Radar system for 3D self-motion estimation

Abstract

The invention relates to a radar-based system (10) for aided driving or automated driving in a vehicle (1), comprising a processor configured to receive signals from at least one sensor (3, 3a, 3b, 3c) of the vehicle (1) configured to detect objects (T1-T9) outside the vehicle (1), the signals comprise position information and a radial velocity of each of the at least three objects (T1-T9) relative to the at least one sensor (3, 3a, 3b, 3c), and the velocity of the vehicle (1) is determined on the basis of the received signals.

Description

Technical Field

[0001] The present invention relates to a radar-based system for assisting driving or autonomous driving in a vehicle, a vehicle, a computer-implemented method for assisting driving or autonomous driving of a vehicle, a computer program, and a computer-readable storage medium. Background Art

[0002] Automotive 3D radars do not always correctly provide three-dimensional radar ranging and direction. Thus, calibration data is very important for the 3D radar of the host vehicle, which can be used to provide correction of measurement data or perform uncertainty calculations. To provide calibration data for the 3D radar in any moving state of the vehicle, complete 3D motion data including three-axis linear velocity and three-axis angular velocity is required as ground truth.

[0003] Advanced inertial measurement units (IMUs), such as costly ADMA sensors, can measure the motion of a vehicle on three axes even during GPS signal loss. They provide dynamic attitude and heading angle determination, as well as accurate acceleration, velocity, and position data.

[0004] However, ADMA sensors are quite expensive. For vehicles not equipped with ADMA sensors, it is difficult to provide continuous and accurate calibration data for the 3D radar.

[0005] In addition, sometimes even if an autonomous vehicle is already equipped with an ADMA sensor, it is still desirable to adopt an alternative 3D self-motion sensing method as a verification of the actually performed radar calibration.

[0006] US2021 / 0124033A1 discloses a method for calibrating vehicle sensors of a motor vehicle. The method includes the following steps: determining sensor data at a plurality of measurement times by vehicle sensors while the motor vehicle moves relative to objects around the motor vehicle; calculating an object position of the objects based on the determined sensor data; calculating a Hough transform based on the calculated object position; determining an alignment of the vehicle sensors relative to the drive axis of the motor vehicle based on the calculated Hough transform; and calibrating the vehicle sensors according to the determined alignment of the vehicle sensors relative to the drive axis of the motor vehicle.

[0007] US2017 / 0212215A1 discloses a method and apparatus for determining misalignment of a radar sensor unit mounted on a vehicle, including providing a target on an alignment device. The vehicle is located at a predetermined position on a test stand and maintains a precise given distance from the alignment device. The actual positions and distances between the targets and the actual positions and distances from the radar sensor unit of the vehicle at the test stand are known and pre-stored. At least one target is at a greater distance from the vehicle than the other targets. The targets receive and return radar waves from the radar sensor unit. The radar sensor unit determines the positions and distances of the targets and compares them with the given or actual positions and distances of the targets to determine the misalignment of the radar sensor unit. A calibration procedure automatically calibrates the azimuth and elevation angles to adjust the misalignment. SUMMARY OF THE INVENTION

[0008] The present invention provides a radar-based system for assisted or autonomous driving in a vehicle according to claim 1, a vehicle according to claim 5, a computer-implemented method for assisted or autonomous driving according to claim 6, a computer program according to claim 9, and a computer-readable storage medium according to claim 10.

[0009] Further advantageous embodiments and improvements of the present invention are listed in the dependent claims.

[0010] According to a first aspect, the present invention provides a radar-based system for assisted or autonomous driving in a vehicle, including a processor configured to: be able to receive signals from at least one sensor of the vehicle configured to be able to detect objects outside the vehicle, wherein the signals include position information and radial velocity of each of at least three objects relative to the at least one sensor, and determine the speed of the vehicle based on the received signals.

[0011] Advantageously, if there are multiple stationary objects, especially more than two stationary objects, around the 3D radar of a self-driving vehicle moving in a straight line, the radar can dynamically estimate its own velocity vector without any time-consuming object tracking. The 3D velocity corresponding to the velocity vector can be calculated from a single measurement containing the 3D position information and Doppler / radial velocity of the target / object.

