first piece of information for all targets to be detected and send it to the control device. The process of generating the first piece of information can be referred to step 403 above, and will not be elaborated further here.

[0175] Furthermore, the control device adjusts the vehicle's motion state based on the received first information to avoid a collision.

[0176] Based on the above introduction, in order to facilitate understanding of the control scheme provided in this application, specific embodiments will be described below.

[0177] In this embodiment, it is assumed that the control device is an intelligent driving domain controller. The first target is screened by the detection device triggered by the intelligent driving domain controller, or the first target is a target adaptively selected by the detection device based on the vehicle driving environment. Please refer to [link to relevant documentation]. Figure 10 This is a flowchart illustrating the detection method, which specifically includes:

[0178] 901. The detection device transmits detection signals into the detection space and receives echo signals.

[0179] For example, the detection space can be a space within a certain distance from the vehicle, and the received echo signal can be a signal reflected or detected by multiple targets within the detection space. After receiving the echo signal, the detection device can determine the position information of each target based on the echo signal of each target.

[0180] 902. The detection device determines whether the intelligent driving domain controller has triggered the selection rule of the target to be detected. If yes, then proceed to step 903; otherwise, continue to step 904.

[0181] The selection rule is used by the detection device to select a target to be detected from multiple targets included in the detection space. This selection rule is the setting rule described in step 703 above. This selection rule can be pre-issued to the detection device by the intelligent driving domain controller, and the detection device can store the selection rule after issuance. Thus, each time the detection device determines each target in the detection space based on the echo signal, it can select the target to be detected according to the locally stored selection rule.

[0182] 903. The detection device selects the target to be detected from multiple targets in the detection space according to the selection rules and the position information of each target in the detection space.

[0183] For example, the process of selecting the target to be detected according to the selection rules triggered by the intelligent driving domain controller can be referred to in step 704 above, and will not be elaborated on here.

[0184] 904. The detection device adaptively selects the target to be detected from multiple targets in the detection space based on the driving environment.

[0185] For example, the method of adaptive target selection in the environment can be found in the relevant description of step 803 above, and will not be repeated here.

[0186] 905. The detection device processes the echo signal of the target to be detected and determines the correspondence between the speed and time of the target.

[0187] For example, when processing the echo signal of the target to be detected, the echo signal and the detection signal can be mixed first to obtain an intermediate frequency signal, then the intermediate frequency signal can be de-skewing and discretely sampled to obtain a digital signal, and finally time-frequency analysis technology can be used to process the digital signal to obtain the velocity of the target at each moment, thereby obtaining the correspondence between the velocity and time of the target.

[0188] 906, the detection device sends the first message to the intelligent driving domain controller.

[0189] The first information may include the relationship between the speed and time of the target to be detected, the acceleration information of the target to be detected, or the motion state information of the target to be detected. The content of the first information and the form in which it is sent to the intelligent driving domain controller can be found in step 403 above, and will not be elaborated further here.

[0190] Based on the aforementioned detection method, this application also provides a detection device. Please refer to [link to relevant documentation]. Figure 10This is a possible structural schematic diagram of the detection device provided in this application. Figure 4 As shown, the detection device 1000 includes a processor 1001 and a transceiver 1002. Optionally, the detection device 1000 may also include a memory 1003, which may be coupled to the processor 1001 to store the necessary program instructions and data of the detection device 1000.

[0191] In one possible implementation, the detection device 1000 may be the detection device described in the foregoing embodiments, which can perform the functions of the detection device in the above method embodiments, such as for implementing the above... Figure 7 , Figure 8 , Figure 9 or Figure 4 The detection device in the method embodiment shown can also achieve the beneficial effects of the above method embodiment.

[0192] For example, when the detection device 1000 is used to achieve Figure 4 The detection device in the illustrated method embodiment functions as follows: Processor 1001 acquires the echo signal obtained from detecting the first target within a first time unit, determines the velocity-time correspondence of the first target based on the echo signal, and sends first information obtained based on the correspondence to the control device via transceiver 1002. The first information includes at least one of the following: the velocity-time correspondence of the first target, acceleration information of the first target, or motion state information of the first target; wherein the acceleration information of the first target is determined based on the velocity-time correspondence of the first target, and the motion state information of the first target is determined based on the acceleration information of the first target. A more detailed description of the processor 1001 and transceiver 1002 can be found in [reference needed]. Figure 11 The relevant descriptions in the illustrated method embodiments are directly derived and will not be repeated here. It should be understood that the processor 1001 in the embodiments of this application can be implemented by a processor or processor-related circuit modules, and the transceiver 1002 can be implemented by an interface circuit or interface circuit-related circuit modules.

