CN113030897B - Radar target clustering method, device, equipment and storage medium based on multipath - Google Patents
Radar target clustering method, device, equipment and storage medium based on multipath Download PDFInfo
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Abstract
The invention is suitable for the technical field of radar measurement and control, and provides a radar target clustering method, a device, equipment and a storage medium based on multipath, wherein the radar target clustering method based on multipath comprises the following steps: receiving a first radar frame; calculating a probability value of multipath generated by point cloud of the first radar frame; determining a clustering threshold of the first radar frame according to the corresponding relation between the probability value and the clustering threshold; clustering the point cloud based on a clustering threshold of the first radar frame and a clustering threshold of at least one second radar frame; the second radar frame is a radar frame preceding the first radar frame. By adopting the method and the device, the accuracy of radar target clustering can be improved, and the accuracy of radar target identification can be further improved.
Description
Technical Field
The invention belongs to the technical field of radar measurement and control, and particularly relates to a radar target clustering method, device, equipment and storage medium based on multipath.
Background
With the rapid development of unmanned technologies, the application of radar in the field of automobiles is becoming more common. During the driving process of the vehicle, the radar can detect targets around the vehicle and identify the types of the targets, such as big vehicles, small vehicles, pedestrians and the like.
However, when the radar identifies a target, a situation of identification error may occur, for example, one large vehicle is identified as a plurality of small vehicles or a plurality of small vehicles is identified as one large vehicle, which results in a low identification accuracy of the target.
Disclosure of Invention
In view of this, embodiments of the present invention provide a method, an apparatus, a device, and a storage medium for clustering radar targets based on multipath, so as to solve the problem in the prior art that the target identification accuracy of a radar is low.
The first aspect of the embodiments of the present invention provides a radar target clustering method based on multipath, including:
receiving a first radar frame;
calculating a probability value of multipath generated by point cloud of a first radar frame;
determining a clustering threshold of the first radar frame according to the corresponding relation between the probability value and the clustering threshold;
clustering point clouds based on the clustering threshold of the first radar frame and the clustering threshold of at least one second radar frame; the second radar frame is a radar frame preceding the first radar frame.
Optionally, calculating a probability value of a multipath generated by a point cloud of the first radar frame includes:
clustering point clouds of the first radar frame according to a preset clustering threshold to obtain at least one target;
calculating probability values of at least one object generating multipath;
and determining the probability value of the point cloud of the first radar frame generating the multipath according to the probability value of the multipath generated by the at least one target.
Optionally, determining a probability value of the point cloud of the first radar frame generating the multipath according to the probability value of the multipath generated by the at least one target includes:
and determining the probability value of generating the multipath for the point cloud of the first radar frame by the maximum probability value in the probability values of generating the multipath by at least one target.
Optionally, determining the clustering threshold of the first radar frame according to the corresponding relationship between the probability value and the clustering threshold includes:
and determining the multiplication value of the probability value and a preset clustering threshold as the clustering threshold of the first radar frame.
Optionally, determining the clustering threshold of the first radar frame according to the corresponding relationship between the probability value and the clustering threshold includes:
determining a preset probability interval where the probability value is located;
and determining the clustering threshold corresponding to the preset probability interval as the clustering threshold of the first radar frame.
Optionally, clustering point clouds based on a clustering threshold of a first radar frame and a clustering threshold of at least one second radar frame includes:
averaging the clustering threshold of the first radar frame and the clustering threshold of at least one second radar frame to obtain an average clustering threshold;
and clustering the point cloud according to the average clustering threshold.
Optionally, clustering point clouds based on a clustering threshold of a first radar frame and a clustering threshold of at least one second radar frame includes:
respectively multiplying the clustering threshold of the first radar frame and the clustering threshold of at least one second radar frame by corresponding weight values to obtain weighted clustering thresholds;
and clustering the point cloud according to the weighted clustering threshold.
A second aspect of an embodiment of the present invention provides a radar target clustering device based on multipath, including:
a receiving module for receiving a first radar frame;
the calculation module is used for calculating the probability value of multipath generated by the point cloud of the first radar frame;
the determining module is used for determining the clustering threshold of the first radar frame according to the corresponding relation between the probability value and the clustering threshold;
the clustering module is used for clustering point clouds based on the clustering threshold of the first radar frame and the clustering threshold of at least one second radar frame; the second radar frame is a radar frame preceding the first radar frame.
