Alignment Detection for Vehicle Radar Transceivers

Abstract

This disclosure focuses on the pitch angle (φ p ) and roll angle (φ r The present invention relates to a measurement system (12) for measuring the alignment of a vehicle radar transceiver (3), the measurement system having a The measurement system (12) is configured to: - transmit a radar signal (5); - receive a reflected radar signal (6) reflected by at least one target object (7); and - determine by the reflected radar signal (6) a measured azimuth angle (θ) of each target object (7) relative to a reference plane (R). det ) and the measured elevation angle (ψ det The measurement system (12) is adapted to measure a measurement angle (θ) such that: - assuming that each target object (7) and the radar transceiver (3) are positioned in a common plane (P) at a distance (d) from the ground surface (G), and - the equation is satisfied: det , ψ det ) to determine the pitch angle (α p ) and roll angle (α r ) is further adapted to estimate

Description

[Technical field]

[0001] The present disclosure relates to measuring the alignment of a vehicle radar transceiver, where alignment is defined by the pitch, yaw and roll angles of the radar transceiver relative to a fixed coordinate system. [Background technology]

[0002] Today, vehicles may be fitted with one or more radar transceivers to detect reflections from surrounding objects to implement safety features such as collision avoidance and autonomous / assisted driving. Such radar transceivers need to obtain the azimuth angle, which is the angle in the direction of the target, the distance to the object, and the relative speed between the vehicle and the object. They may also need to report the elevation angle to the target.

[0003] In most vehicle radar applications, it is important to measure the azimuth angle with a relatively high degree of accuracy. The angular accuracy of a radar system depends on fundamental parameters such as the number of receive channels, component tolerances, assembly accuracy, and installation conditions.

[0004] The proper radar transceiver orientation when mounted on a vehicle is given when its x and y axes span a plane parallel to the vehicle's xy plane, with its x axis pointing along its specified mounting aiming direction. Complete 3D misalignment is three times the angle that a radar sensor or radar transceiver must be rotated to bring it from its proper orientation to its actual misaligned orientation. The first rotation is about its z-axis and is called yaw; the second rotation is about its y-axis and is called pitch, and the third rotation is about its x-axis and is called roll.

[0005] In order to transform the target coordinates from the radar transceiver coordinate system to the vehicle coordinate system, it is important to know the complete position and orientation of the radar transceiver coordinate system in the vehicle coordinate system. Due to mounting tolerances or due to accident impacts, the radar sensor may also be misaligned in pitch and / or roll angles. In this case, if the pitch and roll misalignments are not known, a correct transformation of the radar target into another coordinate system (e.g., the car coordinate system) is not possible. Moreover, if the pitch and roll misalignments are not known, a correct estimation of the yaw misalignment is not possible.

[0006] The radar transceiver may further be affected by various vehicle components, such as different types of bumpers and vehicle front and rear geometries. The radar transceiver is also affected by variations during manufacturing and assembly. Thus, the sensor system requires calibration to generate an accurate sensor output signal. This calibration is often performed during manufacturing in the factory, which is time consuming and drives up costs. The optimal calibration parameters may also change over time, which may require recalibration, which may be inconvenient. Summary of the Invention [Problem to be solved by the invention]

[0007] It is an object of the present disclosure to present an alternative, less complex method and system for detecting the alignment and possible misalignment of radar transceivers.

[0008] This object is achieved by a measurement system for measuring the alignment of a vehicle radar transceiver, the alignment being determined by a pitch angle φ of the radar transceiver relative to a fixed coordinate system. p and roll angle φ rThe measurement system includes a radar system, the radar system including a radar transceiver and a control unit. The measurement system transmits a radar signal, receives a reflected radar signal reflected by at least one target object, and determines a measured azimuth angle θ of each target object relative to a reference plane R by the reflected radar signal. det and the measured elevation angle ψ det The measurement system is adapted to measure a measurement angle θ, assuming that each target object and the radar transceiver are positioned in a common plane P at a distance d from the ground surface G, such that the following equation is satisfied: det , ψ det using the pitch angle α of the radar transceiver relative to a fixed coordinate system p and roll angle α r The method is further adapted to estimate

[0009]

number

[0010] This is the pitch angle α of the radar transceiver relative to a fixed coordinate system. p and roll angle α r This means that an accurate estimate of the pitch angle α can be obtained in a relatively simple manner. This estimate is based on the assumption that each target object and the radar transceiver are positioned in a common plane, and the pitch angle α p and roll angle α r is the measurement azimuth angle θ det and the measured elevation angle ψ det It is based on the inventor's insight into how the [Means for solving the problem]

[0011] According to some aspects, the measurement system is adapted to satisfy the equation by using a non-linear least squares fit.

