Method for automatically detecting obstacle in front of vehicle based on radar

Abstract

The invention provides a method for automatically detecting obstacles in front of a vehicle based on radars. The method comprises the steps that a first radar and a second radar are symmetrically arranged in front of the vehicle; the detection range of the first radar and the detection range of the second radar are divided into a first area, a second area and a third area; the first area and the third area are provided with a first threshold, and the second area is provided with a superposition threshold; the first radar and the second radar detect front objects through a first threshold and a superposition threshold, and output detection results in each detection area; wherein the first area is located on the left side of the first radar, the third area is located on the right side of the second radar, the second area is located between the first radar and the second radar, and the second area comprises an electromagnetic wave detection range which both the first radar and the second radar can reach. Therefore, the intelligent degree and the accuracy of the detection are improved.

Description

Technical Field

[0001] The present invention relates to the technical field of vehicle radar detection, and more specifically, to a method for automatically detecting obstacles in front of a vehicle based on radar. Background Art

[0002] In the current automotive autonomous driving technology, a key component is the forward millimeter-wave radar installed in front of the vehicle. This device transmits electromagnetic waves to the surrounding environment through its transmitting antenna to detect various targets in front, including trucks, cars, and pedestrians. When these electromagnetic waves encounter the surface of the target, they are reflected, and some of the reflected electromagnetic waves return to the receiving antenna of the forward millimeter-wave radar. Subsequently, these reflected signals are processed by a series of complex algorithms to determine the type of target in front. This process is an important basis for realizing autonomous driving functions such as adaptive cruise control and emergency braking. However, it is worth noting that a single forward millimeter-wave radar generates main lobes and side lobes when emitting electromagnetic waves. The main lobe is used to actually detect the target in front, and the side lobes, although not directly used for detection, often reflect targets with weaker energy from the surroundings, such as diffuse reflections, grass, or small targets.

[0003] In order to effectively process these reflected signals from the side lobes, a single forward millimeter-wave radar usually adopts a filter threshold control strategy. The core of this strategy is to set a single threshold to filter the side lobes of electromagnetic waves. However, in practical applications, if the radar cross-section of pedestrians reflected by the main lobe is -7dBsm, and the radar cross-section of diffuse reflections, grass or small targets reflected by the side lobes is also around -7dBsm, then special attention should be paid when setting the threshold. If the threshold is set too high, some important target information may be missed, thereby affecting the accuracy of the autonomous driving function and the driving safety of passengers; if the threshold is set too low, it may introduce too much noise and interference signals, which is also not conducive to the stable operation of the autonomous driving system. Therefore, how to reasonably set the filter threshold while ensuring detection accuracy has become an issue that requires careful balance. Summary of the invention

[0004] The present invention provides a method for automatically detecting obstacles in front of a vehicle based on radar, aiming to solve the problem of inaccurate detection caused by the single setting of electromagnetic wave sidelobe threshold in traditional methods, and to improve the intelligence and accuracy of detection.

[0005] To achieve the above object, the present invention provides a method for automatically detecting obstacles in front of a vehicle based on radar, comprising:

[0006] A first radar and a second radar are symmetrically arranged in front of the vehicle;

[0007] Dividing the detection ranges of the first radar and the second radar into a first area, a second area, and a third area;

[0008] The first area and the third area are provided with a first threshold, and the second area is provided with an overlapping threshold;

[0009] The first radar and the second radar detect the front object through the first threshold and the superposition threshold, and output the detection results in each detection area;

[0010] The first area is located on the left side of the first radar, the third area is located on the right side of the second radar, the second area is located between the first radar and the second radar, and the second area includes an electromagnetic wave detection range that can be reached by both the first radar and the second radar.

[0011] In one embodiment, the first radar includes a first main lobe and a first side lobe, and the second radar includes a second main lobe and a second side lobe.

