Speed determination method, device and equipment

Abstract

The invention provides a speed determination method, device and equipment, and the method comprises the steps: obtaining the first point cloud data of a target object obtained through the measurement of a plurality of radars installed on a vehicle, and enabling a first azimuth angle to be the azimuth angle between the radars and the target object under a radar coordinate system; for each piece of first point cloud data, determining a second azimuth angle corresponding to the first point cloud data according to an angle relationship between a first azimuth angle of the first point cloud data and an installation angle of the first radar relative to the vehicle, an included angle between a connecting line of the to-be-measured target and an original point of the vehicle coordinate system and a coordinate axis of the vehicle coordinate system and the first point cloud data correspond to the first radar; and based on the first speed in each piece of first point cloud data and the second azimuth angle corresponding to each piece of first point cloud data, carrying out joint calculation, and determining the driving speed of the target object. According to the embodiment of the invention, the accuracy of speed calculation of the to-be-detected target in the detection overlapping region can be improved.

Description

Technical Field

[0001] The present application relates to the field of sensor technology, and in particular to a speed determination method, device and equipment. Background Art

[0002] Multi-radar fusion architecture is a system design framework that integrates multiple radar systems. In the multi-radar fusion architecture, multiple radar systems can work simultaneously and integrate their data to provide more comprehensive and accurate environmental perception and target tracking information.

[0003] In a multi-radar fusion architecture, the target to be measured will be detected by multiple radars in the radar detection overlapping area. For the speed calculation of the target to be measured in the detection overlapping area, the traditional multi-radar fusion architecture is to first use each single radar data processor to calculate the target speed, generate a single radar track, and then send it to the fusion center; the center completes the association and fusion to form a multi-millimeter-wave radar fusion track. However, this method of using the point cloud information of a single radar for speed calculation will cause serious information loss, resulting in low accuracy of speed calculation of the target to be measured in the detection overlapping area. Summary of the invention

[0004] The present application provides a speed determination method, device and equipment, which can improve the accuracy of speed solution of a target to be measured in a detection overlap area.

[0005] In a first aspect, an embodiment of the present application provides a speed determination method, the method comprising:

[0006] Acquire first point cloud data of the target object measured by multiple radars installed on the vehicle, wherein the first point cloud data measured by each radar includes a first speed and a first azimuth, the first speed is a component of the target object's travel speed on a line connecting the target object and the radar, and the first azimuth is an azimuth between the radar and the target object in a radar coordinate system;

[0007] For each first point cloud data, determine a second azimuth corresponding to the first point cloud data according to an angular relationship between a first azimuth of the first point cloud data and an installation angle of the first radar relative to the vehicle, wherein the second azimuth is an angle between a line connecting the target to be measured and the origin of the vehicle coordinate system in a vehicle coordinate system and a coordinate axis of the vehicle coordinate system, and the first point cloud data corresponds to the first radar;

[0008] Based on the first speed in each first point cloud data and the second azimuth corresponding to each first point cloud data, a joint solution is performed to determine the driving speed of the target object.

[0009] In a second aspect, the present application provides a speed determination device, the device comprising:

[0010] an acquisition module, configured to acquire first point cloud data of a target object measured by a plurality of radars installed on the vehicle, wherein the first point cloud data measured by each radar includes a first speed and a first azimuth, the first speed being a component of a travel speed of the target object on a line connecting the target object and the radar, and the first azimuth being an azimuth between the radar and the target object in a radar coordinate system;

[0011] A first determination module is used to determine, for each first point cloud data, a second azimuth corresponding to the first point cloud data according to an angular relationship between a first azimuth of the first point cloud data and an installation angle of the first radar relative to the vehicle, wherein the second azimuth is an angle between a line connecting a target to be measured and an origin of the vehicle coordinate system in a vehicle coordinate system and a coordinate axis of the vehicle coordinate system, and the first point cloud data corresponds to the first radar;

[0012] The second determination module is used to perform a joint calculation based on the first speed in each first point cloud data and the second azimuth corresponding to each first point cloud data to determine the driving speed of the target object.

[0013] In a third aspect, an embodiment of the present application provides an electronic device, the electronic device comprising: a processor and a memory storing computer program instructions;

[0014] When the processor executes the computer program instructions, the speed determination method in any one of the embodiments of the first aspect is implemented.

[0015] In a fourth aspect, an embodiment of the present application provides a computer storage medium having computer program instructions stored thereon, and when the computer program instructions are executed by a processor, a speed determination method as in any one of the embodiments in the first aspect is implemented.

[0016] In a fifth aspect, an embodiment of the present application provides a computer program product. When the instructions in the computer program product are executed by a processor of an electronic device, the electronic device executes a speed determination method as in any one of the embodiments in the first aspect above.

[0017] In a speed determination method, device and equipment provided in an embodiment of the present application, the method first converts the point cloud data of the target object measured by multiple radars installed on the vehicle from the first azimuth of the radar coordinate system to the second azimuth of the vehicle coordinate system for processing. This step ensures that the point cloud data measured by all radars are in the same coordinate system, eliminates the coordinate differences between different radar data, and provides a consistent data basis for subsequent speed solution. Next, the travel speed of the target object is determined by joint solution using the converted data. Due to the use of a multi-radar joint solution method, the solution speed and accuracy are improved compared with the traditional single radar solution. This is because the multi-radar joint solution can simultaneously use the point cloud data measured by multiple radars, avoiding the problem of information loss and inaccurate speed solution caused by insufficient single radar data, thereby improving the accuracy and reliability of speed solution. Therefore, by converting the data of multiple radars to the vehicle coordinate system and using the joint solution method, the accuracy of the speed solution of the target to be measured in the detection overlap area is effectively improved. BRIEF DESCRIPTION OF THE DRAWINGS

[0018] In order to more clearly illustrate the technical solution of the embodiments of the present application, the following is a brief introduction to the drawings required for use in the embodiments of the present application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without any creative work.

