CN111226132A

CN111226132A - Target detection method and device, millimeter wave radar and movable platform

Info

Publication number: CN111226132A
Application number: CN201980004959.3A
Authority: CN
Inventors: 李怡强; 卜运成; 陆新飞
Original assignee: SZ DJI Technology Co Ltd
Current assignee: Shenzhen Zhuoyu Technology Co ltd
Priority date: 2019-03-18
Filing date: 2019-03-18
Publication date: 2020-06-02
Also published as: WO2020186420A1

Abstract

Provided are a target detection method, a device, a millimeter wave radar and a movable platform, wherein the method comprises the following steps: acquiring detection information of a detection target and track reflection intensity of the detection target (S101); clustering the reflection points of the detection target according to the detection information of the detection target to generate clustered reflection points, and determining the number of the clustered reflection points (S102); determining the confidence coefficient of the type of the detection target according to the number of the clustering reflection points and the track reflection intensity of the detection target (S103); and determining the detection target as a preset type according to the confidence degree of the type of the detection target (S104). Therefore, the detection target is adaptively identified, and the identification efficiency and accuracy of the detection target are improved.

Description

Target detection method and device, millimeter wave radar and movable platform

Technical Field

The invention relates to the technical field of automatic driving, in particular to a target detection method, target detection equipment, a millimeter wave radar and a movable platform.

Background

At present, the target detection technology is more and more widely applied in various fields, for example, trucks in the field of automatic Driving, in recent years, the fields of Advanced Driver Assistance System (ADAS) and Automatic Driving (AD) are rapidly developed, and millimeter wave radars are widely used due to the advantages of all-weather, long operating distance, high speed measurement precision and the like.

However, object recognition is always a disadvantage of the millimeter wave radar, and especially when detecting objects such as trucks, buses, and container trucks, the millimeter wave radar often causes target splitting, track splitting, and the like, so that the correct type of the target cannot be determined, and a large number of misjudgments and false alarms are caused for automatic driving and assistant driving, which may cause potential safety hazards for ADAS systems and AD systems. Therefore, how to more effectively improve the target identification efficiency and the system safety is of great significance.

Disclosure of Invention

The embodiment of the invention provides a target detection method, target detection equipment, a millimeter wave radar and a movable platform, which can adaptively identify a detected target and improve the identification efficiency and accuracy of the detected target.

In a first aspect, an embodiment of the present invention provides a target detection method, applied to a millimeter wave radar, including:

acquiring detection information of a detection target and track reflection intensity of the detection target;

clustering the reflection points of the detection target according to the detection information of the detection target to generate clustered reflection points, and determining the number of the clustered reflection points;

determining the confidence coefficient of the type of the detection target according to the number of the clustering reflection points and the track reflection intensity of the detection target;

and determining the detection target to be a preset type according to the confidence coefficient of the type of the detection target.

In a second aspect, an embodiment of the present invention provides another target detection method, which is applied to a millimeter wave radar, and includes:

acquiring a clustering reflection point of a detection target, and acquiring a position coordinate of the clustering reflection point, wherein the position coordinate is determined and obtained based on a pre-established coordinate system;

and determining the length and the width of the detection target according to the position coordinates of the clustering reflection points.

In a third aspect, an embodiment of the present invention provides a target detection device, which is applied to a millimeter wave radar, and includes: one or more processors, working collectively or individually, the processors being configured to:

In a fourth aspect, an embodiment of the present invention provides another target detection device, which is applied to a millimeter wave radar, where the millimeter wave radar is capable of obtaining reflection intensity information of a detection target and the number of clustered reflection points, and determining a confidence level of the detection target according to the reflection intensity information and the number of clustered reflection points; the apparatus includes one or more processors, working collectively or individually, to perform the following operations:

acquiring a clustering reflection point of the detection target, and acquiring a position coordinate of the clustering reflection point, wherein the position coordinate is determined based on a pre-established coordinate system;

In a fifth aspect, an embodiment of the present invention provides a millimeter wave radar, including:

the antenna is used for acquiring echo signals;

a processor communicatively coupled to the antenna, the processor configured to:

In a sixth aspect, an embodiment of the present invention provides another millimeter wave radar, including:

the antenna is used for acquiring echo signals;

In a seventh aspect, an embodiment of the present invention provides a movable platform, including:

a body;

the power system is arranged on the movable platform and used for providing moving power for the movable platform;

the apparatus as provided in the third or fourth aspect above.

In an eighth aspect, the present invention provides a computer-readable storage medium, which stores a computer program, and when the computer program is executed by a processor, the computer program implements the method according to the first aspect or the second aspect.

In the embodiment of the invention, the target detection equipment can acquire the detection information of the detection target and the track reflection intensity of the detection target, cluster the reflection points of the detection target according to the detection information of the detection target to generate clustered reflection points, and determine the number of the clustered reflection points. The target detection device may determine a confidence level of the type of the detection target according to the number of the cluster reflection points and the track reflection intensity of the detection target, and determine that the detection target is a preset type according to the confidence level of the type of the detection target. By the implementation mode, the detection target can be adaptively identified, and the identification efficiency and accuracy of the detection target are improved.

Drawings

In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings needed in the embodiments 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 without creative efforts.

Fig. 1 is a schematic flow chart of a target detection method according to an embodiment of the present invention;

FIG. 2a is a schematic diagram of a distribution of reflection points of a truck according to an embodiment of the present invention;

FIG. 2b is a schematic view of a reflection point distribution of another truck according to an embodiment of the present invention;

FIG. 3 is a schematic flow chart of another target detection method provided by the embodiment of the invention;

FIG. 4a is a schematic diagram of an energy envelope versus distance according to an embodiment of the present invention;

FIG. 4b is a schematic diagram of the relationship between energy and distance of an unmanned vehicle according to an embodiment of the present invention;

FIG. 5 is a schematic view of a coordinate system of a truck provided by an embodiment of the present invention;

fig. 6 is a schematic structural diagram of an object detection device according to an embodiment of the present invention;

fig. 7 is a schematic structural diagram of another object detection device according to an embodiment of the present invention.

Detailed Description

The technical solutions in the embodiments of the present invention will be described clearly below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.

Some embodiments of the invention are described in detail below with reference to the accompanying drawings. The embodiments described below and the features of the embodiments can be combined with each other without conflict.

The target detection method provided in the embodiment of the present invention may be performed by a target detection apparatus, which may be applied to a millimeter wave radar. In some embodiments, the millimeter wave radar may be disposed on a movable platform; in some embodiments, the millimeter wave radar may be spatially independent of the movable platform. In some embodiments, the movable platform can be applied to intelligent terminals such as unmanned vehicles, unmanned ships and unmanned planes.

Taking an unmanned vehicle in the field of automatic driving as an example, large unmanned vehicles such as trucks and the like are usually mistaken for multiple target points by millimeter wave radars in actual roads in the field of automatic driving at present, so that an ADAS system determines whether the targets are the same object or not, and whether the positions of the targets are in a dangerous area or not causes misjudgment, thereby causing bad conditions such as misinformation or alarm delay and the like.

