CN111123253B - Vehicle identification method, system and medium based on adaptive threshold target clustering - Google Patents
Vehicle identification method, system and medium based on adaptive threshold target clustering Download PDFInfo
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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
- G01S13/02—Systems using reflection of radio waves, e.g. primary radar systems; Analogous systems
- G01S13/06—Systems determining position data of a target
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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
- G01S13/02—Systems using reflection of radio waves, e.g. primary radar systems; Analogous systems
- G01S13/50—Systems of measurement based on relative movement of target
- G01S13/58—Velocity or trajectory determination systems; Sense-of-movement determination systems
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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
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
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Abstract
The invention discloses a vehicle identification method, a system and a storage medium based on adaptive threshold target clustering, which belong to the technical field of radar and are used for solving the problem of charge leakage caused by vehicle following of ETC at present, and the adopted technical scheme is as follows: processing each radar echo signal to obtain the information of the ith echo, including the distance RiVelocity viAnd angle thetai，i∈[1,N](ii) a Obtaining a horizontal direction speed error delta v according to the radar speed resolution delta v, the radar angle resolution delta theta and the information of the ith echoxIt is taken as a speed threshold deltav(ii) a For satisfying | vi‑vj|≤δv i,j∈[1,N]Average the velocity of all echoes to obtain an average velocity
By mean velocity
Obtaining a distance threshold deltaRFor satisfying | Ri‑Rj|≤δR i,j∈[1,N]Clustering all the points, and taking the clustered information as the motion characteristic of the target; to pairThe remaining points are clustered to effectively distinguish different targets. The method, the system and the medium have the advantages of good clustering effect, radar detection precision improvement and the like.
Description
Technical Field
The invention mainly relates to the technical field of ETC, in particular to a vehicle identification method based on adaptive threshold target clustering.
Background
The millimeter wave radar is a radar which works in a millimeter wave band for detection, and generally, the millimeter wave refers to a radar with a frequency of 30 to 300GHz (with a wavelength of 1 to 10 mm). The radar transmits millimeter waves to the surrounding space, the millimeter waves encounter an object and are reflected back to the radar, and the radar can obtain information such as the distance, the speed, the angle and the like of the object through a series of processing. Because the same object generally has a plurality of reflected echoes, the reflected echoes need to be clustered, and only one reflected echo of one object is clustered as much as possible.
The common millimeter wave radar target clustering method considers that the same object has little difference in space and speed information, and a distance threshold delta is setRAngle threshold deltaθAnd a speed threshold deltavAnd calculating the difference values of the distance, the angle and the speed of different echoes, if the difference values are smaller than corresponding thresholds, regarding the echoes to belong to the same object, clustering the echoes, and taking the statistical average of the distance, the angle and the speed of the echoes as the information of the object.
The existing radar target clustering technology adopts a fixed threshold to cluster targets, and cannot change according to target motion characteristics, because objects are in different motion states and different positions, clustering effects under different environments are greatly different, so that target detection effects are unstable and cannot reach the optimum, one object can be clustered into two objects when the threshold is set too small, and two objects can be clustered into one object when the threshold is set too large; therefore, the traditional millimeter wave radar clustering method adopts a method for setting a fixed threshold, so that the clustering effect of the targets at a distance cannot be considered, when the distance threshold is set to be small, the targets at the distance can be split, when the distance threshold is set to be large, the targets at the near distance can not be distinguished, and the radar measurement error is not considered by the fixed threshold, so that the optimal threshold can be found by a large amount of experiments for different radars.
Secondly, influence brought by measurement errors is not considered, clustering errors are easily caused, and different targets are clustered into one target. When vehicles are charged at an ETC toll station, the problem of charge leakage caused by vehicle following can occur, and even if a radar is additionally arranged to detect a target, two vehicles can be identified as one vehicle due to too close distance.
Disclosure of Invention
The technical problem to be solved by the invention is as follows: aiming at the technical problems in the prior art, the invention provides a vehicle identification method, a system and a storage medium based on adaptive threshold target clustering, which have good clustering effect and improve radar detection precision.
In order to solve the technical problems, the technical scheme provided by the invention is as follows:
a vehicle identification method based on adaptive threshold target clustering comprises the following steps:
1) processing each radar echo signal to obtain the information of the ith echo, including the distance RiVelocity viAnd angle thetai，i∈[1,N]；
2) According to the radar speed resolution ratio delta v, the radar angle resolution ratio delta theta and the information of the ith echo, obtaining the speed error delta v in the horizontal directionxIt is taken as a speed threshold deltav(ii) a For satisfying | vi-vj|≤δv i,j∈[1,N]Average the velocity of all echoes to obtain an average velocity
3) Will average the speed
Multiplying the preset time to obtain a distance threshold deltaRFor satisfying | Ri-Rj|≤δR i,j∈[1,N]Clustering all the points, and taking the clustered information as the motion characteristic of the target;
4) and clustering the rest points according to the step 2) and the step 3) until no point which can be clustered exists, thereby effectively distinguishing different targets.
