CN112731320A - Method, device and equipment for estimating error data of vehicle-mounted radar and storage medium - Google Patents
Method, device and equipment for estimating error data of vehicle-mounted radar and storage medium Download PDFInfo
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Abstract
The application relates to a method, a device, equipment and a storage medium for estimating error data of a vehicle-mounted radar, wherein the method comprises the following steps: determining first position information of a static target at each sampling moment in preset time based on a vehicle-mounted radar to obtain a first position information set; acquiring a first vehicle speed and a first yaw rate at each sampling moment; determining second position information of the static target at each sampling moment based on first position information of the static target at the first sampling moment and the first vehicle speed and the first yaw rate at each sampling moment to obtain a second position information set; and determining error data of the vehicle-mounted radar based on the first position information set and the second position information set, wherein the error data comprises a vehicle speed error, a yaw rate error and an installation azimuth angle error of the vehicle-mounted radar. Therefore, the vehicle speed error, the yaw rate error and the installation azimuth angle error can be estimated on line at the same time to complete error correction, and no special requirement is required on the running condition of the vehicle.
Description
Technical Field
The present disclosure relates to radar technologies, and in particular, to a method, an apparatus, a device, and a storage medium for estimating error data of a vehicle radar.
Background
The intelligent driving system is a new trend of vehicle development, and the radar system, especially the millimeter wave radar system, has wide application in the intelligent driving system because of the advantages of low cost, all-weather work, accurate distance measurement and the like. The vehicle-mounted radar system can measure information such as the position, the angle and the Doppler velocity of a target object around a vehicle body in real time, track the target object by combining motion information of the vehicle, and obtain the distance and the velocity of the target object in a self-vehicle coordinate system.
Factors influencing the tracking performance of the vehicle-mounted radar system on the target object include external factors except the measurement accuracy of a sensor of the vehicle-mounted radar system, and mainly include an installation azimuth angle error, a vehicle speed deviation and a yaw rate error of the radar system.
Although the error of the installation azimuth angle is calibrated on line, the installation azimuth angle of the radar system has certain error inevitably caused by factors such as looseness and aging of mechanical parts and the like along with the prolonging of the service time of a vehicle, and the reduction of the system precision is directly brought by the deviation of a small angle; the vehicle speed and the yaw rate are important input signals of the radar system, generally, vehicle speed information is obtained by comprehensively calculating the wheel speed measured by a wheel speed sensor, wherein tire pressure, load and abrasion can affect the measurement accuracy of the wheel speed sensor, so that the vehicle speed information has certain deviation from the actual vehicle speed; the yaw rate is generally obtained by measuring through a micro inertial sensor, and the micro inertial sensor can have a certain offset error or zero offset during measurement due to the influence of using time, ambient temperature, vibration and the like.
It can be seen that although the radar system is strictly corrected when leaving the factory, when the vehicle runs, there will inevitably exist some offsets due to vibration, collision or loss influence of other mechanical structures, so as to reduce the accuracy of the radar system, and therefore it is very necessary to estimate the vehicle speed error, yaw rate error and installation azimuth error based on the radar system and complete online correction, so as to reduce the influence caused by the estimation.
Disclosure of Invention
The embodiment of the application provides a method, a device, equipment and a storage medium for estimating error data of a vehicle-mounted radar, which can estimate a vehicle speed error, a yaw rate error and an installation azimuth error of the vehicle-mounted radar on line simultaneously on the premise of not increasing additional equipment and cost so as to correct the errors, thereby reducing the influence of the errors on radar application.
In one aspect, an embodiment of the present application provides a method for estimating error data of a vehicle-mounted radar, including:
determining first position information of a static target at each sampling moment in preset time based on a vehicle-mounted radar to obtain a first position information set;
acquiring a first vehicle speed and a first yaw rate at each sampling moment;
determining second position information of the static target at each sampling moment based on first position information of the static target at the first sampling moment and the first vehicle speed and the first yaw rate at each sampling moment to obtain a second position information set;
and determining error data of the vehicle-mounted radar based on the first position information set and the second position information set, wherein the error data comprises a vehicle speed error, a yaw rate error and an installation azimuth angle error of the vehicle-mounted radar.
