Use of a radar sensor with a waveguide antenna array for determining the self-velocity estimate and the target's angle estimate.

Abstract

The present invention relates to the use of a radar sensor comprising a waveguide antenna array having at least two groups of antenna units each comprising a plurality of antenna elements, wherein the antenna elements within each antenna unit are arranged side by side in a first direction, and in a first group (104) the antenna units are arranged offset from each other in a second direction perpendicular to the first direction, and in a second group the antenna units are arranged offset from each other in the first direction, and to a method for determining an estimated own velocity and an estimated angle of a target, the method having the following steps: The distances between the radar sensor with synthetic aperture and the respective targets are measured by the radar sensor with synthetic aperture. In addition, the relative velocities of the respective targets are measured by the radar sensor with synthetic aperture using the Doppler effect. An angle estimation of an angle estimation value characterizing the angle between the direction of the own velocity of the radar sensor with synthetic aperture and the respective targets is performed. Thereafter, for each target, an individual estimated own velocity (Equation A) of the radar sensor with synthetic aperture is determined using the relative velocity and the angle estimation value. Classification and grouping are performed with respect to stationary targets for which the individual estimated own velocities (Equation A) are together within a settable range (B) of the individual estimated own velocities, and moving targets for which the individual estimated own velocities (Equation A) are outside the range (B). For the stationary targets, a combined estimated own velocity is determined from the individual estimated own velocities (Equation A) of the stationary targets. Finally, a corrected angle estimation value for the stationary targets is determined using the combined estimated own velocity and the respective measured relative velocities.

Description

[Technical Field]

[0001] The present invention relates to the field of radar sensor equipment, and in particular to the field of Multiple-Input-Multiple-Output (MIMO) and Synthetic Aperture (SAR) radar. [Background technology]

[0002] Radar systems for measuring the distance, relative velocity, and angle of objects are increasingly being used in automobiles for safety and comfort functions. Currently, multiple-input-multiple-output (MIMO) radars, i.e., radars with multiple transmission paths for transmitting and receiving radar signals, are used for this purpose. Recently, synthetic aperture (SAR) radars have become known. The synthetic aperture principle enables particularly accurate angle measurements when the radar sensor is moving. Synthetic apertures are based on the radar sensor's movement, and utilize the fact that the transmitting and receiving antennas are located in different spatial positions at each measurement point. In this case, measurements are processed with a synthetic antenna aperture. For evaluation, this can be equated to a large antenna aperture along the vehicle's trajectory. This achieves a large synthetic aperture that would be impractical or impossible to achieve with a real antenna aperture due to the large number of antenna elements required. SAR allows for a higher resolution in angle measurements than with a real antenna aperture.

[0003] To evaluate the measured radar signal as a synthetic aperture, the radar environment is usually assumed to be stationary. In addition, the radar sensor's self-motion and therefore the position at which each measurement is taken must be known. This radar trajectory is incorporated into the SAR evaluation algorithm and is the basis for calculating the SAR image. Depending on the evaluation algorithm, the self-velocity estimate may be sufficient to calculate the SAR image instead of a more accurate trajectory. In this case, the trajectory is typically assumed to be linear, whereas more complex trajectories cannot be represented.

[0004] Today's automotive radar systems typically use fast-rising-ramp frequency-modulated continuous-wave radar (FMCW), also known as fast-chirp modulation, which involves multiple successive linear frequency ramps with the same gradient. The mixing of the transmitted and received signals produces a low-frequency signal (called the beat frequency), whose frequency is proportional to the range. The system is typically designed so that the component of the beat frequency caused by the Doppler frequency is negligible. The obtained range information is fully unambiguous. Furthermore, by observing the time evolution of the phase of the complex range signal across the ramp, the Doppler shift can be determined, and from this, the relative velocity can be determined. The determination of range and relative velocity is performed independently of each other. A two-dimensional Fourier transform is typically used for this purpose.

