CN117077407B - Target detection method and device - Google Patents
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Abstract
The invention discloses a target detection method and a target detection device, wherein the method comprises the following steps: acquiring detection attribute information corresponding to a detection unit, object attribute information corresponding to a detection object and current simulation time; the detection attribute information comprises a detection radius value, a detection period, detection unit equipment information and detection unit coordinates; the object attribute information includes object coordinates and object heights; based on the attribute information of the detection unit and the current simulation time, respectively carrying out static detection analysis and dynamic detection analysis on the detection object to obtain static detection information and dynamic detection information; analyzing and processing the object height, static detection information and dynamic detection information to obtain target detection result information; the target detection result information characterizes the detectable recognition condition of the detection unit on the detection object. Therefore, the method and the device are beneficial to simplifying the detection flow, shortening the detection time length and further improving the detection efficiency.
Description
Technical Field
The present invention relates to the field of detection technologies, and in particular, to a method and an apparatus for detecting a target.
Background
Along with the development and progress of society, informatization and data formation become main trends of various industries, and analog simulation is also one of important fields. In the traditional simulation process, the detection system can complete detection requirements to various degrees according to model requirements, and sensor digitization is achieved. However, the detection function is only completed and cannot be accepted by the large-scale simulation combat scene, and the traditional detection system has the problems of redundant detection flow and long detection time, so that the operation efficiency of the large-scale simulation combat scene is affected to a certain extent, unnecessary burden is brought to a computer, and the detection flow is optimized and the detection efficiency is improved. Therefore, the target detection method and device are provided, so that the detection flow is simplified, the detection time is shortened, and the detection efficiency is further improved.
Disclosure of Invention
The technical problem to be solved by the invention is to provide the target detection method and the device which are beneficial to simplifying the detection flow, shortening the detection time length and further improving the detection efficiency.
In order to solve the above technical problems, a first aspect of an embodiment of the present invention discloses a target detection method, where the method includes:
acquiring detection attribute information corresponding to a detection unit, object attribute information corresponding to a detection object and current simulation time; the detection attribute information comprises a detection radius value, a detection period, detection unit equipment information and detection unit coordinates; the object attribute information comprises object coordinates and object heights;
based on the attribute information of the detection unit and the current simulation time, respectively carrying out static detection analysis and dynamic detection analysis on the detection object to obtain static detection information and dynamic detection information;
analyzing and processing the object height, the static detection information and the dynamic detection information to obtain target detection result information; the target detection result information characterizes the detectable recognition condition of the detection unit on the detection object.
In a first aspect of the embodiment of the present invention, the performing static and dynamic detection analysis on the detection object based on the attribute information of the detection unit and the current simulation time to obtain static detection information and dynamic detection information includes:
Determining detection range attribute information based on the detection unit attribute information; the detection range attribute information comprises N first fan-shaped areas and M second fan-shaped areas; the M is 2 times of the N;
determining dynamic detection information based on the object attribute information and the detection range attribute information;
and determining static detection information based on the detection range attribute information and the current simulation time.
As an optional implementation manner, in the first aspect of the embodiment of the present invention, the determining, based on the detection unit attribute information, detection range attribute information includes:
determining a first detection area and a second detection area based on the detection radius value; the first detection area is a circular area constructed by taking one half of the detection radius value as a radius; the second detection area is a closed annular area with the first detection area removed from a circular area constructed by taking the detection radius value as a radius;
equally dividing the first detection area by a first radian to obtain the N first initial sector areas;
sequentially numbering the N first initial sector areas clockwise according to a first numbering format by taking the forward direction of the Y axis as a starting point to obtain N first sector areas;
Equally dividing the second detection areas by a second radian to obtain M second initial sector areas;
and numbering the M second initial sector areas clockwise according to a second numbering format by taking the Y-axis forward direction as a starting point to obtain the M second sector areas.
As an optional implementation manner, in the first aspect of the embodiment of the present invention, the determining dynamic probe information based on the object attribute information and the probe range attribute information includes:
calculating the coordinates of the detection unit and the object attribute information by using a first detection model to obtain a first detection value;
wherein, the first detection model is:
wherein TC1 is the first probe value; (x, y, z) is the detection unit coordinates; (x 1, y1, z 1) is an object coordinate in the object attribute information;
judging whether the first detection value is smaller than or equal to the detection radius value or not to obtain a first dynamic judgment result;
when the first dynamic judgment result is negative, determining that the dynamic detection information is that the dynamic detection does not pass;
when the first dynamic judgment result is yes, determining a second detection value based on the detection unit equipment information;
Judging whether the second detection value is larger than the first detection value or not to obtain a second dynamic judgment result;
when the second dynamic judgment result is negative, determining that the dynamic detection information is that the dynamic detection does not pass;
when the second dynamic judgment result is yes, acquiring field area information;
judging whether the coordinate of the detection unit is positioned in the field area information or not to obtain a third dynamic judgment result;
when the third dynamic judgment result is negative, determining that the dynamic detection information is that the dynamic detection does not pass;
and when the third dynamic judgment result is yes, determining that the dynamic detection information is the dynamic detection passing.