Optionally, determining second position information of the stationary target at each sampling time based on the first position information of the stationary target at the first sampling time and the first vehicle speed and the first yaw rate at each sampling time comprises:
for one of the sampling instants: determining the longitudinal position variation of the static target at the current sampling moment based on the current sampling moment and the first vehicle speed of each sampling moment before the current sampling moment; determining the transverse position variation of the static target at the current sampling moment based on the current sampling moment and the first vehicle speed and the first yaw rate at each sampling moment before the current sampling moment; and determining second position information of the static target at the current sampling moment based on the first position information at the first sampling moment, the longitudinal position variation and the transverse position variation.
Optionally, determining error data of the vehicle-mounted radar based on the first set of location information and the second set of location information includes:
establishing an observation equation at each sampling moment based on the first position information set and the second position information set to obtain an observation equation set;
and carrying out iterative solution on the observation equation set by using a nonlinear optimization method to obtain a vehicle speed error, a yaw angular velocity error and an installation azimuth angle error.
Optionally, the observation equation at each sampling time includes a first observation equation and a second observation equation;
establishing an observation equation for each sampling instant based on the first set of location information and the second set of location information, comprising:
for one of the sampling instants: performing coordinate conversion on first position information of the current sampling moment based on a first coordinate conversion matrix, and performing coordinate conversion on second position information of the current sampling moment based on a current second coordinate conversion matrix to obtain converted first position information and converted second position information; a first observation equation is determined based on the converted longitudinal coordinates of the first position information and the converted longitudinal coordinates of the second position information, and a second observation equation is determined based on the converted lateral coordinates of the first position information and the converted lateral coordinates of the second position information.
Optionally, the method further includes the step of obtaining a current second coordinate transformation matrix; acquiring a current second coordinate transformation matrix, including:
determining the orientation angle variation of the static target at the current sampling moment based on the current sampling moment and the first yaw velocity of each sampling moment before the current sampling moment;
the current second coordinate conversion matrix is determined based on the orientation angle variation.
On the other hand, the embodiment of the present application provides an estimation apparatus for vehicle-mounted radar error data, including:
the first determining module is used for determining first position information of the static target at each sampling moment in preset time based on the vehicle-mounted radar to obtain a first position information set;
the acquisition module is used for acquiring a first vehicle speed and a first yaw rate at each sampling moment;
the second determining module is used for determining second position information of the static target at each sampling moment based on first position information of the static target at the first sampling moment and the first vehicle speed and the first yaw rate at each sampling moment to obtain a second position information set;
and the third determining module is used for determining error data of the vehicle-mounted radar based on the first position information set and the second position information set, wherein the error data comprises a vehicle speed error, a yaw rate error and an installation azimuth angle error of the vehicle-mounted radar.
Optionally, the second determining module is further configured to, for one of the sampling time instants: determining the longitudinal position variation of the static target at the current sampling moment based on the current sampling moment and the first vehicle speed of each sampling moment before the current sampling moment; determining the transverse position variation of the static target at the current sampling moment based on the current sampling moment and the first vehicle speed and the first yaw rate at each sampling moment before the current sampling moment; and determining second position information of the static target at the current sampling moment based on the first position information at the first sampling moment, the longitudinal position variation and the transverse position variation.
Optionally, the third determining module is further configured to establish an observation equation at each sampling time based on the first position information set and the second position information set to obtain an observation equation set;
and carrying out iterative solution on the observation equation set by using a nonlinear optimization method to obtain a vehicle speed error, a yaw angular velocity error and an installation azimuth angle error.
In another aspect, an embodiment of the present application provides an apparatus, where the apparatus includes a processor and a memory, where the memory stores at least one instruction or at least one program, and the at least one instruction or the at least one program is loaded by the processor and executes the above estimation method for vehicle-mounted radar error data.
In another aspect, an embodiment of the present application provides a computer storage medium, where at least one instruction or at least one program is stored in the storage medium, and the at least one instruction or the at least one program is loaded and executed by a processor to implement the above-mentioned method for estimating vehicle-mounted radar error data.
