阅读说明：本技术 用于识别雷达传感器中的角度测量误差的方法 (Method for detecting angle measurement errors in a radar sensor ) 是由 T·布罗舍 于 2019-05-25 设计创作，主要内容包括：一种用于识别用于机动车的角度分辨雷达传感器(10)中的角度测量误差的方法,在所述方法中,针对静止的雷达目标(20)分别测量径向速度(V-r)和至少一个定位角度并基于所测量的定位角度计算出用于所述径向速度(V-r)的预期值,并将所述预期值与所测量的值进行比较,其特征在于,针对一个或多个静止的目标(20)进行所述径向速度(V-r)和所述定位角度的测量,针对所述目标中的每个都计算出个别指标值,对所获得的个别指标值进行角度相关的缩放以补偿失真角度误差的角度相关性,并且由经缩放的个别指标值计算出用于所述角度测量误差的指标,其中,所述个别指标值说明所测量的径向速度与所预期的径向速度的偏差。(Method for detecting angle measurement errors in an angle-resolved radar sensor (10) for a motor vehicle In which the respective diameters are measured for stationary radar targets (20)Velocity (V _ r) and at least one positioning angle And calculating an expected value for the radial velocity (V _ r) on the basis of the measured positioning angle and comparing the expected value with the measured value, characterized in that the radial velocity (V _ r) and the positioning angle are carried out for one or more stationary targets (20) For each of the targets, an individual index value is calculated, angle-dependent scaling of the obtained individual index value is performed to compensate for the angle dependence of the distorted angle error, and an index for the angle measurement error is calculated from the scaled individual index value, wherein the individual index value accounts for the deviation of the measured radial velocity from the expected radial velocity.)

1. A method for detecting an angle measurement error in an angle-resolved radar sensor (10) for a motor vehicle (28)In which method the radial velocity (V _ r) and at least one positioning angle (V _ r) are measured separately for a stationary radar target (20)And calculating an expected value for the radial velocity (V _ r) based on the measured positioning angle and comparing the expected value with the measured value, characterized in that the radial velocity (V _ r) and the positioning angle are performed for one or more stationary targets (20)For each of said targets, calculating an individual index value (q _ p) describing the deviation of the measured radial velocity from the expected radial velocity, angle-dependently scaling the individual index values to compensate for the angle dependence of the distorted angle error, and calculating an index (I) for the angle measurement error from the scaled individual index values.

2. Method according to claim 1, for an FMCW radar in which the frequency of the radar signal is modulated in a ramp-like manner in measurement intervals that follow one another, in which method the calculation of the individual index values is made on the basis of measurement results obtained within the same measurement interval.

3. Method according to claim 2, in which method the individual index values are combined into valid values (Q _ m) after the angle-dependent scaling, and the valid values obtained in measurement intervals following one another are temporally filtered, and the index (I) is calculated on the basis of the result of the filtering.

4. Method according to any of the previous claims, in which the angle-dependent scaling is performed in a two-dimensional angle space.

5. Method according to any of the preceding claims, in which method a misalignment error of the radar sensor (10) is identified and corrected on the basis of the measured radial velocity and azimuth angle, and the calculation of the individual indicator values (I) is performed on the basis of the angle measurement corrected for the misalignment error.

6. A radar sensor for a motor vehicle, having a transmitting and receiving unit and having a control and evaluation device (18), characterized in that the evaluation device (18) is designed to carry out the method according to one of the preceding claims.

Technical Field

The invention relates to an angle resolution for identifying a motor vehicleMethod for angular measurement error in a radar sensor, in which method a radial velocity and at least one positioning angle are measured for a stationary radar target, respectively, and an expected value for the radial velocity is calculated on the basis of the measured positioning angles and compared with the measured values.

Background

Radar sensors are used in motor vehicles for measuring distances, relative radial velocities and angles to physical objects. The purpose is to support comfort and safety functions, possibly in combination with other suitable sensing means (e.g. ultrasound, video or lidar). In radar measurements, a physical object may have one or more target reflections at different locations, especially in case of extended objects or good separability of the radar sensor.

