Method for determining own velocity estimate and angle estimate of a target

Abstract

A method for determining self-velocity estimates and angle estimates of targets by means of a radar sensor having a synthetic aperture. By means of the sensor, the distance to the targets is measured and the relative velocity of the targets is measured by means of the Doppler effect. An angle estimate of the angle between the direction of the self-velocity of the sensor and the targets is carried out. By means of the relative velocities and the angle estimates, individual self-velocity estimates of the sensor are determined for each target, which are classified and divided into a group of individual self-velocity estimates with respect to stationary targets, whose individual self-velocity estimates lie within a predefinable range (B) from one another, and with respect to moving targets, whose individual self-velocity estimates lie outside the range. A combined self-velocity estimate is determined from the individual self-velocity estimates. A corrected angle estimate is determined from the combined self-velocity estimate and the relative velocities.

Description

Technical Field

[0001] This invention relates to a method for determining the velocity and angle estimates of a target using a radar sensor with synthetic aperture radar. The invention also relates to a radar sensor configured for implementing the method according to the invention. Background Technology

[0002] Radar systems used to measure distance, relative speed, and angle are increasingly being used in motor vehicles for safety and comfort features. Today, radar with synthetic aperture (SAR) is particularly prevalent for this purpose. The principle of SAR enables exceptionally accurate angle measurements even with the inherent motion of the radar sensor. SAR utilizes the fact that, due to the inherent motion of the radar sensor, the transmitting and receiving antennas are at different locations at each measurement moment. These measurements are then processed into a synthetic aperture. In analysis, this can be equated to a large antenna aperture along the driving trajectory. This achieves a large synthetic aperture that would be impractical or even impossible with a true antenna aperture due to the large number of antenna elements required. With SAR, using a single transmitting antenna and a single receiving antenna, it is possible to achieve a resolution in angle measurements that is unattainable with a true antenna aperture.

[0003] To analyze the measured radar signal as a synthetic aperture radar (SAR), it is typically assumed that the radar environment is stationary. Additionally, the free motion of the radar sensor and the individual measured positions should be known. The radar trajectory is incorporated into the SAR analysis algorithm and forms the basis for SAR image calculation. Depending on the analysis algorithm, a more accurate trajectory estimate may be sufficient to calculate the SAR image. Here, it is generally assumed that the trajectory is linear, and more complex trajectories cannot be plotted.

[0004] Modern radar systems in the automotive field typically use frequency-modulated continuous wave (FMCW) radar with a rapidly rising ramp—so-called fast linear frequency modulation—where multiple linear frequency ramps with the same steep slope operate sequentially. The mixing of the transmitted and received signals yields a low-frequency signal (called the beat frequency), the frequency of which is proportional to the range. The system is typically designed so that the Doppler frequency component of the beat frequency becomes negligible. The obtained range information is largely unique and unambiguous. Furthermore, the Doppler frequency shift can be determined by observing the phase evolution of the complex range signal over time on the ramps, and the relative velocity can be derived from this. The determination of range and relative velocity are performed independently of each other. Typically, a two-dimensional Fourier transform is used for this.

[0005] Conventional SAR analysis is based on stationary targets. Moving targets, which do not satisfy this assumption, result in erroneous, angularly displaced, and unclear imaging in SAR images. However, moving targets are equally interesting in the case of motor vehicles (e.g., to avoid collisions with them). To estimate the radar sensor's free trajectory or free velocity, two approaches are known: one is to use external sensors—such as inertial measurement units (IMUs) or odometry sensors; the other is to use computationally expensive autofocus algorithms, which are unsuitable for real-time processing. Summary of the Invention

[0006] A method is proposed for determining the intrinsic velocity and angle estimates of multiple targets in a surrounding environment using a radar sensor with synthetic aperture radar. This radar sensor can be used, for example, in a vehicle. A distinction is then made between stationary targets (also called static targets) and moving targets (also called dynamic targets). Stationary targets are objects in the surrounding environment that do not move, such as buildings, trees, roads, and infrastructure along roads. Moving targets are objects in the surrounding environment that are in motion, such as other vehicles, pedestrians, and other road users.