[0012] In one embodiment, the first radar and the second radar generate three amplitudes after superposition, including the amplitude generated by the superposition of the first main lobe and the first main lobe, the amplitude generated by the superposition of the first main lobe and the second side lobe, or the amplitude generated by the superposition of the second main lobe and the first side lobe, and the amplitude generated by the superposition of the first side lobe and the second side lobe.

[0013] In one embodiment, the amplitude generated by the superposition of the first main lobe and the first main lobe identifies the effective actual target object and is completely converted into an output signal;

[0014] The amplitude generated by the superposition of the first main lobe and the second side lobe or the amplitude generated by the superposition of the second main lobe and the first side lobe identifies the effective actual target and is completely converted into an output signal;

[0015] The amplitude generated by the superposition of the first side lobe and the second side lobe identifies invalid targets and provides false information. At this time, a superposition threshold is set for the amplitude generated by the superposition of the first side lobe and the second side lobe to perform information filtering.

[0016] In one embodiment, setting a first threshold for the first area specifically includes: using a first sidelobe filtering algorithm for the first area, wherein the first sidelobe filtering algorithm filters invalid targets identified by the first sidelobe.

[0017] In one embodiment, setting a superposition threshold for the second area specifically includes: the second area adopts a second sidelobe filtering algorithm, and the second sidelobe filtering algorithm filters invalid targets identified by superposition of the first sidelobe and the second sidelobe.

[0018] In one embodiment, setting a first threshold for the third area specifically includes: the third area adopts a first sidelobe filtering algorithm, and the first sidelobe filtering algorithm filters invalid targets identified by the second sidelobe.

[0019] In one embodiment, the first radar receives signals about the target object in the first area and the second area filtered by the first sidelobe filtering algorithm and the second sidelobe filtering algorithm;

[0020] The second radar receives signals about the target object in the second area and the third area filtered by the first sidelobe filtering algorithm and the second sidelobe filtering algorithm.

[0021] In one embodiment, the first radar and the second radar have the same horizontal detection angle range, amplitude, and period.

[0022] In one embodiment, when the vehicle is autonomously driving, after the first radar and the second radar receive valid signals from target objects, they transmit the signals from the target objects to the autonomous driving domain controller.

[0023] The present invention has the following beneficial effects:

[0024] 1. Improved accuracy: The present invention sets two radars to avoid the problems of too simple electromagnetic wave sidelobe threshold setting and single detection area algorithm in a single millimeter wave radar, and significantly improves the detection precision, accuracy and stability of the target.

[0025] 2. Intelligence: The present invention is applicable to autonomous driving functions and can enhance the perception capabilities of L2, L2+ and even higher-level autonomous driving, while enhancing the comfort and safety of drivers, bringing significant economic benefits to manufacturing companies. BRIEF DESCRIPTION OF THE DRAWINGS

[0026] Figure 1 A schematic diagram of a flow chart of a method for automatically detecting obstacles in front of a vehicle based on radar according to an embodiment of the present invention;

[0027] Figure 2 A schematic diagram of the principle of a method for automatically detecting obstacles in front of a vehicle based on radar according to an embodiment of the present invention;

[0028] Figure 3 A schematic diagram of a structure for dividing a detection range into regions in a method for automatically detecting obstacles in front of a vehicle based on radar according to an embodiment of the present invention;

[0029] Figure 4 FIG. 4 is a schematic diagram of beam comparison between a single radar and two radars according to an embodiment of the present invention. DETAILED DESCRIPTION

[0030] In order to make the purpose, technical scheme and advantages of the implementation of this application clearer, the technical scheme in the embodiment of this application will be described in more detail below in conjunction with the drawings in the embodiment of this application. In the drawings, the same or similar reference numerals represent the same or similar elements or elements with the same or similar functions. The described embodiments are part of the embodiments of this application, not all of them. The embodiments described below with reference to the drawings are exemplary and are intended to be used to explain this application, and should not be construed as limitations on this application. Based on the embodiments in this application, all other embodiments obtained by ordinary technicians in this field without making creative work are within the scope of protection of this application.

