WO2022183408A1

WO2022183408A1 - Lane line detection method and lane line detection apparatus

Info

Publication number: WO2022183408A1
Application number: PCT/CN2021/078907
Authority: WO
Inventors: 张慧; 马莎; 宋思达; 吕笑宇
Original assignee: 华为技术有限公司
Priority date: 2021-03-03
Filing date: 2021-03-03
Publication date: 2022-09-09
Also published as: CN113167885B; CN113167885A

Abstract

The present application provides a lane line detection method and a lane line detection apparatus, which can be applied to the field of autonomous driving or intelligent driving. Said method comprises: acquiring echo data of the ground by means of a radar, the ground comprising a lane line; pre-processing the described echo data to obtain first data; filtering the first data to obtain second data, the second data being data having an amplitude less than a first threshold; and performing imaging processing on the second data to obtain a synthetic aperture radar (SAR) image of the lane line. The lane line detection method and the lane line detection apparatus can acquire a high-resolution SAR image of a lane line, effectively improving the accuracy of lane line detection.

Description

Lane line detection method and lane line detection device

technical field

The present application relates to the field of assisted driving or automatic driving, and in particular, to a lane line detection method and a lane line detection device.

Background technique

In many advanced assisted driving and autonomous driving applications, such as lane departure warning (LDW), lane keeping assist (LKA), etc., the detection of lane lines is very important. At present, the main source of lane line information is the optical image obtained by the camera or the point cloud image obtained by the lidar. However, the method of obtaining lane line information based on cameras fails in dark scenes, and lacks depth information or lacks depth information accuracy. Lidar has limited detection capabilities in conditions such as rain, snow, haze or road dust. Radar (or millimeter wave radar) has all-day and all-weather working capabilities, but the angular resolution of the point cloud data obtained by it is limited by the length of the antenna aperture (or virtual aperture), the point cloud is sparse, and it is difficult to complete the lane line detection. detection.

Synthetic aperture radar (SAR) imaging technology can use the relative motion of the radar and the target to form a large synthetic aperture, break through the limitation of the real aperture of the antenna, and achieve high-resolution imaging. One application of SAR imaging technology is to use vehicle-mounted radar to perform SAR imaging of stationary parking lots or roadside parking areas, so that high-resolution images can be obtained for empty parking space detection.

At present, there is no research on lane line detection using SAR imaging technology. Therefore, it is urgent to provide a lane line detection method based on SAR imaging technology to obtain high-resolution lane line images.

SUMMARY OF THE INVENTION

The present application provides a lane line detection method and a lane line detection device, which can acquire a high-resolution SAR image of the lane line, and effectively improve the accuracy of the lane line detection.

In a first aspect, a lane line detection method is provided, the method includes: using a radar to obtain echo data of the ground, where the ground includes lane lines; preprocessing the echo data to obtain first data; The data is filtered to obtain second data, and the second data is data whose amplitude is smaller than the first threshold; the above-mentioned second data is subjected to imaging processing to obtain the SAR image of the lane line.

In the lane line detection method provided by the embodiment of the present application, first data is obtained by preprocessing echo data obtained by radar, and the first data is filtered out by using a first threshold to obtain second data smaller than the first threshold , and perform imaging processing on the second data to obtain the SAR image of the lane line. In the embodiment of the present application, the influence of the strong scattering target is filtered out during the imaging process, so that the lane line can be displayed in the SAR image, the detection of the lane line by using the SAR imaging technology is realized, and the SAR of the lane line with high resolution can be obtained. image, improving the accuracy of lane line detection.

It should be understood that the echo data of the ground acquired by the above radar may include echo data of the lane line and echo data of other targets around the lane line.

It should be understood that in the application scenario of the vehicle-mounted radar, the echo data obtained by the vehicle-mounted radar includes the echo data of the lane line and the echo data of other strong scattering targets such as guardrails and vehicles. That is, the above-mentioned first data not only includes the data of the lane line to be detected, but also aliases the data of other strong scattering targets except the data of the lane line.

Optionally, the above filtering process may be performed according to a preset first threshold to obtain second data whose amplitude is smaller than the first threshold.

Exemplarily, the above-mentioned first data is a collection of multiple sampling point data, wherein each sampling point data has a corresponding amplitude value.

It should also be understood that the first data or the second data in this embodiment of the present application may be data in the form of a two-dimensional array. Exemplarily, the above two-dimensional array corresponds to a two-dimensional coordinate system, the abscissa may represent the distance direction (ie fast time), and the ordinate may represent the azimuth direction (ie slow time). In the application scenario of the vehicle-mounted radar, the azimuth direction represents the moving direction of the vehicle (that is, the moving direction of the vehicle-mounted radar), and the distance direction represents the vertical direction of the vehicle's movement. With reference to the first aspect, in some implementations of the first aspect, filtering the above-mentioned first data to obtain the second data includes: removing data whose amplitude is greater than or equal to the above-mentioned first threshold from the above-mentioned first data , get the second data.

The above-mentioned method of acquiring the second data has a simple and easy processing process, effectively reduces the computational pressure of the data processing device, and improves the efficiency of lane detection at the same time.

With reference to the first aspect, in some implementations of the first aspect, filtering the above-mentioned first data to obtain the second data includes: according to the data whose amplitude is greater than or equal to the first threshold in the first data, The point spread function of the data is obtained; the data corresponding to the point spread function is removed from the first data to obtain the second data.

It should be understood that the data whose amplitude is greater than or equal to the first threshold may be referred to as main lobe data, and the data corresponding to the point spread function may be referred to as side lobe data.

It should be understood that the point spread function is a function used to estimate the minimum spatially resolved distance of an imaging system.

It should also be understood that the data processing device can obtain the point spread function of the data whose magnitude is greater than or equal to the first threshold in two different ways. And the point spread functions corresponding to different data are equivalent to translation and amplitude-phase transformation of the same signal form.

Optionally, if the data processing device performs windowing during the imaging process, the influence of the window function on the main lobe width and side lobe intensity of the distance envelope of the point spread function needs to be considered when filtering out the data.

In the embodiment of the present application, according to the data whose amplitude is greater than or equal to the first threshold, the point spread function of the data is obtained, and the main lobe data of the point spread function corresponding to the data can be removed, and at the same time the main lobe data of the point spread function corresponding to the data can be further filtered out The influence of the side lobe data of the point spread function can more effectively improve the accuracy of lane line detection.

With reference to the first aspect, in some implementations of the first aspect, preprocessing the echo data to obtain the first data includes: performing Doppler parameter estimation, motion parameter estimation, and motion compensation on the echo data and distance compression to obtain the above-mentioned first data.

It should be understood that if the echo data obtained by the above-mentioned radar is forward-squinting echo data (that is, the working mode of the radar is the echo data obtained by forward-squinting) or the echo data obtained by back-squinting (that is, the working mode of the radar is obtained by the backward-squinting view). echo data), then after performing Doppler parameter estimation and motion parameter estimation on the echo data obtained by the radar, it is also necessary to perform range linear motion compensation and Doppler center correction, so that the processed strabismus data can be equivalent to Front and side view data, and follow-up processing such as motion compensation.

With reference to the first aspect, in some implementations of the first aspect, performing imaging processing on the above-mentioned second data to obtain the SAR image of the above-mentioned lane line, including: quantizing the second data, Doppler modulation frequency estimation, Azimuth phase error correction and azimuth compression are performed to obtain the SAR image.

It should be understood that the foregoing quantification process may be performed in any step after the foregoing filtering process, or may be performed after the SAR image is acquired, which is not limited in this embodiment of the present application.