[0019] Figure 1 is a flow chart of a speed determination method provided by an embodiment of the present application;

[0020] Figure 2 is a schematic diagram of a vector of a first speed and a driving speed provided by an embodiment of the present application;

[0021] Figure 3 is a schematic diagram of a vector of a first speed, a driving speed, a first lateral component, and a second longitudinal component provided by an embodiment of the present application;

[0022] Figure 4 is a structural schematic diagram of a speed determination device provided in an embodiment of the present application;

[0023] Figure 5 It is a schematic diagram of the structure of an electronic device provided in an embodiment of the present application. DETAILED DESCRIPTION

[0024] In order to more clearly understand the above-mentioned objectives, features and advantages of the present disclosure, the scheme of the present disclosure will be further described below. It should be noted that the embodiments of the present disclosure and the features in the embodiments can be combined with each other without conflict.

[0025] In the following description, many specific details are set forth to facilitate a full understanding of the present disclosure, but the present disclosure may also be implemented in other ways different from those described herein; it is obvious that the embodiments in the specification are only part of the embodiments of the present disclosure, rather than all of the embodiments.

[0026] It should be noted that, in this article, relational terms such as "first" and "second" are only used to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Moreover, the term "comprising" or any other variant thereof is intended to cover non-exclusive inclusion, so that a process, method, article or device including a series of elements includes not only those elements, but also other elements not explicitly listed, or also includes elements inherent to such process, method, article or device. In the absence of further restrictions, the elements defined by the sentence "comprising a ..." do not exclude the existence of other identical elements in the process, method, article or device including the elements.

[0027] The multi-radar post-fusion architecture first uses the data processor of each single radar to perform track tracking, generate a single radar track, and then send it to the fusion center; the center completes the association and fusion to form a multi-millimeter-wave radar fusion track. This method does not use multi-radar point cloud information for speed solution. At present, the point cloud information of a single radar is mainly used for speed solution. For the multi-radar fusion architecture, the target in the radar detection overlapping area will be measured by multiple radars. If the point cloud information of a single radar is used for speed solution, the information loss is large. At the beginning of the track, the time required to store enough point cloud information for speed solution will also be longer, resulting in more time for the track to stabilize. At the same time, since the Doppler velocity is a vector, the direction of the Doppler velocity measured by different radars is inconsistent, so the point cloud data of different radars cannot be directly substituted into the traditional speed solution model for solution.

[0028] In order to solve the problems existing in the prior art, the embodiments of the present application provide a speed determination method, device and equipment.

[0029] The present application embodiment provides a speed determination method, device and apparatus. The speed determination method provided by the present application embodiment is first introduced below. Figure 1 As shown, the method specifically comprises the following steps:

[0030] S100, obtaining first point cloud data of a target object measured by multiple radars installed on a vehicle, wherein the first point cloud data measured by each radar includes a first speed and a first azimuth, the first speed being a component of a driving speed of the target object on a line connecting the target object and the radar, and the first azimuth being an azimuth between the radar and the target object in a radar coordinate system.

[0031] Optionally, in an embodiment of the present application, first, multiple radar systems are installed on the vehicle, and these radar systems can be distributed at different locations on the vehicle to cover all directions around the vehicle. And ensure that each radar system is in operation so that they can work simultaneously and detect surrounding target objects. Each radar system will detect the target object within its detection range and generate corresponding point cloud data. These point cloud data contain the location information and other attributes of the target object.

[0032] Subsequently, the corresponding point cloud data can be obtained through the data processor or interface of each radar system. These data can be stored and transmitted in various formats, such as two-dimensional or three-dimensional coordinate representation, speed information, etc.

[0033] Subsequently, relevant information of the target object, including the first speed and the first azimuth, is extracted from the point cloud data obtained by each radar system. The first speed represents the component of the target object's speed on the line connecting the target object and the radar, while the first azimuth represents the azimuth between the radar and the target object in the radar coordinate system. Finally, the first point cloud data of the target object obtained from each radar system is integrated for subsequent processing and analysis.

[0034] S200, for each first point cloud data, determine the second azimuth angle corresponding to the first point cloud data according to the angular relationship between the first azimuth angle of the first point cloud data and the installation angle of the first radar relative to the vehicle, the second azimuth angle being the angle between a line connecting the target to be measured and the origin of the vehicle coordinate system in the vehicle coordinate system and the coordinate axis of the vehicle coordinate system, and the first point cloud data corresponds to the first radar.

[0035] Optionally, in the embodiment of the present application, the second azimuth is the angle between the line connecting the target to be measured and the origin of the vehicle coordinate system in the vehicle coordinate system and the positive direction of the y-axis of the vehicle coordinate system. If x of the target to be measured in the vehicle coordinate system is greater than 0, the second azimuth is positive; if x of the target to be measured in the vehicle coordinate system is less than 0, the second azimuth is negative.

[0036] Optionally, in a feasible implementation of the present application, first, it is necessary to obtain the installation angle of each radar relative to the vehicle. This angle represents the direction difference between the radar and the front of the vehicle, which can be determined when the radar is installed.

[0037] For each measured first point cloud data, extract the first azimuth angle, which represents the relative direction between the radar and the target object in the radar's own coordinate system. Next, using trigonometric functions and angle addition and subtraction rules, the angle between the line connecting the target object relative to the vehicle coordinate origin and the positive direction of the y-axis of the vehicle coordinate system in the unified vehicle coordinate system is calculated according to the installation angle of the radar and the first azimuth angle, that is, the second azimuth angle. In the calculation process, it is necessary to consider whether the installation position of the radar is relative to the front, rear or side of the vehicle, and whether there is an inclination angle in the vertical direction. In addition, the positive and negative signs of the second azimuth angle are determined according to the positive and negative x-coordinate values ​​of the target object in the vehicle coordinate system, that is, when the target object is located in the positive direction of the x-axis of the vehicle coordinate system, the second azimuth angle is positive; otherwise, it is negative. This process ensures that all radar measured data can be accurately converted to the same vehicle coordinate system, providing a basis for the subsequent joint solution based on speed and azimuth angle.

