CN112710315A - Vehicle positioning method and device based on intelligent vehicle - Google Patents
Vehicle positioning method and device based on intelligent vehicle Download PDFInfo
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- CN112710315A CN112710315A CN202011493144.7A CN202011493144A CN112710315A CN 112710315 A CN112710315 A CN 112710315A CN 202011493144 A CN202011493144 A CN 202011493144A CN 112710315 A CN112710315 A CN 112710315A
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01C—MEASURING DISTANCES, LEVELS OR BEARINGS; SURVEYING; NAVIGATION; GYROSCOPIC INSTRUMENTS; PHOTOGRAMMETRY OR VIDEOGRAMMETRY
- G01C21/00—Navigation; Navigational instruments not provided for in groups G01C1/00 - G01C19/00
- G01C21/26—Navigation; Navigational instruments not provided for in groups G01C1/00 - G01C19/00 specially adapted for navigation in a road network
- G01C21/28—Navigation; Navigational instruments not provided for in groups G01C1/00 - G01C19/00 specially adapted for navigation in a road network with correlation of data from several navigational instruments
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01S—RADIO DIRECTION-FINDING; RADIO NAVIGATION; DETERMINING DISTANCE OR VELOCITY BY USE OF RADIO WAVES; LOCATING OR PRESENCE-DETECTING BY USE OF THE REFLECTION OR RERADIATION OF RADIO WAVES; ANALOGOUS ARRANGEMENTS USING OTHER WAVES
- G01S19/00—Satellite radio beacon positioning systems; Determining position, velocity or attitude using signals transmitted by such systems
- G01S19/38—Determining a navigation solution using signals transmitted by a satellite radio beacon positioning system
- G01S19/39—Determining a navigation solution using signals transmitted by a satellite radio beacon positioning system the satellite radio beacon positioning system transmitting time-stamped messages, e.g. GPS [Global Positioning System], GLONASS [Global Orbiting Navigation Satellite System] or GALILEO
- G01S19/42—Determining position
- G01S19/45—Determining position by combining measurements of signals from the satellite radio beacon positioning system with a supplementary measurement
- G01S19/47—Determining position by combining measurements of signals from the satellite radio beacon positioning system with a supplementary measurement the supplementary measurement being an inertial measurement, e.g. tightly coupled inertial
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Abstract
The embodiment of the application provides a vehicle positioning method and device based on an intelligent vehicle, and the method comprises the following steps: acquiring initial positioning information and current compensation positioning information of the intelligent vehicle; acquiring three-axis angular velocity information and three-axis acceleration information of the intelligent vehicle; calculating according to the initial positioning information, the compensation positioning information, the three-axis angular velocity information and the three-axis acceleration information to obtain estimated positioning information; and performing Kalman filtering on the estimated positioning information to obtain vehicle positioning information. Thus, the implementation of the embodiment can improve the positioning precision of the intelligent vehicle or the automatic driving vehicle.
Description
Technical Field
The application relates to the field of intelligent driving, in particular to a vehicle positioning method and device based on an intelligent vehicle.
Background
At present, automatic driving has been gradually applied to vehicles, and it is expected to bring greater convenience to human beings. However, there are many difficulties in the current automatic driving technology, one of which is the problem of vehicle positioning accuracy. In practice, it is found that a currently commonly used vehicle positioning mode is an IMU attitude positioning mode, and although the method can acquire a real-time driving state of a vehicle, certain errors are inevitable when the method is used for a long time, so that the positioning accuracy of the vehicle deviates, and the positioning of an automatic driving vehicle is influenced.
Disclosure of Invention
The embodiment of the application aims to provide a vehicle positioning method and device based on an intelligent vehicle, which can improve the positioning accuracy of the intelligent vehicle or an automatic driving vehicle.
The embodiment of the application provides a vehicle positioning method based on an intelligent vehicle in a first aspect, and the method comprises the following steps:
acquiring initial positioning information and current compensation positioning information of the intelligent vehicle;
acquiring three-axis angular velocity information and three-axis acceleration information of the intelligent vehicle;
calculating according to the initial positioning information, the compensation positioning information, the three-axis angular velocity information and the three-axis acceleration information to obtain estimated positioning information;
and performing Kalman filtering on the estimated positioning information to obtain vehicle positioning information.
In the implementation process, the vehicle positioning method based on the intelligent vehicle can preferentially acquire the initial positioning information and the current compensation positioning information of the intelligent vehicle; then acquiring three-axis angular velocity information and three-axis acceleration information of the intelligent vehicle; calculating according to the initial positioning information, the compensation positioning information, the three-axis angular velocity information and the three-axis acceleration information to obtain estimated positioning information; and finally, performing Kalman filtering on the estimated positioning information to obtain vehicle positioning information. Therefore, the implementation mode can acquire the satellite positioning information and the inertial differential positioning information and process the two positioning information in real time according to the Kalman filtering to obtain accurate vehicle positioning information, so that the positioning precision of the intelligent vehicle or the automatic driving vehicle can be improved.