[0012] According to some aspects, the measurement system is adapted to satisfy the equation using Bayesian estimation.

[0013] This means that known methods can be used to make the desired estimations, although of course many other numerical methods are applicable.

[0014] This object is also achieved by a method and a vehicle with the above mentioned advantages. [Brief description of the drawings]

[0015] The present disclosure will now be described in more detail with reference to the accompanying drawings. [Figure 1] FIG. 2 is a schematic top view of the vehicle and the measurement system. [Diagram 2] 1 shows a schematic side view of a radar transceiver and a target object. [Diagram 3] 1 shows a schematic perspective view of a radar transceiver in a coordinate system. [Figure 4] 1 shows a first schematic diagram of a radar transceiver in a coordinate system; [Diagram 5] 2 shows a schematic second view of a radar transceiver in a coordinate system. [Figure 6] 3 shows a schematic third view of a radar transceiver in a coordinate system. [Figure 7] 1 shows a schematic side perspective view of a target object for a radar transceiver. [Figure 8A] 4 illustrates azimuth cuts for different measurement azimuth angles. [Figure 8B] 4 illustrates azimuth cuts for different measurement azimuth angles. [Figure 8C] 4 illustrates azimuth cuts for different measurement azimuth angles. [Figure 8D] 4 illustrates azimuth cuts for different measurement azimuth angles. [Figure 9] 1 is a graphical representation showing how measured azimuth and elevation angles relate to each other for a particular misalignment. [Figure 10] The nonlinear parameter optimization for the cross-traffic scenario without installation errors is illustrated. [Figure 11] The nonlinear parameter optimization for the cross-traffic scenario without installation errors is illustrated. [Figure 12] This paper illustrates nonlinear parameter optimization for a cross-traffic scenario with mounting errors. [Figure 13] This paper illustrates nonlinear parameter optimization for a cross-traffic scenario with mounting errors. [Figure 14] Illustrates Bayesian estimation for a cross-traffic scenario with mounting errors. [Figure 15] Illustrates Bayesian estimation for a cross-traffic scenario with mounting errors. [Figure 16] Illustrates Bayesian estimation for a cross-traffic scenario with mounting errors. [Figure 17] Illustrates Bayesian estimation for a cross-traffic scenario with mounting errors. [Figure 18] Illustrates Bayesian estimation for a cross-traffic scenario with mounting errors. [Figure 19] Illustrates Bayesian estimation for a cross-traffic scenario with mounting errors. [Figure 20] 1 illustrates a schematic diagram of a control unit. [Figure 21] 1 illustrates an exemplary computer program product. [Figure 22] 1 shows a flow chart of a method according to the present disclosure. DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS

[0016] Aspects of the present disclosure will now be more fully described with reference to the accompanying drawings. However, the different devices and methods disclosed herein may be embodied in many different forms and should not be construed as being limited to the aspects set forth herein. Like numbers in the drawings refer to like elements throughout.

[0017] The terms used herein are for the purpose of describing aspects of the present disclosure only and are not intended to be limiting of the present disclosure. As used herein, the singular forms "a," "an," and "the" are intended to include the plural forms as well, unless the context clearly indicates otherwise.

[0018] 1 shows a top view of a vehicle 1 equipped with a radar system 2, which comprises a vehicle radar transceiver 3 and a control unit 4. The radar transceiver 3 has a particular field of view (FOV) 9 and a front face 11 that includes a radar aperture.

[0019] According to some embodiments, the radar transceiver 3 is positioned behind or inside a bumper 8 which acts as a radome for the radar transceiver 3 .