The method, the device, the equipment and the storage medium for estimating the error data of the vehicle-mounted radar have the following beneficial effects that:
determining first position information of a static target at each sampling moment in preset time based on a vehicle-mounted radar to obtain a first position information set; acquiring a first vehicle speed and a first yaw rate at each sampling moment; determining second position information of the static target at each sampling moment based on first position information of the static target at the first sampling moment and the first vehicle speed and the first yaw rate at each sampling moment to obtain a second position information set; and determining error data of the vehicle-mounted radar based on the first position information set and the second position information set, wherein the error data comprises a vehicle speed error, a yaw rate error and an installation azimuth angle error of the vehicle-mounted radar. Therefore, the vehicle speed error, the yaw rate error and the installation azimuth angle error can be estimated on line at the same time to complete error correction, and no special requirement is required on the running condition of the vehicle.
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In order to more clearly illustrate the technical solutions in the embodiments of the present application, the drawings needed to be used in the description of the embodiments are briefly introduced below, and it is obvious that the drawings in the following description are only some embodiments of the present application, and it is obvious for those skilled in the art to obtain other drawings based on these drawings without creative efforts.
Fig. 1 is a schematic flowchart of a method for estimating error data of a vehicle-mounted radar according to an embodiment of the present disclosure;
fig. 2 is a schematic diagram of an application scenario provided in an embodiment of the present application;
FIG. 3 is a schematic diagram of an iterative curve of an installation azimuth error of a vehicle-mounted radar according to an embodiment of the present application;
FIG. 4 is a schematic illustration of a convergence curve of a vehicle speed error provided by an embodiment of the present application;
FIG. 5 is a schematic diagram illustrating a convergence curve of a yaw-rate error provided by an embodiment of the present application;
fig. 6 is a schematic structural diagram of an apparatus for estimating vehicle radar error data according to an embodiment of the present disclosure;
fig. 7 is a block diagram of a hardware structure of a server of a method for estimating vehicle-mounted radar error data according to an embodiment of the present application.
Detailed Description
The technical solutions in the embodiments of the present application will be clearly and completely described below with reference to the drawings in the embodiments of the present application, and it is obvious that the described embodiments are only a part of the embodiments of the present application, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present application.
It should be noted that the terms "first," "second," and the like in the description and claims of this application and in the drawings described above are used for distinguishing between similar elements and not necessarily for describing a particular sequential or chronological order. It is to be understood that the data so used is interchangeable under appropriate circumstances such that the embodiments of the application described herein are capable of operation in sequences other than those illustrated or described herein. Furthermore, the terms "comprises," "comprising," and "having," and any variations thereof, are intended to cover a non-exclusive inclusion, such that a process, method, system, article, or server that comprises a list of steps or elements is not necessarily limited to those steps or elements expressly listed, but may include other steps or elements not expressly listed or inherent to such process, method, article, or apparatus.
In order to improve the tracking precision of a vehicle-mounted radar to a target object and reduce the influence of various errors such as a vehicle speed error, a yaw rate error, a radar installation azimuth angle error and the like, the embodiment of the application provides a method for estimating vehicle-mounted radar error data on the one hand.
The following describes a specific embodiment of an estimation method for vehicle-mounted radar error data, fig. 1 is a schematic flow chart of the estimation method for vehicle-mounted radar error data provided by the embodiment of the present application, and the present specification provides the method operation steps as in the embodiment or the flow chart, but may include more or less operation steps based on conventional or non-inventive labor. The order of steps recited in the embodiments is merely one manner of performing the steps in a multitude of orders and does not represent the only order of execution. In practice, the system or server product may be implemented in a sequential or parallel manner (e.g., parallel processor or multi-threaded environment) according to the embodiments or methods shown in the figures. Specifically, as shown in fig. 1, the method may include:
s101: the method comprises the steps of determining first position information of a static target at each sampling moment in preset time based on a vehicle-mounted radar, and obtaining a first position information set.