[0031] Figure 1 The present invention is a flowchart of a method for automatically detecting obstacles in front of a vehicle based on radar according to an embodiment of the present invention. The method for automatically detecting obstacles in front of a vehicle based on radar includes:

[0032] A first radar and a second radar are symmetrically arranged in front of the vehicle;

[0033] Dividing the detection ranges of the first radar and the second radar into a first area, a second area, and a third area;

[0034] The first area and the third area are provided with a first threshold, and the second area is provided with an overlapping threshold;

[0035] The first radar and the second radar detect the front object through the first threshold and the superposition threshold, and output the detection results in each detection area;

[0036] The first area is located on the left side of the first radar, the third area is located on the right side of the second radar, the second area is located between the first radar and the second radar, and the second area includes an electromagnetic wave detection range that can be reached by both the first radar and the second radar.

[0037] Specifically, the detection ranges of the first radar and the second radar are divided into areas according to the detection ranges and angles of the first radar and the second radar.

[0038] In one embodiment, the first radar includes a first main lobe and a first side lobe, and the second radar includes a second main lobe and a second side lobe.

[0039] In one embodiment, the first radar and the second radar generate three amplitudes after superposition, including the amplitude generated by the superposition of the first main lobe and the first main lobe, the amplitude generated by the superposition of the first main lobe and the second side lobe, or the amplitude generated by the superposition of the second main lobe and the first side lobe, and the amplitude generated by the superposition of the first side lobe and the second side lobe.

[0040] In one embodiment, the amplitude generated by the superposition of the first main lobe and the first main lobe identifies the effective actual target object and is completely converted into an output signal;

[0041] The amplitude generated by the superposition of the first main lobe and the second side lobe or the amplitude generated by the superposition of the second main lobe and the first side lobe identifies the effective actual target and is completely converted into an output signal;

[0042] The amplitude generated by the superposition of the first side lobe and the second side lobe identifies invalid targets and provides false information. At this time, a superposition threshold is set for the amplitude generated by the superposition of the first side lobe and the second side lobe to perform information filtering.

[0043] In one embodiment, setting a first threshold for the first area specifically includes: using a first sidelobe filtering algorithm for the first area, wherein the first sidelobe filtering algorithm filters invalid targets identified by the first sidelobe.

[0044] In one embodiment, setting a superposition threshold for the second area specifically includes: the second area adopts a second sidelobe filtering algorithm, and the second sidelobe filtering algorithm filters invalid targets identified by superposition of the first sidelobe and the second sidelobe.

[0045] In one embodiment, setting a first threshold for the third area specifically includes: the third area adopts a first sidelobe filtering algorithm, and the first sidelobe filtering algorithm filters invalid targets identified by the second sidelobe.

[0046] Specifically, the core of the sidelobe filtering algorithm is to reduce or eliminate the sidelobe components in the radar signal, which are usually caused by the non-ideality of the antenna pattern. In vehicle radar, sidelobes may cause false alarms, misidentification of targets, or degradation of signal quality. Therefore, the sidelobe filtering algorithm is crucial to improving the detection accuracy and anti-interference ability of the radar.

[0047] Common sidelobe filtering algorithms include:

[0048] Window function weighting method: By weighting the radar transmission signal or receiving signal, the sidelobe level is reduced. Common window functions include Blackman window, rectangular window, Hamming window, triangular window and Hanning window.

[0049] Adaptive sidelobe cancellation algorithm: Utilizes the signals received by the auxiliary antenna and the main antenna to eliminate sidelobe interference through adaptive filtering technology. The algorithm can adjust the filter coefficients in real time to adapt to different interference environments.

[0050] Sidelobe blanking technology: Use an auxiliary antenna with a gain less than the main lobe gain of the main antenna but greater than the sidelobe gain of the main antenna. By comparing the signal amplitudes received by the main channel and the auxiliary channel, when the interference signal amplitude received by the auxiliary channel is greater than the target signal amplitude received by the main channel, the output of the main channel is turned off to eliminate sidelobe interference.