[0038] S300: Perform a joint calculation based on a first speed in each first point cloud data and a second azimuth corresponding to each first point cloud data to determine a driving speed of the target object.

[0039] Optionally, in a feasible implementation of the present application, for the first point cloud data measured by each radar, the azimuth and the first speed of the target object in the vehicle coordinate system are known. Subsequently, the kinematic model of the radar and the data measured by multiple radars can be used to determine the speed of the target object through a joint solution method. Specifically, it involves the application of vector operations, least squares method or other mathematical models to infer the speed of the target object. The joint solution takes into account the measurement data of different radars and their respective azimuths, and comprehensively considers the information of multiple observations, thereby improving the accuracy of speed solution.

[0040] Specifically, in a specific embodiment of the present application, for each point cloud data measured by a radar, the data measured by different radars can first be unified into the same coordinate system, that is, the second azimuth corresponding to each point cloud data can be obtained. Then, the kinematic model of the radar is used to consider the relative motion relationship between the radar and the target object. Based on the data measured by the radar and the position and direction of the radar, the motion equation of the target object in the vehicle coordinate system is derived. Next, using the data measured by multiple radars, a joint solution model can be constructed. This model comprehensively considers the measurement data of different radars and their respective azimuths to maximize the use of all available information. Subsequently, the least squares method is used to fit the model to obtain the optimal velocity estimate, that is, the lateral and longitudinal components of the velocity in the vehicle coordinate system.

[0041] In these optional embodiments, by utilizing information from multiple radars, the motion state of the target object can be more fully understood, thereby improving the accuracy and reliability of velocity calculation.

[0042] In a speed determination method, device and equipment provided in an embodiment of the present application, the method first converts the point cloud data of the target object measured by multiple radars installed on the vehicle from the first azimuth of the radar coordinate system to the second azimuth of the vehicle coordinate system for processing. This step ensures that the point cloud data measured by all radars are in the same coordinate system, eliminates the coordinate differences between different radar data, and provides a consistent data basis for subsequent speed solution. Next, the travel speed of the target object is determined by joint solution using the converted data. Due to the use of a multi-radar joint solution method, the solution speed and accuracy are improved compared with the traditional single radar solution. This is because the multi-radar joint solution can simultaneously use the point cloud data measured by multiple radars, avoiding the problem of information loss and inaccurate speed solution caused by insufficient single radar data, thereby improving the accuracy and reliability of speed solution. Therefore, by converting the data of multiple radars to the vehicle coordinate system and using the joint solution method, the accuracy of the speed solution of the target to be measured in the detection overlap area is effectively improved.

[0043] In one embodiment, the above step 200 may specifically perform the following steps:

[0044] S210: For each first point cloud data, taking the sum of the first azimuth angle of the first point cloud data and the installation angle of the first radar relative to the vehicle as the second azimuth angle corresponding to the first point cloud data.

[0045] Optionally, in a possible implementation of the present application, in order to calculate the second azimuth, it is necessary to combine the first azimuth of the first point cloud data with the installation angle of the radar relative to the vehicle.

[0046] Specifically, it is necessary to determine the angle difference between the installation angle of the radar relative to the vehicle and the first azimuth of the first point cloud data. Since the installation direction of the radar may not be consistent with the forward direction of the vehicle, the positive and negative angles need to be considered.

[0047] If the installation direction of the radar is consistent with the vehicle's forward direction, the installation angle of the radar relative to the vehicle is added to the first azimuth of the first point cloud data. If the installation direction is opposite, the relative angles are subtracted. In this way, the second azimuth can be obtained.

[0048] In these optional embodiments, the azimuth of the first point cloud data is converted to the vehicle coordinate system by taking into account the installation angle of the radar relative to the vehicle, thereby ensuring the consistency of the azimuth. In this way, all azimuths are in the same coordinate system, which facilitates subsequent speed solution and data processing. Therefore, when performing joint solution, all data are in the same coordinate system, avoiding the complexity and uncertainty caused by coordinate system conversion, thereby improving the accuracy of speed solution.

[0049] In one embodiment, the above step 300 may specifically perform the following steps:

[0050] S310, performing joint construction based on the first velocity in each first point cloud data and the second azimuth corresponding to each first point cloud data, and determining a set of equations to be solved;

[0051] S320, determining the driving speed of the target object by solving the equation group.

[0052] Optionally, in a feasible implementation of the present application, for each radar measured first point cloud data, a first velocity and a second azimuth of the target object are obtained. For each radar measured data, an equation is constructed using a kinematic model of the radar and data measured by multiple radars.

[0053] Then, the equations obtained from each radar measurement are combined into an overall set of equations. Assuming there are N radar measurement data, there will be N sets of equations. Then, using the constructed set of equations, a numerical method or an analytical method is used to solve the velocity vector of the target object. For example, the velocity of the target object can be estimated by minimizing the error function by the least squares method.

[0054] In these optional embodiments, the first speed and the corresponding second azimuth in the first point cloud data measured by each radar are used to jointly construct and solve the equation group, which can achieve efficient use of multi-radar fusion data and accurate determination of driving speed. Such a method can make the most of the observation information of each radar, comprehensively consider the data of multiple observations, and avoid the problem of insufficient information or error accumulation that may occur when only a single radar data is used for speed calculation. By jointly constructing and solving the equation group, the accuracy and reliability of speed calculation can be improved, so as to more accurately understand the motion state and behavior characteristics of the target object, and provide more reliable data support for intelligent driving and environmental perception.