[0020] FIG. 1 further shows a measurement system 12 for measuring the alignment of the vehicle radar transceiver 3, which alignment is determined by the pitch angle φ of the radar transceiver 3 relative to a fixed coordinate system x, y, z, as shown in FIGS. 3 to 6. p , yaw angle φ y and roll angle φ r FIG. 3 shows a schematic perspective view of the radar transceiver 3 in the coordinate system x, y, z, and FIG. 4 to FIG. 6 show the pitch angle φ of the radar transceiver 3. p , yaw angle φ y and roll angle φ r 1 shows a schematic diagram of a radar transceiver 3 with a front surface 11 of the radar transceiver 3 in a coordinate system x, y, z illustrating.

[0021] The measurement system 12 includes a radar system 2, which includes a radar transceiver 3 and a control unit 4. According to some embodiments, the measurement system 12 further includes at least one target object 7, for example if a target object 7 is included in a given test setup.

[0022] Referring also to FIG. 2 , the measurement system 12 transmits a radar signal 5, receives a reflected radar signal 6 reflected by a target object 7, and determines a measured azimuth angle θ of the target object 7 relative to a reference plane R by the reflected radar signal 6. det and the measured elevation angle ψ det The system is adapted to measure

[0023] For this purpose, the radar transceiver 3 is adapted to transmit a radar signal 5 and to receive a reflected radar signal 6 reflected by a target object 7. The control unit 4 is adapted to control the radar transceiver 3, e.g., the transmission timing, the transmission frequency content, as well as the actual transmission time waveform. The control unit 4 is also adapted, according to some embodiments, to perform signal processing to extract target data related to the detected target object, e.g., a 2D FFT to obtain a range-Doppler matrix in a manner known from the past. According to some embodiments, the control unit 4 is connected to an external computing device 20.

[0024] According to the present disclosure, the measurement system 12 assumes that the target object 7 and the radar transceiver 3 are positioned in a common plane P at a distance d from the ground surface G, and determines the measurement angle θ such that the following equation is satisfied: det , ψ det using the pitch angle α of the radar transceiver 3 relative to the fixed coordinate system x, y, z p and roll angle α r It has been further adapted to estimate

[0025]

number

[0026] This is the pitch angle α of the radar transceiver 3 relative to the fixed coordinate system x, y, z. p and roll angle α r This means that an accurate estimate of can be obtained in a relatively simple manner.

[0027] According to some embodiments, the measurement system 12 includes a target object 7 that is determined to be in motion.

[0028] This disclosure relates to pitch angle α p and roll angle α r is the measurement azimuth angle θ det and the measured elevation angle ψ det Based on inventor insight into how the technology impacts

[0029] This is illustrated in Figure 7, where φ p There is a certain error due to pitch misalignment such that the measured azimuth angle θ of the target objects 71, 72, 73, 74 is ≠ 0. det1 , θ det2 , θ det3 , θ det4 Depending on the elevation angle ψ det It means that the target objects 71, 72, 73, 74 and the radar transceiver 3 are assumed to lie in a common plane P.

[0030] 8A-8D show this when the target objects 71, 72, 73, and 74 are measured at different azimuth angles θ 1det , θ 2det , θ 3det , θ 4det This is illustrated by showing the corresponding azimuthal cuts for

[0031] FIG. 8A shows the first measurement azimuth angle θ det1 and the first measurement elevation angle ψ det1 4 shows the case where a first target object 71 is present.

[0032] FIG. 8B shows the second measurement azimuth angle θ det2 and the second measurement elevation angle ψ det2 4 shows the case where a second target object 72 is present.

[0033] FIG. 8C shows the third measurement azimuth angle θ det3 and the third measurement elevation angle ψ det3 4 shows the case where a third target object 73 is present.

[0034] FIG. 8D shows the fourth measurement azimuth angle θ 4det and the fourth measurement elevation angle ψ det4 4 shows the case where a fourth target object 74 is present.

[0035] Due to the pitch misalignment separating the common plane P from the reference plane R, the larger the measured azimuth angle is relative to the aiming direction B, the smaller the measured elevation angle will be.

[0036] Figure 9 shows the p =-6.5° pitch misalignment and φ r θ = -4.0°。 For example, the measured azimuth angle θ = -4.0°. det The target object 7' detected at =0.0° is approximately

[0037]

number

[0038] and the measured elevation angle ψ det The target object 7” detected at =0.0° is approximately at the measured azimuth angle

[0039]

number

[0040] It becomes.

