CN112313539B

CN112313539B - Guardrail detection method and equipment, storage medium and movable platform

Info

Publication number: CN112313539B
Application number: CN201980039524.2A
Authority: CN
Inventors: 卜运成; 李怡强; 陆新飞
Original assignee: SZ DJI Technology Co Ltd
Current assignee: Shenzhen Zhuoyu Technology Co ltd
Priority date: 2019-11-26
Filing date: 2019-11-26
Publication date: 2024-03-15
Anticipated expiration: 2039-11-26
Also published as: CN112313539A; WO2021102689A1

Abstract

A guardrail detection method and device (100), a storage medium and a movable platform based on millimeter wave radar. The guardrail fitting method comprises the steps of transmitting millimeter wave radar signals and receiving echo signals (201) reflected by targets; processing the echo signals to obtain guardrail reflection points (202); and determining a guardrail model according to the guardrail reflection points, and further determining and outputting characterization parameters of the current guardrail to represent the current guardrail (203). According to the method, the current guardrail is represented by the characterization parameters of the current guardrail, so that the data output pressure of the guardrail reflection point can be effectively reduced.

Description

Guardrail detection method and equipment, storage medium and movable platform

Technical Field

The invention relates to the technical field of guardrail detection and fitting, in particular to a guardrail detection method and device based on millimeter wave radar, a storage medium and a movable platform.

Background

In recent years, millimeter wave radars are increasingly applied to the field of automatic driving of automobiles by virtue of the unique all-day and all-weather characteristics, the advantages of long acting distance, high speed measurement precision and the like. The millimeter wave radar can provide a plurality of help for automatic driving or auxiliary driving for detection and fitting of guardrails on two sides of a road, such as calculation of probability that a target vehicle is positioned on a self-lane, detection of a vehicle passable area, reduction of false alarms of targets outside the guardrails and the like. The guard rail presents a large number of reflection points in the millimeter wave radar detection result, and if the guard rail reflection points are all output, larger data output pressure can be brought. On the other hand, the shape of the guardrail changes along with the change of road bending, so that a single guardrail fitting model cannot meet the requirement.

Disclosure of Invention

The present invention has been made in order to solve at least one of the above problems. The invention provides a guardrail detection method and equipment based on millimeter wave radar, a storage medium and a movable platform, wherein the characterization parameters of the current guardrail are used for replacing the current guardrail, so that the data output pressure of guardrail reflection points can be effectively reduced.

Specifically, the embodiment of the invention provides a guardrail detection method based on millimeter wave radar, which comprises the following steps:

transmitting millimeter wave radar signals and receiving echo signals reflected by a target;

processing the echo signals to obtain guardrail reflection points;

and determining a guardrail model according to the guardrail reflection points, and further determining and outputting characterization parameters of the current guardrail to represent the current guardrail.

The embodiment of the invention also provides guardrail detection equipment based on the millimeter wave radar, which comprises:

the millimeter wave radar sensor is used for transmitting millimeter waves to a target area and receiving millimeter wave echo signals reflected back by objects in the target area;

the processor is configured to process the echo signals to obtain guardrail reflection points;

Embodiments of the present invention also provide a storage medium having stored thereon a computer program which, when run, performs a method as described above.

The embodiment of the invention also provides a movable platform which comprises the guardrail fitting system.

The embodiment of the invention provides a guardrail detection method and equipment based on millimeter wave radar, a storage medium and a movable platform, wherein the characterization parameters of the current guardrail are used for replacing the current guardrail, so that the data output pressure of guardrail reflection points can be effectively reduced.

Drawings

FIG. 1 shows a schematic block diagram of an example electronic device for implementing a millimeter wave radar-based guardrail fitting method and system in accordance with an embodiment of the present invention;

FIG. 2 shows a schematic flow chart of a millimeter wave radar-based guardrail detection method in accordance with an embodiment of the present invention;

FIG. 3 shows a schematic diagram of a radar sensor detecting two side guards;

fig. 4 shows a schematic flow chart of a method of detecting a fence based on millimeter wave radar according to another embodiment of the present invention;

FIG. 5 shows a schematic diagram of the reflection points presented by the guard rail in the radar detection result;

fig. 6 shows a schematic flow chart of a millimeter wave radar-based guardrail detection method in accordance with a further embodiment of the present invention;

FIG. 7 shows a schematic diagram of coordinate system definition in the fitting method shown in FIG. 6;

FIG. 8 shows a schematic calculation of the distance and speed of the guard rail reflection point in the detection method shown in FIG. 6;

figure 9 shows a schematic diagram of filtering a guard rail identification region of a range-doppler image;

FIG. 10 shows a schematic diagram of coordinate transformation of the filtered pixel of FIG. 9;

FIG. 11 shows a schematic flow chart of a target bike path evaluation method based on guardrail identification according to a further embodiment of the invention;

fig. 12 shows a schematic block diagram of a millimeter-wave radar-based guardrail detection apparatus in accordance with an embodiment of the present invention.

Detailed Description

In order to make the objects, technical solutions and advantages of the present invention more apparent, exemplary embodiments according to the present invention will be described in detail with reference to the accompanying drawings. It should be apparent that the described embodiments are only some embodiments of the present invention and not all embodiments of the present invention, and it should be understood that the present invention is not limited by the example embodiments described herein. Based on the embodiments of the invention described in the present application, all other embodiments that a person skilled in the art would have without inventive effort shall fall within the scope of the invention.

In the following description, numerous specific details are set forth in order to provide a more thorough understanding of the present invention. It will be apparent, however, to one skilled in the art that the invention may be practiced without one or more of these details. In other instances, well-known features have not been described in detail in order to avoid obscuring the invention.

It should be understood that the present invention may be embodied in various forms and should not be construed as limited to the embodiments set forth herein. Rather, these embodiments are provided so that this disclosure will be thorough and complete, and will fully convey the scope of the invention to those skilled in the art.

The terminology used herein is for the purpose of describing particular embodiments only and is not intended to be limiting of the invention. As used herein, the singular forms "a", "an" and "the" are intended to include the plural forms as well, unless the context clearly indicates otherwise. It will be further understood that the terms "comprises" and/or "comprising," when used in this specification, specify the presence of stated features, integers, steps, operations, elements, and/or components, but do not preclude the presence or addition of one or more other features, integers, steps, operations, elements, components, and/or groups thereof. As used herein, the term "and/or" includes any and all combinations of the associated listed items.