With reference to the first aspect, in some implementations of the first aspect, the above-mentioned SAR image is an image in the slant range plane, and the method further includes: performing geometric deformation correction and coordinate transformation on the SAR image to obtain the SAR image in the ground range plane. image.

In the embodiment of the present application, by converting the image in the slant range plane to the image in the ground distance plane, the acquired lane line image can be closer to the lane line of the real road, and the accuracy of the lane line detection can be more effectively improved .

In combination with the first aspect, in some implementations of the first aspect, the transmit signal bandwidth B, the lower viewing angle θ, and the oblique viewing angle β of the above-mentioned radar satisfy:

Among them, Δx is the width of the above lane line,

Satisfy

c is the propagation speed of the electromagnetic wave.

Optionally, in actual calculation, c=3×10 ⁸ m/s.

Optionally, in order to ensure that the lane line is within the imaging area during normal driving, it is required that the single-sided swath width (ie the width of the imaging area) ΔX satisfies ΔX≧L ₁ −L ₂ . where _L1 is the lane width and _L2 is the vehicle width.

Optionally, the installation height H, the oblique angle β and the lower angle θ of the radar should be set to ensure that the beam is not reflected by the vehicle body as much as possible.

With reference to the first aspect, in some implementations of the first aspect, the working mode of the above-mentioned radar is a side view, a forward squinting or a backward squinting, and the imaging area of the radar is one side or both sides of the vehicle including the lane line road.

It should be understood that the working mode of the above radar is that when the radar is viewed from the side, the oblique angle of view of the radar is β=0°. When the working mode of the above-mentioned radar is to look backward, the value of the angle of oblique angle β of the radar is negative.

In the lane line detection method provided by the embodiments of the present application, in the application scenario of the vehicle-mounted radar, the vehicle-mounted radar adopts the forward-looking working mode, and can obtain the information of the lane line in front of the vehicle in advance, so that the vehicle or the driver can know the road conditions in front of the vehicle in advance. , and flexibly adjust the driving route according to the road conditions in front of the vehicle. On the other hand, the vehicle radar adopts the working mode of side view or backward view, which can be applied to applications such as map drawing.

With reference to the first aspect, in some implementations of the first aspect, the above-mentioned radar is a millimeter-wave radar.

It should be understood that the millimeter-wave radar has the ability to penetrate smoke, dust or fog, so that the millimeter-wave radar can work all day, all day long. In the application scenario of vehicle radar, using millimeter wave radar as vehicle radar can better assist driving or automatic driving.

It should also be understood that the lane line detection method provided by the embodiments of the present application is also applicable to radars in other frequency bands.

In a second aspect, a lane line detection apparatus is provided, which is used to execute the method in any possible implementation manner of the above-mentioned first aspect. Specifically, the apparatus includes a module for executing the method in any one of the possible implementation manners of the first aspect above.

In a third aspect, another apparatus for lane line detection is provided, including a processor, which is coupled to a memory and can be configured to execute instructions in the memory, so as to implement the method in any one of the possible implementations of the first aspect. Optionally, the apparatus further includes a memory. Optionally, the apparatus further includes a communication interface to which the processor is coupled.

In an implementation manner, the lane line detection device is a data processing device. When the lane line detection device is a data processing device, the communication interface may be a transceiver, or an input/output interface.

In another implementation manner, the lane line detection device is a chip configured in a server. When the lane line detection device is a chip configured in the server, the communication interface may be an input/output interface.

In a fourth aspect, a processor is provided, including: an input circuit, an output circuit, and a processing circuit. The processing circuit is configured to receive the signal through the input circuit and transmit the signal through the output circuit, so that the processor executes the method in any one of the possible implementation manners of the above first aspect.

In a specific implementation process, the above-mentioned processor may be a chip, the input circuit may be an input pin, the output circuit may be an output pin, and the processing circuit may be a transistor, a gate circuit, a flip-flop, and various logic circuits. The input signal received by the input circuit may be received and input by, for example, but not limited to, a receiver, the signal output by the output circuit may be, for example, but not limited to, output to and transmitted by a transmitter, and the input circuit and output The circuit can be the same circuit that acts as an input circuit and an output circuit at different times. The embodiments of the present application do not limit the specific implementation manners of the processor and various circuits.

In a fifth aspect, a processing apparatus is provided, including a processor and a memory. The processor is configured to read the instructions stored in the memory, and can receive signals through the receiver and transmit signals through the transmitter, so as to execute the method in any one of the possible implementation manners of the first aspect.

Optionally, there are one or more processors and one or more memories.

Alternatively, the memory may be integrated with the processor, or the memory may be provided separately from the processor.

In the specific implementation process, the memory can be a non-transitory memory, such as a read only memory (ROM), which can be integrated with the processor on the same chip, or can be separately set in different On the chip, the embodiment of the present application does not limit the type of the memory and the setting manner of the memory and the processor.

It should be understood that the relevant data interaction process, such as sending indication information, may be a process of outputting indication information from the processor, and receiving capability information may be a process of receiving input capability information by the processor. Specifically, the data output by the processing can be output to the transmitter, and the input data received by the processor can be from the receiver. Among them, the transmitter and the receiver may be collectively referred to as a transceiver.

The processing device in the fifth aspect may be a chip, and the processor may be implemented by hardware or software. When implemented by hardware, the processor may be a logic circuit, an integrated circuit, etc.; when implemented by software When implemented, the processor can be a general-purpose processor, which is realized by reading software codes stored in a memory, and the memory can be integrated in the processor or located outside the processor and exist independently.

In a sixth aspect, a computer program product is provided, the computer program product comprising: a computer program (also referred to as code, or instructions), which, when the computer program is executed, causes the computer to execute any one of the above-mentioned first aspects methods in possible implementations.

In a seventh aspect, a computer-readable storage medium is provided, the computer-readable storage medium stores a computer program (also referred to as code, or instruction) when it is run on a computer, causing the computer to execute the above-mentioned first aspect. method in any of the possible implementations.

In an eighth aspect, a terminal is provided, which can be a transportation tool or a smart device (such as a smart home or smart manufacturing equipment, etc.), including a drone, an unmanned transportation vehicle, a car or a robot, etc., and the transportation tool or smart device includes The apparatus in any possible implementation manner of the second aspect, the third aspect or the fifth aspect.

Description of drawings

1 is a schematic diagram of an application scenario provided by an embodiment of the present application;

FIG. 2 is a schematic flowchart of a lane line detection method provided by an embodiment of the present application;

FIG. 3 is a three-dimensional geometric diagram of radar imaging provided by an embodiment of the present application;

4 is a schematic diagram of an imaging area provided by an embodiment of the present application;

5 is a schematic diagram of another imaging area provided by an embodiment of the present application;

6 is a schematic flowchart of an imaging algorithm provided by the present application;

FIG. 7 is a schematic flowchart of another imaging algorithm provided by the present application;

FIG. 8 is a schematic flowchart of still another imaging algorithm provided by an embodiment of the present application;

FIG. 9 is a schematic block diagram of a lane line detection device provided by an embodiment of the present application;

FIG. 10 is a schematic block diagram of another lane line detection apparatus provided by an embodiment of the present application.

Detailed ways

The technical solutions in the present application will be described below with reference to the accompanying drawings.

In order to clearly describe the technical solutions of the embodiments of the present application, the following points are first made.

First, in the embodiments shown below, terms and English abbreviations, such as strong scattering target, point spread function, etc., are exemplary examples given for convenience of description, and should not constitute any limitation to the present application. This application does not exclude the possibility of defining other terms that can achieve the same or similar functions in existing or future agreements.

Second, in the embodiments shown below, the first, the second, and various numeral numbers are only for the convenience of description, and are not used to limit the scope of the embodiments of the present application. For example, distinguishing different data.

