WO2022206519A1 - Procédé et appareil d'étalonnage de paramètre externe pour radar monté sur véhicule - Google Patents

Procédé et appareil d'étalonnage de paramètre externe pour radar monté sur véhicule Download PDF

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Publication number
WO2022206519A1
WO2022206519A1 PCT/CN2022/082560 CN2022082560W WO2022206519A1 WO 2022206519 A1 WO2022206519 A1 WO 2022206519A1 CN 2022082560 W CN2022082560 W CN 2022082560W WO 2022206519 A1 WO2022206519 A1 WO 2022206519A1
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WIPO (PCT)
Prior art keywords
vehicle
radar
road
point cloud
cloud data
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PCT/CN2022/082560
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English (en)
Chinese (zh)
Inventor
尹晓萌
王建国
陈默
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华为技术有限公司
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Publication of WO2022206519A1 publication Critical patent/WO2022206519A1/fr

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    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01S—RADIO DIRECTION-FINDING; RADIO NAVIGATION; DETERMINING DISTANCE OR VELOCITY BY USE OF RADIO WAVES; LOCATING OR PRESENCE-DETECTING BY USE OF THE REFLECTION OR RERADIATION OF RADIO WAVES; ANALOGOUS ARRANGEMENTS USING OTHER WAVES
    • G01S7/00—Details of systems according to groups G01S13/00, G01S15/00, G01S17/00
    • G01S7/02—Details of systems according to groups G01S13/00, G01S15/00, G01S17/00 of systems according to group G01S13/00
    • G01S7/40—Means for monitoring or calibrating
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01S—RADIO DIRECTION-FINDING; RADIO NAVIGATION; DETERMINING DISTANCE OR VELOCITY BY USE OF RADIO WAVES; LOCATING OR PRESENCE-DETECTING BY USE OF THE REFLECTION OR RERADIATION OF RADIO WAVES; ANALOGOUS ARRANGEMENTS USING OTHER WAVES
    • G01S13/00—Systems using the reflection or reradiation of radio waves, e.g. radar systems; Analogous systems using reflection or reradiation of waves whose nature or wavelength is irrelevant or unspecified
    • G01S13/02—Systems using reflection of radio waves, e.g. primary radar systems; Analogous systems
    • G01S13/06—Systems determining position data of a target
    • G01S13/42—Simultaneous measurement of distance and other co-ordinates
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01S—RADIO DIRECTION-FINDING; RADIO NAVIGATION; DETERMINING DISTANCE OR VELOCITY BY USE OF RADIO WAVES; LOCATING OR PRESENCE-DETECTING BY USE OF THE REFLECTION OR RERADIATION OF RADIO WAVES; ANALOGOUS ARRANGEMENTS USING OTHER WAVES
    • G01S13/00—Systems using the reflection or reradiation of radio waves, e.g. radar systems; Analogous systems using reflection or reradiation of waves whose nature or wavelength is irrelevant or unspecified
    • G01S13/88—Radar or analogous systems specially adapted for specific applications
    • G01S13/93—Radar or analogous systems specially adapted for specific applications for anti-collision purposes
    • G01S13/931—Radar or analogous systems specially adapted for specific applications for anti-collision purposes of land vehicles
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01S—RADIO DIRECTION-FINDING; RADIO NAVIGATION; DETERMINING DISTANCE OR VELOCITY BY USE OF RADIO WAVES; LOCATING OR PRESENCE-DETECTING BY USE OF THE REFLECTION OR RERADIATION OF RADIO WAVES; ANALOGOUS ARRANGEMENTS USING OTHER WAVES
    • G01S7/00—Details of systems according to groups G01S13/00, G01S15/00, G01S17/00
    • G01S7/02—Details of systems according to groups G01S13/00, G01S15/00, G01S17/00 of systems according to group G01S13/00
    • G01S7/40—Means for monitoring or calibrating
    • G01S7/4004—Means for monitoring or calibrating of parts of a radar system
    • G01S7/4026—Antenna boresight

Definitions

  • the present application relates to the field of connected vehicles, and in particular, to a method and device for calibrating external parameters of a vehicle-mounted radar.
  • Vehicle-mounted radar can realize functions such as obstacle measurement, collision prediction, adaptive cruise control, etc., which can effectively reduce the difficulty of driving, reduce the burden on drivers and reduce the incidence of accidents, so it has been widely used in the automotive field.
  • a vehicle-mounted radar eg, the radar on vehicle A in FIG. 1
  • vehicle-mounted radar can perceive the coordinates of surrounding objects (eg, vehicle B on the road in FIG. 1 ) in the vehicle-mounted radar coordinate system.
  • the conversion from the vehicle radar coordinate system to the vehicle coordinate system requires the use of an important parameter, that is, the external parameters of the vehicle radar.
  • the external parameters of the vehicle radar Once the external parameters of the vehicle radar are inaccurate, it will affect the determination of the object's position in the real environment and cannot guarantee driving safety.
  • the process of determining the external parameters of the vehicle radar is called the external parameter calibration process of the vehicle radar.
  • the purpose of the present application is to provide a method and device for calibrating external parameters of a vehicle-mounted radar, which are used to realize the online calibration of the vehicle-mounted radar and improve the calibration efficiency.
  • a method for calibrating external parameters of a vehicle-mounted radar which is applied to a vehicle, and the vehicle includes a radar.
  • the method includes: acquiring driving information of the vehicle, where the driving information includes at least one of driving state information or driving road condition information; wherein the driving state information includes speed, acceleration, yaw angle, or yaw angle speed.
  • the driving road condition information includes at least one of the driving road of the vehicle or the objects around the driving road; according to the driving information, the vehicle radar is calibrated with external parameters.
  • the vehicle can complete the external parameter calibration of the on-board radar during the driving process, without returning to the factory for calibration, the efficiency is high, the normal use of the on-board radar is not affected, and the user experience is high.
  • the performing external parameter calibration on the vehicle radar according to the driving information includes: according to the driving state information, when it is determined that at least one of the following conditions is satisfied, performing external parameter calibration on the vehicle radar Calibration, wherein the conditions include: the vehicle is traveling at an average speed, the speed is less than a first threshold, the vehicle is traveling at an average speed, the acceleration is less than a second threshold, the yaw angle is within a preset range, Or the yaw angular velocity is less than the third threshold.
  • the vehicle when the vehicle is driving, it is determined that the current state is suitable for online calibration according to parameters such as speed, acceleration, yaw angle, and yaw angular velocity, and the external parameters of the vehicle radar are calibrated.
  • parameters such as speed, acceleration, yaw angle, and yaw angular velocity
  • the external parameters of the vehicle radar are calibrated.
  • the vehicle when the vehicle is driving at a constant speed, it is considered that the vehicle is relatively stable, and it can be calibrated online if it meets the calibration conditions.
  • the performing external parameter calibration on the vehicle radar according to the driving information includes: determining, according to the driving road condition information, that the driving road is a straight road and/or that there are targets around the driving road When a reference object is used, external parameter calibration is performed on the vehicle-mounted radar.
  • the external parameters of the vehicle-mounted radar are calibrated to realize the online calibration of the vehicle-mounted radar, and the efficiency is high.
  • the vehicle is calibrated using the target reference around the driving road, and the calibrated external parameters are more suitable for the real situation and have higher accuracy.
  • the external parameter includes at least one of a rotation angle or a translation distance of the vehicle-mounted radar; the method further includes: determining the vehicle-mounted radar according to a target reference around the driving road At least one of the rotation angle or the translation distance of the radar.
  • the vehicle is calibrated using the target reference objects around the driving road during the driving process.
  • the calibrated external parameters are more suitable for the real situation and have higher accuracy.
  • the determining the rotation angle of the vehicle-mounted radar according to the target reference around the driving road includes: determining the vehicle-mounted radar according to the ground of the driving road or a plane object parallel to the ground The pitch angle and roll angle of the vehicle are determined; the yaw angle of the vehicle-mounted radar is determined according to the objects arranged along the driving road.
  • the pitch angle, roll angle and yaw angle can be calibrated using different target reference objects with high accuracy.
  • the objects disposed along the travel road include: first type objects disposed along the travel road and parallel to the ground of the travel road, and/or along the travel road and the second type of objects arranged perpendicular to the ground of the driving road;
  • the first type of objects includes: at least one of a road edge, a guardrail, a green belt or a lane line;
  • the second type of objects includes: trees, At least one of a sign or street light.
  • the yaw angle determined in this way is more accurate. Because a calibration scheme is to determine the rotation matrix R of the radar coordinate system relative to the vehicle coordinate system according to the deviation between the first normal vector of the point cloud data of the ground in the radar coordinate system and the standard normal vector of the ground, and then, according to The rotation matrix R can get the yaw angle. However, since the change of the yaw angle has no effect on the deviation between the first normal vector and the standard normal vector of the ground, in other words, the change of the yaw angle will not cause the change of the rotation matrix R. Therefore, pushing back the yaw angle by R is not accurate. However, in the embodiment of the present application, the yaw angle is determined by the objects arranged along the driving road, and the calibration accuracy of the yaw angle is improved.
  • the method further includes: acquiring external parameters of the vehicle-mounted radar; determining a target plane object around the driving road; using the external parameters to place the target plane object in the vehicle-mounted radar coordinate system Convert the corresponding first point cloud data in the inertial coordinate system to the second point cloud data in the inertial coordinate system; if the flatness of the second point cloud data does not meet the first condition, adjust the external parameter.
  • the vehicle can verify whether the external parameters of the vehicle-mounted radar are accurate. After the second point cloud data, the flatness of the second point cloud data does not meet the first condition, indicating that the external parameters are not accurate, then adjust the external parameters. This method can verify whether the external parameters are accurate and improve the accuracy of external parameter calibration.