In order to provide a thorough understanding of the present invention, detailed steps and detailed structures will be presented in the following description to illustrate the technical solution presented by the present invention, however, the present invention may have other embodiments in addition to the detailed description.

First, an example electronic device 100 for implementing an example electronic device of a millimeter wave radar-based guardrail detection method and apparatus according to an embodiment of the present invention is described with reference to fig. 1. As shown in fig. 1, electronic device 100 includes one or more processors 102, one or more storage devices 104, input/output devices 106, a communication interface 108, and a radar sensor 110, which are interconnected by a bus system 112 and/or other forms of connection mechanisms (not shown). It should be noted that the components and structures of the electronic device 100 shown in fig. 1 are exemplary only and not limiting, and that the electronic device may have other components and structures or may not include some of the components described above, as desired.

The processor 102 generally represents any type or form of processing unit capable of processing data or interpreting and executing instructions. In general, the processor may be a Central Processing Unit (CPU), an image processing unit (GPU), an Application Specific Integrated Circuit (ASIC), a Field Programmable Gate Array (FPGA), an encoder, an Image Signal Processor (ISP), or other form of processing unit having data processing and/or instruction execution capabilities, and may control other components in the electronic device 100 to perform desired functions. For example, the processor 102 can include one or more embedded processors, processor cores, microprocessors, logic circuits, hardware Finite State Machines (FSMs), digital Signal Processors (DSPs), or combinations thereof. In particular embodiments, processor 102 may receive instructions from a software application or module. The instructions may cause the processor 102 to perform the methods and self-moving devices and methods for hybrid navigation of a degree device described and/or illustrated herein.

The storage 104 may include one or more computer program products that may include various forms of computer-readable storage media, such as volatile memory and/or non-volatile memory. The volatile memory may include, for example, random Access Memory (RAM) and/or cache memory (cache), and the like. The non-volatile memory may include, for example, read Only Memory (ROM), hard disk, flash memory, and the like. One or more computer program instructions may be stored on the computer readable storage medium that can be executed by the processor 102 to implement client functions and/or other desired functions in embodiments of the present invention as described below. Various applications and various data, such as various data used and/or generated by the applications, may also be stored in the computer readable storage medium.

The input/output device 106 may be a device used by a user to input instructions and output various information to the outside, and for example, the input device may include one or more of a keyboard, a mouse, a microphone, a touch screen, and the like. The output device may include one or more of a display, a speaker, etc.

Communication interface 108 broadly represents any type or form of adapter or communication device capable of facilitating communication between example electronic device 100 and one or more additional devices. For example, the communication interface 108 may facilitate communication between the electronic device 100 and front-end or accessory electronic devices as well as back-end servers or clouds. Examples of communication interface 108 include, but are not limited to, a wired network interface (such as a network interface card), a wireless network interface (such as a wireless network interface card), a modem, a universal serial interface (USB), an HDMI interface, and any other suitable interface. In one embodiment, the communication interface 108 provides a direct connection to a remote server/remote headend device through a direct connection to a network such as the Internet. In particular embodiments, communication interface 108 provides a direct connection to a remote server/remote headend device through a direct connection to a network, such as a private network. The communication interface 108 may also indirectly provide such a connection through any other suitable connection.

The radar sensor 110 may be any suitable radar sensor. Illustratively, in the present embodiment, the radar sensor 110 is a millimeter wave radar sensor, and the millimeter wave radar sensor includes, for example, a wire, a transceiver module, and a signal processing module, and the transceiver module includes, for example, a linear VCO, an amplifier, a balanced mixer, and the like, and of course, the millimeter wave radar sensor may also include other structures, and the structure of the radar sensor 110 is not particularly limited in this application.

As previously described, the paraxial guard rail may form a large number of reflection points in the millimeter wave radar, and in general, the millimeter wave radar system is limited in processing power and memory capacity, and is limited in the number of reflection points capable of detecting output, and the excessive guard rail scattering points may reduce the detection capability of other objects of interest (such as vehicles located in blind areas). At the same time, an excessive number of reflection points brings about a large data output pressure. Based on the application, a guardrail fitting method based on millimeter wave radar is provided, so that data output pressure is reduced. The guardrail detection method based on the millimeter wave radar according to the embodiment of the present invention is described below with reference to fig. 2 to 5.

It should be noted that, the guardrail in the application may include continuous obstacles on one side or two sides of a road or on one side or two sides of a lane in the middle of a road, and specifically may be, for example, stone piers on two sides of a highway, fences separated in the middle of a bidirectional lane, continuous warning barriers placed in temporary maintenance of a road, and the like.

FIG. 2 shows a schematic flow chart of a millimeter wave radar-based guardrail detection method in accordance with an embodiment of the present invention; fig. 3 shows a schematic view of a radar sensor detecting a two-sided fence.

As shown in fig. 2, the method disclosed in the present embodiment includes:

step 201, transmitting millimeter wave radar signals and receiving echo signals reflected by a target.

Illustratively, millimeter wave signals are transmitted by a millimeter wave radar sensor whose detection range is shown in fig. 3, and echo signals reflected by a target are received.

And 202, processing the echo signals to obtain guardrail reflection points.

Illustratively, various suitable echo signal processing methods are employed to derive the guardrail reflection point based on the echo signal. The obtained guardrail reflection points can comprise parameters such as coordinates of the guardrail in a radar detection coordinate system or distance from the vehicle.

And 203, determining a guardrail model according to the guardrail reflection points, and further determining and outputting characterization parameters of the current guardrail to represent the current guardrail.

When the guardrail reflection points are obtained in step S202, fitting is performed according to parameters of the guardrail reflection points, such as coordinates, so as to obtain a certain guardrail model and parameters of the model, and then the characterization parameters of the guardrail are output to represent the current guardrail.

Illustratively, the characterization parameters include parameters of the guardrail model at coordinates of a start point and an end point in the guardrail reflection point. The parameters of the guardrail model include, for example, the magnitude of the coefficients in the model, the guardrail model being illustratively rectilinear y=ax+b, the guardrail parameters including the magnitudes of a and b, and the coordinates of the start and end points in the guardrail reflection points. The shape and position of the current guardrail can be determined through coordinates of a starting point and an ending point in the guardrail reflecting points. Because the total reflection points do not need to be output to represent the detected guard rail, the data output pressure is greatly reduced, so that the detection capability of the radar sensor on other objects of interest is prevented from being influenced.