Optionally, the calculation module is further configured to:
clustering point clouds of the first radar frame according to a preset clustering threshold to obtain at least one target;
calculating probability values of at least one object generating multipath;
and determining the probability value of the point cloud of the first radar frame generating the multipath according to the probability value of the multipath generated by the at least one target.
Optionally, the calculation module is further configured to:
and determining the probability value of generating the multipath for the point cloud of the first radar frame by the maximum probability value in the probability values of generating the multipath by at least one target.
Optionally, the determining module is further configured to:
and determining the multiplication value of the probability value and a preset clustering threshold as the clustering threshold of the first radar frame.
Optionally, the determining module is further configured to:
determining a preset probability interval where the probability value is located;
and determining the clustering threshold corresponding to the preset probability interval as the clustering threshold of the first radar frame.
Optionally, the clustering module is further configured to:
averaging the clustering threshold of the first radar frame and the clustering threshold of at least one second radar frame to obtain an average clustering threshold;
and clustering the point cloud according to the average clustering threshold.
Optionally, the clustering module is further configured to:
respectively multiplying the clustering threshold of the first radar frame and the clustering threshold of at least one second radar frame by corresponding weight values to obtain weighted clustering thresholds;
and clustering the point cloud according to the weighted clustering threshold.
A third aspect of embodiments of the present invention provides an electronic device, which includes a memory, a processor, and a computer program stored in the memory and executable on the processor, and the processor implements the steps of the method according to the first aspect when executing the computer program.
A fourth aspect of embodiments of the present invention provides a computer-readable storage medium storing a computer program which, when executed by a processor, performs the steps of the method according to the first aspect.
Compared with the prior art, the embodiment of the invention has the following beneficial effects:
after receiving a first radar frame, the embodiment of the invention can calculate the probability value of the multipath generated by the point cloud of the first radar frame, and then determine the clustering threshold of the first radar frame according to the corresponding relation between the probability value and the clustering threshold. As such, the point cloud may be clustered based on the clustering threshold of the first radar frame and the clustering threshold of the at least one second radar frame. Therefore, the probability value of the multipath generated by the point cloud in the first radar frame can be utilized to judge the type of the target which influences the clustering accuracy rate in the first radar frame in advance, and then the target clustering can be carried out by adopting the clustering threshold corresponding to the target type. Therefore, the condition of clustering errors caused by clustering by adopting a fixed initial clustering threshold can be avoided, and the clustering threshold matched with the target in the point cloud is adopted for clustering, so that the clustering accuracy can be improved, and further, the target identification accuracy of the radar can be improved.
Drawings
In order to more clearly illustrate the technical solutions in the embodiments of the present invention, the drawings needed to be used in the embodiments or the prior art descriptions will be briefly described below, and it is obvious that the drawings in the following description are only some embodiments of the present invention, and it is obvious for those skilled in the art to obtain other drawings based on these drawings without inventive exercise.
Fig. 1 is a flowchart illustrating steps of a multipath-based radar target clustering method according to an embodiment of the present invention;
fig. 2 is a schematic diagram of a radar target clustering device based on multipath according to an embodiment of the present invention;
fig. 3 is a schematic diagram of an electronic device according to an embodiment of the present invention.
Detailed Description
In the following description, for purposes of explanation and not limitation, specific details are set forth, such as particular system structures, techniques, etc. in order to provide a thorough understanding of the embodiments of the invention. It will be apparent, however, to one skilled in the art that the present invention may be practiced in other embodiments that depart from these specific details. In other instances, detailed descriptions of well-known systems, devices, circuits, and methods are omitted so as not to obscure the description of the present invention with unnecessary detail.
In order to illustrate the technical means of the present invention, the following description is given by way of specific examples.
As described in the background art, when a radar identifies a target, an identification error condition that a large vehicle is identified as a plurality of small vehicles or a plurality of small vehicles is identified as a large vehicle sometimes occurs, resulting in a low identification accuracy of the target.
