Method and control unit for operating an autonomous vehicle

Abstract

Electronic control unit configured to: Received, from an environment sensor (20), measured locations (x s,i ) and measured apparent velocities (v1,v2) of several Doppler simulators (DS1 to DS10) and providing a list [[x s,1 , v1], [x s,2 , v2], [x s,2 , v2], ..., [x s,N , v N ]] of all measured apparent locations (x s,i ) and their corresponding measured apparent velocities (v i ); Retrieve predefined locations (x w,i ) and given apparent velocities (v1',v2') of the Doppler simulators (DS1 to DS10) in the form of a look-up list [[x w,1 , v1'], [x w,2 '],v2'], [x w,3 , v3'], ..., [x w,N , v N ']]; and Determining a misadjustment (ϕ0, θ o ) of the environment sensor (20) from the received locations (x w,i ), the measured locations (x s,i), the measured apparent speeds (v1,v2) and the received apparent speeds (v1',v2'), wherein the control unit is configured to determine the measured locations (x s,i ) the specified locations (x w,i ) according to an assignment list [x s,1 , x w,2 ], [x s,2 , x w,1 ], [x s,2 , x w,5 ], ... [x s , N , x w,N ]].

Description

TECHNICAL FIELDThe present disclosure relates to the field of driver assistance systems or autonomous or semi-autonomous vehicles, in particular a sensor for detecting the environment in a vehicle, and also a method for calibrating the sensor and a control unit for carrying out this method.BACKGROUND ARTSensors for detecting the environment are important for the correct functioning of driver assistance systems such as lane keeping assistants, cruise control systems, brake assistants, blind spot monitoring systems or automatic distance warning systems. Systems for autonomous driving also require correctly functioning sensors for detecting the environment.One problem of the known sensors is the possibly difficult to avoid misalignment of a sensor in the azimuth and elevation direction, which falsifys the environment detection.US 2016 / 0320476 A1 discloses a calibration of a measurement system comprising camera and radar for tracking moving sports objects.OBJECT OF THE INVENTIONProceeding from this, the object of the invention is to provide an electronic device and a method for a sensor architecture, with which the behavior of the radar sensor architecture is optimized.This object is achieved by the electronic control unit according to claim 1. Further advantageous embodiments of the invention are evident from the dependent claims and the following description of preferred exemplary embodiments of the present invention.The exemplary embodiments show an electronic control unit configured to receive, from a surroundings sensor, measured locations and measured apparent speeds of a plurality of Doppler simulators, to retrieve predefined locations and predefined apparent speeds of the Doppler simulators; and to ascertain a maladjustment of the surroundings sensors from the received locations, the measured locations, the measured apparent speeds and the received apparent speeds.Doppler simulators are devices known to the person skilled in the art, which are capable of simulating a moving object at an adjustable speed by means of artificial Doppler displacement to a radar or lidar sensor. A radar or lidar sensor does not recognize the actual speed of the Doppler simulator, but rather the apparent speed simulated by it.The electronic control unit can be used, for example, in a vehicle. The vehicle may be, for example, a vehicle. It can be, for example, a motor vehicle, a land vehicle, air vehicle or watercraft, for example a keyless transport system (FTS), an autonomous passenger car, a rail vehicle, a drone or a boat.The electronic control unit has, for example, a processor which is designed to carry out the functions described here. The processor can be, for example, a computing unit such as a central processing unit (CPU=central processing unit) which executes program instructions.The electronic control unit can be used, for example, to use the determined incorrect setting for calibrating the environment sensors. In this way, measurement errors of the environment sensors due to the malposition can be avoided.The retrieval of predetermined position data of the reflectors can be effected, for example, by reading the predetermined position data from a memory. The position data can be supplied to the electronic device, for example, by being input via a user interface or a network interface. The position data described are calibration data which are determined by means of other position determination methods, that is to say not with the environment sensor to be calibrated.According to the invention, the electronic control unit is further configured to assign the measured locations to the predetermined locations based on the measured apparent speeds and the received apparent speeds.Since the control