Fig. 4 shows a schematic flow chart of a method of detecting a fence based on millimeter wave radar according to another embodiment of the present invention; fig. 5 shows a schematic diagram of the reflection points presented by the guard rail in the radar detection result.

As shown in fig. 4, the method disclosed in the present embodiment includes:

step 401, transmitting millimeter wave radar signals and receiving echo signals reflected by a target.

And step 402, processing the echo signals to obtain a detection result of the target, wherein the detection result comprises a plurality of reflection points.

For example, the echo signal may be processed by a processing method commonly used in the art to obtain a detection result of the target, and as shown in fig. 5, the guard rail presents a large number of reflection points in the detection result of the millimeter wave radar sensor. Some of these reflection points are guardrail reflection points, and others are not.

And step 403, screening guardrail reflection points from the detection result according to guardrail characteristics.

After the reflection points are obtained in step 402, the guardrail reflection points need to be screened from the detection results according to the guardrail characteristics.

Illustratively, the method for screening the guardrail reflection points from the detection result according to the guardrail characteristics comprises the following steps: firstly, determining whether the reflection point is static relative to the ground according to the information of the echo signal corresponding to the reflection point. Since the guardrail is stationary relative to the ground, the guardrail reflective points are also stationary relative to the ground. The speed of the reflecting point can be determined according to the information of the echo signal corresponding to the reflecting point, and then the speed of the reflecting point relative to the ground can be determined according to the speed and the vehicle speed, if the speed of the reflecting point relative to the ground is 0, the reflecting point is possibly a guardrail reflecting point; and otherwise, the reflection point is not the guardrail reflection point.

Secondly, whether the distance between the reflecting point and the adjacent reflecting point is smaller than a set threshold value. Since the relative distances between all the reflecting points of the guardrail are relatively close, whether the reflecting point is the guardrail reflecting point can be judged by judging whether the distance between the reflecting point and the adjacent reflecting point is smaller than a set threshold value. For example, the distance information of the reflecting point, such as the distance information of the vehicle, may be determined according to the information of the echo signal corresponding to the reflecting point, and then the distance between the reflecting point and the adjacent reflecting point is obtained according to the distance information of each reflecting point, if the distance between the reflecting point and the adjacent reflecting point is greater than the set threshold value, the reflecting point is far away from the adjacent reflecting point, possibly not being a guardrail reflecting point, otherwise, the guardrail reflecting point is more likely.

Finally, the above analysis is combined to determine whether the reflection point is a guardrail reflection point. And if the reflecting point is static relative to the ground and the distance between the reflecting point and the adjacent reflecting point is smaller than a set threshold value, judging that the reflecting point is a guardrail reflecting point.

And step 404, determining a guardrail model according to the guardrail reflection points, and further determining and outputting characterization parameters of the current guardrail to represent the current guardrail.

When the guardrail reflection point is determined from the reflection point in step 403, fitting is performed according to the parameters of the guardrail reflection point, such as coordinates, so as to obtain a determined guardrail model and the parameters of the model, and then the characterization parameters of the guardrail are output to represent the current guardrail.

Further, in this embodiment, in order to avoid the problem of poor applicability of a single guardrail model, in this embodiment, a plurality of guardrail models are preset, fitted separately, and then the optimal guardrail model is selected from them.

Illustratively, the method for determining the guardrail model according to the guardrail reflection points comprises the following steps:

firstly, fitting the screened guardrail reflection points according to preset guardrail models respectively to obtain parameters of each guardrail model and fitting residual errors. Namely, the preset guardrail models are fitted respectively according to parameters of guardrail reflecting points, such as coordinates and other data, so that parameters of each guardrail model are obtained, and then a fitting residual error of each guardrail model is calculated. Illustratively, the predetermined guardrail model includes a straight line model, a quadratic polynomial model, a circular curve model, or a clothoid curve model.

And secondly, selecting a guardrail model with the minimum fitting residual error from all guardrail models as a model of the currently detected guardrail. After the fitting residual error of each guardrail model is obtained, the guardrail model with the smallest fitting residual error is selected as the model of the guardrail detected before.

Further, in this embodiment, after determining the guardrail model, the schematic diagram of the guardrail may be generated based on the parameters of the guardrail model with the minimum fitting residual error and the coordinates of the start point and the end point in the reflection points of the guardrail, so that the shape and the position of the guardrail are conveniently known to the user.

According to the guardrail detection method based on the millimeter wave radar, parameterization and automation of guardrail fitting are achieved, all guardrail reflection points are replaced by guardrail model parameters and coordinates of starting points and end points in the guardrail reflection points to represent guardrails, so that guardrail reflection point data output pressure can be effectively reduced, optimal models can be respectively fitted and selected from preset guardrail models, the optimal guardrail fitting models can be automatically selected to adapt to various scenes, and accuracy and robustness of guardrail fitting are improved.

Further, in the above embodiment, the guardrail fitting is mainly performed by clustering the stationary reflection points, and then fitting a guardrail curve. However, the clustering effect of stationary reflection points is severely affected by radar angular accuracy and multipath effects. When radar angle measurement accuracy is not high or multipath effects are available (angle measurement results deviate greatly), stationary reflection points are difficult to cluster, and the guardrail is difficult to identify and fit. The method has the problem of high computational complexity, and the method firstly carries out CFAR, MUSIC angle measurement, clustering and other algorithms on the stationary reflection points, so that the computational complexity of the algorithms is high, and the performance requirement on a processor is increased, so that the cost is high.

In view of this, the present application also provides a method for detecting a guardrail based on millimeter wave radar, which uses the hidden relation between the distance doppler information and the guardrail spatial position and the self-vehicle speed to detect and fit the guardrail. The detection method can greatly improve the detection and fitting capacity of the radar to the guardrail under the condition of not increasing the hardware cost and the antenna performance of the radar. Meanwhile, the computational complexity of the detection method is far smaller than that of the traditional method. The guardrail detecting method is described below with reference to fig. 6 to 10.