  • the flatness of the second point cloud data does not satisfy the first condition, including: any two reflection points of different transmit beams in the second point cloud data on the target plane object
  • the first vector between is not perpendicular to the normal vector of the point cloud data corresponding to any one or more transmit beams in the second point cloud data; or, any two different transmit beams in the second point cloud data are in the
  • the included angle between the first vector between the reflection points on the target plane object and the normal vector of the point cloud data corresponding to any one or more transmit beams in the second point cloud data is not within a preset range.
  • the second point cloud data is the coordinates of the target plane object in the inertial coordinate system. If the flatness of the second point cloud data is good, it means that the second point cloud data obtained by using the current external parameters of the vehicle radar through a series of coordinate transformations is flat, which is more in line with the real situation, indicating that the current external parameters are relatively accurate of. If the flatness of the second point cloud data is poor, it means that the second point cloud data obtained through a series of coordinate transformations using the current external parameters is not flat and does not conform to the real situation (because the real situation is that the surface of the target plane object is flat ), indicating that the current external parameters are inaccurate, and the external parameters of the vehicle radar need to be calibrated. In this way, it can be accurately judged whether the current external parameter is accurate, and the accuracy is high.
  • the adjusting the external parameter includes: generating an objective function based on the external parameter, where the objective function is used to describe the angle between the first vector and the normal vector , or, the objective function is used to describe the projection distance of the normal vector on the first vector; within a preset extrinsic parameter adjustment range, search for an extrinsic parameter that makes the objective function reach a minimum value.
  • an objective function can be generated to find the optimal value of the external parameter to improve the accuracy of the external parameter.
  • a method for calibrating external parameters of a vehicle-mounted radar which is applied to a vehicle, and the vehicle includes a radar.
  • the method includes: acquiring external parameters of the vehicle-mounted radar, and using the external parameters to convert the first point cloud data corresponding to the target plane object around the vehicle's driving road in the vehicle-mounted radar coordinate system into the first point cloud data in the inertial coordinate system Two point cloud data; if the flatness of the second point cloud data does not meet the first condition, the external parameter is calibrated.
  • the flatness of the second point cloud data does not satisfy the first condition, including: in the second point cloud data, between any two reflection points of different transmit beams on the target plane object The first vector of and the normal vector of the point cloud data corresponding to any one or more transmit beams in the second point cloud data are not perpendicular;
  • the first vector between the reflection points of any two different transmit beams on the target plane object in the second point cloud data and the point cloud data corresponding to any one or more transmit beams in the second point cloud data The angle between the normal vectors of is not within the preset range.
  • the external parameter includes at least one of the rotation angle or the translation distance of the vehicle radar; the method further includes: according to the target reference around the driving road , and determine at least one of the rotation angle or the translation distance of the vehicle-mounted radar.
  • the determining the rotation angle of the vehicle-mounted radar according to the target reference around the driving road includes: determining the vehicle-mounted radar according to the ground of the driving road or a plane object parallel to the ground The pitch angle and roll angle of the vehicle are determined; the yaw angle of the vehicle-mounted radar is determined according to the objects arranged along the driving road.
  • the objects arranged along the driving road include: objects of the first type arranged along the driving road and parallel to the ground of the driving road, and/or, along the driving road and with The second type of objects vertically arranged on the ground of the driving road;
  • the first type of objects includes: at least one of road edges, guardrails, green belts or lane lines;
  • the second type of objects includes: trees, signs or at least one of street lights.
  • Another way of calibrating the external parameter is: based on the external parameter, generate an objective function, and the objective function is used to describe the angle between the first vector and the normal vector, or, The objective function is used to describe the projection distance of the normal vector on the first vector; within a preset extrinsic parameter adjustment range, search for an extrinsic parameter that makes the objective function reach a minimum value.
  • a method for calibrating external parameters of a vehicle-mounted radar is also provided, which is applied to a vehicle, and the vehicle includes a radar.
  • the method includes:
  • the external parameters of the vehicle radar are calibrated.
  • the external parameter includes at least one of a rotation angle or a translation distance of the vehicle-mounted radar; according to the target reference, the external parameters of the vehicle-mounted radar are calibrated, including: according to the target reference The target reference around the driving road determines at least one of the rotation angle or the translation distance of the vehicle-mounted radar.
  • the determining the rotation angle of the vehicle-mounted radar according to the target reference around the driving road includes: determining the vehicle-mounted radar according to the ground of the driving road or a plane object parallel to the ground The pitch angle and roll angle of the vehicle are determined; the yaw angle of the vehicle-mounted radar is determined according to the objects arranged along the driving road.
  • the objects arranged along the driving road include: objects of the first type arranged along the driving road and parallel to the ground of the driving road, and/or, along the driving road and with The second type of objects vertically arranged on the ground of the driving road;
  • the first type of objects includes: at least one of road edges, guardrails, green belts or lane lines;
  • the second type of objects includes: trees, signs or at least one of street lights.
  • a method for calibrating external parameters of a vehicle-mounted radar is also provided, which is applied to a vehicle, and the vehicle includes a radar.
  • the method includes: acquiring external parameters of the vehicle-mounted radar; using the external parameters to convert the first point cloud data corresponding to the target plane object around the vehicle's driving road in the vehicle-mounted radar coordinate system into the first point cloud data in the inertial coordinate system Two point cloud data; generate an objective function, the objective function is used to describe the first vector and the second point between the reflection points of any two different emission beams on the target plane object in the second point cloud data the angle between the normal vectors of the point cloud data corresponding to any one or more transmit beams in the point cloud data, or the objective function is used to describe the projection distance of the normal vector on the first vector; Within the preset external parameter adjustment range, find the external parameter that makes the objective function reach the minimum value.
  • the method before searching for an external parameter that makes the objective function reach a minimum value, the method further includes: determining that the flatness of the second point cloud data does not satisfy the first condition.
  • the flatness of the second point cloud data does not satisfy the first condition, including: in the second point cloud data, between any two reflection points of different transmit beams on the target plane object
  • the first vector of the second point cloud data is not perpendicular to the normal vector of the point cloud data corresponding to any one or more transmit beams in the second point cloud data; or,
  • the first vector between the reflection points of any two different transmit beams on the target plane object in the second point cloud data and the point cloud data corresponding to any one or more transmit beams in the second point cloud data The angle between the normal vectors of is not within the preset range.
  • acquiring the external parameters of the vehicle-mounted radar includes: determining a target reference around the road where the vehicle travels; and calibrating the external parameters of the vehicle-mounted radar according to the target reference.
  • the external parameter includes at least one of a rotation angle or a translation distance of the vehicle-mounted radar; according to the target reference, the external parameters of the vehicle-mounted radar are calibrated, including: according to the target reference The target reference around the driving road determines at least one of the rotation angle or the translation distance of the vehicle-mounted radar.
  • the determining the rotation angle of the vehicle-mounted radar according to the target reference around the driving road includes: determining the vehicle-mounted radar according to the ground of the driving road or a plane object parallel to the ground The pitch angle and roll angle of the vehicle are determined; the yaw angle of the vehicle-mounted radar is determined according to the objects arranged along the driving road.
  • the objects arranged along the driving road include: objects of the first type arranged along the driving road and parallel to the ground of the driving road, and/or, along the driving road and with The second type of objects vertically arranged on the ground of the driving road;
  • the first type of objects includes: at least one of road edges, guardrails, green belts or lane lines;
  • the second type of objects includes: trees, signs or at least one of street lights.
  • an external parameter calibration device for a vehicle-mounted radar may be a vehicle or a device within a vehicle (such as a chip or a system-on-chip).
  • the device includes: an acquisition unit for acquiring driving information of the vehicle, where the driving information includes at least one of driving state information or driving road condition information; wherein the driving state information includes speed, acceleration, yaw angle or At least one of yaw angular velocity; the driving road condition information includes at least one of the driving road of the vehicle or the objects around the driving road; the processing unit, according to the driving information, performs external processing on the vehicle radar; parameter calibration.
  • the processing unit is specifically configured to: according to the driving state information, when it is determined that at least one of the following conditions is satisfied, perform external parameter calibration on the vehicle radar, wherein the conditions include:
  • the speed is less than a first threshold
  • the vehicle is traveling at an average speed
  • the acceleration is less than a second threshold
  • the yaw angle is within a preset range
  • the yaw angle speed is less than a third threshold.
  • the processing unit is specifically configured to: determine, according to the driving road condition information, that the driving road is a straight road and/or when there is a target reference object around the driving road, perform the detection on the vehicle radar Perform external parameter calibration.
  • the external parameter includes at least one of a rotation angle or a translation distance of the vehicle-mounted radar; the processing unit is further configured to: determine, according to the target reference around the driving road, the at least one of the rotation angle or the translation distance of the vehicle-mounted radar.
  • the processing unit when used to determine the rotation angle of the vehicle radar according to the target reference objects around the driving road, it is specifically used for: according to the ground or For a plane object parallel to the ground, the pitch angle and the roll angle of the vehicle-mounted radar are determined; and the yaw angle of the vehicle-mounted radar is determined according to the objects arranged along the driving road.
  • the objects disposed along the travel road include: first type objects disposed along the travel road and parallel to the ground of the travel road, and/or along the travel road The second type of object on the driving road and perpendicular to the ground of the driving road; wherein, the first type of object includes: at least one of a road edge, a guardrail, a green belt or a lane line; the second type of object Type objects include: at least one of trees, signs, or street lights.
  • the acquisition unit is further configured to: acquire external parameters of the vehicle radar; the processing unit is further configured to: use the external parameters to record the target plane objects around the driving road on the vehicle
  • the corresponding first point cloud data in the radar coordinate system is converted into the second point cloud data in the inertial coordinate system; if the flatness of the second point cloud data does not meet the first condition, the external parameter is adjusted.
  • the flatness of the second point cloud data does not satisfy the first condition, including: any two reflection points of different transmit beams in the second point cloud data on the target plane object
  • the first vector between is not perpendicular to the normal vector of the point cloud data corresponding to any one or more transmit beams in the second point cloud data; or, any two different transmit beams in the second point cloud data are in the
  • the included angle between the first vector between the reflection points on the target plane object and the normal vector of the point cloud data corresponding to any one or more transmit beams in the second point cloud data is not within a preset range.