unit according to the invention assigns the measured locations to the predetermined locations, it enables "labeling" of the targets and enables correct assignment of the observed targets to the known positions. This ensures correct separation of the Doppler simulator targets from the environment. According to embodiments of this invention, Doppler simulators are used as targets, and the adjustable speed of a particular target may be used as a "label" to uniquely identify the target.Preferably, the electronic control unit is further configured to associate a measured location with the predetermined location whose predetermined apparent velocity is most similar to the measured apparent velocity.The electronic control unit is preferably further configured to ascertain relative coordinates measured from at least three of the measured locations of the reflectors and to ascertain the incorrect setting of the environment sensor from the measured relative coordinates of the measured locations, and / or to ascertain predefined relative coordinates from at least two of the predefined position data of the reflectors and to ascertain the incorrect setting of the environment sensor from the predefined relative coordinates of the predefined position data. By using relative coordinates, a dependence on the position of the sensor or of the vehicle can be avoided.According to one specific embodiment, the electronic control unit is also configured to ascertain a rotation matrix from the specific locations and the predefined locations, the rotation matrix describing the incorrect setting of the surroundings sensors.The electronic control unit is preferably further configured to calculate a maladjustment of the environment sensor in the azimuthal direction and / or a maladjustment in the elevation direction.According to an embodiment, the electronic control unit is further configured to solve a system of equations, wherein for a plurality of pairs of the reflectors, the measured relative coordinates and the predetermined relative coordinates are respectively related via the rotation matrix in order to establish the system of equations. The equation system is solved in particular in order to calculate the entries of the rotation matrix. To solve the equation system, it is possible, for example, to use the Gaussian elimination method, matrix inversion or finite termination of the Neumann series. By solving the equation system, the malposition of the environment sensor can be calculated.Preferably, the equation system is based on at least three pairs of the reflectors. In this manner, nine independent pairs of reflectors can be selected to re-establish equations from which the equation system is formed.The exemplary embodiments also show a method comprising receiving, from a surroundings sensor, measured locations and measured apparent speeds of a plurality of Doppler simulators, retrieving predefined locations and predefined apparent speeds of the Doppler simulators, and ascertaining a maladjustment of the surroundings sensor from the received locations, the measured apparent speeds and the received apparent speeds.BRIEF DESCRIPTIONS OF THE FIGURESEmbodiments will now be described by way of example and with reference to the accompanying drawings, in which: FIG. 1 is a block diagram schematically illustrating configuration of a vehicle according to an exemplary embodiment of the present invention, FIG. 2 is a block diagram showing an exemplary configuration of a control unit inside a vehicle, FIG. 3 shows a typical driving situation of an autonomously driving vehicle, FIG. 4 shows an exemplary construction for a calibration method according to the present invention. FIG. 5 is an enlarged view of the structure shown in FIG. 4. FIG. 6 shows the assignment of the measured locations to the known locations based on the measured apparent speeds of the Doppler simulators. FIG. 7 is a flow chart schematically illustrating the calibration method shown in FIGS. 4, 5 and 6.We propose an algorithm for determining the orientation and installation position of a radar sensor with respect to an absolute coordinate system connected to a fixed point in the vehicle in which the sensor is mounted. The algorithm uses equipment available on the market simulating moving targets, the radar being able to measure accurately the position and speed of said targets. The method uses several such targets, each assigned a unique speed that can be used as a marker in the recognition and mapping. The orientation and position of the sensor is determined by comparing the detected targets with the already known positions.The method according to the invention is now described below with reference to a detailed description of the individual figures: FIG. 1 is a block diagram schematically illustrating configuration of a vehicle 1 with an autonomous or semi-autonomous