Angle-resolved radar sensor

Abstract

The invention relates to an angle-resolved radar sensor (8), comprising a transmitting and receiving device and an evaluation device (32) for determining positioning data of a target (24) reflecting radar radiation, the evaluation device (32) being configured to identify a multi-path scene in which the radar radiation is reflected by the target (24). A portion of the received signal representative of the target is based on the reflection of the transmitted and / or received signal at the reflection surface (42), characterized in that the evaluation device (32) is further configured to automatically determine the azimuth angle (gamma) of the reflection surface (42) or to read it from an external source, and determining a tangential velocity (v [theta]) of the target (24) based on the different Doppler shifts of the signal portions obtained on the different paths.

Description

Technical Field

[0001] The present invention relates to an angle-resolved radar sensor having transmitting and receiving means and an evaluation means for determining the location data of a target reflecting radar radiation, wherein the evaluation means is configured to identify multipath scenarios in which a portion of the received signal representing the target is based on the reflection of the transmitted and / or received signals on a reflecting surface.

[0002] In particular, the present invention relates to a radar sensor for detecting traffic conditions in a driver assistance system of a motor vehicle. Background Technology

[0003] In environmental monitoring within driver assistance systems, the distance, relative speed, azimuth, and elevation angles of the located target are crucial. Radar sensors, by measuring Doppler shift, can only measure the radial component of relative speed. However, the tangential component of speed is also important for identifying lane changes and crossing vehicles and pedestrians. This component can be determined by radar sensors, for example, by tracking the distance and azimuth of a target over multiple measurement cycles. Alternatively, multiple sensors can be used to measure radial speed from different directions. Other sensors, such as lidar and cameras, offer further alternatives for estimating tangential speed. Nevertheless, it is desirable to use radar sensors to measure tangential speed. Even when using radar sensors alongside lidar sensors or cameras in the same vehicle, the tangential speed measured by the radar sensors can be used to improve target fusion.

[0004] One known method for estimating tangential velocity using radar sensors within a single measurement cycle utilizes multiple reflection points of the same object with lateral offsets. For this to work, multiple reflection points with different azimuth angles must exist. However, even then, the lateral offsets are limited by the object size, making the estimation highly inaccurate.

[0005] A radar sensor of the type described at the beginning is known from DE 10 2021 212 376 A1, which can also identify multipath scenarios in which signals propagating from the radar sensor to the target or signals returning from the target to the radar sensor, or both, are reflected at a wall (e.g., the surface of a guardrail). In addition to the direct signal path and the reflected path, there are two so-called intersecting paths, where only the outgoing beam or only the returning beam is reflected. Using a MIMO radar with at least three transmit antennas and at least three receive antennas, the signals from the four possible paths can be separated, thus distinguishing real targets from false targets generated by reflections, and enabling more accurate range, velocity, and angle measurements.

[0006] Patent application DE102022209813.7 discloses a method for determining the spatial orientation of a reflective surface using such a radar sensor. Alternatively, the reflective surface can be identified and the reflection assigned to a direct object using an estimate of roadside buildings. Here, roadside buildings can be detected, for example, by evaluating stationary targets as measured by the radar sensor, or, for example, by fusion with video or lidar data. Another method for locating reflective surfaces is described at: https: / / de.mathworks.com / help / driving / ug / multipath-radar-detection-and-tracking.html. Summary of the Invention

[0007] The purpose of this invention is to achieve accurate estimation of tangential velocity in a single measurement cycle using only a single (MIMO) radar sensor.

[0008] According to the present invention, this objective is achieved by further configuring the evaluation device to determine the azimuth angle of the reflecting surface itself or to read the azimuth angle from an external source, and to determine the tangential velocity of the target based on the different Doppler frequency shifts of the signal portions obtained on different paths.

[0009] Here, the distance, velocity, and angle information from the direct path and reflected path of the same object are combined. The aforementioned radar sensors, according to existing technology, have enabled the identification and allocation of reflections and the determination of the angle of the reflecting mirror. Under these conditions, it is possible to utilize the fact that the tangential component of the target velocity affects the Doppler frequency shift of the radar signal in different ways along different signal paths, thereby allowing the tangential velocity to be determined based on the measured Doppler frequency shift.

