WO2022134510A1 - 一种车载bsd毫米波雷达低速下障碍物识别方法 - Google Patents

一种车载bsd毫米波雷达低速下障碍物识别方法 Download PDF

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WO2022134510A1
WO2022134510A1 PCT/CN2021/102232 CN2021102232W WO2022134510A1 WO 2022134510 A1 WO2022134510 A1 WO 2022134510A1 CN 2021102232 W CN2021102232 W CN 2021102232W WO 2022134510 A1 WO2022134510 A1 WO 2022134510A1
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target
vehicle
threshold
information
state
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PCT/CN2021/102232
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English (en)
French (fr)
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周琼峰
刘加欢
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南京市德赛西威汽车电子有限公司
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Priority to US18/269,296 priority Critical patent/US20240053468A1/en
Publication of WO2022134510A1 publication Critical patent/WO2022134510A1/zh

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    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01S—RADIO DIRECTION-FINDING; RADIO NAVIGATION; DETERMINING DISTANCE OR VELOCITY BY USE OF RADIO WAVES; LOCATING OR PRESENCE-DETECTING BY USE OF THE REFLECTION OR RERADIATION OF RADIO WAVES; ANALOGOUS ARRANGEMENTS USING OTHER WAVES
    • G01S13/00—Systems using the reflection or reradiation of radio waves, e.g. radar systems; Analogous systems using reflection or reradiation of waves whose nature or wavelength is irrelevant or unspecified
    • G01S13/88—Radar or analogous systems specially adapted for specific applications
    • G01S13/93—Radar or analogous systems specially adapted for specific applications for anti-collision purposes
    • G01S13/931—Radar or analogous systems specially adapted for specific applications for anti-collision purposes of land vehicles
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01S—RADIO DIRECTION-FINDING; RADIO NAVIGATION; DETERMINING DISTANCE OR VELOCITY BY USE OF RADIO WAVES; LOCATING OR PRESENCE-DETECTING BY USE OF THE REFLECTION OR RERADIATION OF RADIO WAVES; ANALOGOUS ARRANGEMENTS USING OTHER WAVES
    • G01S7/00—Details of systems according to groups G01S13/00, G01S15/00, G01S17/00
    • G01S7/02—Details of systems according to groups G01S13/00, G01S15/00, G01S17/00 of systems according to group G01S13/00
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01S—RADIO DIRECTION-FINDING; RADIO NAVIGATION; DETERMINING DISTANCE OR VELOCITY BY USE OF RADIO WAVES; LOCATING OR PRESENCE-DETECTING BY USE OF THE REFLECTION OR RERADIATION OF RADIO WAVES; ANALOGOUS ARRANGEMENTS USING OTHER WAVES
    • G01S7/00—Details of systems according to groups G01S13/00, G01S15/00, G01S17/00
    • G01S7/02—Details of systems according to groups G01S13/00, G01S15/00, G01S17/00 of systems according to group G01S13/00
    • G01S7/28—Details of pulse systems
    • G01S7/285—Receivers
    • G01S7/292—Extracting wanted echo-signals
    • G01S7/2923—Extracting wanted echo-signals based on data belonging to a number of consecutive radar periods
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01S—RADIO DIRECTION-FINDING; RADIO NAVIGATION; DETERMINING DISTANCE OR VELOCITY BY USE OF RADIO WAVES; LOCATING OR PRESENCE-DETECTING BY USE OF THE REFLECTION OR RERADIATION OF RADIO WAVES; ANALOGOUS ARRANGEMENTS USING OTHER WAVES
    • G01S7/00—Details of systems according to groups G01S13/00, G01S15/00, G01S17/00
    • G01S7/02—Details of systems according to groups G01S13/00, G01S15/00, G01S17/00 of systems according to group G01S13/00
    • G01S7/41—Details of systems according to groups G01S13/00, G01S15/00, G01S17/00 of systems according to group G01S13/00 using analysis of echo signal for target characterisation; Target signature; Target cross-section
    • G01S7/415—Identification of targets based on measurements of movement associated with the target
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01S—RADIO DIRECTION-FINDING; RADIO NAVIGATION; DETERMINING DISTANCE OR VELOCITY BY USE OF RADIO WAVES; LOCATING OR PRESENCE-DETECTING BY USE OF THE REFLECTION OR RERADIATION OF RADIO WAVES; ANALOGOUS ARRANGEMENTS USING OTHER WAVES
    • G01S13/00—Systems using the reflection or reradiation of radio waves, e.g. radar systems; Analogous systems using reflection or reradiation of waves whose nature or wavelength is irrelevant or unspecified
    • G01S13/88—Radar or analogous systems specially adapted for specific applications
    • G01S13/93—Radar or analogous systems specially adapted for specific applications for anti-collision purposes
    • G01S13/931—Radar or analogous systems specially adapted for specific applications for anti-collision purposes of land vehicles
    • G01S2013/9315—Monitoring blind spots

Definitions

  • the invention relates to the technical field of vehicle obstacle identification, in particular to a vehicle-mounted BSD millimeter-wave radar obstacle identification method at low speed.
  • the vehicle-mounted BSD millimeter-wave radar is mainly used to detect and remind the target in the blind spot behind the vehicle during normal driving, so as to avoid collision with the vehicle behind when the vehicle changes lanes. However, it does not play its role when the vehicle is driving at low speed. The role of detection.
