CN114004150A

CN114004150A - Method, device, equipment and storage medium for evaluating and disposing threat degree of flying object

Info

Publication number: CN114004150A
Application number: CN202111278227.9A
Authority: CN
Inventors: 刘志升; 崔陆
Original assignee: Beijing Sail Cable Technology Co ltd
Current assignee: Beijing Sail Cable Technology Co ltd
Priority date: 2021-10-30
Filing date: 2021-10-30
Publication date: 2022-02-01

Abstract

The embodiment of the application provides a method, a device, equipment and a storage medium for evaluating and disposing threat degrees of flyers, and relates to the field of target detection and identification. The method comprises the following steps: obtaining threat factors of a flying object, wherein the threat factors comprise distance, height, initial speed, landing speed and flight time; calculating a threat value of the flying object according to the threat factor; and setting a corresponding treatment process through a trained neural network model according to the threat factor and the threat value of the flying object, wherein the treatment process comprises a primary response, a secondary response and a tertiary response. The method and the device can improve the problem that the evaluation accuracy of the threat degree of the unexploded object after the grenade is thrown is not high, and the problem that the processing flow matching degree of the unexploded object is low, and achieve the effects of improving the evaluation accuracy of the threat degree of the unexploded object after the grenade is thrown and matching a more proper processing flow.

Description

Method, device, equipment and storage medium for evaluating and disposing threat degree of flying object

Technical Field

Embodiments of the present application relate to the field of target detection and identification technologies, and in particular, to a method, an apparatus, a device, and a storage medium for evaluating and handling a threat level of a flying object.

Background

The grenade has the advantages of simple structure, low manufacturing cost, convenient use and the like, is equipped with infantry and is used for breaking simple civil engineering works or completing other combat tasks. When the grenade is used for throwing training, various dangerous situations are easy to occur. In the case of a target range, a dumb mine (unexploded product) appears in the grenade throwing training process, and extremely high danger is brought to personnel in the training field.

For the related technologies, the inventor thinks that the threat degree evaluation of the training of throwing the hand mine is mainly before throwing, the threat degree evaluation accuracy of the unexploded article after throwing the hand mine is not high, and the treatment process matching degree of the unexploded article is low.

Disclosure of Invention

The embodiment of the application provides a method, a device, equipment and a storage medium for evaluating and disposing threat degree of a flying object, and can solve the problems that evaluation accuracy of threat degree of an unexploded object thrown by a grenade is not high, and the disposal flow matching degree of the unexploded object is low.

In a first aspect of the present application, a method for threat assessment and treatment of a flying object is provided, including:

obtaining threat factors of a flying object, wherein the threat factors comprise distance, height, initial speed, landing speed and flight time;

calculating a threat value of the flying object according to the threat factor;

according to the threat factor and the threat value of the flying object, setting a corresponding treatment process through a trained neural network model, wherein the treatment process comprises the following steps: primary response, secondary response, and tertiary response.

Through adopting above technical scheme, acquire the threat factor of flight thing, calculate the threat value of flight thing, according to the threat factor and the threat value of flight thing, through the neural network model that the training was accomplished, carry out the settlement of corresponding processing procedure, can improve the problem that the processing procedure matching degree of the unexploded article threat degree after the grenade was thrown is not high, and unexploded article was thrown to the grenade reaches and improves the unexploded article threat degree evaluation precision after the grenade was thrown, matches the effect of more suitable processing procedure.

In one possible implementation, the obtaining the threat factors of multiple targets includes:

the threat factor is measured by monitoring devices including radar detection devices, photo detection devices, and radio detection devices.

In one possible implementation, the calculating the threat value of the flying object according to the threat factor includes:

calculating a threat value for the flying object using:

θ＝λ_GS*100％

f(d)＝1000/d(0<d<30)

f(d)＝1/d(30<d<100)

f(h)＝5h(0<h<50)

f(v1)＝2v1(0<v1<30)

f(v2)＝5v2(0<v2<30)

f(t)＝t(0<t<10)

wherein λ is_GSIs a threat coefficient, theta is a threat value, and n is the number of flyers; f (d) is a distance evaluation function, f (h) is a height evaluation function, f (v1) is an initial velocity evaluation function, f (v2) is a landing velocity evaluation function, and f (t) is a flight time evaluation function.

In one possible implementation, the training step of the neural network model includes:

obtaining a training sample, wherein the training sample comprises a historical threat factor and a historical threat value of a flying object;

and training a neural network model according to the training samples.

