How to calibrate a radar sensor

Abstract

The present invention relates to a method for calibrating a radar sensor, comprising the steps of: storing (1) an antenna diagram, which assigns a control vector (B) to each of a number of angles (A) before the radar sensor is put into use; performing (10) radar measurements on one or more targets; and converting the received signals for each target into a measurement vector for the target. Step (11) to save as TIFF2024544270000059.tif98 and the measurement vector from the control vector (C) for each target Deviation of TIFF2024544270000060.tif88 Steps (12, 13) of calculating TIFF2024544270000061.tif811 and the calculated deviation for all targets A step of statistically evaluating TIFF2024544270000062.tif811 (14) and steps of correcting the antenna diagram or radar measurements with the statistically evaluated deviation (D) (15, 16, 17, 18) are performed.

Description

[Technical Field]

[0001] The present invention relates to a method for calibrating a radar sensor. [Background technology]

[0002] In automotive driver assistance systems, such as automatic distance control systems and collision warning systems, radar sensors are often used to detect the traffic environment. In addition to distance and relative speed, the azimuth angle of a located object is usually important, since it allows lane matching when locating a preceding vehicle. The elevation angle of a located object can also be important, since it allows determining the relevance of the target, for example, whether it is surmountable, drivable, or an obstacle that could cause a collision.

[0003] The azimuth and elevation angles of a target can be determined from the amplitude and / or phase difference of the transmitting and / or receiving antennas of an antenna array. During angle estimation, the received signal is compared with an antenna diagram corresponding to previously measured angles. If a single target is located, or if multiple targets that are clearly distinguishable from one another based on their range and relative velocity are located, the estimated angle is obtained as the position of the best match (correlation) between the received signal and the antenna diagram. In the general case of multiple target estimation, special estimation algorithms are known that provide estimates of the localization angles of all targets involved.

[0004] Conventionally, the antenna diagram of each radar sensor is measured at the factory before it is put into service. The measurement data is converted into a predefined format for storage and analysis in the control unit. Normalization is performed here. Alternatively, the antenna diagram can be defined analytically. In this case, the relative phase is given by 2π sin(d RX,TX / λ), and d RX,TXis the distance between the considered transmitter and receiver combinations in the virtual array. Such analytical antenna diagrams are determined purely by calculation.

[0005] Ageing effects, temperature effects, and hidden installation of radar sensors behind bumpers or vehicle manufacturer emblems can lead to deviations between the measured antenna diagram and the actual amplitude and phase differences between the transmitting and / or receiving antennas. Such deviations can in principle also be caused by radar sensor misalignment (e.g. elevation misalignment: several targets have elevation angles that deviate significantly from the azimuth calibration) or by incomplete calibration (too few azimuth and / or elevation calibration measurements). These deviations can lead to angular errors and poor correlation values.

[0006] The correlation value is used, for example, to detect the overlap of multiple targets within a measurement cell, to activate the multi-target angle estimation algorithm, to detect distortive agnosia, i.e., the disruption of angle measurement capabilities due to coatings on the radar sensor (ice, snow, mud, etc.), to serve as a quality criterion for the reliability of the estimates, and / or to serve as a criterion for object formation (tracking). Therefore, a decrease in the correlation value due to the above-mentioned effects increases the number of malfunctions of the multi-target angle estimation algorithm (ghost targets with large angle errors of several degrees) on the one hand, and increases the number of false positives of distortive agnosia on the other hand. Furthermore, a decrease in the correlation value may disrupt object formation.

[0007] From DE 10 2014 208 899 A1, a method is known in which correction of amplitude and / or phase differences is performed in a MIMO radar sensor (multiple-input-multiple-output, i.e., multiple transmit and multiple receive antennas) using SIMO angle estimation (single-input-multiple-output, i.e., one transmit antenna and multiple receive antennas) or MISO angle estimation (multiple-input-single-output, i.e., multiple transmit and one receive antenna). Summary of the Invention

[0008] A method for calibrating a radar sensor is proposed, in which an antenna diagram of the radar sensor is determined and stored in a manner known per se before the radar sensor is put into use. The antenna diagram assigns a control vector to each of a number of angles or angle combinations consisting of azimuth and elevation pairs. Only a few coefficients can be stored, from which the control vector can be reconstructed. The complete antenna calibration curve can also be stored, but this is not required.