driving control unit according to an exemplary embodiment of the present invention. The vehicle 1 includes a plurality of electronic components connected to each other via a vehicle communication network 19. The vehicle communication network 19 may be, for example, a standard vehicle communication network installed in the vehicle, such as a CAN bus (controller area network), a LIN bus (local interconnect network), a LAN bus (local area network), a MOST bus and / or a FlexRay bus (registered trade mark) or the like.In the example illustrated in FIG. 1, the vehicle 1 includes a control unit 12 (ECU 1). This control unit 12 controls a steering system. The steering system refers to the components that enable directional control of the vehicle.The vehicle 1 further includes a control unit 14 (ECU 2) that controls a brake system. The brake system relates to the components that enable braking of the vehicle.The vehicle 1 further includes a control unit 16 (ECU 3) that controls a powertrain. The drive train relates to the drive components of the vehicle. The drive train may include a motor, a transmission, a drive / propeller shaft, a differential, and a final drive.The vehicle 1 further comprises one or more environment sensors 20 which are designed to sense the environment of the vehicle 1, wherein the environment sensors 20 are mounted on the vehicle 1 and, if appropriate, sense objects or states in the environment of the vehicle independently, i.e. without information signals from the outside. These include in particular cameras, radar sensors, lidar sensors, ultrasonic sensors or the like. The environment sensors 20 may be disposed inside the vehicle or outside the vehicle (e.g., on the outside of the vehicle). For example, a camera may be installed in a front region of the vehicle 1 for capturing images of a region located in front of the vehicle.Vehicle sensor system of autonomous vehicle 1 also includes a satellite navigation unit 24 (GPS unit). It should be noted that in the context of the present invention, GPS is exemplary of all global navigation satellite systems (GNSS), such as GPS, A-GPS, Galileo, GLONASS (Russia), compass (China), IRNSS (India), and the like.The vehicle 1 further includes an autonomous driving control unit 18 (ECU 4). The autonomous driving control unit 18 is configured to control the vehicle 1 to act wholly or partly without influence of a human driver in road traffic. The control unit 18 (ECU 4) is configured to evaluate information of the environment sensor system 20 or to control the environment sensor system. When an autonomous driving operation state is activated on the control side or on the driver side, the autonomous driving control unit 18 determines parameters for the autonomous driving of the vehicle (for example, target speed, target torque, distance to the preceding vehicle, distance to the edge of the road, steering operation and the like) based on available data over a predetermined travel distance, environmental data recorded by the environmental sensors 20, and vehicle operation parameters detected by the vehicle sensors and supplied to the control unit 18 from the control units 12, 14 and 16.For example, for adaptive cruise control (ACC), the control unit for autonomous driving 18 can measure the position and the speed of the vehicle driving ahead via the environment sensors 20 and adjust the speed of the vehicle and the distance to the vehicle driving ahead accordingly via driving and braking intervention.The vehicle 1 further includes a user interface 26 (HMI=human machine interface) that allows a vehicle occupant to interact with one or more vehicle systems. This user interface 26 may include an electronic display (e.g., a GUI=graphic user interface) for outputting graphics, icons, and / or content in text form, and an input interface for receiving input (e.g., manual input, voice input, and input through gestures, head or eye movements). The input interface may include, for example, keyboards, switches, touch screens (touch screen), eye trackers, and the like.FIG. 2 is a block diagram illustrating an example configuration of an autonomous driving control unit 18 (ECU 4). The autonomous driving control unit 18 may be, for example, an electronic control unit (ECU or electronic control module ECM). The autonomous driving control unit 18 (ECU 4) includes a processor 40. the processor 40 may be, for example, a computing unit such as a central processing unit (CPU=central processing unit) that executes program instructions.The processor of the autonomous driving control unit 18 is designed to calculate an optimum driving position (following distance, lateral offset) taking into account the permissible lane region, on the basis of a planned driving maneuver, based on the information of the sensor-based environmental model. The calculated optimal driving position