The applicant finds that the reason for the radar target identification error is that an unreasonable clustering threshold, usually a fixed initial clustering threshold, such as 0.5 meter, is selected when the radar performs target clustering, which results in low accuracy of radar target clustering. For example, for a target with a large size, the distribution of points in the corresponding point cloud is concentrated, and when the radar performs clustering processing by using the initial clustering threshold, the target with the large size is often clustered into a plurality of targets with small sizes, so that erroneous clustering is performed. When the radar identifies the target, the target is identified based on the clustering result, so that when the target is identified based on the wrong clustering, the identification result is also wrong.
In order to solve the problems in the prior art, embodiments of the present invention provide a method, an apparatus, a device, and a storage medium for clustering radar targets based on multipath. First, a multipath-based radar target clustering method provided by the embodiment of the present invention is described below.
Multipath and probability values for generating multipath are described below.
In the field of electromagnetism, electronic equipment such as radars or communication transmitters can emit electromagnetic waves, the electromagnetic waves are refracted and reflected for multiple times in the natural environment and then received by electronic equipment such as receivers, and information carried by the electromagnetic waves can be extracted and analyzed through various signal processing and data processing methods. From this information, information such as distance and angle to the transmitter or the environmental object can be known. In a relatively open environment, electromagnetic waves can be received by the receiver after being reflected by a space target, and at the moment, the receiving system can demodulate and solve target information normally. If the space of the target is complex, such as indoor space, urban area, tunnel, etc., the receiving device receives not only the electromagnetic wave directly reflected by the target, but also the echo generated by multiple combined reflections of the target and the surrounding complex reflecting surface. Generally, an echo received by a receiver via a primary reflection of a target is called a direct wave, and an echo received by a receiver via multiple reflections of the target and a spatial reflector is called a multipath wave.
Taking a radar receiver as an example, due to multiple reflections of multipath signals, the radar will detect a false target at a position in space where no target exists, the false target may be referred to as a multipath target corresponding to a real target, and accordingly, probability values of multipath generation may be used to measure probability of a target corresponding to the multipath target.
In some embodiments, the probability value of the multipath generated by the target can be calculated by using the method of micro-Doppler and flight path similarity of the target.
Since multipath objects are often a negative target, they are often suppressed or culled after they are found. However, the applicant has found that the probability values for different types of objects to produce multipath are characterised by large size objects and larger probability values for producing multipath. As shown in table one, probability values for multiple sizes of objects to produce multipath are shown.
Watch 1
Based on the characteristics, the waste utilization can be carried out on the multipath, the target type of the target is judged by utilizing the probability value of the multipath generated by the target, and then the clustering threshold corresponding to the target type can be adopted for target clustering. Therefore, the condition of clustering errors caused by clustering by adopting a fixed initial clustering threshold can be avoided.
The execution subject of the multipath-based radar target clustering method can be a multipath-based radar target clustering device, and the multipath-based radar target clustering device can be an electronic device with data processing capability, such as a microwave radar, a vehicle-mounted radar, a traffic radar, a security radar and the like, and the embodiment of the invention is not particularly limited.
As shown in fig. 1, the method for clustering radar targets based on multipath according to the embodiment of the present invention may include the following steps:
step S110, a first radar frame is received.
In some embodiments, the first radar frame may be a radar frame currently performing target recognition, and the radar frame may include a large number of points reflecting information of target distance, speed, and the like, and the sum of the points may be referred to as a point cloud.
Step S120, calculating a probability value of multipath generated by the point cloud of the first radar frame.
In some embodiments, when a large-sized target exists in the point cloud, a large clustering threshold is used for clustering the point cloud, so that the accuracy of point cloud clustering can be improved. Therefore, the clustering threshold of the targets with larger sizes in the point cloud often determines the clustering accuracy. Thus, the probability value of the point cloud generating multipath can be the probability value of the multipath generated by the object with larger size in the point cloud.
In this way, after receiving the first radar frame, the multipath-based radar target clustering device can calculate the probability value of the multipath generated by the point cloud of the first radar frame.
In some embodiments, the point clouds of the first radar frame may be clustered according to a preset clustering threshold to obtain at least one object, and then probability values of the at least one object generating multi-paths may be calculated. Finally, a probability value of the point cloud of the first radar frame generating multipath can be determined according to the probability value of the at least one target generating multipath.