[0009] After the radar sensor is put into use, radar measurements are performed on one or more targets. At this time, targets suitable for calibration can be selected. For example, only targets with a signal-to-noise ratio above a threshold can be considered during the measurement. The received signals acquired during the radar measurement are stored in a measurement vector for each target.

[0010] The deviation of the measurement vector from the control vector of the antenna diagram is then calculated for each target. For this purpose, preferably the scalar product

[0011]

number

[0012] , the angle

[0013]

number

[0014] Hermitian conjugate control vector of

[0015]

number

[0016] and the measurement vector

[0017]

number

[0018] Then, the deviation can be calculated according to the following formula 1.

[0019]

number

[0020] Let, be the measurement vector

[0021]

number

[0022] and the calculated scalar product

[0023]

number

[0024] Control vector multiplied by

[0025]

number

[0026] It can be calculated according to Equation 2 as the difference between

[0027]

number

[0028] scalar product

[0029]

number

[0030] is the pair of azimuth and elevation angles

[0031]

number

[0032] For a combination of angles consisting of azimuth and elevation angles,

[0033]

number

[0034] Hermitian conjugate control vector of

[0035]

number

[0036] and the measurement vector

[0037]

number

[0038] Therefore, it may be calculated according to formula 1*. Then, the deviation

[0039]

number

[0040] Let, be the measurement vector

[0041]

number

[0042] and the calculated scalar product

[0043]

number

[0044] Control vector multiplied by

[0045]

number

[0046] It can be calculated according to Equation 2 as the difference between

[0047]

number

[0048] The calculated deviations are then statistically evaluated for all selected targets, where the calculated deviations are averaged or the median of the calculated deviations is calculated. When averaging, the calculated deviations may be additionally weighted by the signal-to-noise ratio of each of the relevant targets. Alternatively, a histogram may be generated for the statistical evaluation.

[0049] Finally, the antenna diagram or radar measurement value is corrected with the statistically evaluated deviation. Here, a previously calculated or measured antenna diagram is corrected, or future radar measurements are corrected directly. For radar sensors capable of simultaneously detecting multiple targets, a further processing step may be provided in which a correction of the current radar measurement value is performed in the same cycle in which the statistically evaluated deviation is calculated. This is particularly useful when a coating (such as ice, snow, or slush) is detected on the radar sensor, but the radar measurement must be performed in the best possible way.

[0050] Radar sensor misalignment means that most targets are not in the calibration plane (e.g., at 0° elevation in the sensor coordinate system). This leads to angular errors that cannot be corrected even with perfectly specified misalignment. Since it is not possible to distinguish between physical misalignment and antenna diagram distortion, angular errors due to antenna diagram distortion are not directly corrected. The described radar sensor calibration corrects amplitude and / or phase deviations relative to the antenna diagram, thereby correcting correlation degradation. This improves the activation of multi-target angle estimation algorithms and the detection of distortive blind spots. It also improves target formation that is hindered by correlation degradation.

[0051] Only the azimuth angle or, if necessary, the elevation angle can be considered during the correction. Alternatively, the azimuth-elevation pair can be considered during the correction. In this case, a two-dimensional correction (2D correction map) that depends on the azimuth angle and the elevation angle is realized.

[0052] The correction can be applied to all angles, correcting for amplitude and / or phase deviations across the entire angular range measured by the radar sensor. Such a comprehensive correction can be applied to both the antenna diagram and the radar measurement, as described above. With a comprehensive correction, the radar measurement of the target is already sufficient to calculate the deviations.

[0053] Alternatively, angle-dependent correction may be provided, in which amplitude and / or phase deviations are corrected for a given angular range. This allows different angular ranges with different deviations to be corrected separately. Such correction may be applied only to the antenna diagram. In angle-dependent correction, radar measurements are made on multiple targets. In particular, one or more targets are measured at each angular range.

[0054] To prevent erroneous corrections in the event of distortive agnosia, deviations can be recorded and statistically evaluated over a significantly longer period than is intended for the detection of distortive agnosia.

[0055] The calibration may be performed separately for different temperature ranges. As described above, the deviation is calculated and correction is performed separately for each temperature range. This allows correction of temperature effects that cause rapid changes. The temperature is preferably determined using a temperature sensor, which is typically already provided in the radar sensor.

[0056] An embodiment of the invention is illustrated in the drawings and explained in more detail in the following description. [Brief explanation of the drawings]

[0057] [Figure 1] 1 shows a flow chart of a first embodiment of the method according to the invention; [Figure 2] 4 shows a flow chart of a second embodiment of the method according to the invention; DETAILED DESCRIPTION OF THE INVENTION

[0058] 1 and 2 each show a flow chart of an embodiment of a method according to the invention for calibrating a radar sensor. In both cases, an antenna diagram of the radar sensor is stored before the radar sensor is put into use. 1 The antenna diagram is stored in a number of angles.