When the target detection equipment detects the target, the millimeter wave radar can be used for selecting the track of the detected target, and then the reflecting points of the detected target can be clustered according to the distance information, the speed information and other information of the detected target so as to select the clustered reflecting points. After the target detection device selects the clustering reflection points, the confidence of the detection target can be determined according to the confidence of the clustering reflection points of the previous frame and the number of the clustering reflection points of the current frame, and the detection target is determined to be a preset type according to the confidence of the detection target. After determining that the detection target is of a preset type, the target detection device may perform filtering processing according to the position coordinates of the clustered reflection points and by combining the length and the width of the previous frame of detection target, so as to determine the length and the width of the detection target. After the length and the width of the detection target are determined, the target detection equipment can also expand a detection range to search whether other clustering reflection points exist on the track of the detection target, if so, the length and the width of the detection target are recalculated, and the position information of the detection target is marked.

By the target detection method provided by the embodiment of the invention, the target identification can be efficiently and accurately completed by utilizing the spatial topological relation and the reflection intensity relation among all the reflection points of the detected target on the basis of not additionally adding millimeter wave radar hardware and a processor, so that the problems are solved, the robustness of the whole ADAS and AD system is improved, and the user experience is improved.

Moreover, the identification of the ultra-large detection target is always a difficult and painful point in the industry, the method provided by the embodiment of the invention can also estimate the width and the length of the detection target and the position information of the detection target, can effectively identify different types of detection targets such as the large detection target and the like, and effectively solves the problem.

The following describes schematically a target detection method provided by an embodiment of the present invention with reference to the drawings.

Referring to fig. 1 in detail, fig. 1 is a schematic flowchart of a target detection method according to an embodiment of the present invention, where the method may be executed by a target detection device, where the target detection device is applied to a millimeter wave radar, and the millimeter wave radar is disposed on a movable platform, as described above. Specifically, the method of the embodiment of the present invention includes the following steps.

S101: and acquiring detection information of a detection target and track reflection intensity of the detection target.

In the embodiment of the invention, the target detection equipment can acquire the detection information of the detection target and the track reflection intensity of the detection target. In some embodiments, the detection target includes, but is not limited to, an unmanned vehicle, an unmanned ship, an unmanned plane, and other intelligent terminals.

In some embodiments, the detection information of the detection target includes at least one of: and the speed information and the distance information of the reflection point of the detection target. In some embodiments, the object detection apparatus may determine velocity information of a reflection point of the detection object by acquiring a doppler bin. In some embodiments, the doppler bin refers to a doppler frequency point, and the doppler frequency point is in a direct proportion relation with the velocity information of the reflection point of the detection target. In some embodiments, the target detection device may determine distance information of a reflection point of the detection target by a millimeter wave radar; in some embodiments, the distance information may include a lateral distance and a longitudinal distance.

In one embodiment, the object detection device may detect a detection object and record a track of the detection object before acquiring detection information of the detection object and a track reflection intensity of the detection object. In some embodiments, the target detection device may select a mature flight path as the flight path of the detection target according to the recorded flight path of the detection target. In some embodiments, the mature track may be selected by a user or selected according to a preset condition, and the embodiment of the present invention is not particularly limited.

Taking an unmanned vehicle as an example, the target detection device may obtain a doppler bin such as a Dbin of a reflection point of the unmanned vehicle_candiAnd obtainingDoppler bin such as Dbin of the track of the unmanned vehicle_trackAnd acquiring the speed information of the reflection point of the unmanned vehicle. The target detection equipment can acquire the longitudinal distance Ry of the track of the unmanned vehicle_trackAnd a lateral distance Rx_trackAnd acquiring the longitudinal distance Ry of the reflection point of the unmanned vehicle_candiAnd a lateral distance Rx_candi。

S102: and clustering the reflection points of the detection target according to the detection information of the detection target to generate clustered reflection points, and determining the number of the clustered reflection points.

In the embodiment of the present invention, the target detection device may cluster the reflection points of the detection target according to the detection information of the detection target to generate clustered reflection points, and determine the number of the clustered reflection points.

In some embodiments, the reflection point of the detection target may include a plurality. Assuming that the detection target is a truck, the reflection points of the truck are illustrated by taking fig. 2a and fig. 2b as examples, fig. 2a is a schematic distribution diagram of the reflection points of one truck according to the embodiment of the present invention, and fig. 2b is a schematic distribution diagram of the reflection points of another truck according to the embodiment of the present invention. As shown in fig. 2a and 2b, the vehicle includes a main lane 21, an adjacent lane 22, a truck 23, and a millimeter wave radar 24, and the distribution characteristics of the reflection points of the truck 23 are related to the view angle between the millimeter wave radars 24. As shown in fig. 2a, when the truck 23 is in the adjacent lane 22 on the side of the millimeter wave radar 24, the reflection points of the truck 23 are concentrated on the irradiation surface side of the millimeter wave radar 24, and the density of the reflection points gradually decreases with increasing distance, and further the reflection points at the wheels are also concentrated. As shown in fig. 2b, when the truck 23 is located right in front of the lane 21 where the millimeter wave radar 24 is located, the reflection points are concentrated at two positions of the head and the tail of the truck 23, and there is a sporadic reflection point in the middle of the truck body due to the ground multipath effect.

In an embodiment, when the target detection device clusters the reflection points of the detection target according to the detection information of the detection target, the target detection device may obtain detection information of a plurality of reflection points of the detection target, and detect whether the detection information of the plurality of reflection points meets a first preset condition, and if so, the reflection points meeting the first preset condition may be clustered.

In some embodiments, the detection information includes distance information and velocity information of a reflection point of the detection target; the meeting of the first preset condition comprises the following steps: the distance information is within a preset distance threshold range, and the speed information is within a preset speed information threshold range. In some embodiments, the velocity information is determined by obtaining doppler bins for the reflection points. In certain embodiments, the distance information includes a longitudinal distance and a lateral distance; in some embodiments, the preset distance range includes a preset longitudinal distance range and a preset transverse distance range.

Taking an unmanned vehicle as an example, suppose the Doppler bin of the reflection point of the unmanned vehicle is Dbin_candiThe Doppler bin of the track of the unmanned vehicle is Dbin_trackThe longitudinal distance of the track of the unmanned vehicle is Ry_trackAnd a lateral distance Rx_trackThe longitudinal distance of the reflection point of the unmanned vehicle is Ry_candiAnd a lateral distance Rx_candiThen, the first preset condition that is satisfied may be as shown in the following formula (1):

wherein 1.2 in the formula (1)>Ry_track-Ry_candi>-7.0 represents that the longitudinal distance in the distance information satisfies a preset longitudinal distance range, | Rx_track-Rx_candi|<2.0 indicates that the lateral distance in the distance information satisfies a preset lateral distance range, | Dbin in the formula (1) since the velocity information is determined by the Doppler bin_track-Dbin_candi|<And 5 represents that the speed information is within a preset speed information threshold value range.

According to the embodiment of the invention, the reflecting points of the detection target are clustered by using the detection information of the detection target and the first preset condition, so that the accuracy and the effectiveness of clustering are improved, and preparation is made for improving the confidence coefficient of the detection target.

S103: and determining the confidence coefficient of the type of the detection target according to the number of the clustering reflection points and the track reflection intensity of the detection target.

In the embodiment of the present invention, the target detection device may determine the confidence of the type of the detection target according to the number of the cluster reflection points and the track reflection intensity of the detection target.

