CN115270066B - A method, system, device, and medium for determining the relative velocity of a target object. - Google Patents
A method, system, device, and medium for determining the relative velocity of a target object.Info
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- CN115270066B CN115270066B CN202210912557.7A CN202210912557A CN115270066B CN 115270066 B CN115270066 B CN 115270066B CN 202210912557 A CN202210912557 A CN 202210912557A CN 115270066 B CN115270066 B CN 115270066B
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- G—PHYSICS
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- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F17/00—Digital computing or data processing equipment or methods, specially adapted for specific functions
- G06F17/10—Complex mathematical operations
- G06F17/16—Matrix or vector computation, e.g. matrix-matrix or matrix-vector multiplication, matrix factorization
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01S—RADIO DIRECTION-FINDING; RADIO NAVIGATION; DETERMINING DISTANCE OR VELOCITY BY USE OF RADIO WAVES; LOCATING OR PRESENCE-DETECTING BY USE OF THE REFLECTION OR RERADIATION OF RADIO WAVES; ANALOGOUS ARRANGEMENTS USING OTHER WAVES
- G01S13/00—Systems using the reflection or reradiation of radio waves, e.g. radar systems; Analogous systems using reflection or reradiation of waves whose nature or wavelength is irrelevant or unspecified
- G01S13/02—Systems using reflection of radio waves, e.g. primary radar systems; Analogous systems
- G01S13/50—Systems of measurement based on relative movement of target
- G01S13/58—Velocity or trajectory determination systems; Sense-of-movement determination systems
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01S—RADIO DIRECTION-FINDING; RADIO NAVIGATION; DETERMINING DISTANCE OR VELOCITY BY USE OF RADIO WAVES; LOCATING OR PRESENCE-DETECTING BY USE OF THE REFLECTION OR RERADIATION OF RADIO WAVES; ANALOGOUS ARRANGEMENTS USING OTHER WAVES
- G01S7/00—Details of systems according to groups G01S13/00, G01S15/00, G01S17/00
- G01S7/02—Details of systems according to groups G01S13/00, G01S15/00, G01S17/00 of systems according to group G01S13/00
- G01S7/41—Details of systems according to groups G01S13/00, G01S15/00, G01S17/00 of systems according to group G01S13/00 using analysis of echo signal for target characterisation; Target signature; Target cross-section
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Abstract
本发明提供一种目标对象相对速度确定方法、系统、设备、介质，通过获取目标对象的多个雷达点的方位角，确定各所述雷达点的方位角正弦值和方位角余弦值；基于各所述雷达点的方位角正弦值和方位角余弦值生成第一矩阵和第二矩阵，确定第三矩阵，根据所述第三矩阵确定矩阵行列式值、第三矩阵的特征值；若所述矩阵行列式值大于第一预设阈值，且特征商大于第二预设阈值，对所述第三矩阵进行正则化处理；基于所述雷达点的地面径向速度、正则化处理后的第三矩阵和第二矩阵确定所述目标对象相对于本车的目标对象相对速度，所述雷达点的地面径向速度通过本车的纵向速度、横向速度和所述方位角确定，所述方位角通过所述本车的前毫米波雷达采集得到。
This invention provides a method, system, device, and medium for determining the relative velocity of a target object. The method involves acquiring the azimuth angles of multiple radar points on the target object, determining the sine and cosine values of the azimuth angles for each radar point, generating a first matrix and a second matrix based on the sine and cosine values of the azimuth angles of each radar point, determining a third matrix, and determining the matrix determinant and eigenvalues of the third matrix based on the third matrix. If the matrix determinant is greater than a first preset threshold and the eigenvalue is greater than a second preset threshold, the third matrix is regularized. The relative velocity of the target object with respect to the vehicle is determined based on the ground radial velocity of the radar points, the regularized third matrix, and the second matrix. The ground radial velocity of the radar points is determined by the longitudinal and lateral velocity of the vehicle and the azimuth angle, which is acquired by the vehicle's front millimeter-wave radar.
Description
Technical Field
The application relates to the technical field of vehicle radar speed measurement, in particular to a method, a system, equipment and a medium for determining the relative speed of a target object.