[0012] The relative velocity of a stationary target is the additive inverse of the velocity of the moving radar. In a single measurement, the velocity is the same for all stationary targets. Thus, a system of equations can be used for each measurement point corresponding to the detected target / object. The system of equations is linear in the elements of the velocity vector, and thus they can be estimated using linear regression.

[0013] The 3D velocity vector contains three unknown variables, which means that at least three stationary targets must be measured in a single radar scan to perform the estimation process. Considering the existence of measurement errors, in order to obtain a more accurate solution, it is beneficial to use more stationary objects as measurement points because linear regression provides the optimal solution (with the minimum mean square error).

[0014] In a preferred embodiment, the processor is further configured to be capable of receiving signals from each of at least three sensors of the vehicle configured to be capable of detecting objects outside the vehicle, wherein the signals from each of the at least three sensors include position information and radial velocity of each of at least three objects relative to the corresponding sensor, and determining the linear velocity and angular velocity of the vehicle based on the received signals, the relative position of each of the at least three sensors relative to the vehicle, and the rotation matrix from the vehicle to each of the at least three sensors.

[0015] If the vehicle is not in a straight driving state, but is turning and / or starting to go uphill / downhill and / or encountering a mountain road or a construction site with an uneven road surface, the vehicle not only has a linear velocity but also an angular velocity, and the measurement data thereof may also need to be corrected.

[0016] In this case, another system of equations can be used for the host vehicle including at least three radar sensors. In particular, each sensor can detect three different stationary objects around the vehicle. Therefore, the elements of the linear velocity vector and the angular velocity vector can be estimated by performing linear regression on the system of equations with the stationary object data measured by at least three synchronized radars.

[0017] In other words, in an environment containing many stationary targets, the vehicle can use the solution provided by the present invention to estimate its complete 3D self-motion state through three installed radars.

[0018] In addition, the present invention provides an alternative 3D self-motion sensing method as a verification of the actual radar calibration performed by, for example, the ADMA sensor of an autonomous vehicle.

[0019] In a further preferred embodiment, the position information includes the azimuth angle, elevation angle, and distance of the object relative to the corresponding sensor.

[0020] In a further preferred embodiment, the angular velocity of the vehicle includes a yaw angle and / or a pitch angle.

[0021] In most cases, if a vehicle is moving on a road but not moving directly forward / backward, it turns left, turns right, or turns around. In this regard, the yaw angle, which is one of the vehicle motion data, is measured, and the measured yaw angle must be corrected as needed. For example, on a rural road, a vehicle may often encounter uphill and downhill slopes. In this case, the pitch angle is measured, and the measured pitch angle must be corrected as needed. In some undeveloped areas outside the city, such as in a field or at a construction site, the vehicle travels on a bumpy road or a road with potholes. In this case, the roll angle is measured, and the measured roll angle must be corrected as needed. The last case may occur less frequently than the two cases mentioned above. Therefore, the embodiments of the present invention mainly focus on calibrating the measured yaw angle and / or pitch angle in order to accelerate the calibration process. However, the calibration of the measured roll angle of the vehicle is also part of the solution of the present invention.

[0022] According to a second aspect, the present invention also provides a vehicle, which includes a sensor configured to be able to detect an object outside the vehicle and a radar-based system according to the first aspect of the present invention.

[0023] According to a third aspect, the present invention also provides a computer-implemented method for assisted driving or autonomous driving of a vehicle including a radar-based system. The computer-implemented method includes the following steps: receiving a signal from at least one sensor of the vehicle configured to be able to detect an object outside the vehicle, wherein the signal includes position information and radial velocity of each of at least three objects relative to the at least one sensor, and determining the speed of the vehicle based on the received signal.