As an optional implementation manner, in the first aspect of the embodiment of the present invention, the determining, based on the detection unit device information, a second detection value includes:
calculating the detection unit equipment information by using a second detection model to obtain a detection power value;
wherein the second detection model is:
in the method, in the process of the invention,the detected power value; j is the interference power in the detection unit equipment information, K is the suppression coefficient in the detection unit equipment information;
Calculating the detection unit equipment information and the detection power value by using a third detection model to obtain a second detection value;
wherein the third detection model is:
wherein R' is the second detection value; p (P) t Transmitting power in the equipment information of the detection unit; g is the gain in the detection unit equipment information; sigma is the echo area in the detection unit equipment information; lambda is the electromagnetic wavelength in the detection unit device information.
In a first aspect of the embodiment of the present invention, the analyzing the object height, the static detection information, and the dynamic detection information to obtain target detection result information includes:
judging whether the dynamic detection information is that the dynamic detection fails or not, and obtaining a fourth dynamic judgment result;
when the fourth dynamic judgment result is yes, determining that the target detection result information is the target and cannot be detected;
when the fourth dynamic judgment result is negative, determining target static detection information based on the detection unit coordinates, the object coordinates and the static detection information;
judging whether the terrain height in the target static detection information is smaller than the object height or not to obtain a first static judgment result;
When the first static judgment result is negative, determining that the target detection result information is undetectable;
when the first static judgment result is yes, judging whether the curvature value in the target static detection information is smaller than the object height, and obtaining a second static judgment result;
when the second static judgment result is negative, determining that the target detection result information is undetectable;
and when the second static judgment result is yes, determining that the target detection result information is that the target is detectable.
As an optional implementation manner, in the first aspect of the embodiment of the present invention, the determining, based on the detection unit coordinates, the object coordinates, and the static detection information, target static detection information includes:
determining coordinate azimuth information based on the detection unit coordinates and the object coordinates;
and determining static detection information of the target based on the coordinate azimuth information and the detection range attribute information.
The second aspect of the embodiment of the invention discloses a target detection device, which comprises:
the acquisition module is used for acquiring the detection attribute information corresponding to the detection unit, the object attribute information corresponding to the detection object and the current simulation time; the detection attribute information comprises a detection radius value, a detection period, detection unit equipment information and detection unit coordinates; the object attribute information comprises object coordinates and object heights;
The analysis module is used for respectively carrying out static detection analysis and dynamic detection analysis on the detection object based on the detection unit attribute information and the current simulation time to obtain static detection information and dynamic detection information;
the processing module is used for analyzing and processing the object height, the static detection information and the dynamic detection information to obtain target detection result information; the target detection result information characterizes the detectable recognition condition of the detection unit on the detection object.
In a third aspect, the invention discloses another object detection device, said device comprising:
a memory storing executable program code;
a processor coupled to the memory;
the processor invokes the executable program code stored in the memory to perform some or all of the steps in the object detection method disclosed in the first aspect of the embodiment of the present invention.
A fourth aspect of the present invention discloses a computer readable storage medium storing computer instructions which, when called, are adapted to perform part or all of the steps in the object detection method disclosed in the first aspect of the embodiments of the present invention.
Compared with the prior art, the embodiment of the invention has the following beneficial effects:
in the embodiment of the invention, detection attribute information corresponding to a detection unit, object attribute information corresponding to a detection object and current simulation time are acquired; the detection attribute information comprises a detection radius value, a detection period, detection unit equipment information and detection unit coordinates; the object attribute information includes object coordinates and object heights; based on the attribute information of the detection unit and the current simulation time, respectively carrying out static detection analysis and dynamic detection analysis on the detection object to obtain static detection information and dynamic detection information; analyzing and processing the object height, static detection information and dynamic detection information to obtain target detection result information; the target detection result information characterizes the detectable recognition condition of the detection unit on the detection object. Therefore, the method and the device are beneficial to simplifying the detection flow, shortening the detection time length and further improving the detection efficiency.
Drawings
In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings required for the description of the embodiments will be briefly described below, and it is apparent that the drawings in the following description are only some embodiments of the present invention, and other drawings may be obtained according to these drawings without inventive effort for a person skilled in the art.
FIG. 1 is a schematic flow chart of a target detection method according to an embodiment of the present invention;
FIG. 2 is a schematic diagram of a structure of an object detecting device according to an embodiment of the present invention;
fig. 3 is a schematic structural diagram of another object detecting device according to an embodiment of the present invention.
Detailed Description
In order to make the present invention better understood by those skilled in the art, the following description will clearly and completely describe the technical solutions in the embodiments of the present invention with reference to the accompanying drawings, and it is apparent that the described embodiments are only some embodiments of the present invention, not all embodiments. All other embodiments, which can be made by those skilled in the art based on the embodiments of the invention without making any inventive effort, are intended to be within the scope of the invention.
The terms first, second and the like in the description and in the claims and in the above-described figures are used for distinguishing between different objects and not necessarily for describing a sequential or chronological order. Furthermore, the terms "comprise" and "have," as well as any variations thereof, are intended to cover a non-exclusive inclusion. For example, a process, method, apparatus, article, or device that comprises a list of steps or elements is not limited to the list of steps or elements but may, in the alternative, include other steps or elements not expressly listed or inherent to such process, method, article, or device.
Reference herein to "an embodiment" means that a particular feature, structure, or characteristic described in connection with the embodiment may be included in at least one embodiment of the invention. The appearances of such phrases in various places in the specification are not necessarily all referring to the same embodiment, nor are separate or alternative embodiments mutually exclusive of other embodiments. Those of skill in the art will explicitly and implicitly appreciate that the embodiments described herein may be combined with other embodiments.