In an embodiment, when the target detection device determines the confidence level of the type of the detection target according to the number of the cluster reflection points and the track reflection intensity of the detection target, the number of the cluster reflection points may be obtained, and if the number of the cluster reflection points satisfies a second preset condition, the confidence level may be updated; and the target detection device may acquire the track reflection intensity of the detection target, and may update the confidence level if the track reflection intensity of the detection target satisfies a third preset condition.

In an embodiment, if the number of the clustering reflection points satisfies a second preset condition, the target detection device may determine that the confidence level is increased by a first preset value; and/or, if the number of the clustering reflection points does not satisfy a second preset condition, the target detection device may determine that the confidence is an original value. In some embodiments, the second preset condition is that the number of the clustered reflection points is greater than a preset number threshold.

In some embodiments, assuming that Cref represents the number of the cluster reflection points, the number of the cluster reflection points satisfying the second preset condition may be the number of the cluster reflection points Cref > 5. In other embodiments, the meeting of the second preset condition may also be that the number of the clustering reflection points is greater than other numerical values, and the embodiment of the present invention is not particularly limited.

In certain embodiments, it is assumed that Cref represents the number of the cluster reflection points, P_nRepresenting the current confidence of the detected object, P_n-1Represents the upper part of the detection targetA confidence level once, if the preset number threshold is 5 and the first preset value is 5, when the number of the clustering reflection points meets a second preset condition, the confidence level is updated according to the following formula (2):

as can be seen from formula (2), if the number of the cluster reflection points is greater than 5, the target detection device may determine that the confidence level is increased by 5, that is, P_n＝P_n-1+ 5; if the number of the clustering reflection points is not greater than 5, the target detection device may determine that the confidence is an original value, that is, P_n＝P_n-1。

For example, assuming that the number Cref of the cluster reflection points is 10, the last confidence P of the detected target _n-115, the number of the cluster reflection points is 10>5, a second preset condition is satisfied, so that the current confidence degree P of the detection target can be known according to the formula (2)_n＝15+5＝20。

For another example, assuming that the number Cref of the cluster reflection points is 4, the last confidence P of the detection target_n-15, the number of the clustering reflection points is 4<5, therefore, according to the above formula (2), the current confidence P of the detected object_n＝P_n-1＝5。

In some embodiments, when the target detection device detects that the track reflection intensity of the detection target meets a third preset condition and updates the confidence level, if the track reflection intensity of the detection target is detected to be greater than a first preset intensity threshold, the confidence level may be increased by a second preset value; and/or, if the track reflection intensity of the detection target is less than a second preset intensity threshold, the confidence may subtract a first preset value; and/or if the reflection intensity information of the detection target is between a first preset intensity threshold and a second preset intensity threshold, the confidence may be an original value.

In some embodiments, assume that the Power_trackRepresenting the track reflection intensity of the detected target, the Power_truckA first preset intensity threshold, Power, representative of said detection target_carAnd (3) representing a second preset intensity threshold, and if the first preset value is 5 and the second preset value is 2, updating the confidence coefficient according to the following formula (3) when the target detection device detects that the track reflection intensity of the detected target meets a third preset condition.

According to the formula (3), if the track reflection intensity of the detected target is greater than a first preset intensity threshold, Power is obtained_track>Power_truckThen the confidence may be increased by a second preset value, P_n+ 2; power if the track reflection intensity of the detection target is smaller than a second preset intensity threshold value_track<Power_carThen the confidence may be subtracted by a first predetermined value (P) to obtain_n-5)。

For example, assuming that the first preset value is 5, the second preset value is 2, and the current confidence level P is_n5, if the track reflection intensity of the detected target is greater than a first preset intensity threshold, the confidence level P is_nIncreasing 2 to 10, if the track reflection intensity of the detected target is less than a second preset intensity threshold, the confidence level P_nMinus 5 is 0. And if the reflection intensity information of the detection target is between a first preset intensity threshold value and a second preset intensity threshold value, the confidence coefficient is an original value of 5.

According to the embodiment of the invention, the confidence coefficient of the detection target is determined by utilizing the number of the clustering reflection points and the track reflection intensity of the detection target, so that the accuracy of the confidence coefficient can be improved, and the accuracy of judging the type of the detection target is improved.

S104: and determining the detection target to be a preset type according to the confidence coefficient of the type of the detection target.

In the embodiment of the present invention, the target detection device may determine that the detection target is a preset type according to the confidence of the type of the detection target.

In one embodiment, when determining that the detection target is a preset type according to the confidence of the type of the detection target, the target detection device may detect the same detection target multiple times, and determine the current confidence of the detection target according to the current reflection intensity of the detection target, the number of the clustered reflection points, and the previous confidence of the detection target, so as to determine that the detection target is the preset type according to the current confidence.

In some embodiments, if the current confidence is greater than a third preset value, the target detection device may determine that the detection target is a preset type. In certain embodiments, the preset type includes at least one of: trucks, cars, buses, container trucks.

For example, if the preset type is a truck and the third preset value corresponding to the truck is k, the current confidence P is calculated according to the above formula (2) and/or formula (3)_nIs equal to m, and m>k, the object detection device may determine that the detection object is a truck.

In an embodiment, the detection information of the detection target and the track reflection intensity of the detection target may be obtained through the methods of S101 and S102, and the reflection points of the detection target are clustered according to the detection information of the detection target to generate clustered reflection points, and the number of the clustered reflection points is determined. The target detection device may determine that the detection target is of a preset type according to the number of the clustering reflection points, and then according to the number of the clustering reflection points and the track reflection intensity of the detection target. Thereby reducing the time to identify the target. In the embodiment of the invention, the target detection equipment can acquire the detection information of the detection target and the track reflection intensity of the detection target, cluster the reflection points of the detection target according to the detection information of the detection target to generate clustered reflection points, and determine the number of the clustered reflection points. The target detection device may determine a confidence level of the type of the detection target according to the number of the clustered reflection points and the track reflection intensity of the detection target, so that the target detection device may determine that the detection target is a preset type according to the confidence level of the type of the detection target. By the implementation mode, the detection target can be adaptively identified, and the identification efficiency and accuracy of the detection target are improved.

Referring to fig. 3 in detail, fig. 3 is a schematic flowchart of another target detection method according to an embodiment of the present invention, where the method may be executed by a target detection device, where the target detection device is applied to a millimeter wave radar, and the millimeter wave radar is disposed on a movable platform. It should be noted that in this embodiment, the clustered reflection points may be determined by a method for determining clustered reflection points in the target detection method provided in the embodiment described in fig. 1. It is understood that the determination method of the clustered reflection points in the present embodiment includes, but is not limited to, this. For example, the reflection points are clustered according to their position-reflection intensity. The method of the embodiment of the invention is a schematic illustration for determining the length and the width of the detection target according to the position coordinates of the clustered reflection points, and comprises the following steps.

S301: and acquiring the clustering reflection point of the detection target, and acquiring the position coordinate of the clustering reflection point.

In the embodiment of the invention, the target detection equipment can acquire the clustering reflection points of the detection target and acquire the position coordinates of the clustering reflection points, wherein the position coordinates are determined and obtained based on a pre-established coordinate system. In some embodiments, the pre-established coordinate system may be a coordinate system established with an arbitrary position point of the detection target as an origin, and the embodiment of the present invention is not limited in particular. Taking an unmanned vehicle as an example, the pre-established coordinate system may be established by taking the foremost end of the vehicle head as an origin, the horizontal right direction of the vehicle head as an abscissa, and the direction from the vehicle head to the vehicle tail as an ordinate.

