CN112731320B - Estimation method, device, equipment and storage medium of vehicle-mounted radar error data - Google Patents
Estimation method, device, equipment and storage medium of vehicle-mounted radar error data Download PDFInfo
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Abstract
The application relates to a vehicle-mounted radar error data estimation method, a device, equipment and a storage medium, wherein the method comprises the following steps: determining first position information of each sampling moment of a static target 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 the first position information of the static target at the first sampling moment, the first vehicle speed and the first yaw rate at each sampling moment, and obtaining 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 finish error correction, and no special requirement is required for the running condition of the vehicle.
Description
Technical Field
The present application relates to the field of radar technologies, and in particular, to a method, an apparatus, a device, and a storage medium for estimating vehicle radar error data.
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, ranging accuracy and the like. The vehicle-mounted radar system can measure the position, angle, doppler speed and other information of the target objects around the vehicle body in real time, and track the target objects by combining the motion information of the vehicle, so as to obtain the distance and speed of the target objects under the vehicle coordinate system.
Factors affecting the tracking performance of the vehicle radar system on the target object include some external factors besides the measurement accuracy of the sensor, and mainly include an installation azimuth angle error, a vehicle speed deviation and a yaw rate error of the radar system.
Although the installation azimuth angle error is calibrated on line, as the service time of the vehicle is prolonged, factors such as looseness and aging of mechanical parts inevitably cause certain error of the installation azimuth angle of the radar system, and the system accuracy is directly reduced due to the small-angle error; the vehicle speed and the yaw rate are important input signals of a radar system, and in general, the vehicle speed information is comprehensively calculated by measuring the wheel speed by a wheel speed sensor, wherein the tire pressure, the load and the abrasion all influence the measurement accuracy of the wheel speed sensor, so that the vehicle speed information has a certain deviation from the actual vehicle speed; the yaw rate is generally obtained by measuring a micro inertial sensor, and the micro inertial sensor can have certain offset error or zero offset during measurement due to the influences of service time, ambient temperature, vibration and the like.
It can be seen that although the radar system is subjected to strict correction at the time of shipment, with the running use of the vehicle, there is inevitably some offset due to the loss influence of vibration, collision or other mechanical structures, thereby reducing the accuracy of the radar system, and thus, it is highly necessary to estimate and complete on-line correction of the vehicle speed error, yaw rate error and installation azimuth angle error based on the radar system, so as to reduce the influence thereof.
Disclosure of Invention
The embodiment of the application provides a vehicle-mounted radar error data estimation method, device, equipment and storage medium, which can estimate a vehicle speed error, a yaw rate error and an installation azimuth angle error of a vehicle-mounted radar on line at the same time on the premise of not increasing additional equipment and cost so as to correct the vehicle speed error, the yaw rate error and the installation azimuth angle error of the vehicle-mounted radar, thereby reducing the influence of the error on radar application.
In one aspect, an embodiment of the present application provides a method for estimating vehicle radar error data, including:
determining first position information of each sampling moment of a static target 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 the first position information of the static target at the first sampling moment, the first vehicle speed and the first yaw rate at each sampling moment, and obtaining 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 the second position information of the stationary object at each sampling time based on the first position information of the stationary object at the first sampling time and the first vehicle speed and the first yaw rate at each sampling time includes:
for one of the sampling instants: determining the longitudinal position change quantity 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 change quantity 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 of 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 change amount and the transverse position change amount.
Optionally, determining error data of the vehicle 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 rate error and an installation azimuth angle error.
Optionally, the observation equation of 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 the first position information at the current sampling moment based on the first coordinate conversion matrix, and performing coordinate conversion on the second position information at the current sampling moment based on the current second coordinate conversion matrix to obtain converted first position information and second position information; a first observation equation is determined based on the longitudinal coordinates of the converted first position information and the longitudinal coordinates of the converted second position information, and a second observation equation is determined based on the lateral coordinates of the converted first position information and the lateral coordinates of the converted second position information.