The invention discloses a target detection method and a target detection device, which are beneficial to simplifying the detection flow, shortening the detection time length and further improving the detection efficiency. The following will describe in detail.
Example 1
Referring to fig. 1, fig. 1 is a flow chart of a target detection method according to an embodiment of the invention. The target detection method described in fig. 1 is applied to a target detection system, such as a local server or a cloud server for target detection management, which is not limited in the embodiment of the present invention. As shown in fig. 1, the object detection method may include the operations of:
101. and acquiring detection attribute information corresponding to the detection unit, object attribute information corresponding to the detection object and current simulation time.
In the embodiment of the invention, the detection attribute information comprises a detection radius value, a detection period, detection unit equipment information and detection unit coordinates.
In the embodiment of the invention, the object attribute information comprises object coordinates and object heights.
102. Based on the attribute information of the detection unit and the current simulation time, static detection analysis and dynamic detection analysis are respectively carried out on the detection object, and static detection information and dynamic detection information are obtained.
103. And analyzing and processing the object height, the static detection information and the dynamic detection information to obtain target detection result information.
In the embodiment of the invention, the target detection result information characterizes the detectable identification condition of the detection unit on the detection object.
The detection unit is a simulation unit with weak maneuverability deployed in a simulation system, is used for carrying a detection main body structure and other structures, and can simulate the simulation unit in a battlefield, including but not limited to a ship, a submarine, a ground unit and a satellite. The main detection structure of the detection unit is a sensor simulation assembly carried on the detection platform, and the main detection structure is used for detecting other side simulation units in a simulation environment, is a module for generating detection results, can simulate the detection flow of a general sensor, and detection inspection items comprise but are not limited to detection distance inspection, topography shielding inspection, field of view inspection, earth curvature inspection and detection interference inspection.
It should be noted that, when the target detection result information is that the target cannot be detected, the characterization detection unit cannot detect the detection object. When the target detection result information is that the target can be detected, the characterization detection unit can detect the detected object
Therefore, the implementation of the target detection method described by the embodiment of the invention is beneficial to simplifying the detection flow, shortening the detection time length and further improving the detection efficiency.
In an optional embodiment, the performing static and dynamic detection analysis on the detected object based on the attribute information of the detection unit and the current simulation time to obtain static detection information and dynamic detection information includes:
determining detection range attribute information based on the detection unit attribute information; the detection range attribute information comprises N first fan-shaped areas and M second fan-shaped areas; m is 2 times of N;
determining dynamic detection information based on the object attribute information and the detection range attribute information;
and determining static detection information based on the detection range attribute information and the current simulation time.
Preferably, N is 16; m is 32.
It should be noted that, the above detection attribute information further includes a detection device type.
In this optional embodiment, as an optional implementation manner, the determining static detection information based on the detection range attribute information and the current simulation time includes:
Acquiring attribute simulation time information; the attribute simulation time information comprises a plurality of equipment simulation time mapping relations; the equipment simulation time mapping relation characterizes simulation period time corresponding to equipment types;
judging whether the equipment type corresponding to the equipment simulation time mapping relation is consistent with the detection equipment type or not according to any equipment simulation time mapping relation, and obtaining a consistent judging result;
when the consistency judgment result is yes, determining the simulation period time corresponding to the equipment simulation time mapping relation as the target simulation period time;
judging whether the current simulation time is an integer multiple of the target simulation period time or not to obtain a time judgment result;
when the time judgment result is negative, determining that the historical static detection information is static detection information;
when the time judgment result is yes, acquiring sector area parameter information;
determining current detection information based on the sector area parameter information;
judging whether the current simulation time is 0 or not, and obtaining a zero-time judgment result;
when the zero judgment result is yes, determining that the current detection information is static detection information;
when the zero judgment result is no, replacing and updating the historical static detection information with the static detection information;
And determining the current detection information as new static detection information.
It should be noted that the simulation cycle time corresponding to the device type corresponds to the detection unit. For example, the simulation cycle time for ships, submarines, and ground units with mobility is 180 seconds, and the simulation cycle time for satellites and ground units without mobility is 3600 seconds. Further, the simulation cycle time characterizes an update cycle of the static probe information. Further, in the embodiment of the present application, the simulation step is 1 second, and therefore, it is characterized that the simulation is performed for 180 simulation steps when the simulation cycle time is 180 seconds.
It should be noted that the above-mentioned sector area parameter information includes KK number of sector area parameters. Further, KK is the sum of N and M.
Further, the fan-shaped area parameter includes a main body height, a first distance and a second distance corresponding to the obstacle.
Further, the first distance characterizes a distance from the obstacle to the detection unit. The second distance characterizes the feature points corresponding to the obstacle to the sector area.
Further, the feature points corresponding to the sector areas represent far-end points of left boundaries of the sector areas.
Further, the fan-shaped area includes a first fan-shaped area and a second fan-shaped area.
It should be noted that the static detection information includes KK static detection result information.
Further, the current detection information includes KK current detection result information. Each current probe result information corresponds to a static probe result information.