In some embodiments, the clustered reflection points are obtained by clustering and determining the reflection points of the detection target according to the detection information of the detection target. In certain embodiments, the detection information includes at least one of: and the speed information and the distance information of the reflection point of the detection target. The specific embodiments are as described above and will not be described herein.

S302: and determining the length and the width of the detection target according to the position coordinates of the clustering reflection points.

In the embodiment of the present invention, the target detection device may determine the length and the width of the detection target according to the position coordinates of the clustered reflection points.

In some embodiments, the location coordinates include lateral coordinates and longitudinal coordinates; the object detection apparatus may determine the length and width of the detection object from the lateral coordinate and the longitudinal coordinate.

In some embodiments, the object detection device may determine the length and the width of the current detection object according to the horizontal coordinate and the vertical coordinate of the clustered reflection point, and determine the length and the width of the detection object according to the length and the width of the current detection object and the length and the width of the last detection object.

In some embodiments, when the object detection apparatus determines the length and the width of the current detection object according to the horizontal coordinate and the vertical coordinate of the clustered reflection point, the object detection apparatus may determine the width of the current detection object according to the horizontal coordinate of the clustered reflection point and determine the length of the current detection object according to the vertical coordinate of the clustered reflection point.

In some embodiments, when determining the width of the current detection target according to the horizontal coordinate of the clustered reflection point, the target detection device may obtain a maximum value and a minimum value of the horizontal coordinate of the clustered reflection point, and determine that a difference between the maximum value and the minimum value of the horizontal coordinate of the clustered reflection point is the width of the current detection target.

In some embodiments, when the target detection device determines the length of the current detection target according to the longitudinal coordinate of the clustered reflection point, the target detection device may obtain a maximum value and a minimum value of the longitudinal coordinate of the clustered reflection point, and determine that a difference between the maximum value and the minimum value of the longitudinal coordinate of the clustered reflection point is the length of the current detection target.

In some embodiments, when the target detection device determines the length and the width of the current detection target according to the horizontal coordinate and the vertical coordinate of the clustered reflection point, the target detection device may determine the horizontal distance of the clustered reflection point according to the horizontal coordinate of the clustered reflection point, and determine the vertical distance of the clustered reflection point according to the vertical coordinate of the clustered reflection point.

Suppose X_iRepresents the lateral distance, Y, of the ith clustered reflection point_iRepresents the longitudinal distance of the ith cluster reflection point if Wtruck_nIndicating the width of the current detection target, Ltruck_nWhen the length of the current detection target is expressed, the calculation formula of the length and the width of the current detection target is shown in the following formula (4):

wherein, said max (X)_i) Represents the maximum value of the transverse coordinate, said min (X)_i) Represents the minimum value of the transverse coordinate, said max (Y)_i) Represents the maximum value of the longitudinal coordinate, said min (Y)_i) Representing the minimum value of the longitudinal coordinate. Taking the truck shown in fig. 5 as an example, fig. 5 is a schematic diagram of a coordinate system of the truck according to the embodiment of the present invention. Assuming that the origin of the pre-established coordinate system is at the central position 51 of the foremost end of the truck head, the horizontal right of the head is an abscissa, and the direction from the head to the parking space is an ordinate, if the minimum value of the lateral coordinates of the detected clustering reflection point 52 is-0.8 m, and the maximum value is 0.8, the lateral distance of the clustering reflection point 52 can be determined to be 0.8- (-0.8) or 1.6 m.

In some embodiments, when determining the length and width of the detection target according to the length and width of the current detection target and the length and width of the detection target detected last time, the target detection apparatus may obtain the length and width of the detection target detected last time, perform filtering processing on the length and width of the detection target according to the length and width of the current detection target and the length and width of the detection target detected last time, and determine the length and width of the detection target according to a result of the filtering processing.

In some embodiments, suppose Wtreck_n-1Ltruck for last detecting the width of the detection target_n-1For the last detection of the length of the detection target, if Wtruck_nIndicating the width of the current detection target, Ltruck_nRepresenting the length of the current detection target, the calculation formula of the length and the width of the current detection target may be as shown in the following formula (5):

for example, assume that the width Wtruck of the detection target was last detected_n-1Is 1.6m, and the length Ltruck of the detection target is detected last time_n-1If the detected distance is 4.6, the width 1.6 of the detected target detected last time and the length 4.6 of the detected target detected last time are substituted into the formula (5) to obtain Wtruck_nEqual to 1.6, Ltruck_nEqual to 4.6.

In an embodiment, after determining the length and the width of the detection target according to the position coordinates of the clustered reflection points, the target detection device may further detect whether other emission points acquired by the millimeter wave radar satisfy a fourth preset condition, if so, add the reflection points satisfying the fourth preset condition to the current clustered reflection points, and re-determine the length and the width of the detection target according to the position coordinates of the clustered reflection points.

In some embodiments, the fourth preset condition is satisfied, including: the difference between the longitudinal coordinates of the other reflection points and the current longitudinal coordinate of the clustered reflection point is greater than the current length of the detection target and smaller than a specified search distance; and the absolute value of the difference between the current horizontal coordinates of the clustering reflection point and the other reflection points is smaller than a first preset threshold value; the speed information of other reflection points is within a preset speed information threshold range; and the difference between the track reflection intensity of the detection target and the reflection intensity of other reflection points is greater than the energy envelope of the detection target; and the reflection intensity of the other reflection points is greater than a preset reflection intensity threshold value.

In some embodiments, assume L_expandIndicating a specified search distance, Ltruck_nRepresenting the length, Power, of the current detection target_trackRepresenting track reflection intensity, Power_candiRepresenting the reflection intensity of the reflection point, Power_{delta_cri}Representing the energy envelope, Dbin, of said detection target_candiDoppler bin, Dbin representing a reflection point_trackThe first preset threshold value of the doppler bin representing the track is 2, and the range of the preset speed information threshold value is a range smaller than 5, then the fourth preset condition may be as shown in the following formula (6):

in some embodiments, the energy envelope of the reflection points of the detection target includes a plurality of energy points, and the energy envelope and the distance satisfy a certain statistical rule. Taking fig. 4a as an example, fig. 4a is a schematic diagram of a relationship between an energy envelope and a distance according to an embodiment of the present invention, and it can be seen from fig. 4a that the strongest energy point is located closest to the millimeter wave radar, and energy of the remaining reflection points is located at the envelope or slightly lower than the envelope due to the effect of surface reflection.

Taking the relationship between energy and distance of the unmanned vehicle shown in fig. 4b as an example, fig. 4b is a schematic diagram illustrating the relationship between energy and distance of the unmanned vehicle provided by the embodiment of the present invention, and as shown in fig. 4b, the relationship between energy and distance of the unmanned vehicle includes the relationship between energy and distance of a truck and the relationship between energy and distance of a car. As can be seen from fig. 4b, the strongest point energy of the truck is greater than that of a normal vehicle at all distances.

In some embodiments, the specified search distance is calculated from the length of the detection target; in some embodiments, the specified search distance comprises a maximum length of the detection target. Wherein the specified search distance can be calculated by the following formula (7):

L_expand＝max(L_truck*1.5,40) (7)

for example, assume the length L of the detection target_truckAnd if the length is 5m, substituting the length of the detection target of 5m into the formula (7) to calculate that the specified search distance is 40.