Preferably, in step 2), the horizontal direction velocity error Δ v is obtained by equation (1) according to the radar velocity resolution Δ v and the radar angle resolution Δ θx
And theta is the included angle between the normal line of the radar and the ground.
Preferably, the θ is 45 degrees.
Preferably, in step 3), the preset time is the sum of the reaction time of the driver and the braking time, and is 0.4-1 s.
The invention also discloses a vehicle identification system based on the self-adaptive threshold target clustering, which comprises
A first module for processing each radar echo signal to obtain the information of the ith echo, including the distance RiVelocity viAnd angle thetai，i∈[1,N]；
A second module for obtaining a horizontal direction velocity error Deltav according to the radar velocity resolution Deltav, the radar angle resolution Deltatheta and the information of the ith echoxIt is taken as a speed threshold deltav(ii) a For satisfying | vi-vj|≤δv i,j∈[1,N]Average the velocity of all echoes to obtain an average velocity
Third stepModule for averaging the speed
Multiplying the preset time to obtain a distance threshold deltaRFor satisfying | Ri-Rj|≤δR i,j∈[1,N]Clustering all the points, and taking the clustered information as the motion characteristic of the target;
and the fourth module is used for clustering the rest points until no point which can be clustered exists, so that different targets are effectively distinguished.
The invention further discloses a computer-readable storage medium having stored thereon a computer program which, when being executed by a processor, carries out the steps of the method for vehicle identification based on adaptive threshold object clustering as described above.
The invention also discloses a computer device comprising a processor and a memory, the memory having stored thereon a computer program, characterized in that the computer program, when executed by the processor, implements the steps of the method for vehicle identification based on adaptive threshold object clustering as described above.
The invention further discloses a terminal device, which comprises one or more processors and one or more memories, wherein at least one program code is stored in the one or more memories, and the at least one program code is loaded by the one or more processors and executed to realize the steps of the vehicle identification method based on the adaptive threshold target clustering.
Compared with the prior art, the invention has the advantages that:
according to the vehicle identification method based on the adaptive threshold target clustering, a speed threshold is set according to a measurement error during target clustering, a distance threshold is set according to the motion speed of an object and the driving response time, different thresholds are adopted for different conditions, the target clustering effect is good, the precision is high, the conditions that the target is split and cannot be distinguished are prevented, and the radar detection stability is improved; the speed threshold and the distance threshold are obtained through the method, a large amount of experimental debugging is not needed, the operation is simple and convenient, and the realization is easy.
Drawings
Fig. 1 is a view showing an installation structure of a radar in an embodiment of the present invention.
Fig. 2 is a schematic diagram of a radar emitting radar signals in the present invention.
FIG. 3 is a diagram illustrating a simulation of horizontal velocity error in the present invention.
FIG. 4 is a flow chart of an embodiment of the method of the present invention.
Detailed Description
The invention is further described below with reference to the figures and the specific embodiments of the description.
As shown in figure 1, the invention adopts a method of detecting and counting the number of targets by additionally installing a millimeter wave radar, and solves the problem of charge leakage caused by vehicle following of ETC by matching with ETC. Specifically, the millimeter wave radar is additionally arranged on a straight rod with the height of 5.5m-6.5m, the included angle between the radar detection normal line and the ground is theta, wherein the theta is 45 degrees, the detection distance is longer, and the shielding of a front vehicle on a rear vehicle is avoided.
Suppose that the ETC installs two target vehicles (a and B) in the millimeter wave radar detection azimuth as described above, as shown in fig. 2:
calculating different reflection points of the target A according to the distance and the angle, and converting the radial velocity v of the reflection points into the velocity v of the moving direction (namely the horizontal direction) of the target AxAssume that there are three target reflection points A1, A2, A3 for target A, and their corresponding distances, azimuths, and velocities are R, respectively1、R2、R3And theta1、θ2、θ3And v1、v2、v3Then their direction of motion (horizontal) velocity can be calculated as:
then the calculated speeds of all the reflection points of the target a should be basically the same in theory, and the calculated speeds of all the reflection points of the target B are also basically the same in the same way, but the speeds of a and B are actually different, and theoretically, the two can be easily distinguished by the speeds, but due to the measurement error, an adaptive threshold needs to be set to distinguish the two. Assuming that the radar speed measurement error (resolution) is Δ v and the angle measurement error (resolution) is Δ θ, the horizontal direction velocity error can be defined as:
in the case of an angle error of 1 ° and a velocity resolution of 0.28m/s, matlab simulation is shown in fig. 3, and it can be seen that the velocity error in the horizontal direction fluctuates back and forth within 0.6 °.