Further, the step of obtaining the initial positioning information and the current compensated positioning information of the intelligent vehicle comprises:
acquiring initial positioning information and current differential positioning information of the intelligent vehicle;
acquiring an outfield calibration parameter of the intelligent vehicle;
and performing compensation correction on the differential positioning information according to the external field calibration parameters to obtain compensation positioning information.
In the implementation process, in the step of acquiring the initial positioning information and the current compensation positioning information of the intelligent vehicle, the method can preferentially acquire the initial positioning information and the current differential positioning information of the intelligent vehicle; then acquiring an outfield calibration parameter of the intelligent vehicle; and finally, performing compensation correction on the differential positioning information according to the external field calibration parameters to obtain compensation positioning information. Therefore, by implementing the embodiment, the parameter correction can be carried out on the position deviation between the antenna setting position and the position of the vehicle body, so that the satellite positioning precision is higher, and the positioning precision of the intelligent vehicle or the automatic driving vehicle is improved.
Further, the step of acquiring the three-axis angular velocity information and the three-axis acceleration information of the intelligent vehicle includes:
acquiring an internal field calibration parameter, measurement angular velocity information and measurement acceleration information of the intelligent vehicle;
and performing compensation correction on the measured angular velocity information and the measured acceleration information according to the internal field calibration parameters to obtain triaxial angular velocity information and triaxial acceleration information.
In the implementation process, in the step of acquiring the three-axis angular velocity information and the three-axis acceleration information of the intelligent vehicle, the method can preferentially acquire the infield calibration parameter, the measurement angular velocity information and the measurement acceleration information of the intelligent vehicle; and then acquiring and compensating the measured angular velocity information and the measured acceleration information according to the internal field calibration parameters to obtain triaxial angular velocity information and triaxial acceleration information. Therefore, the implementation of the embodiment can realize the internal reference correction of the inertial measurement unit, so that various data acquired by the inertial measurement unit have higher accuracy, and the positioning precision of the intelligent vehicle or the automatic driving vehicle can be improved.
Further, the step of calculating according to the initial positioning information, the compensation positioning information, the three-axis angular velocity information, and the three-axis acceleration information to obtain the estimated positioning information includes:
acquiring motion constraint parameters and odometer information;
and calculating according to the motion constraint parameters, the odometer information, the initial positioning information, the compensation positioning information, the three-axis angular velocity information and the three-axis acceleration information to obtain estimated positioning information.
In the implementation process, the method can preferentially acquire motion constraint parameters and odometer information in the process of obtaining estimated positioning information by calculating according to initial positioning information, compensation positioning information, three-axis angular velocity information and three-axis acceleration information; and calculating according to the motion constraint parameters, the odometer information, the initial positioning information, the compensation positioning information, the three-axis angular velocity information and the three-axis acceleration information to obtain estimated positioning information. Therefore, by implementing the implementation mode, various positioning data and motion information can be uniformly constrained according to the three-dimensional coordinate system formed by the motion direction of the actual vehicle and the plane where the actual vehicle is located, so that the data and the information correspond to the intelligent vehicle (or the automatic driving vehicle), and the positioning precision of the intelligent vehicle or the automatic driving vehicle is further improved; meanwhile, the current position of the intelligent vehicle (or the automatic driving vehicle) can be further determined by introducing the odometer information according to the odometer data conversion, so that the positioning precision of the intelligent vehicle or the automatic driving vehicle can be improved.
Further, the method further comprises:
and determining the vehicle positioning information as the initial positioning information, and triggering and executing the step of acquiring the initial positioning information and the current compensation positioning information of the intelligent vehicle.
In the implementation process, after the vehicle positioning information is obtained, the method determines the vehicle positioning information as initial positioning information, and re-executes the steps of obtaining the initial positioning information and the current compensation positioning information of the intelligent vehicle. Therefore, by implementing the implementation mode, repeated positioning of the intelligent vehicle (or the automatic driving vehicle) can be realized, so that full-range navigation of the intelligent vehicle (or the automatic driving vehicle) is realized, and the positioning precision of the intelligent vehicle or the automatic driving vehicle is improved.