[0041] As a result, the measured azimuth angle θ det and the measured elevation angle ψ det At least one measured azimuth angle θ is obtained using different measurements for det and at least one measured elevation angle ψ det These angle values ​​φ satisfy the above formula (1) p , φ r By finding , the pitch and roll alignment errors can be measured. Typically multiple detections are used.

[0042] According to some embodiments, the aiming direction B lies within a reference plane R.

[0043] Pitch misalignment angle φ p and roll misalignment angle φ r Different numerical methods can be used to solve for , and examples of the use of different numerical methods are disclosed below.

[0044] 10-13, according to some embodiments, the measurement system 12 is adapted to satisfy the equation by using a non-linear least squares fit with non-linear parameter optimization. In the illustrated example, there is a cross traffic scenario with five vehicles intersecting and the radar transceiver 3 is mounted behind the bumper 8.

[0045] Figure 10 shows the case where there is no installation error, i.e., the pitch misalignment is φ p = 0° and the roll misalignment is φ r = 0° and the resulting calculated pitch misalignment is φ p = 0.42° and the resulting calculated roll misalignment is φ r = -0.11°. The dotted line relates to the expectation of the nonlinear parameter optimization and the solid line to the result, both as a function of azimuth and elevation angles.

[0046] Figure 11 illustrates the estimated parameter values ​​plotted as a function of the iteration number of the parameter optimization described above with reference to Figure 10. The x-axis shows the iteration number and the y-axis shows the estimated parameter values.

[0047] Figure 12 shows the pitch misalignment of p =-6.5°, and the roll misalignment is φ r =-4.0°, and the resulting calculated pitch misalignment is φ p=-5.84° and the resulting calculated roll misalignment is φ r =-3.68°. The dotted line relates to the expectation of the nonlinear parameter optimization and the solid line to the results, both as a function of azimuth and elevation angles.

[0048] Figure 13 illustrates the estimated parameter values ​​plotted as a function of the iteration number of the parameter optimization described above with reference to Figure 12. The x-axis shows the iteration number and the y-axis shows the estimated parameter values.

[0049] 14-19, according to some embodiments, the measurement system 12 is adapted to satisfy the equation by using Bayesian estimation. In the illustrated example, there is a cross traffic scenario with five vehicles intersecting and the radar transceiver 3 is mounted behind the bumper 8.

[0050] Figures 14 to 19 visualize the mechanism of Bayesian estimation, where observations of detected target objects are used to refine knowledge about parameters present in the form of distributions. The prior parameter distribution is updated with each observation to a posterior parameter distribution. As more and more observations of detected target objects are observed, the posterior distribution becomes sharper over time. In each left diagram, the x-axis shows the azimuth angle and the y-axis shows the elevation angle relative to the observation. In each right diagram, the x-axis shows the pitch misalignment angle of the radar transceiver and the y-axis shows the roll misalignment angle of the radar transceiver.

[0051] In Figs. 14 to 16, there is no installation error, that is, φ p = 0° pitch misalignment and φ r = 0° roll misalignment.

[0052] In Figure 14, for the zero observation case, no observations of the detected target object have been captured, and therefore the pitch and roll distributions are the initial distributions. The resulting calculated pitch misalignment is φ p= 0° and the resulting calculated roll misalignment is φ r =0°.

[0053] FIG. 15 shows the posterior distribution after 50 observations, and the resulting calculated pitch misalignment, φ p = 1.93° and the resulting calculated roll misalignment is φ r =-0.79°.

[0054] Figure 16 shows the posterior distribution after 500 observations. The resulting calculated pitch misalignment is φ p = 0.38° and the resulting calculated roll misalignment is φ r =-0.15°.

[0055] The results are very accurate, and as a result, the parameter pitch misalignment angle φ p and roll misalignment angle φ r An estimate of can be measured.

[0056] In Figures 17 to 19, there is an installation error, and p =-6.5° pitch misalignment and φ r =-4° roll misalignment exists.

[0057] In Figure 17, for the 0 observation case, no observations of the detected target object have been captured, and therefore the pitch and roll distributions are the initial distributions. The resulting calculated pitch misalignment is φ p = 0° and the resulting calculated roll misalignment is φ r =0°.

[0058] Figure 18 shows the posterior distribution after 50 observations. The resulting calculated pitch misalignment is φ p =-6.15° and the resulting calculated roll misalignment is φ r=-3.13°.