In this optional embodiment, as an optional implementation manner, the determining the current detection information based on the fan-shaped area parameter information includes:
for any sector area parameter in the sector area parameter information, calculating the sector area parameter by using a first parameter calculation model to obtain the terrain height in the current detection result information corresponding to the sector area parameter;
the first parameter calculation model is as follows:
wherein H is the height of the terrain; RR is the body height; c1 is a first distance; d1 is a second distance;
calculating the altitude and the detection radius value corresponding to the detection unit corresponding to the fan-shaped region parameter by using a first parameter calculation model to obtain a curvature value in the current detection result information corresponding to the fan-shaped region parameter;
the second parameter calculation model is as follows:
Wherein R is a detection radius value; RR1 is the curvature value; RR2 is the altitude corresponding to the detection unit.
The curvature value represents the altitude value of the curvature of the earth passing through the detection radius.
Therefore, the implementation of the target detection method described by the embodiment of the invention is beneficial to simplifying the detection flow, shortening the detection time length and further improving the detection efficiency.
In another alternative embodiment, determining the detection range attribute information based on the detection unit attribute information includes:
determining a first detection area and a second detection area based on the detection radius value; the first detection area is a circular area constructed by taking one half of the detection radius value as the radius; the second detection area is a closed annular area with the first detection area removed from a circular area constructed by taking the detection radius value as the radius;
dividing the first detection area by a first radian to obtain N first initial sector areas;
sequentially numbering N first initial fan-shaped areas clockwise according to a first numbering format by taking the forward direction of the Y axis as a starting point to obtain N first fan-shaped areas;
dividing the second detection area by a second radian to obtain M second initial sector areas;
And numbering the M second initial fan-shaped areas clockwise according to a second numbering format by taking the Y-axis forward direction as a starting point to obtain M second fan-shaped areas.
The first radian is pi/8 radian. The second radian pi/16 radian.
It should be noted that, the first number format is a, where a is a natural number, such as 1,2,3,4, etc. The second numbering format is B.
The Y-axis forward direction is the north direction.
For example, the detection units radiate outwards in a standard circle, the maximum detection radius (detection radius value) is R, the fluctuation of the internal environment information is small within 0.5R, and the fluctuation of the internal environment information is large within 0.5R, so that the 0.5R is used as a dividing line to make concentric circles. The inner circle is equally divided into 16 first fan-shaped areas with pi/8 radian, and the first fan-shaped areas are respectively marked with A1-A16; similarly, the outer circle is equally divided into 32 second fan-shaped areas with pi/16 radian, and the second fan-shaped areas are respectively marked as B1-B32.
Therefore, the implementation of the target detection method described by the embodiment of the invention is beneficial to simplifying the detection flow, shortening the detection time length and further improving the detection efficiency.
In yet another alternative embodiment, determining dynamic probe information based on object attribute information and probe range attribute information includes:
Calculating the coordinates of the detection unit and the attribute information of the object by using a first detection model to obtain a first detection value;
wherein, the first detection model is:
wherein TC1 is a first detection value; (x, y, z) is the detection unit coordinates; (x 1, y1, z 1) is an object coordinate in the object attribute information;
judging whether the first detection value is smaller than or equal to the detection radius value, and obtaining a first dynamic judgment result;
when the first dynamic judgment result is negative, determining that the dynamic detection information is that the dynamic detection does not pass;
when the first dynamic judgment result is yes, determining a second detection value based on the detection unit equipment information;
judging whether the second detection value is larger than the first detection value or not to obtain a second dynamic judgment result;
when the second dynamic judgment result is negative, determining that the dynamic detection information is that the dynamic detection does not pass;
when the second dynamic judgment result is yes, acquiring field area information;
judging whether the coordinate of the detection unit is positioned in the field area information or not to obtain a third dynamic judgment result;
when the third dynamic judgment result is negative, determining that the dynamic detection information is that the dynamic detection does not pass;
and when the third dynamic judgment result is yes, determining the dynamic detection information as dynamic detection passing.
It should be noted that, the detection unit needs to perform dynamic target detection in each simulation step period to obtain dynamic detection information.
It should be noted that, the field-of-view area information is a rectangular area, and represents a field-of-view visible area of the sensing device corresponding to the detection unit, that is, an area perceived by the sensing device, such as a visible area perceived by a camera, infrared rays, electromagnetic waves, and the like.
Therefore, the implementation of the target detection method described by the embodiment of the invention is beneficial to simplifying the detection flow, shortening the detection time length and further improving the detection efficiency.
In yet another alternative embodiment, determining the second detection value based on the detection unit device information includes:
calculating the equipment information of the detection unit by using a second detection model to obtain a detection power value;
wherein the second detection model is:
in the method, in the process of the invention,detecting a power value; j is the interference power in the equipment information of the detection unit, K is the suppression coefficient in the equipment information of the detection unit;
calculating the detection unit equipment information and the detection power value by using a third detection model to obtain a second detection value;
wherein, the third detection model is:
wherein R is ′ Is the second detection value; p (P) t Transmitting power in equipment information for a detection unit; g is the gain in the detection unit equipment information; sigma is the echo area in the equipment information of the detection unit; lambda is the electromagnetic wavelength in the detection unit device information.
Therefore, the implementation of the target detection method described by the embodiment of the invention is beneficial to simplifying the detection flow, shortening the detection time length and further improving the detection efficiency.