Taking the example of clustering the point cloud of the first radar frame to obtain 3 targets, probability values of multipath generated by the 3 targets can be calculated, and thus, 3 probability values can be obtained. The highest of these 3 probability values may then be determined as the probability value that produces multipath for the point cloud of the first radar frame.
Step S130, determining a clustering threshold of the first radar frame according to the corresponding relation between the probability value and the clustering threshold.
In some embodiments, different probability values correspond to different object types, and different object types may correspond to different clustering thresholds, so that a correspondence between the probability values and the clustering thresholds may be obtained. For example, the probability value of multipath occurrence for a large vehicle may be 80%, and the clustering threshold corresponding to the large vehicle may be 1 meter, then the probability value of 80% may correspond to the clustering threshold of 1 meter.
Therefore, after the probability value of the multipath generated by the point cloud of the first radar frame is calculated, the radar target clustering device based on the multipath can determine the clustering threshold of the first radar frame according to the corresponding relation between the probability value and the clustering threshold.
In some embodiments, the value obtained by multiplying the probability value by a preset clustering threshold may be determined as the clustering threshold of the first radar frame.
Taking the preset clustering threshold of 1.2 meters as an example, if the probability value of the point cloud of the first radar frame generating multipath is 80%, the clustering threshold of the first radar frame may be 0.96 meters.
In some embodiments, a preset probability interval in which the probability value is located may be determined, and then a clustering threshold corresponding to the preset probability interval may be determined as the clustering threshold of the first radar frame.
Specifically, the preset probability interval may be set to 10% -30%, 31% -60%, 61% -80%, 81% -100%, and the corresponding clustering threshold may be 0.5 m, 0.6 m, 0.8 m, or 1 m. Thus, when the probability value is 85%, the corresponding clustering threshold may be 1 meter.
And step S140, clustering point clouds based on the clustering threshold of the first radar frame and the clustering threshold of at least one second radar frame.
In some embodiments, the second radar frame may be a radar frame that precedes the first radar frame.
In some embodiments, considering that the reliability of the clustering threshold of a single radar frame is low, the clustering threshold for finally clustering can be obtained by using the clustering thresholds of a plurality of radar frames before the radar frame, so that the accuracy and robustness of clustering are improved.
In some embodiments, the clustering threshold of the first radar frame and the clustering threshold of the at least one second radar frame may be averaged to obtain an average clustering threshold, and then the point cloud may be clustered according to the average clustering threshold.
Taking 5 second radar frames as an example, assuming that the clustering threshold of the first radar frame is 0.9 m, and the clustering thresholds of the 5 second radar frames are 0.4 m, 0.5 m, 0.6 m, 0.7 m and 0.8 m, respectively, the average clustering threshold is 0.65 m.
In some embodiments, the clustering threshold of the first radar frame and the clustering threshold of the at least one second radar frame may be multiplied by corresponding weight values, respectively, to obtain weighted clustering thresholds, and then the point clouds may be clustered according to the weighted clustering thresholds.
In the embodiment of the invention, after a first radar frame is received, a probability value of a point cloud of the first radar frame generating multipath can be calculated, and then a clustering threshold of the first radar frame is determined according to a corresponding relation between the probability value and the clustering threshold. As such, the point cloud may be clustered based on the clustering threshold of the first radar frame and the clustering threshold of the at least one second radar frame. Therefore, the probability value of multipath generated by point cloud in the first radar frame can be utilized to judge the type of the target influencing the clustering accuracy rate in the first radar frame in advance, and then the clustering threshold corresponding to the target type can be adopted to cluster the target. Therefore, the condition of clustering errors caused by clustering by adopting a fixed initial clustering threshold can be avoided, and the clustering threshold matched with the target in the point cloud is adopted for clustering, so that the clustering accuracy can be improved, and further, the target identification accuracy of the radar can be improved.
In addition, the method has the advantages of simple implementation, convenience in engineering implementation and low cost, only needs to add a software module in the conventional radar system, does not need extra hardware cost, has strong universality and can be used in various radar systems.
Based on the multipath-based radar target clustering method provided by the embodiment, correspondingly, the invention also provides a specific implementation mode of the multipath-based radar target clustering device applied to the multipath-based radar target clustering method. Please see the examples below.