The second aspect of the embodiments of the present application provides a vehicle positioning device based on a smart vehicle, which includes:
the first acquisition unit is used for acquiring initial positioning information and current compensation positioning information of the intelligent vehicle;
the second acquisition unit is used for acquiring the three-axis angular velocity information and the three-axis acceleration information of the intelligent vehicle;
the calculation unit is used for calculating according to the initial positioning information, the compensation positioning information, the three-axis angular velocity information and the three-axis acceleration information to obtain estimated positioning information;
and the filtering unit is used for carrying out Kalman filtering on the estimated positioning information to obtain fused positioning information.
In the implementation process, the vehicle positioning device based on the intelligent vehicle can acquire the initial positioning information and the current compensation positioning information of the intelligent vehicle through the first acquisition unit; acquiring triaxial angular velocity information and triaxial acceleration information of the intelligent vehicle through a second acquisition unit; calculating according to the initial positioning information, the compensation positioning information, the three-axis angular velocity information and the three-axis acceleration information by a calculating unit to obtain estimated positioning information; and finally, performing Kalman filtering on the estimated positioning information through a filtering unit to obtain vehicle positioning information. Therefore, by implementing the implementation mode, the satellite positioning information and the inertial differential positioning information can be obtained, and the two types of positioning information are processed in real time according to Kalman filtering to obtain accurate vehicle positioning information, so that the positioning precision of an intelligent vehicle or an automatic driving vehicle can be improved.
Further, the first acquisition unit includes:
the first acquisition subunit is used for acquiring initial positioning information and current differential positioning information of the intelligent vehicle;
the first obtaining subunit is further configured to obtain outfield calibration parameters of the intelligent vehicle;
and the first compensation subunit is used for performing compensation correction on the differential positioning information according to the external field calibration parameter to obtain compensation positioning information.
In the implementation process, the first obtaining unit may obtain initial positioning information and current differential positioning information of the intelligent vehicle through the first obtaining subunit; acquiring an external field calibration parameter of the intelligent vehicle through a first acquiring subunit; and then the first compensation subunit performs compensation correction on the differential positioning information according to the external field calibration parameters to obtain compensation positioning information. Therefore, by implementing the embodiment, the parameter correction can be carried out on the position deviation between the antenna setting position and the position of the vehicle body, so that the satellite positioning precision is higher, and the positioning precision of the intelligent vehicle or the automatic driving vehicle is improved.
Further, the second acquisition unit includes:
the second acquisition subunit is used for acquiring an internal field calibration parameter, measurement angular velocity information and measurement acceleration information of the intelligent vehicle;
and the second compensation subunit is used for performing compensation correction on the measured angular velocity information and the measured acceleration information according to the internal field calibration parameters to obtain triaxial angular velocity information and triaxial acceleration information.
In the implementation process, the second obtaining unit can obtain the infield calibration parameter, the measured angular velocity information and the measured acceleration information of the intelligent vehicle through the second obtaining subunit; and then the second compensation subunit performs compensation correction on the measured angular velocity information and the measured acceleration information according to the internal field calibration parameters to obtain triaxial angular velocity information and triaxial acceleration information. Therefore, by implementing the embodiment, the internal reference correction of the inertial measurement unit can be realized, so that various data acquired by the inertial measurement unit have higher accuracy, and the positioning precision of the intelligent vehicle or the automatic driving vehicle can be improved.
A third aspect of the embodiments of the present application provides an electronic device, including a memory and a processor, where the memory is used for storing a computer program, and the processor runs the computer program to make the electronic device execute the method for positioning a vehicle based on a smart vehicle according to any one of the first aspect of the embodiments of the present application.
A fourth aspect of the embodiments of the present application provides a computer-readable storage medium, which stores computer program instructions, and when the computer program instructions are read and executed by a processor, the computer program instructions perform a method for positioning a vehicle based on an intelligent vehicle according to any one of the first aspect of the embodiments of the present application.
Drawings
In order to more clearly illustrate the technical solutions of the embodiments of the present application, the drawings that are required to be used in the embodiments of the present application will be briefly described below, it should be understood that the following drawings only illustrate some embodiments of the present application and therefore should not be considered as limiting the scope, and that those skilled in the art can also obtain other related drawings based on the drawings without inventive efforts.
Fig. 1 is a schematic flowchart of a vehicle positioning method based on an intelligent vehicle according to an embodiment of the present disclosure;
FIG. 2 is a schematic flow chart diagram illustrating another method for locating a vehicle based on an intelligent vehicle according to an embodiment of the present application;
fig. 3 is a schematic structural diagram of a vehicle positioning device based on an intelligent vehicle according to an embodiment of the present application;
FIG. 4 is a schematic structural diagram of another intelligent vehicle-based vehicle positioning device provided in the embodiments of the present application;
FIG. 5 is a schematic structural diagram of another intelligent vehicle-based vehicle positioning device provided in the embodiments of the present application;
fig. 6 is a schematic flowchart illustrating an example of a vehicle positioning method based on an intelligent vehicle according to an embodiment of the present application.