In an alternative embodiment, the analyzing the object height, the static detection information and the dynamic detection information to obtain the target detection result information includes:
judging whether the dynamic detection information is that the dynamic detection fails or not, and obtaining a fourth dynamic judgment result;
when the fourth dynamic judgment result is yes, determining that the target detection result information is the target and cannot be detected;
when the fourth dynamic judgment result is negative, determining target static detection information based on the detection unit coordinates, the object coordinates and the static detection information;
judging whether the terrain height in the target static detection information is smaller than the object height or not to obtain a first static judgment result;
when the first static judgment result is negative, determining that the target detection result information is the target and can not be detected;
When the first static judgment result is yes, judging whether the curvature value in the target static detection information is smaller than the height of the object, and obtaining a second static judgment result;
when the second static judgment result is negative, determining that the target detection result information is the target and can not be detected;
and when the second static judgment result is yes, determining the target detection result information as the target detectable.
It should be noted that, by pre-judging the dynamic detection information, the detection result is primarily judged, so as to determine whether to perform further static detection, i.e. if the dynamic detection is not passed, static environment detection is not required, and the final detection result is that the target cannot be detected, so that the judgment flow can be simplified, and the efficiency of environment monitoring can be improved.
Therefore, the implementation of the target detection method described by the embodiment of the invention is beneficial to simplifying the detection flow, shortening the detection time length and further improving the detection efficiency.
In another alternative embodiment, determining the static probe information for the target based on the probe unit coordinates, the object coordinates, and the static probe information includes:
determining coordinate azimuth information based on the coordinates of the detection unit and the coordinates of the object;
and determining static detection information of the target based on the coordinate azimuth information and the detection range attribute information.
The coordinate azimuth information includes a first detection value and a coordinate angle. Further, the coordinate angle is an angle turned clockwise to a position where the object coordinate is located with the coordinate of the detection unit as an origin, and the Y-axis forward direction is used as a starting direction, that is, an angle from the first direction to the second direction is calculated with the Y-axis forward direction as a first direction and a line direction from the coordinate of the detection unit to the object coordinate as a second direction.
In this optional embodiment, as an optional implementation manner, determining the static detection information of the target based on the coordinate azimuth information and the detection range attribute information includes:
judging whether the first detection value is greater than one half of the detection radius value, and obtaining a numerical value judgment result;
when the value judgment result is yes, determining a closed annular area where the second fan-shaped area is located as a target detection area;
when the numerical value judgment result is negative, determining a circular area where the first fan-shaped area is located as a target detection area;
when the target detection area is a closed annular area where the second fan-shaped area is located, calculating a difference value between the coordinate angle and the second radian to obtain an angle difference value;
When the target detection area is a circular area where the first fan-shaped area is located, calculating a difference value between the coordinate angle and the first radian to obtain an angle difference value;
rounding the angle dividing value upwards to obtain a target angle dividing value;
determining a sector area corresponding to a sector area number matched with the target angle dividing difference value as a target sector area;
and determining the static detection value information corresponding to the target sector area as target static detection information.
The fan-shaped region includes a first fan-shaped region and a second fan-shaped region. Further, the numerical part of the sector number, which is matched with the target angle dividing value, of the sector number is consistent with the target angle dividing value, for example, when the target angle dividing value is 5, the sector number includes A1, A2, A3, A4, A5, A6, A7, and A5 is the sector number matched with the target angle dividing value, and the sector is the target sector.
Therefore, the implementation of the target detection method described by the embodiment of the invention is beneficial to simplifying the detection flow, shortening the detection time length and further improving the detection efficiency.
Example two
Referring to fig. 2, fig. 2 is a schematic structural diagram of an object detecting device according to an embodiment of the invention. The device described in fig. 2 can be applied to a target detection system, such as a local server or a cloud server for target detection management, and the embodiment of the invention is not limited. As shown in fig. 2, the apparatus may include:
An obtaining module 201, configured to obtain detection attribute information corresponding to a detection unit, object attribute information corresponding to a detection object, and a current simulation time; the detection attribute information comprises a detection radius value, a detection period, detection unit equipment information and detection unit coordinates; the object attribute information includes object coordinates and object heights;
the analysis module 202 is configured to perform static and dynamic detection analysis on the detection object based on the detection unit attribute information and the current simulation time, so as to obtain static detection information and dynamic detection information;
the processing module 203 is configured to analyze and process the object height, the static detection information and the dynamic detection information to obtain target detection result information; the target detection result information characterizes the detectable recognition condition of the detection unit on the detection object.
Therefore, implementing the object detection device described in fig. 2 is beneficial to simplifying the detection flow, shortening the detection duration, and further improving the detection efficiency.
In another alternative embodiment, as shown in fig. 2, the analysis module 202 performs static and dynamic detection analysis on the detection object based on the attribute information of the detection unit and the current simulation time, to obtain static detection information and dynamic detection information, including:
Determining detection range attribute information based on the detection unit attribute information; the detection range attribute information comprises N first fan-shaped areas and M second fan-shaped areas; m is 2 times of N;
determining dynamic detection information based on the object attribute information and the detection range attribute information;
and determining static detection information based on the detection range attribute information and the current simulation time.
Therefore, implementing the object detection device described in fig. 2 is beneficial to simplifying the detection flow, shortening the detection duration, and further improving the detection efficiency.