[0059]

number

[0060] Each of the control vectors

[0061]

number

[0062] In this example, the angle

[0063]

number

[0064] is the azimuth angle. In a further embodiment not shown, the angle may be an elevation angle. Also, in another embodiment also not shown, multiple angles

[0065]

number

[0066] Instead, a combination of azimuth and elevation angles is used. In the first embodiment of Fig. 1, the radar sensor performs radar measurements 10 on one or more targets, in this embodiment after it has been put into service. Suitable targets are selected for calibration, for example targets with a signal-to-noise ratio above a threshold. The received signals obtained in the radar measurements 10 are then used to generate a measurement vector for each target.

[0067]

number

[0068] 11. Scalar product

[0069]

number

[0070] is the Hermitian conjugate control vector of the antenna diagram

[0071]

number

[0072] and the measurement vector

[0073]

number

[0074] and is calculated according to Equation 11. Then, the measurement vector

[0075]

number

[0076] and the scalar product

[0077]

number

[0078] The control vector of the antenna diagram multiplied by

[0079]

number

[0080] From this, the difference is formed according to Equation 213, and thus the deviation

[0081]

number

[0082] is calculated.

[0083]

number

[0084] Then, the calculated deviation

[0085]

number

[0086] is averaged over all targets14, and the mean deviation

[0087]

number

[0088] When averaging, the calculated deviations may be weighted by the respective signal-to-noise ratios of the relevant targets. Alternatively, other types of statistical evaluations may be used, such as median calculations or histograms.

[0089] In this first embodiment, a global correction is performed in which amplitude and / or phase deviations are corrected for the entire angular range 15. The antenna diagram is then averaged over the deviations

[0090]

number

[0091] 16. Or future radar measurements will be averaged.

[0092]

number

[0093] 17. Furthermore, if the radar sensor detects multiple targets simultaneously, the current radar measurement is corrected with the same period 18. The second embodiment of Fig. 2 differs from the first embodiment in that different angular ranges are examined separately. After the radar sensor is put into use, in this embodiment radar measurements 20 are performed on multiple targets at different angular ranges. The received signals are then converted into measurement vectors 20 for each target.

[0094]

number

[0095] 21, deviation saved

[0096]

number

[0097] is calculated for each target according to Equation 1 and Equation 2 above, and the deviation

[0098]

number

[0099] is the averaged deviation

[0100]

number

[0101] , or is statistically evaluated in other ways as described above. See the description of the first embodiment. In this second embodiment, an angle-dependent correction is performed in which the amplitude and / or phase deviations are corrected only for a given angular range 25. The antenna diagram is then plotted using the averaged deviations.

[0102]

number

[0103] This is corrected to 26. In both embodiments, steps 10 through 18 or steps 20 through 26 can be repeated for different temperature ranges.

Claims

1. 1. A method for calibrating a radar sensor, comprising: before starting to use said radar sensor, a control vector [Equation 1] (1) storing an antenna diagram that allows the assignment of - performing (10; 20) radar measurements on one or more targets; The received signal for each target is converted into a measurement vector for that target. [Equation 2] and saving the data (11; 21) respectively. - the control vector for each target [Equation 3] the measurement vector from [Equation 4] deviation of [Equation 5] (12, 13; 22, 23) steps of calculating - Calculated deviations for all targets [Equation 6] Statistically evaluating (14; 24) - said statistically evaluated deviation [Equation 7] correcting (15, 16, 17, 18; 25, 26) said antenna diagram or said radar measurements with Including, the measurement vector [Equation 8] The control vector [Equation 9] When calculating the deviation from (12, 13; 22, 23), the Hermitian conjugate control vector [Equation 10] and the measurement vector [0011] The scalar product with [0012] is calculated (12; 22), and the deviation [0013] is the measurement vector [0014] and the calculated scalar product [Equation 15] (13;23) where the control vector is calculated as the difference between the vector and the control vector multiplied by

2. The correction (25) according to the angle of the antenna diagram is performed by the statistically evaluated deviation [0016] 2. The method of claim 1, wherein the method is carried out by

3. 2. The method of claim 1, wherein the calibration is performed for a combination of angles consisting of azimuth and elevation.

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