As shown in fig. 2, there is provided a multipath-based radar object clustering apparatus, including:
a receiving module 210, configured to receive a first radar frame;
a calculating module 220, configured to calculate a probability value of multipath generated by the point cloud of the first radar frame;
a determining module 230, configured to determine a clustering threshold of the first radar frame according to a corresponding relationship between the probability value and the clustering threshold;
a clustering module 240 configured to cluster the point clouds based on a clustering threshold of the first radar frame and a clustering threshold of the at least one second radar frame; the second radar frame is a radar frame preceding the first radar frame.
Optionally, the calculation module is further configured to:
clustering point clouds of the first radar frame according to a preset clustering threshold to obtain at least one target;
calculating probability values of at least one object generating multipath;
and determining the probability value of the point cloud of the first radar frame generating the multipath according to the probability value of the multipath generated by the at least one target.
Optionally, the calculation module is further configured to:
and determining the probability value of generating the multipath for the point cloud of the first radar frame by the maximum probability value in the probability values of generating the multipath by at least one target.
Optionally, the determining module is further configured to:
and determining the multiplication value of the probability value and a preset clustering threshold as the clustering threshold of the first radar frame.
Optionally, the determining module is further configured to:
determining a preset probability interval where the probability value is located;
and determining the clustering threshold corresponding to the preset probability interval as the clustering threshold of the first radar frame.
Optionally, the clustering module is further configured to:
averaging the clustering threshold of the first radar frame and the clustering threshold of at least one second radar frame to obtain an average clustering threshold;
and clustering the point cloud according to the average clustering threshold.
Optionally, the clustering module is further configured to:
respectively multiplying the clustering threshold of the first radar frame and the clustering threshold of at least one second radar frame by corresponding weight values to obtain weighted clustering thresholds;
and clustering the point cloud according to the weighted clustering threshold.
In the embodiment of the invention, after a first radar frame is received, a probability value of a point cloud of the first radar frame generating multipath can be calculated, and then a clustering threshold of the first radar frame is determined according to a corresponding relation between the probability value and the clustering threshold. As such, the point cloud may be clustered based on the clustering threshold of the first radar frame and the clustering threshold of the at least one second radar frame. Therefore, the probability value of the multipath generated by the point cloud in the first radar frame can be utilized to judge the type of the target which influences the clustering accuracy rate in the first radar frame in advance, and then the target clustering can be carried out by adopting the clustering threshold corresponding to the target type. Therefore, the condition of clustering errors caused by clustering by adopting a fixed initial clustering threshold can be avoided, and the clustering threshold matched with the target in the point cloud is adopted for clustering, so that the clustering accuracy can be improved, and further, the target identification accuracy of the radar can be improved.
In addition, the method has the advantages of simple implementation, convenience in engineering implementation and low cost, only needs to add a software module in the conventional radar system, does not need extra hardware cost, has strong universality and can be used in various radar systems.
Fig. 3 is a schematic diagram of an electronic device according to an embodiment of the present invention. As shown in fig. 3, the electronic apparatus 3 of this embodiment includes: a processor 30, a memory 31 and a computer program 32 stored in said memory 31 and executable on said processor 30. The processor 30, when executing the computer program 32, implements the steps in the various multipath-based radar object clustering method embodiments described above. Alternatively, the processor 30 implements the functions of the modules/units in the above-described device embodiments when executing the computer program 32.
Illustratively, the computer program 32 may be partitioned into one or more modules/units that are stored in the memory 31 and executed by the processor 30 to implement the present invention. The one or more modules/units may be a series of computer program instruction segments capable of performing specific functions, which are used to describe the execution of the computer program 32 in the electronic device 3. For example, the computer program 32 may be divided into a receiving module, a calculating module, a determining module, and a clustering module, and the specific functions of each module are as follows:
a receiving module for receiving a first radar frame;
the calculation module is used for calculating the probability value of multipath generated by the point cloud of the first radar frame;
the determining module is used for determining the clustering threshold of the first radar frame according to the corresponding relation between the probability value and the clustering threshold;
the clustering module is used for clustering point clouds based on the clustering threshold of the first radar frame and the clustering threshold of at least one second radar frame; the second radar frame is a radar frame preceding the first radar frame.