In yet another alternative embodiment, as shown in fig. 2, the analysis module 202 determines detection range attribute information based on the detection unit attribute information, including:
determining a first detection area and a second detection area based on the detection radius value; the first detection area is a circular area constructed by taking one half of the detection radius value as the radius; the second detection area is a closed annular area with the first detection area removed from a circular area constructed by taking the detection radius value as the radius;
dividing the first detection area by a first radian to obtain N first initial sector areas;
sequentially numbering N first initial fan-shaped areas clockwise according to a first numbering format by taking the forward direction of the Y axis as a starting point to obtain N first fan-shaped areas;
Dividing the second detection area by a second radian to obtain M second initial sector areas;
and numbering the M second initial fan-shaped areas clockwise according to a second numbering format by taking the Y-axis forward direction as a starting point to obtain M second fan-shaped areas.
Therefore, implementing the object detection device described in fig. 2 is beneficial to simplifying the detection flow, shortening the detection duration, and further improving the detection efficiency.
In yet another alternative embodiment, as shown in fig. 2, the analysis module 202 determines dynamic probe information based on object attribute information and probe range attribute information, including:
calculating the coordinates of the detection unit and the attribute information of the object by using a first detection model to obtain a first detection value;
wherein, the first detection model is:
wherein TC1 is a first detection value; (x, y, z) is the detection unit coordinates; (x 1, y1, z 1) is an object coordinate in the object attribute information;
judging whether the first detection value is smaller than or equal to the detection radius value, and obtaining a first dynamic judgment result;
when the first dynamic judgment result is negative, determining that the dynamic detection information is that the dynamic detection does not pass;
when the first dynamic judgment result is yes, determining a second detection value based on the detection unit equipment information;
Judging whether the second detection value is larger than the first detection value or not to obtain a second dynamic judgment result;
when the second dynamic judgment result is negative, determining that the dynamic detection information is that the dynamic detection does not pass;
when the second dynamic judgment result is yes, acquiring field area information;
judging whether the coordinate of the detection unit is positioned in the field area information or not to obtain a third dynamic judgment result;
when the third dynamic judgment result is negative, determining that the dynamic detection information is that the dynamic detection does not pass;
and when the third dynamic judgment result is yes, determining the dynamic detection information as dynamic detection passing.
Therefore, implementing the object detection device described in fig. 2 is beneficial to simplifying the detection flow, shortening the detection duration, and further improving the detection efficiency.
In yet another alternative embodiment, as shown in fig. 2, the analysis module 202 determines the second detection value based on the detection unit device information, including:
calculating the equipment information of the detection unit by using a second detection model to obtain a detection power value;
wherein the second detection model is:
in the method, in the process of the invention,detecting a power value; j is the interference power in the equipment information of the detection unit, K is the suppression coefficient in the equipment information of the detection unit;
Calculating the detection unit equipment information and the detection power value by using a third detection model to obtain a second detection value;
wherein, the third detection model is:
wherein R is ′ Is the second detection value; p (P) t Transmitting power in equipment information for a detection unit; p (P) t Gain in the detection unit device information; sigma is the echo area in the equipment information of the detection unit; lambda is the electromagnetic wavelength in the detection unit device information.
Therefore, implementing the object detection device described in fig. 2 is beneficial to simplifying the detection flow, shortening the detection duration, and further improving the detection efficiency.
In yet another alternative embodiment, as shown in fig. 2, the processing module 203 performs analysis processing on the object height, the static detection information and the dynamic detection information to obtain target detection result information, including:
judging whether the dynamic detection information is that the dynamic detection fails or not, and obtaining a fourth dynamic judgment result;
when the fourth dynamic judgment result is yes, determining that the target detection result information is the target and cannot be detected;
when the fourth dynamic judgment result is negative, determining target static detection information based on the detection unit coordinates, the object coordinates and the static detection information;
judging whether the terrain height in the target static detection information is smaller than the object height or not to obtain a first static judgment result;
When the first static judgment result is negative, determining that the target detection result information is the target and can not be detected;
when the first static judgment result is yes, judging whether the curvature value in the target static detection information is smaller than the height of the object, and obtaining a second static judgment result;
when the second static judgment result is negative, determining that the target detection result information is the target and can not be detected;
and when the second static judgment result is yes, determining the target detection result information as the target detectable.
Therefore, implementing the object detection device described in fig. 2 is beneficial to simplifying the detection flow, shortening the detection duration, and further improving the detection efficiency.
In yet another alternative embodiment, as shown in fig. 2, the processing module 203 determines the target static detection information based on the detection unit coordinates, the object coordinates, and the static detection information, including:
determining coordinate azimuth information based on the coordinates of the detection unit and the coordinates of the object;
and determining static detection information of the target based on the coordinate azimuth information and the detection range attribute information.
Therefore, implementing the object detection device described in fig. 2 is beneficial to simplifying the detection flow, shortening the detection duration, and further improving the detection efficiency.
Example III
Referring to fig. 3, fig. 3 is a schematic structural diagram of another object detecting device according to an embodiment of the present invention. The device described in fig. 3 can be applied to a target detection system, such as a local server or a cloud server for target detection management, and the embodiment of the invention is not limited. As shown in fig. 3, the apparatus may include:
a memory 301 storing executable program code;
a processor 302 coupled with the memory 301;
the processor 302 invokes executable program code stored in the memory 301 for performing the steps in the object detection method described in embodiment one.
Example IV
The embodiment of the invention discloses a computer-readable storage medium storing a computer program for electronic data exchange, wherein the computer program causes a computer to execute the steps in the object detection method described in the embodiment one.