[0055] In one embodiment, the above step 310 may specifically perform the following steps:

[0056] S311, for each first point cloud data, determine the sine value and cosine value of the second azimuth angle corresponding to the first point cloud data according to the trigonometric function and the angle formula;

[0057] S312, according to a preset Doppler solution formula, using the first velocity in each first point cloud data, and the sine value and cosine value of the second azimuth angle corresponding to each first point cloud data, determine a solution equation group.

[0058] Optionally, in a possible implementation of the present application, first, the second azimuth angle can be calculated based on the angular relationship between the first azimuth angle in the first point cloud data and the installation angle of the radar relative to the vehicle. This angular relationship can be solved by trigonometric functions and angle formulas. For example, the second azimuth angle can be calculated using the sine and angle formula and the cosine and angle formula. Subsequently, the sine value and cosine value of the second azimuth angle can be calculated based on the obtained second azimuth angle using the properties of trigonometric functions. The calculation of the sine value and the cosine value will be used for the construction and solution of the subsequent set of equations.

[0059] Then, according to the preset Doppler solution formula, the first velocity, the sine value and the cosine value of the second azimuth in the first point cloud data measured by each radar are substituted into the formula to obtain an equation. For each radar measured data, an equation can be established. In this way, a system of equations consisting of multiple equations is obtained.

[0060] Through the above steps, the process of jointly constructing and solving the equation group for the first velocity and the corresponding second azimuth of each first point cloud data can be realized. Such a method can make full use of multi-radar fusion data and improve the accuracy and reliability of velocity solution.

[0061] In one embodiment, the above step 312 may specifically perform the following steps:

[0062] S3121, for each first point cloud data, substitute the first velocity corresponding to the first point cloud data and the sine value and cosine value of the second azimuth angle corresponding to the first point cloud data into the Doppler solution formula to obtain a first equation corresponding to each first point cloud data;

[0063] S3122, combining the first equations corresponding to each first point cloud data to obtain a set of equations to be solved;

[0064] S3123, converting the set of equations to be solved into a matrix form to obtain a matrix equation.

[0065] In these optional embodiments, in the embodiments, by substituting the sine value and cosine value of the first velocity and the second azimuth corresponding to each first point cloud data into the Doppler solution formula, the Doppler velocity equation corresponding to each point cloud data is obtained. The advantage of this is that the radar measurement data and the azimuth information of the target in the vehicle coordinate system are utilized to convert the radar measurement data into the movement speed of the target. This joint construction method combines the observation data of multiple radars, comprehensively considers the measurement results of different radars and their respective observation angles, thereby improving the accuracy and reliability of the velocity solution.

[0066] In one embodiment, the Doppler solution formula is:

[0067]

[0068] in, is the first velocity of the jth first point cloud data, v x is the first lateral component of the driving speed, v y is the first longitudinal component of the driving speed, j is the point cloud data number, α j is the second azimuth corresponding to the j-th first point cloud data;

[0069] The matrix equation is:

[0070] Optionally, in a specific embodiment of the present application, as Figure 3 As shown, velocity solution is essentially to convert v x and v y Projected to Doppler velocity v r direction, and consider the sum of these two velocity projections as the Doppler velocity, that is:

[0071] v r =v x sinα+v y cosα

[0072] Herev x and v y are the lateral and longitudinal components of the target speed (i.e., the speed of the target object), α is the azimuth of the target, and v r is the Doppler velocity (i.e., the first velocity), where the azimuth angle and Doppler velocity in the radar coordinate system are directly measurable by the radar. Note that v x 、v y and α should be expressed in the same coordinate system. In the traditional velocity solution process, it is considered that v x and v y is the component of the target velocity in the radar coordinate system, and the velocity determination method eliminated in this application considers that v x and v yIt is the component of the target velocity in the global coordinate system (i.e., the vehicle coordinate system), so considering the point cloud observation variable measured by the radar (i.e., the first point cloud data) Calculate the sine and cosine of the global azimuth (i.e. the second azimuth) and unify v x 、v y and azimuth coordinate system, and then directly obtain v in the global coordinate system through velocity solution x and v y The details are as follows:

[0073] First, calculate the global azimuth, which is the sine and cosine of the second azimuth:

[0074] sinα k = sin(θ i,j +γ i )=sinθ i,j cosγ i +sinγ i cosθ i,j

[0075] cosα k =cos(θ i,j +γ i )=cosθ i,j cosγ i -sinγ i sinθ i,j

[0076] Among them, θ i,j is the local azimuth of the point cloud (i.e. the first azimuth), γ i is the radar installation angle, i represents the radar number, α j is the global azimuth (the second azimuth), j represents the point cloud number measured by the radar. Through this step, the sine and cosine values ​​of the global azimuth are obtained from the local azimuth of the point cloud and the radar installation angle. This step is also equivalent to converting the point cloud observation variable (i.e., the first point cloud data) (R, v rj ,θ i,j ) is transferred from the local coordinate system to the global coordinate system and becomes (R,v rj ,α j ), where R is the slant distance of the point cloud measured by the radar, which does not change with the coordinates; v r The Doppler velocity (i.e., the first velocity) measured by the radar is the component of the target velocity in the radar azimuth. It is a vector whose magnitude and direction do not change with the coordinates. Its direction is always from the radar to the target direction. Figure 2 This is also the reason why the global velocity solution can be performed after the direction of the Doppler velocity is uniformly expressed in the global coordinate system (i.e., the vehicle coordinate system), θ i,jIt is the target azimuth measured by the radar. This quantity is based on the radar coordinate system. Therefore, when solving the global velocity, the global azimuth needs to be calculated from this azimuth.

[0077] Then, construct the equation group. If there are n point clouds belonging to the current target, the first point cloud data is (R, v rj ,α j ), then by the formula: v rj =v x sinα j +v y cosα j , we can get n equations, among which, v x 、v y is an unknown number, which can be rewritten into matrix form as shown below:

[0078]

[0079] It is worth noting that the v x 、v y are the lateral and longitudinal components of the velocity in the global coordinate system (i.e., the vehicle coordinate system), while in the traditional velocity solution, the lateral and longitudinal components of the velocity in the radar coordinate system are obtained. This also means that the traditional velocity solution processes multiple radar data and the result obtained is not accurate, because directly solving v together x 、v y The coordinate system is not unified.