  • the processing unit when adjusting the external parameters, is specifically configured to: generate an objective function based on the external parameters, where the objective function is used to describe the first vector and the method The included angle between the vectors, or the objective function is used to describe the projection distance of the normal vector on the first vector; within the preset external parameter adjustment range, find a value that makes the objective function reach the minimum value. External reference.
  • an external parameter calibration device for a vehicle-mounted radar.
  • the device may be a vehicle, or a module (such as a chip or system-on-chip) in a vehicle that includes a radar.
  • the device includes: an acquisition unit for acquiring external parameters of the vehicle-mounted radar; a processing unit for using the external parameters to obtain the first point corresponding to the target plane object around the vehicle's driving road in the vehicle-mounted radar coordinate system
  • the cloud data is converted into second point cloud data in the inertial coordinate system; if the flatness of the second point cloud data does not meet the first condition, the external parameters are calibrated.
  • the flatness of the second point cloud data does not satisfy the first condition, including: in the second point cloud data, between any two reflection points of different transmit beams on the target plane object
  • the first vector of the second point cloud data is not perpendicular to the normal vector of the point cloud data corresponding to any one or more transmit beams in the second point cloud data; or, any two different transmit beams in the second point cloud data are at the target
  • the included angle between the first vector between the reflection points on the plane object and the normal vector of the point cloud data corresponding to any one or more transmit beams in the second point cloud data is not within a preset range.
  • the external parameter includes at least one of the rotation angle or the translation distance of the vehicle-mounted radar; according to the target reference around the driving road, determine At least one of the rotation angle or the translation distance of the vehicle radar.
  • the determining the rotation angle of the vehicle-mounted radar according to the target reference around the driving road includes: determining the vehicle-mounted radar according to the ground of the driving road or a plane object parallel to the ground The pitch angle and roll angle of the vehicle are determined; the yaw angle of the vehicle-mounted radar is determined according to the objects arranged along the driving road.
  • the objects arranged along the driving road include: objects of the first type arranged along the driving road and parallel to the ground of the driving road, and/or, along the driving road and with The second type of objects vertically arranged on the ground of the driving road;
  • the first type of objects includes: at least one of road edges, guardrails, green belts or lane lines;
  • the second type of objects includes: trees, signs or at least one of street lights.
  • Another way for the processing unit to calibrate the external parameters is to generate an objective function based on the external parameters, where the objective function is used to describe the angle between the first vector and the normal vector , or, the objective function is used to describe the projection distance of the normal vector on the first vector; within a preset extrinsic parameter adjustment range, search for an extrinsic parameter that makes the objective function reach a minimum value.
  • an external parameter calibration device for a vehicle-mounted radar may be a vehicle, or a module (such as a chip or a system of chips) in a vehicle that includes a radar.
  • the device includes: a determining unit for determining a target reference around the road where the vehicle travels; a processing unit for calibrating the external parameters of the vehicle-mounted radar according to the target reference.
  • the external parameter includes at least one of a rotation angle or a translation distance of the vehicle-mounted radar; according to the target reference, the external parameters of the vehicle-mounted radar are calibrated, including: according to the target reference The target reference around the driving road determines at least one of the rotation angle or the translation distance of the vehicle-mounted radar.
  • the determining the rotation angle of the vehicle-mounted radar according to the target reference around the driving road includes: determining the vehicle-mounted radar according to the ground of the driving road or a plane object parallel to the ground The pitch angle and roll angle of the vehicle are determined; the yaw angle of the vehicle-mounted radar is determined according to the objects arranged along the driving road.
  • the objects arranged along the driving road include: objects of the first type arranged along the driving road and parallel to the ground of the driving road, and/or, along the driving road and with The second type of objects vertically arranged on the ground of the driving road;
  • the first type of objects includes: at least one of road edges, guardrails, green belts or lane lines;
  • the second type of objects includes: trees, signs or at least one of street lights.
  • a device for calibrating external parameters of a vehicle-mounted radar may be a vehicle, or a module (such as a chip or a system of chips) in a vehicle that includes a radar.
  • the device includes: an acquisition unit for acquiring external parameters of the vehicle-mounted radar; a processing unit for using the external parameters to obtain the first point corresponding to the target plane object around the vehicle's driving road in the vehicle-mounted radar coordinate system
  • the cloud data is converted into second point cloud data in the inertial coordinate system;
  • the processing unit is further configured to generate an objective function, and the objective function is used to describe any two different emission beams in the second point cloud data on the target plane object
  • the angle between the first vector between the reflection points on the second point cloud data and the normal vector of the point cloud data corresponding to any one or more transmit beams in the second point cloud data, or the objective function is used to describe the The projection distance of the normal vector on the first vector;
  • the processing unit is further configured to search for the extrinsic parameter that makes the objective function reach the
  • the method before searching for an external parameter that makes the objective function reach a minimum value, the method further includes: determining that the flatness of the second point cloud data does not satisfy the first condition.
  • the flatness of the second point cloud data does not satisfy the first condition, including: in the second point cloud data, between any two reflection points of different transmit beams on the target plane object
  • the first vector of the second point cloud data is not perpendicular to the normal vector of the point cloud data corresponding to any one or more transmit beams in the second point cloud data; or,
  • the first vector between the reflection points of any two different transmit beams on the target plane object in the second point cloud data and the point cloud data corresponding to any one or more transmit beams in the second point cloud data The angle between the normal vectors of is not within the preset range.
  • acquiring the external parameters of the vehicle-mounted radar includes: determining a target reference around the road where the vehicle travels; and calibrating the external parameters of the vehicle-mounted radar according to the target reference.
  • the external parameter includes at least one of a rotation angle or a translation distance of the vehicle-mounted radar; according to the target reference, the external parameters of the vehicle-mounted radar are calibrated, including: according to the target reference The target reference around the driving road determines at least one of the rotation angle or the translation distance of the vehicle-mounted radar.
  • the determining the rotation angle of the vehicle-mounted radar according to the target reference around the driving road includes: determining the vehicle-mounted radar according to the ground of the driving road or a plane object parallel to the ground The pitch angle and roll angle of the vehicle are determined; the yaw angle of the vehicle-mounted radar is determined according to the objects arranged along the driving road.
  • the objects arranged along the driving road include: objects of the first type arranged along the driving road and parallel to the ground of the driving road, and/or, along the driving road and with The second type of objects vertically arranged on the ground of the driving road;
  • the first type of objects includes: at least one of road edges, guardrails, green belts or lane lines;
  • the second type of objects includes: trees, signs or at least one of street lights.
  • a device for calibrating external parameters of a vehicle-mounted radar comprising a memory and one or more processors; wherein, the memory is used to store computer program codes, and the computer program codes include computer instructions; The computer instructions, when executed by the processor, cause the apparatus to perform the method of any one of the first to fourth aspects above.
  • a vehicle which includes the above-mentioned device for calibrating external parameters of a vehicle-mounted radar according to any one of the fifth aspect to the tenth aspect.
  • the vehicle-mounted radar external parameter calibration device may be, for example, a processing module in a vehicle, such as a vehicle-mounted processor or an electronic control unit (electronic control unit, ECU) or the like.
  • a computer-readable storage medium comprising computer instructions, when the computer instructions are executed in the external parameter calibration device of the vehicle-mounted radar, the external parameter calibration device of the vehicle-mounted radar is made to perform the above-mentioned first.
  • a twelfth aspect further provides a computer program product that, when the computer program product runs on a processor, causes the processor to perform the method according to any one of the first to fourth aspects above.
  • FIG. 1 is a schematic diagram of an application scenario provided by an embodiment of the present application
  • FIG. 2 is a schematic diagram of a radar coordinate system, a vehicle coordinate system, and an inertial coordinate system provided by an embodiment of the present application;
  • FIG. 3 is a schematic diagram of a relative relationship between a radar coordinate system and a vehicle coordinate system provided by an embodiment of the present application;
  • FIG. 4 is an exemplary functional block diagram of a vehicle according to an embodiment of the present application.
  • FIG. 5 is an exemplary schematic flowchart of a method for calibrating a vehicle-mounted radar provided by an embodiment of the present application
  • FIG. 6 is another exemplary schematic flowchart of a calibration method for a vehicle-mounted radar provided by an embodiment of the present application
  • FIG. 7 is a schematic diagram of judging the flatness of a point cloud according to an embodiment of the present application.
  • FIG. 8 is another exemplary schematic flowchart of a calibration method for a vehicle-mounted radar provided by an embodiment of the present application.
  • FIG. 9 is a schematic diagram of an image collected by a vehicle according to an embodiment of the present application.
  • FIG. 10 is a schematic structural diagram of an exemplary structure of a vehicle-mounted radar external parameter calibration device provided by an embodiment of the application.
  • FIG. 11 is a schematic structural diagram of another exemplary structure of a vehicle-mounted radar external parameter calibration device provided by an embodiment of the present application.
  • Vehicle radar refers to a radar set on a vehicle, which can be a vehicle carrier radar, such as a lidar, a microwave radar, or a millimeter-wave radar.
  • Vehicle-mounted radar can realize functions such as obstacle measurement, collision prediction, adaptive cruise control, etc., which can effectively reduce the difficulty of driving, reduce the burden on drivers and reduce the incidence of accidents, so it has been widely used in the automotive field.
  • the vehicle carrier radar can detect the relative distance, relative speed and angle between the vehicle and the target (such as objects around the vehicle), and then track and identify the target according to the obtained information. After a reasonable decision, the driver will be informed or warned in various ways such as sound, light and touch, or the car will be actively intervened in time, so as to ensure the safety and comfort of the driving process and reduce the probability of accidents.
  • Vehicle radars may include transmitters and receivers.
  • the transmitter is used to transmit the electromagnetic wave energy beam.
  • the electromagnetic wave is transmitted to the antenna through the transceiver switch.