[0007] The radar sensor moves and emits multiple measurement signals. The relative velocity for each target is determined from the emitted and received signals. To determine the relative velocity, the Doppler effect is analyzed and processed in the measurement signals, and in particular, the Doppler frequency shift is determined. Furthermore, the distance between the radar sensor with synthetic aperture and the target is also determined from the emitted and received signals. This can be done, for example, through Fourier processing. To identify the target in the measurement, detection is performed with a constant false alarm rate (CFAR).

[0008] A coarse angle estimation is then performed. Here, an angle estimate is estimated separately for each target, representing the target angle between the direction of the radar sensor's own velocity—i.e., the direction of the radar sensor's motion ("forward direction")—and the corresponding target. Angle estimation can be performed, for example, using digital beamforming. For this purpose, the radar sensor has at least one additional receive channel and / or at least one additional transmit channel. Preferably, the angle estimate directly indicates the target angle. However, the target angle can also be derived indirectly from the angle estimate through transformation or from mathematical relations. Since the angle estimate is further processed afterward, it can be significantly less accurate than a conventional angle measurement.

[0009] Through retroprojection, an individual intrinsic velocity estimate for a radar sensor with synthetic aperture is calculated separately for each target using relative velocity and angle estimates. That is, for each target, the measured or estimated values ​​are used to obtain an individual intrinsic velocity estimate for the radar sensor with synthetic aperture. Therefore, typically multiple individual intrinsic velocity estimates are obtained, which are thus related to the target's velocity. For stationary targets, the individual intrinsic velocity estimates are close to each other because the relative velocity between the target and the radar sensor is proportional to the radar sensor's intrinsic velocity and the target angle. However, for moving targets, the individual intrinsic velocity estimates differ significantly from each other because the relative velocity is related to the target velocity in addition to the radar sensor's intrinsic velocity and the target angle. Furthermore, in typical cases, there are significantly more stationary targets in the surrounding environment than moving targets with the same relative velocity relative to the radar sensor, and moving targets normally have different velocities from each other.

[0010] Therefore, it is possible to classify and segment individual self-velocity estimates, especially through clustering. To this end, a region is defined for each individual self-velocity estimate, which allows for differentiation between stationary and moving targets. Individual self-velocity estimates that are mutually surrounding each other within a predefined range are assigned to stationary targets. Individual self-velocity estimates outside this region are assigned to moving targets. Thus, moving targets (MTI – moving target indication) can be identified. The separately calculated individual self-velocity estimates can be recorded, for example, in a histogram for classification.

[0011] Then, depending on the allocation, the individual intrinsic velocity estimates are analyzed and processed separately. For a stationary target, a combined intrinsic velocity estimate is obtained from the individual intrinsic velocity estimates allocated to the stationary target. The combined intrinsic velocity estimate can be considered as the actual intrinsic velocity of the radar sensor, since, in principle, it is calculated only from a stationary target (autofocus). Furthermore, a corrected angle estimate of the stationary target is calculated using the combined intrinsic velocity estimate and the corresponding measured relative velocity. The corrected angle estimate can be considered as the actual angle of the target relative to the radar sensor.

[0012] The combined free velocity estimate and the corrected angle estimate obtained in this way are more accurate than those obtained conventionally using radar with synthetic aperture, because moving targets are filtered out during the calculation.

[0013] This method can also directly determine the intrinsic speed and angle estimates from measurements without the need for additional sensors, such as IMUs or odometer sensors. Odometer sensors typically used in vehicles are often positioned too far from radar sensors and perform too few measurements in each time interval.

[0014] Advantageously, the predefined range used in the classification and division of individual velocity estimates is the measurement error tolerance range. This range is derived from the error in the measurement of relative velocity and the error in the angle estimation. This ensures that the division is specifically performed within the limits of measurement error and thus provides the maximum possible selectivity.

[0015] Preferably, angle estimation is performed for each target using multiple receive and / or transmit channels at different locations. Specifically, a sensor array with multiple receive and / or transmit channels is configured for this purpose. This allows digital beamforming to be performed in a simple manner.

[0016] To determine the portfolio's own velocity estimate, the average velocity value of the individual own velocity estimates can be calculated. Here, classical averaging, such as arithmetic mean, weighted average, such as weighted by weights related to the signal-to-noise ratio, determining the maximum value in the histogram, and finding the median can be performed.