Today's radar sensors are mostly FMCW (Frequency Modulated Continuous Wave) radar sensors with Fast-Chirp Modulation, i.e. Fast wideband ramps with ramp durations of 10 mus to several 10 mus, which means that the FMCW modulates the high slope of the ramp, thereby enabling to approximately ignore the doppler component within the ramp. Thus, by analytically processing the individual ramps, pitch information is essentially obtained. A measurement cycle also contains in most cases a plurality of (for example 256) ramps, each ramp having for example 512 sample values. The temporal variation of the phase position at the respective sampling point is then analyzed ramp by ramp, yielding additional independent information about the doppler frequency (velocity) of the target or of the target reflection, and this analysis is usually done by means of a two-dimensional fourier transform.

For angle estimation, MIMO antenna systems (Multiple Input Multiple Output) having Multiple transmit and receive channels are increasingly used. The transmit channels are typically separated by a Time Division Multiplexing (TDM) method. However, radar systems based on other methods such as frequency division multiplexing, code division multiplexing (FDM, CDM), or OFDM are also possible.

The angle analysis process is typically based on an analysis process of propagation time differences or phase differences between different receive channels, or in the case of MIMO, between different transmit/receive channel combinations. The transmit/receive channel combination can also be viewed in its role as an equivalent virtual array with only one transmit channel or as a virtual receive channel.

A method of the type mentioned at the outset is known from DE 102014223461 a1, with which a misalignment (Dejustage) of the radar sensor can be detected and a corresponding misalignment angle (Dejustagewikel) can be estimated and compensated for. Here, the misadjustment angle is an error angle in azimuth and elevation, which is the same for all angles to be estimated. The angle-dependent angle error is not taken into account.

However, in angle estimation or angle measurement, so-called distortion errors may also occur, which are caused, for example, by the refraction of radar waves at unpredictable interference sources, for example at the radar sensor or at the cover (Belag) on the radome (icing, snow cover, etc.), or in the case of indirect shielding (Verbau) of the radar sensor, for example behind an unsuitable bumper (for example after a replacement after a parking collision (Parkrempler), after a repainting, etc.). In this distorted angle measurement error, the deviation between the true and measured positioning angle is angle-dependent in its part.

Disclosure of Invention

The object of the present invention is to provide a method by means of which the presence of a distorted angle measurement error can be detected.

According to the invention, this object is achieved by: the method comprises the steps of measuring the radial velocity and the positioning angle for one or more stationary targets, calculating for each of these targets an individual indicator value (Einzel-indekter) which accounts for the deviation of the measured radial velocity from the expected radial velocity, angle-dependently scaling the obtained individual indicator values so as to approximately compensate for the angle dependence of the distorted angle error, and calculating from the scaled individual indicator values an indicator for the angle measurement error.

Neglecting the pitch (nickel), roll (Wanken), and yaw (giaren) of the vehicle, the sensitivity of the individual index value is 0 in the main beam direction (optical axis) of the radar, and increases as the angular deviation (Winkelablage) increases.

The angular dependence of the sensitivity of the individual index values for the distortion angle error can be calculated and compensated at least approximately by scaling of the angular dependence, so that a total index is obtained by averaging (mistelung) or summing the totality of the radar targets under consideration, which is largely independent of the more or less random angular distribution of the radar targets under consideration, and shows the presence of the distortion angle error and its size (Ausma β). Distorted angle errors can also be identified in this way, in particular when there are no misalignment errors and therefore the average angle deviation for all targets is expected to be a value close to zero.

Based on the thus obtained indices, it is possible to estimate the accuracy and reliability of the obtained angle measurements and to take them into account appropriately in the auxiliary functions based on these measurements.

Advantageous embodiments and embodiments of the invention result from the dependent claims.

In one embodiment, the angle-dependent scaling of the parameters is performed in a two-dimensional angular space (e.g., in azimuth and in elevation).

Optionally, the measurement results can also be evaluated with respect to possible misalignment errors, for example according to the method described in DE 102014283461 a 1. Then, if the misalignment error is known, it can be taken into account when calculating the expected radial velocity, thereby improving the accuracy in identifying the distortion error.

In FMCW radars, in which the frequency of the transmitted radar signal is modulated in a ramp-like manner in successive measurement intervals, it is expedient to carry out the determination of the individual index values on the basis of the measured values obtained for different radar targets in the same measurement interval. However, it is also possible to temporally filter the individual index values and/or the total index value, for example by means of an IIR filter, an FIR filter, a kalman filter, a quantile (Quantil) or the like, so that the current index value is correlated with the corresponding value from the preceding measurement interval, and thus the temporal course of change can be better identified and the accuracy can be further increased.