Detailed Description
The technical solutions in the embodiments of the present application will be described below with reference to the drawings in the embodiments of the present application.
It should be noted that: like reference numbers and letters refer to like items in the following figures, and thus, once an item is defined in one figure, it need not be further defined and explained in subsequent figures. Meanwhile, in the description of the present application, the terms "first", "second", and the like are used only for distinguishing the description, and are not to be construed as indicating or implying relative importance.
Example 1
Referring to fig. 1, fig. 1 is a schematic flow chart of a vehicle positioning method based on an intelligent vehicle according to an embodiment of the present application. The method is applied to the intelligent vehicle, and particularly applied to a scene for positioning the intelligent vehicle or navigating the intelligent vehicle. The vehicle positioning method based on the intelligent vehicle comprises the following steps:
s101, acquiring initial positioning information and current compensation positioning information of the intelligent vehicle.
In this embodiment, the compensated positioning information is positioning information obtained after calibration based on GNSS data (i.e., positioning data of a global navigation satellite system), RTK data (carrier phase difference fraction data), and an external field calibration parameter (installation deviation data).
In this embodiment, the compensated positioning information is used to represent positioning information obtained after calibration is performed according to the differential positioning information and the external field calibration parameters.
In this embodiment, the outfield calibration parameter is used to indicate the boom arm position and the position of the mounting error compensation.
In this embodiment, the differential positioning information is used to refer to a positioning result of the access after-searching differential.
In this embodiment, the differential positioning information is subjected to the external reference correction to obtain the compensated positioning information.
In this embodiment, the method may perform an initialization alignment on the integrated navigation device by using the high-precision GNSS position, velocity, and dual-antenna heading information in advance.
S102, obtaining three-axis angular velocity information and three-axis acceleration information of the intelligent vehicle.
In this embodiment, the method may read the three-axis angular velocity information and the three-axis acceleration information through a preset interface. In this embodiment, different interface types are defined.
S103, calculating according to the initial positioning information, the compensation positioning information, the three-axis angular velocity information and the three-axis acceleration information to obtain estimated positioning information.
In this embodiment, the method performs strapdown calculation using an accelerometer and a three-axis gyro of an IMU (inertial measurement unit), and calculates position, velocity, and attitude information of the inertial measurement unit by using integration.
In this embodiment, after the position, speed, and attitude information of the mobile terminal itself is calculated, the distance and speed of movement are determined by combining the difference between the initial positioning information and the compensated positioning information, so as to further determine more accurate estimated positioning information.
And S104, performing Kalman filtering on the estimated positioning information to obtain vehicle positioning information.
In the embodiment, the method uses multi-sensor fusion resolving, estimates Kalman filtering parameters (including a state transition matrix, a system noise matrix, a measurement noise matrix and the like) in real time according to IMU, GNSS and odometer information, and performs Kalman filtering calculation in real time.
In this embodiment, the KALMAN filtering dimension of the present invention is 30 dimensions, which is specifically as follows:
error state vector of order 30: position, velocity, attitude, accelerometer zero-bias, gyroscope zero-bias, GNSS antenna lever arm, mounting error angle of T and B coordinate systems, rear wheel center lever arm, drive wheel speed, and the like.
As an optional implementation, the method further comprises:
and outputting the vehicle positioning information.
By implementing the implementation mode, the navigation result of the intelligent vehicle can be output, including the position, the speed, the course and the IMU information of the intelligent vehicle, so that the data can be known and acquired, and the prompt of a user and the continuous navigation of the intelligent vehicle are facilitated.
In this embodiment, the compensated positioning information used in the method is GNSS information, and GNSS refers to a global navigation satellite system, and is a satellite system that performs positioning and navigation by using observations such as pseudo-ranges, ephemeris, and satellite transmission time of a set of satellites.
In this embodiment, the device for obtaining the compensation positioning information is a GNSS board card, and the GNSS board card includes a GNSS receiver having a carrier phase differential function (also called carrier phase differential technology, RTK for short), so that the GNSS board card can be compatible with a location service for searching for thousands of locations.
In this embodiment, a location service cloud platform is constructed based on cloud computing and data technology by integrating and constructing one Beidou foundation network based on the concept of 'Internet + location (Beidou)' so as to meet the requirements of the national, industrial and mass markets for accurate location service.
In the embodiment, the method simultaneously receives the positioning signal from the satellite and the positioning information of the ground base station (or the thousand-search position service), and the position of the method is calculated, and the long-term accuracy of the method can reach about 2 cm.
In this embodiment, the execution subject of the method may be a computing device such as a computer and a server, and is not limited in this embodiment.