Background
In the automatic driving technique, it is extremely important for accurate measurement of the vehicle speed. In the prior art, the point of the millimeter wave radar on the target object obtained by obtaining signals through each channel of the front millimeter wave radar is the radial speed of the front radar relative to the vehicle measured under the polar coordinate system, the speed of the front millimeter wave radar relative to the vehicle generated when the front millimeter wave radar strikes a certain position of the target is represented, the number of the points of the front millimeter wave radar on the same target depends on the size of the target, the distance of the target and the material quality of the target, the estimated speed of the target is more accurate when the points are often more, but certain situations exist, such as the points are generated when the radar strikes the wheels of the target, the relative radial speed is often large when the points strike the tire due to the linear speed of the wheels, the speed estimation of the target under the vehicle coordinate system is influenced by the points including a pile of noise points detected by the front radar, and the speed estimation of the target under the vehicle coordinate system is also influenced. In addition, including if the points on the target object are all near the line AB, i.e., equivalent to collinear, there is a great impact on solving the solution of the linear equation set, and also on the speed estimation of the target in the vehicle coordinate system. Therefore, in the prior art, there are various problems that the measurement of the target speed is wrong due to too many factors influencing the measurement, low test precision and the like.
Disclosure of Invention
In view of the above-mentioned shortcomings of the prior art, the present invention provides a solution, a system, a device, a medium for estimating a target speed based on a detection radar, so as to solve the above-mentioned technical problems.
The invention provides a method for manufacturing a semiconductor device, which comprises the following steps:
a method of determining a relative speed of a target object, the method of determining an estimated speed of the target object comprising:
acquiring azimuth angles of a plurality of radar points of a target object, and determining azimuth angle sine values and azimuth angle cosine values of the radar points;
Generating a first matrix and a second matrix based on azimuth sine values and azimuth cosine values of the radar points, and determining a third matrix, wherein the second matrix is an inverse matrix of the first matrix, and the third matrix is a product of the first matrix and the second matrix;
determining matrix determinant values and characteristic values of a third matrix according to the third matrix;
if the matrix determinant value is larger than a first preset threshold value and the characteristic quotient is larger than a second preset threshold value, regularizing the third matrix, wherein the characteristic quotient is the quotient of the maximum characteristic value and the minimum characteristic value of the third matrix;
And determining the relative speed of the target object relative to the target object of the vehicle based on the ground radial speed of the radar point, the regularized third matrix and the second matrix, wherein the ground radial speed of the radar point is determined by the longitudinal speed, the transverse speed and the azimuth angle of the vehicle, and the azimuth angle is acquired by the front millimeter wave radar of the vehicle.
In an embodiment of the present application, the first matrix is a matrix of n×2, n is a number of radar points acquired by the target object, a first column of the first matrix is an azimuth cosine value of each radar point, and a second column of the first matrix is an azimuth sine value of each radar point;
The second matrix is a transposed matrix of the first matrix, and the second matrix is a 2*n matrix;
the third matrix is a second matrix multiplied by the first matrix, and the third matrix is a matrix of 2 x 2.
In one embodiment of the present application, the ground radial velocity of the radar point comprises:
Collecting a vehicle CAN signal based on the vehicle CAN, and obtaining the longitudinal speed and the transverse speed of the vehicle according to the vehicle CAN signal;
and respectively projecting the longitudinal speed and the transverse speed of the vehicle to the direction of the connecting line of the vehicle and the radar point, wherein the ground radial speed of the radar point is the projection value of the longitudinal speed of the vehicle in the direction of the connecting line of the vehicle and the radar point plus the projection value of the transverse speed of the vehicle in the direction of the connecting line of the vehicle and the radar point.
In an embodiment of the present application, if the matrix determinant value is greater than a first preset threshold value and the feature quotient is greater than a second preset threshold value, regularizing the third matrix includes the steps of:
introducing regularization to process the third matrix to obtain an optimized third matrix solution set;
Introducing regularization iteration to optimize the third matrix according to preset times, combining the third matrix after each iteration to calculate a characteristic quotient, judging whether the characteristic quotient of each iteration is larger than a second preset threshold value, if not, determining that the calculated ground radial velocity of the radar point is accurate and reserved, and if so, discarding the calculated ground radial velocity of the radar point.