By expanding the search range, the embodiment of the invention can redetermine the length and the width of the detection target if other clustering reflection points meeting the fourth preset condition exist on the flight path where the detection target is matched, thereby avoiding misjudgment of the type of the detection target, identifying the ultra-large detection target and improving the detection efficiency.

In some embodiments, after determining the length and the width of the detection target, the target detection device may further obtain position information of the detection target, and determine the designated center position of the detection target according to the position information and a preset position compensation value. In certain embodiments, the location information includes, but is not limited to, being determined from the lateral coordinates of the reflection point. In certain embodiments, the preset position compensation value includes, but is not limited to, a lateral position compensation value, wherein the preset position compensation value is provided by an empirical value.

Taking a truck as an example, assuming that the designated center position of the detection target is the center position of the head of the truck, X_centerIndicating the center position of the head, X_offsetRepresenting the lateral position compensation value, X_iAnd the horizontal coordinate of the ith clustering reflection point is represented, and n represents the number of the clustering reflection points. Then X_centerThe calculation formula may be as shown in the following formula (8):

wherein, the

Used for calculating the sum of the horizontal coordinates of the first clustering reflection point to the nth clustering reflection point.

According to the embodiment of the invention, through the implementation mode of determining the designated central position of the detection target, the position of the detection target can be adjusted, the problems of collision and the like caused by deviation of the detection target from a flight path are avoided, and the safety of the detection target is improved. The problem that the radar cannot estimate the position of the vehicle head accurately is solved.

In some embodiments, after determining the length and the width of the detection target, the target detection apparatus may further determine that the detection target is of a preset type according to the length and the width of the detection target. In certain embodiments, the preset type includes at least one of: trucks, cars, buses, container trucks.

In the embodiment of the invention, the target detection equipment can obtain the clustering reflection points of the detection target, obtain the position coordinates of the clustering reflection points, and determine the length and the width of the detection target according to the position coordinates of the clustering reflection points, so that the length and the width of the detection target can be more accurately and effectively determined, the ultra-large detection target can be identified, the type of the detection target can be more effectively judged, and the detection efficiency is improved. By determining the designated central position of the detection target, the problems of collision and the like caused by deviation of the detection target from the flight path are avoided, and the safety of the detection target is improved.

Referring to fig. 6, fig. 6 is a schematic structural diagram of a target detection device according to an embodiment of the present invention, where the device includes a memory 601, a processor 602, and a data interface 603;

the memory 601 may include a volatile memory (volatile memory); the memory 601 may also include a non-volatile memory (non-volatile memory); the memory 601 may also comprise a combination of memories of the kind described above. The processor 602 may be a Central Processing Unit (CPU). The processor 602 may further include a hardware chip. The hardware chip may be an application-specific integrated circuit (ASIC), a Programmable Logic Device (PLD), or a combination thereof. The PLD may be a Complex Programmable Logic Device (CPLD), a field-programmable gate array (FPGA), or any combination thereof.

The processor 602 is configured to invoke the program instructions, and when the program instructions are executed, the processor is configured to:

Further, the detection information at least includes one of the following: and the speed information and the distance information of the reflection point of the detection target.

Further, the number of reflection points of the detection target is plural.

Further, before acquiring the detection information of the detection target and the track reflection intensity of the detection target, the processor 602 is further configured to:

and detecting the detection target and recording the flight path of the detection target.

Further, when the processor 602 performs clustering on the reflection point of the detection target according to the detection information of the detection target, the method is specifically configured to:

acquiring detection information of a plurality of reflection points of the detection target;

detecting whether the detection information of the plurality of reflection points meets a first preset condition or not;

and if so, clustering the reflection points meeting the first preset condition.

Further, when the processor 602 determines the confidence of the type of the detection target according to the number of the clustered reflection points and the reflection intensity information of the detection target, the processor is specifically configured to:

acquiring the number of the clustering reflection points, and updating the confidence coefficient if the number of the clustering reflection points meets a second preset condition;

and acquiring the track reflection intensity of the detection target, and updating the confidence coefficient if the track reflection intensity of the detection target meets a third preset condition.

Further, the processor 602 is specifically configured to:

if the number of the clustering reflection points meets a second preset condition, determining that the confidence coefficient is increased by a first preset value; and/or the presence of a gas in the gas,

and if the number of the clustering reflection points does not meet a second preset condition, determining the confidence coefficient as an original value.

Further, the detection information includes distance information and speed information of a reflection point of the detection target;

the meeting of the first preset condition comprises the following steps: the distance information is within a preset distance threshold range, and the speed information is within a preset speed information threshold range.

Further, the speed information is determined by acquiring a doppler frequency point of the reflection point.

Further, the second preset condition means that the number of the clustered reflection points is greater than a preset number threshold.

Further, if the track reflection intensity of the detection target meets a third preset condition, the processor 602 is specifically configured to, when updating the confidence level:

if the track reflection intensity of the detection target is greater than a first preset intensity threshold value, increasing a first preset value by the confidence coefficient; and/or the presence of a gas in the gas,

if the track reflection intensity of the detection target is smaller than a second preset intensity threshold value, subtracting a second preset value from the confidence coefficient; and/or the presence of a gas in the gas,

and if the reflection intensity information of the detection target is between a first preset intensity threshold value and a second preset intensity threshold value, the confidence coefficient is an original value.

Further, the third preset condition is that the reflection intensity information is greater than a preset reflection intensity threshold.

Further, when determining that the detection target is a preset type according to the confidence of the type of the detection target, the processor 602 is specifically configured to:

detecting the same detection target for multiple times;

determining the current confidence of the detection target according to the current reflection intensity and the number of the clustering reflection points of the detection target and the last confidence of the detection target;

and determining the detection target to be a preset type according to the current confidence.

Further, when determining the type of the detection target according to the current confidence, the processor 602 is specifically configured to:

and if the current confidence coefficient is greater than a third preset value, determining that the detection target is a preset type.

Further, the preset type includes at least one of: trucks, cars, buses, container trucks.

In the embodiment of the invention, the target detection equipment can acquire the detection information of the detection target and the track reflection intensity of the detection target, cluster the reflection points of the detection target according to the detection information of the detection target to generate clustered reflection points, and determine the number of the clustered reflection points. The target detection device may determine a confidence level of the type of the detection target according to the number of the clustered reflection points and the track reflection intensity of the detection target, so that the target detection device may determine that the detection target is a preset type according to the confidence level of the type of the detection target. By the implementation mode, the detection target can be adaptively identified, and the identification efficiency and accuracy of the detection target are improved.

Referring to fig. 7, fig. 7 is a schematic structural diagram of another target detection device according to an embodiment of the present invention, where the device includes a memory 701, a processor 702, and a data interface 703;

the memory 701 may include a volatile memory (volatile memory); the memory 701 may also include a non-volatile memory (non-volatile memory); the memory 701 may also comprise a combination of memories of the kind described above. The processor 702 may be a Central Processing Unit (CPU). The processor 702 may further include a hardware chip. The hardware chip may be an application-specific integrated circuit (ASIC), a Programmable Logic Device (PLD), or a combination thereof. The PLD may be a Complex Programmable Logic Device (CPLD), a field-programmable gate array (FPGA), or any combination thereof.