In a second aspect of the present application, there is provided a flight threat assessment and treatment device, comprising:

the system comprises an acquisition module, a detection module and a processing module, wherein the acquisition module is used for acquiring threat factors of the flying object, and the threat factors comprise distance, height, starting speed, landing speed and flight time;

the calculation module is used for calculating the threat value of the flyer according to the threat factor;

and the setting module is used for setting a corresponding treatment process through a trained neural network model according to the threat factor and the threat value of the flying object, wherein the treatment process comprises a primary response, a secondary response and a tertiary response.

In a possible implementation manner, the obtaining module is specifically configured to:

In a possible implementation manner, the calculation module is specifically configured to:

calculating a threat value for the flying object using:

θ＝λ_GS*100％

f(d)＝1000/d(0<d<30)

f(d)＝1/d(30<d<100)

f(h)＝5h(0<h<50)

f(v1)＝2v1(0<v1<30)

f(v2)＝5v2(0<v2<30)

f(t)＝t(0<t<10)

In one possible implementation manner, the setting module further includes:

the acquisition unit is used for acquiring a training sample, wherein the training sample comprises a historical threat factor and a historical threat value of the flyer;

and the training unit is used for training a neural network model according to the training samples.

In a third aspect of the present application, an electronic device is provided. The electronic device includes: a memory having a computer program stored thereon and a processor implementing the method as described above when executing the computer program.

In a fourth aspect of the application, a computer-readable storage medium is provided, on which a computer program is stored, which computer program, when being executed by a processor, carries out the steps of the method.

It should be understood that what is described in this summary section is not intended to limit key or critical features of the embodiments of the application, nor is it intended to limit the scope of the application. Other features of the present application will become apparent from the following description.

Drawings

The above and other features, advantages and aspects of various embodiments of the present application will become more apparent by referring to the following detailed description when taken in conjunction with the accompanying drawings. In the drawings, like or similar reference characters designate like or similar elements, and wherein:

fig. 1 shows a flowchart of a method for threat level assessment and handling of a flying object in an embodiment of the present application.

Fig. 2 shows a structural diagram of a device for threat level assessment and handling of a flying object in an embodiment of the present application.

Fig. 3 shows a schematic structural diagram of an electronic device suitable for implementing embodiments of the present application.

Detailed Description

In order to make the objects, technical solutions and advantages of the embodiments of the present application clearer, the technical solutions in the embodiments of the present application will be clearly and completely described below with reference to the drawings in the embodiments of the present application.

The method for evaluating and disposing the threat level of the flying object provided by the embodiment of the application can be applied to the technical field of target detection and identification, such as scenes of the method, the device, the equipment, the storage medium and the like for evaluating and disposing the threat level of the flying object. At present, the threat degree evaluation of the training of throwing the hand mine is mainly before throwing, the threat degree evaluation accuracy of the unexploded objects thrown by the hand mine is not high, and the matching degree of the disposal process of the unexploded objects is low. To solve the technical problem, embodiments of the present application provide a method for threat level assessment and handling of a flying object. In some embodiments, the method of threat assessment and handling of a flying object may be performed by an electronic device.

Fig. 1 shows a flowchart of a method for threat level assessment and handling of a flying object in an embodiment of the present application. Referring to fig. 1, the method for assessing and handling the threat level of a flying object in the present embodiment includes:

step 101: and acquiring threat factors of the flying object, wherein the threat factors comprise distance, height, initial speed, landing speed and flight time.

Step 102: and calculating the threat value of the flyer according to the threat factors.

Step 103: and setting a corresponding disposal flow through the trained neural network model according to the threat factor and the threat value of the flying object, wherein the disposal flow comprises a primary response, a secondary response and a tertiary response.

In the embodiment of the application, by adopting the technical scheme, the threat factor of the flyer is obtained, the threat value of the flyer is calculated, the setting of the corresponding disposal flow is carried out through the trained neural network model according to the threat factor and the threat value of the flyer, the problems that the threat degree evaluation accuracy of the unexploded item after the grenade is thrown is not high, and the disposal flow matching degree of the unexploded item is low can be solved, and the effects of improving the threat degree evaluation accuracy of the unexploded item after the grenade is thrown and matching the more appropriate disposal flow are achieved.

In the embodiment of the application, the related method is based on the data fusion, decision and reasoning process of the regional situation assessment, has more related factors, and is a multi-objective decision process and a multi-attribute decision problem. The suspected target is subjected to threat assessment, firstly, a threat factor of the target is extracted to be calculated to obtain a relevant threat value, and the key point is selection and processing of the threat factor.

In the embodiment of the application, different threat factors are caused by different application environments and target objects, so that the processing methods of the target objects are different, and reasonable selection of the threat factors and the processing methods is crucial to evaluation of the target threat degree.