[0017] Preferably, the system also calculates corresponding angle and velocity estimates for the moving target. However, since the velocity of the moving target is unknown, the above analysis will result in erroneous angle estimates. As the angle estimate for the corresponding moving target, the angle estimate already obtained in the above angle estimation for that moving target can be used. This avoids erroneous angle estimates, although no improved angle estimation is achieved. It is particularly advantageous to use the aforementioned multiple receiving and / or transmitting channels for this purpose. Furthermore, the radial velocity estimate for the corresponding moving target can be obtained from the relative velocity measured using Doppler frequency shift. For this purpose, the combined free velocity estimate obtained above is considered the radar's free velocity and is subtracted from the relative velocity after being weighted by the target angle.

[0018] Not only is the motion of the radar assumed, but the motion of the moving target is also assumed to be two-dimensional in a plane. However, the target measured by the sensor may be at different heights relative to this plane. This is especially likely to occur when, for example, only a portion of the object is detected. In this case, the elevation angle between the plane and the target can be determined. Preferably, for each target, this elevation angle is taken into account when determining the individual intrinsic velocity estimate of the radar sensor with synthetic aperture using relative velocity and the estimated angle.

[0019] Preferably, the radar sensor is a chirp-sequenz radar, which acts as a frequency-modulated continuous wave radar and outputs a linear signal (chirp-signal) with a rapidly rising ramp. This allows for easy range measurement in a manner known per se. Furthermore, the Doppler effect, particularly the Doppler frequency shift, can be determined from the phase evolution of the complex range signal over time on the ramp, thereby enabling the measurement of relative velocity.

[0020] To determine relative velocity using the Doppler effect, known methods can be employed. The Keystone treatment (CZT) is preferred here because it is computationally efficient and can compensate for migrations.

[0021] The computer program is configured to perform each step of the method, particularly when implemented on a computing or control device of a radar sensor. This computer program enables the implementation of the method in a conventional radar sensor. For this purpose, the computer program is stored on a machine-readable storage medium.

[0022] In addition, a radar sensor with synthetic aperture is provided, which has a sensor array and is configured to determine the target's free velocity estimate and angle estimate by means of the method. Attached Figure Description

[0023] Embodiments of the present invention are shown in the accompanying drawings and described in more detail in the following description.

[0024] Figure 1 A schematic diagram of a traffic situation is shown, illustrating different targets and their corresponding angles and relative speeds, and using a radar sensor with synthetic aperture according to the invention.

[0025] Figure 2 A flowchart illustrating an embodiment of the method according to the present invention is shown.

[0026] Figure 3a This diagram shows the distribution of individual autonomous velocity estimates from radar sensors for different targets.

[0027] Figure 3b Showing the use of Figure 3a Histogram of the distribution in.

[0028] Figure 4 The diagram shows the location of a trajectory generated based on an embodiment of the method according to the invention and a trajectory generated by means of an odometer sensor. Detailed Implementation

[0029] Figure 1 A schematic diagram of a traffic situation is shown, featuring vehicle F and several other vehicles. Vehicle F is equipped with a radar sensor S with synthetic aperture according to the invention. The other vehicles are referred to as targets Z1 to Z3. Typically, other targets are present in the surrounding environment, not shown here, such as buildings, road infrastructure (i.e., traffic signs, guardrails, etc.), or the road itself. Vehicle F, and therefore the radar sensor S, travels at its own speed v. ego Moving along a straight line. Starting from radar sensor S, the inherent velocity v is shown for each of the shown targets Z1, Z2, and Z3. ego The azimuth angles α1, α2, and α3 between the direction of the target and the direction of the corresponding target Z1, Z2, and Z3 are shown. Furthermore, the relative velocities v of each target Z1, Z2, and Z3 relative to the radar sensor S are also shown. rel,1 v rel,2 v rel,3 If one of the targets, for example, target Z1, is a stationary target, that is, it is not moving, then the corresponding relative velocity v rel,1 It is the inherent velocity v of the radar sensor S. ego The projection onto the corresponding azimuth angle α1 is given. Figure 1 The projection is shown for all three targets Z1, Z2, and Z3. In the case of a moving target, such as target Z2 moving at an unknown speed, the speed of target Z2 is the relative speed v. rel,2 Part of and the measured relative velocity v rel,2 There is a deviation from the projection.