In an embodiment of the present application, the preset number of times is five, and after the regularization iteration is introduced into the third matrix for five times, if the eigenvector calculated according to the third matrix is still greater than the second preset threshold, the relative speed of the target object with respect to the target object of the host vehicle is abandoned.
In an embodiment of the present application, the third matrix introducing regularization iteration process includes the steps of:
And calculating the characteristic quotient of the third matrix after regularization every time the third matrix is subjected to regularization, stopping L2 regularization on the third matrix if the calculated characteristic quotient of the third matrix is not greater than a second preset threshold value, and reserving the ground radial speed of the radar point calculated according to the third matrix after regularization.
In an embodiment of the present application, the third matrix introducing regularization iteration process further includes the steps of:
And calculating matrix determinant values of the third matrix after regularization every time the third matrix is subjected to regularization, and if the matrix determinant values of the third matrix after regularization are larger than a first preset threshold value, abandoning the calculation of the relative speed of the target object relative to the target object of the vehicle by using the third matrix.
In an embodiment of the present application, regularizing the third matrix includes:
l1 regularization or L2 regularization.
A system for estimating a target speed based on a detection radar, comprising:
the acquisition module acquires azimuth angles of a plurality of radar points of the target object, and determines an azimuth angle sine value and an azimuth angle cosine value of the radar points;
The calculation module generates a first matrix and a second matrix based on azimuth sine values and azimuth cosine values of the radar points, determines a third matrix, wherein the second matrix is an inverse matrix of the first matrix, the third matrix is a product of the first matrix and the second matrix, and determines the relative speed of the target object relative to the target object of the vehicle based on the ground radial speed of the radar points, the regularized third matrix and the second matrix;
And the optimization module is used for determining matrix determinant values and characteristic values of the third matrix according to the third matrix, and carrying out regularization treatment on the third matrix if the matrix determinant values are larger than a first preset threshold value and the characteristic quotient is larger than a second preset threshold value, wherein the characteristic quotient is the quotient of the maximum characteristic value and the minimum characteristic value of the third matrix.
An electronic device, the electronic device comprising:
One or more processors;
Storage means for storing one or more programs that, when executed by the one or more processors, cause the electronic device to implement the target object relative velocity determination method of any of claims 1 to 9.
A computer-readable storage medium having stored thereon a computer program which, when executed by a processor of a computer, causes the computer to perform the target object relative velocity determination method of any one of claims 1 to 9.
The invention has the beneficial effects that:
according to the method, the radial speed of the vehicle under the polar coordinate system is converted into the absolute radial speed relative to the ground, the absolute radial speed matrix equation of the millimeter wave Lei Dadian cloud data relative to the ground is combined and established, the absolute radial speed matrix equation solution set is calculated to obtain the speed of the target point, whether a pathological matrix exists or not is judged, L1 or L2 regularization adjustment is introduced to optimize the pathological matrix solution set, errors are eliminated more accurately, and the speed of the target is calculated.
It is to be understood that both the foregoing general description and the following detailed description are exemplary and explanatory only and are not restrictive of the application as claimed.
Drawings
The accompanying drawings, which are incorporated in and constitute a part of this specification, illustrate embodiments consistent with the application and together with the description, serve to explain the principles of the application. It is evident that the drawings in the following description are only some embodiments of the present application and that other drawings may be obtained from these drawings without inventive effort for a person of ordinary skill in the art. In the drawings:
FIG. 1 is a schematic diagram showing a positional relationship between a radar and a target according to an exemplary embodiment of the present application;
FIG. 2 is a schematic diagram illustrating a positional relationship between a radar and a target in accordance with an exemplary embodiment of the present application;
FIG. 3 is a schematic diagram of a system architecture shown in an exemplary embodiment of the present application;
FIG. 4 is a schematic diagram showing a disease matrix judgment step according to an exemplary embodiment of the present application;
FIG. 5 is a schematic diagram illustrating a ill-conditioned matrix optimization step according to an exemplary embodiment of the application;
fig. 6 shows a schematic diagram of a computer system suitable for use in implementing an embodiment of the application.