Likewise, the relative movement of the radar target in question can be tracked over a plurality of measurement periods by means of known tracking procedures and compared with the own movement of the vehicle (Eigenbewegung). In this way, it is generally possible to separate from each other the parts of the deviation between the measured radial velocity and the expected radial velocity, which parts are derived from distorted angle errors in azimuth angle on the one hand and in elevation angle on the other hand, so that distorted angle errors can also be quantitatively determined and compensated for. This can be achieved, for example, by: a Synthetic Aperture Radar (SAR) analysis process is performed that is based on a temporal course of doppler frequency, and the target location in the SAR results is compared to the target location that is derived based on radar measurements (target range, azimuth angle, and elevation angle).

Drawings

Embodiments are further explained below based on the drawings.

The figures show:

fig. 1 shows a schematic diagram for illustrating a distorted angle error at a radar sensor;

FIG. 2 shows a schematic for illustrating the misalignment angle;

FIGS. 3 and 4 show sketches illustrating the dependence of the radial velocity of a radar target on the positioning angle;

FIG. 5 shows a schematic diagram illustrating the angular relationship of a radar target in a spherical coordinate system;

FIG. 6 shows a schematic diagram illustrating the angular relationship of a radar target in a pyramidal coordinate system;

FIG. 7 shows a flow chart illustrating the basic steps of a method according to the invention

Fig. 8 shows a schematic diagram illustrating the zoom function and the limit function.

Detailed Description

Fig. 1 schematically shows a horizontal sectional view of a radar sensor 10 having a housing 12 which accommodates a MIMO antenna array 14 and is bounded on the transmitting and receiving sides by a radome 16. Connected to the antenna array 14 is a control and evaluation device 18 for controlling the function of the radar sensors and determining the distance r, the relative velocity V _ r (radial velocity), the azimuth angle of radar targets 20 located in the locating area on the basis of the received radar echoesAnd an elevation angle alpha (collectively referred to as the positioning angle). Schematically indicating a radar beam 22 reflected at four radar targets 20 and again received by antenna array 14.

As an example, it is assumed that a cover 24 (e.g. an ice shell) is present on the radome 16, at the surface of which the radar beam 22 is refracted, so that a distorted angle measurement occurs in the angle measurement (here in azimuth angle)Error of the measurementIt can be seen that the radar beam 22 is refracted by the cladding 24 with different intensities and in different directions, thereby distorting the angle measurement errorDepending on the position of the respective radar target 20 relative to the radar sensor 10.

The radar sensor 10 is mounted in the front of a motor vehicle and is used in particular for locating a vehicle travelling in front and other obstacles in the front zone of the vehicle. In this case, the (justicet) radar sensor is usually aligned in such a way that its optical axis coincides with an axis x, which indicates the direction of travel of the motor vehicle.

For comparison, fig. 2 shows a situation in which no distortion angle error occurs, but the radar sensor 10 is not correctly aligned, so that its optical axis 26 deviates from the x-axis in azimuth. As a result, the azimuth angles measured for the different radar targets 20With offset errorHowever, measurement error from distortion angleDifference, offset errorWith the same sign and the same magnitude for all targets 20.

In the following, a method is described by means of which the presence of such angle measurement errors, in particular distorted angle measurement errors according to fig. 1, can be reliably detected.

In fig. 3, the maneuver is shown in plan overviewA vehicle 28 that moves past a stationary radar target 20 (e.g., a traffic sign at a road edge). The vehicle's own speed V is denoted as a vector. The vector V rel — V specifies the relative speed of the radar target 20 relative to the motor vehicle 28. In the following, for the sake of simplicity, it is assumed that the direction of movement of the antenna of the radar sensor mounted in the motor vehicle coincides with the direction of movement of the rear axle of the vehicle. However, in general, due to pitch motion, roll motion, and rotational motion (yaw) around the vertical axis, the direction of the actual own velocity of the antenna 14 may deviate from the x-axis of the coordinate system depending on the installation position of the radar 10 in the vehicle. The actual speed V of the antenna at its installation location and the angle measurement that has to be corrected accordingly (by using the antenna) must be adjusted accordinglyOr (α, β) is the angle between the actual direction of motion of the antenna and the corresponding target) to take this into account or to limit the analysis process to driving situations with negligible pitch, roll and yaw motion.