In this embodiment, an execution subject of the method may also be a smart device such as a smart phone and a tablet, which is not limited in this embodiment.
In this embodiment, the executing body of the method may be called a navigation computer, and is an intelligent navigation device disposed in an intelligent vehicle.
It can be seen that, by implementing the vehicle positioning method based on the intelligent vehicle described in fig. 1, the initial positioning information and the current compensation positioning information of the intelligent vehicle can be preferentially obtained; then acquiring three-axis angular velocity information and three-axis acceleration information of the intelligent vehicle; calculating according to the initial positioning information, the compensation positioning information, the three-axis angular velocity information and the three-axis acceleration information to obtain estimated positioning information; and finally, performing Kalman filtering on the estimated positioning information to obtain vehicle positioning information. Therefore, by implementing the implementation mode, the satellite positioning information and the inertial differential positioning information can be obtained, and the two types of positioning information are processed in real time according to Kalman filtering to obtain accurate vehicle positioning information, so that the positioning precision of an intelligent vehicle or an automatic driving vehicle can be improved.
Example 2
Referring to fig. 2, fig. 2 is a schematic flowchart of another intelligent vehicle-based vehicle positioning method according to an embodiment of the present application. The flowchart of the intelligent vehicle-based vehicle positioning method depicted in fig. 2 is improved from the flowchart of the intelligent vehicle-based vehicle positioning method depicted in fig. 1. The vehicle positioning method based on the intelligent vehicle comprises the following steps:
s201, acquiring initial positioning information and current differential positioning information of the intelligent vehicle.
In this embodiment, the differential positioning information is used to indicate positioning result information obtained by performing high-precision positioning on the GNSS board card using the kilogramme service.
In the present embodiment, the differential positioning information is positioning data determined based on GNSS data (i.e., positioning data of a global navigation satellite system) and RTK data (carrier phase differential data).
In this embodiment, the differential positioning information is used to refer to a positioning result of accessing the post-hit differential.
In this embodiment, the differential positioning information may include a GNSS antenna position, a GNSS antenna speed, a GNSS heading, and a GNSS pitch.
S202, obtaining external field calibration parameters of the intelligent vehicle.
In this embodiment, an antenna or other device for acquiring current differential positioning information is generally disposed above the vehicle body. Therefore, there is a setup offset between the IMU (inertial measurement unit) and the antenna, which then requires external field calibration parameters for calibration.
In the present embodiment, the antenna, the IMU, and other devices are installed at various positions of the vehicle and are rigidly connected to the vehicle body.
In this embodiment, the execution main body of the method may access vehicle information through an OBD port (a K-Line communication method based on an ISO protocol), and configure lever arm information and installation errors through a serial port to perform external field calibration, thereby obtaining the external field calibration parameters.
And S203, compensating and correcting the differential positioning information according to the external field calibration parameters to obtain the compensated positioning information.
In this embodiment, the outfield calibration parameter may compensate and correct the differential positioning information, so that the vehicle position corresponding to the compensation positioning information is more accurate.
In this embodiment, the outfield calibration parameter is used to indicate the boom arm position and the position of the mounting error compensation.
In this embodiment, by the compensation correction described above, the mounting error can be compensated, and the position velocity at the GNSS antenna can be converted to the IMU by the lever arm compensation.
In this embodiment, the compensated positioning information may be a combination of differential positioning information and external field calibration parameters.
And S204, obtaining an internal field calibration parameter, measurement angular velocity information and measurement acceleration information of the intelligent vehicle.
In this embodiment, the internal field calibration parameters may include cross-coupled arrays, zero offset, scale error, and the like.
In the embodiment, the method can also acquire the temperature data of the intelligent vehicle in real time through the temperature sensor, so that the method can perform temperature difference compensation in real time according to the internal field calibration parameters, and the data measurement accuracy is improved.
S205, compensating and correcting the measured angular velocity information and the measured acceleration information according to the internal field calibration parameters to obtain triaxial angular velocity information and triaxial acceleration information.
In this embodiment, the method may compensate an IMU (inertial measurement unit) by using the internal field calibration parameter, improve data accuracy of the measured angular velocity information and the measured acceleration information, and obtain the three-axis angular velocity information and the three-axis acceleration information.
And S206, acquiring motion constraint parameters and odometer information.
In this embodiment, the measurement matrix used by the kalman filter may be obtained by performing motion constraint on GNSS observation data, and specifically includes:
when the intelligent vehicle is static, the constraint speed is equal to zero, the angular speed is equal to zero, and the acceleration is equal to a preset value;
when the intelligent vehicle moves, the speed value of the rotating shaft direction of the constraint wheel is the vehicle speed, and the speed of the vertical direction of the constraint road surface or the track surface is equal to zero.