Detailed Description
Further advantages and effects of the present invention will become readily apparent to those skilled in the art from the disclosure herein, by referring to the accompanying drawings and the preferred embodiments. The invention may be practiced or carried out in other embodiments that depart from the specific details, and the details of the present description may be modified or varied from the spirit and scope of the present invention. It should be understood that the preferred embodiments are presented by way of illustration only and not by way of limitation.
It should be noted that the illustrations provided in the following embodiments merely illustrate the basic concept of the present invention by way of illustration, and only the components related to the present invention are shown in the drawings and are not drawn according to the number, shape and size of the components in actual implementation, and the form, number and proportion of the components in actual implementation may be arbitrarily changed, and the layout of the components may be more complicated.
In the following description, numerous details are set forth in order to provide a more thorough explanation of embodiments of the present invention, it will be apparent, however, to one skilled in the art that embodiments of the present invention may be practiced without these specific details, in other embodiments, well-known structures and devices are shown in block diagram form, rather than in detail, in order to avoid obscuring the embodiments of the present invention.
It should be noted that radar speed measurement mainly uses the Doppler Effect (Doppler Effect) principle that when a target approaches the radar antenna, the frequency of the reflected signal will be higher than the frequency of the transmitter, whereas when the target approaches the antenna, the frequency of the reflected signal will be lower than the frequency of the transmitter. Thus, the relative speed between the target and the radar can be calculated by means of the frequency change value (the target flies towards the radar, the Doppler frequency is positive, and the Doppler frequency is negative when the target flies away from the radar). As shown in fig. 1, the embodiment of the application relates to millimeter wave radar speed measurement, and the millimeter wave radar is a radar working in millimeter wave band (MILLIMETER WAVE) detection. Typically millimeter waves refer to the frequency domain (wavelength 1-10 mm) of 30-300 GHz. The millimeter wave has the wavelength between centimetre wave and light wave, so that the millimeter wave has the advantages of microwave guidance and photoelectric guidance.
As shown in fig. 2, a method for determining a relative speed of a target object, the method comprising:
S210, acquiring azimuth angles of a plurality of radar points of a target object, and determining azimuth angle sine values and azimuth angle cosine values of the radar points;
S220, generating a first matrix and a second matrix based on azimuth sine values and azimuth cosine values of the radar points, and determining a third matrix, wherein the second matrix is an inverse matrix of the first matrix, and the third matrix is a product of the first matrix and the second matrix;
S230, determining matrix determinant values and characteristic values of a third matrix according to the third matrix;
S240, if the matrix determinant value is greater than a first preset threshold value and the characteristic quotient is greater than a second preset threshold value, regularizing the third matrix, wherein the characteristic quotient is the quotient of the maximum characteristic value and the minimum characteristic value of the third matrix;
S250, determining the relative speed of the target object relative to the target object of the vehicle based on the ground radial speed of the radar point, the third matrix and the second matrix after regularization treatment, wherein the ground radial speed of the radar point is determined by the longitudinal speed, the transverse speed and the azimuth angle of the vehicle, and the azimuth angle is acquired by the front millimeter wave radar of the vehicle.
As shown in fig. 1, the moving speed of the vehicle is decomposed, the radial speed along the straight line direction of the vehicle-target point is calculated, and the absolute radial speed relative to the ground is obtained by converting the point cloud speed measured by the projection of the millimeter wave radar onto the target point. And (3) combining to form an absolute radial matrix equation of millimeter wave radar point cloud data relative to the ground by obtaining a data set, and calculating a solution set of the absolute radial velocity matrix equation to obtain the velocity of the target point.
Regularization (Regularization) is a generic term for a class of methods in machine learning that introduce additional information into the original loss function in order to prevent overfitting and improve model generalization performance. That is, the objective function becomes the original loss function+the additional term, and there are two general types of additional terms, english called L1-norm and L2-norm, chinese called L1 regularization and L2 regularization, or L1 norm and L2 norm (actually, the square of the L2 norm). L2 regularization can prevent model overfitting.