[0010] Advantageous configurations and extensions of the invention are derived from the dependent claims. Attached Figure Description

[0011] An embodiment will now be described in detail with reference to the accompanying drawings. The drawings show: Figure 1 A block diagram of a radar sensor is shown; Figure 2 A schematic diagram illustrating a scenario with multipath propagation is shown; Figure 3 A flowchart of the method according to the present invention is shown; Figure 4 Examples showing signal spectrum; and Figure 4 and 5 A schematic diagram illustrating the method according to the present invention is shown. Detailed Implementation

[0012] Figure 1 The construction of the MIMO (Multiple Input Multiple Output) radar sensor 8 is illustrated schematically and in a simplified manner.

[0013] Frequency modulation device 10 controls high-frequency oscillator 12, which generates a signal sequence in the form of frequency ramps for multiple transmitting antennas 14. An amplifier 16 is arranged in each of the multiple transmitting channels to block or amplify the signal before it is forwarded to the corresponding antenna. Oscillator 12 and amplifier 16 are controlled by multiplexing device 18, for example, according to a time-division and frequency-division multiplexing scheme, such that each transmitting antenna 14 transmits a frequency-modulated signal in a specific frequency subband within a specific time slot.

[0014] The signal transmitted and reflected by the target 24 (e.g., a reflection point of a vehicle) is received by multiple receiving antennas 26 and mixed with a portion of the signal from the high-frequency oscillator 12 via a mixer 28 in each receiving channel, thereby downconverting it to a low-frequency range. It is then converted from analog to digital in a conventional manner by an analog-to-digital converter 30. The digitized signal is subsequently further processed in a digital evaluation device 32. The radar sensor can operate, for example, based on the principle of fast chirp. The frequency ramp of the transmitted signal is very steep, such that the frequency of the low-frequency (beat frequency) signal obtained after mixing depends virtually only on the signal's propagation time, and thus on the distance to the target, and only a negligible small Doppler shift even when the target moves radially. When multiple such ramps are transmitted rapidly and continuously, the radial movement of the target causes a phase shift between the ramps. By performing a Fourier transform on the ramp sequence, the Doppler shift can be determined, thereby determining the target's radial velocity.

[0015] In evaluation device 32, a two-dimensional spectrum in the distance and relative velocity dimensions is first calculated using a Fourier transform in a known manner. Based on this spectrum, individual targets can be identified and their distance and relative velocity determined. In the subsequent evaluation phase, angle estimation is performed.

[0016] Transmitting antenna 14 forms a transmitting array with n transmitting channels TX1, ..., TXn, and receiving antenna 26 forms a receiving array with k receiving channels RX1, ..., RXk. For example, both arrays are two-dimensional, thus enabling MIMO angle measurements in azimuth and elevation.

[0017] Figure 2The diagram illustrates a scenario characterized by multipath propagation. The signal transmitted from radar sensor 8 can propagate to target 24 not only via direct path 38, but also via indirect path 40, which first reaches reflector surface 42 (e.g., a guardrail) and then deflects back to target 24. Similarly, the signal reflected at target 24 can propagate to radar sensor 8 not only via direct path 44, but also via indirect path 46, where it is also reflected at reflector surface 42, thus presenting a false target (Scheinziel) 24' to the radar sensor. These two paths, where the signal travels via direct path 38 or 44 in one direction and indirect path 40 or 46 in the opposite direction, are called intersecting paths. The angle estimation in evaluation device 32 is based on an intersecting path model, which simulates not only the propagation of the signal along the direct and indirect paths, but also the propagation along the intersecting paths.

[0018] The details of the evaluation method based on this model are described in DE102021212376A1. The range, radial velocity, and angular data obtained in this manner form the basis of the method for determining the tangential velocity of target 24. The main steps of this method are as follows: Figure 3 As shown. In step S1, multipath estimation is performed based on the cross-path model. Depending on the radar sensor's resolution in the range and velocity dimensions, the signals obtained for a single target and related false targets may reside in the same range / velocity cell or two different cells after the two-dimensional Fourier transform. Especially in the former case, there may be superposition of signals from the same target but propagating through different paths and therefore having different propagation times.

[0019] Figure 4 An example of a spectrum obtained in this way is shown. Figure 4 Curve 48 in the diagram gives the received signal power P as a function of the signal propagation length A (proportional to frequency). Curve 48 is formed by the superposition of four signal components, represented by curves 50, 52, and 54. Curve 50 represents a signal component that propagates through direct path 38 in the transmitting direction and through direct path 44 in the receiving direction; therefore, its maximum value occurs at a relatively small signal propagation length A. Curve 54 represents a signal component that propagates through indirect paths 40 and 46 in both directions; therefore, its maximum value occurs at a much larger signal propagation length. Curve 52 represents two essentially identical signal components, corresponding to two intersecting paths (38 and 46, and 40 and 44). The maximum values ​​of these curves occur at a signal propagation length equal to the average of the positions of the maximum values ​​of curves 50 and 54.