[0193] This application also provides a control device; please refer to [link / reference]. Figure 4 The control device 1100 includes a processor 1101 and a transceiver 1102. Optionally, the control device 1100 may also include a memory 1103, which may be coupled to the processor 1101 to store the necessary program instructions and data of the control device 1100.

[0194] In one possible implementation, the control device 1100 may be the control device described in the foregoing embodiments, which can perform the functions of the control device in the above method embodiments, such as for implementing the above... Figure 7 ,Figure 8 , Figure 9 or Figure 4 The control device in the method embodiment shown can also achieve the beneficial effects of the above method embodiment.

[0195] This application also provides a terminal device. The terminal device may include any of the aforementioned detection devices and / or control devices, such as detection device 1000 and / or control device 1100. Further, optionally, the terminal device may also include a memory for storing programs or instructions. Of course, the terminal device may also include other devices, such as a wireless control device.

[0196] For example, the terminal device may be a vehicle (e.g., driverless car, smart car, electric car, or digital car), robot, surveying equipment, drone, smart home device (e.g., television, robot vacuum cleaner, smart lamp, audio system, smart lighting system, electrical control system, home background music, home theater system, intercom system, or video surveillance), smart manufacturing equipment (e.g., industrial equipment), smart transportation equipment (e.g., AGV, driverless vehicle, or truck), or smart terminal (mobile phone, computer, tablet, PDA, desktop computer, headphones, audio equipment, wearable device, in-vehicle device, virtual reality device, augmented reality device, etc.).

[0197] Based on the aforementioned detection method, this application also provides a chip, which includes at least one processor and interface circuitry. Further, optionally, the chip may also include a memory, wherein the processor executes computer programs or instructions stored in the memory, causing the chip to perform the aforementioned... Figure 7 , Figure 8 , Figure 9 or Figure 4 The method described in any of the embodiments.

[0198] Based on the aforementioned detection method, this application also provides a computer-readable storage medium storing a computer program or instructions. When the computer program or instructions are executed by the detection device, the detection device performs the aforementioned... Figure 7 , Figure 8 , Figure 9 or Figure 4 The method described in any of the embodiments.

[0199] Based on the aforementioned detection method, this application also provides a computer program product, which includes a computer program or instructions. When the computer program or instructions are executed by the detection device, the detection device performs the aforementioned... Figure 7 , Figure 8 , Figure 9 or ​The method described in any of the embodiments.

[0200] In this application, "at least one" means one or more, and "more than one" means two or more. "And / or" describes the relationship between related objects, indicating that three relationships can exist. For example, A and / or B can mean: A alone, A and B simultaneously, or B alone, where A and B can be singular or plural. "At least one of the following" or similar expressions refer to any combination of these items, including any combination of singular or plural items. For example, at least one of a, b, or c can mean: a, b, c, "a and b", "a and c", "b and c", or "a and b and c", where a, b, and c can be single or multiple. In the textual description of this application, the character " / " generally indicates that the preceding and following related objects are in an "or" relationship. In the formulas of this application, the character " / " indicates that the preceding and following related objects are in a "division" relationship. Additionally, in this application, the word "exemplarily" is used to indicate an example, illustration, or explanation. Any embodiment or design described as "example" in this application should not be construed as being more preferred or advantageous than other embodiments or designs. Alternatively, it can be understood that the use of the word "example" is intended to present concepts in a specific manner and does not constitute a limitation of this application.

[0201] It is understood that the various numerical designations used in this application are merely for descriptive convenience and are not intended to limit the scope of the embodiments of this application. The order of the process numbers described above does not imply the order of execution; the execution order of each process should be determined by its function and inherent logic. Terms such as "first," "second," and similar expressions are used to distinguish similar objects and are not necessarily used to describe a specific order or sequence. Furthermore, the terms "comprising" and "having," and any variations thereof, are intended to cover non-exclusive inclusion, such as including a series of steps or units. A method, system, product, or device is not necessarily limited to those steps or units explicitly listed, but may include other steps or units not explicitly listed or inherent to these processes, methods, products, or devices.

Claims

1. A method of detecting, characterized by, The method is suitable for a detection device, and comprises: obtaining echo signals obtained by detecting a first target in a first time unit; determining a corresponding relationship between a speed of the first target and time based on the echo signals; sending first information to a control device, the first information comprising at least one of the following: the corresponding relationship between the speed of the first target and time, acceleration information of the first target, or motion state information of the first target; wherein the acceleration information of the first target is determined according to the corresponding relationship between the speed of the first target and time, and the motion state information of the first target is determined according to the acceleration information of the first target.

2. The method of claim 1, wherein, The sending of the first information to the control device comprises: sending the first information to the control device through a detection stage interface of the detection device.