In the embodiment of the application, the static target is observed, the position of the static target is measured by the vehicle-mounted radar, namely, the first position information of the static target at each sampling moment in the preset time is measured to obtain the first position information, and the first position information is directly measured by the vehicle-mounted radar, so that the first position information has an installation azimuth error. As shown in fig. 2, the origin of the reference coordinate system is set as the center point of the rear axle of the vehicle, the driving direction of the vehicle is the x-axis, the x-axis is perpendicular to the 2-dimensional plane, and the left direction is the y-axis, so that the right-hand law is satisfied; in the running process of the bicycle, the speed direction is parallel to the x-axis direction; the counter-clockwise direction of the yaw angular velocity is a positive direction; all positional information referred to below is based on this reference coordinate systemAnd (4) determining. For example, the first position information of the stationary target measured by the vehicle-mounted radar at time t0 is (x)0,y0) The first set of position information measured at the preset time t 0-tN is { (x)0,y0)，(x1,y1)……(xN,yN)}。
S103: the first vehicle speed and the first yaw rate at each sampling time are acquired.
In the embodiment of the application, at each sampling moment when the vehicle-mounted radar measures the static target, a first vehicle speed corresponding to each sampling moment can be determined through a wheel speed sensor, and a corresponding first yaw rate is determined through a micro-inertia sensor; as shown in FIG. 2, for any time t from t0 to tN, the first vehicle speed calculated by the wheel speed sensor is
The micro inertial sensor measures a first yaw rate of
Since the first vehicle speed and the first yaw rate are measured by the sensors, the first vehicle speed has a vehicle speed error, the first yaw rate has a yaw rate error, and the following equations (1) and (2) exist:
wherein v ish(t) is the true vehicle speed; w is ah(t) is true yaw rate; k is a radical ofvIs a vehicle speed deviation coefficient;
is the yaw-rate offset error. Further, the error of the installation azimuth angle of the vehicle-mounted radar is set to phi, and k is thereby setv、
And phi is the vehicle radar error data described herein.
S105: and determining second position information of the static target at each sampling moment based on the first position information of the static target at the first sampling moment and the first vehicle speed and the first yaw rate at each sampling moment, so as to obtain a second position information set.
S107: and determining error data of the vehicle-mounted radar based on the first position information set and the second position information set, wherein the error data comprises a vehicle speed error, a yaw rate error and an installation azimuth angle error of the vehicle-mounted radar.
In the embodiment of the application, based on the initial position of the stationary target, that is, the first position information of the stationary target at the first sampling time, under the condition of given vehicle motion, the second position information of the stationary target based on the reference coordinate system at each sampling time is obtained through calculation, so as to obtain the second position information set, and then an equation is established with the first position information set of the stationary target directly output by the vehicle-mounted radar in step S101, so that a vehicle speed error, a yaw rate error and an installation azimuth angle error of the vehicle-mounted radar are solved.
In an optional implementation manner, step S105 may specifically include:
for one of the sampling instants: determining the longitudinal position variation of the static target at the current sampling moment based on the current sampling moment and the first vehicle speed of each sampling moment before the current sampling moment; specifically, the longitudinal position variation can be obtained by integrating the vehicle speed, and therefore the longitudinal position variation can be determined according to the formula (3):
wherein, Δ xh(tk) Representing the longitudinal position variation at the current sampling moment; k is equal to {1,2 … … N }, tkRepresenting the current sampling instant;
then, determining the transverse position variation of the static target at the current sampling moment based on the current sampling moment and the first vehicle speed and the first yaw rate at each sampling moment before the current sampling moment; specifically, the lateral acceleration can be obtained by multiplying the yaw rate by the vehicle speed, and the lateral position change amount can be obtained by quadratic integration, so that the lateral position change amount can be determined according to the formula (4):
wherein, Δ yh(tk) Representing the amount of change in the lateral position at the current sampling instant;
then, second position information of the static target at the current sampling time is determined based on the first position information, the longitudinal position variation and the transverse position variation at the first sampling time, namely the x-axis position of the first position information is added with the longitudinal position variation, and the y-axis position is added with the transverse position variation to obtain corresponding second position information.