  • the antenna then transmits the electromagnetic wave into the air along a certain direction and angle. If there is a target within a certain distance along the emission direction of the electromagnetic wave energy beam, then The electromagnetic wave energy beam is reflected by the target, and when the electromagnetic wave encounters the target object, a part of the energy will be reflected and received by the antenna of the vehicle carrier radar, and then transmitted to the receiver through the transceiver switch.
  • the receiver is used to determine the information related to the target according to the received echo signal and the transmitted electromagnetic wave energy beam. For example, the distance to the target, the point cloud density of the target, etc.
  • the radar sensor transmits an electromagnetic wave energy beam through the transmitter, and further processes the signal processor to obtain the relative distance, angle and relative speed of the target object.
  • Vehicle lidar is a type of vehicle radar. Vehicle lidars have transmitters and receivers. The transmitter emits a laser beam, and after the laser beam encounters a target (such as an object around the vehicle), it is reflected and returned to the receiver. Multiplying the interval between transmit and receive times by the speed of light and dividing by 2, the distance between the transmitter and the target can be calculated.
  • Vehicle lidar includes single-beam laser transmitter, four-line laser radar, sixteen-line laser radar, thirty-two-line laser radar and so on.
  • the single-beam laser transmitter can rotate at a constant speed inside the lidar, and emits a laser every time it rotates a small angle. After a certain angle, a complete frame of data is generated. Therefore, the data of single-line lidar can be regarded as a row of lattices at the same height.
  • Four-line LiDAR polls four laser transmitters. After one polling period, a frame of laser point cloud data is obtained.
  • the laser point cloud data can be composed of planar information, and the height information of obstacles can be obtained. Therefore, the higher the number of laser emitters, the higher the efficiency and the richer the information obtained.
  • FIG. 2 is a schematic diagram of the vehicle coordinate system.
  • the origin of the vehicle coordinate system can be at any position on the vehicle (such as the center of mass, the ground below the midpoint of the rear axle of the vehicle), the x-axis is forward along the front of the vehicle, and the z-axis is perpendicular to the chassis of the vehicle. When facing forward, the y-axis points to the left of the vehicle.
  • FIG. 2 is a schematic diagram of the radar coordinate system.
  • the origin of the radar coordinate system is at the location where the radar is installed on the vehicle.
  • the x-axis, y-axis, and z-axis can be defined in various ways. For example, they are designed by the manufacturer of the vehicle-mounted radar, and the designs of different manufacturers are different. Generally speaking, there is a rotation and translation relationship between the radar coordinate system and the vehicle coordinate system.
  • FIG. 2 is a schematic diagram of the inertial coordinate system.
  • Inertial coordinate system also known as public coordinate system, world coordinate system or global coordinate system, etc., its coordinate origin is a fixed point in space and is an absolute coordinate system. All objects in space can be based on inertial coordinate system. to determine the location of the object.
  • the common coordinate system may be a world coordinate system with east, north, and sky as the X-axis, Y-axis, and Z-axis.
  • the coordinates of the target in the radar coordinate system are different from those in the real world, so the target can be placed in the radar coordinate system.
  • the coordinates are converted to the vehicle coordinate system, and then converted to the inertial coordinate system to determine the position of the target in the real environment. It should be understood that, in the process of converting one coordinate system to another coordinate system, the relative positional relationship (such as rotation and translation relationship) between the two coordinate systems needs to be used. Therefore, to realize the conversion from the radar coordinate system to the inertial coordinate system, it is necessary to use: 1.
  • the relative positional relationship between the radar coordinate system and the vehicle coordinate system which is used to convert the coordinates from the radar coordinate system to the vehicle coordinate system.
  • the relative positional relationship 2 between the vehicle coordinate system and the inertial coordinate system, the relative positional relationship 2 is used for coordinate transformation from the vehicle coordinate system to the world coordinate system.
  • the parameters that need to be used when the radar coordinate system is converted to the vehicle coordinate system are called the external parameters of the vehicle radar.
  • External parameters of vehicle radar referred to as external parameters
  • the radar coordinate system and the vehicle coordinate system have a relative positional relationship, and the relative positional relationship includes a rotation and translation relationship.
  • the relative position relationship is called the external parameters of the vehicle-mounted radar, that is to say, the external parameters of the vehicle-mounted radar include the rotation and translation relationship of the radar coordinate system of the vehicle-mounted radar with respect to the vehicle coordinate system.
  • FIG. 3 is a schematic diagram of the relative positional relationship between the radar coordinate system and the vehicle coordinate system.
  • the origin of the radar coordinate system is defined as OL
  • its coordinate system is OL -X L Y L Z L
  • the origin of the vehicle coordinate system is defined as O V
  • the external parameters of the vehicle-mounted radar include the rotation and translation relationship of the radar coordinate system relative to the vehicle coordinate system, wherein the rotation relationship is described by the rotation angle, and the translation relationship is described by the translation distance.
  • the rotation angle of the radar coordinate system relative to the vehicle coordinate system can be described by three attitude angles, namely the pitch angle ⁇ (pitch), the yaw angle ⁇ (yaw), and the roll angle ⁇ (roll).
  • the pitch angle ⁇ (pitch) refers to the counterclockwise rotation angle around the Y L axis
  • the yaw angle ⁇ (yaw) refers to the counterclockwise rotation angle around the Z L axis
  • the roll angle ⁇ (roll) refers to the rotation angle around the XL axis The angle by which the axis is rotated counterclockwise.
  • the translation distance of the radar coordinate system relative to the vehicle coordinate system can be described using three translation distances, ie, ⁇ x, ⁇ y, ⁇ z.
  • ⁇ x is the projection value on the x-axis direction of the distance from the origin of the coordinates of the radar coordinate system OL to the origin of the coordinates of the vehicle coordinate system OV.
  • ⁇ y is the projection value on the y-axis direction of the distance from the origin of the coordinates of the radar coordinate system OL to the origin of the coordinates of the vehicle coordinate system OV.
  • ⁇ z is the projection value in the z -axis direction of the distance from the origin of the coordinates of the radar coordinate system OL to the origin of the coordinates of the vehicle coordinate system OV.
  • the radar coordinate system coordinate origin OL is connected with the vehicle coordinate system.
  • - ⁇ x refers to the opposite direction to ⁇ x
  • - ⁇ y to the opposite direction to ⁇ y
  • - ⁇ z to the opposite direction to ⁇ z.
  • the rotation angle and translation distance can be used to place a target (such as an object around the vehicle) in the radar coordinate system
  • the coordinates are converted to the vehicle coordinate system. Since the rotation angle and translation distance are collectively referred to as the external parameters of the vehicle-mounted radar, the process of determining the rotation angle and translation distance of the radar coordinate system relative to the vehicle coordinate system can be called the calibration process of the external parameters of the vehicle-mounted radar. It can be understood as determining, obtaining, calculating, etc.
  • the external parameter calibration of the vehicle radar refers to the process of determining the external parameters of the vehicle radar.
  • the external parameters of the vehicle radar include the rotation angle and translation distance of the radar coordinate system relative to the vehicle coordinate system. Therefore, the external parameter calibration process of the vehicle radar can be understood as determining the rotation angle of the radar coordinate system relative to the vehicle coordinate system. (including three attitude angles) and the process of translation distance.
  • the external parameters of the vehicle radar are the important parameters that need to be used in the process of converting from the coordinates in the radar coordinate system to the vehicle coordinate system. If the calibration of the external parameters of the vehicle radar is not accurate, the exact coordinates of the target in the vehicle coordinate system cannot be obtained, and the accurate position of the target in the inertial coordinate system cannot be obtained. That is, the vehicle cannot determine the real position of the surrounding objects, which will affect the safe driving of the vehicle. For example, due to the inaccurate external parameters of the on-board radar, the vehicle determines that the object in front is 2m away from the vehicle after a series of coordinate transformations, but in fact the object in front is only 1m away from the vehicle, which is prone to danger and cannot guarantee driving safety.
  • the present application provides an external parameter calibration method for a vehicle-mounted radar.
  • the external parameters of the vehicle radar are calibrated according to the driving information of the vehicle.
  • the driving information of the vehicle includes at least one of driving road condition information or driving state information.
  • the traveling state information includes at least one of speed, acceleration, yaw angle, or yaw angular velocity.
  • the driving road condition information includes at least one of a driving road of the vehicle or objects around the driving road. That is to say, the external parameter calibration of the on-board radar can be completed while the vehicle is running, without the need to return to the factory for calibration, which is more convenient and has a better user experience.
  • the vehicle when the vehicle is driving, if the external parameters of the on-board radar are calibrated according to the driving information, after a period of driving, the external parameters of the on-board radar will be calibrated. Change, for example, from external parameter 1 to external parameter 2, then the vehicle uses external parameter 2 for calculation (such as determining the coordinates of the target in the inertial coordinate system). That is to say, the calibration of the external parameters of the vehicle radar is completed during the driving process of the vehicle.
  • the completion of the external parameter calibration of the vehicle radar during the driving process of the vehicle can be understood as online calibration
  • the online calibration can be understood as the completion of the calibration during the operation of the vehicle radar or the operation of the vehicle system.
  • the mid-vehicle radar is in an online state (or a working state or a running state).
  • the calibration method that is different from online calibration is offline calibration, such as return-to-factory calibration.
  • the on-board radar cannot be used normally, that is, it is in an offline state. Therefore, the external parameter calibration method of the vehicle radar provided in the embodiment of the present application is more practical, and can perform online calibration in real time, improve the accuracy of determining the position of a target (eg, objects around the vehicle), and ensure driving safety.
  • the external parameter calibration method of the vehicle-mounted radar provided in the embodiment of the present application can be applied to a vehicle.
  • the vehicle includes an onboard radar.
  • in-vehicle radar or radar sensor
  • vehicles such as unmanned vehicles, smart vehicles, electric vehicles, digital vehicles, etc.
  • the on-board radar deployed on the vehicle can perceive the fan-shaped area shown by the solid line frame, and the fan-shaped area can be understood as the on-board radar sensing area.
  • Signals, such as point cloud data are transmitted to the processing module for further processing.