[0059] Figure 19 shows the posterior distribution after 500 observations. The resulting calculated pitch misalignment is φ p =-5.89° and the resulting calculated roll misalignment is φ r =-3.57°. The result is very accurate, and as a result, the parameter pitch misalignment angle φ p and roll misalignment angle φ r An estimate of can be measured.

[0060] Although only one implementation of each of the numerical methods described above is provided, it will be appreciated that there are many other ways to implement these methods.

[0061] Furthermore, the above-mentioned numerical method reduces the pitch misalignment angle φ p and roll misalignment angle φ r This is merely an example of how to derive θ, and many other such numerical methods are of course conceivable and obvious to one skilled in the art.

[0062] According to some aspects, the pitch misalignment angle φ p and roll misalignment angle φ r Once these are measured, they can be stored in memory and used by the control unit 4, which measures the measured pitch misalignment angle φ p and roll misalignment angle φ r is adapted to provide compensation for subsequent detection of the target object such that

[0063] As will be described in more detail below, in accordance with some aspects, a control unit and a computer program are used to control the pitch angle φ p and roll angle φ r The most likely misalignment value can be determined.

[0064] 20 illustrates generally, in terms of some functional units, components of a control unit 70, corresponding to the illustrated control unit 4, according to one embodiment. The processing circuitry 71 is provided using any combination of one or more suitable central processing units (CPUs), multiprocessors, microcontrollers, digital signal processors (DSPs), dedicated hardware accelerators, etc. capable of executing software instructions stored in a computer program product, for example in the form of a storage medium 72. The processing circuitry 71 may further be provided as at least one application specific integrated circuit (ASIC), or field programmable gate array (FPGA).

[0065] In particular, the processing circuitry 71 is configured to cause the control unit 70 to perform a series of operations or steps, which operations or steps were described above in connection with the various metrology systems 12 and methods. For example, the storage medium 72 can store a set of operations, and the processing circuitry 71 can be configured to retrieve the set of operations from the storage medium 72 and cause the control unit 70 to perform the set of operations. The set of operations can be provided as a set of executable instructions. As a result, the processing circuitry 71 is configured to perform the methods and operations disclosed herein.

[0066] Storage medium 72 may also comprise a persistent storage device, which may be, for example, any one or combination of magnetic memory, optical memory, solid state memory, or even remotely attached memory.

[0067] The control unit 70 may further comprise a communication interface 73 for communicating with at least one other unit. The interface 73 may thus comprise one or more transmitters and receivers with analog and digital components and a suitable number of ports for wired or wireless communication.

[0068] The processing circuitry 71 is adapted to control the overall operation of the control unit 70, for example, by sending data and control signals to, receiving data and reports from, and retrieving data and instructions from, the external unit and the storage medium 72. Other components and associated functions of the control unit 70 have been omitted so as not to obscure the concepts presented herein.

[0069] FIG. 21 illustrates a computer program product 81 including computer-executable instructions 82 disposed on a computer-readable medium 83 for performing any of the methods disclosed herein.

[0070] With reference to FIG. 22, the present disclosure also relates to a method for measuring the alignment of a vehicle radar transceiver 3, the alignment being determined by a pitch angle φ of the radar transceiver 3 relative to a fixed coordinate system x, y, z. p and roll angle φ r The method includes transmitting S100 a radar signal 5, receiving S200 a reflected radar signal 6 reflected by at least one target object 7, and using the reflected radar signal 6 to measure a measured azimuth angle θ of each target object 7 relative to a reference plane R. det and the measured elevation angle ψ det and measuring S300.

[0071] The method further comprises assuming S400 that each target object 7 and the radar transceiver 3 are positioned in a common plane P at a distance h from the ground surface G, and determining a measurement angle θ such that the following equation is satisfied: det , ψ detusing the pitch angle α of the radar transceiver 3 relative to the fixed coordinate system x, y, z p and roll angle α r and estimating S500.

[0072]

number

[0073] According to some embodiments, the method includes using a target object 7 that is determined to be in motion.

[0074] According to some embodiments, the method includes filling S510 the equation by using a nonlinear least squares fit.

[0075] According to some aspects, the method includes satisfying S520 the equation by using Bayesian estimation.