Correspondingly, in an optional implementation manner, step S107 may specifically include:
s1071: establishing an observation equation at each sampling moment based on the first position information set and the second position information set to obtain an observation equation set;
specifically, the observation equation at each sampling time may include a first observation equation and a second observation equation, and the step S1071 may specifically include: for one of the sampling instants: performing coordinate conversion on first position information of the current sampling moment based on a first coordinate conversion matrix, and performing coordinate conversion on second position information of the current sampling moment based on a current second coordinate conversion matrix to obtain converted first position information and converted second position information; determining a first observation equation based on the converted longitudinal coordinate of the first position information and the converted longitudinal coordinate of the second position information, and determining a second observation equation based on the converted transverse coordinate of the first position information and the converted transverse coordinate of the second position information;
in addition, the step also comprises the step of obtaining the current second coordinate transformation matrix; acquiring a current second coordinate transformation matrix, including: determining the orientation angle variation of the static target at the current sampling moment based on the current sampling moment and the first yaw velocity of each sampling moment before the current sampling moment; specifically, the heading angle change amount of the host vehicle can be obtained by integrating the yaw rate once, and therefore the heading angle change amount can be determined according to equation (5):
wherein, Δ H (t)k) Representing the orientation angle variation at the current sampling moment;
then, determining a current second coordinate transformation matrix based on the orientation angle variation; specifically, the current second coordinate transformation matrix is determined according to formula (6):
assume that at time t, the target position of the radar output is
Then the following equation (7) holds:
wherein the content of the first and second substances,
converting a matrix into a first coordinate;
and T (delta H) transfers the second position information calculated based on the first sampling moment to the own vehicle coordinate system of the target sampling moment T, and T (phi) transfers the coordinate measured by the radar to the own vehicle coordinate system of the target sampling moment T.
Finally, the two observation equations at each sampling time can be obtained from equations (3) to (7) as follows:
then the stationary target at time t 0-tN may have the following set of observation equations:
and secondly, carrying out iterative solution on the observation multi-element nonlinear equation set (9) by using a nonlinear optimization method to obtain a vehicle speed error, a yaw angular velocity error and an installation azimuth angle error.
The following description is made by way of an example. Assuming that the self-vehicle linearly moves at a constant speed of 30km/h, the vehicle speed has 8% deviation, the error of the installation azimuth angle of the vehicle-mounted radar is 5 degrees, the yaw rate has an offset error of 0.2 degree/s, and the output frequency of a radar system is 20 HZ; considering the noise existing in the system measurement, the noise of the yaw angular velocity measurement is 0.01 degrees/s, and the noise of the vehicle speed is 0.1 m/s;
for a static target with real coordinates of (100,3), under the condition of unknown azimuth error of the vehicle-mounted radar, the initial coordinates of the static target are assumed to be (110,0), namely x0＝110，y0The initial value of each error is 0. By means of non-linear optimization methods, reference may be made in particular to the prior art, initial values
Assuming that the target is continuously observed for 5s, N ═ T/dt ═ 100 sampling moments, that is, the set of established observation equations (9) includes 200 observation equations; and (4) carrying out iterative solution on the 200 observation equations to complete the estimation of each error, wherein the errors gradually converge to a stable value along with the increase of the iteration times. As shown in fig. 3-5, fig. 3 is a schematic diagram of an iterative curve of the installation azimuth error of the vehicle-mounted radar provided by the embodiment of the present application, and the error can be completed about 5 times under a given conditionConvergence, convergence result 4.99 °; FIG. 4 is a schematic diagram of a convergence curve of a vehicle speed error provided in the present embodiment, where the error convergence can be completed in about 3 iterations, and the convergence result is 8.13%; fig. 5 is a schematic diagram of a convergence curve of the yaw rate error provided in the embodiment of the present application, where the error convergence is completed in about 4 iterations, and the convergence result is 0.21 °/s. According to the test result, the method for estimating the error data of the vehicle-mounted radar can simultaneously obtain the errors of the mounting azimuth angle, the vehicle speed and the yaw rate on line, and is high in accuracy.