  • the processing module After receiving the signal from the vehicle radar, the processing module outputs the measurement information of the target (for example, the relative distance, angle, and relative speed between the target and the vehicle).
  • the processing module here can be either a hardware or software module independent of the vehicle-mounted radar, or a hardware or software module deployed in the vehicle-mounted radar, which is not limited here. It can be seen that by installing the on-board radar on the vehicle body, measurement information such as the position and relative distance of surrounding objects can be sensed in real time or periodically, and then assisted driving or unmanned driving of the vehicle can be realized according to these measurement information. For example, the distance of surrounding objects relative to the vehicle is used to determine the number, density, etc. of obstacles around the vehicle.
  • the vehicle-mounted radar in the present application may be a laser radar, a microwave radar, or a millimeter-wave radar, which is not limited in the embodiment of the present application.
  • this application does not limit the number of vehicle-mounted radars deployed on the vehicle in the scenario shown in FIG. 4 .
  • FIG. 5 is a schematic flowchart of a method for calibrating external parameters of a vehicle-mounted radar according to an embodiment of the present application. This method can be applied to a vehicle as shown in FIG. 4 . As shown in Figure 5, the process includes:
  • the driving information of the vehicle includes at least one item of driving road condition information or driving state information.
  • the driving status information and the driving road condition information are described below.
  • the traveling state information includes at least one of speed, acceleration, yaw angle, or yaw angle velocity.
  • the speed and/or acceleration may be determined according to motion parameters collected by motion sensors in the vehicle.
  • the motion sensor may be, for example, an accelerometer, a gyroscope, an inertial measurement unit (IMU), and the like.
  • the accelerometer can measure the linear acceleration of the three axes of the vehicle, which is used to calculate the driving speed of the vehicle.
  • the velocity and/or acceleration can also be obtained through a satellite navigation and positioning system.
  • the IMU can output the speed, acceleration, etc. of the vehicle.
  • the satellite navigation and positioning system includes, but is not limited to, global navigation satellite system (GNSS), global positioning system (global positioning system, GPS), Galileo system, etc. or enhanced systems of these systems.
  • GNSS is a radio navigation system with artificial satellites as "beacon", which provides all-weather, high-precision position, speed and time information for various carriers (such as vehicles) in the global land, sea, air and sky (such as vehicles). positioning navigation and timing, PNT).
  • the driving speed and/or acceleration of the vehicle can be determined by means of GNSS.
  • speed and/or acceleration can also be measured by a wheel velocity sensor (WSS).
  • WSS is a sensor for measuring the rotational speed of the wheels of the vehicle, and the traveling speed and/or acceleration of the vehicle can be determined by measuring the rotational speed of the wheels of the vehicle.
  • the wheel speed sensor includes, but is not limited to, a magnetoelectric wheel speed sensor, a Hall-type wheel speed sensor, and the like.
  • the yaw angle and/or the yaw angular velocity can be determined by on-board radar.
  • the yaw angle ⁇ (yaw) refers to the rotation angle of the vehicle around the Z L axis in the radar coordinate system O L -X L Y L Z L during the driving process, which can be simply understood as The angle of deviation from the route, for example, the vehicle turns left, right, U-turn, etc.
  • the yaw angular velocity refers to the change of the yaw angle per unit time. Therefore, the yaw angular velocity can be determined by determining the yaw angle within a certain period of time.
  • the yaw angle can be understood as the left turn angle
  • the yaw angle speed refers to the change of the yaw angle per unit time, so it can be understood as the change of the left turn angle, which reflects the left turn speed of the vehicle.
  • the yaw angle and/or the yaw angular velocity can also be calculated by a steering wheel sensor (steering wheel sensor, SAS).
  • SAS can determine the steering wheel rotation angle, rotation direction, and steering speed, etc., and the yaw angle can be estimated through these parameters. Heading angle and/or yaw angle.
  • the yaw angle and/or the yaw rate can also be estimated by the IMU.
  • the IMU can detect angular velocity, angular acceleration, etc., and the yaw angle and/or yaw angular velocity can be calculated from the detected parameters.
  • the driving road condition information is used to indicate at least one of the driving road of the vehicle or the object information around the driving road.
  • the use of the driving road condition information to indicate the driving road of the vehicle may be understood as being used to indicate the attribute of the driving road, such as a straight road, a right-turn road, a left-turn road, and the like.
  • road 1 is determined as the driving road of the vehicle, and then it can be determined according to the description information of the road 1 in the map Attributes of road 1 such as straight road, right turn road and so on.
  • the vehicle may collect images during the driving process, and determine the attributes of the driving road of the vehicle through image recognition, such as a straight road, a right-turn road, and the like.
  • an input button may be provided on the vehicle, and the driver may input the attribute of the driving road through the input button.
  • the object information around the driving road of the vehicle can be determined in various ways.
  • the vehicle collects images during driving, and determines the objects around the road where the vehicle travels through image recognition.
  • objects around the road where the vehicle travels can also be determined according to the point cloud data obtained by the vehicle-mounted radar.
  • the on-board radar can transmit electromagnetic waves that are emitted by surrounding objects and then collect the emitted electromagnetic waves.
  • the reflected electromagnetic waves are point cloud data.
  • objects around the road where the vehicle is traveling can be identified.
  • objects around the driving road of the vehicle include trees, curbs, street lights, signs, and the like.
  • S502 may include the following three situations.
  • the driving information of the vehicle includes driving state information.
  • S502 can be refined as follows: according to the driving state information, it is determined to calibrate the external parameters of the vehicle radar. Specifically, it may include: according to the driving state information, when it is determined that at least one of the following conditions is satisfied, determining to calibrate the external parameters of the vehicle-mounted radar.
  • the conditions include:
  • the vehicle travels at a constant speed. For example, whether the vehicle is traveling at a constant speed can be determined according to the speed, acceleration, etc. in the traveling state information.
  • the traveling speed of the vehicle is less than the first threshold value or within the first range.
  • the running acceleration of the vehicle is smaller than the second threshold value or within the second range.
  • the first threshold, the first range, the second threshold, and the second range may be set by default (for example, set by default before the vehicle leaves the factory), or set by the user, which is not limited in this embodiment of the present application.
  • the yaw angle is within the preset range.
  • the preset range is, for example, -5 degrees to 5 degrees. That is, the vehicle is going straight or approximately straight.
  • the yaw angular velocity is less than the third threshold or within the third range.
  • the third threshold and the third range may be set by default (for example, set by default before the vehicle leaves the factory), or set by the user, which is not limited in the embodiment of the present application.
  • the driving information of the vehicle includes driving road condition information.
  • S502 can be refined as: according to the driving road condition information, it is determined to calibrate the external parameters of the vehicle radar. Specifically, it may include: according to the driving road condition information, when it is determined that at least one of the following conditions is satisfied, determining to calibrate the external parameters of the vehicle-mounted radar.
  • the conditions include:
  • the driving road of the vehicle is a straight road.
  • the vehicle may determine the driving road condition information, and the driving road condition information is used to indicate the attributes of the driving road of the vehicle, such as a straight road, a right-turn road, and the like. Therefore, it can be determined whether the driving road is a straight road according to the driving road condition information.
  • the vehicle may determine the driving road condition information, and the driving road condition information may be used to indicate objects around the driving road of the vehicle, such as trees, road edges, street lights, signs, and the like. Therefore, it can be determined whether there is a target reference around the vehicle driving road according to the vehicle driving road condition information.
  • target references include the following two categories.
  • the determining that a target reference exists around the vehicle driving road includes: determining that at least one of the two types of target references exists around the driving road.
  • the two categories include:
  • the first type of target reference includes: at least one of the ground of the driving road or a plane object parallel to the ground.
  • the second type of target reference includes: objects set along the driving road. For example, at least one of a type A object along the driving road and parallel to the ground of the driving road, or a type B object along the driving road and perpendicular to the ground of the driving road.
  • the A-type object includes at least one of a road edge, a guardrail, a green belt or a lane line.
  • Type B objects include: at least one of trees, signs, or street lights.
  • the third situation can be understood as the combination of the first situation and the second situation, that is, the driving information of the vehicle includes the driving road condition information and the driving state information.
  • S502 can be refined as follows: determine whether to calibrate the external parameters of the on-board radar according to the driving state information (see the first case for the realization principle); if so, continue to judge whether to calibrate the external parameters of the on-board radar according to the driving road condition information. Calibration (see the second case for the implementation principle), if not, it is determined not to calibrate the external parameters of the vehicle radar, and there is no need to continue to make judgments based on the driving road condition information.
  • S502 can also be refined as follows: determine whether to calibrate the external parameters of the vehicle-mounted radar according to the driving road condition information; if so, continue to judge whether to calibrate the external parameters of the vehicle-mounted radar according to the driving state information; if not, determine not to calibrate the vehicle-mounted radar. It is not necessary to continue to make judgments based on the driving state information. These two methods can perform double judgment and improve the accuracy.
  • the first embodiment above is to determine whether to calibrate the external parameters of the vehicle radar according to the driving information of the vehicle.
  • the second embodiment provides another way of determining whether to calibrate the external parameters of the vehicle-mounted radar.
  • FIG. 6 is another schematic flowchart of a method for calibrating external parameters of a vehicle-mounted radar according to an embodiment of the present application. As shown in Figure 6, the process includes:
  • the acquired external parameters may be external parameters of the vehicle-mounted radar calibrated last time or initial external parameters (for example, external parameters set at the factory).
  • the extrinsic parameter includes at least one of a rotation angle or a translation distance.
  • the rotation angle includes three attitude angles, namely, the pitch angle ⁇ (pitch), the yaw angle ⁇ (yaw), and the roll angle ⁇ (roll).
  • the translation distance includes ⁇ x, ⁇ y, and ⁇ z.