3. The method according to claim 1 or 2, characterized in that, The first target is determined according to a set rule, or the first target is determined according to a distance between the detection device and other vehicles in a detection environment.

4. The method according to any one of claims 1 to 3, characterized in that, The determining of the corresponding relationship between the speed of the first target and time based on the echo signals comprises: determining the speed of the first target at different times in a frame of echo signals obtained by detection.

5. The method of claim 4, wherein, The determining of the speed of the first target at different times comprises: segmenting the echo signals to obtain a plurality of sub-echo signals; respectively determining the speed of the first target corresponding to the plurality of sub-echo signals.

6. The method of claim 4, wherein, The determining of the speed of the first target at different times comprises: performing sliding window processing on the echo signals to obtain a plurality of sub-echo signals; respectively determining the speed of the first target corresponding to the plurality of sub-echo signals.

7. The method according to any one of claims 1 to 6, characterized in that, The motion state information comprises at least one of the following: uniform motion state, rapid acceleration motion state, acceleration motion state, rapid deceleration motion state, or deceleration motion state.

8. The method according to any one of claims 1 to 7, characterized in that, The motion state information of the first target comprises a confidence degree of the motion state corresponding to the first target.

9. The method of claim 8, wherein, The confidence degree of the motion state corresponding to the first target is calculated according to an error between the acceleration information of the first target and a set acceleration of the motion state corresponding to the first target.

10. The method according to any one of claims 1 to 9, characterized in that, The acceleration information of the first target comprises an acceleration of the first target and an acceleration error, the acceleration error being determined based on a signal-to-noise ratio of the echo signals; the acceleration combined with the acceleration error is used to determine the error between the acceleration of the first target and the set acceleration.

11. The method according to any one of claims 1 to 10, characterized in that, The echo signals comprise at least one of the following: an echo signal with the largest received intensity among a plurality of echo signals received in the first time unit; an echo signal with the earliest received time among the plurality of echo signals received in the first time unit.

12. A control method characterized by, The method is suitable for a control device, and comprises: receive first information from the detection device, the first information being determined based on echo signals obtained by detecting a first target in a first time unit; the first information comprising at least one of the following: a corresponding relationship between a velocity of the first target and time, acceleration information of the first target, or motion state information of the first target; wherein the acceleration information of the first target is determined according to the corresponding relationship between the velocity of the first target and time, and the motion state information of the first target is determined according to the acceleration information of the first target; determine a motion state of the first target according to the first information, and control the vehicle to avoid the first target according to the motion state of the first target.

13. The method of claim 12, wherein, The control device is connected to a detection stage interface of the detection device, and the first information is sent by the detection device through the detection stage interface of the detection device.

14. The method according to claim 12 or 13, characterized in that, The first target is determined according to a set rule, or the first target is determined according to a distance between the other vehicle in the detection environment and the ego vehicle.

15. The method according to any one of claims 12-14, characterized in that, The motion state information comprises at least one of the following: a uniform motion state, an emergency acceleration motion state, an acceleration motion state, an emergency deceleration motion state, or a deceleration motion state.

16. The method according to any one of claims 12-15, characterized in that, The motion state information of the first target comprises a confidence degree of the motion state corresponding to the first target.

17. The method of claim 16, wherein, The confidence degree of the motion state corresponding to the first target is calculated according to an error between the acceleration information of the first target and a set acceleration of the motion state corresponding to the first target.

18. The method according to any one of claims 12-17, characterized by, The acceleration information of the first target comprises an acceleration of the first target and an acceleration error, and the acceleration error is determined based on a signal-to-noise ratio of the echo signals; the acceleration combined with the acceleration error is used to determine the error between the acceleration of the first target and the set acceleration.

19. A detection device, characterized in that comprise a module or unit for performing the method of any one of claims 1-11.

20. A detection device, characterized by comprise a processor and a memory, wherein the memory stores instructions, and the processor executes the instructions to cause the detection device to perform the method of any one of claims 1-11.

21. A control device characterized by comprising: comprise a module or unit for performing the method of any one of claims 12-18.

22. A control device characterized by comprising: comprise a processor and a memory, wherein the memory stores instructions, and the processor executes the instructions to cause the control device to perform the method of any one of claims 12-18.

23. A terminal device, comprising: comprise the detection device of claim 19 or 20, and / or the control device of claim 21 or 22.

24. A computer-readable storage medium, characterized in that, store a program or instructions, which, when executed, implement the method of any one of claims 1-18.

25. A computer program product, characterised in that, comprise computer program code, which, when executed on a computer, causes the computer to perform the method of any one of claims 1-18.

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