is used for controlling actuators of the vehicle subsystems 12, 14 and 16, for example brake, drive and / or steering actuators.The autonomous driving control unit 18 further includes a memory and an input / output interface. The memory may be one or more non-transitory computer readable media and includes at least a program storage area and a data storage area. The program storage area and the data storage area may include combinations of various types of memory, for example, read only memory 43 (ROM=read only memory) and random access memory 42 (RAM=random access memory) (e.g., dynamic RAM ("DRAM"), synchronous DRAM ("SDRAM"), etc.). Further, the autonomous driving control unit 18 may include an external storage drive 44 such as an external hard disk drive (HDD), a flash memory drive, or a nonvolatile solid state drive (SSD).The autonomous driving control unit 18 further comprises a communication interface 45 via which the control unit can communicate with the vehicle communication network ( 19 in FIG. 1 ), for example in order to obtain data from the environment sensors ( 20 in FIG. 1 ).FIG. 3 shows a typical driving situation of an autonomous or else partially autonomous driving vehicle. An autonomous or semi-autonomous driving vehicle 1 is driving in the right lane 4 of a road 5. the autonomous vehicle 1 comprises an autonomous driving control unit ( 18 in FIG. 1 ) which determines parameters for the autonomous operation of the vehicle (for example, setpoint speed, setpoint torque, distance from the preceding vehicle, distance from the edge of the road, steering operation and the like) on the basis of available data over a predefined travel distance, environmental data recorded by environmental sensors 20, and vehicle operating parameters which are detected by means of the vehicle sensors and are fed to the control unit 18 from the control units 12, 14 and 16. As can be seen from FIG. 3, the autonomous vehicle 1 drives behind a preceding vehicle, in this case a truck 2, which covers a region 10 of the detection region 8 of the environment sensors ( 20 in FIG. 1 ) of the vehicle 1, in this case in particular a front camera. The control unit for autonomous driving ( 18 in FIG. 1 ) of the vehicle 1 comprises a processor which is designed to calculate an optimum driving position, taking into account the permissible lane region, on the basis of a planned driving maneuver, on the basis of information from a sensor-based environmental model, a region to be detected being covered in the best possible manner by said permissible lane region with the installed environmental sensors ( 20 in FIG. 1 ).FIG. 4 schematically shows the principle of a calibration method according to the present invention. The method is used to calibrate a surroundings sensor system 20 of a vehicle 1. The principle of the calibration method is illustrated in two dimensions, here x and y, for simplifying the illustration, so that FIG. 4 corresponds to a plan view. The principle can likewise also be applied in three dimensions (x, y, z). By way of example, the environment sensor system is a radar sensor, or a lidar sensor. The calibration method is based on an absolute coordinate system KS (environment coordinate system). For the calibration, ten Doppler simulators DS1-DS10, the positions of which are known in the absolute coordinate system KS, are provided by way of example.Doppler simulators are devices known to the person skilled in the art, which are capable of simulating a moving object at an adjustable speed by means of artificial Doppler displacement to a radar or lidar sensor. A radar or lidar sensor does not recognize the actual speed of the Doppler simulator, but rather the apparent speed simulated by it.In the present method, each of the ten Doppler simulators DS1-DS10 is preset to have its own apparent speed which is easily distinguishable from the other apparent speeds, for example 10 km / h for Doppler simulator DS1, 20 km / h for Doppler simulator DS2, etc. Furthermore, the apparent speed assigned to one Doppler simulator DS1-DS10 can be considered as known in the art. The apparent speeds and their assignment to the Doppler simulators DS1-DS10 can be stored, for example, in a memory of the control unit 18 (ECU 4 in FIG. 1 ) as a look-up table. The control unit 18 can thus retrieve this assignment at any time.In order to calibrate the environment sensor system 20 according to the method according to the invention, the vehicle 1 is positioned at any desired position of the absolute coordinate system KS, wherein the environment sensor system 20 can see the ten placed Doppler simulators DS1-DS10 from the position of the vehicle 1.FIG. 5 shows a section of the structure shown in FIG. 4, which, for the sake of simplifying the illustration, comprises only the Doppler simulators DS 1 and DS 2. The representation can be extended