Fig. 6 shows a schematic flow chart of a millimeter wave radar-based guardrail detection method in accordance with a further embodiment of the present invention; FIG. 7 shows a schematic diagram of coordinate system definition in the fitting method shown in FIG. 6; FIG. 8 shows a schematic calculation of the guardrail reflection point distance and speed in the fitting method shown in FIG. 6; figure 9 shows a schematic diagram of filtering a guard rail identification region of a range-doppler image; fig. 10 shows a schematic diagram of the coordinate transformation of the filtered pixel of fig. 9.

The definition of the coordinate system in the present embodiment is first described with reference to fig. 7. As shown in fig. 7, in the present embodiment, since the in-vehicle radar is mounted directly in front of the vehicle, the center of the in-vehicle radar is taken as the origin, the normal direction of the radar transmission beam is taken as the y-axis positive direction, and then a cartesian coordinate system is established in terms of the right-hand system.

Next, as shown in fig. 8, in the present embodiment, the method for calculating the lateral distance of the guardrail reflection point is as follows:

since the guardrail reflection point is geostationary, the true relative velocity V between the guardrail reflection point and the radar _real The speed V of the vehicle is the magnitude _vehicle The size and the direction are opposite to the speed direction of the vehicle. Namely, satisfies the following relation:

V _real ＝-V _vehicle

guard rail reflecting point speed V actually measured by radar _doppier Is V _real The component between the radar center and the reflection point, this speed is called radial speed.

Guard rail reflecting point distance R actually measured by radar _radial Is the distance between the guardrail reflective point to the radar center, which is referred to as the radial distance.

Lateral distance R of guardrail reflection point _x Radial distance R _radial Radial velocity V _doppier With the own vehicle speed V _vehicle Satisfy the following relation (sine and cosine formula)

(Rx/R_radial)/(2+ (V_doppler/V_vehicle)/(2=1) (formula 1)

So the lateral distance R _x Can be calculated by the following formula:

based on the above definition, the guardrail detecting method of the present embodiment will be described next with reference to fig. 6 and fig. 9 and 10.

As shown in fig. 6, the method disclosed in this embodiment includes:

and step 401, processing the echo signals to obtain a range-doppler image.

Specifically, the range-doppler image is an image obtained by performing two-dimensional FFT processing on an intermediate frequency time domain signal of a radar receiving end modulated in a fast saw-tooth waveform, and as shown in the left diagram of fig. 9, the horizontal axis represents the range and the vertical axis represents the speed. The x-coordinate of each pixel point represents the radial distance between the reflection point and the radar, the y-coordinate represents the radial relative velocity (doppler effect) between the reflection point and the radar, and the magnitude of the value represents the reflection intensity of the reflection point. Illustratively, colors in a range-doppler image represent reflected intensities, for example red and blue, with redder representing stronger reflected intensities and bluer representing weaker reflected intensities.

Step 402, a guardrail identification region is determined on the range-doppler image based on vehicle speed.

As shown in the left-hand diagram of fig. 9, the curve in the box is generated by the guardrail, and the curve equation can be derived from equation 1.

V can be obtained from 3 _doppier And R is R _radial Is a curve relationship of (a). From 3, it is also known that the guard rail curve on the range-Doppler image is represented by R _x And V _vehicle Two parameters.

Illustratively, in this embodiment, the method for determining the guardrail identification area on the range-doppler image based on the vehicle speed is: first, defining a maximum speed of a pixel point in a guardrail identification area based on a vehicle speed; next, defining a minimum speed of the pixels in the guardrail identification area based on the vehicle speed; then, setting the maximum distance of the pixel points in the guardrail identification area; then, setting the minimum distance of the pixel points in the guardrail identification area; and finally, determining the guardrail identification area according to the maximum speed, the minimum speed, the maximum distance and the minimum distance.

Exemplary, e.g., maximum velocity V of a pixel point in the guardrail identification region _max For vehicle speed V _vehicle Subtracting a preset value V _offset The minimum speed is the vehicle speed V _vehicle Multiplying by a preset value A, the set maximum distance and minimum distance are R respectively _max And R is _min The guardrail identification area is expressed as:

V _max ＝V _vehicle -V _offset ，

V _min ＝V _vehicle *A，

R _min ＝B

R _max ＝C

wherein V is _offset A, B, C are preset values which can be determined empirically or experimentally, for example, V _offset Taking 2m/s, 3m/s, 4m/s, etc., A taking 0.4, 0.5, 0.6, etc., B taking 3, 4, 5, 6, C taking 50, 60, 70, 80, etc., where V is given to _offset Specific numerical values of A, B, C are not limited.

The guardrail identification area can be determined on the range-doppler image by the above relation, for example, the square area of the left graph in fig. 9 is the guardrail identification area. Some of the pixels in this area are guardrail reflective dots, and others are not.

And step 403, performing filtering processing on the pixel points in the guardrail identification area on the range-doppler image according to the reflection intensity, so as to reserve the pixel points with the reflection intensity exceeding a threshold value as guardrail reflection points.

After the guard rail identification area on the range-doppler image is determined in step 402, filtering is performed on the pixel points in the guard rail identification area according to the reflection intensity, so as to keep the pixel points with the reflection intensity exceeding the threshold value as guard rail reflection points.

Illustratively, as shown in fig. 9, for the pixel points in the guard rail identification area on the range-doppler image, the reflection intensity filtering is performed according to the range-reflection intensity characteristic curve of the guard rail, and only the pixel points where the reflection intensity exceeds the threshold value remain.

And filtering the pixel points in the guardrail identification area on the range-Doppler image according to the reflection intensity to obtain guardrail reflection points.

Step 404, mapping the pixel points with the reflection intensity exceeding the threshold value to map the pixel points with the reflection intensity exceeding the threshold value from the range-doppler coordinate system to the cartesian coordinate system with the radar as the origin.

When the guard bar reflection points are obtained from the range-doppler image, that is, the guard bar reflection points are mapped according to the second method, the pixel points representing the guard bar reflection points are mapped from the range-doppler coordinate system to the cartesian coordinate system established by the vehicle-mounted radar shown in fig. 7, so that curve fitting is finally performed on the mapped pixel points to perform guard bar fitting.