[0080] In these optional embodiments, the obtained Doppler velocity equations are combined into a set of equations to be solved and then converted into a matrix form, which helps to solve the velocity of the target in a more efficient manner, thereby improving the efficiency of velocity solution.

[0081] In one embodiment, the above step 320 may specifically perform the following steps:

[0082] S321, solving the set of equations according to the third formula to obtain a first transverse component and a first longitudinal component;

[0083] S322, determining a travel speed according to the first lateral component and the first longitudinal component;

[0084] The third formula is: X = (A T A) -1 A T b;

[0085] in,

[0086] Optionally, in a specific implementation of the present application, A is a coefficient matrix, X is a velocity vector of the target object to be solved, and b is a known observation variable vector (ie, a first velocity).

[0087] Specifically, in this step, the observed variables can be substituted into the third formula and calculated using known parameters. According to the principle of least squares method, the observed data (i.e., the first velocity) is fitted by minimizing the residual, thereby determining the first lateral component and the first longitudinal component of the target object.

[0088] A first lateral component and a first longitudinal component of the target object are obtained, which respectively represent the lateral velocity and the longitudinal velocity of the target object in the vehicle coordinate system.

[0089] Then, using these two components, we can combine them into a velocity vector V. The transverse component of the velocity vector is v x , the longitudinal component is v y , the vector thus formed represents the speed of the target object in the vehicle coordinate system. In two-dimensional space, according to the properties of a right triangle, the Pythagorean theorem can be used to find the magnitude of the velocity vector, that is, the magnitude of the speed. In this way, by combining the lateral component and the longitudinal component into a vector and calculating the magnitude of the vector, the speed of the target object in the vehicle coordinate system can be obtained, thereby clearly expressing the motion state of the target object and providing an important information basis for subsequent target tracking and environmental perception.

[0090] In these optional embodiments, the combined solution method can comprehensively consider the measurement data of multiple radars and make full use of the observation information of each radar, thereby improving the accuracy and stability of speed solution. This helps the vehicle to perceive the surrounding environment more accurately, improve driving safety, and achieve more accurate target tracking and driving path planning.

[0091] In one embodiment, the driving speed includes a first lateral component and a first longitudinal component; after the above step 300, the method may specifically perform the following steps:

[0092] S400, performing a trigonometric operation on a first installation angle of the first radar relative to the vehicle according to a fourth formula based on the first lateral component and the first longitudinal component to determine a second lateral component and a second longitudinal component of the target object in a radar coordinate system of the first radar;

[0093] S500, tracking the target object according to the second transverse component and the second longitudinal component, and determining a motion trajectory of the target object relative to the first radar;

[0094] Among them, the fourth formula is:

[0095] Among them, vl x is the second lateral velocity, vl y is the second longitudinal velocity, γ1 is the first installation angle of the first radar relative to the vehicle, v x is the first transverse component, v y is the first longitudinal component.

[0096] Optionally, in a feasible implementation of the present application, first, the initial state of the target object is initialized, including information such as position, velocity, and acceleration. Then, according to the dynamic model and motion state equation of the target object, the state at the current moment is used to predict the target state at the next moment. Specifically, it involves the state transition equation and process noise model.

[0097] When new observation data (i.e., the second lateral component and the second longitudinal component) are available, the predicted target state is compared with the observation data, and the target state is corrected using the measurement information through Bayesian filtering theory. This repeats the prediction and update steps to continuously track the motion trajectory of the target object. Each update adjusts the estimated value of the target state based on the latest observation data and updates the uncertainty of the state. This enables real-time monitoring and prediction of the target object, providing more accurate environmental perception and target tracking capabilities for the intelligent driving system.

[0098] Optionally, in a complete embodiment of the present application, an example of global velocity solution under a multi-radar front fusion architecture is given below to further illustrate the implementation effect of the velocity determination method involved in the present application. Radars 1 and 2 mentioned in this example are the right rear corner radar and the left rear corner radar, respectively.

[0099] For a target that is in the detection area of ​​two radars at the same time, the point cloud data detected by the two radars are as follows:

[0100]

[0101] The sine and cosine values ​​of the global azimuth (i.e., the second azimuth) of these point clouds are calculated, as shown in the following table:

[0102]

[0103]

[0104] Then, the system of equations is constructed, whose matrix representation is as follows:

[0105]

[0106] Then solve the equations to obtain v in the global coordinate system x =0.6278 and v y=3.4879, the target is a vehicle traveling in the same direction as the vehicle, and the solution result is accurate.

[0107] Usually, speed calculation requires the accumulation of point cloud data measured by multiple frames of radar. The calculation can only be performed when the point cloud data reaches a certain amount. From the above example, we can see that if the point cloud observation of a single radar is used for calculation, the accumulation speed of point cloud data will be much slower, which is not conducive to the start of a fast track.

[0108] The speed solution determination method involved in the present invention solves the defect that the traditional solution method cannot use multiple radar data for speed solution at the same time. The present application uses data measured by multiple radars to perform global speed solution, and makes great use of the original point cloud data information, so that the solution result is more accurate. In addition, in the process of starting the track, the speed solution will not be performed until the point cloud accumulates to a certain number. Since the present application uses multiple radar data for solution, for targets in the overlapping area of ​​radar measurement, two radars measure the target at the same time, and more measurement values ​​will be returned in the same frame, so the speed solution conditions will be reached faster, thereby shortening the track start time.

[0109] Figure 4 A schematic structural diagram of a speed determination device provided in another embodiment of the present application is shown. For ease of explanation, only the parts related to the embodiment of the present application are shown.