[0024] In a preferred embodiment of the computer-implemented method, the receiving a signal from at least one sensor of the vehicle configured to be able to detect an object outside the vehicle includes: receiving a signal from each of at least three sensors of the vehicle, wherein the signal from each of the at least three sensors includes position information and radial velocity of each of at least three objects relative to the corresponding sensor, and the determining the speed of the vehicle based on the received signal includes: determining the linear velocity and angular velocity of the vehicle based on the received signal, the relative position of each of the at least three sensors relative to the vehicle, and the rotation matrix from the vehicle to each of the at least three sensors.

[0025] In another preferred embodiment of the computer-implemented method, the position information includes the azimuth angle, elevation angle, and distance of the object relative to the corresponding sensor.

[0026] According to a fourth aspect, the present invention also provides a computer program including instructions, which when executed by a computer, cause the computer to execute the method according to the third aspect of the present invention.

[0027] According to a fifth aspect, the present invention also provides a computer-readable storage medium, wherein the computer-readable storage medium stores a computer program, and when the computer executes the computer program, the computer can implement the method according to the third aspect of the present invention. BRIEF DESCRIPTION OF THE DRAWINGS

[0028] In conjunction with the accompanying drawings, further advantageous details and features can be obtained from the following description of several exemplary embodiments of the present invention, wherein:

[0029] Figure 1 Schematically shows a vehicle including a radar for measuring three objects / targets in one embodiment of the present invention;

[0030] Figure 2 Schematically shows a vehicle including three radars for measuring nine objects / targets in one embodiment of the present invention;

[0031] Figure 3 Schematically shows a host vehicle including an embodiment of the radar-based system of the present invention;

[0032] Figure 4 Shows a block diagram of an embodiment of the computer-implemented method of the present invention;

[0033] Figure 5 Shows a block diagram of an embodiment of a computer program including instructions of the present invention, which when executed by a computer, cause the computer to execute according to Figure 4 the embodiment of the method of the present invention shown; and

[0034] Figure 6 Shows a block diagram of an embodiment of the computer-readable storage medium of the present invention, wherein the computer-readable storage medium stores a computer program; and when the computer executes the computer program, the computer can implement according to Figure 4 the embodiment of the method of the present invention shown. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0035] It should be understood that the terms used herein are for describing various embodiments and are not intended to be limiting. Unless otherwise defined, the meanings of all technical and scientific terms used herein correspond to the general understanding of those skilled in the relevant technical fields of the present disclosure; they should not be construed too broadly or too narrowly.

[0036] In addition, it should be noted that the terms "a", "an", "two", "three", etc. used in the claims and / or the specification should not be construed as numerical words, but rather as non-exhaustive numerical indications of the scope of protection. For example, the term "an ABC" is intended to mean "at least one ABC". However, the terms "one", "two", "three", etc. used in the claims and the specification are also disclosed as numerical words and thus are also disclosed as numerical indications for final consideration, and this also applies to the content described in the present invention.

[0037] Figure 1 Schematically shown is a vehicle 1 including a radar sensor 3 in an embodiment according to the present invention. The radar sensor 3 has a detection range 7 and measures three stationary objects / targets T1 - T3. In a single measurement, the relative velocities V1 - V3 of the stationary targets T1 - T3 with respect to the radar are the same and correspond to the additive inverse of the velocity 2 of the moving radar 3 / vehicle 1.

[0038] If the vehicle 1 moves in a straight line, the vehicle 1 only has a linear velocity vector and no angular velocity vector. The following formula can be used to estimate the self-motion of the vehicle 1 based on the measured targets T1 - T3:

[0039] dot(Position, -Velocity) = Radial_Velocity * |Position| Formula 1,

[0040] where dot() represents the dot product of two vectors. Position is the 3D position vector of the corresponding target with respect to the radar 3, which is converted from the angle measurement of the target by the radar, such as the elevation angle, azimuth angle, and distance of the target with respect to the radar 3. Radial_Velocity is the radial component of the relative velocity (V1 - V3) of the corresponding target, which is denoted by the reference numeral R Figure 1 in v1 -R v3 is represented.

[0041] According to the algebraic definition of the dot product, assuming that the position is the 3D vector [al, a2, a3] of the target T1 and the velocity is the velocity [x, y, z] of the vehicle 1, then Formula 1 is

[0042] al * x + a2 * y + a3 * z = Radial_Velocity * |Position|.