[0030] Figure 2 A flowchart illustrating one embodiment of the method according to the invention is shown. Multiple targets are studied here, generally labeled i. Measurement 1 is performed during the movement of the vehicle F and the radar sensor S. The radar sensor S is constructed as a sensor array and has multiple transmit channels and, if necessary, multiple receive channels. Measurement 1 is performed using frequency-modulated continuous wave radar modulation (FMCW), in which a linearly modulated signal with a rapidly rising linear frequency ramp of the same slope is output at predetermined time intervals. The reflected signal is recorded and processed as the received signal. The instantaneous mixing of the transmitted and received signals yields a low-frequency beat signal whose frequency is proportional to the distance to target i. Measurement 1 is performed such that the Doppler effect, or Doppler frequency shift, is negligible in the beat frequency or is taken into account in the analysis.

[0031] Keystone processing 2 is then performed. Here, Doppler frequency shift or Doppler frequency estimation is performed by determining the phase evolution of the complex measurement signal over time on the frequency ramp, wherein a corresponding linear distance change (migration) is compensated for for each estimate. The relative velocity of each target i is thus obtained. Next, distance estimation is performed using conventional Fourier processing, particularly the Fast Fourier Transform (FFT) from the time domain to the frequency domain. The resulting two-dimensional spectra (range and relative velocity) of each transmit-receive channel combination are incoherently averaged. To do this, the magnitude of each individual spectrum in these spectra is calculated, and these magnitudes or their squares are then summed. To identify targets in these measurements, detection is performed with a constant false alarm rate (CFAR).

[0032] In addition, angle estimation 6 is performed, in which azimuth angle estimates are obtained for these targets. Azimuth angle estimate The azimuth angle represents the distance between the measurement axis of radar sensor S and target i, and therefore also reflects the installation status of radar sensor S. Since the installation status is known, the estimated azimuth angle can be obtained through coordinate transformation. Converted to its own speed v ego The azimuth angle α between the direction of the target i and the direction of the target i i The estimated value. For in Figure 1 In the case shown, the measuring axis is perpendicular to the vehicle's free velocity v. ego The direction of θ. Therefore, the following relationship exists: θ i =90-α i To perform angle estimation, digital beamforming is used. Here, simultaneous measurements are performed and the phase difference is calculated via multiple receive and transmit channels at different locations on the sensor array, thereby obtaining the azimuth angle estimate. The free velocity v of radar sensor S ego The effect is negligible for this type of angle estimation, and therefore related to the inherent velocity v of the radar sensor S. ego Obtaining the azimuth angle estimate irrelevantly When performing angle estimation 6, the elevation angle φ between the plane in which the vehicle moves and the height of the detected target i is also calculated. i .

[0033] Therefore, the relative velocity is known for each target i. Azimuth angle estimate And, if necessary, the elevation angle φ i Therefore, for each target i, the individual's own velocity is estimated separately according to Formula 1. Perform calculation 7:

[0034]

[0035] exist Figure 3a The figure shows the individual free velocity estimates calculated in this way for some target i. Figure 3b The histogram shows the free velocity estimates for several different individuals. Plot the obtained quantity n in both graphs. The two graphs show the estimated individual velocity. Accumulation occurs within range B. Under typical traffic conditions, there are significantly more stationary targets than moving targets with the same radial relative velocity to radar sensor S.

[0036] refer to Figure 2 Clustering is performed (8), where the estimated free velocity of individuals within range B is... Assigned to stationary targets, and include estimates of individual free velocity outside range B. Assigned to moving targets. Therefore, moving targets (MTI - moving target indication) are identified and distinguished from stationary targets. Range B is defined by the errors in Measurement 1 and Angle Estimation 6 and describes the range of error tolerances.

[0037] Estimates of the individual's own velocity assigned to a stationary target, i.e., within range B. Calculate the average of 9 to obtain an estimate of the combined free velocity. Different methods of averaging can be performed, such as classical averaging, arithmetic averaging, weighted averaging (e.g., weighted by weights related to signal-to-noise ratio), determining the maximum value in a histogram, and finding the median. This is due to the inherent velocity estimate of the combination. In principle, it is calculated in the absence of a moving target, therefore it can be regarded as the actual free velocity of the radar sensor S. This achieves autofocus. For each stationary target, the relative velocity obtained from the Keystone processing 2 using the Doppler effect is also calculated using Formula 2 for that stationary target. And the estimated value of the individual's own velocity calculated for this stationary target. Perform angle calculation 10:

[0038]

[0039] Therefore, the corrected angle estimate is calculated. It can be regarded as the actual azimuth angle of the target relative to the radar sensor S.