[0005] Traditional SAR evaluation assumes stationary targets. Moving targets that do not meet this assumption are depicted incorrectly, at a different angle, and blurred in SAR images. However, moving targets are also of concern in automobiles (e.g., to avoid collisions with such moving targets). Two approaches are known for estimating the radar sensor's self-trajectory or self-velocity. One approach uses external sensors, such as an inertial measurement unit (IMU) or an odometry sensor. The other approach uses autofocus algorithms, which are computationally very complex and cannot be applied to real-time processing. Summary of the Invention [Problem to be solved by the invention]

[0006] The subject of the present invention is the use of a radar sensor with a waveguide antenna array for a method for determining an estimate of the vehicle's own velocity and the angle of several surrounding targets, the process steps of which are described in more detail below. [Means for solving the problem]

[0007] The waveguide antenna array of the radar sensor has at least two groups of antenna units, with the antenna elements in each antenna unit arranged side by side in a first direction. In the first group, the antenna units are offset from one another in a second direction perpendicular to the first direction. In the second group, the antenna units are offset from one another in the first direction, thereby providing a multiple-input-multiple-output (MIMO) radar sensor.

[0008] The radar sensor utilizes Digital Beamforming (DBF), so that the antenna elements of one antenna unit can jointly record and evaluate one radar signal. A first group with these antenna units in a second direction is preferably used to measure the azimuth angle, and a second group with these antenna units in the first direction is preferably used to measure the elevation angle.

[0009] In the second group, the antenna units may be arranged with a stagger only in the first direction, which reduces the computational costs of digital beamforming. Optionally, in the second group, the antenna units may additionally be arranged with a stagger in the second direction, which enables measurements in the second direction for the second group, and the radar sensor is designed based on multiple-input-multiple-output (MIMO).

[0010] Preferably, the arrays are alternately assigned to the transmitting or receiving side. Based on the MIMO principle, the transmitting and receiving antennas are in principle interchangeable. In the following, a distinction is made between stationary targets (also called static targets) and moving targets (also called moving targets). Stationary targets are objects in the surroundings that do not move themselves, such as buildings, trees, infrastructure on and beside the road. Moving targets are objects that move in the surroundings, such as other vehicles, pedestrians and other road users.

[0011] The radar sensor moves and transmits a number of measurement signals while receiving signals reflected by the target. Therefore, the radar sensor is a synthetic aperture radar sensor. From the transmitted and received signals, the relative velocity of each target is determined. To determine the relative velocity, the Doppler effect in the measurement signals is evaluated, and in particular the Doppler shift is determined. Additionally, the distance between the radar sensor and the target is also determined from the transmitted and received signals. This can be done, for example, via Fourier processing. To recognize the target being measured, detection is performed using a constant alarm rate (CFAR).

[0012] Subsequently, a coarse angle estimation is performed. For this, an angle estimate is estimated for each target, which characterizes the target angle between the direction of the radar sensor's own velocity, i.e., the direction in which the radar sensor is moving ("forward"), and the respective target. The angle estimation can be performed, for example, by digital beamforming. For this purpose, the radar sensor has at least one additional receiving channel and / or at least one additional transmitting channel. Preferably, the angle estimate directly indicates the target angle. However, the target angle can also be determined indirectly from a transformation of the angle estimate or a mathematical relationship. Since the angle estimate is still further processed later, this angle estimate may be significantly less accurate than a conventional angle measurement.

[0013] By backprojection, an individual self-velocity estimate of the radar sensor is calculated separately for each target using the relative velocity and angle estimates. That is, for each target, measured or estimated values ​​are used to obtain an individual self-velocity estimate of the radar sensor. Therefore, typically, multiple individual self-velocity estimates depending on the target's velocity are determined. For stationary targets, these individual self-velocity estimates are close together because the relative velocity between the target and the radar sensor is proportional to the radar sensor's own velocity and target angle. However, for moving targets, these individual self-velocity estimates are farther apart because the relative velocity depends not only on the radar sensor's own velocity and target angle but also on the target's velocity. In addition, in typical situations, there are significantly more stationary targets in the surrounding area than moving targets with the same relative velocity to the radar sensor, and moving targets usually have different velocities from each other.

[0014] This allows classification and grouping of the individual own velocity estimates, particularly by clustering. For this purpose, a range is defined for the individual own velocity estimates, which allows for the discrimination between stationary and moving targets. Individual own velocity estimates that coexist within a configurable range are assigned to stationary targets. Individual own velocity estimates that lie outside this range are assigned to moving targets. This allows for the identification of moving targets (MTI - Moving Target Indication). The individually calculated individual own velocity estimates can be recorded, for example, in a histogram for classification.

[0015] The individual own velocity estimates are then evaluated separately according to the assignment. For stationary targets, a combined own velocity estimate is determined from the individual own velocity estimates assigned to the stationary targets. This combined own velocity estimate can be considered the actual own velocity of the radar sensor, since it is essentially calculated from stationary targets only (autofocus). In addition, for stationary targets, a corrected angle estimate is calculated using the combined own velocity estimate and each measured relative velocity. This corrected angle estimate can be considered the actual angle of the target relative to the radar sensor.