Specifically, the lateral distance R of the guardrail-reflecting point in a Cartesian coordinate system with the radar as an origin is determined according to the speed of the guardrail-reflecting point measured by the radar, the running speed of the vehicle and the distance between the guardrail-reflecting point measured by the radar and the center of the radar _x And a longitudinal distance R _y 。

Illustratively, the lateral distance R of each guardrail-reflecting point in a radar-origin Cartesian coordinate system is determined in accordance with the following equation _x ，

According to the formula Determining the transverse distance R of each guardrail reflection point in a Cartesian coordinate system taking radar as an origin _y ，

Wherein R is _radial For radial distance of guard bar reflecting point in Cartesian coordinate system with radar as origin (i.e. guard bar reflecting point measured by radar guiding radar center)Distance of (V), V _doppier Speed of guard rail reflection point measured for radar, V _vehicle Is the running speed of the vehicle.

And 405, performing guardrail fitting according to the transverse distance and the longitudinal distance of the guardrail reflection points in a Cartesian coordinate system with the radar as an origin, so as to determine a guardrail model.

By way of example, the curve model may select a straight line, a circle, or a clothoid, for example, by curve fitting using a least squares method.

According to the guardrail detection method, detection and identification of the guardrail by the radar can be realized under the condition that the hardware cost of the radar and the design complexity of the antenna are not increased. Compared with the traditional method, the method has the advantages of low calculation complexity, strong robustness, no dependence on angle measurement precision and the like, and can greatly improve the detection capability of the radar on the guardrail. Compared with the traditional method, the guardrail fitting method according to the embodiment has the advantages that the detection precision of the guardrail is greatly improved, and the calculation complexity is greatly reduced.

Further, in the practical application of the vehicle-mounted millimeter wave radar, whether the target is on the self-lane is accurately judged, however, under the condition of a curve, the millimeter wave radar cannot accurately judge whether the target vehicle is on the self-lane due to the in-out curve hysteresis effect, the accuracy of the vehicle sensor and the like. And the false alarm and missing detection rate of the ADAS system and the AD system in the curve condition are greatly increased, so that potential safety hazards are brought. In view of this, the application provides a new method for determining whether a target is in a self-lane by using the vehicle millimeter wave radar, and on the basis of not adding radar hardware and a processor and not depending on other sensors (such as a camera and other visual sensors), the accuracy of determining whether the target is in a self-lane in a curve by using the detection and identification information of the millimeter wave radar on the guardrail or the road edge is greatly improved. A target bike path evaluation method based on guardrail recognition according to an embodiment of the present invention will be described with reference to fig. 11.

Fig. 11 shows a schematic flow chart of a target bike path evaluation method based on guardrail recognition according to still another embodiment of the present invention.

As shown in fig. 11, the method disclosed in this embodiment includes:

and step 501, fitting according to a clothoid curve model according to guardrail reflection points to obtain curve parameters.

The guardrail reflection points can be obtained based on radar echo signals according to the method disclosed by the embodiment or other methods, and curve parameters are obtained by fitting according to a clothoid curve model after the guardrail reflection points are obtained. The curve parameters are illustratively obtained by curve fitting, for example by least squares or the like.

Illustratively, the clothoid model is expressed as y=a×x ³ +b*x ² +c；

And fitting according to a clothoid model according to the ordinate and the abscissa of each guardrail reflection point under a Cartesian coordinate system (the coordinate system is established by taking the middle of a vehicle head as an original point, the forward direction of the vehicle as the positive direction of a y axis and the right side of the vehicle as the positive direction of an x axis) and the number of the guardrail reflection points to obtain curve parameters a, b and c.

Step 502, calculating the distance between the vehicle and the guardrail fitting curve.

Specifically, the distance between the vehicle and the guardrail fitting curve is determined according to the curve parameters. Illustratively, y=a×x ³ +b*x ² +c is an example, e.g., the distance of the vehicle from the guardrail fitting curve equals c.

Step 503, calculating the distance between the target and the guardrail fitting curve.

Specifically, the distance between the target and the guardrail fitting curve is determined according to the clothoid model and the curve parameters and the ordinate and abscissa of the target.

And step 504, calculating the self-lane evaluation value of the current period of the target according to the distance between the vehicle and the guardrail fitting curve and the distance between the target and the guardrail fitting curve.

Specifically, the self-lane evaluation value of the current update period of the target is determined according to the distance between the vehicle and the guardrail fitting curve, the distance between the target and the guardrail fitting curve and the lane distance judgment threshold. The lane distance determination threshold may be empirically determined, for example, 1.5 meters, 1.64 meters, 1.75 meters, 1.82 meters, etc.

And 505, smoothing the self-lane evaluation value of the current period of the target to obtain a smoothed value of the current period of the target.

And determining a target current period smooth value according to the self-lane evaluation value of the current updating period, the smooth value of the previous period and the smooth coefficient. The smoothing factor may be determined empirically, for example, as 0.3, 0.4, 0.5, 0.6, 0.7, 0.8, or 0.9.

Step 506, judging whether the target is on the lane where the vehicle is based on the current cycle smooth value of the target,

and if the current period smooth value of the target is larger than the set threshold value, judging that the target is on the lane where the vehicle is located, otherwise, considering that the target is not on the lane where the vehicle is located. The set threshold may be empirically or experimentally determined and may be, for example, 50, 60, 70 or 80.

According to the target self-lane evaluation method based on guardrail identification, provided by the embodiment of the invention, the judging capability of whether the target is in the lane or not is greatly improved in a curve scene, and the false alarm rate and the omission ratio are greatly reduced. That is, the judging capability of the vehicle-mounted millimeter wave radar on whether the target is in a self-lane or not in the turning process is greatly improved, so that the robustness of the whole ADAS and AD system is improved, and the user experience is improved.

As shown in fig. 12, the millimeter wave radar-based guard rail detection 600 of the present embodiment includes a millimeter wave radar sensor 610, a memory 620, and a processor 630.

The millimeter wave radar sensor 610 is configured to transmit millimeter waves to a target area and receive millimeter wave echo signals reflected back by objects within the target area. Millimeter-wave radar sensor 610 may also process the echo signals to obtain detection results or guardrail reflection points. Millimeter-wave radar sensor 610 includes, for example, a wire, a transceiver module including, for example, a linear VCO, an amplifier, a balanced mixer, etc., and a signal processing module, although millimeter-wave radar sensor may include other configurations.