The electronic device 3 may be a desktop computer, a notebook, a palm computer, a cloud server, or other computing devices. The electronic device may include, but is not limited to, a processor 30, a memory 31. It will be appreciated by those skilled in the art that fig. 3 is merely an example of the electronic device 3, and does not constitute a limitation of the electronic device 3, and may include more or less components than those shown, or combine certain components, or different components, for example, the electronic device may also include input output devices, network access devices, buses, etc.
The Processor 30 may be a Central Processing Unit (CPU), other general purpose Processor, a Digital Signal Processor (DSP), an Application Specific Integrated Circuit (ASIC), a Field Programmable Gate Array (FPGA) or other Programmable logic device, discrete Gate or transistor logic, discrete hardware components, etc. A general purpose processor may be a microprocessor or the processor may be any conventional processor or the like.
The memory 31 may be an internal storage unit of the electronic device 3, such as a hard disk or a memory of the electronic device 3. The memory 31 may also be an external storage device of the electronic device 3, such as a plug-in hard disk, a Smart Media Card (SMC), a Secure Digital (SD) Card, a Flash memory Card (Flash Card), and the like, which are provided on the electronic device 3. Further, the memory 31 may also include both an internal storage unit and an external storage device of the electronic device 3. The memory 31 is used for storing the computer program and other programs and data required by the electronic device. The memory 31 may also be used to temporarily store data that has been output or is to be output.
It will be apparent to those skilled in the art that, for convenience and brevity of description, only the above-mentioned division of the functional units and modules is illustrated, and in practical applications, the above-mentioned function distribution may be performed by different functional units and modules according to needs, that is, the internal structure of the apparatus is divided into different functional units or modules to perform all or part of the above-mentioned functions. Each functional unit and module in the embodiments may be integrated in one processing unit, or each unit may exist alone physically, or two or more units are integrated in one unit, and the integrated unit may be implemented in a form of hardware, or in a form of software functional unit. In addition, specific names of the functional units and modules are only for convenience of distinguishing from each other, and are not used for limiting the protection scope of the present application. The specific working processes of the units and modules in the system may refer to the corresponding processes in the foregoing method embodiments, and are not described herein again.
In the above embodiments, the descriptions of the respective embodiments have respective emphasis, and reference may be made to the related descriptions of other embodiments for parts that are not described or illustrated in a certain embodiment.
Those of ordinary skill in the art will appreciate that the various illustrative elements and algorithm steps described in connection with the embodiments disclosed herein may be implemented as electronic hardware or combinations of computer software and electronic hardware. Whether such functionality is implemented as hardware or software depends upon the particular application and design constraints imposed on the implementation. Skilled artisans may implement the described functionality in varying ways for each particular application, but such implementation decisions should not be interpreted as causing a departure from the scope of the present invention.
In the embodiments provided in the present invention, it should be understood that the disclosed apparatus/terminal device and method may be implemented in other ways. For example, the above-described embodiments of the apparatus/terminal device are merely illustrative, and for example, the division of the modules or units is only one logical division, and there may be other divisions when actually implemented, for example, a plurality of units or components may be combined or integrated into another system, or some features may be omitted, or not executed. In addition, the shown or discussed mutual coupling or direct coupling or communication connection may be an indirect coupling or communication connection through some interfaces, devices or units, and may be in an electrical, mechanical or other form.
The units described as separate parts may or may not be physically separate, and parts displayed as units may or may not be physical units, may be located in one place, or may be distributed on a plurality of network units. Some or all of the units can be selected according to actual needs to achieve the purpose of the solution of the embodiment.
In addition, functional units in the embodiments of the present invention may be integrated into one processing unit, or each unit may exist alone physically, or two or more units are integrated into one unit. The integrated unit can be realized in a form of hardware, and can also be realized in a form of a software functional unit.
The integrated modules/units, if implemented in the form of software functional units and sold or used as separate products, may be stored in a computer readable storage medium. Based on such understanding, all or part of the flow of the method according to the embodiments of the present invention may also be implemented by a computer program, which may be stored in a computer-readable storage medium, and when the computer program is executed by a processor, the steps of the method embodiments may be implemented. 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 the computer program code, recording medium, usb 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 medium, and the like. It should be noted that the computer readable medium may contain content that is subject to appropriate increase or decrease as required by legislation and patent practice in jurisdictions, for example, in some jurisdictions, computer readable media does not include electrical carrier signals and telecommunications signals as is required by legislation and patent practice.