Optionally, the method further comprises the step of acquiring a current second coordinate transformation matrix; obtaining a current second coordinate transformation matrix, including:
determining the change amount of the orientation angle of the static target at the current sampling time based on the current sampling time and the first yaw rate of each sampling time before the current sampling time;
the current second coordinate transformation matrix is determined based on the change in orientation angle.
On the other hand, the embodiment of the application provides an estimation device of vehicle-mounted radar error data, which comprises the following steps:
The first determining module is used for determining first position information of each sampling moment of the stationary target 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 the first position information of the static target at the first sampling moment, the first vehicle speed and the first yaw rate at each sampling moment and obtaining 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 instants: determining the longitudinal position change quantity 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 change quantity 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 of 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 change amount and the transverse position change amount.
Optionally, the third determining module is further configured to establish an observation equation set at each sampling time based on the first location information set and the second location information set, 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 rate error and an installation azimuth angle error.
On the other hand, the embodiment of the application provides equipment, which comprises a processor and a memory, wherein at least one instruction or at least one section of program is stored in the memory, and the processor loads and executes the estimation method of the 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, where 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 radar error data.
The method, the device, the equipment and the storage medium for estimating the vehicle-mounted radar error data provided by the embodiment of the application have the following beneficial effects:
Determining first position information of each sampling moment of a static target 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 the first position information of the static target at the first sampling moment, the first vehicle speed and the first yaw rate at each sampling moment, and obtaining 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 finish error correction, and no special requirement is required for the running condition of the vehicle.
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In order to more clearly illustrate the technical solutions of the embodiments of the present application, the drawings required for the description of the embodiments will be briefly described below, and it is apparent that the drawings in the following description are only some embodiments of the present application, and other drawings may be obtained according to these drawings without inventive effort for a person skilled in the art.
Fig. 1 is a schematic flow chart of a method for estimating vehicle-mounted radar error data according to an embodiment of the present application;
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 iteration curve of an on-board radar installation azimuth error provided by an embodiment of the present application;
FIG. 4 is a schematic diagram of a convergence curve of a vehicle speed error according to an embodiment of the present application;
FIG. 5 is a schematic view of a convergence curve of yaw-rate error provided by an embodiment of the present application;
fig. 6 is a schematic structural diagram of an estimation device for vehicle-mounted radar error data according to an embodiment of the present application;
Fig. 7 is a hardware block diagram of a server of a method for estimating vehicle-mounted radar error data according to an embodiment of the present application.
Detailed Description
The following description of the embodiments of the present application will be made clearly and completely with reference to the accompanying drawings, in which it is apparent that the embodiments described are only some embodiments of the present application, but not all embodiments. All other embodiments, which can be made by those skilled in the art based on the embodiments of the application without making any inventive effort, are intended to be within the scope of the application.
It should be noted that the terms "first," "second," and the like in the description and the claims of the present application and the above figures are used for distinguishing between similar objects and not necessarily for describing a particular sequential or chronological order. It is to be understood that the data so used may be interchanged where appropriate such that the embodiments of the application described herein may be implemented in sequences other than those illustrated or otherwise 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 or inherent to such process, method, article, or apparatus, 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 the vehicle-mounted radar on a target object, the influence of various errors such as a vehicle speed error, a yaw rate error, a radar installation azimuth angle error and the like is reduced, and the embodiment of the application provides an estimation method of vehicle-mounted radar error data.
In the following, a specific embodiment of a method for estimating vehicle radar error data according to the present application is described, and fig. 1 is a schematic flow chart of a method for estimating vehicle radar error data according to an embodiment of the present application, and the present specification provides method operation steps as an example or a flowchart, but may include more or fewer operation steps based on conventional or non-inventive labor. The order of steps recited in the embodiments is merely one way of performing the order of steps and does not represent a unique order of execution. When implemented in a real system or server product, the methods illustrated in the embodiments or figures may be performed sequentially or in parallel (e.g., in a parallel processor or multithreaded environment). As shown in fig. 1, the method may include:
S101: and determining first position information of each sampling moment of the stationary target in preset time based on the vehicle-mounted radar to obtain a first position information set.