Third, "at least one" means one or more, and "plurality" means two or more. "And/or", which describes the association relationship of the associated objects, indicates that there can be three kinds of relationships, for example, A and/or B, which can indicate: the existence of A alone, the existence of A and B at the same time, and the existence of B alone, where A, B can be singular or plural. The character "/" generally indicates that the associated objects are an "or" relationship. "At least one item(s) below" or similar expressions thereof refer to any combination of these items, including any combination of single item(s) or plural items(s). For example, at least one (a) of a, b and c may represent: a, or b, or c, or a and b, or a and c, or b and c, or a, b and c, wherein a, b, c can be single or multiple.

Fourth, words such as "exemplarily" or "such as" mean an example, illustration, or illustration. Any embodiment or design described herein as "exemplarily" or "such as" should not be construed as preferred or advantageous over other embodiments or designs. Rather, the use of words such as "exemplarily" or "such as" is intended to present the related concepts in a specific manner.

To facilitate understanding of the embodiments of the present application, related terms involved in the present application are introduced below.

1. Full-time working ability: refers to the ability to work during the day and at night.

2. All-weather working ability: refers to working in sunny, rainy, foggy, snowy days, etc.

3. Resolution: refers to the minimum size that two targets can be distinguished, generally taking 3 decibel (dB) resolution, that is, half-power point resolution, or Rayleigh resolution, which is the width of the main lobe between the two nearest zero points half of .

4. Radar: It is an electronic device that uses electromagnetic waves to detect targets. Radar irradiates the target by emitting electromagnetic waves and receives the echo of the target. From this, information such as the distance from the target to the electromagnetic wave emission point, the distance change rate (radial velocity), the azimuth, and the altitude are obtained.

The radar can transmit pulse signals periodically while working, and sample the echo signal for the duration of the pulse. Although the sampling interval of the echo signal and the pulse repetition interval (i.e. the period of the pulse signal) can be on the same time axis, they are very different in magnitude.

5. Main lobes and side lobes: Side lobes can also be called side lobes. In the radar detection target, the main lobe is the area around the maximum radiation direction, usually the area within 3dB of the main beam peak, which is the main working direction of the radar. It is understandable that the main lobe can contain radar waves with the strongest radiation intensity. The other lobes other than the main lobe are side lobes, which are beams with less radiation around the main beam. Understandably, the presence of side lobes may reduce the ability of the radar to detect targets.

In many advanced assisted driving and automatic driving applications such as lane departure warning, lane keeping assistance, etc., it is very important to detect the lane line to ensure the normal driving of the vehicle. At present, in the process of lane line detection, the main source of lane line information is the optical image obtained by the camera or the point cloud image obtained by the lidar.

An existing lane line detection method is: firstly perform lane line detection and parameter estimation based on visual detection, then use lidar detection data to perform boundary line detection, and finally fuse the lane line detection results with the boundary line results to obtain the lane Check parameters. Another lane line detection method is to use the machine vision method to detect the lane lines obtained by the camera, use the millimeter wave radar to detect the static guardrails on both sides of the road to obtain the boundary information of the road, and then use the low-precision global positioning system (global positioning system). positioning system, GPS) to obtain the current road information, and integrate the lane line and road edge information to achieve lane-level positioning.

However, the above method has the following two disadvantages. On the one hand, the method of obtaining lane line information based on cameras fails in dark scenes, and lacks depth information or lacks depth information accuracy. On the other hand, what the radar completes is all road edge detection (such as guardrails, etc.), rather than lane line detection. The road edges obtained by radar are low-resolution point cloud data, and high-resolution radar images containing lane lines are not obtained.

It should be understood that radar point cloud data is generally realized by multiple input multiple output (MIMO) technology. The angular resolution of point cloud data obtained by this technology is limited by the length of the antenna aperture (or virtual aperture), and the point cloud is sparse. and low resolution. Therefore, the point cloud image obtained by the radar is difficult to detect the lane line.

SAR imaging technology can use the relative motion of the radar and the target to form a large synthetic aperture, break through the limitation of the real aperture of the antenna, and achieve high-resolution imaging. The principle of SAR imaging technology is: use a small antenna on the radar as a single radiating unit, move the unit continuously along a straight line, and receive the echo signals of the same target object at different positions and process them, and then the comparison of the target object can be obtained. high-resolution images. The above small antennas can be combined into an equivalent "large antenna" by moving. Therefore, the realization condition of SAR imaging technology is that the radar is moving and the target is stationary, so as to ensure the relative movement between the radar and the target. That is, in the application scenario of the on-board radar, the on-board radar is in a moving state, which means that the vehicle installed with the on-board radar is in a driving state.

One application of SAR imaging technology is to use vehicle-mounted radar to perform SAR imaging of stationary parking lots or roadside parking areas, so that high-resolution images can be obtained for empty parking space detection. At present, there is no research and report on lane line detection using SAR imaging technology. Therefore, it is urgent to provide a lane line detection method based on SAR imaging technology to obtain high-resolution lane line images.

FIG. 1 shows an application scenario 100 provided by an embodiment of the present application. As shown in FIG. 1 , a vehicle 110 is traveling in the lane 1, and the vehicle 110 is equipped with an on-board radar. During driving, the vehicle 110 can detect surrounding targets according to the on-board radar on the vehicle 110 , for example, the speed limit signs 120 , road signs 130 ,

lane lines

140 and 150 around the vehicle 110 . Among them, the lane line 140 is used to separate the vehicles traveling in the same phase, indicating that the vehicle cannot cross the lane line to change lanes, and the lane line 150 is used to separate the vehicles traveling in the same phase, indicating that the vehicle can cross the lane line to change lanes when it is safe to do so .

Optionally, the vehicle 110 in the foregoing scenario 100 may be a vehicle configured with an advanced driving assistance system, or the vehicle 110 may also be a vehicle configured with an intelligent driving system, which is not limited in this embodiment of the present application.

It should be understood that the application scenario 100 provided by the embodiment of the present application is only an example, and does not impose any limitation on the application scenario of the embodiment of the present application. Optionally, the above application scenario 100 may also include other objects not shown in FIG. 1 , such as other vehicles and roadside guardrails, which are not limited in this embodiment of the present application.

In the above application scenario shown in FIG. 1 , the on-board radar of the vehicle 110 transmits a signal, and the signal will be reflected when encountering any of the above targets (speed limit sign 120 , road sign 130 , lane line 140 or lane line 150 ), and Generate echo signals. Since there are many different types of targets around the vehicle 110 , the echo signals received by the vehicle-mounted radar also include a plurality of echo signals with different intensities.

It should be understood that the strength of the echo signal is related to factors such as the material of the target, the roughness of the target surface, or the energy of the radar transmit signal. For example, the echo signal strength reflected by targets such as metal guardrails, stationary vehicles or obstacles is relatively large; the echo signal strength reflected by targets such as lane lines is relatively small. For the convenience of description, the target corresponding to the echo signal with higher intensity is called a strong scattering target (such as guardrails, vehicles, etc.), and the target corresponding to the echo signal with a lower intensity is called a weak scattering target (such as lane lines). ).

Since the echo signal includes multiple echo signals with different intensities, the echo signal of the strong scattering target usually drowns the echo signal of the weak scattering target. Illustratively, the echo signals of the speed limit sign 120 described above may overwhelm the echo signals of the pavement marking 130 , the lane markings 140 or the lane markings 150 . Therefore, when using the above SAR imaging technology to acquire SAR images, even if there are lane lines in the current scene, their amplitudes will be submerged by the side lobes of strong scattering targets such as roadside guardrails or vehicles, and it is difficult to see in the acquired SAR images. Lane line information on the ground.