The processor 702 is configured to invoke the program instructions, and when the program instructions are executed, to:

Further, the clustered reflection points are obtained by clustering and determining the reflection points of the detection target according to the detection information of the detection target.

Further, the position coordinates include lateral coordinates and longitudinal coordinates; the processor 702 is specifically configured to, when determining the length and the width of the detection target according to the position coordinates of the clustered reflection points:

and determining the length and the width of the detection target according to the transverse coordinate and the longitudinal coordinate.

Further, the processor 702 is specifically configured to:

determining the length and the width of the current detection target according to the horizontal coordinate and the longitudinal coordinate of the clustering reflection point;

and determining the length and the width of the detection target according to the length and the width of the current detection target and the length and the width of the last detection target.

Further, when determining the length and the width of the detection target according to the length and the width of the current detection target and the length and the width of the last detection target, the processor 702 is specifically configured to:

acquiring the length and the width obtained by detecting the detection target at the last time;

carrying out filtering processing on the length and the width of the detection target according to the length and the width of the current detection target and the length and the width of the last detection target;

and determining the length and the width of the detection target according to the result of the filtering processing.

Further, when determining the length and the width of the current detection target according to the horizontal coordinate and the vertical coordinate of the clustered reflection point, the processor 702 is specifically configured to:

determining the width of the current detection target according to the transverse coordinates of the clustering reflection points;

and determining the length of the current detection target according to the longitudinal coordinate of the clustering reflection point.

Further, when the processor 702 determines the width of the current detection target according to the horizontal coordinate of the clustered reflection point, the processor is specifically configured to:

acquiring the maximum value and the minimum value of the horizontal coordinate of the clustering reflection point;

and determining the difference between the maximum value and the minimum value of the horizontal coordinates of the clustered reflection points as the width of the current detection target.

Further, when determining the length of the current detection target according to the longitudinal coordinate of the clustered reflection point, the processor 702 is specifically configured to:

acquiring the maximum value and the minimum value of the longitudinal coordinate of the clustering reflection point;

and determining the difference between the maximum value and the minimum value of the longitudinal coordinate of the clustering reflection point as the length of the current detection target.

Further, after determining the length and the width of the detection target according to the position coordinates of the clustered reflection points, the processor 702 is further configured to:

detecting whether other transmitting points acquired by the millimeter wave radar meet a fourth preset condition or not;

and if so, adding the reflection points meeting the fourth preset condition into the current clustering reflection points, and re-determining the length and the width of the detection target according to the position coordinates of the clustering reflection points.

Further, the satisfying of the fourth preset condition includes:

the difference between the longitudinal coordinates of the other reflection points and the current longitudinal coordinate of the clustered reflection point is greater than the current length of the detection target and smaller than a specified search distance;

and the absolute value of the difference between the current horizontal coordinates of the clustering reflection point and the other reflection points is smaller than a first preset threshold value;

the speed information of other reflection points is within a preset speed information threshold range;

and the difference between the track reflection intensity of the detection target and the reflection intensity of other reflection points is greater than the energy envelope of the detection target;

and the reflection intensity of the other reflection points is greater than a preset reflection intensity threshold value.

Further, the specified search distance is calculated according to the length of the detection target.

Further, the specified search distance includes a maximum length of the detection target.

Further, after determining the length and the width of the detection target, the processor 702 is further configured to:

acquiring position information of the detection target;

and determining the designated central position of the detection target according to the position information and a preset position compensation value.

and determining the detection target to be a preset type according to the length and the width of the detection target.

In the embodiment of the invention, the target detection equipment can acquire the clustering reflection points of the detection target, acquire the position coordinates of the clustering reflection points, and determine the length and the width of the detection target according to the position coordinates of the clustering reflection points. By the embodiment, the length and the width of the detection target can be determined more accurately and effectively so as to judge the type of the detection target more effectively.

An embodiment of the present invention provides a millimeter wave radar, including: the antenna is used for acquiring echo signals; a processor communicatively coupled to the antenna, the processor configured to:

Further, the number of reflection points of the detection target is plural.

Further, before acquiring the detection information of the detection target and the track reflection intensity of the detection target, the processor is further configured to:

Further, when the processor clusters the reflection point of the detection target according to the detection information of the detection target, the processor is specifically configured to:

and if so, clustering the reflection points meeting the first preset condition.

Further, when the processor determines the confidence of the type of the detection target according to the number of the clustered reflection points and the reflection intensity information of the detection target, the processor is specifically configured to:

Further, the processor is specifically configured to:

Further, if the track reflection intensity of the detection target meets a third preset condition, the processor is specifically configured to, when updating the confidence level:

Further, when determining that the detection target is a preset type according to the confidence of the type of the detection target, the processor is specifically configured to:

detecting the same detection target for multiple times;

Further, when determining the type of the detection target according to the current confidence, the processor is specifically configured to:

In the embodiment of the invention, the millimeter wave radar can acquire the detection information of the detection target and the track reflection intensity of the detection target, cluster the reflection points of the detection target according to the detection information of the detection target to generate clustered reflection points, and determine the number of the clustered reflection points. The target detection device may determine a confidence level of the type of the detection target according to the number of the clustered reflection points and the track reflection intensity of the detection target, so that the target detection device may determine that the detection target is a preset type according to the confidence level of the type of the detection target. By the implementation mode, the detection target can be adaptively identified, and the identification efficiency and accuracy of the detection target are improved.

An embodiment of the present invention further provides another millimeter wave radar, including: the antenna is used for acquiring echo signals; a processor communicatively coupled to the antenna, the processor configured to:

Further, the position coordinates include lateral coordinates and longitudinal coordinates; when the processor determines the length and the width of the detection target according to the position coordinates of the clustered reflection points, the processor is specifically configured to:

Further, the processor is specifically configured to:

Further, when determining the length and the width of the detection target according to the length and the width of the current detection target and the length and the width of the last detection target, the processor is specifically configured to:

Further, when determining the length and the width of the current detection target according to the horizontal coordinate and the vertical coordinate of the clustered reflection point, the processor is specifically configured to:

Further, when determining the width of the current detection target according to the horizontal coordinate of the clustered reflection point, the processor is specifically configured to:

Further, when determining the length of the current detection target according to the longitudinal coordinate of the clustered reflection point, the processor is specifically configured to:

Further, after determining the length and the width of the detection target according to the position coordinates of the clustered reflection points, the processor is further configured to:

Further, the satisfying of the fourth preset condition includes:

Further, after determining the length and the width of the detection target, the processor is further configured to:

acquiring position information of the detection target;

In the embodiment of the invention, the millimeter wave radar can acquire the clustering reflection points of the detection target, acquire the position coordinates of the clustering reflection points, and determine the length and the width of the detection target according to the position coordinates of the clustering reflection points. By the embodiment, the length and the width of the detection target can be determined more accurately and effectively so as to judge the type of the detection target more effectively.

An embodiment of the present invention provides a movable platform, including: a body; the power system is arranged on the movable platform and used for providing moving power for the movable platform;

the processor is used for acquiring detection information of a detection target and track reflection intensity of the detection target; clustering the reflection points of the detection target according to the detection information of the detection target to generate clustered reflection points, and determining the number of the clustered reflection points; determining the confidence coefficient of the type of the detection target according to the number of the clustering reflection points and the track reflection intensity of the detection target; and determining the detection target to be a preset type according to the confidence coefficient of the type of the detection target.