In the embodiment of the application, the stationary target is observed, the position of the stationary target is measured by adopting the vehicle-mounted radar, namely, the first position information of each sampling moment of the stationary target 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 angle 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 running direction of the vehicle is the x-axis, the 2-dimensional plane is perpendicular to the x-axis, 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 of the bicycle is parallel to the x-axis direction; the yaw rate is counterclockwise in the positive direction; all positional information referred to below is determined based on the reference coordinate system. For example, the first position information of the stationary target measured by the vehicle-mounted radar at time t0 is (x 0,y0), and the first set of position information measured at the preset times t0 to 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 of a stationary target measured by a vehicle-mounted radar, 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 inertial sensor; as shown in FIG. 2, for any time t out of t0 to tN, the first vehicle speed calculated by the wheel speed sensor isThe first yaw rate measured by the micro inertial sensor is/>Since the first vehicle speed and the first yaw rate are measured by the sensor, there is a vehicle speed error, and the first yaw rate has a yaw rate error, and the following formulas (1) and (2) exist:
Wherein v h (t) is the true vehicle speed; w h (t) is true yaw rate; k v is a vehicle speed deviation coefficient; The error is biased for yaw rate. In addition, the installation azimuth angle error of the vehicle radar is set to be phi, so that k v and/or > And phi is the radar error data of the vehicle according to the application.
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, the first vehicle speed and the first yaw rate at each sampling moment, and obtaining 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, namely, the first position information of the stationary target at the first sampling moment, under the given self-vehicle movement condition, calculating the second position information of the stationary target based on the reference coordinate system at each sampling moment to obtain a second position information set, and establishing an equation with the first position information set of the stationary target directly output by the vehicle-mounted radar in the step S101, thereby solving the vehicle speed error, the yaw rate error and the installation azimuth angle error of the vehicle-mounted radar.
In an alternative embodiment, step S105 may specifically include:
For one of the sampling instants: determining the longitudinal position change quantity 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 change amount can be obtained for the vehicle speed integration, and thus the longitudinal position change amount can be determined according to the formula (3):
Wherein Δx h(tk) represents the longitudinal position change amount at the current sampling time; k epsilon {1,2 … … N }, t k represents the current sampling time;
Then, determining the transverse position change quantity of the stationary target at the current sampling moment based on the current sampling moment and the first vehicle speed and the first yaw rate of each sampling moment before the current sampling moment; specifically, the lateral acceleration can be obtained from the product of the yaw rate and the vehicle speed, and the lateral position change amount can be obtained by twice integration, so that the lateral position change amount can be determined according to the formula (4):
wherein Δy h(tk) represents the lateral position change amount at the current sampling time;
Then, second position information of the stationary object at the current sampling time is determined based on the first position information, the longitudinal position change amount and the transverse position change amount of the first sampling time, namely, the x-axis position and the longitudinal position change amount of the first position information are added, and the y-axis position and the transverse position change amount are added to obtain corresponding second position information.