[0051] In one embodiment, the first radar receives signals about the target object in the first area and the second area filtered by the first sidelobe filtering algorithm and the second sidelobe filtering algorithm;

[0052] The second radar receives signals about the target object in the second area and the third area filtered by the first sidelobe filtering algorithm and the second sidelobe filtering algorithm.

[0053] In one embodiment, the first radar and the second radar have the same horizontal detection angle range, amplitude, and period.

[0054] In one embodiment, when the vehicle is autonomously driving, after the first radar and the second radar receive valid signals from target objects, they transmit the signals from the target objects to the autonomous driving domain controller.

[0055] It is also possible to verify the effective target signals received by the first radar and the second radar. By comparing and confirming the signal output of the targets in multiple areas, it is possible to verify whether the first radar and the second radar accurately identify the target signals in the second area.

[0056] An embodiment of the present invention is specifically as follows:

[0057] Two identical forward millimeter-wave radars are arranged in front of the vehicle, one on each side, which are the first radar and the second radar. For example, the horizontal detection angle range of the two millimeter-wave radars is 120°, and the amplitude, period, etc. are exactly the same;

[0058] According to the superposition principle of the main and sidelobe beam amplitudes, the detection area of ​​the two forward millimeter-wave radar systems can be divided into three areas, assuming that they are the first area, the second area, and the third area. Among them, for the first and third areas, because outside the car's own lane, there is no need to detect targets at a long distance, such as cars, and only the targets at a short distance on the left and right sides, such as pedestrians, can be detected. A relatively stable radar cross-sectional area can be received. Therefore, when making a target algorithm, it can be distinguished from the need to take into account the detection of long-distance targets. The algorithm for the first and third areas can be used specifically, and the threshold of the sidelobe filter can be appropriately increased to filter out weak targets and invalid targets.

[0059] For the second area: For example, the radar uses a single forward millimeter wave radar beam with a main lobe amplitude of 2L and a side lobe amplitude of 0.5L. Figure 3 As shown in the figure, if the same forward millimeter-wave radar is arranged on the left and right sides of the car, the following will appear in the second area: Figure 4 The superposition state of the two forward millimeter-wave radar beams shown in the figure will form three amplitudes: 4L amplitude obtained by superposing the first main lobe and the second main lobe, 2.5L amplitude obtained by superposing the first main lobe and the second side lobe or the second main lobe and the first side lobe, and 1L amplitude obtained by superposing the first side lobe and the second side lobe.

[0060] The superimposed amplitude of 4L is an effective actual target and can be completely converted into an output signal;

[0061] For the superposition amplitude of 2.5L, there is an effective actual target, so it also needs to be fully converted into output information;

[0062] The superimposed amplitude of 1L is an invalid target and a false signal, which can be filtered out by a threshold.

[0063] For the superposition amplitude of 2.5L, a new filtering threshold algorithm is set specifically for the second area according to the superposition RCS (radar cross section) strength received by the left and right radars. In this way, the sidelobe threshold that should have received the false target with an amplitude of 0.5L can be increased to the superposition threshold of the main lobe + side lobe amplitude of 2.5L, such as Figure 4 The superposition threshold shown can solve the problem of difficulty in distinguishing effective actual targets, such as pedestrians, from false targets, such as diffuse reflection clutter, due to the long detection distance and the weak radar cross-section area of ​​the target object, so as to accurately output the signal of the target object, such as pedestrians, and improve the experience and safety of autonomous driving.

[0064] From the algorithm level, Figure 4 As shown, for the first radar, different sidelobe filtering algorithms can be used in different detection areas, and the radar cross-section RCS reflected by different targets in the first area and the second area can be received. In this way, different sidelobe filtering algorithms can be set, as well as different sidelobe filtering thresholds, to distinguish false targets or invalid targets and clutter; for the second radar, the principle is the same.