Further, the number of reflection points of the detection target is plural.

and if so, clustering the reflection points meeting the first preset condition.

Further, the processor is specifically configured to:

detecting the same detection target for multiple times;

In the embodiment of the invention, the movable platform can acquire the detection information of the detection target and the track reflection intensity of the detection target, and cluster the reflection points of the detection target according to the detection information of the detection target to generate clustered reflection points and determine the number of the clustered reflection points. The target detection device may determine a confidence level of the type of the detection target according to the number of the clustered reflection points and the track reflection intensity of the detection target, so that the target detection device may determine that the detection target is a preset type according to the confidence level of the type of the detection target. By the implementation mode, the detection target can be adaptively identified, and the identification efficiency and accuracy of the detection target are improved.

An embodiment of the present invention further provides another movable platform, including: a body; the power system is arranged on the movable platform and used for providing moving power for the movable platform;

the processor is used for acquiring a clustering reflection point of a detection target and acquiring a position coordinate of the clustering reflection point, wherein the position coordinate is determined and obtained based on a pre-established coordinate system; and determining the length and the width of the detection target according to the position coordinates of the clustering reflection points.

Further, the processor is specifically configured to:

Further, the satisfying of the fourth preset condition includes:

acquiring position information of the detection target;

In the embodiment of the invention, the movable platform can acquire the clustering reflection points of the detection target, acquire the position coordinates of the clustering reflection points, and determine the length and the width of the detection target according to the position coordinates of the clustering reflection points. By the embodiment, the length and the width of the detection target can be determined more accurately and effectively so as to judge the type of the detection target more effectively.

The embodiment of the present invention further provides a computer-readable storage medium, where a computer program is stored, and when the computer program is executed by a processor, the method described in the embodiment of the present invention is implemented, and also the device corresponding to the embodiment of the present invention may be implemented, which is not described herein again.

The computer readable storage medium may be an internal storage unit of the device according to any of the foregoing embodiments, for example, a hard disk or a memory of the device. The computer readable storage medium may also be an external storage device of the device, such as a plug-in hard disk, a Smart Media Card (SMC), a Secure Digital (SD) Card, a Flash memory Card (Flash Card), etc. provided on the device. Further, the computer-readable storage medium may also include both an internal storage unit and an external storage device of the apparatus. The computer-readable storage medium is used for storing the computer program and other programs and data required by the terminal. The computer readable storage medium may also be used to temporarily store data that has been output or is to be output.

The above disclosure is intended to be illustrative of only some embodiments of the invention, and is not intended to limit the scope of the invention.

Claims

1. A target detection method is applied to a millimeter wave radar, and is characterized by comprising the following steps:

2. The method of claim 1, wherein the detection information comprises at least one of: and the speed information and the distance information of the reflection point of the detection target.

3. The method according to claim 1, wherein the reflection point of the detection target is plural.

4. The method of claim 1, wherein before the obtaining the detection information of the detected object and the track reflection intensity of the detected object, further comprises:

5. The method according to claim 3, wherein the clustering the reflection points of the detection targets according to the detection information of the detection targets comprises:

and if so, clustering the reflection points meeting the first preset condition.

6. The method of claim 5, wherein determining the confidence level of the type of the detection target according to the number of the clustered reflection points and the reflection intensity information of the detection target comprises:

7. The method of claim 6, comprising:

8. The method of claim 5,

the detection information comprises distance information and speed information of a reflection point of the detection target;

9. The method of claim 8, wherein the velocity information is determined by obtaining doppler bins for the reflection points.

10. The method of claim 6,

the second preset condition means that the number of the clustering reflection points is greater than a preset number threshold.

11. The method according to claim 6, wherein the updating the confidence level if the track reflection intensity of the detected target satisfies a third preset condition comprises:

if the track reflection intensity of the detection target is greater than a first preset intensity threshold value, increasing a second preset value to the confidence coefficient; and/or the presence of a gas in the gas,

if the track reflection intensity of the detection target is smaller than a second preset intensity threshold value, subtracting a first preset value from the confidence coefficient; and/or the presence of a gas in the gas,

12. The method according to claim 11, wherein the third predetermined condition is that the reflection intensity information is greater than a predetermined threshold value of reflection intensity.

13. The method according to claim 1, wherein the determining the detection target as a preset type according to the confidence of the type of the detection target comprises:

detecting the same detection target for multiple times;

14. The method of claim 13, wherein determining the type of the detection target based on the current confidence level comprises:

15. The method of claim 1, wherein the preset type comprises at least one of: trucks, cars, buses, container trucks.

16. A target detection method is applied to a millimeter wave radar, and is characterized by comprising the following steps:

17. The method according to claim 16, wherein the clustered reflection points are determined by clustering the reflection points of the detection targets according to the detection information of the detection targets.

18. The method of claim 17, wherein the detection information comprises at least one of: and the speed information and the distance information of the reflection point of the detection target.

19. The method of claim 16, wherein the position coordinates include lateral coordinates and longitudinal coordinates; determining the length and the width of the detection target according to the position coordinates of the clustered reflection points, including:

20. The method of claim 19, wherein the method comprises:

21. The method of claim 20, wherein determining the length and width of the detection target according to the length and width of the current detection target and the length and width of the last detection target comprises:

22. The method of claim 20, wherein the determining the length and the width of the current detection target according to the horizontal coordinate and the vertical coordinate of the clustered reflection point comprises:

23. The method of claim 22, wherein determining the width of the current detection target according to the lateral coordinates of the clustered reflection points comprises:

24. The method of claim 22, wherein determining the length of the current detection target according to the longitudinal coordinate of the clustered reflection point comprises:

25. The method according to claim 16, wherein after determining the length and the width of the detection target according to the position coordinates of the clustered reflection points, the method further comprises:

26. The method according to claim 25, wherein said fourth preset condition is satisfied, comprising:

27. The method of claim 26,

the specified search distance is calculated according to the length of the detection target.

28. The method of claim 27, wherein the specified search distance comprises a maximum length of the detection target.

29. The method of claim 16, wherein after determining the length and the width of the detection target, further comprising:

acquiring position information of the detection target;

30. The method of claim 16, wherein after determining the length and the width of the detection target, further comprising:

31. The method of claim 30, wherein the preset type comprises at least one of: trucks, cars, buses, container trucks.

32. An object detection device applied to a millimeter wave radar, comprising: one or more processors, working collectively or individually, the processors being configured to:

33. The apparatus of claim 32, wherein the detection information comprises at least one of: and the speed information and the distance information of the reflection point of the detection target.

34. The apparatus of claim 32, wherein the detection target has a plurality of reflection points.

35. The apparatus of claim 32, wherein the processor, prior to obtaining detection information of a detected object and the track reflection intensity of the detected object, is further configured to:

36. The apparatus according to claim 34, wherein the processor is configured to, when clustering the reflection points of the detection target according to the detection information of the detection target, specifically:

and if so, clustering the reflection points meeting the first preset condition.

37. The apparatus according to claim 36, wherein the processor is configured to, when determining the confidence level of the type of the detection target according to the number of the clustered reflection points and the reflection intensity information of the detection target, specifically:

38. The device of claim 37, wherein the processor is specifically configured to:

39. The apparatus of claim 36,

40. The apparatus of claim 39, wherein the velocity information is determined by obtaining Doppler frequency bins for the reflection points.