An embodiment of the present application further provides an estimation apparatus for vehicle-mounted radar error data, and fig. 6 is a schematic structural diagram of the estimation apparatus for vehicle-mounted radar error data provided in the embodiment of the present application, and as shown in fig. 6, the apparatus includes:
the first determining module 601 is configured to determine first position information of a stationary target at each sampling time within a preset time based on a vehicle-mounted radar to obtain a first position information set;
an obtaining module 602, configured to obtain a first vehicle speed and a first yaw rate at each sampling time;
a second determining module 603, configured to determine second position information of the stationary target at each sampling time based on the first position information of the stationary target at the first sampling time and the first vehicle speed and the first yaw rate at each sampling time, so as to obtain a second position information set;
a third determining module 604, configured to determine error data of the vehicle-mounted radar based on the first set of location information and the second set of location information, where the error data includes a vehicle speed error, a yaw rate error, and an installation azimuth error of the vehicle-mounted radar.
In an optional embodiment, the second determining module 603 is further configured to, for one of the sampling time instants: determining the longitudinal position variation of the static target at the current sampling moment based on the current sampling moment and the first vehicle speed of each sampling moment before the current sampling moment; determining the transverse position variation of the static target at the current sampling moment based on the current sampling moment and the first vehicle speed and the first yaw rate at each sampling moment before the current sampling moment; and determining second position information of the static target at the current sampling moment based on the first position information at the first sampling moment, the longitudinal position variation and the transverse position variation.
In an optional implementation manner, the third determining module 604 is further configured to establish an observation equation at each sampling time based on the first set of location information and the second set of location information, so as to obtain an observation equation set;
and carrying out iterative solution on the observation equation set by using a nonlinear optimization method to obtain a vehicle speed error, a yaw angular velocity error and an installation azimuth angle error.
In an alternative embodiment, the observation equation for each sampling instant includes a first observation equation and a second observation equation; a third determining module 604, further configured to, for one of the sampling instants: performing coordinate conversion on first position information of the current sampling moment based on a first coordinate conversion matrix, and performing coordinate conversion on second position information of the current sampling moment based on a current second coordinate conversion matrix to obtain converted first position information and converted second position information; a first observation equation is determined based on the converted longitudinal coordinates of the first position information and the converted longitudinal coordinates of the second position information, and a second observation equation is determined based on the converted lateral coordinates of the first position information and the converted lateral coordinates of the second position information.
In an optional implementation manner, the third determining module 604 is further configured to obtain a current second coordinate transformation matrix; determining the orientation angle variation of the static target at the current sampling moment based on the current sampling moment and the first yaw velocity of each sampling moment before the current sampling moment; the current second coordinate conversion matrix is determined based on the orientation angle variation.
The device and method embodiments in the embodiments of the present application are based on the same application concept.
The method provided by the embodiment of the application can be executed in a computer terminal, a server or a similar operation device. Taking the operation on a server as an example, fig. 7 is a hardware structure block diagram of the server of the method for estimating vehicle-mounted radar error data according to the embodiment of the present application. As shown in fig. 7, the server 700 may have a relatively large difference due to different configurations or performances, and may include one or more Central Processing Units (CPUs) 710 (the processors 710 may include but are not limited to a Processing device such as a microprocessor NCU or a programmable logic device FPGA, etc.), a memory 730 for storing data, and one or more storage media 720 (e.g., one or more mass storage devices) for storing an application 723 or data 722. Memory 730 and storage medium 720 may be, among other things, transient storage or persistent storage. The program stored in the storage medium 720 may include one or more modules, each of which may include a series of instruction operations for the server. Still further, central processor 710 may be configured to communicate with storage medium 720 and execute a series of instruction operations in storage medium 720 on server 700. The server 700 may also include one or more power supplies 760, one or more wired or wireless network interfaces 750, one or more input-output interfaces 740, and/or one or more operating systems 721, such as Windows, Mac OS, Unix, Linux, FreeBSD, etc.