accordingly to the case of ten Doppler simulators DS 1 to DS 10, which is assumed here by way of example. In order to calibrate the environment sensor system 20 according to the method according to the invention, the vehicle 1, as already mentioned above, is placed at any point in the absolute coordinate system KS, so that the ego vehicle or the environment sensor system 20 is located at the point p s from which the environment sensor system 20 can see ten Doppler simulators DS 1 to DS 10 (only DS 1 and DS 2 shown here). The absolute positions x w,1 to x w,10 of the Doppler simulators DS 1 to DS 10 in the absolute coordinate system KS are assumed to be known in the calibration phase, i.e. they have been determined by means of external means and they are supplied to the process as predetermined known parameters, for example entered via the user interface ( 26 in FIG. 1 ).The environment sensor system 20 now determines the relative positions x s,1 to x s,10 of the Doppler simulators DS 1 to DS 10 in the relative coordinate system of the sensor. As shown in FIG. 5, these position determinations are subject to errors, since the sensor system 20 can have a production-related incorrect setting, here, for example, an angular error φ 0 in the azimuthal direction. For this reason, the relative location x s,1 of the Doppler simulator R1 is deviated from its true relative location x' s,1. The off-setting φ0in azimuthal direction is here assumed to be a systematic error of the measurement and is consequently the same for all measurements. The same applies to the other Doppler simulators. In addition to the location of the Doppler simulators, these also present to the sensor system 20 a apparent velocity v 1 to v 10( here only v 1 and v 2 shown), which is different and known for each of the Doppler simulators. In the following, it is therefore possible to identify each of the Doppler simulators unambiguously on the basis of the measured apparent speeds v i. The assignment of which Doppler simulator has which apparent speed must likewise be fed to the method as an external parameter, for example via the user interface ( 26 in FIG. 1 ).FIG. 6 ashows measured locations and known (predefined) locations of Doppler simulators as they are processed by the control unit according to the invention. FIG. 6a shows as squares the true locations of the Doppler simulators DS1 and DS2 in the absolute coordinate system (shown as in FIG. 5 by the x and y axes) which are known and thus predetermined. Furthermore, FIG. 6 ashows, as circles, the apparent locations SP 1 and SP 2 of the two Doppler simulators, as measured by the sensor system S 1 installed on the vehicle F 1. These false locations SP 1 and SP 2 arise due to the production-related, systematic measurement error of the sensor system S 1. The double arrows in FIG. 6 a show that each apparent location SP 1 and SP 2 is assigned to a true location of the Doppler simulators DS 1 and DS 2, i.e. that each apparent location SP 1 and SP 2 is based on one of the Doppler simulators DS 1 and DS 2. Thus, in the example of FIG. 6 a, the apparent location SP 1 returns to the Doppler simulator DS 1 and the apparent location SP 2 returns to the Doppler simulator DS 2.The aim of the method according to the invention is to find a correction such that the true location (square) determined by an external method and the apparent location (circle) are located one above the other. Each measured apparent position (circle) is assigned the correct true location (square). Even if the production-related error is large, the method according to the invention can, for example, decide whether the apparent location SP 1 belongs to the true location of the Doppler simulator DS 1 or to the true location of the Doppler simulator DS 2. This avoids erroneous assignments which would lead to an erroneous correction when determining a correction matrix, as described in more detail below, and could thus render the result of the correction method unusable.FIG. 6 bshows an assignment of the measured locations to the known locations based on the measured apparent speeds of the Doppler simulators, as determined by the control unit according to the invention. For this purpose, in addition to the location of the Doppler simulators DS1 and DS2, their respective apparent speeds v 1 and v 2 are also determined. Since it is now known in advance which of the Doppler simulators DS1 and DS2 simulates which of the apparent speeds v 1 and v 2 respectively, it can now be decided whether the apparent location SP1 is to be assigned to the known true location of the Doppler simulator DS1 or to the known true location of the Doppler simulator DS2. Since the first measured apparent location SP 1 appears to move at the apparent speed v 1 and the second measured apparent location SP 2 appears to move at the apparent speed v 2 the apparent