  • the surrounding environment is relatively complex, and there are usually many obstacles around it.
  • the BSD radar is in the blind spot. Compared with other positions, the angle and velocity measurement errors of the detection point are relatively large, and it is difficult to judge the dynamic and static state of the target.
  • the recognition efficiency of different materials is different for the vehicle-mounted BSD millimeter-wave radar to identify stationary obstacles.
  • Some targets have very few reflection points, and The location is unstable and it is easy to miss identification; therefore, if the vehicle-mounted BSD millimeter-wave radar can help identify obstacles when the vehicle is driving at a low speed, it can assist the driver to travel safely and at the same time improve the efficiency of the radar.
  • the present invention provides a vehicle-mounted BSD millimeter-wave radar obstacle identification method at low speed.
  • the technical scheme of the present invention is as follows:
  • a vehicle-mounted BSD millimeter-wave radar method for identifying obstacles at low speeds comprising:
  • the vehicle-mounted BSD millimeter-wave radar detects the surrounding targets in real time, collects the target detection point information of the current frame and processes it, and obtains the target information list;
  • the identification of the motion and static states of the target detection points in the target information list specifically includes:
  • the state of the target is determined in combination with the vehicle state and the target distance information.
  • the target detection point information includes the position information of the target, the radial movement speed information of the target relative to the vehicle, and the azimuth angle information of the target relative to the vehicle;
  • the calculation of the absolute value of the target's ground radial velocity specifically includes: the sum of the cosine product of the vehicle speed and the azimuth angle of the target relative to the vehicle and the radial velocity of the target relative to the vehicle.
  • the divided intervals include a first threshold interval, a second threshold interval, a third threshold interval and a fourth threshold interval;
  • the settings of the first threshold interval, the second threshold interval, the third threshold interval and the fourth threshold interval are set according to the statistics of a large number of real vehicle test data
  • the first threshold interval is less than or equal to 0.1m/s
  • the second threshold interval is greater than 0.1m/s and less than or equal to 0.25m/s;
  • the third threshold interval is greater than 0.25m/s and less than or equal to 0.4m/s;
  • the fourth threshold interval is greater than 0.4m/s and less than or equal to 0.6m/s.
  • judging the state of the target according to the interval of the absolute value of the target's radial velocity over the ground in combination with the vehicle state and the target distance information specifically includes:
  • the target is judged to be a stationary target
  • the motion state of the vehicle is judged.
  • the target and the vehicle are in the first threshold range.
  • the target is determined to be a stationary target, and when the vehicle is in motion, the target is determined to be a stationary target;
  • the motion state of the vehicle is judged.
  • the target and the vehicle are in the first threshold range.
  • the target is judged to be a stationary target; when the vehicle is in a straight line, and the left and right distance between the target and the vehicle is within the first threshold range or the distance between the target and the vehicle is within the first threshold.
  • the target is judged to be a stationary target; when the vehicle is in a turning state, the target is judged to be a stationary target;
  • the motion state of the vehicle is judged.
  • the target and the vehicle are in the first threshold range.
  • the target is judged to be a stationary target; when the vehicle is in a straight-line driving state and the distance between the target and the vehicle is within the third threshold range, the target is judged to be a stationary target;
  • the vehicle is in a turning state and the distance between the target and the vehicle is within the fourth threshold range, it is determined that the target is a stationary target.
  • the judgment of the straight-line driving state and the turning state of the vehicle includes:
  • the absolute value of the yaw angular velocity of the vehicle is compared with the fifth threshold.
  • the absolute value of the yaw angular velocity of the vehicle is less than or equal to the fifth threshold, it is determined that the vehicle is in a straight driving state, otherwise, it is determined that the vehicle is in a turning state.
  • the settings of the first threshold, the second threshold, the third threshold, the fourth threshold and the fifth threshold are statistically set according to a large number of real vehicle test data
  • the first threshold setting range is: 0.8m-1.2m
  • the second threshold setting range is: 2.5m-3.5m;
  • the third threshold setting range is: 4.5m-5.5m
  • the fourth threshold setting range is: 25m-35m;
  • the fifth threshold setting range is: 4°/s-6°/s.
  • clustering the target detection points in the stationary target list specifically includes:
  • the clustered target list After traversing the stationary target list, the clustered target list is obtained, that is, the identified obstacle information is obtained.
  • the identified obstacle information includes the number of targets, the range of the position of the target, the position of the cluster center target, and the average speed of the target relative to the vehicle.
  • calculating the collision risk between the vehicle and the obstacle includes: calculating the collision time between the vehicle and the target according to the position of the target and the average speed of the target relative to the vehicle, that is, to obtain the collision time between the vehicle and the obstacle. collision risk between objects.
  • the obstacle identification method of the invention is simple and easy to operate, can quickly and accurately judge the dynamic and static state of the target, has strong applicability and high recognition rate, increases the application scenarios of the BSD radar, reduces the collision risk in the blind area of the vehicle, and improves the speed of the vehicle. driving safety.
  • Fig. 1 is the flow chart of the steps of the present invention.
  • FIG. 2 is a schematic diagram of the distribution of obstacles around the vehicle of the present invention.