In view of this, the present application provides a lane line detection method and a lane line detection device. The first data is obtained by preprocessing the echo data obtained by the radar, and the first data is filtered to obtain a signal smaller than the first threshold. The second data is then subjected to imaging processing to obtain a SAR image of the lane line. In the embodiment of the present application, the influence of the strong scattering target is filtered out during the imaging process, so that the lane line can be displayed in the SAR image, the detection of the lane line by using the SAR imaging technology is realized, and the SAR of the lane line with high resolution can be obtained. image, improving the accuracy of lane line detection.

It should be understood that the lane line detection method provided in this embodiment of the present application may be used for a radar in a linear frequency modulated continuous wave (LFMCW) system. The radar signal system can also be extended to digitally modulated radar, for example, the radar signal system can be phase modulated continuous wave (PMCW).

It should also be understood that the method in this embodiment of the present application may be executed by a data processing device, or may be executed by a chip in the data processing device, which is not limited in this embodiment of the present application. The embodiments of the present application are described by taking a data processing device as an example. It should be understood that, in the application scenario of the vehicle-mounted radar, the data processing device may be the vehicle-mounted radar, or may be other devices installed on the vehicle together with the vehicle-mounted radar, which is not limited in this application.

The following describes the lane line detection method 200 provided by the embodiment of the present application in detail with reference to FIG. 2 .

FIG. 2 is a schematic flowchart of a lane line detection method 200 provided by an embodiment of the present application. It should be understood that the method 200 may be applied to the application scenario 100 shown in FIG. 1 above, and may also be applied to an airborne radar or other scenarios, which is not limited in this embodiment of the present application. As shown in Figure 2, the method 200 includes:

S201. Use radar to acquire echo data of the ground, where the ground includes lane lines.

It can be known from the working principle of the radar that the sampling interval of the echo signal and the pulse repetition interval (ie the period of the pulse signal) can be on the same time axis, but the magnitude is very different. Therefore, in order to facilitate the processing of the obtained sampled data, the data processing device may divide the echo sampling interval and the pulse repetition period into two dimensions, which are called fast time and slow time respectively. Exemplarily, the data processing device may divide the echo signals in each pulse interval as a row, and store the obtained sample data (ie, the above echo data) in the form of a two-dimensional array. Exemplarily, the above two-dimensional array may correspond to a two-dimensional coordinate system, the horizontal axis represents fast time (ie echo sampling interval), and the vertical axis represents slow time (ie pulse repetition period).

S202. Preprocess the echo data to obtain first data.

Exemplarily, the data processing device may perform a series of preprocessing such as Doppler parameter estimation, motion parameter estimation, motion compensation, range compression, etc. on the above echo data, and convert the echo data obtained in the above S201 into image data ( That is, the above-mentioned first data).

S203. Perform filtering processing on the first data to obtain second data, where the second data is data whose amplitude is smaller than the first threshold.

Since the data of other strong scattering targets other than the data of weak scattering targets such as lane lines are aliased in the above-mentioned first data, the data processing device can filter and process other strong scattering targets that affect the imaging of lane lines in the first data. Filter out the data of the target, thereby obtaining data including weakly scattering targets (ie, the above-mentioned second data).

Exemplarily, the above-mentioned first data may be a collection of multiple sampling point data, wherein each sampling point data corresponds to an amplitude value.

It should also be understood that the first data or the second data in this embodiment of the present application may be data in the form of a two-dimensional array. Exemplarily, the above-mentioned two-dimensional array may correspond to a two-dimensional coordinate system, the abscissa of the two-dimensional coordinate system may represent the distance direction (that is, the fast time), and the ordinate of the two-dimensional coordinate system may represent the azimuth direction (that is, the slow time). ). In the application scenario of the vehicle-mounted radar, the azimuth direction represents the movement direction of the vehicle (ie, the movement direction of the vehicle-mounted radar), and the distance direction represents the vertical direction of the vehicle's movement.

S204. Perform imaging processing on the second data to obtain the SAR image of the lane line.

In this embodiment of the present application, the data processing device may obtain the above-mentioned second data in two possible ways.

In a possible implementation manner, the data processing device may delete data whose amplitude is greater than or equal to the first threshold in the first data to obtain the second data.

The above method of acquiring the second data has a simple and easy processing process, effectively reduces the computing pressure of the data processing device, and at the same time improves the efficiency of lane detection.

In another possible implementation manner, the data processing device may obtain a point spread function of the data whose amplitude is greater than or equal to the first threshold according to the data whose amplitude is greater than or equal to the first threshold in the first data, and perform a point spread function in the first The data corresponding to the point spread function is removed from the first data to obtain the second data.

It should be understood that the data between the two first zero-crossing points on both sides of the maximum peak value of the above-mentioned point spread function can be called main lobe data, and the other data corresponding to the above-mentioned point spread function other than the main lobe data can be called side lobe data. data.

The above method of acquiring the second data can further filter out the side lobe data of the point spread function of the data while removing the main lobe data of the point spread function corresponding to the data, and simultaneously eliminate the main lobe data and The influence of side lobe data effectively improves the accuracy of lane line detection.

It should also be understood that the data processing device can obtain the point spread function of the data whose amplitude is greater than or equal to the first threshold in two different ways, which is not limited in this embodiment of the present application.

Mode 1, the data processing device can obtain the sampling point number corresponding to the data whose amplitude is greater than or equal to the first threshold, and input the sampling point number and the amplitude of the data whose amplitude is greater than or equal to the first threshold into the objective function , the type of the objective function can be, for example, a sinc type function, and a point spread function of data whose amplitude is greater than or equal to the first threshold is obtained. Exemplarily, in this embodiment of the present application, the above determined function is referred to as a target sinc-type function.

It should be understood that the point spread functions corresponding to different data are equivalent to translation and amplitude and phase transformation of the same signal form.

Exemplarily, taking the sampling point number i of any data whose amplitude is greater than or equal to the first threshold as an example, the data processing device can determine the signal amplitude A _i of the data according to the amplitude within the distance unit where the peak of the data is located, The serial number i and amplitude A _i of the above-mentioned sampling point data are input into the target sinc function to obtain the point spread function of the data, so that the corresponding amplitude values of the data at other distance unit positions can be obtained. The data processing device can then subtract the corresponding amplitude of the point spread function of the data on each distance unit from the data corresponding to each distance profile, so as to complete the filtering of the side lobes of the data and obtain the above-mentioned second data.

It should be understood that the objective function used to obtain the point spread function above is different under different SAR imaging algorithms, that is, the data processing device can determine the objective function according to the adopted SAR imaging processing algorithm. Illustratively, the SAR imaging algorithm may include a frequency scaling (FS) imaging algorithm, a range Doppler (RD) imaging algorithm, and the like.

It should also be understood that in the imaging process, in order to increase the peak-to-side lobe ratio and reduce the influence of the side lobes, a windowing process is usually performed. Therefore, in the imaging process, whether to perform windowing processing and the selected type of window function will affect the form of the above objective function.

In the following, taking the echo signal obtained by the radar under the FMCW system, when the SAR imaging process is performed, the windowing process is not performed as an example to describe in detail how the target sinc function corresponding to the SAR imaging algorithm is determined. Exemplarily, the expression of the SAR imaging algorithm in the azimuth time domain of the data after the range compression is completed is:

Among them, τ represents the fast range time, ζ represents the azimuth slow time, ζ _c represents the beam center deviation time, A _i is the gain related to the backscattering coefficient of the target, and represents the gain of the ith target,

is the sinc-type range envelope, which includes the target range migration with azimuth, and the last two terms give the gain and phase in the azimuth independent of range.