[0043] Since the Position and Radial_Velocity of the target T1 can be directly measured or calculated by the radar 3, the product Radial_Velocity * |Position| is a constant, denoted by the symbol A1, which results in Formula 1 being further transformed into al * x + a2 * y + a3 * z = A1.

[0044] In this transformed formula 1, there are three unknown variables x, y, and z. To solve the equation, at least three targets T1 - T3 must be measured in one radar scan. Considering the possibility of measurement errors, it is better to use more stationary targets as measurement points in order to obtain a more accurate solution, because linear regression provides the optimal solution (with the minimum mean square error).

[0045] Figure 2 Vehicle 1 according to an embodiment of the present invention is schematically shown, which includes three radars 3a - 3c mounted on the vehicle body of vehicle 1, and each radar measures three objects / targets T1 - T3, T4 - T6, T7 - T9 respectively. In Figure 2 the example shown, vehicle 1 is not moving straight ahead. Therefore, when estimating the complete 3D self - motion state of the vehicle, it is also necessary to consider its angular velocity vector (i.e., [roll angle 22, pitch angle 24, yaw angle 26]).

[0046] Since radars 3a - 3c are mounted on vehicle 1 as rigid bodies, in a single measurement, they have the same linear velocity vector as vehicle 1 (represented by reference point 5), and the linear velocity vector is Figure 2 represented by reference numeral 20 in Figure 1 the same as the embodiment shown. The relative velocity of the stationary targets T1 - T9 with respect to their corresponding radars is the same, and corresponds to the additive inverse of the velocity 20 of the moving radars 3a - 3c / vehicle 1.

[0047] The velocity of the stationary objects T1 - T9 in the perspective of the corresponding vehicle - body - mounted radar can be calculated by the following formula:

[0048] Velocity=Radar_orientation*(V_hull+M_rolling*(Radar_orientation -1 *Position+Radar_position))

[0049] Formula 2,

[0050] where V_hull is the 3D velocity vector of vehicle 1 at its reference point 5. Radar_position is the relative position of radars 3a - 3c with respect to the vehicle reference point 5. Radar_orientation is the 3D rotation matrix from the vehicle reference point 5 to the radar orientation. M_rolling is a 3x3 matrix that contains the three - axis angular velocity of vehicle 1 (i.e., roll angle 22, pitch angle 24, and yaw angle 26):

[0051]

[0052] The V_hull is the 3D velocity vector (Vx, Vy, Vz) of the vehicle, and the angular velocities 22, 24, 26 in the M_roiling matrix can be estimated by performing linear regression on Formula 2 using the data of the stationary points T1 - T9 measured by three synchronized radars 3a - 3c.

[0053] Therefore, in an environment containing many stationary targets, the vehicle can estimate its complete 3D self - motion state through the three installed radars. Considering the possibility of measurement errors, it is better to use more stationary targets as measurement points to obtain a more accurate solution because linear regression provides the optimal solution (with the minimum mean square error).

[0054] Figure 3 The ego - vehicle 1 is schematically shown, which includes three radar sensors 3a, 3b, 3c mounted on the vehicle body and the radar - based system 10 of the present invention for assisted driving or autonomous driving. The system 10 includes a processor configured to: be able to receive signals from each of at least three sensors 3a, 3b, 3c of the vehicle 1 configured to be able to detect objects outside the vehicle, wherein the signals from each of at least three sensors 3a, 3b, 3c include position information and radial velocity of each of at least three objects relative to the corresponding sensor, and determine the linear velocity and angular velocity of the vehicle 1 based on the received signals, the relative position of each of at least three sensors 3a, 3b, 3c relative to the vehicle 1, and the rotation matrix from the vehicle 1 to each of at least three sensors 3a, 3b, 3c.

[0055] Figure 4 An embodiment of the computer - implemented method for assisted driving or autonomous driving of a vehicle including a radar - based system according to the present invention shown includes steps S10 and S20. In step S10, signals are received from at least one sensor of the vehicle configured to be able to detect objects outside the vehicle, wherein the signals include position information and radial velocity of each of at least three objects relative to the at least one sensor. In step S20, the speed of the vehicle is determined based on the received signals.