[0016] The method further allows for the determination of ego-velocity and angle estimates directly from the measurements without the need for additional sensors, such as an IMU or odometry sensor, which are typically used in vehicles and are often located too far away from the radar sensor and also perform too few measurements per time interval.

[0017] The use of a radar sensor with a waveguide antenna array for the aforementioned method combines the waveguide antenna with MIMO and SAR concepts. The same antenna unit or antenna element is used for both MIMO and SAR. As a result, the number of channels in the radar sensor can be reduced, thereby minimizing the antenna area. This is a significant advantage, especially for waveguide antennas, which typically require large installation spaces and are labor-intensive to manufacture due to their three-dimensional structure.

[0018] The use of waveguide antennas allows a great degree of freedom in the placement of the antenna array elements, which allows for an advantageous λ / 2 placement of the antenna units to be easily achieved, which is advantageous both in terms of dynamics and unambiguous angle estimation.

[0019] For the received, downconverted, and baseband sampled radar signal of the antenna array to be compatible with the combination of MIMO and SAR, it must be possible to uniquely sample the Doppler frequency. The range in which the radial component of the relative velocity can be uniquely captured is v rel,r,u for,

[0020]

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[0021] applies. In the formula, v rel,r,max and v rel,r,min is the upper or lower limit of this range. D,u represents the bandwidth of the Doppler frequency that can be captured univocally to the maximum extent, c is the wave propagation speed, f c is the carrier frequency of the radar signal, and T ctc represents the period between two frequency ramps (chirp-to-chirp) of the same transmit antenna.

[0022] In time division multiplexing, for a fixed bandwidth and a fixed ramp slope or ramp duration, the period T between two frequency ramps is ctc Since σ increases with the number of transmitters, conventional FMCW-MIMO radar sensors based on time division multiplexing are limited in the number of transmitters. In the present invention, multiplexing in the frequency dimension (FDM, frequency division multiplexing) or multiplexing in the code dimension (CDM, code division multiplexing) is preferably implemented. In this case, SAR does not have such a limitation on the number of transmitters.

[0023] Advantageously, the configurable range used for sorting and grouping the individual self-speed estimates is a measurement error tolerance range. This error tolerance range is determined from the error in the measurement of the relative speed and the error in the angle estimation. This allows the grouping to be performed uniquely within the measurement error tolerance limit, thereby providing the greatest possible selectivity.

[0024] To determine the combined ego velocity estimate, an averaged velocity value of the individual ego velocity estimates may be calculated, for which classical averaging, e.g., arithmetic averaging, weighted averaging with weights that depend on the signal-to-noise ratio, determining the maximum value in a histogram, generating a median, etc. may be performed.

[0025] It is also preferable to determine respective angle estimates and respective velocity estimates for moving targets. However, since the velocity of the moving target is unknown, the above-described evaluation would result in erroneous angle estimates. The angle estimate for each moving target can be the angle estimate determined during the above-described angle estimation for that moving target. While this does not necessarily improve the angle estimation, it does prevent erroneous angle estimates. Furthermore, a radial velocity estimate for each moving target can be determined from the relative velocity measured using the Doppler shift. For this purpose, the combined own velocity estimate determined above is assumed to be the radar's own velocity, and is weighted by the cosine of the target angle and subtracted from the relative velocity.

[0026] The movement of the radar and the movement of the moving target are assumed to be two-dimensional movements within a plane. However, the target measured by the sensor may be at a different height relative to this plane. This may occur, for example, when only a portion of the object is captured. In this case, an elevation angle between this plane and the target can be determined. This elevation angle is preferably taken into account when determining the radar sensor's individual self-velocity estimate for each target using the relative velocity and the estimated angle.

[0027] The radar sensor is preferably a chirp sequence radar, which functions as a frequency-modulated continuous wave radar and transmits a chirp signal with a rapidly rising ramp, allowing distance to be easily measured in a manner known per se. In addition, the Doppler effect, in particular the Doppler shift, can be determined from the time evolution of the phase of the complex distance signal across the ramp, allowing relative velocity to be measured.

[0028] Any known method can be used to determine the relative velocity using the Doppler effect, in which case the Keystone process based on the Chirp-Z Transform (CZT) is preferred, as this process is particularly computationally efficient and can correct for migration effects that occur.