[0076] The present disclosure is not limited to the described embodiments, but may be freely modified within the scope of the appended claims. For example, the radar transceiver may be of any suitable type and may, according to some aspects, comprise suitable devices such as an antenna, a transmitter, a receiver, a control unit, etc.

[0077] The control unit 4 may be constituted by one unit or by two or more distributed sub-units. The control unit 4 may be adapted, according to some embodiments, to perform one or more of the steps described as being performed by the measurement system 12.

[0078] The present disclosure may be applied to any suitable radar transceiver or transceivers included in the radar system 2.

[0079] The present disclosure is useful, for example, when the radar transceiver 3 is not accessible to a person performing an alignment test, for example to place an inclinometer on the radar transceiver 3. Thus, the person performing the alignment test needs a way to know that the radar transceiver 3 is aligned on the vehicle within tolerances agreed to by the radar manufacturer, and this is provided by the present disclosure.

[0080] According to some aspects, the alignment of the radar transceiver 3 is oriented towards the alignment of an antenna 21 included in the radar transceiver 3, which is adapted to transmit radar signals and receive reflected radar signals in a well-known manner. According to some aspects, the radar transceiver 3 is an integrated unit, and any adjustment or misalignment of the radar transceiver 3 directly affects the antenna 21 included in the radar transceiver 3.

[0081] It should be noted that when it is stated that each target object 7 and the radar transceiver 3 are positioned in a common plane P at a distance h from the ground surface G, this is an assumption. This does not necessarily mean that this is the case in practice.

Claims

1. A method for measuring the alignment of a vehicle radar transceiver (3), said alignment being determined by the pitch angle (φ) of said radar transceiver (3) relative to a fixed coordinate system (x, y, z). ｐ ) and roll angle (φ ｒ ) wherein the method is defined by Transmitting (S100) a radar signal (5); Receiving (S200) a reflected radar signal (6) reflected by at least one target object (7); The reflected radar signal (6) is used to determine the measured azimuth angle (θ) of each target object (7) relative to a reference plane (R). ｄｅｔ ) and the measured elevation angle (ψ ｄｅｔ (S300) measuring the The method comprises: Assuming (S400) that each target object (7) and the radar transceiver (3) are positioned within a common plane (P) at a distance (h) from the ground surface (G); The measured angle (θ ｄｅｔ , ψ ｄｅｔ ) to determine the pitch angle (α) of the radar transceiver (3) relative to a fixed coordinate system (x, y, z). ｐ ) and the roll angle (α ｒ estimating (S500) [0010]

2. The method of claim 1 , wherein the method includes using a target object (7) that is determined to be moving.

3. The method of claim 1 or 2, wherein the method includes satisfying (S510) the equation by using a non-linear least squares fit.

4. The method of claim 1 or 2, wherein the method comprises satisfying (S520) the equation by using Bayesian estimation.

5. A metrology system (12) for measuring the alignment of a vehicle radar transceiver (3), said alignment being determined by the pitch angle (φ) of said radar transceiver (3) relative to a fixed coordinate system (x, y, z). ｐ ) and roll angle (φ ｒ ), the measurement system (12) comprises a radar system (2), the radar system (2) comprises the radar transceiver (3) and a control unit (4), and the measurement system (12) is defined by: - transmitting a radar signal (5), - receiving a reflected radar signal (6) reflected by at least one target object (7); and - The reflected radar signal (6) determines the measured azimuth angle (θ) of each target object (7) relative to a reference plane (R). ｄｅｔ ) and the measured elevation angle (ψ ｄｅｔ ) The measurement system (12) - each target object (7) and said radar transceiver (3) are assumed to be positioned in a common plane (P) at a distance (d) from the ground surface (G); and The measured angle (θ ｄｅｔ , ψ ｄｅｔ ) to determine the pitch angle (α) of the radar transceiver (3) relative to a fixed coordinate system (x, y, z). ｐ ) and the roll angle (α ｒ ). [0025]

6. The measurement system of claim 5 , wherein the measurement system (12) includes a target object (7) that is determined to be moving.

7. 7. The metrology system of claim 5 or 6, wherein the metrology system (12) is adapted to satisfy the equation by using a non-linear least squares fit.

8. 7. The measurement system of claim 5 or 6, wherein the measurement system (12) is adapted to satisfy the equation using Bayesian estimation.

9. A vehicle (1) comprising a measurement system (12) according to any one of claims 5 to 8.

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