[0056] Figure 5 An embodiment of the computer program 200 according to the present invention shown includes instructions 250, which, when the computer executes the program 200, cause the computer to execute Figure 4 the embodiment of the method according to the present invention shown.

[0057] Figure 6 An embodiment of the computer - readable storage medium 300 according to the present invention shown stores a computer program 350. When the computer executes the computer program 350, the computer is able to execute Figure 4 the embodiment of the method according to the present invention shown.

[0058] The present invention has been described and illustrated in detail above through the above-preferred embodiments. However, the present invention is not limited to the disclosed embodiments, and other variations derivable therefrom are still within the scope of protection of the present invention.

Claims

1. A radar-based system (10) for assisted or autonomous driving in a vehicle (1), the radar-based system comprising a processor configured to: Receive signals from at least one sensor (3, 3a, 3b, 3c) of the vehicle (1) configured to detect objects (T1 - T9) outside the vehicle (1), wherein, The signals include position information and radial velocity of each of at least three objects (T1 - T9) relative to the at least one sensor (3, 3a, 3b, 3c), and determine the speed of the vehicle (1) based on the received signals.

2. The radar-based system (10) according to claim 1, wherein, The processor is further configured to: Receive signals from each of at least three sensors (3a, 3b, 3c) of the vehicle (1) configured to detect objects outside the vehicle (1), wherein the signals from each of the at least three sensors (3a, 3b, 3c) include position information and radial velocity of each of at least three objects (T1 - T9) relative to the respective sensor (3a, 3b, 3c); and Determine the linear velocity and angular velocity of the vehicle (1) based on the received signals, the relative position of each of the at least three sensors (3a, 3b, 3c) relative to the vehicle (1), and the rotation matrix from the vehicle (1) to each of the at least three sensors (3a, 3b, 3c).

3. The radar-based system (10) according to claim 1 or 2, wherein, The position information includes the azimuth angle, elevation angle, and distance of the object relative to the respective sensor (3, 3a, 3b, 3c).

4. The radar-based system (10) according to any one of the preceding claims, wherein, The angular velocity of the vehicle (1) includes the yaw angle (26) and / or the pitch angle (24).

5. A vehicle (1), the vehicle comprising: Sensors (3, 3a, 3b, 3c) configured to detect objects (T1 - T9) outside the vehicle (1), and a radar-based system (10) according to any one of the preceding claims.

6. A computer-implemented method for assisted or autonomous driving of a vehicle including a radar-based system, the computer-implemented method comprising the following steps: (S10) Receive signals from at least one sensor of the vehicle configured to detect objects outside the vehicle, wherein the signals include position information and radial velocity of each of at least three objects relative to the at least one sensor; and (S20) Determine the speed of the vehicle based on the received signals.

7. The computer-implemented method according to claim 6, wherein, (S10)Receiving signals from at least one sensor of a vehicle configured to be able to detect objects outside the vehicle includes: receiving signals from each of at least three sensors of the vehicle configured to be able to detect objects outside the vehicle, and the signals from each of the at least three sensors include position information and radial velocity of each of the at least three objects relative to the corresponding sensor; and (S20)Determining the speed of the vehicle based on the received signals includes: determining the linear speed and angular speed of the vehicle based on the received signals, the relative position of each of the at least three sensors with respect to the vehicle, and the rotation matrix from the vehicle to each of the at least three sensors.

8. The computer-implemented method according to claim 6 or 7, wherein, the position information includes the azimuth angle, elevation angle and distance of the object relative to the corresponding sensor.

9. A computer program (200) comprising instructions (250), which when executed by a computer, cause the computer to perform the method according to any one of claims 6 to 8.

10. A computer-readable storage medium (300), wherein, the computer-readable storage medium (300) stores a computer program (350); and when the computer executes the computer program (350), the computer is capable of implementing the method according to any one of claims 6 to 8.

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