The radar target 20 is located by a radar sensor 10 (not shown in fig. 3) mounted in the front of a motor vehicle 28. In the case shown in fig. 3, a relatively small positioning angle (azimuth angle) is measured for the targetThe vector V _ r can be decomposed into a radial component along the line of sight between the radar sensor and the radar target and a transverse component perpendicular thereto. The magnitude of the radial component being the radial velocityWhere V is the magnitude of the own speed of the vehicle or antenna on the ground and at the same time the magnitude of the relative speed V rel.

FIG. 4 shows the situation at a later moment in time, i.e. when the azimuth angle isIncrease and causeThe relative speed V _ r is reduced relative to the self speed V.

If it is known that the radar target 20 is a stationary target and if the speed V of the vehicle itself, or in particular of the antenna array at the respective installation location, is also known, for example on the basis of direct measurement by means of wheel revolution sensors on the vehicle, on the basis of the yaw rate or the like, V _ r can be determined according to the formula specified aboveTo calculate. On the other hand, V _ r can also be measured directly by means of the radar sensor 10, due to the doppler effect. The comparison of the measured value with the calculated value enables the azimuth angle to be checkedIs correct.

In fig. 3 and 4, only two spatial dimensions are considered. The radial velocity V _ r also depends on the elevation angle α of the radar target 20, taking into account all three spatial dimensions, i.e. according to the following formula:

fig. 5 shows the radar target 20 in a three-dimensional cartesian coordinate system with axes x, y and z. In spherical coordinates, the position of the radar target 20 is defined by a radius r, an azimuth angleAnd the elevation angle alpha. For the sake of simplicity, the (vectorial) own speed V of the motor vehicle or of the antenna array is shown parallel to the x-axis in fig. 5 and 6. Also indicating possible angle measurement errors in azimuthAnd a possible angle measurement error in elevation angle α _ e.

For the conversion from spherical coordinates to cartesian coordinates, the following relationship applies:

z＝r*sin(α)

instead of the spherical coordinates according to fig. 5, optionally also pyramidal coordinates (r, β, α) can be used, as shown in fig. 6. The elevation angle α has the same meaning in pyramidal coordinates as in spherical coordinates. The elevation angle describes the angle between the position vector (Ortsvektor) of the radar target 20 and the x-y plane. However, in pyramidal coordinates, the azimuthal angle is replaced by an angle βThe angle describes the angle between the position vector of the radar target and the x-z plane. Therefore, for the conversion to cartesian coordinates:

x＝r*(cos²(α)-sin²(β))^1/2

y＝r*sin(β)

z＝r*sin(α)

likewise, examples for possible angle measurement errors β _ e are indicated.

Error in angle measurementα _ e, β _ e may in principle relate to misadjustment errors and/or distortion errors. Methods for identifying misalignment errors are well known. In order to also detect distortion errors, the method illustrated in the flow chart in fig. 7 can be implemented, for example.

The set of stationary targets located in a given measurement period is marked with R _ m (m is an index identifying the measurement period). Criteria for distinguishing between stationary and moving objects are known and include, among other things, comparing the measured relative speed of an object with the vehicle's own speed. In step S1, a subset P _ m is selected from the set R _ m, which will be used to check for distortion measurement errors. The number of selected targets N _ m should be so large that a certain compensation of statistical fluctuations is achieved. Furthermore, the selected targets should be distributed as uniformly as possible over as large a spatial angle as possible.

Then, in step S2, the motion state of the own vehicle 28 is estimated, for example, based on the signal of the wheel revolution sensor. In this way, in the coordinate system according to fig. 5 or 6, an estimated value for a vector V is obtained, which vector describes the self-movement of the vehicle and thus of the radar sensor antenna installed in the vehicle. The result of the estimating step S2 may at the same time form the basis for identifying stationary objects in step S1 of the next measurement cycle.

Preferably, in another step S3, the validity of the target selected in step S1 is verified again. In particular taking into account the movement of the vehicle itself, and in particular of the antenna, which has been determined in step S2. Here, the criteria are, for example, the minimum self speed of the vehicle or radar sensor on the ground, the acceleration and yaw rate of the self vehicle, the number of elements (targets) in P _ m, and the numerical spread of angle measurement data (streummg).