The above-mentioned embodiments are only used to illustrate the technical solution of the present invention, and not to limit the same; although the present invention has been described in detail with reference to the foregoing embodiments, it should be understood by those of ordinary skill in the art that: the technical solutions described in the foregoing embodiments may still be modified, or some technical features may be equivalently replaced; such modifications and substitutions do not substantially depart from the spirit and scope of the embodiments of the present invention, and are intended to be included within the scope of the present invention.
Claims (9)
1. A radar target clustering method based on multipath is characterized by comprising the following steps:
receiving a first radar frame;
calculating a probability value of multipath generated by point cloud of the first radar frame;
determining a clustering threshold of the first radar frame according to the corresponding relation between the probability value and the clustering threshold;
clustering the point cloud based on the clustering threshold of the first radar frame and the clustering threshold of at least one second radar frame; the second radar frame is a radar frame located before the first radar frame;
wherein said calculating a probability value of point clouds yielding multipaths for the first radar frame comprises:
clustering the point cloud of the first radar frame according to a preset clustering threshold to obtain at least one target; calculating probability values of the at least one target producing multipath; and determining the probability value of the multipath generated by the point cloud of the first radar frame according to the probability value of the multipath generated by the at least one target.
2. The multipath-based radar target clustering method of claim 1, wherein the determining the probability value that the point cloud of the first radar frame produces multipath based on the probability value that the at least one target produces multipath comprises:
and determining the probability value of generating the multipath for the point cloud of the first radar frame by the maximum probability value in the probability values of generating the multipath by the at least one target.
3. The multipath-based radar target clustering method of claim 1, wherein the determining the clustering threshold for the first radar frame based on the correspondence between the probability value and the clustering threshold comprises:
and determining the multiplication value of the probability value and a preset clustering threshold as the clustering threshold of the first radar frame.
4. The multipath-based radar target clustering method of claim 1, wherein the determining the clustering threshold for the first radar frame based on the correspondence between the probability value and the clustering threshold comprises:
determining a preset probability interval in which the probability value is located;
and determining the clustering threshold corresponding to the preset probability interval as the clustering threshold of the first radar frame.
5. The multipath-based radar target clustering method of claim 1, wherein the clustering the point cloud based on the clustering threshold of the first radar frame and the clustering threshold of at least one second radar frame comprises:
averaging the clustering threshold of the first radar frame and the clustering threshold of the at least one second radar frame to obtain an average clustering threshold;
and clustering the point cloud according to the average clustering threshold.
6. The multipath-based radar target clustering method of claim 1, wherein the clustering the point cloud based on the clustering threshold of the first radar frame and the clustering threshold of at least one second radar frame comprises:
respectively multiplying the clustering threshold of the first radar frame and the clustering threshold of the at least one second radar frame by corresponding weight values to obtain weighted clustering thresholds;
and clustering the point cloud according to the weighted clustering threshold.
7. A radar target clustering device based on multipath is characterized by comprising:
a receiving module for receiving a first radar frame;
the calculation module is used for calculating the probability value of multipath generated by the point cloud of the first radar frame;
a determining module, configured to determine a clustering threshold of the first radar frame according to a correspondence between the probability value and the clustering threshold;
a clustering module for clustering the point cloud based on a clustering threshold of the first radar frame and a clustering threshold of at least one second radar frame; the second radar frame is a radar frame located before the first radar frame;
the calculation module is specifically configured to:
clustering point clouds of the first radar frame according to a preset clustering threshold to obtain at least one target; calculating probability values of at least one object generating multipath; and determining the probability value of the point cloud of the first radar frame generating the multipath according to the probability value of the multipath generated by the at least one target.
8. An electronic device comprising a memory, a processor and a computer program stored in the memory and executable on the processor, characterized in that the steps of the method according to any of claims 1 to 6 are implemented when the computer program is executed by the processor.
9. A computer-readable storage medium, in which a computer program is stored which, when being executed by a processor, carries out the steps of the method according to any one of claims 1 to 6.
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