The expression of the range-compressed data in the azimuth frequency domain is:

Among them, f _ζ represents the azimuth frequency (also called Doppler frequency),

is the frequency domain form of the azimuth antenna pattern ω _a (ζ-ζ _c ₎ , Ka represents the azimuth modulation frequency, which is determined by parameters such as wavelength, radar speed, target distance, etc. R _0i represents the nearest slope of the ith target. distance. Similar to formula (1), the last three terms in the above formula give the gain and phase in the azimuth independent of the range, and the sinc-type range envelope is unchanged.

For the azimuth time domain and azimuth frequency domain data after range compression, the discrete form of the target sinc function in the range direction can be expressed as:

Among them, m represents the serial number of the range sampling unit, n represents the serial number of the azimuth sampling unit, R _i (n) represents the distance from the i-th target to the radar at time n in the azimuth direction, the parameter α represents the amplitude, and the parameter a represents the distance to the radar. The parameters related to the corresponding relationship between the sampling point and the actual distance, b represents the parameters related to the main lobe/side lobe width of the sinc-type function, and the general parameters a and b can be determined according to the radar system parameters or according to the sampling point of the distance envelope function.

For the range compression of the radar de-frequency-modulated echo signal under the FMCW system, ideally, the expression of the sinc-type range envelope is:

Among them, M represents the number of sampling points in the distance dimension, K _r represents the frequency modulation slope of the transmitted signal, c represents the speed of light, and F _s represents the signal sampling rate.

The above formula (3) is the target sinc-type function corresponding to the FS imaging algorithm. It should be understood that, when obtaining the point spread function of the data whose amplitude is greater than or equal to the first threshold value in the above-mentioned method 1, the distance of the data can be directed to the sampling unit serial number m, and the azimuth is to the distance R _i (n) corresponding to the sampling unit serial number n. , and the amplitude α of the data is substituted into formula (3) to obtain the point spread function of the data.

It should be understood that the sampling point number i of the data in the above example includes the range sampling unit number m and the azimuth sampling unit number n of the data.

Mode 2, the data processing device can estimate the amplitude and phase error of the point spread function of the data whose amplitude value is greater than or equal to the first threshold by the least square method, and obtain the point spread of the data according to the objective function (for example, the objective sinc type function). function.

Exemplarily, according to the data whose amplitude is greater than or equal to the first threshold in the first data, and the L (L is an integer greater than or equal to 0) data values on both sides of the distance dimension on the data distance profile, according to the principle of least squares Estimate the parameters α, a, and b in the above formula (3) to obtain the point scattering function.

It should be understood that the determination method of the objective function in Mode 2 is similar to that in Mode 1, and details are not repeated here.

As an optional embodiment, in the above S202, the echo data is preprocessed to obtain the first data, including: performing Doppler parameter estimation, motion parameter estimation, motion compensation and range compression on the echo data to obtain The above-mentioned first data. Correspondingly, in the above S204, performing imaging processing on the second data to obtain the SAR image of the lane line, including: quantizing the second data, Doppler modulation frequency estimation, azimuth phase error correction and azimuth compression to obtain the lane SAR image of the line.

It should be understood that the above motion compensation may include first-order motion compensation and second-order motion compensation.

As an optional embodiment, in the above S202, the echo data is preprocessed to obtain the first data, including: performing Doppler parameter estimation, motion parameter estimation, first-order motion compensation and distance estimation on the echo data obtained by the radar to compress to obtain the above-mentioned first data. Correspondingly, in the above S204, performing imaging processing on the second data to obtain a SAR image of the lane line, including: quantizing the second data, second-order motion compensation, Doppler modulation frequency estimation, azimuth phase error correction, azimuth phase error correction, and azimuth phase error correction. Compression to get the SAR image of the lane line.

It should be understood that if the echo data obtained by the above-mentioned radar is forward-squinting echo data (that is, the working mode of the radar is the echo data obtained by forward-squinting) or the echo data obtained by back-squinting (that is, the working mode of the radar is obtained by the backward-squinting view). echo data), then after performing Doppler parameter estimation and motion parameter estimation on the echo data obtained by the radar, it is also necessary to perform range linear motion compensation and Doppler center correction, so that the processed strabismus data can be equivalent to Front and side view data, and perform subsequent processing such as first-order motion compensation.

It should also be understood that the above-mentioned quantification process may be performed in any step after obtaining the above-mentioned second data (ie, S203 ), or may be performed after the SAR image is obtained, which is not limited in this embodiment of the present application.

As an optional embodiment, when the obtained SAR image of the lane line is an image in the slant range plane. The method 200 may further include: performing geometric deformation correction and coordinate transformation on the SAR image of the lane line to obtain an image in the ground distance plane.

The lane line images in the slant range plane and the ground range plane are described in detail below with reference to FIG. 3 . FIG. 3 shows a three-dimensional geometric diagram of radar imaging provided by an embodiment of the present application. As shown in Figure 3, the y-axis of the coordinate system represents the direction of vehicle movement (that is, the direction of movement of the radar, which is called the azimuth direction), the x-axis represents the direction of vertical vehicle movement (called the distance direction), and the z-axis represents the vertical plane xy. vertical upward direction. H (on the y-axis) is the height of the radar from the ground, taking the target P as an example, R ₀ is the shortest slant distance, θ is the down angle corresponding to the shortest distance, β is the slant angle, R is the slant distance, and X ₀ is P The corresponding ground distance, X _min and X _min are the nearest ground distance and the farthest ground distance of the imaging area.

The image in the ground distance plane is an image with an imaging width of X _min -X _min , and the image in the slant distance plane is an image with an imaging width of W ₁ -W ₂ .

As an optional embodiment, the transmit signal bandwidth B, the lower viewing angle θ, and the oblique viewing angle β of the above-mentioned radar satisfy:

where, Δx the width of the lane line,

Satisfy

c is the propagation speed of the electromagnetic wave.

Optionally, in actual calculation, c=3×10 ⁸ m/s.

As an optional embodiment, the working mode of the above-mentioned radar is a side view, a forward view or a backward view, and the imaging area of the radar is the road surface including the lane line on one side or both sides of the vehicle.

FIG. 4 and FIG. 5 are schematic diagrams of two different imaging modes according to the embodiments of the present application.

FIG. 4 is a schematic diagram of an imaging area provided by an embodiment of the present application. As shown in FIG. 4 , 1, 2, and 3 in the figure represent the possible installation positions of the on-board radar (only used for left and right indication, not height). When the vehicle 410 is in a normal driving state, the data processing device on the vehicle 410 can The lane markings 420 on the right side of the vehicle 410 or the lane markings 430 on the left side are imaged. FIG. 4 shows the imaging range of the lane line 420 on the right side of the vehicle 410 , that is, the shaded area on the right side of the vehicle 410 .

FIG. 5 is a schematic diagram of another imaging area provided by an embodiment of the present application. As shown in FIG. 5 , 1 and 2 in the figure represent the possible installation positions of the on-board radar (only used for left and right indication, not height). When the vehicle 510 is in a normal driving state, the data processing device on the vehicle 510 can The lane lines 520 and 530 on both sides of 510 are imaged. FIG. 5 shows the imaging ranges of the

lane lines

520 and 530 on the left and right sides of the vehicle 510 , that is, the shadow areas on both sides of the vehicle 510 .

As an optional embodiment, the above-mentioned radar is a millimeter-wave radar.

It should be understood that millimeter waves refer to electromagnetic waves with wavelengths between 1 mm and 10 mm, and the corresponding frequency range of millimeter waves is 30 GHz to 300 GHz. The characteristics of millimeter wave can include: large bandwidth, short wavelength, high resolution and strong penetration, the characteristics of millimeter wave make it suitable for application in the automotive field. Therefore, millimeter-wave radar has the ability to penetrate smoke, dust or fog, allowing millimeter-wave radar to work around the clock, all day long.