In this embodiment, the data can be further refined, thereby improving the accuracy of obtaining the vehicle positioning information.
And S207, calculating according to the motion constraint parameters, the odometer information, the initial positioning information, the compensation positioning information, the three-axis angular velocity information and the three-axis acceleration information to obtain estimated positioning information.
In this embodiment, the motion constraint parameters are used to constrain the directions and values of all data in the whole data.
For example, the motion constraint parameters may be used to perform driving direction constraint on the three-axis acceleration information, so that the three-axis acceleration information is unified with the motion direction of the intelligent vehicle.
And S208, performing Kalman filtering on the estimated positioning information to obtain vehicle positioning information.
In this embodiment, the method may obtain the measurement equation by using the GNSS information and the motion constraint, and then directly estimate the state quantity in real time by using the kalman filtering method to obtain the vehicle positioning information.
In the embodiment, the state quantity can be predicted and updated in real time by using a Kalman filtering method, and the position, the speed and the attitude error of the system can be calibrated in real time by fusing multi-sensor information.
S209, determining the vehicle positioning information as initial positioning information, and triggering the step S201.
In this embodiment, the method is applied using four coordinate systems, which are as follows:
the T coordinate system, i.e. the coordinate system of the IMU, is usually located inside the vehicle body; wherein, the T coordinate system is a coordinate system which is generally in a fixed direction and is parallel to the horizontal plane;
a coordinate system B, namely a motion coordinate system of the intelligent vehicle, wherein the position origin of the coordinate system is superposed with the origin of the IMU coordinate system; the B coordinate system is a coordinate system which is generally along the motion direction of the intelligent vehicle and is parallel to the vehicle plane;
a C coordinate system, namely a coordinate system constructed by the center of a rear wheel shaft of the intelligent vehicle, wherein the center positions of the left rear wheel and the right rear wheel are symmetrical with each other by taking the origin of the C coordinate system as the center;
a G coordinate system, that is, a coordinate system using the GNSS positioning antenna as an origin; typically, the antenna is disposed above the smart vehicle.
Referring to fig. 6, fig. 6 is a schematic flowchart illustrating an example of a vehicle positioning method based on an intelligent vehicle according to the present embodiment. The IMU is an inertia measurement unit and is used for acquiring three-axis angular velocity information and three-axis acceleration information; the GNSS board card is used to obtain initial positioning information and current compensation positioning information of the intelligent vehicle, and other contents can be known from this embodiment, which is not described in detail again in this embodiment.
Therefore, by implementing the vehicle positioning method based on the intelligent vehicle described in fig. 2, the satellite positioning information and the inertial differential positioning information can be obtained, and the two types of positioning information can be processed in real time according to the kalman filter, so that the accurate vehicle positioning information can be obtained, and the positioning accuracy of the intelligent vehicle or the automatic driving vehicle can be improved.
Example 3
Referring to fig. 3, fig. 3 is a schematic structural diagram of a vehicle positioning device based on an intelligent vehicle according to an embodiment of the present application. Wherein, this vehicle positioner based on intelligent vehicle includes:
a first obtaining unit 310, configured to obtain initial positioning information and current compensation positioning information of the smart vehicle;
the second obtaining unit 320 is configured to obtain three-axis angular velocity information and three-axis acceleration information of the smart vehicle;
the calculating unit 330 is configured to calculate according to the initial positioning information, the compensation positioning information, the three-axis angular velocity information, and the three-axis acceleration information to obtain estimated positioning information;
and the filtering unit 340 is configured to perform kalman filtering on the estimated positioning information to obtain vehicle positioning information.
In this embodiment, for the explanation of the vehicle positioning device based on the intelligent vehicle, reference may be made to the description in embodiment 1 or embodiment 2, and details are not repeated in this embodiment.
Therefore, by implementing the vehicle positioning device based on the intelligent vehicle described in fig. 3, the satellite positioning information and the inertial differential positioning information can be acquired, and the two types of positioning information can be processed in real time according to the kalman filter, so that the accurate vehicle positioning information can be obtained, and the positioning accuracy of the intelligent vehicle or the automatic driving vehicle can be improved.
Example 4
Referring to fig. 4, fig. 4 is a schematic structural diagram of another vehicle positioning device based on an intelligent vehicle according to an embodiment of the present application. The schematic structure of the vehicle positioning device based on the intelligent vehicle depicted in fig. 4 is improved according to the schematic structure of the vehicle positioning device based on the intelligent vehicle depicted in fig. 3. Wherein, the first obtaining unit 310 includes:
a first obtaining subunit 311, configured to obtain initial positioning information and current differential positioning information of the smart vehicle;
the first obtaining subunit 311 is further configured to obtain an external field calibration parameter of the intelligent vehicle;
the first compensation subunit 312 is configured to perform compensation and correction on the differential positioning information according to the external field calibration parameter, so as to obtain compensated positioning information.