[0040] However, for moving targets, the angle calculation 10 described above will lead to an incorrect angle estimate because the velocity component of the moving target is unknown and therefore cannot be taken into account. Therefore, for moving targets, the azimuth angle estimate obtained in angle estimation 6 is used instead. Therefore, although an improved angle estimation was not achieved, erroneous angle estimations were avoided. Finally, the radial velocity estimate of the 12 moving targets can be calculated by taking the relative velocity obtained through Keystone processing 2 with the aid of Doppler frequency shift. Subtract the estimated free velocity of the combination obtained by averaging 9 for a stationary target.

[0041] exist Figure 4 The figure shows the odometer trajectory T obtained using a conventional method with the aid of an odometer sensor. O The trajectory T generated based on an embodiment of the method according to the invention V A comparison between the two trajectories reveals that they are very well aligned, thus providing accurate results for autofocus using the method according to the invention.

Claims

1. A method for determining a target using a radar sensor (S) with synthetic aperture (S) i The estimated free velocity of ) ego,komb ) and angle estimates ( korr,i ) method, The method comprises the following steps: - Using the radar sensor (S) with synthetic aperture, measurements are taken between (1) the radar sensor (S) with synthetic aperture and each target ( i The distance (A) between them; - Using the radar sensor (S) with synthetic aperture, the Doppler effect is used to measure (1) each target ( i The relative velocity of ) rel,i ); - Perform angle estimation values ​​separately ( i Angle estimation (6), the angle estimate representing the direction of the native velocity of the radar sensor (S) with synthetic aperture relative to the corresponding target ( i The angle between them; - For each target ( i ), by means of the relative velocity ( rel,i ) and the estimated angle ( i To obtain the individual intrinsic velocity estimate of the radar sensor (S) with synthetic aperture (S), ego,i ), without the need for additional sensors; - Estimates of the individual's own velocity for stationary and moving targets ( ego,i ) are classified and divided (8), the individual free velocity estimate of the stationary target ( ego,i The moving targets are located within a pre-defined range (B), and the individual free velocity estimates of the moving targets are ( ego,i It is located outside the range (B); - Estimated individual velocity of the stationary target ( ego,i ) Obtain the estimated value of the combined free velocity ( ego,komb );and - Using the inherent velocity estimate of the combination ( ego,komb ) and the corresponding measured relative velocity ( rel,i ) Obtain the corrected angle estimate of the stationary target. korr,i ).

2. The method according to claim 1, characterized in that, The predefined range (B) is determined by the relative velocity ( rel,i The error tolerance range is the range of the measurement (1) performed and the error obtained from the angle estimation (6).

3. The method according to claim 1 or 2, characterized in that, For each target, multiple receiving and / or transmitting channels at different locations are used. i (6) Perform the angle estimation.

4. The method according to claim 1 or 2, characterized in that, The average velocity of the stationary target is determined by weighted or unweighted averaging as the estimated velocity of the combination. ego,komb ).

5. The method according to claim 1 or 2, characterized in that, For a moving target, the angle estimate obtained from the angle estimate (6) is used (11). i ) is used as the angle estimate of the moving target.

6. The method according to claim 1 or 2, characterized in that, The relative velocity of a moving target as measured by the Doppler effect. rel,i ) Obtain the velocity estimate of the moving target.

7. The method according to claim 1 or 2, characterized in that, For each target ( i ), by means of the relative velocity ( rel,i ) and the estimated angle ( i To obtain the individual intrinsic velocity estimate of the radar sensor (S) with synthetic aperture (S), ego,i When considering the elevation angle ( ).

8. The method according to claim 1 or 2, characterized in that, The radar sensor (S) is a linear frequency modulated sequence radar.

9. The method according to claim 1 or 2, characterized in that, The relative velocity was obtained by using the Doppler effect and Keystone processing (2). rel,i The retrieval of ).

10. A computer program configured to perform each step of the method according to any one of claims 1 to 9.

11. A machine-readable storage medium on which a computer program according to claim 10 is stored.

12. A radar sensor (S) having a synthetic aperture, the radar sensor having a sensor array and configured to determine an intrinsic velocity estimate by means of the method according to any one of claims 1 to 9. ego,komb ) and angle estimates ( korr,i ).

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