The input/output interface 740 may be used to receive or transmit data via a network. Specific examples of the network described above may include a wireless network provided by a communication provider of the server 700. In one example, the input/output Interface 740 includes a Network adapter (NIC) that can be connected to other Network devices through a base station to communicate with the internet. In one example, the input/output interface 740 may be a Radio Frequency (RF) module, which is used for communicating with the internet in a wireless manner.
It will be understood by those skilled in the art that the structure shown in fig. 7 is only an illustration and is not intended to limit the structure of the electronic device. For example, server 700 may also include more or fewer components than shown in FIG. 7, or have a different configuration than shown in FIG. 7.
Embodiments of the present application also provide a storage medium that may be disposed in a server to store at least one instruction, at least one program, a set of codes, or a set of instructions related to implementing an estimation method of vehicle-mounted radar error data in method embodiments, where the at least one instruction, the at least one program, the set of codes, or the set of instructions is loaded and executed by the processor to implement the estimation method of vehicle-mounted radar error data.
Alternatively, in this embodiment, the storage medium may be located in at least one network server of a plurality of network servers of a computer network. Optionally, in this embodiment, the storage medium may include, but is not limited to: a U-disk, a Read-Only Memory (ROM), a Random Access Memory (RAM), a removable hard disk, a magnetic or optical disk, and other various media capable of storing program codes.
As can be seen from the above embodiments of the method, the apparatus, the device or the storage medium for estimating error data of the vehicle-mounted radar, in the present application, the first position information of the stationary target at each sampling time within the preset time is determined based on the vehicle-mounted radar, so as to obtain a first position information set; acquiring a first vehicle speed and a first yaw rate at each sampling moment; determining second position information of the static target at each sampling moment based on first position information of the static target at the first sampling moment and the first vehicle speed and the first yaw rate at each sampling moment to obtain a second position information set; and determining error data of the vehicle-mounted radar based on the first position information set and the second position information set, wherein the error data comprises a vehicle speed error, a yaw rate error and an installation azimuth angle error of the vehicle-mounted radar. Therefore, the vehicle speed error, the yaw rate error and the installation azimuth angle error can be estimated on line at the same time to complete error correction, and no special requirement is required on the running condition of the vehicle.
It should be noted that: the sequence of the embodiments of the present application is only for description, and does not represent the advantages and disadvantages of the embodiments. And specific embodiments thereof have been described above. Other embodiments are within the scope of the following claims. In some cases, the actions or steps recited in the claims may be performed in a different order than in the embodiments and still achieve desirable results. In addition, the processes depicted in the accompanying figures do not necessarily require the particular order shown, or sequential order, to achieve desirable results. In some embodiments, multitasking and parallel processing may also be possible or may be advantageous.
The embodiments in the present specification are described in a progressive manner, and the same and similar parts among the embodiments are referred to each other, and each embodiment focuses on the differences from the other embodiments. In particular, for the apparatus embodiment, since it is substantially similar to the method embodiment, the description is relatively simple, and for the relevant points, reference may be made to the partial description of the method embodiment.
It will be understood by those skilled in the art that all or part of the steps for implementing the above embodiments may be implemented by hardware, or may be implemented by a program instructing relevant hardware, where the program may be stored in a computer-readable storage medium, and the above-mentioned storage medium may be a read-only memory, a magnetic disk or an optical disk, etc.
The above description is only exemplary of the present application and should not be taken as limiting the present application, as any modification, equivalent replacement, or improvement made within the spirit and principle of the present application should be included in the protection scope of the present application.
Claims (10)
1. A method of estimating vehicle-mounted radar error data, comprising:
determining first position information of a static target at each sampling moment in preset time based on a vehicle-mounted radar to obtain a first position information set;
acquiring a first vehicle speed and a first yaw rate at each sampling moment;
determining second position information of the static target at each sampling moment based on first position information of the static target at a first sampling moment and the first vehicle speed and the first yaw rate of each sampling moment, and obtaining a second position information set;
error data of the vehicle-mounted radar is determined based on the first set of position information and the second set of position information, wherein the error data comprises a vehicle speed error, a yaw rate error and an installation azimuth error of the vehicle-mounted radar.