[0110] Reference Figure 4 , the speed determining means may include:

[0111] An acquisition module 401 is used to acquire first point cloud data of a target object measured by multiple radars installed on a vehicle, wherein the first point cloud data measured by each radar includes a first speed and a first azimuth, the first speed is a component of the target object's travel speed on a line connecting the target object and the radar, and the first azimuth is an azimuth between the radar and the target object in a radar coordinate system;

[0112] A first determination module 402 is used to determine, for each first point cloud data, a second azimuth corresponding to the first point cloud data according to an angular relationship between a first azimuth of the first point cloud data and an installation angle of the first radar relative to the vehicle, wherein the second azimuth is an angle between a line connecting the target to be measured and the origin of the vehicle coordinate system in a vehicle coordinate system and a coordinate axis of the vehicle coordinate system, and the first point cloud data corresponds to the first radar;

[0113] The second determination module 403 is used to perform a joint calculation based on the first speed in each first point cloud data and the second azimuth corresponding to each first point cloud data to determine the driving speed of the target object.

[0114] In one embodiment, the first determining module 402 may include:

[0115] The first determination submodule is used to, for each first point cloud data, use the sum of the first azimuth angle of the first point cloud data and the installation angle of the first radar relative to the vehicle as the second azimuth angle corresponding to the first point cloud data.

[0116] In one embodiment, the second determining module 403 may include:

[0117] A second determination submodule is used to perform joint construction based on the first velocity in each first point cloud data and the second azimuth corresponding to each first point cloud data to determine the solution equation group;

[0118] The third determination submodule is used to determine the driving speed of the target object by solving the equation group.

[0119] In one embodiment, the second determining submodule may include:

[0120] A first determining unit is used to determine, for each first point cloud data, a sine value and a cosine value of a second azimuth angle corresponding to the first point cloud data according to a trigonometric function and an angle formula;

[0121] The second determination unit is used to determine the solution equation group according to a preset Doppler solution formula by using the first velocity in each first point cloud data and the sine value and cosine value of the second azimuth angle corresponding to each first point cloud data.

[0122] In one embodiment, the second determining unit may include:

[0123] A substitution subunit is used to substitute, for each first point cloud data, a first velocity corresponding to the first point cloud data and a sine value and a cosine value of a second azimuth corresponding to the first point cloud data into a Doppler solution formula to obtain a first equation corresponding to each first point cloud data;

[0124] A combining subunit, used for combining the first equations corresponding to each first point cloud data to obtain a solver equation group;

[0125] In one embodiment, the speed determination device may further include:

[0126] The conversion module is used to convert the equation group to be solved into a matrix form to obtain a matrix equation.

[0127] In one embodiment, the Doppler solution formula is:

[0128]

[0129] in, is the first velocity of the jth first point cloud data, v x is the first lateral component of the driving speed, vy is the first longitudinal component of the driving speed, j is the point cloud data number, α j is the second azimuth corresponding to the j-th first point cloud data;

[0130] The matrix equation is:

[0131] In one embodiment, the third determining submodule may include:

[0132] A first calculation unit, used for solving the set of equations according to a third formula to obtain a first transverse component and a first longitudinal component;

[0133] a third determining unit, configured to determine a travel speed according to the first lateral component and the first longitudinal component;

[0134] Among them, the third formula is: X = (A T A) -1 A T b;

[0135] in,

[0136] In one embodiment, the driving speed includes a first lateral component and a first longitudinal component; the speed determination device may further include:

[0137] a calculation module, configured to perform a trigonometric operation on a first installation angle of the first radar relative to the vehicle according to a fourth formula based on the first lateral component and the first longitudinal component, to determine a second lateral component and a second longitudinal component of the target object in a radar coordinate system of the first radar;

[0138] A tracking module, used to track the target object according to the second transverse component and the second longitudinal component, and determine a motion trajectory of the target object relative to the first radar;

[0139] Among them, the fourth formula is:

[0140] Among them, vl x is the second lateral velocity, vl y is the second longitudinal velocity, γ1 is the first installation angle of the first radar relative to the vehicle, v x is the first transverse component, v y is the first longitudinal component.

[0141] It should be noted that the information interaction, execution process, etc. between the above-mentioned devices / units are based on the same concept as the method embodiment of the present application, and are devices corresponding to the above-mentioned battery thermal runaway warning method. All implementation methods in the above-mentioned method embodiment are applicable to the embodiments of the device. Its specific functions and technical effects can be found in the method embodiment part, which will not be repeated here.

[0142] The technicians in the relevant field can clearly understand that for the convenience and simplicity of description, only the division of the above-mentioned functional units and modules is used as an example for illustration. In practical applications, the above-mentioned function allocation can be completed by different functional units and modules as needed, that is, the internal structure of the device can be divided into different functional units or modules to complete all or part of the functions described above. The functional units and modules in the embodiment can be integrated in a processing unit, or each unit can exist physically separately, or two or more units can be integrated in one unit. The above-mentioned integrated unit can be implemented in the form of hardware or in the form of software functional units. In addition, the specific names of the functional units and modules are only for the convenience of distinguishing each other, and are not used to limit the scope of protection of this application. The specific working process of the units and modules in the above-mentioned system can refer to the corresponding process in the aforementioned method embodiment, which will not be repeated here.

[0143] Figure 5 A schematic diagram of the hardware structure of an electronic device provided in an embodiment of the present application is shown.

[0144] The device may include a processor 501 and a memory 502 storing program instructions.

[0145] When the processor 501 executes the program, the steps in any of the above method embodiments are implemented.

[0146] Exemplarily, the program may be divided into one or more modules / units, one or more modules / units are stored in the memory 502, and executed by the processor 501 to complete the present application. One or more modules / units may be a series of program instruction segments capable of completing a specific function, and the instruction segments are used to describe the execution process of the program in the device.