Correspondingly, in an alternative embodiment, 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 the first position information at the current sampling moment based on the first coordinate conversion matrix, and performing coordinate conversion on the second position information at the current sampling moment based on the current second coordinate conversion matrix to obtain converted first position information and second position information; determining a first observation equation based on the longitudinal coordinates of the converted first position information and the longitudinal coordinates of the converted second position information, and determining a second observation equation based on the lateral coordinates of the converted first position information and the lateral coordinates of the converted second position information;
in addition, the step also comprises the step of acquiring a current second coordinate transformation matrix; obtaining a current second coordinate transformation matrix, including: determining the change amount of the orientation angle of the static target at the current sampling time based on the current sampling time and the first yaw rate of each sampling time before the current sampling time; specifically, the change amount of the heading angle of the own vehicle can be obtained by once integrating the yaw rate, and therefore the change amount of the heading angle can be determined according to the formula (5):
Wherein Δh (t k) represents the change amount of the orientation angle at the current sampling time;
Then, determining a current second coordinate transformation matrix based on the change amount of the orientation angle; specifically, the current second coordinate transformation matrix is determined according to formula (6):
Assuming time t, the target position of the radar output is Then the following equation (7) holds:
Wherein, A first coordinate transformation matrix;
T (delta H) transfers the second position information calculated based on the first sampling instant to the own vehicle coordinate system of the target sampling instant T, and T (phi) transfers the coordinate of radar measurement to the own vehicle coordinate system of the target sampling instant T.
Finally, two observation equations for each sampling instant can be obtained from equations (3) - (7) as:
The stationary object can get the following observation equation set at time t 0-tN:
And secondly, carrying out iterative solution on the observed multi-element nonlinear equation set (9) by using a nonlinear optimization method to obtain a vehicle speed error, a yaw rate error and an installation azimuth angle error.
The following is an example. Assuming that the vehicle moves linearly at a constant speed of 30km/h, the vehicle speed has 8% deviation, the installation azimuth angle error of the vehicle-mounted radar is 5 degrees, the yaw angle speed has an offset error of 0.2 degrees/s, and the output frequency of the radar system is 20HZ; considering that noise exists in system measurement, the yaw rate measurement noise is 0.01 degree/s, and the vehicle speed noise is 0.1m/s;
For a stationary target with true coordinates (100, 3), in the case of unknown vehicle radar azimuth errors, it is assumed that the initial coordinates of the stationary target are (110,0), i.e., x 0＝110,y0 =0, and the initial values of the other errors are 0. The nonlinear optimization method can be specifically referred to the prior art and the initial value Assuming that the target is observed continuously for 5s, n=t/dt=100 sampling instants, i.e. the set of established observation equations (9) contains 200 observation equations; and (3) carrying out iterative solution on the 200 observation equations to finish estimation of each error, wherein the error gradually converges to a stable value along with the increase of iteration times. As shown in fig. 3-5, fig. 3 is a schematic diagram of an iteration curve of an installation azimuth error of a vehicle-mounted radar according to an embodiment of the present application, under a given condition, error convergence can be completed about 5 times, and a convergence result is 4.99 °; FIG. 4 is a schematic diagram of a convergence curve of a vehicle speed error according to an embodiment of the present application, wherein the error can be converged after about 3 iterations, and the convergence result is 8.13%; FIG. 5 is a graph showing a convergence curve of a yaw-rate error according to an embodiment of the present application, wherein the error convergence is completed in about 4 iterations, and the convergence result is 0.21/s. As can be seen from the test results, the estimation method of the vehicle-mounted radar error data provided by the embodiment of the application can simultaneously obtain the installation azimuth angle error, the vehicle speed error and the yaw rate error on line, and has high accuracy.
The embodiment of the application also provides a device for estimating vehicle-mounted radar error data, and fig. 6 is a schematic structural diagram of the device for estimating vehicle-mounted radar error data, as shown in fig. 6, where the device includes:
A first determining module 601, configured to determine first location information of each sampling time of a stationary target in a preset time based on an on-vehicle radar, to obtain a first location information set;
An acquisition module 602, configured to acquire 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, to obtain a second position information set;
A third determining module 604, configured to determine error data of the vehicle radar based on the first set of position information and the second set of position information, where the error data includes a vehicle speed error, a yaw rate error, and an installation azimuth error of the vehicle radar.
In an alternative embodiment, the second determining module 603 is further configured to, for one of the sampling instants: determining the longitudinal position change quantity 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 change quantity 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 of 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 change amount and the transverse position change amount.