[0065] From the perspective of radar signal self-fusion, Figure 2 As shown, after the first radar and the second radar receive the reflected signal of the target object, they can simultaneously transmit it to the autonomous driving domain controller, and then perform signal fusion in the autonomous driving domain controller. In this way, the accuracy of the target object signals identified by the two radars in the second area can be verified again, further improving the safety of autonomous driving.

[0066] The principle of the method is as follows: the first radar transmits electromagnetic waves, the electromagnetic waves reach the targets in the first area and the second area of ​​the detection range, and then the target signals in the first area and the second area are reflected back to the first radar. The second radar sets a first threshold for the first area and a superposition threshold for the second area through different sidelobe threshold algorithms, and then the first radar filters out the target signals in the first area and the target signals in the second area.

[0067] The second radar transmits electromagnetic waves, which reach the targets in the third area and the second area of ​​the detection range, and then reflect the target signals in the third area and the second area back to the first radar. The second radar sets a first threshold for the third area and a superposition threshold for the second area through different sidelobe threshold algorithms, and then filters out the target signals in the third area and the target signals in the second area.

[0068] The first radar inputs the target signal in the first area and the target signal in the second area to the autonomous driving domain controller; at the same time, the second radar also inputs the target signal in the third area and the target signal in the second area to the autonomous driving domain controller;

[0069] In the autonomous driving domain controller, the target signals in the second area are compared and integrated, and the information obtained from the first area, the second area, and the third area is judged to determine whether it is correct, and then the information is output.

[0070] The present invention has the following beneficial effects:

[0071] 1. Improved accuracy: The present invention sets two radars to avoid the problems of too simple electromagnetic wave sidelobe threshold setting and single detection area algorithm in a single millimeter wave radar, and significantly improves the detection precision, accuracy and stability of the target.

[0072] 2. Intelligence: The present invention is applicable to autonomous driving functions and can enhance the perception capabilities of L2, L2+ and even higher-level autonomous driving, while enhancing the comfort and safety of drivers, bringing significant economic benefits to manufacturing companies.

[0073] In the description of the present application, it should be noted that the terms used herein are only for describing specific embodiments, and are not intended to limit the exemplary embodiments according to the present application. For ease of description, the sizes of the various parts shown in the drawings are not drawn according to the actual proportional relationship. The technology, methods and equipment known to ordinary technicians in the relevant field may not be discussed in detail, but in appropriate cases, the technology, methods and equipment should be regarded as part of the authorization specification. In all examples shown and discussed here, any specific value should be interpreted as merely exemplary, rather than as a limitation. Therefore, other examples of the exemplary embodiments may have different values. It should be noted that similar numbers and letters represent similar items in the following drawings, so once an item is defined in one drawing, it does not need to be further discussed in subsequent drawings.

[0074] It should be noted that, in the present application, the terms "comprises", "includes" or any other variants thereof are intended to cover non-exclusive inclusion, so that a process, method, article or device including a series of elements includes not only those elements, but also includes other elements not explicitly listed, or also includes elements inherent to such process, method, article or device. It should also be pointed out that the scope of the methods and devices in the embodiments of the present application is not limited to performing functions in the order shown or discussed, and may also include performing functions in a substantially simultaneous manner or in reverse order according to the functions involved. For example, the described method may be performed in an order different from that described, and various steps may be added, omitted, or combined. In addition, the features described with reference to certain examples may be combined in other examples.

[0075] In addition, it should be noted that, unless otherwise clearly specified and limited, the words "connect" and "drive" used in the description of this application should be understood in a broad sense, which can be direct, through an intermediate medium, or the relationship between two elements. Those skilled in the art can understand their specific meanings in this application according to specific circumstances. In this article, "first" and "second" and other similar words are only used to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any actual relationship or order between these entities or operations.