2. The method of claim 1, wherein determining the second position information of the stationary target at each of the sampling instants based on the first position information of the stationary target at the first sampling instant and the first vehicle speed and the first yaw rate at each of the sampling instants comprises:
for one of the sampling instants: determining the longitudinal position variation of the static target at the current sampling moment based on the current sampling moment and the first vehicle speed of each sampling moment before the current sampling moment; determining the lateral position variation amount of the static target at the current sampling moment based on the current sampling moment and the first vehicle speed and the first yaw rate at each sampling moment before the current sampling moment; and determining second position information of the static target at the current sampling moment based on the first position information of the first sampling moment, the longitudinal position variation and the transverse position variation.
3. The method of claim 1, wherein determining error data for the on-board radar based on the first set of location information and the second set of location information comprises:
establishing an observation equation of each sampling moment based on the first position information set and the second position information set to obtain an observation equation set;
and carrying out iterative solution on the observation equation set by using a nonlinear optimization method to obtain the vehicle speed error, the yaw rate error and the installation azimuth angle error.
4. The method of claim 3, wherein the observation equations for each sampling instant comprise a first observation equation and a second observation equation;
the establishing the observation equation for each sampling instant based on the first set of location information and the second set of location information comprises:
for one of the sampling instants: performing coordinate conversion on first position information of the current sampling moment based on a first coordinate conversion matrix, and performing coordinate conversion on second position information of the current sampling moment based on a current second coordinate conversion matrix to obtain converted first position information and converted second position information; determining the first observation equation based on the converted longitudinal coordinate of the first position information and the converted longitudinal coordinate of the second position information, and determining the second observation equation based on the converted lateral coordinate of the first position information and the converted lateral coordinate of the second position information.
5. The method of claim 4, further comprising the step of obtaining the current second coordinate transformation matrix; the obtaining the current second coordinate transformation matrix includes:
determining an orientation angle change amount of the stationary target at the current sampling time based on the current sampling time and a first yaw rate of each sampling time before the current sampling time;
determining the current second coordinate conversion matrix based on the orientation angle variation.
6. An estimation device of vehicle-mounted radar error data, characterized by comprising:
the first determining module is used for determining first position information of the static target at each sampling moment in preset time based on the vehicle-mounted radar to obtain a first position information set;
the acquisition module is used for acquiring a first vehicle speed and a first yaw rate at each sampling moment;
the second determining module is used for determining second position information of the static target at each sampling moment based on first position information of the static target at a first sampling moment and the first vehicle speed and the first yaw rate at each sampling moment to obtain a second position information set;
and the third determination module is used for determining error data of the vehicle-mounted radar based on the first position information set and the second position information set, wherein the error data comprises a vehicle speed error, a yaw rate error and an installation azimuth angle error of the vehicle-mounted radar.
7. The apparatus of claim 6,
the second determining module is further configured to, for one of the sampling instants: determining the longitudinal position variation of the static target at the current sampling moment based on the current sampling moment and the first vehicle speed of each sampling moment before the current sampling moment; determining the lateral position variation amount of the static target at the current sampling moment based on the current sampling moment and the first vehicle speed and the first yaw rate at each sampling moment before the current sampling moment; and determining second position information of the static target at the current sampling moment based on the first position information of the first sampling moment, the longitudinal position variation and the transverse position variation.
8. The apparatus of claim 6,
the third determining module is further configured to establish an observation equation at each sampling time based on the first position information set and the second position information set to obtain an observation equation set;
and carrying out iterative solution on the observation equation set by using a nonlinear optimization method to obtain the vehicle speed error, the yaw rate error and the installation azimuth angle error.
9. An apparatus, characterized in that the apparatus comprises a processor and a memory, in which at least one instruction or at least one program is stored, which is loaded by the processor and which performs the method of estimating vehicle radar error data according to any one of claims 1-5.
10. A computer storage medium, characterized in that at least one instruction or at least one program is stored in the storage medium, which is loaded and executed by a processor to implement the method for estimating vehicle-mounted radar error data according to any one of claims 1 to 5.
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