  • R Assuming that the rotation angle is represented by R, then R can be expressed as:
  • r 11 is the projection of the x-axis of the radar coordinate system on the x-axis of the vehicle coordinate system
  • r 12 is the projection of the x-axis of the radar coordinate system on the y-axis of the vehicle coordinate system
  • r 13 is the x-axis of the radar coordinate system in the The projection of the z-axis of the vehicle coordinate system
  • r 21 is the projection of the y-axis of the radar coordinate system on the x-axis of the vehicle coordinate system
  • r 22 is the projection of the y-axis of the radar coordinate system on the y-axis of the vehicle coordinate system
  • r 23 is The projection of the y-axis of the radar coordinate system on the z-axis of the vehicle coordinate system
  • r 31 is the projection of the z-axis of the radar coordinate system on the x-axis of the vehicle coordinate system
  • r 32 is the z-axis of the radar coordinate system on the y-axis of the vehicle coordinate system
  • T is represented as:
  • the step may further include: determining a target plane object.
  • the target plane object may be a sign, ground, billboard and other plane objects around the vehicle.
  • the vehicle can acquire images including surrounding objects, and determine the target planar object based on the images.
  • point cloud data of surrounding objects may also be acquired, where the point cloud data corresponds to all surrounding objects, and the point cloud data is represented in a radar coordinate system.
  • the point cloud data of the target plane object is determined from the point cloud data. For example, it can be determined that points in the point cloud data that are on the same plane or approximately the same plane constitute the point cloud data of the target plane object.
  • S602 includes two processes.
  • Process 1 Convert the first point cloud data of the target plane object in the radar coordinate system to the third point cloud data in the vehicle coordinate system.
  • Process 2 Convert the third point cloud data to the second point cloud data in the inertial coordinate system.
  • Process 1 Convert the first point cloud data to the third point cloud data in the vehicle coordinate system according to the following formula (1).
  • (x 0 , y 0 , z 0 ) is the coordinate of a point in the first point cloud data in the radar coordinate system
  • (x 1 , y 1 , z 1 ) is the coordinate of this point in the vehicle coordinate system.
  • R and T are the external parameters of the vehicle radar, where R is the rotation angle and T is the translation distance.
  • R and T please refer to the introduction of S601.
  • the third point cloud data is converted to the second point cloud data in the inertial coordinate system according to the following formula (2).
  • (x 1 , y 1 , z 1 ) are the coordinates of a point in the third point cloud data in the vehicle coordinate system
  • (x 2 , y 2 , z 2 ) are the coordinates of this point in the inertial coordinate system.
  • R1 is the rotation angle of the vehicle coordinate system relative to the inertial coordinate system
  • T1 is the translation distance of the vehicle coordinate system relative to the inertial coordinate system.
  • R1 and T1 are preset, or, R1 and T1 may also be calculated by sensing devices such as GNSS, IMU, WSS, and SAS, and the specific calculation process is not repeated in the embodiments of this application.
  • S603 Determine whether the flatness of the second point cloud data satisfies the first condition.
  • the flatness of the second point cloud data can be understood as the degree to which the second point cloud data are on the same plane. For example, if most or all of the point cloud data in the second point cloud data are on the same plane, the flatness of the second point cloud data is considered to be good.
  • the first way is to determine whether the flatness of the second point cloud data satisfies the first condition, which may include: when the first vector and the second vector in the second point cloud data are perpendicular or nearly perpendicular, determining the second point cloud data The flatness of satisfies the first condition, otherwise, it is determined that the flatness of the second point cloud data does not satisfy the first condition.
  • the first vector is the vector between the reflection points of any two different transmit beams on the target plane object in the second point cloud data
  • the second vector is the corresponding one or more transmit beams in the second point cloud data The normal vector of the point cloud data.
  • any two different emission beams can be beams emitted by any two different transmitters on the vehicle radar, or any two different beams emitted by the same transmitter, or, two adjacent beams, or , are the two closest beams, etc., which are not limited in the embodiments of the present application.
  • first vector and the second vector are nearly perpendicular can be understood as the angle between the first vector and the second vector being smaller than the preset angle or within the preset angle range.
  • the value is not limited in this embodiment of the present application, for example, 85 degrees to 95 degrees.
  • the method may further include the step of: selecting part of the point cloud data from the second point cloud data, and determining the first vector based on the part of the point cloud data.
  • the vehicle-mounted radar can emit a beam, and the emitted beam is emitted on the target plane object to generate a reflection point, and the reflected beam is received by the vehicle-mounted radar.
  • the vehicle-mounted radar calculates the reflection point according to the transmitted beam and the received reflected beam.
  • the coordinate value in the system ie the first point cloud data
  • the coordinate value in the radar coordinate system is converted to the coordinate value in the inertial coordinate system (ie the second point cloud data).
  • the points in the second point cloud data correspond to different reflection points, that is, correspond to different emission light beams.
  • the partial point cloud data may be point cloud data corresponding to a plurality of different emission beams in the second point cloud data, for example, point cloud data corresponding to emission beam 1 and emission beam 2, then the first vector can emit beams 1
  • the vector between the reflection point 1 on the target plane object and the reflection point 2 of the emission beam 2 on the target plane object for example, see Figure 7, which is a schematic diagram of the second point cloud data, assuming points P and Point Q is a reflection point corresponding to two different transmit beams in the second point cloud data, so the vector between point P and point Q may be the first vector.
  • the step may further include: determining the second vector.
  • the second vector may be the normal vector corresponding to all point cloud data in the second point cloud data, or the second vector may be part of the point cloud data in the second point cloud data (for example, part of the points selected when determining the first vector)
  • the normal vector corresponding to the cloud data or, the second vector may also be the normal vector of the point cloud data corresponding to any one or more transmit beams in the second point cloud data.
  • FIG. 7 is a schematic diagram of the second point cloud data
  • point P and point Q are points corresponding to two different transmit beams in the second point cloud data. If the first vector between point P and point Q is perpendicular or nearly perpendicular to the normal vector of the second point cloud data, the flatness of the second point cloud data is better, so the first vector and the normal vector are perpendicular or nearly perpendicular , it is determined that the flatness of the second point cloud data satisfies the first condition.
  • the second way is to determine whether the flatness of the second point cloud data satisfies the first condition, which may include: determining a plurality of sets of first vectors according to the second point cloud data, and there is a difference between each set of first vectors and the second vector. An included angle, if the average or weighted average of the multiple included angles is 90 degrees or close to 90 degrees, then it is determined that the flatness of the second point cloud data satisfies the first condition.
  • the part of the point cloud data selected from the second point cloud data may be point cloud data corresponding to a plurality of different emitted light beams in the second point cloud data.
  • M M is greater than 2
  • transmit beams are selected
  • there are corresponding M reflection points and the M reflection points can generate multiple different first vectors.
  • each first vector can be determined with the first vector
  • the angle between the two vectors get multiple angles, count the average or weighted average of the multiple angles, if the average or weighted average is 90 degrees or close to 90 degrees, then determine the second point cloud data.
  • the flatness satisfies the first condition.
  • S604 may be performed.
  • the flatness of the second point cloud data satisfies the first condition, it is not necessary to calibrate the external parameters of the vehicle-mounted radar.
  • the second point cloud data is the coordinates of the target plane object in the inertial coordinate system. If the flatness of the second point cloud data is good, it means that the second point cloud data obtained by using the current external parameters of the vehicle radar through a series of coordinate transformations is flat, which is more in line with the real situation, indicating that the current external parameters are relatively accurate of. If the flatness of the second point cloud data is poor, it means that the second point cloud data obtained through a series of coordinate transformations using the current external parameters is not flat and does not conform to the real situation (because the real situation is that the surface of the target plane object is flat ), indicating that the current external parameters are inaccurate, and the external parameters of the vehicle radar need to be calibrated. In this way, it can be accurately judged whether the current external parameters are accurate, that is, whether the external parameters of the vehicle-mounted radar need to be calibrated.
  • Embodiment 1 and Embodiment 2 provide two ways to determine whether to calibrate the external parameters of the vehicle-mounted radar. It is assumed that the method of the first embodiment is taken as the first method, and the method of the second embodiment is taken as the second method.
  • the vehicle may default to the first mode or default to the second mode.
  • the user can specify to use the first method or the second method, for example, a switch button is set on the vehicle, and the switch between the first method and the second method is realized by the switch button.
  • the vehicle can also determine whether to adopt the first method or the second method according to conditions (such as environmental conditions or speed conditions).
  • the third embodiment can be understood as a combination of the first embodiment and the second embodiment. Specifically, when it is determined that the external parameters of the vehicle-mounted radar are calibrated using the method of the first embodiment, the external parameters of the vehicle-mounted radar are calibrated. After the calibration is completed, the method of the second embodiment is used to determine whether the calibrated external parameters meet the conditions. If satisfied, adjust the calibrated external parameters.
  • FIG. 8 is another schematic flowchart of a method for calibrating external parameters of a vehicle-mounted radar according to an embodiment of the present application. As shown in Figure 8, the process includes:
  • the driving information includes at least one item of driving state information or driving road condition information.
  • S802 according to the driving information, determine to calibrate the external parameters of the vehicle-mounted radar.
  • S803 may be refined as: calibrating the external parameters of the vehicle-mounted radar according to the target reference. Because the external parameter includes at least one of a rotation angle or a translation distance of the radar coordinate system relative to the vehicle coordinate system. Therefore, S803 can be refined as: determining at least one of a rotation angle or a translation distance of the radar coordinate system relative to the vehicle coordinate system according to the target reference.
  • the rotation angle includes three attitude angles, namely pitch angle, roll angle and yaw angle.
  • different attitude angles may be determined according to different target reference objects. Specifically, the following two cases are included.
  • the first type of target reference refers to the ground on the road of the vehicle and the plane objects parallel to the ground.
  • determining the pitch angle and the roll angle according to the first type of target reference includes the following steps 1 to 4.
  • step 1 point cloud data 1 is obtained, and point cloud data 1 is the point cloud data corresponding to the first type of target reference in the radar coordinate system.
  • Step 2 Determine the first normal vector of the point cloud data 1.
  • Step 3 Determine the rotation matrix of the radar coordinate system relative to the vehicle coordinate system according to the first normal vector and the standard normal vector.