location SP 1 can be assigned to the Doppler simulator DS 1 and its known location x s,1' as is illustrated in FIG. 6 b by the dotted pattern, and the apparent location SP 2 can be assigned to the Doppler simulator DS 2 and its known location x s,2' as is illustrated in FIG. 6 b by the dashed pattern.An assignment according to the invention of the measured locations (apparent locations) to the known true locations of the Doppler simulators can be achieved, for example, as described below.First, locations x s,i and their velocity v i of the Doppler simulators are measured by the radar / lidar sensor (S 1 in FIGS. 6 a, b) that appear as objects of sensor detection. The index i here denotes a running variable which runs over all measured Doppler simulators. Since the location measurements are erroneous and the Doppler simulators only specify to be a moving object, as has been described in more detail above, these locations x s,i and speeds v i are apparent locations and apparent speeds, respectively, and are therefore referred to below as apparent locations x s,i and apparent speeds v i respectively. According to the invention, the measurement process provides a list of all measured apparent locations x s,i and their associated measured apparent speeds v i: where N denotes the total number of Doppler simulators.The true locations x w,j in the absolute coordinate system (KS see FIG. 5 ) and associated apparent speeds v j' of the Doppler simulators are known in advance and are taken according to the invention from a look-up list. The index j here denotes a running variable which in turn runs over the set of all Doppler simulators, wherein N denotes the total number of Doppler simulators.In order to assign the measured apparent locations x s,i of the Doppler simulators to the stored true locations x w,j of the Doppler simulators, the measured apparent speeds v i are now compared with the stored apparent speeds v j'. The comparison results in a unique assignment list which, according to the invention, has the following form and which assigns the measured false locations x s,i to the stored true locations x w,j.In the ideal case, the sensor S 1 can ideally determine the apparent speeds v i simulated by the Doppler simulators, so that they exactly correspond to the stored apparent speeds v j' so that the assignment can be realized by a trivial comparison of the speeds. In reality, however, measurement errors will occur, so that measured and stored speeds do not exactly match. In this case, pairs of speeds are sought for which values of the measured and of the stored apparent speeds coincide best. It is therefore true to find pairs (k and l describe here fixed indices) for which the following applies:Speed pairs are thus sought whose difference is minimal compared to all other conceivable pairs. In this way, each measured location x s,k can now be assigned a known location x w,l for which the apparent speeds preset in the Doppler simulators are selected, in view of the very high speed resolution of the radar sensor, as described above, such that measurement errors do not play any role in the speed measurement.The true locations x w,j in the absolute coordinate system (KS in FIG. 5 ) are known and can be converted into the coordinate system of the sensor S 1 with the aid of the position vector (see FIG. 5 ), according toIn the following, an algorithm based on the above-described FIGS. 5 and 6 bwill be described algorithmically as to how the sensor error can be determined in the form of a rotation matrix R with the aid of the uniquely assigned pairs of true and measured locations (x s,k, x w,l). For this purpose, the pairs of measured and true locations associated with one another are indexed together.Hereinafter, x s,i, × s,i' and x w,i denote the measured location of the i-th Doppler simulator, the corresponding true location in the sensor coordinate system, and the true location in the absolute coordinate system (KS in FIG. 5 ), respectively, as correctly assigned to each other as described above.After the relative locations of all Doppler simulators x s,i have been determined and, based on their apparent velocity v i have been assigned to the known locations x w,i the measurement error of the sensor system 20 is to be determined. As shown in FIG. 5, this error results in an angular measurement error in the azimuthal direction φ 0.To this error in azimuthal direction φ 0 shown in FIG. 5, an error θ 0 in elevation direction optionally also adds in three dimensions, which error is not depicted in FIG. 5, but is also taken into account in the following algorithm representation.As can be seen from FIG. 5, the geometric equation appliesThe incorrect setting of environment sensor system 20 can be described by a 3x3 rotation matrix R, which depends on the incorrect settings in azimuth direction φ 0 and in elevation direction