The ground radial velocity of the radar point comprises:
collecting a vehicle CAN signal based on the vehicle CAN, and obtaining the longitudinal speed Vx and the transverse speed Vy of the vehicle according to the vehicle CAN signal;
And projecting the longitudinal speed Vx and the transverse speed Vy of the vehicle to the radial speed direction of the millimeter Bao Leida under the polar coordinate, and acquiring the absolute radial speed of the millimeter wave Lei Dadian cloud relative to the ground according to a first preset formula.
The first preset formula is:
RRotg=Vx*cosα+Vy*sinα;
Wherein RRotg is the absolute radial velocity relative to the ground in the polar coordinate system, and α is the azimuth of the millimeter wave radar generation point.
The method comprises the steps of receiving some vehicle CAN signals on a vehicle body CAN to obtain some vehicle information, estimating some vehicle information by a vehicle state estimation module to obtain the information of Vx and Vy of the vehicle, projecting the Vx and Vy of the vehicle to the radial speed direction of a millimeter wave radar under polar coordinates to obtain the absolute radial speed of a millimeter wave Lei Dadian cloud relative to the ground, and converting all point cloud data according to a first preset formula to obtain the absolute radial speed as shown in the first preset formula.
The step of calculating the absolute radial velocity matrix equation solution to obtain the velocity of the target point comprises the following steps:
Establishing a second preset formula for calculating the absolute radial speed of the millimeter wave Lei Dadian cloud relative to the ground based on a least square method, simplifying the second preset formula into a third preset formula, and solving the absolute radial speed of the millimeter wave Lei Dadian cloud data relative to the ground through a transposed matrix.
In an embodiment of the present invention, the second preset formula is:
Wherein RRotg is the absolute radial speed of the millimeter wave Lei Dadian cloud relative to the ground, alpha is the azimuth angle of the millimeter wave radar striking a point on a target vehicle, 1 to n represent the number of the point clouds striking the target vehicle, vx_obj is the longitudinal speed of the target vehicle under the vehicle coordinate system, and Vy_obj is the transverse speed of the target vehicle under the vehicle coordinate system;
In theory, the accuracy of estimating the speed of the target point by utilizing the millimeter wave radar point cloud data depends on the number of the points, the millimeter wave radar is hit on the same target point, the speed of the target is estimated according to a least square method, and the calculation is performed by combining a second preset formula.
In an embodiment of the present invention, the third predetermined formula is y=ax, wherein Y isA isI.e. the first matrix, x is
Wherein the second preset formula may be reduced to y=ax,
And multiplying both sides of the third preset formula by the transposed matrix A T of A to obtain A TY＝AT Ax, wherein A T is a second matrix and A T A is a third matrix.
Wherein A T A is a matrix solution set and is a reversible matrix, and x is the radial velocity of the millimeter wave Lei Dadian cloud relative to the ground.
Since there are many points on the object, the a matrix is a matrix of a plurality of rows and two columns, that is, a matrix of n×2, which is not a square matrix, and the inversion operation cannot be performed, so both sides of the equation are multiplied by a T (the transposed matrix of the a matrix) to make it a square matrix of 2×2, the equation is converted into a matrix of a TA＝ATAx,AT a now being 2×2, assuming ATA is a reversible matrix, and the solution of the vector of x is successful at this time.
In an embodiment of the present invention, as shown in fig. 4, the more the number of point clouds is, the more accurate the estimated speed of the target point is, but there are often specific situations, such as radar hitting the wheels of the target vehicle, because there is a linear speed of the moving wheels, the points hitting the moving tires are often larger than the points hitting the vehicle except the tires, the relative radial speed is larger than the general points, and there are a plurality of noise points detected by the radar, and further, if hitting the target vehicle, there are many points, but these points are all near the AB straight line, that is, equivalent to being collinear, there is a great influence on the solution for solving the linear equation set, which may cause occurrence of a disease matrix, that is, the third matrix may be a disease matrix, affecting the ground radial speed of the radar points calculated by the third matrix, and further affecting the relative speed accuracy of the target object with respect to the target object of the vehicle, so the method needs to determine whether the third matrix is a disease matrix, including the steps of:
S410, calculating a value of a determinant of the matrix A T A, judging whether the value of the determinant is larger than a preset threshold, if so, continuing to solve the radial velocity of the millimeter wave Lei Dadian cloud relative to the ground, and if not, directly discarding the radial velocity of the millimeter wave Lei Dadian cloud relative to the ground calculated by using the absolute radial velocity matrix;
S420, solving the eigenvalue of the matrix A T A, dividing the maximum eigenvalue obtained by solving by the minimum eigenvalue to obtain the condition number of the matrix A T A, judging whether the condition number of the matrix A T A is larger than a preset threshold, if not, the matrix A T A is not a disease state matrix, and if so, the matrix A T A is a disease state matrix.