[0029] Exemplary embodiments of the invention are illustrated in the drawings and are explained in more detail in the following description. [Brief explanation of the drawings]

[0030] [Figure 1] 1 is an isometric view of a waveguide antenna of a radar sensor used in the method according to the invention; [Figure 2] 1 is a schematic diagram of a vehicle equipped with a radar sensor and a traffic situation with various targets and their associated angles and relative velocities; [Figure 3] FIG. 2 is a flow diagram of one exemplary embodiment of the method. [Figure 4a] FIG. 4a shows a distribution of the radar sensor's individual self-velocity estimates for various targets. [Figure 4b] Figure 4b is a histogram for the distribution of Figure 4a. [Figure 5] 3A and 3B are trajectory diagrams of a trajectory generated according to an embodiment of the method according to the invention and a trajectory generated by an odometry sensor; DETAILED DESCRIPTION OF THE INVENTION

[0031] FIG. 1 shows a waveguide antenna 100 of a radar sensor S (not shown here). The waveguide antenna 100 has a waveguide antenna array consisting of a plurality of antenna elements 101. The plurality of antenna elements 101, twelve in each example, are arranged in a row in a first direction R1 and together form one antenna unit 102 (one antenna unit is exemplarily highlighted by a frame in FIG. 1 ). In this example, the first direction R1 corresponds to a vertical line in the global reference coordinate system. The antenna elements 101 of one antenna unit 102 together transmit and receive radar signals. In FIG. 1 , a phase center 103 is marked for each antenna unit 102. The antenna units 102 of the waveguide antenna array are divided into two groups 104 and 105. In this example, the first group 104 includes eight antenna units 102, each of which has twelve antenna elements 101 arranged in a row in the first direction R1. In the first group 104, the antenna units 102 are arranged offset relative to one another in a second direction R2, which in this example corresponds to one of the horizons in the global reference frame and corresponds to the self-velocity v of the vehicle F carrying the radar sensor S, as shown in FIG. ego Generally, the second direction R2 is the direction of the vehicle F's own velocity v ego , which simply steers the antenna lobe. The second direction R2 is associated with the azimuth angles α1, α2, and α3, and the first group 104 of antenna units 102 serves to measure the azimuth angles α1, α2, and α3. The second group 105 includes three antenna units 102 in this example, each of which also has 12 antenna elements 101 arranged in a row in the first direction R1. In the second group 105, the antenna units 102 are offset from one another in both the first direction R1 and the second direction R2. The second group 105 of antenna units 102 is associated with the elevation angle Φ iThe waveguide antenna 100 is useful for measuring the direction angles α1, α2, and α3 and the azimuth angles α1, α2, and α3. In the illustrated state, the first group 104 of antenna units 102 is assigned to the receiving side RX, and the second group 105 of antenna units 102 is assigned to the transmitting side TX. Radar signals received by the first group 104 are processed using digital beamforming. However, this assignment may be reversed, so that the first group 104 is assigned to the transmitting side TX and the second group 105 is assigned to the receiving side RX. The waveguide antenna 100 is therefore designed for MIMO. In other exemplary embodiments not shown, the antenna units 102 in the second group 105 may be offset from one another only in the first direction R1. This simplifies two-dimensional digital beamforming. The described waveguide antenna 100 or a radar sensor S equipped with the described waveguide antenna array is used in the method described below.

[0032] 2 shows a schematic diagram of a traffic situation with a vehicle F having a radar sensor S equipped with the above-mentioned waveguide antenna 100 and several other vehicles represented as targets Z1 to Z3. There are typically further targets in the surrounding area that are not shown here, such as buildings, road infrastructure, i.e. signs, guardrails and the like, or the road itself. The vehicle F, and therefore also the radar sensor S, can measure its own velocity v ego The radar sensor S detects the target Z1, Z2, and Z3 shown in the figure, and the vehicle moves along a straight line with its own velocity v ego The azimuth angles α1, α2, and α3 between the direction of the radar sensor S and the directions of the targets Z1, Z2, and Z3 are shown. In addition, the relative velocities v of the targets Z1, Z2, and Z3 with respect to the radar sensor S are shown. rel,1 , v rel,2 , v rel,3 If one of the targets, for example target Z1, is a stationary target, i.e., it is not moving, the imputed relative velocity v rel,1 is the self-velocity v of the radar sensor S egoThe projections are given as the projections of the target Z1, Z2, and Z3 onto the assigned azimuth angle α1. The projections are shown for all three targets Z1, Z2, and Z3 in Figure 1. For a moving target, say target Z2, moving with an unknown velocity, the velocity of target Z2 is given by the relative velocity v rel,2 is a part of the measured relative velocity v rel,2 differs from this projection.