  • first and second are only used for descriptive purposes, and are mainly used to distinguish different devices, elements or components (the specific types and structures may be the same or different), and are not used for Indicate or imply the relative importance and quantity of the indicated devices, elements or components, but should not be construed as indicating or implying relative importance.
  • This embodiment discloses a vehicle-mounted BSD millimeter-wave radar method for identifying obstacles at low speeds, as shown in FIG. 1 , including:
  • the vehicle-mounted BSD millimeter-wave radar detects surrounding targets in real time, collects the target detection point information of the current frame and processes it to obtain a target information list.
  • This step specifically includes:
  • the vehicle-mounted BSD millimeter-wave radar detects the surrounding targets in real time, processes the detected data information to obtain the target detection point information of the current frame, and collects the target detection point information of multiple frames to obtain the target information list.
  • the target detection point information includes the position information of the target, the radial movement speed information of the target relative to the vehicle, and the azimuth angle information of the target relative to the vehicle;
  • the target information list includes the position information of the target, the radial velocity information of the target relative to the vehicle, and the azimuth angle information of the target relative to the vehicle.
  • the motion and static state recognition of the target detection points in the target information list specifically includes:
  • the calculation of the absolute value of the target's ground radial velocity specifically includes: the sum of the cosine product of the vehicle speed and the azimuth angle of the target relative to the vehicle and the radial velocity of the target relative to the vehicle.
  • abSpeed represents the absolute value of the target's radial velocity to the ground
  • rSpeed represents the radial velocity of the target relative to the vehicle
  • Speed represents the speed of the vehicle
  • angle represents the azimuth angle of the target relative to the vehicle.
  • S22 Divide the dynamic and static state judgment threshold into intervals according to the size of the dynamic and static state judgment threshold.
  • the interval divided by the dynamic and static state judgment threshold includes a first threshold interval, a second threshold interval, a third threshold interval and a fourth threshold interval;
  • the settings of the first threshold interval, the second threshold interval, the third threshold interval and the fourth threshold interval are set according to the statistics of a large number of real vehicle test data
  • the first threshold interval is less than or equal to 0.1 m/s
  • the second threshold interval is greater than 0.1m/s and less than or equal to 0.25m/s;
  • the third threshold interval is greater than 0.25m/s and less than or equal to 0.4m/s;
  • the fourth threshold interval is greater than 0.4m/s and less than or equal to 0.6m/s.
  • S23 Compare the absolute value of the target's radial velocity over the ground with the dynamic and static state judgment threshold, and determine the interval in which the absolute value of the target's radial velocity over the ground is located.
  • S24 Determine the state of the target according to the interval in which the absolute value of the radial velocity of the target is located in combination with the state of the vehicle and the target distance information.
  • This step specifically includes:
  • the target is judged to be a stationary target
  • the motion state of the vehicle is further judged.
  • the target When the distance between the front and rear of the vehicle is within the second threshold range, the target is determined to be a stationary target, and when the vehicle is in motion, the target is determined to be a stationary target;
  • the target is judged as a stationary target. It is a stationary target; if the vehicle is in a turning state, it is judged that the target is a stationary target;
  • the target is determined to be stationary; if the vehicle is in a turning state, and the target When the distance to and from the vehicle is within the fourth threshold range, the target is determined to be a stationary target.
  • the left and right distance between the target and the vehicle specifically refers to the left and right distance between the target and the BSD radar installation location of the vehicle
  • the front and rear distance between the target and the vehicle specifically refers to the front and rear distance between the target and the BSD radar installation location of the vehicle.
  • the judgment of the vehicle's straight-line driving state and turning state includes:
  • the settings of the first threshold, the second threshold, the third threshold, the fourth threshold and the fifth threshold are statistically set according to a large number of real vehicle test data
  • the first threshold setting range is: 0.8m-1.2m
  • the second threshold setting range is: 2.5m-3.5m;
  • the third threshold setting range is: 4.5m-5.5m
  • the fourth threshold setting range is: 25m-35m;
  • the fifth threshold setting range is: 4°/s-6°/s.
  • the first threshold is set to 1.0m
  • the second threshold is set as: 3m;
  • the third threshold is set to: 5m;
  • the fourth threshold is set to: 30m;
  • the fifth threshold is set to: 5°/s.
  • this step can also be expressed in the following manner:
  • the target is judged to be a stationary target
  • the motion state of the vehicle is judged.
  • the vehicle is in a stationary state, and the left and right distance between the target and the BSD radar installation position of the vehicle is 1m
  • the target is judged to be a stationary target, and when the vehicle is in motion, the target is judged to be a stationary target;
  • the motion state of the vehicle is judged.
  • the vehicle is in a stationary state, and the left and right distance between the target and the BSD radar installation position of the vehicle is 1m
  • the target is judged to be a stationary target.
  • the vehicle is in motion, it is judged that the vehicle is driving in a straight line according to the absolute value of the yaw angular velocity of the vehicle. The state is still in the turning state.
  • the target is judged to be a stationary target; when the vehicle is in a turning state, the target is judged to be a stationary target;
  • the motion state of the vehicle is judged.
  • the vehicle is in a stationary state, and the left and right distance between the target and the BSD radar installation position of the vehicle is 1m
  • the target is judged to be a stationary target.
  • the vehicle is in motion, it is judged that the vehicle is driving in a straight line according to the absolute value of the yaw angular velocity of the vehicle. The state is still in the turning state.