Meanwhile, in the embodiment, the shortest time of 0.4s is considered in consideration of the fact that the reaction time plus the braking time of the driver is 0.4s-1s in practice, so that when the vehicle speed is high, a certain safety distance exists between the two vehicles, the distance can be used as a threshold of target clustering, and the distance threshold value is larger and larger along with the increase of the speed.
As shown in fig. 4, the vehicle identification method based on adaptive threshold target clustering of the present invention includes the steps of:
1) processing each radar echo signal to obtain the information of the ith echo, including the distance RiVelocity viAnd angle thetai，i∈[1,N]；
2) According to the radar speed resolution ratio delta v, the radar angle resolution ratio delta theta and the information of the ith echo, obtaining the speed error delta v in the horizontal directionxIt is taken as a speed threshold deltav(ii) a For satisfying | vi-vj|≤δv i,j∈[1,N]Average the velocity of all echoes to obtain an average velocity
3) Will average the speed
Multiplying the preset time to obtain a distance threshold deltaRFor satisfying | Ri-Rj|≤δR i,j∈[1,N]Clustering all the points, and taking the clustered information as the motion characteristic of the target;
4) and clustering the rest points according to the step 2) and the step 3) until no point which can be clustered exists, thereby effectively distinguishing different targets.
In step 2), according to the radar speed resolution Deltav and the radar angle resolution Deltatheta, obtaining the horizontal direction speed error Deltav through the formula (1)x
And theta is the included angle between the normal line of the radar and the ground.
According to the vehicle identification method based on the adaptive threshold target clustering, the speed threshold is set according to the measurement error when the targets are clustered, the distance threshold is set according to the motion speed of the object and the driving reaction time, different thresholds are adopted according to different conditions, the target clustering effect is good, the precision is high, the conditions that the targets are split and cannot be distinguished are prevented, and the radar detection stability is improved; the speed threshold and the distance threshold are obtained through the method, a large amount of experimental debugging is not needed, the operation is simple and convenient, and the realization is easy.
The process of the invention is further illustrated below with reference to a complete embodiment:
(1) detecting a target vehicle by using the millimeter wave radar erection mode in the figure 2, wherein the speed resolution of the millimeter wave radar is delta v, and the angle measurement resolution is delta theta;
(2) the radar receives and obtains N echoes of a target, each echo is subjected to signal processing to obtain the information of the ith echo, including the distance RiVelocity viAnd angle thetai，i∈[1,N]；
(3) Calculating to obtain delta v by using the radar resolution information delta v and delta theta and using the formula (1)xIt is taken as a speed threshold deltavFor satisfying | vi-vj|≤δv i,j∈[1,N]Average the velocity of all echoes to obtain an average velocity
(4) Mixing 0.4s with the average velocity obtained in step (3)
Multiplying to obtain a distance threshold deltaRFor satisfying | Ri-Rj|≤δR i,j∈[1,N]Clustering all the points, and taking the clustered information as the motion characteristic of the target;
(5) and re-clustering the rest points according to a 3-step and 4-step method until no point which can be clustered exists, so that different targets are effectively distinguished even if the targets are close to each other.
The invention also discloses a vehicle identification system based on the self-adaptive threshold target clustering, which comprises
A first module for processing each radar echo signal to obtain the information of the ith echo, including the distance RiVelocity v isiAnd angle thetai，i∈[1,N]；
A second module for obtaining the horizontal direction speed error Deltav according to the radar speed resolution Deltav, the radar angle resolution Deltatheta and the information of the ith echoxIt is taken as a speed threshold deltav(ii) a For satisfying | vi-vj|≤δv i,j∈[1,N]Average the velocities of all echoes to obtain an average velocity
A third module for averaging the speed
Multiplying the preset time to obtain a distance threshold deltaRFor satisfying | Ri-Rj|≤δR i,j∈[1,N]All the points are clustered, and the clustered information is used as the motion characteristics of the targetPerforming sign;
and the fourth module is used for clustering the rest points until no point which can be clustered exists, so that different targets are effectively distinguished.
The invention further discloses a computer-readable storage medium having stored thereon a computer program which, when being executed by a processor, carries out the steps of the method for vehicle identification based on adaptive threshold object clustering as described above. The invention also discloses a computer device comprising a processor and a memory, the memory having stored thereon a computer program, characterized in that the computer program, when executed by the processor, implements the steps of the method for vehicle identification based on adaptive threshold object clustering as described above. The invention further discloses a terminal device, which comprises one or more processors and one or more memories, wherein at least one program code is stored in the one or more memories, and the at least one program code is loaded by the one or more processors and executed to realize the steps of the vehicle identification method based on the adaptive threshold target clustering.