In one embodiment of the present invention, as shown in fig. 5, the step of introducing regularization adjustment to optimize the solution set of the disease state matrix includes:
S510, regularization is introduced into a solution of the absolute radial velocity of the millimeter wave Lei Dadian cloud relative to the ground, so that an optimized pathological matrix solution set is obtained;
S520, introducing regularization iteration optimization of the pathological matrix according to preset times, calculating the condition number of the pathological matrix after each iteration, judging whether the condition number of each iteration is larger than a preset threshold value, if not, determining that the calculated radial velocity of the millimeter wave Lei Dadian cloud relative to the ground is accurate and reserved, and if so, discarding the calculated velocity.
After each iteration, the condition number is calculated, whether the condition number is larger than a preset threshold value or not is judged, if the condition number is larger than the preset threshold value, the iteration is continued for 5 times, and if the condition number is larger than the preset threshold value after 5 times, the estimated speed of the target point is abandoned.
In an embodiment of the present invention, the solution of the radial velocity of the millimeter wave Lei Dadian cloud with respect to the ground is expressed as x= (a TA)-1*AT Y;
The regularized optimal solution set is expressed as x= (A TA+λI)-1*AT Y).
As shown in fig. 3, a system for estimating a target speed based on a detection radar, comprising:
the acquisition module acquires azimuth angles of a plurality of radar points of the target object, and determines an azimuth angle sine value and an azimuth angle cosine value of the radar points;
The calculation module generates a first matrix and a second matrix based on azimuth sine values and azimuth cosine values of the radar points, determines a third matrix, wherein the second matrix is an inverse matrix of the first matrix, the third matrix is a product of the first matrix and the second matrix, and determines the relative speed of the target object relative to the target object of the vehicle based on the ground radial speed of the radar points, the regularized third matrix and the second matrix;
And the optimization module is used for determining matrix determinant values and characteristic values of the third matrix according to the third matrix, and carrying out regularization treatment on the third matrix if the matrix determinant values are larger than a first preset threshold value and the characteristic quotient is larger than a second preset threshold value, wherein the characteristic quotient is the quotient of the maximum characteristic value and the minimum characteristic value of the third matrix.
The embodiment of the application also provides electronic equipment, which comprises one or more processors and a storage device, wherein the storage device is used for storing one or more programs, and the electronic equipment is enabled to realize the target object relative speed determining method provided in the above embodiments when the one or more programs are executed by the one or more processors.
Fig. 6 shows a schematic diagram of a computer system suitable for use in implementing an embodiment of the application. It should be noted that, the computer system 600 of the electronic device shown in fig. 6 is only an example, and should not impose any limitation on the functions and the application scope of the embodiments of the present application.
As shown in fig. 6, the computer system 600 includes a central processing unit (Central Processing Unit, CPU) 601 that can perform various appropriate actions and processes, such as performing the methods described in the above embodiments, according to a program stored in a Read-Only Memory (ROM) 602 or a program loaded from a storage portion 608 into a random access Memory (Random Access Memory, RAM) 603. In the RAM 603, various programs and data required for system operation are also stored. The CPU 601, ROM 602, and RAM 603 are connected to each other through a bus 604. An Input/Output (I/O) interface 605 is also connected to bus 604.