  • the vehicle-mounted radar detects the point cloud data 1 corresponding to the ground. Since the vehicle-mounted radar is offset from the vehicle coordinate system (or inertial coordinate system), the detected point on the ground corresponds to Cloud data 1 and the real ground are not necessarily on the same plane.
  • the normal vector of point cloud data 1 corresponding to the detected ground ie the first normal vector
  • the normal vector of the real ground ie the standard normal vector
  • the deviation between the first normal vector and the standard normal vector can reflect the rotation matrix of the radar coordinate system and the vehicle coordinate system. Therefore, the rotation matrix of the radar coordinate system and the vehicle coordinate system can be determined by the first normal vector and the standard normal vector.
  • the rotation matrix satisfies the following formula:
  • the rotation matrix R of the radar coordinate system relative to the vehicle coordinate system can be obtained by the above formula.
  • Step 4 according to the rotation matrix, determine the pitch angle and the roll angle.
  • pitch and roll angles are determined according to the following formulas:
  • R is the rotation matrix
  • the above step 4 can obtain not only the pitch angle and the roll angle, but also the yaw angle according to the rotation matrix R, but since the rotation matrix is based on the normal vector of the point cloud data 1 corresponding to the detected ground (that is, the first The deviation between the first normal vector and the normal vector of the real ground (ie the standard normal vector) is inferred, and the change of the yaw angle has no effect on the deviation between the first normal vector and the standard normal vector. The change of the sailing angle will not cause the first normal vector of the point cloud data 1 to change. Therefore, according to the deviation between the first normal vector of the point cloud data 1 corresponding to the detected ground and the standard normal vector of the real ground, it is inaccurate to obtain the yaw angle by reverse inference. Therefore, the following case (2) can be used to calibrate the yaw angle.
  • the second type of target reference is an object set along the driving road. See above for an introduction to the second category of target references.
  • determining the yaw angle includes the following steps 1 to 2.
  • An implementation method is, according to the street lamp, the process of determining the road direction of the driving road includes: acquiring point cloud data, and determining the street lamp 1 in the point cloud data.
  • Step 2 Determine the yaw angle of the vehicle-mounted radar according to C1.
  • yaw angle arctan(1/C1)
  • yaw angle 90-arctan(C1).
  • the vehicle calibrates the external parameters (such as three attitude angles) of the vehicle-mounted radar according to the target reference objects around the driving road.
  • calibrating the yaw angle based on street lights, signs, trees, etc. around the road helps to improve the accuracy of the calibrated yaw angle.
  • the above embodiment introduces the calibration process of the rotation angle, and the following describes the determination process of the translation distance.
  • the translation distance may be determined according to the first type of target reference.
  • the first type of target reference includes at least one of the ground of the driving road or a plane object parallel to the ground.
  • step 1 point cloud data 2 is determined, and point cloud data 2 corresponds to the first type of target reference in the radar coordinate system.
  • Step 2 according to the point cloud data 2, determine the ground fitting equation.
  • Step 3 Determine the translation distance according to the distance from the origin of the radar coordinate system to the ground fitting equation.
  • the calibration of the external parameters (rotation angle and/or translation distance) of the vehicle-mounted radar is completed. After the calibration of the external parameters is completed, it can be further judged whether the calibrated external parameters are accurate, and if not, the calibrated external parameters can be adjusted, which specifically includes the following steps S804 to S806.
  • the extrinsic parameter includes at least one of a rotation angle or a translation distance. Therefore, adjusting the external parameters can include adjusting the rotation angle, that is, the three attitude angles.
  • the manner of adjusting the rotation angle may include at least one of the following manners A to C.
  • Method A determine the objective function f, the objective function f is used to describe and the angle between. in, is the vector between two points in the second point cloud data (the first vector between point P and point Q as shown in Figure 7); is the normal vector of the second point cloud data (such as the second vector shown in Figure 7). Then, solve the optimal solution of this objective function.
  • the objective function in, and The independent variables in include three attitude angles, so the independent variables of the above formula include three attitude angles, so the objective function f can be expressed as f( ⁇ , ⁇ , ⁇ ).
  • the pitch angle is ⁇ (pitch)
  • the yaw angle is ⁇ (yaw)
  • the roll angle is ⁇ (roll).
  • the search range of the independent variables may include: for example, the pitch angle is in the interval [0, M0], the roll angle is in the interval [0, M1], and the yaw angle is in the interval [0, M1]. [0, M2] interval.
  • the specific values of M0, M1, and M2 are not limited in this embodiment of the present application.
  • the independent variable parameters that can make the objective function f be at [85 degrees, 95 degrees], and the independent variable parameters include the found accurate rotation angles (that is, the three attitude angles). ).
  • Method B determine the objective function f, the objective function f is used to describe and vertical relationship between them. in, is the vector between two points in the second point cloud data (the first vector between point P and point Q as shown in Figure 7); is the normal vector of the second point cloud data (such as the second vector shown in Figure 7). Then, solve the optimal solution of this objective function.
  • the objective function in, and The independent variables include three attitude angles, so f can be expressed as f( ⁇ , ⁇ , ⁇ ).
  • the search range of the independent variables may include: for example, the pitch angle is in the interval [0, M0], the roll angle is in the interval [0, M1], and the yaw angle is in the interval [0, M1]. [0, M2] interval.
  • the independent variable that makes the objective function f reach the minimum value is the exact rotation angle (ie, three attitude angles) found.
  • the objective function f is determined, and the objective function f is used to describe the projection distance of the second vector on the first vector (for example, the projection distance of the second vector on the first vector in FIG. 7 ).
  • the projection distance can be understood as the distance from the vertex of the second vector to the first vector.
  • the objective function f may also describe the distance from a point to a plane, where the plane refers to a plane fitted according to the second point cloud data, and the point is any point in the second point cloud data.
  • the objective function f satisfies the following formula:
  • p k and m k are two points in the second point cloud data.
  • ⁇ k is the normal vector of the fitted plane. If the flatness of the second point cloud data is good, the distance between each point in the second point cloud data and the fitted plane is small. Therefore, within the search range of the independent variable parameters (pitch angle, roll angle, yaw angle), find the extrinsic parameter value that makes the objective function f reach the minimum value.
  • the search range of the independent variables may include: for example, the pitch angle is in the interval [0, M0], the roll angle is in the interval [0, M1], and the yaw angle is in the interval [0, M1]. [0, M2] interval.
  • the independent variable that makes the objective function f reach the minimum value is the exact rotation angle (ie, three attitude angles) found.
  • the third embodiment not only can it be determined whether to calibrate the external parameters of the vehicle radar according to the driving information of the vehicle, but if it is determined to calibrate the external parameters of the vehicle radar, it can also be judged whether the calibrated external parameters meet the conditions. (ie S804 and S805), if not satisfied, adjust the calibrated external parameters to improve the accuracy of the external parameters.
  • FIG. 10 is a structural block diagram of a device 1000 for calibrating external parameters of a vehicle-mounted radar according to an embodiment of the present application.
  • the external parameter calibration device 1000 of the vehicle-mounted radar includes: an acquisition unit 1001 and a processing unit 1002 .
  • the obtaining unit 1001 is configured to obtain the driving information of the vehicle, where the driving information includes at least one of driving state information or driving road condition information; wherein the driving state information includes speed, acceleration, yaw angle or at least one of yaw angular velocity; the driving road condition information is used to indicate at least one of the driving road of the vehicle or the objects around the driving road;
  • the processing unit 1002 is configured to determine, according to the driving information
  • the vehicle-mounted radar is calibrated with external parameters.
  • the acquiring unit 1001 and the processing unit 1002 may be processors, such as application processors or baseband processors, and the processors may include one or more central processing units (CPUs).
  • processors such as application processors or baseband processors
  • processors may include one or more central processing units (CPUs).
  • the external parameter calibration device 1000 of the vehicle-mounted radar may be a vehicle or a vehicle-mounted device, or a processing module or a chip system in a vehicle or a vehicle-mounted device, such as a vehicle-mounted processor or an electronic control unit (ECU).
  • a vehicle-mounted processor or an electronic control unit (ECU).
  • ECU electronice control unit
  • the external parameter calibration apparatus 1000 of the vehicle-mounted radar may also be a processing module (such as a processor) in the vehicle-mounted radar.
  • a processing module such as a processor
  • the external parameter calibration apparatus 1000 of the vehicle-mounted radar may further include a communication unit.
  • the communication unit may include a receiving unit and a transmitting unit.
  • the processing unit 1002 is specifically configured to: determine to perform external parameter calibration on the vehicle radar when at least one of the following conditions is satisfied according to the driving state information, wherein the conditions include:
  • the speed is less than a first threshold
  • the vehicle is traveling at an average speed
  • the acceleration is less than a second threshold
  • the yaw angle is within a preset range
  • the yaw angle speed is less than a third threshold.
  • the processing unit 1002 is specifically configured to: according to the driving road condition information, determine that the driving road is a straight road and/or when there is a target reference object around the driving road, determine whether the driving road is a straight road.
  • the vehicle radar performs external parameter calibration.
  • the external parameter includes at least one of a rotation angle or a translation distance of the vehicle-mounted radar; the processing unit 1002 is further configured to: determine, according to the target reference around the driving road, At least one of the rotation angle or the translation distance of the vehicle radar.
  • the processing unit 1002 when used to determine the rotation angle of the vehicle radar according to the target reference around the driving road, it is specifically used for: according to the ground of the driving road Or a plane object parallel to the ground, determine the pitch angle and roll angle of the vehicle-mounted radar; determine the yaw angle of the vehicle-mounted radar according to the objects arranged along the driving road.
  • the objects disposed along the travel road include: first type objects disposed along the travel road and parallel to the ground of the travel road, and/or along the travel road The second type of object on the driving road and perpendicular to the ground of the driving road; wherein, the first type of object includes: at least one of a road edge, a guardrail, a green belt or a lane line; the second type of object Type objects include: at least one of trees, signs, or street lights.