[0033] FIG. 3 shows a flow diagram of one exemplary embodiment of a method according to the present invention. In this case, a number of targets, collectively designated i, are interrogated. Measurement 1 is performed while the vehicle F and radar sensor S are moving. Measurement 1 is performed using frequency-modulated continuous wave radar modulation (FMCW), in which chirp signals with rapidly rising linear and uniform frequency ramps are emitted at set time intervals. The reflected signals are recorded and processed as received signals. The mixing of the transmitted and received signals at each time results in a low-frequency beat signal, the frequency of which is proportional to the range of target i. Measurement 1 is performed such that the Doppler effect or Doppler shift in the beat frequency is negligible or is taken into account in the evaluation.

[0034] Then, a Keystone process 2 is performed, in which the time evolution of the phase of the complex measurement signal across the frequency ramp is determined to estimate the Doppler shift or Doppler frequency, with the corresponding linear distance change (migration) corrected for each estimated value. This results in the relative velocity for each target i.

[0035]

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[0036] is determined. Distance estimation is then performed using conventional Fourier processing 3 from the time domain to the frequency domain, in particular the Fast Fourier Transform (FFT). The resulting two-dimensional spectra (range and relative velocity) of the individual transmit and receive channel combinations are non-coherently averaged 4. For this purpose, the absolute value of each of these spectra is generated, and then these absolute values ​​or their absolute squares are summed. To recognize the target being measured, a Constant Alarm Rate (CFAR) detection 5 is performed.

[0037] Further angle estimation 6 is performed, in this case the target azimuth angle estimate

[0038]

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[0039] This azimuth angle estimate

[0040]

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[0041] represents the azimuth angle between the measurement axis of radar sensor S and target i, and therefore also reflects the mounting condition of radar sensor S. Since the mounting condition is known, the azimuth angle estimate

[0042]

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[0043] By coordinate transformation, the self-velocity v ego The azimuth angle α between the direction of and the direction of target i i For the example shown in FIG. 2, the measurement axis is the self-velocity v ego This gives rise to the following relationship: i =90-α iFor angle estimation 6, digital beamforming is used, whereby simultaneous measurements are performed via multiple antenna units 102 on a waveguide antenna array and a phase difference is calculated from which an azimuth angle estimate is then calculated.

[0044]

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[0045] The self-velocity v of the radar sensor S can be determined. ego The effect of is negligible for this type of angle estimation, and therefore the azimuth angle estimate

[0046]

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[0047] is the self-velocity v of the radar sensor S ego In addition, the angle estimation 6 determines the elevation angle Φi between the plane in which the vehicle is moving and the height at which target i is acquired. Therefore, for each target i, the relative velocity

[0048]

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[0049] and the azimuth angle estimate

[0050]

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[0051] and possibly the elevation angle Φi are known. This allows us to calculate the individual self-velocity estimates for each target i separately:

[0052]

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[0053] However, Eq.

[0054]

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[0055] It is calculated based on In Fig. 4a, the individual egovelocity estimates calculated in this way for some targets i are

[0056]

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[0057] Figure 4b shows the distribution of many different individual self-velocity estimates.

[0058]

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[0059] In both figures, the individual self-velocity estimates

[0060]

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[0061] It can be seen that the targets are concentrated in range B. In a typical traffic situation, there are clearly more stationary targets than moving targets with the same relative velocity in the radial direction to the radar sensor S.

[0062] 3, a clustering 8 is performed, in which the individual self-velocity estimates that fall within the range B are clustered.

[0063]

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[0064] is assigned to the stationary target, and the individual self-velocity estimates outside range B

[0065]

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[0066] is assigned to the moving target, which allows it to be identified (MTI - Moving Target Indication) and separated from stationary targets. Range B is defined via the error in measurement 1 and angle estimation 6 and is the error tolerance.

[0067] Individual self-velocity estimates assigned to stationary targets, i.e., within range B

[0068]

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[0069] is the combined self-velocity estimate

[0070]

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[0071] 9 to obtain the combined ego velocity estimate. Various types of averaging can be performed, such as classical averaging, e.g., arithmetic averaging, weighted averaging, e.g., with weights that depend on the signal-to-noise ratio, determining the maximum value in a histogram, generating a median, etc.