Example five
The present invention discloses a computer program product comprising a non-transitory computer readable storage medium storing a computer program, and the computer program is operable to cause a computer to perform the steps of the object detection method described in the first embodiment.
The apparatus embodiments described above are merely illustrative, in which the modules illustrated as separate components may or may not be physically separate, and the components shown as modules may or may not be physical, i.e., may be located in one place, or may be distributed over multiple network modules. Some or all of the modules may be selected according to actual needs to achieve the purpose of the solution of this embodiment. Those of ordinary skill in the art will understand and implement the present invention without undue burden.
From the above detailed description of the embodiments, it will be apparent to those skilled in the art that the embodiments may be implemented by means of software plus necessary general hardware platforms, or of course by means of hardware. Based on such understanding, the foregoing technical solutions may be embodied essentially or in part in the form of a software product that may be stored in a computer-readable storage medium including Read-Only Memory (ROM), random-access Memory (Random Access Memory, RAM), programmable Read-Only Memory (Programmable Read-Only Memory, PROM), erasable programmable Read-Only Memory (Erasable Programmable Read Only Memory, EPROM), one-time programmable Read-Only Memory (OTPROM), electrically erasable programmable Read-Only Memory (EEPROM), compact disc Read-Only Memory (Compact Disc Read-Only Memory, CD-ROM) or other optical disc Memory, magnetic disc Memory, tape Memory, or any other medium that can be used for computer-readable carrying or storing data.
Finally, it should be noted that: the disclosure of the target detection method and apparatus in the embodiment of the present invention is only a preferred embodiment of the present invention, and is only for illustrating the technical scheme of the present invention, but not for limiting the same; although the invention has been described in detail with reference to the foregoing embodiments, those of ordinary skill in the art will understand that; the technical scheme recorded in the various embodiments can be modified or part of technical features in the technical scheme can be replaced equivalently; such modifications and substitutions do not depart from the spirit and scope of the corresponding technical solutions.
Claims (7)
1. A method of target detection, the method comprising:
acquiring detection attribute information corresponding to a detection unit, object attribute information corresponding to a detection object and current simulation time; the detection attribute information comprises a detection radius value, a detection period, detection unit equipment information and detection unit coordinates; the object attribute information comprises object coordinates and object heights;
based on the attribute information of the detection unit and the current simulation time, respectively carrying out static detection analysis and dynamic detection analysis on the detection object to obtain static detection information and dynamic detection information;
The detecting unit attribute information and the current simulation time are used for respectively carrying out static detection analysis and dynamic detection analysis on the detected object to obtain static detection information and dynamic detection information, and the detecting unit attribute information and the current simulation time comprise the following steps:
determining detection range attribute information based on the detection unit attribute information; the detection range attribute information comprises N first fan-shaped areas and M second fan-shaped areas; the M is 2 times of the N;
determining dynamic detection information based on the object attribute information and the detection range attribute information;
determining static detection information based on the detection range attribute information and the current simulation time;
wherein the determining dynamic detection information based on the object attribute information and the detection range attribute information includes:
calculating the coordinates of the detection unit and the object attribute information by using a first detection model to obtain a first detection value;
wherein, the first detection model is:
wherein TC1 is the first probe value; (x, y, z) is the detection unit coordinates; (x 1, y1, z 1) is an object coordinate in the object attribute information;
judging whether the first detection value is smaller than or equal to the detection radius value or not to obtain a first dynamic judgment result;
When the first dynamic judgment result is negative, determining that the dynamic detection information is that the dynamic detection does not pass;
when the first dynamic judgment result is yes, determining a second detection value based on the detection unit equipment information;
judging whether the second detection value is larger than the first detection value or not to obtain a second dynamic judgment result;
when the second dynamic judgment result is negative, determining that the dynamic detection information is that the dynamic detection does not pass;
when the second dynamic judgment result is yes, acquiring field area information;
judging whether the coordinate of the detection unit is positioned in the field area information or not to obtain a third dynamic judgment result;
when the third dynamic judgment result is negative, determining that the dynamic detection information is that the dynamic detection does not pass;
when the third dynamic judgment result is yes, determining that the dynamic detection information is the dynamic detection passing;
wherein, based on the detection unit device information, determining a second detection value includes:
calculating the detection unit equipment information by using a second detection model to obtain a detection power value;
wherein the second detection model is:
In the method, in the process of the invention,the detected power value; j is the interference power in the detection unit equipment information, K is the suppression coefficient in the detection unit equipment information;
calculating the detection unit equipment information and the detection power value by using a third detection model to obtain a second detection value;
wherein the third detection model is:
wherein R' is the second detection value; p (P) t Transmitting power in the equipment information of the detection unit; g is the gain in the detection unit equipment information; sigma is the echo area in the detection unit equipment information; lambda is the electromagnetic wavelength in the detection unit equipment information;
analyzing and processing the object height, the static detection information and the dynamic detection information to obtain target detection result information; the target detection result information characterizes the detectable recognition condition of the detection unit on the detection object.