  • the acquisition unit 1001 is further configured to: acquire external parameters of the vehicle-mounted radar;
  • the processing unit 1002 is further configured to: use the external parameter to convert the first point cloud data corresponding to the target plane object around the driving road in the vehicle radar coordinate system into the second point cloud data in the inertial coordinate system; If the flatness of the second point cloud data does not meet the first condition, adjust the external parameter.
  • the flatness of the second point cloud data does not satisfy the first condition, including: any two reflection points of different transmit beams in the second point cloud data on the target plane object
  • the first vector between is not perpendicular to the normal vector of the point cloud data corresponding to any one or more transmit beams in the second point cloud data; or, any two different transmit beams in the second point cloud data are in the
  • the included angle between the first vector between the reflection points on the target plane object and the normal vector of the point cloud data corresponding to any one or more transmit beams in the second point cloud data is not within a preset range.
  • the processing unit 1002 when adjusting the external parameters, is specifically configured to: generate an objective function based on the external parameters, where the objective function is used to describe the first vector and the The angle between the normal vectors, or the objective function is used to describe the projection distance of the normal vector on the first vector; within the preset external parameter adjustment range, find the objective function to reach the minimum value of external parameters.
  • the division of units in the embodiments of the present application is schematic, and is only a logical function division. In actual implementation, there may be other division methods.
  • the functional units in the various embodiments of the present application may be integrated into one processing unit. In the device, it can also exist physically alone, or two or more units can be integrated into one unit.
  • the above-mentioned integrated units may be implemented in the form of hardware, or may be implemented in the form of software functional units.
  • the software or firmware includes, but is not limited to, computer program instructions or code, and can be executed by a hardware processor.
  • the hardware includes, but is not limited to, various types of integrated circuits, such as central processing units (CPUs), digital signal processors (DSPs), field programmable gate arrays (FPGAs), or application specific integrated circuits (ASICs).
  • FIG. 11 is a structural block diagram of an external parameter calibration apparatus 1100 of a vehicle-mounted radar provided by an embodiment of the present application.
  • the external parameter calibration apparatus 1100 of the vehicle-mounted radar shown in FIG. 11 includes at least one processor 1101 .
  • the external parameter calibration device 1100 of the vehicle-mounted radar further includes at least one memory 1102 for storing program instructions and/or data. Memory 1102 and processor 1101 are coupled.
  • the coupling in the embodiments of the present application is an indirect coupling or communication connection between devices, units or modules, which may be in electrical, mechanical or other forms, and is used for information exchange between devices, units or modules.
  • the processor 1101 may cooperate with the memory 1102 , the processor 1101 may execute program instructions stored in the memory 1102 , and at least one of the at least one memory 1102 may be included in the processor 1101 .
  • the external parameter calibration device 1100 of the vehicle radar may also include an interface circuit (not shown in the figure), the processor 1101 is coupled with the memory 1102 through the interface circuit, and the processor 1101 can execute the program code in the memory 1102 to achieve The external parameter calibration method of the vehicle-mounted radar provided by the embodiment of the present application.
  • the external parameter calibration apparatus 1100 for vehicle radar may further include a communication interface 1103 for communicating with other devices through a transmission medium, so that the external parameter calibration apparatus 1100 for vehicle radar may communicate with other devices.
  • the communication interface may be a transceiver, a circuit, a bus, a module, or other types of communication interfaces.
  • the transceiver when the communication interface is a transceiver, the transceiver may include an independent receiver and an independent transmitter; a transceiver with integrated transceiver functions, or an interface circuit, etc. may also be included.
  • connection medium between the above-mentioned processor 1101 , the memory 1102 , and the communication interface 1103 is not limited in the embodiments of the present application.
  • the memory 1102, the processor 1101, and the communication interface 1103 are connected through a communication bus 1104 in FIG. 11.
  • the bus is represented by a thick line in FIG. 11, and the connection between other components is only a schematic illustration. , not as a limitation.
  • the bus may include an address bus, a data bus, a control bus, and the like. For convenience of presentation, only one thick line is used in FIG. 11 , but it does not mean that there is only one bus or one type of bus or the like.
  • the device when the computer instructions in the memory 1102 are executed by the processor 1101, the device is caused to execute: acquiring the driving information of the vehicle, where the driving information includes at least one of driving state information or driving road condition information; wherein, The driving state information includes at least one of speed, acceleration, yaw angle or yaw angular velocity; the driving road condition information is used to indicate at least one of a driving road of the vehicle or objects around the driving road; According to the driving information, it is determined to perform external parameter calibration on the vehicle-mounted radar.
  • the present application provides a computer-readable storage medium, including computer instructions, when the computer instructions are executed by a processor, the external parameter calibration device of the vehicle-mounted radar can perform the external parameter calibration of the vehicle-mounted radar described in the embodiments of the present application. parameter calibration method.
  • the present application provides a computer program product, the computer program product includes a computer program, when the computer program product runs on a processor, the external parameter calibration device of the vehicle-mounted radar is made to execute the method described in the embodiments of the present application. External parameter calibration method of vehicle radar.
  • the processor may be a general-purpose processor, a digital signal processor, an application-specific integrated circuit, a field programmable gate array or other programmable logic device, a discrete gate or transistor logic device, or a discrete hardware component, which can implement or
  • a general purpose processor may be a microprocessor or any conventional processor or the like.
  • the steps of the methods disclosed in conjunction with the embodiments of the present application may be directly embodied as executed by a hardware processor, or executed by a combination of hardware and software modules in the processor.
  • the memory may be a non-volatile memory, such as a hard disk drive (HDD) or a solid-state drive (SSD), etc., or may also be a volatile memory (volatile memory), for example Random-access memory (RAM).
  • Memory is any other medium that can be used to carry or store desired program code in the form of instructions or data structures and that can be accessed by a computer, but is not limited thereto.
  • the memory in this embodiment of the present application may also be a circuit or any other device capable of implementing a storage function, for storing program instructions and/or data.
  • “at least one” refers to one or more, and “multiple” refers to two or more.
  • “And/or”, which describes the relationship of the associated objects, indicates that there can be three kinds of relationships, for example, A and/or B, it can indicate that A exists alone, A and B exist at the same time, and B exists alone, where A, B can be singular or plural.
  • the character “/” generally indicates that the associated objects are an “or” relationship.
  • At least one item(s) below” or similar expressions thereof refer to any combination of these items, including any combination of single item(s) or plural items(s).
  • At least one (a) of a, b, or c can represent: a, b, c, a and b, a and c, b and c, or a and b and c, where a, b, c can be single or multiple.
  • the methods provided in the embodiments of the present application may be implemented in whole or in part by software, hardware, firmware, or any combination thereof.
  • software When implemented in software, it can be implemented in whole or in part in the form of a computer program product.
  • the computer program product includes one or more computer instructions. When the computer program instructions are loaded and executed on a computer, all or part of the processes or functions described in the embodiments of the present invention are generated.
  • the computer may be a general purpose computer, a special purpose computer, a computer network, network equipment, user equipment, or other programmable apparatus.
  • the computer instructions may be stored in or transmitted from one computer readable storage medium to another computer readable storage medium, for example, the computer instructions may be downloaded from a website site, computer, server or data center Transmission to another website site, computer, server or data center by means of wired (such as coaxial cable, optical fiber, digital subscriber line, DSL for short) or wireless (such as infrared, wireless, microwave, etc.)
  • a computer-readable storage medium can be any available medium that can be accessed by a computer or a data storage device such as a server, data center, etc. that contains an integration of one or more available media.
  • the available media can be magnetic media (eg, floppy disks, hard disks, magnetic tape), optical media (eg, digital video disc (DVD) for short), or semiconductor media (eg, SSD), and the like.

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  • Engineering & Computer Science (AREA)
  • Radar, Positioning & Navigation (AREA)
  • Remote Sensing (AREA)
  • Physics & Mathematics (AREA)
  • Computer Networks & Wireless Communication (AREA)
  • General Physics & Mathematics (AREA)
  • Electromagnetism (AREA)
  • Radar Systems Or Details Thereof (AREA)
  • Traffic Control Systems (AREA)

Abstract

La présente invention concerne un procédé et un appareil d'étalonnage de paramètre externe pour un radar monté sur véhicule, appliqué à la conduite autonome ou à la conduite assistée. Le procédé comprend les étapes consistant à : acquérir des informations de déplacement d'un véhicule, les informations de déplacement comprenant des informations d'état de déplacement et/ou des informations de condition de route de déplacement, les informations d'état de déplacement comprenant au moins un élément parmi la vitesse, l'accélération, l'angle de lacet ou la vitesse en lacet, et les informations de condition de route de déplacement servant à indiquer au moins un élément parmi une route de déplacement du véhicule ou des objets autour de la route de déplacement ; et effectuer un étalonnage de paramètre externe sur le radar monté sur véhicule en fonction des informations de déplacement. De cette manière, l'étalonnage de paramètre externe pour le radar monté sur véhicule peut être achevé pendant le processus de déplacement du véhicule, il n'est pas nécessaire de retourner à l'usine pour effectuer un étalonnage et, par conséquent, l'efficacité est élevée. En outre, le procédé peut être appliqué à l'Internet des Véhicules, tels que le véhicule à tout (V2X), le véhicule d'évolution à long terme (LTE-V) et le véhicule à véhicule (V2V).
PCT/CN2022/082560 2021-03-31 2022-03-23 Procédé et appareil d'étalonnage de paramètre externe pour radar monté sur véhicule WO2022206519A1 (fr)

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CN116381632B (zh) * 2023-06-05 2023-08-18 南京隼眼电子科技有限公司 雷达横滚角的自标定方法、装置及存储介质
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CN116499498B (zh) * 2023-06-28 2023-08-22 北京斯年智驾科技有限公司 一种车辆定位设备的标定方法、装置及电子设备
CN118351176A (zh) * 2024-06-17 2024-07-16 武汉未来幻影科技有限公司 一种相机与毫米波雷达外参半自动标定方法及其相关设备
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