As an optional implementation, the second obtaining unit 320 includes:
a second obtaining subunit 321, configured to obtain an internal field calibration parameter, measured angular velocity information, and measured acceleration information of the smart vehicle;
and the second compensation subunit 322 is configured to perform compensation correction on the measured angular velocity information and the measured acceleration information according to the infield calibration parameter, so as to obtain triaxial angular velocity information and triaxial acceleration information.
As an alternative embodiment, the calculation unit 330 includes:
a third obtaining subunit 331, configured to obtain the motion constraint parameter and the odometer information;
and the calculating subunit 332 is configured to calculate according to the motion constraint parameter, the odometer information, the initial positioning information, the compensation positioning information, the three-axis angular velocity information, and the three-axis acceleration information, so as to obtain estimated positioning information.
As an alternative embodiment, the vehicle positioning device further comprises:
a determining unit 350, configured to determine the vehicle positioning information as initial positioning information, and trigger the first obtaining unit 310 to perform an operation of obtaining the initial positioning information and current compensated positioning information of the smart vehicle.
In this embodiment, for the explanation of the vehicle positioning device based on the intelligent vehicle, reference may be made to the description in embodiment 1 or embodiment 2, and details are not repeated in this embodiment.
Therefore, by implementing the vehicle positioning device based on the intelligent vehicle described in fig. 4, the satellite positioning information and the inertial differential positioning information can be acquired, and the two types of positioning information can be processed in real time according to the kalman filter, so that the accurate vehicle positioning information can be obtained, and the positioning accuracy of the intelligent vehicle or the automatic driving vehicle can be improved.
Referring to fig. 5, fig. 5 is a schematic structural diagram of another vehicle positioning device based on an intelligent vehicle according to the present embodiment. The first acquiring subunit 311 may include an NGSS board, the second acquiring subunit 321 may include a three-axis gyroscope and a three-axis accelerometer, the third acquiring subunit 331 may include an odometer, and the calculating subunit 332 may include a navigation computer, where the navigation computer may output vehicle positioning information including a direction, a speed, and an attitude.
The embodiment of the present application provides an electronic device, which includes a memory and a processor, where the memory is used to store a computer program, and the processor runs the computer program to make the electronic device execute the method for locating a vehicle based on an intelligent vehicle in any one of embodiment 1 or embodiment 2 of the present application.
The embodiment of the present application provides a computer-readable storage medium, which stores computer program instructions, and when the computer program instructions are read and executed by a processor, the method for positioning a vehicle based on an intelligent vehicle according to any one of embodiment 1 or embodiment 2 of the present application is executed.
In the embodiments provided in the present application, it should be understood that the disclosed apparatus and method can be implemented in other ways. The apparatus embodiments described above are merely illustrative, and for example, the flowchart and block diagrams in the figures illustrate the architecture, functionality, and operation of possible implementations of apparatus, methods and computer program products according to various embodiments of the present application. In this regard, each block in the flowchart or block diagrams may represent a module, segment, or portion of code, which comprises one or more executable instructions for implementing the specified logical function(s). It should also be noted that, in some alternative implementations, the functions noted in the block may occur out of the order noted in the figures. For example, two blocks shown in succession may, in fact, be executed substantially concurrently, or the blocks may sometimes be executed in the reverse order, depending upon the functionality involved. It will also be noted that each block of the block diagrams and/or flowchart illustration, and combinations of blocks in the block diagrams and/or flowchart illustration, can be implemented by special purpose hardware-based systems which perform the specified functions or acts, or combinations of special purpose hardware and computer instructions.
In addition, functional modules in the embodiments of the present application may be integrated together to form an independent part, or each module may exist separately, or two or more modules may be integrated to form an independent part.
The functions, if implemented in the form of software functional modules and sold or used as a stand-alone product, may be stored in a computer readable storage medium. Based on such understanding, the technical solution of the present application or portions thereof that substantially contribute to the prior art may be embodied in the form of a software product stored in a storage medium and including instructions for causing a computer device (which may be a personal computer, a server, or a network device) to execute all or part of the steps of the method according to the embodiments of the present application. And the aforementioned storage medium includes: a U-disk, a removable hard disk, a Read-Only Memory (ROM), a Random Access Memory (RAM), a magnetic disk or an optical disk, and other various media capable of storing program codes.
The above description is only an example of the present application and is not intended to limit the scope of the present application, and various modifications and changes may be made by those skilled in the art. Any modification, equivalent replacement, improvement and the like made within the spirit and principle of the present application shall be included in the protection scope of the present application. It should be noted that: like reference numbers and letters refer to like items in the following figures, and thus, once an item is defined in one figure, it need not be further defined and explained in subsequent figures.