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 location information set and the second location information set, 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 rate 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; the third determining module 604 is further configured to, for one of the sampling instants: performing coordinate conversion on the first position information at the current sampling moment based on the first coordinate conversion matrix, and performing coordinate conversion on the second position information at the current sampling moment based on the current second coordinate conversion matrix to obtain converted first position information and second position information; a first observation equation is determined based on the longitudinal coordinates of the converted first position information and the longitudinal coordinates of the converted second position information, and a second observation equation is determined based on the lateral coordinates of the converted first position information and the lateral coordinates of the converted second position information.
In an alternative embodiment, the third determining module 604 is further configured to obtain the current second coordinate transformation matrix; determining the change amount of the orientation angle of the static target at the current sampling time based on the current sampling time and the first yaw rate of each sampling time before the current sampling time; the current second coordinate transformation matrix is determined based on the change in orientation angle.
The device and method embodiments in the embodiments of the present application are based on the same application concept.
The method embodiments provided by the embodiments of the present application may be executed in a computer terminal, a server, or similar computing device. Taking the operation on the server as an example, fig. 7 is a hardware structure block diagram of the server of a method for estimating vehicle-mounted radar error data according to an embodiment of the present application. As shown in fig. 7, the server 700 may vary considerably in configuration or performance and may include one or more central processing units (Central Processing Units, CPU) 710 (the processor 710 may include, but is not limited to, a microprocessor NCU, or a processing device such as a programmable logic device FPGA), memory 730 for storing data, one or more storage mediums 720 (e.g., one or more mass storage devices) for storing applications 723 or data 722. Wherein memory 730 and storage medium 720 may be transitory or persistent. The program stored in the storage medium 720 may include one or more modules, each of which may include a series of instruction operations on the server. Still further, the central processor 710 may be configured to communicate with the storage medium 720 and execute a series of instruction operations in the storage medium 720 on the 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.
Input-output interface 740 may be used to receive or transmit data via a network. The specific example 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 (Network Interface Controller, NIC) that can connect 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 for communicating with the internet wirelessly.
It will be appreciated by those of ordinary skill in the art that the configuration shown in fig. 7 is merely illustrative and is not intended to limit the configuration of the electronic device described above. 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 code set, or an instruction set related to a method for implementing the method for estimating vehicle radar error data in the method embodiment, where the at least one instruction, the at least one program, the code set, or the instruction set is loaded and executed by the processor to implement the method for estimating vehicle radar error data described above.
Alternatively, in this embodiment, the storage medium may be located in at least one network server among a plurality of network servers of the computer network. Alternatively, in the present embodiment, the storage medium may include, but is not limited to: a usb disk, a Read-Only Memory (ROM), a random access Memory (RAM, random Access Memory), a removable hard disk, a magnetic disk, or an optical disk, or other various media capable of storing program codes.
The embodiments of the method, the device, the equipment or the storage medium for estimating the vehicle-mounted radar error data provided by the application can be seen that the first position information of each sampling moment of the stationary target in the preset time is determined based on the 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 the first position information of the static target at the first sampling moment, the first vehicle speed and the first yaw rate at each sampling moment, and obtaining 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 finish error correction, and no special requirement is required for 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 the foregoing description has been directed to specific embodiments of this specification. Other embodiments are within the scope of the following claims. In some cases, the actions or steps recited in the claims can 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 are also possible or may be advantageous.
In this specification, each embodiment is described in a progressive manner, and identical and similar parts of each embodiment are all referred to each other, and each embodiment mainly describes differences from other embodiments. In particular, for the apparatus embodiments, since they are substantially similar to the method embodiments, the description is relatively simple, and reference is made to the description of the method embodiments in part.
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 for instructing relevant hardware, where the program may be stored in a computer readable storage medium, and the storage medium may be a read-only memory, a magnetic disk or an optical disk, etc.