All or part of the flow of the method of the embodiments may be implemented by a computer program, which may be stored in a computer-readable storage medium and executed by a processor, to implement the steps of the embodiments of the methods. Wherein the computer program comprises computer program code, which may be in the form of source code, object code, an executable file or some intermediate form, etc. The computer readable medium may include: any entity or device capable of carrying computer program code, recording medium, U.S. disk, removable hard disk, magnetic disk, optical disk, computer Memory, Read-Only Memory (ROM), Random Access Memory (RAM), electrical carrier wave signals, telecommunications signals, software distribution media, and the like. The memory may be used to store computer programs and/or modules, and the processor may perform various functions by executing or executing the computer programs and/or modules stored in the memory, as well as by invoking data stored in the memory. The memory may include high speed random access memory, and may also include non-volatile memory, such as a hard disk, a memory, a plug-in hard disk, a Smart Media Card (SMC), a Secure Digital (SD) Card, a Flash memory Card (Flash Card), at least one magnetic disk storage device, a Flash memory device, or other volatile solid state storage device.
The above is only a preferred embodiment of the present invention, and the protection scope of the present invention is not limited to the above-mentioned embodiments, and all technical solutions belonging to the idea of the present invention belong to the protection scope of the present invention. It should be noted that modifications and embellishments within the scope of the invention may be made by those skilled in the art without departing from the principle of the invention.
Claims (7)
1. A vehicle identification method based on adaptive threshold target clustering is characterized by comprising the following steps:
1) processing each radar echo signal to obtain the information of the ith echo, including the distance RiVelocity viAnd angle thetai，i∈[1,N]；
2) Obtaining a horizontal direction speed error delta v according to the radar speed resolution delta v, the radar angle resolution delta theta and the information of the ith echoxIt is taken as a speed threshold deltav(ii) a For satisfying | vi-vj|≤δv i,j∈[1,N]Average the velocity of all echoes to obtain an average velocity
3) Multiplying the average speed v by the preset time to obtain the distance threshold deltaRFor satisfying | Ri-Rj|≤δR i,j∈[1,N]Clustering all the points, and taking the clustered information as the motion characteristic of the target;
4) clustering the rest points according to the step 2) and the step 3) until no point which can be clustered exists, thereby effectively distinguishing different targets;
in the step 2), according to the radar speed resolution delta v and the radar angle resolution delta theta, the horizontal direction speed error delta v is obtained through the formula (1)x
And theta is the included angle between the normal line of the radar and the ground.
2. The adaptive threshold object clustering-based vehicle identification method of claim 1, wherein θ is 45 degrees.
3. The method for vehicle identification based on adaptive threshold object clustering according to claim 1 or 2, wherein in step 3), the preset time is the sum of the reaction time and the braking time of the driver, and is 0.4-1 s.
4. A vehicle identification system based on adaptive threshold target clustering is characterized by comprising
A first module for processing each radar echo signal to obtain the information of the ith echo, including the distance RiVelocity viAnd angle thetai，i∈[1,N]；
A second module for obtaining a horizontal direction velocity error delta v according to the radar velocity resolution delta v, the radar angle resolution delta theta and the information of the ith echoxIt is taken as a speed threshold deltav(ii) a For satisfying | vi-vj|≤δv i,j∈[1,N]Average the velocity of all echoes to obtain an average velocity
A third module for averaging the speed
Multiplying the preset time to obtain a distance threshold deltaRFor satisfying | Ri-Rj|≤δRi,j∈[1,N]Clustering all the points, and taking the clustered information as the motion characteristic of the target;
a fourth module for clustering the rest points until no point which can be clustered exists, thereby effectively distinguishing different targets;
in the second module, according to the radar speed resolution delta v and the radar angle resolution delta theta, the horizontal direction speed error delta v is obtained through the formula (1)x
And theta is the included angle between the normal line of the radar and the ground.
5. A computer-readable storage medium, on which a computer program is stored which, when being executed by a processor, carries out the steps of the method for vehicle identification based on adaptive threshold object clustering according to any one of claims 1-3.
6. A computer arrangement comprising a processor and a memory, said memory having stored thereon a computer program, characterized in that the computer program, when being executed by the processor, is adapted to carry out the steps of the method for adaptive threshold object clustering based vehicle identification according to any of the claims 1-3.
7. A terminal device, characterized in that the terminal comprises one or more processors and one or more memories, in which at least one program code is stored, which is loaded and executed by the one or more processors to implement the steps of the adaptive threshold object clustering based vehicle identification method according to any of claims 1-3.
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| CN113030897B (en) * | 2021-03-10 | 2022-05-31 | 森思泰克河北科技有限公司 | Radar target clustering method, device, equipment and storage medium based on multipath |
| CN117111049B (en) * | 2023-10-23 | 2024-01-30 | 成都瑞达物联科技有限公司 | ETC channel vehicle presence detection method and system |
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