θ 0 which are used here to parameterize rotation matrix R (see "Euler angle"):The following results when used in equation (1):This results in a change-over for the relative positionIn order to achieve independence from the location p s of the vehicle, p s is eliminated from the equation. This is achieved by using relative coordinates. By way of example, all relative coordinates relative to the location of the first Doppler simulator (x s,1 or x w,1) are determined here:For simplicity we can write:Now a 3x3 matrix M can be defined:Numerically, this matrix M can be decomposed into its singular value decomposition UΣV T :From this singular value decomposition, the sought rotation matrix R can be calculated:In the case of exactly three Doppler simulators and taking into account the fact that the location of the first Doppler simulator has already been used for determining the relative coordinates x̅ s,1= x̅ w,1= 0 ( see equation (5)), only the two remaining Doppler simulators i,j ∈ {2,3}. remain for constructing the matrix M ij= ( x̅ s,i x̅ s,j). Since i≠jmust apply for the determination of the rotation matrix, in this case exactly one possible matrix M ij, namely: is obtained from three Doppler simulators.In the case of more than three Doppler simulators, there results combinatorially a number of possible matrices M ij, from which a corresponding number of possible rotation matrices R ij can then be calculated. In this case, the rotation matrix R to be determined can then be determined as the average, median, root mean square, or the like of all or a selection of the rotation matrices R ij. The use of a least-square method for determining the rotation matrix R is also conceivable.Since, as already mentioned above, the rotation matrix R in three-dimensional space via R=R(φ 0) R(θ 0) depends on the incorrect settings of the sensor 20 in the azimuthal direction φ 0 and in the elevation direction θ 0 these two can now be determined from the rotation matrix R. The incorrect settings are thus determined via Euclidean geometry as follows:Here, r 11, r 12 and r 31 denote the entries of the rotation matrix R (see equation (2) above) and arctan2 denotes the extension of the inverse angle function arctangens known to the person skilled in the art.This result can now be used to calibrate the sensor 20. For example, the incorrect settings φ 0 and θ 0 now known by calibration can be stored in a memory and, on the basis thereof, each subsequent measurement can then be corrected by subtraction of the incorrect settings φ 0 and θ 0.As described above, at least ten Doppler simulators are advantageously used for the method according to the invention. With less than ten Doppler simulators, the equation system would be underdetermined and the entries of the rotation matrix R could not be unambiguously determined. In the case of more than ten Doppler simulators, the equation system is overdetermined. In this case, the equation system can be reduced to nine linearly independent equations by means of statistical methods. Using more than ten Doppler simulators improves the result because statistical measurement inaccuracies in the calibration process average out.FIG. 7 is a flowchart schematically illustrating the calibration method shown in FIGS. 4, 5, and 6. At step ST 1, the electronic controller acquires predetermined position data and simulated apparent speeds thereof of the Doppler simulators from an external source. In step ST 2, the electronic controller receives measured locations and apparent speeds of the Doppler simulators from a surroundings sensor 20. In step ST 3, the electronic controller assigns the measured locations to the predetermined locations based on the measured and known apparent speeds of the Doppler simulators (at which locations x s,i and x w,j v i≈v j' ?). applies, respectively. In step ST 4, the electronic controller determines measured relative coordinates and predetermined relative coordinates from at least two of the predetermined locations of the Doppler simulators and measured locations of the Doppler simulators, respectively. At step ST 5, the electronic controller calculates a rotation matrix by solving a system of equations, and for a plurality of pairs of the Doppler simulators, the measured relative coordinates and the predetermined relative coordinates are respectively related via a rotation matrix to establish the system of equations. In step ST 6, the electronic controller calculates a maladjustment (correction angles φ 0 and ψ 0) of environment sensor system 20 from the elements of the rotation matrix.Reference numerals denote reference numerals1 Vehicle 2 Forward vehicle 4 Lane 5 Road 6 Center of road marking 7 Left curve 8 Detection region 10 Concealed region 12 Control unit for steering system 14 Control unit for brake system 16 Control unit for drive train 18 Control unit for