  • the target When the vehicle is in a straight driving state, and the front and rear distance between the target and the BSD radar installation position of the vehicle is within 5m, the target is judged to be a stationary target; when the vehicle is in a turning state, and the target When the distance between the front and rear of the vehicle's BSD radar installation position is within 30m, the target is judged to be a stationary target;
  • the straight-line driving state and turning state of the vehicle can also be expressed in the following ways:
  • This step specifically includes:
  • the specific calculation of this step includes:
  • r represents the position information of the target, that is, the distance between the target and the installation position of the BSD radar of the vehicle, and angle represents the azimuth angle of the target relative to the vehicle.
  • x_a, x_b represent the horizontal coordinates of two adjacent targets a and b
  • y_a, y_b represent the vertical coordinates of two adjacent targets a and b
  • deltX, deltY represent the absolute value of the horizontal coordinate difference between two adjacent targets a and b and the absolute value of the longitudinal coordinate difference
  • the setting range of the sixth threshold is 0.8-1.2m, and preferably, the setting range of the sixth threshold is 1m.
  • the identified obstacle information includes the number of clustered targets, the range of the position of the target, the position of the target in the cluster center, and the average speed of the target relative to the vehicle.
  • BSD radars are installed on the left and right sides of the rear of the vehicle to detect surrounding obstacles and obtain the target points indicated by the black + sign.
  • the dotted box indicates the result of clustering, that is, the target points in the dotted box belong to the same target , that is, the same obstacle; the length and width of the dotted box are the size of the obstacle after identification.
  • This step includes:
  • the collision time between the vehicle and the obstacle is calculated by the following formula, that is, the collision risk:
  • TTC time to collision, which is the time to collision
  • average(r) is the average distance measured by the target point for obstacle identification
  • average(rSpeed) is the average speed of the point measurement, that is, the average speed of the target relative to the vehicle.