[0147] Specifically, the processor 501 may include a central processing unit (CPU), or an application specific integrated circuit (ASIC), or may be configured to implement one or more integrated circuits of the embodiments of the present application.

[0148] The memory 502 may include a large capacity memory for data or instructions. By way of example and not limitation, the memory 502 may include a hard disk drive (HDD), a floppy disk drive, a flash memory, an optical disk, a magneto-optical disk, a magnetic tape, or a universal serial bus (USB) drive or a combination of two or more of these. In appropriate cases, the memory 502 may include a removable or non-removable (or fixed) medium. In appropriate cases, the memory 502 may be inside or outside the integrated gateway disaster recovery device. In a specific embodiment, the memory 502 is a non-volatile solid-state memory.

[0149] The memory may include read-only memory (ROM), random access memory (RAM), magnetic disk storage media devices, optical storage media devices, flash memory devices, electrical, optical or other physical / tangible memory storage devices. Thus, typically, the memory includes one or more tangible (non-transitory) readable storage media (e.g., memory devices) encoded with software including computer executable instructions, and when the software is executed (e.g., by one or more processors), it is operable to perform the operations described with reference to the method according to an aspect of the present disclosure.

[0150] The processor 501 implements any one of the methods in the above embodiments by reading and executing program instructions stored in the memory 502 .

[0151] In one example, the electronic device may further include a communication interface 503 and a bus 510. The processor 501, the memory 502, and the communication interface 503 are connected via the bus 510 and communicate with each other.

[0152] The communication interface 503 is mainly used to implement communication between various modules, devices, units and / or equipment in the embodiments of the present application.

[0153] Bus 510 includes hardware, software or both, and the parts of online data flow billing equipment are coupled to each other. For example, but not limitation, bus may include accelerated graphics port (AGP) or other graphics bus, enhanced industrial standard architecture (EISA) bus, front-end bus (FSB), hypertransport (HT) interconnection, industrial standard architecture (ISA) bus, infinite bandwidth interconnection, low pin count (LPC) bus, memory bus, micro channel architecture (MCA) bus, peripheral component interconnection (PCI) bus, PCI-Express (PCI-X) bus, serial advanced technology attachment (SATA) bus, video electronics standard association local (VLB) bus or other suitable bus or two or more of these combinations. In appropriate cases, bus 510 may include one or more buses. Although the present application embodiment describes and shows a specific bus, the present application considers any suitable bus or interconnection.

[0154] In addition, in combination with the method in the above embodiment, the embodiment of the present application can provide a storage medium for implementation. The storage medium stores program instructions; when the program instructions are executed by a processor, any one of the methods in the above embodiment is implemented.

[0155] An embodiment of the present application further provides a chip, which includes a processor and a communication interface, wherein the communication interface and the processor are coupled, and the processor is used to run programs or instructions to implement the various processes of the above-mentioned method embodiment, and can achieve the same technical effect. To avoid repetition, it will not be repeated here.

[0156] It should be understood that the chip mentioned in the embodiments of the present application can also be called a system-level chip, a system chip, a chip system or a system-on-chip chip, etc.

[0157] An embodiment of the present application provides a computer program product, which is stored in a storage medium. The program product is executed by at least one processor to implement the various processes of the above-mentioned method embodiment and can achieve the same technical effect. To avoid repetition, it will not be repeated here.

[0158] It should be clear that the present application is not limited to the specific configuration and processing described above and shown in the figures. For the sake of simplicity, a detailed description of the known method is omitted here. In the above embodiments, several specific steps are described and shown as examples. However, the method process of the present application is not limited to the specific steps described and shown, and those skilled in the art can make various changes, modifications and additions, or change the order between the steps after understanding the spirit of the present application.

[0159] The functional modules shown in the above block diagram can be implemented as hardware, software, firmware or their combination. When implemented in hardware, it can be, for example, an electronic circuit, an application specific integrated circuit (ASIC), suitable firmware, a plug-in, a function card, etc. When implemented in software, the elements of the present application are programs or code segments that are used to perform the required tasks. Programs or code segments can be stored in machine-readable media, or transmitted on a transmission medium or a communication link by a data signal carried in a carrier wave. "Machine-readable media" can include any medium that can store or transmit information. Examples of machine-readable media include electronic circuits, semiconductor memory devices, ROM, flash memory, erasable ROM (EROM), floppy disks, CD-ROMs, optical disks, hard disks, optical fiber media, radio frequency (RF) links, etc. Code segments can be downloaded via computer grids such as the Internet, intranets, etc.

[0160] It should also be noted that the exemplary embodiments mentioned in this application describe some methods or systems based on a series of steps or devices. However, this application is not limited to the order of the above steps, that is, the steps can be performed in the order mentioned in the embodiment, or in a different order from the embodiment, or several steps can be performed simultaneously.

[0161] Aspects of the present disclosure are described above with reference to the flowchart and / or block diagram of the method, device (system) and program product according to the embodiment of the present disclosure. It should be understood that each box in the flowchart and / or block diagram and the combination of each box in the flowchart and / or block diagram can be implemented by computer program instructions. These program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer or other programmable data processing device to produce a machine so that these instructions executed by the processor of the computer or other programmable data processing device enable the implementation of the function / action specified in one or more boxes of the flowchart and / or block diagram. Such a processor can be, but is not limited to, a general-purpose processor, a special-purpose processor, a special application processor or a field programmable logic circuit. It can also be understood that each box in the block diagram and / or flowchart and the combination of boxes in the block diagram and / or flowchart can also be implemented by dedicated hardware that performs a specified function or action, or can be implemented by a combination of dedicated hardware and computer instructions.

[0162] The above are only specific implementation methods of the present application. Those skilled in the art can clearly understand that for the convenience and simplicity of description, the specific working processes of the systems, modules and units described above can refer to the corresponding processes in the aforementioned method embodiments, and will not be repeated here. It should be understood that the protection scope of the present application is not limited to this. Any technician familiar with the technical field can easily think of various equivalent modifications or replacements within the technical scope disclosed in this application, and these modifications or replacements should be included in the protection scope of this application.