2. The method according to claim 1, wherein determining detection range attribute information based on the detection unit attribute information includes:
determining a first detection area and a second detection area based on the detection radius value; the first detection area is a circular area constructed by taking one half of the detection radius value as a radius; the second detection area is a closed annular area with the first detection area removed from a circular area constructed by taking the detection radius value as a radius;
Equally dividing the first detection area by a first radian to obtain N first initial sector areas;
sequentially numbering the N first initial sector areas clockwise according to a first numbering format by taking the forward direction of the Y axis as a starting point to obtain N first sector areas;
equally dividing the second detection area by a second radian to obtain M second initial sector areas;
and numbering the M second initial sector areas clockwise according to a second numbering format by taking the Y-axis forward direction as a starting point to obtain the M second sector areas.
3. The method of claim 1, wherein the analyzing the object height, the static detection information, and the dynamic detection information to obtain target detection result information includes:
judging whether the dynamic detection information is that the dynamic detection fails or not, and obtaining a fourth dynamic judgment result;
when the fourth dynamic judgment result is yes, determining that the target detection result information is the target and cannot be detected;
when the fourth dynamic judgment result is negative, determining target static detection information based on the detection unit coordinates, the object coordinates and the static detection information;
Judging whether the terrain height in the target static detection information is smaller than the object height or not to obtain a first static judgment result;
when the first static judgment result is negative, determining that the target detection result information is undetectable;
when the first static judgment result is yes, judging whether the curvature value in the target static detection information is smaller than the object height, and obtaining a second static judgment result;
when the second static judgment result is negative, determining that the target detection result information is undetectable;
and when the second static judgment result is yes, determining that the target detection result information is that the target is detectable.
4. The method according to claim 3, wherein determining the target static detection information based on the detection unit coordinates, the object coordinates, and the static detection information includes:
determining coordinate azimuth information based on the detection unit coordinates and the object coordinates;
and determining static detection information of the target based on the coordinate azimuth information and the detection range attribute information.
5. An object detection device, the device comprising:
The acquisition module is used for acquiring the detection attribute information corresponding to the detection unit, the object attribute information corresponding to the detection object and the current simulation time; the detection attribute information comprises a detection radius value, a detection period, detection unit equipment information and detection unit coordinates; the object attribute information comprises object coordinates and object heights;
the analysis module is used for respectively carrying out static detection analysis and dynamic detection analysis on the detection object based on the detection unit attribute information and the current simulation time to obtain static detection information and dynamic detection information;
the detecting unit attribute information and the current simulation time are used for respectively carrying out static detection analysis and dynamic detection analysis on the detected object to obtain static detection information and dynamic detection information, and the detecting unit attribute information and the current simulation time comprise the following steps:
determining detection range attribute information based on the detection unit attribute information; the detection range attribute information comprises N first fan-shaped areas and M second fan-shaped areas; the M is 2 times of the N;
determining dynamic detection information based on the object attribute information and the detection range attribute information;
determining static detection information based on the detection range attribute information and the current simulation time;
Wherein the determining dynamic detection information based on the object attribute information and the detection range attribute information includes:
calculating the coordinates of the detection unit and the object attribute information by using a first detection model to obtain a first detection value;
wherein, the first detection model is:
wherein TC1 is the first probe value; (x, y, z) is the detection unit coordinates; (x 1, y1, z 1) is an object coordinate in the object attribute information;
judging whether the first detection value is smaller than or equal to the detection radius value or not to obtain a first dynamic judgment result;
when the first dynamic judgment result is negative, determining that the dynamic detection information is that the dynamic detection does not pass;
when the first dynamic judgment result is yes, determining a second detection value based on the detection unit equipment information;
judging whether the second detection value is larger than the first detection value or not to obtain a second dynamic judgment result;
when the second dynamic judgment result is negative, determining that the dynamic detection information is that the dynamic detection does not pass;
when the second dynamic judgment result is yes, acquiring field area information;
judging whether the coordinate of the detection unit is positioned in the field area information or not to obtain a third dynamic judgment result;
When the third dynamic judgment result is negative, determining that the dynamic detection information is that the dynamic detection does not pass;
when the third dynamic judgment result is yes, determining that the dynamic detection information is the dynamic detection passing;
wherein, based on the detection unit device information, determining a second detection value includes:
calculating the detection unit equipment information by using a second detection model to obtain a detection power value;
wherein the second detection model is:
in the method, in the process of the invention,the detected power value; j is the interference power in the detection unit equipment information, K is the suppression coefficient in the detection unit equipment information;
calculating the detection unit equipment information and the detection power value by using a third detection model to obtain a second detection value;
wherein the third detection model is:
wherein R' is the second detection value; p (P) t Transmitting power in the equipment information of the detection unit; g is the gain in the detection unit equipment information; sigma is the echo area in the detection unit equipment information; lambda is the electromagnetic wavelength in the detection unit equipment information;
the processing module is used for analyzing and processing the object height, the static detection information and the dynamic detection information to obtain target detection result information; the target detection result information characterizes the detectable recognition condition of the detection unit on the detection object.
6. An object detection device, the device comprising:
a memory storing executable program code;
a processor coupled to the memory;
the processor invokes the executable program code stored in the memory to perform the object detection method of any one of claims 1-4.
7. A computer readable storage medium storing computer instructions which, when invoked, are adapted to perform the object detection method of any one of claims 1-4.
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| CN111308467A (en) * | 2020-03-10 | 2020-06-19 | 宁波飞芯电子科技有限公司 | Detection method and detection device |
| CN111959511A (en) * | 2020-08-26 | 2020-11-20 | 腾讯科技（深圳）有限公司 | Vehicle control method and device |
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