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Abstract

一种车载BSD毫米波雷达低速下障碍物识别方法，包括：车载BSD毫米波雷达实时检测周围目标，收集当前帧的目标检测点信息并对其进行处理，得到目标信息列表；对目标信息列表中的目标检测点进行运动和静止状态识别，并对多帧静止状态下的目标检测点信息进行收集，得到静止目标列表；对静止目标列表中的目标检测点进行聚类，得到识别的障碍物信息；根据障碍物信息，计算本车与障碍物之间的碰撞风险。障碍物识别方法简单易操作，可快速准确的判断目标的动静状态，且适用性强，识别率高，增加了BSD雷达的应用场景，同时降低了车辆盲区的碰撞风险，提高了车辆行驶安全性。

Description

一种车载BSD毫米波雷达低速下障碍物识别方法 技术领域
本发明涉及车辆障碍物识别技术领域，特别是涉及一种车载BSD毫米波雷达低速下障碍物识别方法。
背景技术
目前，车载BSD毫米波雷达主要应用在正常行车过程中对车辆侧后方盲区内的目标进行检测和提醒，避免本车变道时与后方车辆碰撞，然而，其在车辆低速行驶时并没有发挥其检测的作用。
车辆在低速行驶时，一般周围环境相对复杂，通常出现在其周身的障碍物较多，对驾驶水平一般的驾驶员而言，通行相对困难，容易与障碍物碰撞，同时，BSD雷达在盲区内的检测点角度、速度测量误差相对其他位置较大，不易判断目标的动静状态，而且，车载BSD毫米波雷达对静止障碍物的识别，不同材质识别效率不同，有些目标的反射点很少，且位置不稳定，容易漏识别；所以，车载BSD毫米波雷达如果在车辆低速行驶时能够帮助识别障碍物，可以辅助驾驶员安全同行的同时，还提高了雷达的使用效率。
发明内容
本发明为克服上述现有技术中，车辆在低速行驶状态下，车载BSD毫米波雷达对盲区内的障碍物的识别不精准的问题，提供一种车载BSD毫米波雷达低速下障碍物识别方法。
为解决上述技术问题，本发明的技术方案如下：
一种车载BSD毫米波雷达低速下障碍物识别方法，包括：
车载BSD毫米波雷达实时检测周围目标，收集当前帧的目标检测点信息并对其进行处理，得到目标信息列表；
对目标信息列表中的目标检测点进行运动和静止状态识别，并对多帧静止状态下的目标检测点信息进行收集，得到静止目标列表；
对静止目标列表中的目标检测点进行聚类，得到识别的障碍物信息；
根据障碍物信息，计算本车与障碍物之间的碰撞风险。
进一步的，作为优选技术方案，对目标信息列表中的目标检测点进行运动和静止状态识别具体包括：
根据本车的运动速度结合目标检测点信息计算目标的对地径向速度的绝对值；
根据动静状态判断阈值大小对动静状态判断阈值进行区间划分；
将目标的对地径向速度的绝对值与动静状态判断阈值进行比较，判断目标的对地径向速度的绝对值所处区间；
根据目标的对地径向速度的绝对值所处区间结合本车状态和目标距离信息判断目标所处状态。
进一步的，作为优选技术方案，目标检测点信息包括目标的位置信息、目标相对本车的径向运动速度信息和目标相对本车的方位角度信息；
目标的对地径向速度的绝对值的计算具体包括：车速与目标相对本车的方位角度的余弦乘积和目标相对本车的径向运动速度之和。
进一步的，作为优选技术方案，所划分的区间包括第一阈值区间、第二阈值区间、第三阈值区间和第四阈值区间；
其中：第一阈值区间、第二阈值区间、第三阈值区间和第四阈值区间的设置根据大量实车测试数据统计设置；
第一阈值区间为小于等于0.1m/s；
第二阈值区间为大于0.1m/s，小于等于0.25m/s；
第三阈值区间为大于0.25m/s，小于等于0.4m/s；
第四阈值区间为大于0.4m/s，小于等于0.6m/s。
进一步的，作为优选技术方案，根据目标的对地径向速度的绝对值所处区间结合本车状态和目标距离信息判断目标所处状态具体包括：
当目标的对地径向速度的绝对值处于第一阈值区间内时，则判断目标为静止目标；
当目标的对地径向速度的绝对值处于第二阈值区间内时，判断本车的运动状态，当本车处于静止状态时，且目标与本车左右距离在第一阈值范围内，目标与本车前后距离在第二阈值范围内时，则判断目标为静止目标，当本车处于运动状态时，则判断目标为静止目标；
当目标的对地径向速度的绝对值处于第三阈值区间内时，判断本车的运动状态，当本车处于静止状态时，且目标与本车左右距离在第一阈值范围内，目标与 本车前后距离在第二阈值范围内时，则判断目标为静止目标；当本车处于直线行驶状态时，且目标与本车左右距离在第一阈值范围内或者目标与本车前后距离在第三阈值范围内时，则判断目标为静止目标；当本车处于转弯状态时，则判断目标为静止目标；
当目标的对地径向速度的绝对值处于第四阈值区间内时，判断本车的运动状态，当本车处于静止状态时，且目标与本车左右距离在第一阈值范围内，目标与本车前后距离在第二阈值范围内时，则判断目标为静止目标；当本车处于直线行驶状态时，且目标与本车前后距离在第三阈值范围内时，则判断目标为静止目标；当本车处于转弯状态时，且目标与本车前后距离在第四阈值范围内时，则判断目标为静止目标。
进一步的，作为优选技术方案，本车直线行驶状态和转弯状态的判断包括：
将本车偏航角速度的绝对值与第五阈值进行比较，当本车偏航角速度的绝对值小于等于第五阈值时，则判断本车处于直线行驶状态，否则，判断本车处于转弯状态。
进一步的，作为优选技术方案，第一阈值、第二阈值、第三阈值、第四阈值和第五阈值的设置根据大量实车测试数据统计设置；
第一阈值设置范围为：0.8m-1.2m；
第二阈值设置范围为：2.5m-3.5m；
第三阈值设置范围为：4.5m-5.5m；
第四阈值设置范围为：25m-35m；