The one or more memories 620 are used to store one or more computer programs. The one or more memories 530 may include one or more computer program products that may include various forms of computer-readable storage media, such as volatile memory and/or non-volatile memory. The volatile memory may include, for example, random Access Memory (RAM) and/or cache memory (cache), and the like. The non-volatile memory may include, for example, read Only Memory (ROM), hard disk, flash memory, etc. persistent storage. One or more computer program instructions may be stored on the computer readable storage medium and executed by a processor to perform the control methods and/or other desired functions of the embodiments of the present invention described above (implemented by the processor). Various applications and various data, such as various data used and/or generated by the applications, may also be stored in the computer readable storage medium.

The one or more processors 630 may be a Central Processing Unit (CPU) or other form of processing unit having data processing capabilities and/or instruction execution capabilities, such as a micro-controller (MCU), and may control other components in the guardrail fitting system 600 to perform desired functions.

It should be appreciated that in some embodiments, processor 630 may be a processor of millimeter wave radar sensor 610 itself; in some embodiments, processor 630 may also be a processor external to millimeter-wave radar sensor 610 that interfaces with millimeter-wave radar sensor 610 and processes data generated by millimeter-wave radar sensor 610, e.g., processor 630 is a processor of the vehicle itself, rather than a processor internal to millimeter-wave radar sensor 610.

The one or more computer programs, when executed by the one or more processors 630, cause the one or more processors 630 to perform the steps of:

processing the echo signals to obtain guardrail reflection points;

Illustratively, determining a guardrail model from the guardrail reflection points comprises:

fitting the screened guardrail reflection points according to preset guardrail models respectively to obtain parameters of each guardrail model and fitting residual errors;

and selecting the guardrail model with the smallest fitting residual error from all guardrail models as the model of the currently detected guardrail.

Illustratively, the characterization parameters include parameters of the guardrail model at coordinates of a start point and an end point in the guardrail reflection point.

Illustratively, processing the echo signals to obtain guardrail reflection points includes:

processing the echo signals to obtain a detection result of the target, wherein the detection result comprises a plurality of reflection points;

and screening guardrail reflection points from the detection result according to guardrail characteristics.

Illustratively, screening guardrail reflection points from the detection result according to guardrail characteristics includes:

determining whether the reflection point is static relative to the ground according to the information of the echo signal corresponding to the reflection point; and

whether the distance between the reflecting point and the adjacent reflecting point is smaller than a set threshold value,

and if the reflection point is static relative to the ground and the distance between the reflection point and the adjacent reflection point is smaller than a set threshold value, judging that the reflection point is a guardrail reflection point.

processing the echo signals to obtain a range-Doppler image;

determining a guardrail identification region on the range-doppler image based on vehicle speed;

And filtering the pixel points in the guardrail identification area on the range-Doppler image according to the reflection intensity so as to reserve the pixel points with the reflection intensity exceeding a threshold value as guardrail reflection points.

Illustratively, determining a guardrail identification region on the range-doppler image based on vehicle speed includes:

defining a maximum speed of a pixel point in the guardrail identification area based on the vehicle speed;

defining a minimum speed of the pixels in the guardrail identification area based on the vehicle speed;

setting the maximum distance of pixel points in the guardrail identification area;

setting the minimum distance between pixel points in the guardrail identification area; and

and determining the guardrail identification area according to the maximum speed, the minimum speed, the maximum distance and the minimum distance.

Illustratively, the method further comprises:

and mapping the pixel points with the reflection intensity exceeding the threshold value to map the pixel points with the reflection intensity exceeding the threshold value from a range-Doppler coordinate system into a Cartesian coordinate system taking radar as an origin.

Illustratively, mapping the pixel points whose reflected intensities exceed a threshold from a range-doppler coordinate system into a radar-origin cartesian coordinate system includes:

and determining the transverse distance and the longitudinal distance of the guardrail reflection point in a Cartesian coordinate system taking the radar as an origin according to the speed of the guardrail reflection point measured by the radar, the running speed of the vehicle and the distance between the guardrail reflection point measured by the radar and the radar center. Illustratively, the method further comprises: and performing guardrail fitting according to the transverse distance and the longitudinal distance of the guardrail reflection points in a Cartesian coordinate system with the radar as an origin, so as to determine a guardrail model.

Illustratively, the processor is further configured to:

fitting according to the guardrail reflection points and a clothoid curve model to obtain curve parameters;

calculating the distance between the vehicle and the guardrail fitting curve;

calculating the distance between the target and the guardrail fitting curve;

calculating a self-lane evaluation value of the current period of the target according to the distance between the vehicle and the guardrail fitting curve and the distance between the target and the guardrail fitting curve;

smoothing the current period self-lane evaluation value of the target to obtain a target current period smoothing value Pn;

judging whether the target is on the lane where the vehicle is based on the current cycle smooth value of the target,

and if the current period smooth value of the target is larger than the set threshold value, judging that the target is on the lane where the vehicle is located, otherwise, considering that the target is not on the lane where the vehicle is located.

Illustratively, curve parameters are obtained by fitting a clothoid model according to the ordinate and the abscissa of each guardrail reflection point under the Cartesian coordinate system of the vehicle body and the number of the guardrail reflection points,

and determining the distance between the vehicle and the guardrail fitting curve according to the curve parameters.

Illustratively, the distance of the target from the guardrail-fitted curve is determined from the clothoid model and the curve parameters, as well as the ordinate and abscissa of the target.

Illustratively, the self-lane evaluation value of the current update period of the target is determined according to the distance between the vehicle and the guardrail-fitted curve, the distance between the target and the guardrail-fitted curve and the self-lane distance judgment threshold.

Illustratively, the target current period smoothing value is determined from the self-lane evaluation value of the current update period, the smoothing value of the previous period, and the smoothing coefficient.

Illustratively, the predetermined guardrail model includes a straight line model, a quadratic polynomial model, a circular curve model, or a clothoid curve model.

Illustratively, the processor is further configured to:

a schematic diagram of the guardrail is generated based on the coordinates of the start and end points in the reflection points of the guardrail, which fit the parameters of the guardrail model with the smallest residual.

According to the guardrail fitting system, the current guardrail is represented by the characterization parameters of the current guardrail, so that the data output pressure of guardrail reflection points can be effectively reduced.

Further, the guardrail detection device according to the embodiment can realize effective detection of the guardrail by the radar, detection precision reply is improved, and calculation complexity reply is reduced.