The above description is only for the specific embodiments of the present application, but the scope of the present application is not limited thereto, and any person skilled in the art can easily conceive of the changes or substitutions within the technical scope of the present application, and shall be covered by the scope of the present application. Therefore, the protection scope of the present application shall be subject to the protection scope of the claims.
It is noted that, herein, relational terms such as first and second, and the like may be used solely to distinguish one entity or action from another entity or action without necessarily requiring or implying any actual such relationship or order between such entities or actions. Also, the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, article, or apparatus. Without further limitation, an element defined by the phrase "comprising an … …" does not exclude the presence of other identical elements in a process, method, article, or apparatus that comprises the element.
Claims (10)
1. A method for intelligent vehicle-based vehicle positioning, the method comprising:
acquiring initial positioning information and current compensation positioning information of the intelligent vehicle;
acquiring three-axis angular velocity information and three-axis acceleration information of the intelligent vehicle;
calculating according to the initial positioning information, the compensation positioning information, the three-axis angular velocity information and the three-axis acceleration information to obtain estimated positioning information;
and performing Kalman filtering on the estimated positioning information to obtain vehicle positioning information.
2. The smart vehicle-based vehicle locating method of claim 1, wherein the step of obtaining initial location information and current compensated location information of the smart vehicle comprises:
acquiring initial positioning information and current differential positioning information of the intelligent vehicle;
acquiring an outfield calibration parameter of the intelligent vehicle;
and performing compensation correction on the differential positioning information according to the external field calibration parameters to obtain compensation positioning information.
3. The smart vehicle-based vehicle positioning method of claim 1, wherein the step of obtaining three-axis angular velocity information and three-axis acceleration information of the smart vehicle comprises:
acquiring an internal field calibration parameter, measurement angular velocity information and measurement acceleration information of the intelligent vehicle;
and performing compensation correction on the measured angular velocity information and the measured acceleration information according to the internal field calibration parameters to obtain triaxial angular velocity information and triaxial acceleration information.
4. The intelligent vehicle-based vehicle locating method of claim 1, wherein the step of calculating from the initial locating information, the compensated locating information, the three-axis angular velocity information, and the three-axis acceleration information to obtain estimated locating information comprises:
acquiring motion constraint parameters and odometer information;
and calculating according to the motion constraint parameters, the odometer information, the initial positioning information, the compensation positioning information, the three-axis angular velocity information and the three-axis acceleration information to obtain estimated positioning information.
5. The smart vehicle-based vehicle positioning method of claim 1, further comprising:
and determining the vehicle positioning information as the initial positioning information, and triggering and executing the step of acquiring the initial positioning information and the current compensation positioning information of the intelligent vehicle.
6. A vehicle locating device based on an intelligent vehicle, the vehicle locating device comprising:
the first acquisition unit is used for acquiring initial positioning information and current compensation positioning information of the intelligent vehicle;
the second acquisition unit is used for acquiring the three-axis angular velocity information and the three-axis acceleration information of the intelligent vehicle;
the calculation unit is used for calculating according to the initial positioning information, the compensation positioning information, the three-axis angular velocity information and the three-axis acceleration information to obtain estimated positioning information;
and the filtering unit is used for carrying out Kalman filtering on the estimated positioning information to obtain vehicle positioning information.
7. The smart vehicle-based vehicle locating apparatus of claim 6, wherein the first obtaining unit comprises:
the first acquisition subunit is used for acquiring initial positioning information and current differential positioning information of the intelligent vehicle;
the first obtaining subunit is further configured to obtain outfield calibration parameters of the intelligent vehicle;
and the first compensation subunit is used for performing compensation correction on the differential positioning information according to the external field calibration parameter to obtain compensation positioning information.
8. The smart vehicle-based vehicle locating apparatus of claim 6, wherein the second obtaining unit comprises:
the second acquisition subunit is used for acquiring an internal field calibration parameter, measurement angular velocity information and measurement acceleration information of the intelligent vehicle;
and the second compensation subunit is used for performing compensation correction on the measured angular velocity information and the measured acceleration information according to the internal field calibration parameters to obtain triaxial angular velocity information and triaxial acceleration information.
9. An electronic device, characterized in that the electronic device comprises a memory for storing a computer program and a processor for executing the computer program to cause the electronic device to perform the intelligent vehicle based vehicle positioning method of any of claims 1-5.
10. A readable storage medium having stored thereon computer program instructions which, when read and executed by a processor, perform the intelligent vehicle-based vehicle localization method of any one of claims 1 to 5.
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