In the application scenario of vehicle radar, using millimeter wave radar as vehicle radar can better assist driving or automatic driving.

Based on the content described in the above embodiments, in order to better understand the various embodiments of the present application, the following uses the FS imaging algorithm as an example to describe the lane line detection method provided by the embodiments of the present application in detail with reference to FIGS. 6 to 8 . The FS imaging algorithm can include six processes: data preprocessing, motion compensation, range compression, strong scattering point filtering, azimuth compression and data postprocessing.

FIG. 6 is a schematic flowchart of an imaging algorithm 600 provided by the present application. As shown in Figure 6, the specific steps of the algorithm are as follows:

S601. Perform Doppler parameter estimation on the dechirp echo data to obtain first echo data.

S602. Perform motion parameter estimation on the first echo data to obtain second echo data.

S603 , performing linear motion compensation and Doppler center correction on the second echo data in the range time domain and the azimuth time domain to obtain echo data equivalent to a side view.

S604. Select a reference distance, use the trajectory error at the reference distance to perform envelope compensation and phase compensation on all distance directions of the echo data of the equivalent frontal view, complete the first-order motion compensation, and obtain the echo data after the first-order compensation .

S605. Perform azimuth fast Fourier transform (fast fourier transform, FFT) processing on the echo data after the first-order compensation, to obtain echo data after azimuth FFT processing.

S606: Multiply the echo data processed by the azimuth FFT by the frequency scaling factor to perform frequency scaling to obtain echo data after frequency scaling.

S607. Perform range FFT processing on the echo data after frequency scaling, to obtain echo data after range FFT processing.

S608. Perform residual video phase (residual video phase, RVP) correction on the echo data processed by the range FFT to obtain corrected echo data.

S609. Perform range-direction inverse fast Fourier transform (invert fast fourier transformation, IFFT) processing on the corrected echo data to obtain inversely transformed echo data.

S610. Multiply the inversely transformed echo data by a compensation factor to complete inverse frequency scaling, range cell migration (RCM) correction, and second range compression (SRC), to obtain a second range compression echo data.

S611. Perform range FFT processing on the echo data after secondary range compression, complete range compression, and obtain range-compressed data.

S612: Compensate the phase difference caused by the distance difference between other distance units and the reference distance unit on the distance-compressed data, complete second-order motion compensation, and obtain second-order compensated data (ie, the above-mentioned first data).

S613. Determine whether there is data whose amplitude exceeds the threshold η in the data after the second-order compensation. If there is data with an amplitude exceeding the threshold n, execute S614 and S615; if there is no data with an amplitude exceeding the threshold n, execute S616.

S614. Filter out the data exceeding the threshold to obtain filtered data (ie, the above-mentioned second data).

S615. Perform quantization processing on the filtered data to obtain processed data.

In the above filtering process, when the side lobes of the data exceeding the threshold η are small and the influence on the echo of the lane line is negligible, the data and the range gate data corresponding to the surrounding distance units can be directly removed. However, the side lobes of the sinc-type function formed after data compression exceeding the threshold η exist in the entire distance region. Therefore, when the far side lobes of the data also affect the echo of the lane line, the main lobe of the data and its side lobe waveforms need to be reconstructed, and the main lobe of the data exceeding the threshold η is filtered out in the range compressed image compressed data. and its sidelobe effects.

S616. Perform Doppler frequency modulation estimation on the data whose amplitude exceeds the threshold η or the processed data obtained in S615, to obtain data after the frequency modulation estimation.

S617. Perform azimuth and phase error correction on the data after frequency modulation estimation to obtain corrected data.

S618: Multiply the corrected data by the azimuth matching filter function to obtain data after azimuth matching processing.

S619 , perform azimuth IFFT processing on the data after azimuth matching processing, complete azimuth compression, and obtain a SAR image including lane line information (ie, the SAR image in the above-mentioned slant range plane).

S620. Perform geometric deformation correction and coordinate transformation on the SAR image containing lane line information, and convert the SAR image in the slant range plane into the SAR image in the ground range plane.

The lane line detection method provided by the embodiment of the present application obtains data less than a threshold η by filtering the acquired data after the second-order compensation, and finally obtains the imaging result of the lane line. This method is beneficial to obtain high-resolution SAR images of lane lines, and effectively improves the accuracy of lane line detection.

It should be understood that the above S601 to S603 are the specific processes of data preprocessing, S605 to S611 are the specific processes of distance compression, S604, S612, S616 and S617 are the specific processes of motion compensation, and S613 to S615 are the specific processes of filtering out strong scattering points. Flow, S618 and S619 are the specific flow of azimuth compression, and S620 is the specific flow of data post-processing.

It should be understood that the step of filtering the strong scattering points can be performed in any corresponding step in the azimuth time domain or azimuth frequency domain after range compression. Exemplarily, the above step of filtering out strong scattering points may also be performed after RVP correction, or after the second range FFT processing, which is not limited in this embodiment of the present application.

FIG. 7 is a schematic flowchart of another imaging algorithm 700 provided by the present application. The difference from the algorithm flow shown in FIG. 6 is that the algorithm flow shown in FIG. 7 performs the step of filtering out strong scattering points after RVP correction. As shown in Figure 7, the specific steps of the algorithm are as follows:

S701 to S708 are the same as the above-mentioned S601 to S608, and are not repeated here.

S709. Determine whether there is data whose amplitude exceeds the threshold η in the corrected echo data (ie, the above-mentioned first data). If there is data with an amplitude exceeding the threshold n, execute S710 and S711; if there is no data with an amplitude exceeding the threshold n, execute S712.

S710 and S711 are the same as the above-mentioned S614 and S615, and are not repeated here.

S712: Perform range IFFT processing on the data whose amplitude exceeds the threshold η or the processed data obtained in S711 to obtain inversely transformed echo data.

S713 to S715 are the same as the above-mentioned S610 to S612, and are not repeated here.

S716: Perform Doppler frequency modulation estimation on the data after the second-order compensation to obtain data after the frequency modulation estimation.

S717 to S720 are the same as the above-mentioned S617 to S620, and are not repeated here.

The lane line detection method provided by the embodiment of the present application obtains data less than a threshold η by filtering the acquired corrected data, and finally obtains the imaging result of the lane line. This method is conducive to obtaining high-resolution SAR images of lane lines, and effectively improves the accuracy of lane line detection.

It should be understood that S701 to S703 are specific processes of data preprocessing, S705 to S708, S713 and S714 are specific processes of distance compression, S704, S715 to S717 are specific processes of motion compensation, and S709 to S711 are the specific processes of filtering out strong scattering points The specific flow, S718 and S719 are the specific flow of azimuth compression, and S720 is the specific flow of data post-processing.

FIG. 8 is a schematic flowchart of yet another imaging algorithm 800 provided by the present application. The difference from the algorithm flow shown in FIG. 6 is that the algorithm flow shown in FIG. 8 performs the step of filtering out strong scattering points after the second range FFT processing. As shown in Figure 8, the specific steps of the algorithm are as follows:

S801 to S811 are the same as the above-mentioned S601 to S611, and are not repeated here.

S812: Determine whether there is data whose amplitude exceeds the threshold η in the distance-compressed data. If there is data whose amplitude exceeds the threshold n, execute S813 and S814; if there is no data whose amplitude exceeds the threshold n, execute S815.

S813 to S814 are the same as the above-mentioned S614 to S615, and are not repeated here.

S815. Perform second-order motion compensation on the data whose amplitude exceeds the threshold η or the processed data obtained in S814, to obtain second-order compensated data.