environment sensor system 19 Vehicle communication network 20 Environment sensors 22 Image processing system 24 Satellite navigation unit 26 User interface 40 Processor 42 RAM memory 43 ROM memory 44 Storage drive 45 User interface 941 Interface interface KS Absolute coordinate system 1 Vehicle with sensor 20 Sensor R 1 First Doppler simulator R 2 Second Doppler simulator R 3 Third Doppler simulator R 4 Fourth Doppler simulator R 5 Fifth Doppler simulator R 6 Sixth Doppler simulator R 7 Seventh Doppler simulator R 8 Eighth Doppler simulator R 9 Ninth Doppler simulator R 10 tenth Doppler simulator p s absolute position of sensor x w,1 absolute position of first Doppler simulator x w,2 absolute position of second Doppler simulator x s,1 measured position of first Doppler simulator x s,2 measured position of second Doppler simulator φ 0 azimuth angle error of sensor θ 0 elevation angle error of sensor

Claims

An electronic control unit configured to: receive, from a surround sensor (20), measured locations (x s,i) and measured apparent speeds (v 1, v 2) of a plurality of Doppler simulators (DS1 to DS10), and provide a list [[x s,1, v 1], [ x s,2, v 2], [ x s,2, v 2],..., [ x s,N, vN]] of all measured apparent locations (xs,i) and their associated measured apparent speeds (vi); retrieving predetermined locations (x w,i) and predetermined apparent speeds (v 1', v 2') of the Doppler simulators (DS1 to DS10) in the form of a look-up list [[x w,1, v 1'], [ x w,2'], v 2'], [ x w,3, v 3'],..., [ x w,N, vN']] and determining a maladjustment (φ0, θ o) of the environment sensor (20) from the received locations (x w,i), the measured locations (x s,i), the measured apparent speeds (v 1, v 2) and the received apparent speeds (v 1', v 2'), wherein the control unit is configured, in order to assign the measured locations (x s,i) to the predetermined locations (x w,i) on the basis of a comparison of the measured apparent speeds (v 1, v 2) with the received apparent speeds (v 1', v 2') according to an assignment list [x s,1, x w,2], [ x s,2, x w,1], [ xs,2, xw,5],... [xs, N, xw,N]].Electronic control unit according to claim 1, wherein the control unit is configured to associate a measured location (x s,i) with the predetermined location (x w,j) whose predetermined apparent velocity (v j') is most similar to the measured apparent velocity (v i).Electronic control unit according to one of the preceding claims, wherein the electronic control unit is configured to use the determined incorrect setting (φ 0, θ 0) for calibrating the environment sensor (20).Electronic control unit according to one of the preceding claims, wherein the electronic control unit is configured to determine relative coordinates (x s,i- x s,j) measured from at least three of the measured locations (x s,i) of the Doppler simulators (DS1 to DS10), and to determine the maladjustment (φ 0, θ 0) of the environment sensor (20) from the measured relative coordinates (x s,i- x s,j) of the measured locations (x s,i).Electronic control unit according to Claim 4, wherein the electronic control unit is configured to ascertain predefined relative coordinates (x w,i- x w,j) from at least three of the predefined position data (x w,i) of the Doppler simulators (DS1 to DS10), and to ascertain the maladjustment (φ 0, θ 0) of the environment sensor (20) from the predefined relative coordinates (x w,i- x w,j) of the predefined position data (x w,i).Electronic control unit according to one of the preceding claims, which is further configured to ascertain a rotation matrix (R) from the determined locations (x s,i) and the predefined locations (x w,i), wherein the rotation matrix (R) describes the maladjustment (φ 0, θ 0) of the environment sensor.Electronic control unit according to one of the preceding claims, wherein the electronic control unit is configured to calculate a maladjustment (φ 0) of the environment sensors in the azimuthal direction and / or a maladjustment (θ 0) in the elevation direction.Electronic control unit according to claim 4 when dependent on claim 3, wherein the electronic control unit is configured to solve a system of equations, wherein for a plurality of pairs of the Doppler simulators (DS1 to DS10), the measured relative coordinates (x s,i- x s,j) and the predetermined relative coordinates (x w,i- x w,j) are respectively related via the rotation matrix (R) in order to establish the system of equations.Electronic control unit according to claim 6, wherein the electronic control unit is configured to calculate a rotation matrix (R) by means of singular value decomposition (M = UΣV T).Electronic control unit according to claim 7, wherein more than three Doppler simulators are used and an approach is used to solve an overdetermined equation system such as averaging, medianing or least squares estimation.

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