第五阈值设置范围为：4°/s-6°/s。
进一步的，作为优选技术方案，对静止目标列表中的目标检测点进行聚类具体包括：
对静止目标列表中的相邻两目标的位置信息进行最差运算，当相邻两目标的位置差值的绝对值在第六阈值范围内时，则判断相邻两目标为同一目标，否则，判断相邻两目标为两个目标；
遍历完静止目标列表后得到聚类后的目标列表，即得到识别的障碍物信息。
进一步的，作为优选技术方案，识别的障碍物信息包括目标的数量、目标的位置分部范围、聚类中心目标的位置、目标相对本车的平均速度。
进一步的，作为优选技术方案，计算本车与障碍物之间的碰撞风险包括：根据目标的位置和目标相对本车的平均速度计算本车与目标之间的碰撞时间，即得到本车与障碍物之间的碰撞风险。
与现有技术相比，本发明技术方案的有益效果是：
本发明的障碍物识别方法简单易操作，可快速准确的判断目标的动静状态，且适用性强，识别率高，增加了BSD雷达的应用场景，同时降低了车辆盲区的碰撞风险，提高了车辆行驶安全性。
附图说明
图1为本发明步骤流程图。
图2为本发明本车周围障碍物分布示意图。
附图仅用于示例性说明，不能理解为对本专利的限制；为了更好说明本实施例，附图某些部件会有省略、放大或缩小，并不代表实际产品的尺寸；对于本领域技术人员来说，附图中某些公知结构及其说明可能省略是可以理解的；相同或相似的标号对应相同或相似的部件；附图中描述位置关系的用语仅用于示例性说明，不能理解为对本专利的限制。
具体实施方式
下面结合附图对本发明的较佳实施例进行详细阐述，以使本发明的优点和特征更易被本领域技术人员理解，从而对本发明的保护范围作出更为清楚的界定。。
本发明实施例的附图中相同或相似的标号对应相同或相似的部件；在本实用新型的描述中，需要理解的是，若有术语“上”、“下”、“左”、“右”、“顶”、“底”、“内”、“外”等指示的方位或位置关系为基于附图所示的方位或位置关系，仅是为了便于描述本实用新型和简化描述，而不是指示或暗示所指的装置或元件必须具有特定的方位、以特定的方位构造和操作，因此附图中描述位置关系的用语仅用于示例性说明，不能理解为对本专利的限制。
此外，若有“第一”、“第二”等术语仅用于描述目的，主要是用于区分不同的装置、元件或组成部分(具体的种类和构造可能相同也可能不同)，并非用于表明或暗示所指示装置、元件或组成部分的相对重要性和数量，而不能理解为指示或者暗示相对重要性。
实施例1
本实施例公开一种车载BSD毫米波雷达低速下障碍物识别方法，如图1所示， 包括：
S1、车载BSD毫米波雷达实时检测周围目标，收集当前帧的目标检测点信息并对其进行处理，得到目标信息列表。
本步骤具体包括：
车载BSD毫米波雷达实时检测周围目标，将检测到的数据信息经过信号处理后得到当前帧的目标检测点信息，收集多帧目标检测点信息得到目标信息列表。
在本实施例中，目标检测点信息包括目标的位置信息、目标相对本车的径向运动速度信息和目标相对本车的方位角度信息；
目标信息列表包括目标的位置信息、目标相对本车的径向运动速度信息和目标相对本车的方位角度信息。
S2、对目标信息列表中的目标检测点进行运动和静止状态识别，并对多帧静止状态下的目标检测点信息进行收集，得到静止目标列表。
本步骤中对目标信息列表中的目标检测点进行运动和静止状态识别具体包括：
S21、根据本车的运动速度结合目标检测点信息计算目标的对地径向速度的绝对值。
本步骤中，目标的对地径向速度的绝对值的计算具体包括：车速与目标相对本车的方位角度的余弦乘积和目标相对本车的径向运动速度之和。
该目标的对地径向速度的绝对值通过以下公式计算：
abSpeed＝rSpeed+Speed*cos(angle)
其中，abSpeed表示目标的对地径向速度的绝对值，rSpeed表示目标相对本车的径向运动速度，Speed表示本车的车速，angle表示目标相对本车的方位角度。
S22、根据动静状态判断阈值大小对动静状态判断阈值进行区间划分。
本步骤中，对动静状态判断阈值所划分的区间包括第一阈值区间、第二阈值区间、第三阈值区间和第四阈值区间；
其中：第一阈值区间、第二阈值区间、第三阈值区间和第四阈值区间的设置根据大量实车测试数据统计设置；
在本实施例中，第一阈值区间为小于等于0.1m/s；
第二阈值区间为大于0.1m/s，小于等于0.25m/s；
第三阈值区间为大于0.25m/s，小于等于0.4m/s；
第四阈值区间为大于0.4m/s，小于等于0.6m/s。
S23、将目标的对地径向速度的绝对值与动静状态判断阈值进行比较，判断目标的对地径向速度的绝对值所处区间。
S24、根据目标的对地径向速度的绝对值所处区间结合本车状态和目标距离信息判断目标所处状态。
本步骤具体包括：
当目标的对地径向速度的绝对值处于第一阈值区间内时，则判断目标为静止目标；
当目标的对地径向速度的绝对值处于第二阈值区间内时，进一步判断本车的运动状态，当本车处于静止状态时，且目标与本车左右距离在第一阈值范围内，目标与本车前后距离在第二阈值范围内时，则判断目标为静止目标，当本车处于运动状态时，则判断目标为静止目标；
当目标的对地径向速度的绝对值处于第三阈值区间内时，若本车处于静止状态，且目标与本车左右距离在第一阈值范围内，目标与本车前后距离在第二阈值范围内时，则判断目标为静止目标；若本车处于直线行驶状态，且目标与本车左右距离在第一阈值范围内或者目标与本车前后距离在第三阈值范围内时，则判断目标为静止目标；若本车处于转弯状态，则判断目标为静止目标；
当目标的对地径向速度的绝对值处于第四阈值区间内时，若本车处于静止状态，且目标与本车左右距离在第一阈值范围内，目标与本车前后距离在第二阈值范围内时，则判断目标为静止目标；若本车处于直线行驶状态，且目标与本车前后距离在第三阈值范围内时，则判断目标为静止目标；若本车处于转弯状态，且目标与本车前后距离在第四阈值范围内时，则判断目标为静止目标。