S816. Perform Doppler frequency modulation estimation on the data after the second-order compensation to obtain data after the frequency modulation estimation.

S817 to S820 are the same as the above-mentioned S617 to S620, and are not repeated here.

It should be understood that the above step of filtering out the strong scattering points can also be performed after the SAR image is acquired (ie, S620, S720, and S820). Exemplarily, in the application scenario of the vehicle-mounted radar, after the SAR image is obtained, the image of the lane line can be obtained through the image processing technology.

In the lane line detection method provided by the embodiment of the present application, by filtering the obtained distance-compressed data, data less than a threshold η is obtained, and finally an imaging result of the lane line is obtained. This method is conducive to obtaining high-resolution SAR images of lane lines, and effectively improves the accuracy of lane line detection.

It should be understood that S801 to S803 are specific processes of data preprocessing, S805 to S811 are specific processes of distance compression, S804, S815 to S817 are specific processes of motion compensation, S812 to S814 are specific processes of filtering out strong scattering points, S818 And S819 is the specific process of azimuth compression, and S820 is the specific process of data post-processing.

Optionally, if other imaging algorithms are used, for example, RD algorithm, backpropagation algorithm (BP) algorithm, etc., the step of filtering out strong scattering points can be performed after distance compression.

The lane line detection method of the embodiment of the present application is described in detail above with reference to FIG. 2 to FIG. 8 , and the lane line detection apparatus of the embodiment of the present application will be described in detail below with reference to FIG. 9 and FIG. 10 .

It should be understood that the lane line detection device in this embodiment of the present application may be the radar itself, or a chip or integrated circuit of a processor in the radar, or may be a device independent of the radar, installed on the vehicle together with the radar, or processed in the device The chip or integrated circuit of the device is not limited in this embodiment of the present application.

FIG. 9 shows a lane line detection apparatus 900 provided by an embodiment of the present application. The apparatus 900 includes an acquisition module 910 and a processing module 920 .

Among them, the acquisition module 910 is used to obtain echo data of the ground by using radar, and the ground includes lane lines; the processing module 920 is used to preprocess the echo data to obtain first data; performing filtering processing on the data to obtain second data, where the second data is data whose amplitude is smaller than a first threshold; and performing imaging processing on the second data to obtain a SAR image of the lane line.

It should be understood that the echo data on the ground is obtained by the radar through the receiving module and the transmitting module. The transmitting module may be the transmitting antenna or the transmitting antenna array of the radar, and the receiving module may be the receiving antenna or the receiving antenna array of the radar.

If the above-mentioned apparatus 900 is the radar itself, the above-mentioned apparatus further includes: a transceiver module for obtaining echo data on the ground by receiving and/or transmitting signals, and sending the echo data to the obtaining module 910 .

If the above device 900 is a device independent of the radar, the radar can use its own transceiver module to receive and/or transmit signals, obtain echo data on the ground, and then send the echo data to the device 900 . In this way, the above obtaining module 910 is specifically configured to: obtain echo data from the radar.

Optionally, the processing module 920 is further configured to: remove data whose amplitude is greater than or equal to the first threshold from the first data to obtain the second data.

Optionally, the processing module 920 is further configured to: obtain a point spread function of the data according to the data whose amplitude is greater than or equal to the first threshold in the first data; remove all the data in the first data The data corresponding to the point spread function is obtained to obtain the second data.

Optionally, the processing module 920 is further configured to: perform Doppler parameter estimation, motion parameter estimation, motion compensation and range compression on the echo data to obtain the first data.

Optionally, the processing module 920 is further configured to: perform quantization, Doppler modulation frequency estimation, azimuth phase error correction, and azimuth compression on the second data to obtain the SAR image.

Optionally, the processing module 920 is further configured to: perform geometric deformation correction and coordinate transformation on the SAR image to obtain an image in the ground distance plane.

Optionally, the transmit signal bandwidth B, the lower viewing angle θ, and the oblique viewing angle β of the radar satisfy:

where Δx is the width of the lane line,

Satisfy

c is the propagation speed of the electromagnetic wave.

Optionally, the working mode of the radar is a side view, a forward view or a backward view, and the imaging area of the radar is the road surface including the lane line on one side or both sides of the vehicle.

Optionally, the radar is a millimeter wave radar.

It should be understood that the apparatus 900 here is embodied in the form of functional modules. The term "module" as used herein may refer to an application specific integrated circuit (ASIC), an electronic circuit, a processor for executing one or more software or firmware programs (eg, a shared processor, a dedicated processor, or a group of processors, etc.) and memory, merge logic, and/or other suitable components to support the described functions. In an optional example, those skilled in the art can understand that the apparatus 900 may be specifically the data processing device in the above embodiment or a chip in the data processing device, or the function of the data processing device in the above embodiment or the data processing device The functions of the chips in can be integrated in the apparatus 900, and the apparatus 900 can be used to execute each process and/or step corresponding to the data processing device in the above method embodiments, which will not be repeated here in order to avoid repetition.

The above-mentioned apparatus 900 has the function of implementing the corresponding steps performed by the data processing device in the above-mentioned method; the above-mentioned functions may be implemented by hardware, or by executing corresponding software by hardware. The hardware or software includes one or more modules corresponding to the above functions. For example, the above-mentioned obtaining module 910 may be a communication interface, such as a transceiver interface.

In the embodiment of the present application, the apparatus 900 in FIG. 9 may also be a chip or a system of chips, such as a system on chip (system on chip, SoC). Correspondingly, the acquisition module 910 may be a transceiver circuit of the chip, which is not limited in this application.

FIG. 10 shows another lane line detection apparatus 1000 provided by an embodiment of the present application. The apparatus 1000 includes a processor 1010 , a transceiver 1020 and a memory 1030 . The processor 1010, the transceiver 1020 and the memory 1030 communicate with each other through an internal connection path, the memory 1030 is used to store instructions, and the processor 1010 is used to execute the instructions stored in the memory 1030 to control the transceiver 1020 to send signals and / or receive signals.

It should be understood that the lane line detection device 1000 may be the radar itself, or may be a device independent of the radar and installed on the vehicle together with the radar.

If the device 1000 is the radar itself, the transceiver 1020 is configured to: obtain echo data on the ground by receiving and/or transmitting signals; the processor 1010 is configured to: preprocess the echo data to obtain the first performing filtering processing on the first data to obtain second data, where the second data is data whose amplitude is less than a first threshold; and performing imaging processing on the second data to obtain the SAR image.

If the device 1000 is a device independent of the radar, the radar can use its own transceiver to receive and/or transmit signals, obtain echo data on the ground, and then send the echo data to the device 1000 . In this way, the processor 1010 is configured to: receive echo data from the radar through the transceiver 1020, preprocess the echo data to obtain first data, and filter the first data to obtain second data , the second data is data with an amplitude smaller than a first threshold; and, performing imaging processing on the second data to obtain a SAR image of the lane line.

It should be understood that the apparatus 1000 may be specifically the data processing device or the chip in the data processing device in the above embodiments, or the functions of the data processing device or the function of the chip in the data processing device in the above embodiments may be integrated in the apparatus 1000 , the apparatus 1000 may be configured to execute each step and/or process corresponding to the data processing device or a chip in the data processing device in the above method embodiments. Optionally, the memory 1030 may include read only memory and random access memory and provide instructions and data to the processor. A portion of the memory may also include non-volatile random access memory. For example, the memory may also store device type information. The processor 1010 may be configured to execute the instructions stored in the memory, and when the processor executes the instructions, the processor may execute various steps and/or processes corresponding to the data processing device in the above method embodiments.