41. The apparatus of claim 37,

42. The apparatus according to claim 37, wherein if the track reflection intensity of the detected target satisfies a third preset condition, the processor is specifically configured to:

43. The apparatus according to claim 42, wherein the third predetermined condition is that the reflection intensity information is greater than a predetermined threshold value of reflection intensity.

44. The device according to claim 32, wherein the processor, when determining that the detection target is of a preset type according to the confidence of the type of the detection target, is specifically configured to:

detecting the same detection target for multiple times;

45. The device according to claim 44, wherein the processor, when determining the type of the detection target according to the current confidence level, is specifically configured to:

46. The apparatus of claim 32, wherein the preset type comprises at least one of: trucks, cars, buses, container trucks.

47. A target detection device is applied to a millimeter wave radar and is characterized in that the millimeter wave radar can acquire reflection intensity information of a detection target and the number of clustering reflection points, and the confidence of the detection target is determined according to the reflection intensity information and the number of the clustering reflection points; the apparatus includes one or more processors, working collectively or individually, to perform the following operations:

48. The apparatus of claim 47, wherein the clustered reflection points are determined by clustering the reflection points of the detection targets according to the detection information of the detection targets.

49. The apparatus of claim 48, wherein the detection information comprises at least one of: and the speed information and the distance information of the reflection point of the detection target.

50. The apparatus of claim 47, wherein the position coordinates comprise a lateral coordinate and a longitudinal coordinate; when the processor determines the length and the width of the detection target according to the position coordinates of the clustered reflection points, the processor is specifically configured to:

51. The device of claim 50, wherein the processor is specifically configured to:

52. The apparatus of claim 51, wherein the processor is configured to, when determining the length and the width of the detection target according to the length and the width of the current detection target and the length and the width of the last detection target, specifically:

53. The apparatus according to claim 51, wherein the processor is configured to, when determining the length and the width of the current detection target according to the horizontal coordinate and the vertical coordinate of the clustered reflection point, specifically:

54. The apparatus according to claim 53, wherein the processor, when determining the width of the current detection target according to the horizontal coordinates of the clustered reflection points, is specifically configured to:

55. The apparatus according to claim 53, wherein the processor, when determining the length of the current detection target according to the longitudinal coordinate of the clustered reflection point, is specifically configured to:

56. The apparatus of claim 47, wherein the processor, after determining the length and the width of the detection target according to the position coordinates of the clustered reflection points, is further configured to:

57. The apparatus according to claim 56, wherein said fourth preset condition is met, comprising:

58. The apparatus of claim 57,

59. The apparatus of claim 58, wherein the specified search distance comprises a maximum length of the detection target.

60. The device of claim 47, wherein the processor, after determining the length and width of the detection target, is further configured to:

acquiring position information of the detection target;

61. The device of claim 47, wherein the processor, after determining the length and width of the detection target, is further configured to:

62. The apparatus according to claim 61, wherein the preset type comprises at least one of: trucks, cars, buses, container trucks.

63. A millimeter wave radar, comprising:

the antenna is used for acquiring echo signals;

64. The millimeter wave radar according to claim 63, wherein the detection information includes at least one of: and the speed information and the distance information of the reflection point of the detection target.

65. The millimeter wave radar according to claim 63, wherein a reflection point of the detection target is plural.

66. The millimeter wave radar of claim 63, wherein the processor, prior to obtaining detection information for a detected target and the track reflection intensity for the detected target, is further configured to:

67. The millimeter wave radar according to claim 65, wherein the processor is configured to, when clustering the reflection points of the detection target according to the detection information of the detection target, specifically:

and if so, clustering the reflection points meeting the first preset condition.

68. The mmwave radar of claim 67, wherein the processor, when determining the confidence level of the type of the detection target according to the number of the clustered reflection points and the reflection intensity information of the detection target, is specifically configured to:

69. The millimeter-wave radar of claim 68, wherein the processor is specifically configured to:

70. The millimeter wave radar of claim 67,

71. The millimeter wave radar of claim 70, wherein the velocity information is determined by obtaining Doppler bins for the reflection points.

72. The millimeter wave radar of claim 68,

73. The millimeter wave radar according to claim 68, wherein if the track reflection intensity of the detected target satisfies a third preset condition, the processor is specifically configured to, when updating the confidence level:

74. The millimeter wave radar according to claim 73, wherein the third preset condition is that the reflection intensity information is greater than a preset reflection intensity threshold.

75. The millimeter wave radar according to claim 63, wherein the processor, when determining that the detection target is of a preset type according to the confidence level of the type of the detection target, is specifically configured to:

detecting the same detection target for multiple times;

76. The millimeter wave radar according to claim 75, wherein the processor, when determining the type of the detection target according to the current confidence level, is specifically configured to:

77. The millimeter wave radar of claim 63, wherein the preset type includes at least one of: trucks, cars, buses, container trucks.

78. A millimeter wave radar, comprising:

the antenna is used for acquiring echo signals;

79. The millimeter wave radar according to claim 78, wherein the clustered reflection points are determined by clustering the reflection points of the detection targets based on the detection information of the detection targets.

80. The millimeter wave radar according to claim 79, wherein the detection information includes at least one of: and the speed information and the distance information of the reflection point of the detection target.

81. The millimeter wave radar of claim 78, wherein the position coordinates include lateral coordinates and longitudinal coordinates; when the processor determines the length and the width of the detection target according to the position coordinates of the clustered reflection points, the processor is specifically configured to:

82. The millimeter wave radar of claim 81, wherein the processor is specifically configured to:

83. The millimeter wave radar according to claim 82, wherein the processor, when determining the length and width of the detection target based on the length and width of the detection target at the present time and the length and width of the detection target detected last time, is specifically configured to:

84. The millimeter wave radar according to claim 82, wherein the processor, when determining the length and width of the current detection target according to the horizontal coordinate and the vertical coordinate of the clustered reflection point, is specifically configured to:

85. The millimeter-wave radar according to claim 84, wherein the processor, when determining the width of the current detection target according to the lateral coordinates of the clustered reflection points, is specifically configured to:

86. The millimeter wave radar according to claim 84, wherein the processor, when determining the length of the current detection target according to the longitudinal coordinate of the clustered reflection point, is specifically configured to:

87. The millimeter wave radar of claim 78, wherein the processor, after determining the length and width of the detection target according to the position coordinates of the clustered reflection points, is further configured to:

88. The millimeter wave radar of claim 87, wherein the satisfaction of the fourth preset condition comprises:

89. The millimeter wave radar of claim 88,

90. The millimeter wave radar of claim 89, wherein the specified search distance comprises a maximum length of the detection target.

91. The millimeter wave radar of claim 78, wherein the processor, after determining the length and width of the detection target, is further configured to:

acquiring position information of the detection target;

92. The millimeter wave radar of claim 78, wherein the processor, after determining the length and width of the detection target, is further configured to:

93. The millimeter wave radar of claim 92, wherein the preset type comprises at least one of: trucks, cars, buses, container trucks.

94. A movable platform, comprising:

a body;

the apparatus of claims 32-62.

95. A computer-readable storage medium, in which a computer program is stored which, when being executed by a processor, carries out the method according to any one of claims 1 to 31.