Claims

1. A speed determination method, characterized in that: The method comprises: Acquire first point cloud data of a target object measured by multiple radars installed on a vehicle, wherein the first point cloud data measured by each radar includes a first speed and a first azimuth, the first speed being a component of the travel speed of the target object on a line connecting the target object and the radar, and the first azimuth being an azimuth between the radar and the target object in a radar coordinate system; For each of the first point cloud data, determine a second azimuth angle corresponding to the first point cloud data according to an angular relationship between a first azimuth angle of the first point cloud data and an installation angle of the first radar relative to the vehicle, wherein the second azimuth angle is an angle between a line connecting a target to be measured and an origin of the vehicle coordinate system in a vehicle coordinate system and a coordinate axis of the vehicle coordinate system, and the first point cloud data corresponds to the first radar; Based on the first speed in each of the first point cloud data and the second azimuth corresponding to each of the first point cloud data, a joint solution is performed to determine the driving speed of the target object.

2. The method according to claim 1, characterized in that The method of determining, for each of the first point cloud data, a second azimuth angle corresponding to the first point cloud data according to an angular relationship between a first azimuth angle of the first point cloud data and an installation angle of the first radar relative to the vehicle, comprises: For each of the first point cloud data, the sum of the first azimuth angle of the first point cloud data and the installation angle of the first radar relative to the vehicle is used as the second azimuth angle corresponding to the first point cloud data.

3. The method according to claim 1, characterized in that The determining the driving speed of the target object by performing a joint calculation based on the first speed in each of the first point cloud data and the second azimuth corresponding to each of the first point cloud data includes: Based on the first velocity in each of the first point cloud data and the second azimuth corresponding to each of the first point cloud data, a joint construction is performed to determine a set of equations to be solved; The driving speed of the target object is determined by solving the set of equations.

4. The method according to claim 3, characterized in that The step of jointly constructing and determining a set of equations to be solved based on the first velocity in each of the first point cloud data and the second azimuth corresponding to each of the first point cloud data comprises: For each of the first point cloud data, determine the sine value and cosine value of the second azimuth angle corresponding to the first point cloud data according to trigonometric functions and angle formulas; According to a preset Doppler solution formula, the solution equation group is determined by using the first velocity in each of the first point cloud data and the sine value and cosine value of the second azimuth angle corresponding to each of the first point cloud data.

5. The method according to claim 4, characterized in that The method of determining the solution equation group according to the preset Doppler solution formula by using the first velocity in each of the first point cloud data and the sine value and cosine value of the second azimuth angle corresponding to each of the first point cloud data comprises: For each of the first point cloud data, a first velocity corresponding to the first point cloud data and a sine value and a cosine value of a second azimuth angle corresponding to the first point cloud data are substituted into the Doppler solution formula to obtain a first equation corresponding to each of the first point cloud data; Combining the first equations corresponding to each of the first point cloud data to obtain the solution equation group; After combining the first equations corresponding to each of the first point cloud data to obtain the solution equation group, the method further includes: The set of equations to be solved is converted into a matrix form to obtain a matrix equation.

6. The method according to claim 5, characterized in that The Doppler solution formula is: in, is the first velocity of the jth first point cloud data, v x is the first lateral component of the driving speed, v y is the first longitudinal component of the driving speed, j is the point cloud data number, α j is the second azimuth corresponding to the j-th first point cloud data; The matrix equation is:

7. The method according to claim 6, characterized in that Determining the travel speed of the target object by solving the set of equations includes: Solving the set of equations according to the third formula to obtain the first transverse component and the first longitudinal component; determining the travel speed according to the first lateral component and the first longitudinal component; Wherein, the third formula is: X=(A T A) -1 A T b; in, 8. The method according to claim 1, characterized in that The travel speed includes a first lateral component and a first longitudinal component; After determining the driving speed of the target object by performing a joint calculation based on the first speed in each of the first point cloud data and the second azimuth corresponding to each of the first point cloud data, the method further includes: According to the first lateral component and the first longitudinal component, a trigonometric function operation is performed on a first installation angle of the first radar relative to the vehicle according to a fourth formula to determine a second lateral component and a second longitudinal component of the target object in a radar coordinate system of the first radar; Tracking the target object according to the second transverse component and the second longitudinal component to determine a motion trajectory of the target object relative to the first radar; Wherein, the fourth formula is: Among them, vl x is the second lateral velocity, vl y is the second longitudinal velocity, γ1 is the first installation angle of the first radar relative to the vehicle, v x is the first transverse component, v y is the first longitudinal component.

9. A speed determination device, characterized in that: The device comprises: an acquisition module, configured to acquire first point cloud data of a target object measured by a plurality of radars installed on a vehicle, wherein the first point cloud data measured by each radar includes a first speed and a first azimuth, wherein the first speed is a component of a travel speed of the target object on a line connecting the target object and the radar, and the first azimuth is an azimuth between the radar and the target object in a radar coordinate system; a first determining module, configured to determine, for each of the first point cloud data, a second azimuth corresponding to the first point cloud data according to an angular relationship between a first azimuth of the first point cloud data and an installation angle of the first radar relative to the vehicle, wherein the second azimuth is an angle between a line connecting a target to be measured and an origin of the vehicle coordinate system in a vehicle coordinate system and a coordinate axis of the vehicle coordinate system, and the first point cloud data corresponds to the first radar; The second determination module is used to perform a joint calculation based on a first speed in each of the first point cloud data and a second azimuth corresponding to each of the first point cloud data to determine the driving speed of the target object.

10. An electronic device, characterized in that: The device comprises: a processor and a memory storing computer program instructions; When the processor executes the computer program instructions, the speed determination method according to any one of claims 1 to 8 is implemented.

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