Connected to the I/O interface 605 are an input section 606 including a keyboard, a mouse, and the like, an output section 607 including a display such as a Cathode Ray Tube (CRT), a Liquid crystal display (Liquid CRYSTAL DISPLAY, LCD), and a speaker, a storage section 608 including a hard disk, and the like, and a communication section 609 including a network interface card such as a LAN (Local Area Network) card, a modem, and the like. The communication section 609 performs communication processing via a network such as the internet. The drive 610 is also connected to the I/O interface 605 as needed. Removable media 611 such as a magnetic disk, an optical disk, a magneto-optical disk, a semiconductor memory, or the like is installed as needed on drive 610 so that a computer program read therefrom is installed as needed into storage section 608.
In particular, according to embodiments of the present application, the processes described above with reference to flowcharts may be implemented as computer software programs. For example, embodiments of the present application include a computer program product comprising a computer program embodied on a computer readable medium, the computer program comprising a computer program for performing the method shown in the flowchart. In such an embodiment, the computer program may be downloaded and installed from a network through the communication portion 609, and/or installed from the removable medium 611. When executed by a Central Processing Unit (CPU) 601, performs the various functions defined in the system of the present application.
It should be noted that, the computer readable medium shown in the embodiments of the present application may be a computer readable signal medium or a computer readable storage medium, or any combination of the two. The computer readable storage medium may be, for example, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any combination thereof. More specific examples of a computer-readable storage medium may include, but are not limited to, an electrical connection having one or more wires, a portable computer diskette, a hard disk, a Random Access Memory (RAM), a read-Only Memory (ROM), an erasable programmable read-Only Memory (Erasable Programmable Read Only Memory, EPROM), a flash Memory, an optical fiber, a portable compact disc read-Only Memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing. In the present application, a computer-readable signal medium may comprise a data signal propagated in baseband or as part of a carrier wave, with a computer-readable computer program embodied therein. Such a propagated data signal may take any of a variety of forms, including, but not limited to, electro-magnetic, optical, or any suitable combination of the foregoing. A computer readable signal medium may also be any computer readable medium that is not a computer readable storage medium and that can communicate, propagate, or transport a program for use by or in connection with an instruction execution system, apparatus, or device. A computer program embodied on a computer readable medium may be transmitted using any appropriate medium, including but not limited to wireless, wireline, etc., or any suitable combination of the foregoing.
The flowcharts and block diagrams in the figures illustrate the architecture, functionality, and operation of possible implementations of systems, methods and computer program products according to various embodiments of the present application. Where each block in the flowchart or block diagrams may represent a module, segment, or portion of code, which comprises one or more executable instructions for implementing the specified logical function(s). It should also be noted that, in some alternative implementations, the functions noted in the block may occur out of the order noted in the figures. For example, two blocks shown in succession may, in fact, be executed substantially concurrently, or the blocks may sometimes be executed in the reverse order, depending upon the functionality involved. It will also be noted that each block of the block diagrams or flowchart illustration, and combinations of blocks in the block diagrams or flowchart illustration, can be implemented by special purpose hardware-based systems which perform the specified functions or acts, or combinations of special purpose hardware and computer instructions.
The units involved in the embodiments of the present application may be implemented by software, or may be implemented by hardware, and the described units may also be provided in a processor. Wherein the names of the units do not constitute a limitation of the units themselves in some cases.
Another aspect of the present application also provides a computer-readable storage medium having stored thereon a computer program which, when executed by a processor of a computer, causes the computer to perform the target object relative velocity determination method as described above. The computer-readable storage medium may be included in the electronic device described in the above embodiment or may exist alone without being incorporated in the electronic device.
Another aspect of the application also provides a computer program product or computer program comprising computer instructions stored in a computer readable storage medium. The processor of the computer device reads the computer instructions from the computer-readable storage medium, and the processor executes the computer instructions, so that the computer device performs the target object relative velocity determination method provided in the above-described respective embodiments.
The above embodiments are merely illustrative of the principles of the present invention and its effectiveness, and are not intended to limit the invention. Modifications and variations may be made to the above-described embodiments by those skilled in the art without departing from the spirit and scope of the invention. It is therefore intended that all equivalent modifications and changes made by those skilled in the art without departing from the spirit and technical spirit of the present invention shall be covered by the appended claims.
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