在本步骤中：目标与本车左右距离具体指目标与本车BSD雷达安装位置之间的左右距离，目标与本车前后距离具体指目标与本车BSD雷达安装位置之间的前后距离。
本车直线行驶状态和转弯状态的判断包括：
将本车偏航角速度的绝对值与第五阈值进行比较，当本车偏航角速度的绝对 值小于等于第五阈值时，则判断本车处于直线行驶状态，否则，判断本车处于转弯状态。
在本步骤中，第一阈值、第二阈值、第三阈值、第四阈值和第五阈值的设置根据大量实车测试数据统计设置；
第一阈值设置范围为：0.8m-1.2m；
第二阈值设置范围为：2.5m-3.5m；
第三阈值设置范围为：4.5m-5.5m；
第四阈值设置范围为：25m-35m；
第五阈值设置范围为：4°/s-6°/s。
优选的，第一阈值设置为1.0m；
第二阈值设置为：3m；
第三阈值设置为：5m；
第四阈值设置为：30m；
第五阈值设置为：5°/s。
本步骤在另一实施例中，也可通过以下方式表述：
当abSpeed的绝对值小于等于0.1m/s时，则判断目标为静止目标；
当abSpeed的绝对值大于0.1m/s，小于等于0.25m/s时，判断本车的运动状态，当本车处于静止状态时，且目标与本车BSD雷达安装位置之间的左右距离在1m内，目标与本车BSD雷达安装位置之间的前后距离在3m内时，则判断目标为静止目标，当本车处于运动状态时，则判断目标为静止目标；
当abSpeed的绝对值大于0.25m/s，小于等于0.4m/s时，判断本车的运动状态，当本车处于静止状态时，且目标与本车BSD雷达安装位置之间的左右距离在1m内，目标与本车BSD雷达安装位置之间的前后距离在3m内时，则判断目标为静止目标，当本车处于运动状态时，根据本车偏航角速度的绝对值判断本车处于直线行驶状态还是转弯状态，当本车处于直线行驶状态时，且目标与本车BSD雷达安装位置之间的左右距离在1m内或者目标与本车BSD雷达安装位置之间的前后距离在5m内时，则判断目标为静止目标；当本车处于转弯状态时，则判断目标为静止目标；
当abSpeed的绝对值大于0.4m/s，小于等于0.6m/s时，判断本车的运动 状态，当本车处于静止状态时，且目标与本车BSD雷达安装位置之间的左右距离在1m内，目标与本车BSD雷达安装位置之间的前后距离在3m内时，则判断目标为静止目标，当本车处于运动状态时，根据本车偏航角速度的绝对值判断本车处于直线行驶状态还是转弯状态，当本车处于直线行驶状态时，且目标与本车BSD雷达安装位置之间的前后距离在5m内时，则判断目标为静止目标；当本车处于转弯状态时，且目标与本车BSD雷达安装位置之间的前后距离在30m内时，则判断目标为静止目标；
本车直线行驶状态和转弯状态也可通过以下方式表述：
将本车偏航角速度的绝对值与第五阈值进行比较，当本车偏航角速度的绝对值小于等于第五阈值时，则判断本车处于直线行驶状态，否则，判断本车处于转弯状态。
当YawRate的绝对值小于等于5°/s内，则判断本车处于直线行驶状态，否则，判断本车处于转弯状态。
S3、对静止目标列表中的目标检测点进行聚类，得到识别的障碍物信息。
本步骤具体包括：
对静止目标列表中的相邻两目标的位置信息进行最差运算，当相邻两目标的位置差值的绝对值在第六阈值范围内时，则判断相邻两目标为同一目标，否则，判断相邻两目标为两个目标；
本步骤的具体计算包括：
根据目标列表信息计算目标的坐标信息，即目标在本车坐标系下的投影x，y。
其根据目标列表中的目标的位置信息和目标相对本车的方位角度信息转换得到；
具体为：x＝r*sin(angle)，y＝r*cos(angle)；
其中，r表示目标的位置信息，即目标距离本车BSD雷达安装位置之间的距离，angle表示目标相对本车的方位角度。
对相邻两目标的坐标做差取绝对值；
具体为：deltX＝|x_a-x_b|，deltY＝|y_a-y_b|
其中，x_a，x_b表示相邻两目标a和b的横向坐标，y_a，y_b表示相邻两目标a和b的纵向坐标，deltX，deltY表示相邻两目标a和b的横向坐标差的 绝对值和纵向坐标差的绝对值；
将相邻两目标a和b的横向坐标差的绝对值和纵向坐标差的绝对值分别与第六阈值进行比较，当相邻两目标a和b的横向坐标差的绝对值和纵向坐标差的绝对值均小于等于第六阈值时，则判断相邻两目标为同一目标。
在本步骤中，第六阈值的设置范围为0.8-1.2m，优选的，第六阈值的设置范围为1m。
采用上述方法，识别完静止目标列表中的所有目标，以完成静止目标列表的聚类，从而得到识别的障碍物信息，这个过程即障碍物的识别过程。
在本步骤中，识别到的障碍物信息包括聚类的目标的数量、目标的位置分部范围、聚类中心目标的位置、目标相对本车的平均速度。
如图2所示，在车尾左右两侧各安装了BSD雷达，检测周围障碍物，得到黑色+号表示的目标点，虚线框表示聚类的结果，即虚线框内的目标点属于同一目标，即同一障碍物；虚线框的长宽为障碍物识别后的大小。
S4、根据障碍物信息，计算本车与障碍物之间的碰撞风险。
本步骤包括：
根据障碍物相对于本车的平均速度和障碍物的位置，通过以下公式计算本车与障碍物之间的碰撞时间，即碰撞风险：
TTC＝average(r)/average(rSpeed)
其中：TTC即time to collision表示碰撞时间，average(r)表示障碍物识别的目标点测量距离平均值，average(rSpeed)表示点测量的速度平均值，即目标相对本车的平均速度。