[0072]

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[0073] is calculated without moving targets, so the actual self-velocity of radar sensor S^v ego Estimates for

[0074]

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[0075] This allows autofocusing to be achieved. For each stationary target, an angle calculation 10 is also performed to calculate the relative velocity of the stationary target determined by Keystone processing 2 using the Doppler effect.

[0076]

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[0077] and the calculated individual self-velocity estimate for the stationary target

[0078]

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[0079] From this, Equation 3

[0080]

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[0081] This is done using This results in a corrected angle estimate that can be taken as the actual azimuth angle of the target relative to the radar sensor S.

[0082]

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[0083] is calculated. However, for a moving target, the angle calculation 10 described above will result in an erroneous angle estimate, since the velocity component of the moving target is unknown and therefore cannot be taken into account. Therefore, for a moving target, the azimuth angle estimate determined during angle estimation 6

[0084]

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[0085] This does not improve the angle estimation, but it avoids erroneous angle estimation. Finally, the radial velocity estimate of the moving target is calculated by multiplying the relative velocity determined by Keystone processing using Doppler shift by 11.

[0086]

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[0087] from the combined self-velocity estimate determined by averaging 9 for a stationary target

[0088]

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[0089] can be calculated by subtracting 12 weighted by the cosine of the azimuth angle of this target. In Figure 5, the odometry trajectory T is determined using an odometry sensor in the conventional way. O and a trajectory T generated according to an embodiment of the method according to the invention. V Both trajectories match very well, thus demonstrating that autofocus using the method according to the invention provides accurate results.

Claims

1. A method for using a radar sensor (S) comprising a waveguide antenna array having at least two groups (104, 105) of antenna units (102) each having a plurality of antenna elements (101), the antenna elements (101) in each antenna unit (102) being arranged side by side in a first direction (R1), the antenna units (102) in the first group (104) being arranged offset from one another in a second direction (R2) perpendicular to the first direction (R1), and the antenna units (102) in the second group (105) being arranged offset from one another in the first direction (R1), the method comprising: [Equation 1] and the angle estimate of target (i) [Equation 2] The following steps are performed to determine - measuring (1) by said radar sensor (S) the distance (A) between said radar sensor (S) and each of said targets (i); said radar sensor (S) uses the Doppler effect to determine the relative velocity of each of said targets (i); [Equation 3] (1) measuring each of the An angle estimate characterizing the angle between the direction of the self-velocity of said radar sensor (S) and each of said targets (i). [Equation 4] and a step of estimating the angles (6) of the respective For each target (i), the individual self-velocity estimate of said radar sensor (S) [Equation 5] the relative velocity [Equation 6] and the angle estimate [Equation 7] and determining (7) using said individual own speed estimate [Equation 8] Let us denote the individual self-velocity estimate [Equation 9] The immobile target that exists together within the settable range (B) and its individual self-velocity estimate [Equation 10] a step of classifying and grouping (8) the moving targets that are outside said range (B); - Combined egospeed estimate [0011] the individual self-velocity estimate of the stationary target, [0012] and (9) determining - corrected angle estimates for said stationary targets [0013] the combined self-velocity estimate [0014] and each of the measured relative velocities [Equation 15] and determining (10) using The individual self-velocity estimates of the radar sensors (S) with synthetic apertures [0016] the relative velocity for each target (i) [Equation 17] and the angle estimate [Equation 18] When determining (7) using ｉ ) are taken into account, method.

2. 2. The method of claim 1, wherein the antenna units in the second group are additionally offset from one another in the second direction.

3. The settable range (B) is [Equation 19] 2. The method of claim 1, wherein the error tolerance is determined from the error in the measurement (1) of the angle (A) and the error in the angle estimate (6).

4. The averaged velocity values ​​for the stationary targets are combined into an ego-velocity estimate by weighted or unweighted averaging. [Equation 20] The method of claim 1 , wherein the value is determined as:

5. For a moving target, the angle estimate resulting from the angle estimation (6) [Equation 21] 2. The method of claim 1, wherein: is taken (11) as the angle estimate for the moving target.

6. A velocity estimate for a moving target is calculated based on the relative velocity of the target measured using the Doppler effect. [Equation 22] 10. The method of claim 1, wherein the value of the parameter is determined from the parameter.

7. 2. The method of claim 1, wherein the radar sensor (S) is a chirp sequence radar.

8. The relative velocity using the Doppler effect [Equation 23] 2. The method of claim 1, wherein said determining is performed by a Keystone process (2).

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