The foregoing description of the preferred embodiments of the application is not intended to limit the application to the precise form disclosed, and any such modifications, equivalents, and alternatives falling within the spirit and scope of the application are intended to be included within the scope of the application.
Claims (8)
1. The estimation method of the vehicle-mounted radar error data is characterized by comprising the following steps of:
determining first position information of each sampling moment of a static target 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 at each sampling moment to obtain a second position information set;
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;
the determining the second position information of the stationary object at each sampling time based on the first position information of the stationary object at the first sampling time and the first vehicle speed and the first yaw rate at each sampling time includes:
For one of the sampling instants: determining the longitudinal position variation of the stationary target at the current sampling time based on the current sampling time and a first vehicle speed of each sampling time before the current sampling time; determining a lateral position change amount of the stationary target at the current sampling time based on the current sampling time and a first vehicle speed and a first yaw rate at each sampling time before the current sampling time; 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 change amount and the transverse position change amount.
2. The method of claim 1, wherein the determining error data for the vehicle radar based on the first set of location information and the second set of location information comprises:
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 the vehicle speed error, the yaw rate error and the installation azimuth angle error.
3. The method of claim 2, wherein the observation equation for each sampling instant comprises a first observation equation and a second observation equation;
The establishing an observation equation for each sampling time based on the first position information set and the second position information set includes:
for one of the sampling instants: performing coordinate conversion on first position information at the current sampling moment based on a first coordinate conversion matrix, and performing coordinate conversion on second position information at the current sampling moment based on a current second coordinate conversion matrix to obtain converted first position information and second position information; the first observation equation is determined based on the longitudinal coordinates of the converted first position information and the longitudinal coordinates of the converted second position information, and the second observation equation is determined based on the lateral coordinates of the converted first position information and the lateral coordinates of the converted second position information.
4. A method according to claim 3, further comprising the step of obtaining the current second coordinate transformation matrix; the obtaining the current second coordinate transformation matrix includes:
Determining the change amount of the orientation angle of the static target at the current sampling moment based on the current sampling moment and the first yaw rate of each sampling moment before the current sampling moment;
And determining the current second coordinate transformation matrix based on the direction angle variation.
5. An estimation device for vehicle-mounted radar error data, comprising:
The first determining module is used for determining first position information of each sampling moment of the stationary target in preset time based on the vehicle-mounted radar to obtain a first position information set;
the acquisition module is used for acquiring the first vehicle speed and the 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 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 to obtain a second position information set;
A third determining module, configured to determine error data of the vehicle-mounted radar based on the first location information set and the second location information set, where the error data includes a vehicle speed error, a yaw rate error, and an installation azimuth angle error of the vehicle-mounted radar;
The second determining module is further configured to, for one of the sampling instants: determining the longitudinal position variation of the stationary target at the current sampling time based on the current sampling time and a first vehicle speed of each sampling time before the current sampling time; determining a lateral position change amount of the stationary target at the current sampling time based on the current sampling time and a first vehicle speed and a first yaw rate at each sampling time before the current sampling time; 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 change amount and the transverse position change amount.
6. The apparatus of claim 5, wherein the device comprises a plurality of sensors,
The third determining module is further configured to establish an observation equation set at each sampling time based on the first location information set and the second location information set, 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 the vehicle speed error, the yaw rate error and the installation azimuth angle error.
7. An electronic device comprising a processor and a memory, wherein the memory has stored therein at least one instruction or at least one program, the at least one instruction or the at least one program being loaded by the processor and performing the method of estimating vehicle radar error data according to any of claims 1-4.
8. A computer storage medium having stored therein at least one instruction or at least one program loaded and executed by a processor to implement the method of estimating vehicle radar error data according to any of claims 1 to 4.
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| CN113702929B (en) * | 2021-08-16 | 2024-07-05 | 中汽创智科技有限公司 | Method, device, equipment and storage medium for calibrating installation angle of vehicle-mounted radar |
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