[0076] The above embodiments are provided for persons familiar with the art to implement or use the present application. Personnel familiar with the art can make various modifications or changes to the above embodiments without departing from the application concept of the present application. Therefore, the protection scope of the present application is not limited to the above embodiments, but should be the maximum scope of the innovative features mentioned in the claims.

Claims

1. A radar-based automatic detection method for obstacles in front of a vehicle, characterized in that: The radar-based automatic detection method for obstacles in front of a vehicle includes: A first radar and a second radar are symmetrically arranged in front of the vehicle; Dividing the detection ranges of the first radar and the second radar into a first area, a second area, and a third area; The first area and the third area are provided with a first threshold, and the second area is provided with an overlapping threshold; The first radar and the second radar detect the front object through the first threshold and the superposition threshold, and output the detection results in each detection area; The first area is located on the left side of the first radar, the third area is located on the right side of the second radar, the second area is located between the first radar and the second radar, and the second area includes an electromagnetic wave detection range that can be reached by both the first radar and the second radar.

2. The method for automatically detecting obstacles in front of a vehicle based on radar according to claim 1, characterized in that: The first radar includes a first main lobe and a first side lobe, and the second radar includes a second main lobe and a second side lobe.

3. The method for automatically detecting obstacles ahead of a vehicle based on radar according to claim 2, characterized in that: The first radar and the second radar generate three kinds of amplitudes after being superimposed, including the amplitude generated by the superposition of the first main lobe and the first main lobe, the amplitude generated by the superposition of the first main lobe and the second side lobe, or the amplitude generated by the superposition of the second main lobe and the first side lobe, and the amplitude generated by the superposition of the first side lobe and the second side lobe.

4. The method for automatically detecting obstacles ahead of a vehicle based on radar according to claim 3, characterized in that: The amplitude generated by the superposition of the first main lobe and the second main lobe identifies the effective actual target object and is completely converted into an output signal; The amplitude generated by the superposition of the first main lobe and the second side lobe or the amplitude generated by the superposition of the second main lobe and the first side lobe identifies the effective actual target and is completely converted into an output signal; The amplitude generated by the superposition of the first side lobe and the second side lobe identifies invalid targets and provides false information. At this time, a superposition threshold is set for the amplitude generated by the superposition of the first side lobe and the second side lobe to perform information filtering.

5. The method for automatically detecting obstacles ahead of a vehicle based on radar according to claim 4, characterized in that: Setting a first threshold for the first area specifically includes: using a first sidelobe filtering algorithm for the first area, wherein the first sidelobe filtering algorithm filters invalid targets identified by the first sidelobe.

6. The method for automatically detecting obstacles ahead of a vehicle based on radar according to claim 5, characterized in that: The superposition threshold is set for the second area specifically including: the second area adopts a second sidelobe filtering algorithm, and the second sidelobe filtering algorithm filters out invalid targets identified by superposition of the first sidelobe and the second sidelobe.

7. The method for automatically detecting obstacles ahead of a vehicle based on radar according to claim 6, characterized in that: Setting the first threshold for the third area specifically includes: the third area adopts a first sidelobe filtering algorithm, and the first sidelobe filtering algorithm filters invalid targets identified by the second sidelobe.

8. The method for automatically detecting obstacles ahead of a vehicle based on radar according to claim 7, characterized in that: The first radar receives signals about the target object in the first area and the second area filtered by the first sidelobe filtering algorithm and the second sidelobe filtering algorithm; The second radar receives signals about the target object in the second area and the third area filtered by the first sidelobe filtering algorithm and the second sidelobe filtering algorithm.

9. The method for automatically detecting obstacles ahead of a vehicle based on radar according to claim 1, characterized in that: The first radar and the second radar have the same horizontal detection angle range, amplitude and period.

10. The method for automatically detecting obstacles ahead of a vehicle based on radar according to claim 1, characterized in that: When the vehicle is autonomously driving, after the first radar and the second radar receive valid signals from target objects, they transmit the signals from the target objects to the autonomous driving domain controller.

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