In a further optional step S4, the data which describe the vehicle' S own movement are checked and, if necessary, updated on the basis of the radar data obtained in the current and, if necessary, preceding measuring cycles.

It should also be assumed in the example considered here that: independently of the checking for distortion angle errors, a checking for misalignment errors is also carried out, which may be based on the measurement data for the target selected in step S1.

Then, in step S5, the offset for the identified sensor is corrected for the positioning angle (e.g., for positioning angle)And a) measurement data, thereby to correct the distortion errorThe inspection can be performed based on more accurate angle measurement data.

Then, in step S6, for each individual target in the set P _ m (which targets are identified based on the index P), an index value q _ P is calculated, which represents a measure for the deviation of the calculated radial velocity V _ r from the radial velocity actually measured based on the doppler effect. The starting point is equation (1). However, it is desirable to distinguish between the approach and the departure of a radar target by: when the target approaches, V _ r is made to take a negative value. Then, in the spherical coordinates apply:

wherein the content of the first and second substances,αandare possibly erroneous measurements, α _ e andis the angle measurement error.

Similarly, in the pyramidal coordinates apply:

-V_r/V＝(1-sin²(β)-sin²(α))^1/2＝(cos²(β-β_e)-sin²(α-α_e))^1/2 (3)

if it is notαP andis the measured positioning angle for a target with index p and V _ r _ p is the measured radial velocity for that target, a suitable index value q _ p is given, for example, by:

alternatively, in pyramidal coordinates:

q_p＝(-V_R_P/V)-(cos²(α_p)-sin²(β_p))^1/2。 (5)

however, there can also be different definitions for the index value, for example:

or

q_p＝(-V_R_P/V)²-cos²(α_p)+sin²(β_p) (7)

Since the distortion angle measurement error is angle-dependent, as already explained on the basis of fig. 1, the index value obtained in step S6 will in principle also be angle-dependent, i.e. in principle a different index value is obtained for each target in P _ m. Thus, in general, the sum or average of the index values will also depend on the angular distribution of the target. Here, the index values may also take different signs, and depending on the angular distribution of the target, the average value of the index values may in some cases approach zero and may disguise a correct measurement despite the fact that there is a distorted measurement error.

In order to still obtain a convincing indicator for the presence of distortion errors, an angle-dependent scaling of the indicator value is performed in step S7. For this purpose, arbitrary (in the case of a spherical coordinate system) definitions are providedScaling functionOr F (α, β) (in the case of a pyramidal coordinate system), which exhibits, at least approximately, the angular dependence of the distortion angle error. The scaling function may again be, for example, a gradientFunction of (c):

in the case of pyramidal coordinates, a scaling function F (α, β) is formed, which may be, for example, the function F (α, β) ═ F (G (α, β)) of the gradient G (α, β):

G(α,β)＝-[sin(2α)+sin(2β)]*(2*[cos(2α)+cos(2β)])^-1/2 (9)

then, an effective value Q _ m largely independent of the angle is formed from the index values Q _ p for the respective targets, for example, according to the following formula:

where the sum symbol represents the sum over all targets in P _ m. Then, in an optional step S9, the significant values respectively obtained in step S8 in successive measurement cycles are filtered temporally in order to achieve a higher stability with respect to statistical fluctuations. As a result of the filtering, a filtered effective value Q _ filt is obtained. Finally, in step S10, the filtered value is scaled by the scaling factor F _ scal and limited by the upper and lower limit values Q _ min and Q-max, so that finally an index value I is obtained which varies linearly between 0 and 1 according to the function shown in fig. 8. Then, in step S10, the index value I is output to other modules of the driver assistance system, and the accuracy and reliability of the result of the angle measurement are allowed to be evaluated in these modules.

The information used to form the index value I is independent of the phase information obtained in the receive channels of the antenna array 14 and forms a metric that characterizes the angle error and is independent of classical angle estimation. In particular, an angle error or an angle blind area (winkellblindheit) of the radar sensor can be identified even if the quality of the angle estimate is so high that no error can be inferred from the quality.

Under the assumption that the elevation angle α is error-free, the equation (2) or (3) is solvedOr β, a correction value can also be derived which, in addition to the multivalue character of the symbols, describes an angle measurement error in the azimuth angle(in spherical coordinates) and β _ e (in pyramidal coordinates). Instead, a correction value for the elevation angle can be derived assuming no error in the azimuth angle.