[0020] In step S2, the received spectrum is analyzed and checked for characteristics of a multipath scene, and therefore can be used as follows: Figure 4 The signal is separated into four signal components as shown.

[0021] After signal separation in step S2, the angle γ is determined in step S3. This angle indicates the orientation of the reflective surface 42, that is, the azimuth angle formed by the reflective surface 42 and the optical axis of the radar sensor. Figure 2 This explains the special case where γ=0. The more general case where γ is not equal to 0 is... Figure 5 The optical axis of radar sensor 8 is denoted by 56. Due to the tilt of reflector 42, the positions of target 24 and the false target 24' generated by reflection are not symmetrical about optical axis 56, but about line n, which represents the orientation of reflector 42 at reflection point R, i.e., where the radiation from radar sensor 8 is reflected. The (polar) coordinates of target 24, i.e., range d and azimuth θ, can be determined by evaluating the optical axis of radar sensor 8. Figure 4 The signal components represented by curve 50 are used to determine the coordinates of the false target 24', namely the false range d' (scheinbare Distanz) and the false azimuth θ' (scheinbare Azimutwinkel), which can be determined by evaluating the signal components represented by curve 50. Figure 4 The signal component represented by curve 54 is used to determine the false range d'. The false range d' is composed of the distance d1' from the radar sensor to the reflection point R and the distance d" from the reflection point R to the target 24 or the false target 24' (the two distances are equal due to symmetry). Now, the orientation of the reflector 42 is obtained by drawing a straight line g connecting the target 24 and the false target 24', and then drawing a perpendicular bisector (straight line n) on the line segment from 24 to 24'. The azimuth angle γ can be determined in this way.

[0022] Then, in step S4, the tangential velocity v_θ is calculated, which should now be done using... Figure 6 and Figure 7 The vector graphics shown are used for illustration. For simplicity, these vector graphics are explained according to... Figure 2 The special case where γ=0. Figure 6 The image shows radar sensor 8, target 24, decoy target 24', signal path and perpendicular bisector n, as well as the velocity vector v of target 24 and its tangential component, i.e., tangential velocity v_θ. For the radial component, two distinct vectors are obtained: v_r for the direct path and v_r' for the indirect path. Figure 7 The vectors involved are shown in a magnified view.

[0023] Two vectors, v_r and v_r', form an angle with each other. exist Figure 6 and Figure 7 In the simplified case shown, γ=0, applicable Figure 7 Two straight lines, q and q', are drawn that intersect at the target point of vector v_r. q is perpendicular to v_r, and q' is perpendicular to v_r'. Therefore, these two lines also form an angle α with each other. These two lines, together with vector v, form a triangle with height h. The side length of this triangle connecting the target points of v and v_r is v_θ. Therefore, it applies to: and The azimuth angle γ of the perpendicular bisector n can be calculated as follows: By substituting this value into equation (1), we obtain the angle α, and then obtain the magnitude of the radial velocity v_θ according to equation (4).

[0024] In many cases, such as in the reflection of guardrails, the special case of γ=0 is applied, thus simplifying the calculation.

Claims

1. An angle-resolved radar sensor (8), having a transmitting and receiving device and an evaluation device (32) for determining the positioning data of a target (24) reflecting radar radiation, wherein, The evaluation device (32) is configured to identify a multipath scenario in which a portion of the received signal representing the target is based on the reflection of the transmitted and / or received signal at the reflector (42). The evaluation device (32) is further configured to determine the azimuth angle (γ) of the reflector (42) by itself or by reading the azimuth angle from an external source, and to determine the tangential velocity (v_θ) of the target (24) based on the different Doppler frequency shifts of the signal portions obtained on different paths.

2. The radar sensor according to claim 1, wherein, The radar sensor (8) is a MIMO radar sensor having at least three transmitting antennas (14) and at least three receiving antennas (26) for azimuth angle measurement.

3. The radar sensor according to claim 1 or 2, wherein, The evaluation device (32) is configured to calculate the azimuth (γ) of the reflecting surface (42) based on the distance and angle data of the real target (24) and the associated false target (24') generated by reflection.

4. A software product having computer-readable program code, which, when loaded in the computer of the radar sensor evaluation device (32), causes the evaluation device to perform the function of the radar sensor according to any one of claims 1 to 3.

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