Further, the detection device according to the embodiment greatly improves the judging capability of whether the target is in the lane or not in the curve scene, and greatly reduces false alarm and omission ratio.

In addition, according to an embodiment of the present invention, there is also provided a millimeter wave radar-based guardrail detection apparatus, which includes a storage device and a processor, where the storage device stores a computer program executed by the processor, and the computer program executes the method provided by the embodiment of the present invention when executed by the processor.

Furthermore, according to an embodiment of the present invention, there is also provided a storage medium on which program instructions are stored, which program instructions, when being executed by a computer or a processor, are adapted to carry out the respective steps of the control method of the embodiment of the present invention, and to carry out the respective modules in the respective devices of the control system according to the embodiment of the present invention. The storage medium may include, for example, a memory card of a smart phone, a memory component of a tablet computer, a hard disk of a personal computer, read-only memory (ROM), erasable programmable read-only memory (EPROM), portable compact disc read-only memory (CD-ROM), USB memory, or any combination of the foregoing storage media. The computer-readable storage medium may be any combination of one or more computer-readable storage media.

In one embodiment, the computer program instructions, when executed by a computer, perform the steps of: transmitting millimeter wave radar signals and receiving echo signals reflected by a target; processing the echo signals to obtain guardrail reflection points; and determining a guardrail model according to the guardrail reflection points, and further determining and outputting characterization parameters of the current guardrail to represent the current guardrail.

In one embodiment, the computer program instructions, when executed by a computer, perform the steps of: processing the echo signals to obtain a range-Doppler image; determining a guardrail identification region on the range-doppler image based on vehicle speed; and filtering the pixel points in the guardrail identification area on the range-Doppler image according to the reflection intensity so as to reserve the pixel points with the reflection intensity exceeding a threshold value as guardrail reflection points.

In one embodiment, the computer program instructions, when executed by a computer, perform the steps of: fitting according to the guardrail reflection points and a clothoid curve model to obtain curve parameters; calculating the distance between the vehicle and the guardrail fitting curve; calculating the distance between the target and the guardrail fitting curve; calculating a self-lane evaluation value of the current period of the target according to the distance between the vehicle and the guardrail fitting curve and the distance between the target and the guardrail fitting curve; smoothing the current period self-lane evaluation value P of the target to obtain a current period smooth value of the target; and judging whether the target is on the lane where the vehicle is located according to the current cycle smooth value of the target, wherein if the current cycle smooth value of the target is larger than the set threshold value, the target is judged to be on the lane where the vehicle is located, otherwise, the target is not considered to be on the lane where the vehicle is located.

The modules in the control system according to the embodiments of the present invention may be implemented by a processor of an electronic device according to an embodiment of the present invention running computer program instructions stored in a memory, or may be implemented when computer instructions stored in a computer readable storage medium of a computer program product according to an embodiment of the present invention are run by a computer.

In addition, according to an embodiment of the present invention, there is also provided a movable platform including the guardrail fitting system or guardrail fitting device according to an embodiment of the present invention. The movable platform comprises an automobile.

According to the guardrail detection method and equipment based on the millimeter wave radar, the storage medium and the movable platform, the current guardrail is represented by the characterization parameters of the current guardrail, so that the data output pressure of the guardrail reflection point can be effectively reduced.

Although the illustrative embodiments have been described herein with reference to the accompanying drawings, it is to be understood that the above illustrative embodiments are merely illustrative and are not intended to limit the scope of the present invention thereto. Various changes and modifications may be made therein by one of ordinary skill in the art without departing from the scope and spirit of the invention. All such changes and modifications are intended to be included within the scope of the present invention as set forth in the appended claims.

Those of ordinary skill in the art will appreciate that the various illustrative elements and algorithm steps described in connection with the embodiments disclosed herein may be implemented as electronic hardware, or combinations of computer software and electronic hardware. Whether such functionality is implemented as hardware or software depends upon the particular application and design constraints imposed on the solution. Skilled artisans may implement the described functionality in varying ways for each particular application, but such implementation decisions should not be interpreted as causing a departure from the scope of the present invention.

In the several embodiments provided in this application, it should be understood that the disclosed apparatus and method may be implemented in other ways. For example, the above-described device embodiments are merely illustrative, e.g., the division of the elements is merely a logical functional division, and there may be additional divisions when actually implemented, e.g., multiple elements or components may be combined or integrated into another device, or some features may be omitted or not performed.

In the description provided herein, numerous specific details are set forth. However, it is understood that embodiments of the invention may be practiced without these specific details. In some instances, well-known methods, structures and techniques have not been shown in detail in order not to obscure an understanding of this description.

Similarly, it should be appreciated that in order to streamline the invention and aid in understanding one or more of the various inventive aspects, various features of the invention are sometimes grouped together in a single embodiment, figure, or description thereof in the description of exemplary embodiments of the invention. However, the method of the present invention should not be construed as reflecting the following intent: i.e., the claimed invention requires more features than are expressly recited in each claim. Rather, as the following claims reflect, inventive aspects lie in less than all features of a single disclosed embodiment. Thus, the claims following the detailed description are hereby expressly incorporated into this detailed description, with each claim standing on its own as a separate embodiment of this invention.

It will be understood by those skilled in the art that all of the features disclosed in this specification (including any accompanying claims, abstract and drawings), and all of the processes or units of any method or apparatus so disclosed, may be combined in any combination, except combinations where the features are mutually exclusive. Each feature disclosed in this specification (including any accompanying claims, abstract and drawings), may be replaced by alternative features serving the same, equivalent or similar purpose, unless expressly stated otherwise.

Furthermore, those skilled in the art will appreciate that while some embodiments described herein include some features but not others included in other embodiments, combinations of features of different embodiments are meant to be within the scope of the invention and form different embodiments. For example, in the claims, any of the claimed embodiments may be used in any combination.

Various component embodiments of the invention may be implemented in hardware, or in software modules running on one or more processors, or in a combination thereof. Those skilled in the art will appreciate that microprocessors or digital signal processors (Digital Signal Processor, DSP) may be used in practice to implement some or all of the functionality of some of the modules according to embodiments of the present invention. The present invention can also be implemented as an apparatus program (e.g., a computer program and a computer program product) for performing a portion or all of the methods described herein. Such a program embodying the present invention may be stored on a computer readable medium, or may have the form of one or more signals. Such signals may be downloaded from an internet website, provided on a carrier signal, or provided in any other form.