It should be understood that in this embodiment of the present application, the processor may be a central processing unit (central processing unit, CPU), and the processor may also be other general-purpose processors, digital signal processors (DSPs), application specific integrated circuits (ASICs) ), field programmable gate array (FPGA) or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. A general purpose processor may be a microprocessor or the processor may be any conventional processor or the like.

In the implementation process, each step of the above-mentioned method 200 may be completed by a hardware integrated logic circuit in a processor or an instruction in the form of software. The steps of the methods disclosed in conjunction with the embodiments of the present application may be directly embodied as executed by a hardware processor, or executed by a combination of hardware and software modules in the processor. The software modules may be located in random access memory, flash memory, read-only memory, programmable read-only memory or electrically erasable programmable memory, registers and other storage media mature in the art. The storage medium is located in the memory, and the processor executes the instructions in the memory, and completes the steps of the above method in combination with its hardware. To avoid repetition, detailed description is omitted here.

Embodiments of the present application provide a computer-readable storage medium, where the computer storage medium is used to store a computer program, and the computer program is used to implement the methods corresponding to various possible implementations in the foregoing embodiments.

The embodiments of the present application provide a computer program product, and the computer program product includes a computer program program (also referred to as code, or instructions), and when the computer program runs on a computer, the computer can execute the above embodiments Methods corresponding to various possible implementations in .

Those of ordinary skill in the art can realize that the units and algorithm steps of each example described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are performed in hardware or software depends on the specific application and design constraints of the technical solution. Skilled artisans may implement the described functionality using different methods for each particular application, but such implementations should not be considered beyond the scope of this application.

Those skilled in the art can clearly understand that, for the convenience and brevity of description, the specific working process of the above-described systems, devices and units may refer to the corresponding processes in the foregoing method embodiments, which will not be repeated here.

In the several embodiments provided in this application, it should be understood that the disclosed system, apparatus and method may be implemented in other manners. For example, the apparatus embodiments described above are only illustrative. For example, the division of the units is only a logical function division. In actual implementation, there may be other division methods. For example, multiple units or components may be combined or Can be integrated into another system, or some features can be ignored, or not implemented. On the other hand, the shown or discussed mutual coupling or direct coupling or communication connection may be through some interfaces, indirect coupling or communication connection of devices or units, and may be in electrical, mechanical or other forms.

The units described as separate components may or may not be physically separated, and components displayed as units may or may not be physical units, that is, may be located in one place, or may be distributed to multiple network units. Some or all of the units may be selected according to actual needs to achieve the purpose of the solution in this embodiment.

In addition, each functional unit in each embodiment of the present application may be integrated into one processing unit, or each unit may exist physically alone, or two or more units may be integrated into one unit.

The functions, if implemented in the form of software functional units and sold or used as independent products, may be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present application can be embodied in the form of a software product in essence, or the part that contributes to the prior art or the part of the technical solution. The computer software product is stored in a storage medium, including Several instructions are used to cause a computer device (which may be a personal computer, a server, or a network device, etc.) to execute all or part of the steps of the methods described in the various embodiments of the present application. The aforementioned storage medium includes: U disk, mobile hard disk, read-only memory (ROM), random access memory (RAM), magnetic disk or optical disk and other media that can store program codes .

The above are only specific embodiments of the present application, but the protection scope of the present application is not limited to this. should be covered within the scope of protection of this application. Therefore, the protection scope of the present application should be subject to the protection scope of the claims.

Claims

A method for detecting lane lines, comprising:

Using radar to obtain echo data of the ground, the ground including lane lines;

Preprocessing the echo data to obtain first data;

filtering the first data to obtain second data, where the second data is data whose amplitude is less than the first threshold;

Perform imaging processing on the second data to obtain a synthetic aperture radar SAR image of the lane line.
The method of claim 1, wherein the filtering of the first data to obtain the second data comprises:

The second data is obtained by removing data whose amplitude is greater than or equal to the first threshold from the first data.
The method of claim 1, wherein the filtering of the first data to obtain the second data comprises:

obtaining a point spread function of the data according to the data whose amplitude is greater than or equal to the first threshold in the first data;

The data corresponding to the point spread function is removed from the first data to obtain the second data.
The method according to any one of claims 1 to 3, wherein the preprocessing of the echo data to obtain the first data comprises:

Doppler parameter estimation, motion parameter estimation, motion compensation and range compression are performed on the echo data to obtain the first data.
The method according to claim 4, wherein, performing imaging processing on the second data to obtain the SAR image of the lane line, comprising:

Perform quantization, Doppler modulation frequency estimation, azimuth phase error correction, and azimuth compression on the second data to obtain the SAR image.
The method according to any one of claims 1 to 5, wherein the SAR image is an image in a slant range plane, and the method further comprises:

Perform geometric deformation correction and coordinate transformation on the SAR image to obtain an image in the ground distance plane.
The method according to any one of claims 1 to 6, wherein the radar transmit signal bandwidth B, lower viewing angle θ, and oblique viewing angle β satisfy:

where Δx is the width of the lane line,
Satisfy
c is the propagation speed of the electromagnetic wave.
The method according to any one of claims 1 to 7, wherein the working mode of the radar is frontal side view, forward squinting or rearward squinting, and the imaging area of the radar is one side or both sides of the vehicle The road surface that contains the lane lines.
The method according to any one of claims 1 to 8, wherein the radar is a millimeter wave radar.
A lane line detection device, characterized in that it includes:

an acquisition module for acquiring echo data of the ground by using the radar, and the ground includes lane lines;

a processing module, configured to preprocess the echo data to obtain first data; filter the first data to obtain second data, where the second data is data whose amplitude is less than a first threshold; And, performing imaging processing on the second data to obtain a synthetic aperture radar SAR image of the lane line.
The apparatus of claim 10, wherein the processing module is further configured to:

The second data is obtained by removing data whose amplitude is greater than or equal to the first threshold from the first data.
The apparatus of claim 10, wherein the processing module is further configured to:

obtaining a point spread function of the data according to the data whose amplitude is greater than or equal to the first threshold in the first data;

The data corresponding to the point spread function is removed from the first data to obtain the second data.
The device according to any one of claims 10 to 12, wherein the processing module is further configured to:

Doppler parameter estimation, motion parameter estimation, motion compensation and range compression are performed on the echo data to obtain the first data.
The apparatus of claim 13, wherein the processing module is further configured to:

Perform quantization, Doppler modulation frequency estimation, azimuth phase error correction, and azimuth compression on the second data to obtain the SAR image.
The device according to any one of claims 10 to 14, wherein the processing module is further configured to:

Perform geometric deformation correction and coordinate transformation on the SAR image to obtain an image in the ground distance plane.
The device according to any one of claims 10 to 15, wherein the radar transmit signal bandwidth B, lower viewing angle θ, and oblique viewing angle β satisfy:

where Δx is the width of the lane line,
Satisfy
c is the propagation speed of the electromagnetic wave.
The device according to any one of claims 10 to 16, characterized in that, the working mode of the radar is a front view, a forward view or a backward view, and the imaging area of the radar is one side or two sides of the vehicle The road surface that contains the lane lines.
The apparatus according to any one of claims 10 to 17, wherein the radar is a millimeter wave radar.
A lane line detection device, characterized in that it comprises: a processor, the processor is coupled with a memory, the memory is used for storing a computer program, and when the processor calls the computer program, the device is made to execute A method as claimed in any one of claims 1 to 9.
A terminal, characterized in that the terminal comprises the device according to any one of claims 10 to 19.
A computer-readable storage medium, characterized by being used for storing a computer program, the computer program comprising instructions for implementing the method according to any one of claims 1 to 9.
A computer program product comprising computer program code, characterized in that, when the computer program code is run on a computer, the computer is made to implement the method according to any one of claims 1 to 9 .