显然，本发明的上述实施例仅仅是为清楚地说明本发明所作的举例，而并非是对本发明的实施方式的限定。对于所属领域的普通技术人员来说，在上述说明的基础上还可以做出其它不同形式的变化或变动。这里无需也无法对所有的实施方式予以穷举。凡在本发明的精神和原则之内所作的任何修改、等同替换和改进等，均应包含在本发明权利要求的保护范围之内。

Claims (10)

  1. 一种车载BSD毫米波雷达低速下障碍物识别方法，其特征在于，包括：
    车载BSD毫米波雷达实时检测周围目标，收集当前帧的目标检测点信息并对其进行处理，得到目标信息列表；
    对目标信息列表中的目标检测点进行运动和静止状态识别，并对多帧静止状态下的目标检测点信息进行收集，得到静止目标列表；
    对静止目标列表中的目标检测点进行聚类，得到识别的障碍物信息；
    根据障碍物信息，计算本车与障碍物之间的碰撞风险。
  2. 根据权利要求1所述的一种车载BSD毫米波雷达低速下障碍物识别方法，其特征在于，对目标信息列表中的目标检测点进行运动和静止状态识别具体包括：
    根据本车的运动速度结合目标检测点信息计算目标的对地径向速度的绝对值；
    根据动静状态判断阈值大小对动静状态判断阈值进行区间划分；
    将目标的对地径向速度的绝对值与动静状态判断阈值进行比较，判断目标的对地径向速度的绝对值所处区间；
    根据目标的对地径向速度的绝对值所处区间结合本车状态和目标距离信息判断目标所处状态。
  3. 根据权利要求2所述的一种车载BSD毫米波雷达低速下障碍物识别方法，其特征在于，目标检测点信息包括目标的位置信息、目标相对本车的径向运动速度信息和目标相对本车的方位角度信息；
    目标的对地径向速度的绝对值的计算具体包括：车速与目标相对本车的方位角度的余弦乘积和目标相对本车的径向运动速度之和。
  4. 根据权利要求2所述的一种车载BSD毫米波雷达低速下障碍物识别方法，其特征在于，所划分的区间包括第一阈值区间、第二阈值区间、第三阈值区间和第四阈值区间；
    其中：第一阈值区间、第二阈值区间、第三阈值区间和第四阈值区间的设置根据大量实车测试数据统计设置；
    第一阈值区间为小于等于0.1m/s；
    第二阈值区间为大于0.1m/s，小于等于0.25m/s；
    第三阈值区间为大于0.25m/s，小于等于0.4m/s；
    第四阈值区间为大于0.4m/s，小于等于0.6m/s。
  5. 根据权利要求4所述的一种车载BSD毫米波雷达低速下障碍物识别方法，其特征在于，根据目标的对地径向速度的绝对值所处区间结合本车状态和目标距离信息判断目标所处状态具体包括：
    当目标的对地径向速度的绝对值处于第一阈值区间内时，则判断目标为静止目标；
    当目标的对地径向速度的绝对值处于第二阈值区间内时，判断本车的运动状态，当本车处于静止状态时，且目标与本车左右距离在第一阈值范围内，目标与本车前后距离在第二阈值范围内时，则判断目标为静止目标，当本车处于运动状态时，则判断目标为静止目标；
    当目标的对地径向速度的绝对值处于第三阈值区间内时，判断本车的运动状态，当本车处于静止状态时，且目标与本车左右距离在第一阈值范围内，目标与本车前后距离在第二阈值范围内时，则判断目标为静止目标；当本车处于直线行驶状态时，且目标与本车左右距离在第一阈值范围内或者目标与本车前后距离在第三阈值范围内时，则判断目标为静止目标；当本车处于转弯状态时，则判断目标为静止目标；
    当目标的对地径向速度的绝对值处于第四阈值区间内时，判断本车的运动状态，当本车处于静止状态时，且目标与本车左右距离在第一阈值范围内，目标与本车前后距离在第二阈值范围内时，则判断目标为静止目标；当本车处于直线行驶状态时，且目标与本车前后距离在第三阈值范围内时，则判断目标为静止目标；当本车处于转弯状态时，且目标与本车前后距离在第四阈值范围内时，则判断目标为静止目标。
  6. 根据权利要求5所述的一种车载BSD毫米波雷达低速下障碍物识别方法，其特征在于，本车直线行驶状态和转弯状态的判断包括：
    将本车偏航角速度的绝对值与第五阈值进行比较，当本车偏航角速度的绝对值小于等于第五阈值时，则判断本车处于直线行驶状态，否则，判断本车处于转弯状态。
  7. 根据权利要求6所述的一种车载BSD毫米波雷达低速下障碍物识别方法，其特征在于，第一阈值、第二阈值、第三阈值、第四阈值和第五阈值的设置根据大量实车测试数据统计设置；
    第一阈值设置范围为：0.8m-1.2m；
    第二阈值设置范围为：2.5m-3.5m；
    第三阈值设置范围为：4.5m-5.5m；
    第四阈值设置范围为：25m-35m；
    第五阈值设置范围为：4°/s-6°/s。
  8. 根据权利要求1所述的一种车载BSD毫米波雷达低速下障碍物识别方法，其特征在于，对静止目标列表中的目标检测点进行聚类具体包括：
    对静止目标列表中的相邻两目标的位置信息进行最差运算，当相邻两目标的位置差值的绝对值在第六阈值范围内时，则判断相邻两目标为同一目标，否则，判断相邻两目标为两个目标；
    遍历完静止目标列表后得到聚类后的目标列表，即得到识别的障碍物信息。
  9. 根据权利要求8所述的一种车载BSD毫米波雷达低速下障碍物识别方法，其特征在于，识别的障碍物信息包括目标的数量、目标的位置分部范围、聚类中心目标的位置、目标相对本车的平均速度。
  10. 根据权利要求9所述的一种车载BSD毫米波雷达低速下障碍物识别方法，其特征在于，计算本车与障碍物之间的碰撞风险包括：根据目标的位置和目标相对本车的平均速度计算本车与目标之间的碰撞时间，即得到本车与障碍物之间的碰撞风险。
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