It should be noted that the above-mentioned embodiments illustrate rather than limit the invention, and that those skilled in the art will be able to design alternative embodiments without departing from the scope of the appended claims. In the claims, any reference signs placed between parentheses shall not be construed as limiting the claim. The invention may be implemented by means of hardware comprising several distinct elements, and by means of a suitably programmed computer. In the unit claims enumerating several means, several of these means may be embodied by one and the same item of hardware. The use of the words first, second, third, etc. do not denote any order. These words may be interpreted as names.

The foregoing description is merely illustrative of specific embodiments of the present invention and the scope of the present invention is not limited thereto, and any person skilled in the art can easily think about variations or substitutions within the scope of the present invention. The protection scope of the invention is subject to the protection scope of the claims.

Claims

1. The guardrail detection method based on the millimeter wave radar is characterized by comprising the following steps of:

processing the echo signals to obtain guardrail reflection points;

and determining a target guardrail model from at least one preset guardrail model according to the guardrail reflecting points, and further determining and outputting characterization parameters of the current guardrail to represent the current guardrail, wherein the characterization parameters comprise parameters of the target guardrail model and coordinate parameters of a starting point and an ending point in the guardrail reflecting points.

2. The method of claim 1, wherein determining a target guardrail model from at least one preset guardrail model based on the guardrail reflection points comprises:

fitting the screened guardrail reflecting points according to the preset guardrail models respectively to obtain parameters of each preset guardrail model and fitting residual errors;

and selecting a preset guardrail model with the minimum fitting residual error from all the preset guardrail models as a model of the currently detected guardrail.

3. The method of claim 1, wherein processing the echo signals to obtain guardrail reflective points comprises:

4. A method according to claim 3, wherein screening guardrail reflective points from the detection result based on guardrail characteristics comprises:

5. The method of claim 1, wherein processing the echo signals to obtain guardrail reflective points comprises:

processing the echo signals to obtain a range-Doppler image;

6. The method of claim 5, wherein determining a guardrail identification region on the range-doppler image based on vehicle speed comprises:

7. The method as recited in claim 5, further comprising:

8. The method of claim 7, wherein mapping the pixel points for which the reflected intensity exceeds a threshold from a range-doppler coordinate system into a radar-origin cartesian coordinate system comprises:

and determining the transverse distance and the longitudinal distance of the guardrail reflection point in a Cartesian coordinate system taking the radar as an origin according to the speed of the guardrail reflection point measured by the radar, the running speed of the vehicle and the distance between the guardrail reflection point measured by the radar and the radar center.

9. The method as recited in claim 8, further comprising:

and performing guardrail fitting according to the transverse distance and the longitudinal distance of the guardrail reflection points in a Cartesian coordinate system with the radar as an origin, so as to determine a guardrail model.

10. The method as recited in claim 1, further comprising:

calculating the distance between the vehicle and the guardrail fitting curve;

calculating the distance between the target and the guardrail fitting curve;

smoothing the self-lane evaluation value of the current period of the target to obtain a smoothed value of the current period of the target;

11. The method of claim 10, wherein the step of determining the position of the first electrode is performed,

fitting according to a clothoid model according to the ordinate and the abscissa of each guardrail reflection point under the Cartesian coordinate system of the vehicle body and the number of the guardrail reflection points to obtain curve parameters,

12. The method of claim 11, wherein the step of determining the position of the probe is performed,

and determining the distance between the target and the guardrail fitting curve according to the clothoid model and the curve parameters and the ordinate and abscissa of the target.

13. The method of claim 12, wherein the step of determining the position of the probe is performed,

and determining the self-lane evaluation value of the current updating period of the target according to the distance between the vehicle and the guardrail fitting curve, the distance between the target and the guardrail fitting curve and the self-lane distance judgment threshold.

14. The method of claim 13, wherein the step of determining the position of the probe is performed,

and determining a target current period smooth value according to the self-lane evaluation value of the current updating period, the smooth value of the previous period and the smooth coefficient.

15. The method of claim 1, wherein the predetermined guardrail model comprises a straight line model, a quadratic polynomial model, a circular curve model, or a clothoid curve model.

16. The method as recited in claim 1, further comprising:

17. Guardrail detection equipment based on millimeter wave radar, characterized by comprising:

18. The apparatus of claim 17, wherein determining a target guardrail model from at least one preset guardrail model based on the guardrail reflection points comprises:

19. The apparatus of claim 17, wherein processing the echo signals to obtain guardrail reflective points comprises:

20. The apparatus of claim 19, wherein screening guardrail reflective points from the detection result based on guardrail characteristics comprises:

21. The apparatus of claim 17, wherein processing the echo signals to obtain guardrail reflective points comprises:

processing the echo signals to obtain a range-Doppler image;

22. The apparatus of claim 21, wherein determining a guardrail identification region on the range-doppler image based on vehicle speed comprises:

23. The apparatus as recited in claim 21, further comprising:

24. The apparatus of claim 23, wherein mapping the pixel points for which the reflected intensity exceeds a threshold from a range-doppler coordinate system into a radar-origin cartesian coordinate system comprises:

25. The apparatus as recited in claim 24, further comprising:

26. The device of claim 17, wherein the processor is further configured to:

calculating the distance between the vehicle and the guardrail fitting curve;

calculating the distance between the target and the guardrail fitting curve;

27. The apparatus of claim 26, wherein the device comprises a plurality of sensors,

28. The apparatus of claim 27, wherein the device comprises a plurality of sensors,

29. The apparatus of claim 28, wherein the device comprises a plurality of sensors,

30. The apparatus of claim 29, wherein the device comprises a plurality of sensors,

31. The apparatus of claim 17, wherein the pre-set guardrail model comprises a straight line model, a quadratic polynomial model, a circular curve model, or a clothoid curve model.

32. The device of claim 17, wherein the processor is further configured to:

33. A storage medium having stored thereon a computer program which, when run, performs the method of any of claims 1-16.

34. A movable platform, comprising: a guard rail detection apparatus as claimed in any one of claims 17 to 32.

35. The mobile platform of claim 34, wherein the mobile platform comprises an automobile.