In the embodiment of the application, the application scene is selected as a target range, the target object (flying object) is a grenade, and threat assessment and processing are mainly performed on a dumb mine (unexploded object) occurring in a grenade throwing training process.

In the embodiment of the application, the threat factors of the grenade mainly include target attributes, motion parameters, time, position and the like. Wherein, the target attribute is the attribute of the grenade (small volume, small mass, capable of killing living targets and destroying tanks and armored vehicles); the motion parameters are the speed in the grenade throwing training, and the speed comprises the starting speed of the grenade and the landing speed of the grenade; the time is the flight time of the grenade in the throwing process; the positions are the positions and the heights of the grenades from the throwing starting point in the throwing process.

In some embodiments, step a1 is also included in step 101.

Step A1: threat factors are measured by monitoring devices, including radar detection devices, photo detection devices, and radio detection devices.

Referring to fig. 2, in the embodiment of the present application, optionally, the radar detection device is a moving target display tracking radar, the photoelectric detection device is a thermal detector, and the radio detection device is a radio signal detector.

In the embodiment of the application, the tracking range formed by the plurality of moving target display tracking radars covers the whole shooting range, and the multi-target tracking is synchronously carried out on all the hand radars in the shooting range. Each moving target displays information such as the speed, time and position of a plurality of grenades measured by the tracking radar within the measuring range of the moving target. Meanwhile, each moving target display tracking radar carries out visualization processing on information such as the speed, time and position of the plurality of grenades measured by the moving target display tracking radar, carries out real-time data updating together with the tracks of the grenades, sends target information to a training information management platform, and establishes a comprehensive information base.

The moving target display tracking radar also receives the training information management platform, sends out a key target tracking instruction and a specific direction scanning instruction, sends out specific target information and transmits the specific target information to the training information management platform.

In the embodiment of the application, the tracking and identifying range formed by the plurality of thermal detectors covers the whole range, and all grenades in the range are synchronously tracked and identified. Each heat detector measures information about the object properties, speed, time and location of the plurality of grenades within its measurement range. Meanwhile, each thermal detector carries out visualization processing on the information such as the target attributes, the speed, the time, the positions and the like of the plurality of grenades measured by the thermal detector, carries out real-time data updating together with the tracks of the grenades, sends the target information to a training information management platform, and establishes a comprehensive information base.

In the embodiment of the application, the measuring range formed by the plurality of radio signal detectors covers the whole target range, and the environment in the target range and all grenades are synchronously tracked and identified. Each radio signal detector measures information on environmental factors, target properties, speed, time, location, etc. of a plurality of grenades within its measurement range. Meanwhile, each radio signal detector sends the measured information of the environmental factors, the target attributes, the speed, the time, the positions and the like of the plurality of grenades to a training information management platform to establish a comprehensive information base.

In the embodiment of the application, the training information management platform is a command control system, monitors various data information in a target range in real time, and processes the data information.

In some embodiments, step B1 is also included in step 102.

Step B1: calculating a threat value for the flying object using:

θ＝λ_GS*100％

f(d)＝1000/d(0<d<30)

f(d)＝1/d(30<d<100)

f(h)＝5h(0<h<50)

f(v1)＝2v1(0<v1<30)

f(v2)＝5v2(0<v2<30)

f(t)＝t(0<t<10)

In the embodiment of the application, each grenade in the range is a target, and the targets are numbered by the number of the targets by using arabic numerals, namely target 1, target 2 … …, and target N (N ═ 1, 2, 3 … …). Each target corresponds to data information of a group of threat factors, and each data in the data information of the group of threat factors corresponds to an evaluation function.

In the embodiment of the application, the command control system records the data information of each group of threat factors of each grenade in real time, performs data fusion on the data information, performs inference analysis according to attributes, classification and size, and calculates a threat value (threat assessment value) by combining the evaluation function calculation result of the data information of each group of threat factors of each grenade.

In the embodiment of the present application, the relationship numbers in the parameter value 45000000 and the evaluation function are empirical values, and the numerical values in the embodiment of the present application are all calculated as absolute values.

For example, 1 dumb mine appears in the shooting range, the dumb mine is 10 meters away from a throwing point, the relative height of a landing point is 5 meters, the initial speed of throwing is 10m/s, the landing speed is 15m/s, and the flight time is 5 seconds, so that:

n＝1；

f1(d)＝1000/10＝100；

f1(h)＝5*10＝50；

f1(v1)＝2*10＝20；

f1(v2)＝3*10＝30；

f1(t)＝5；

and (3) calculating:

θ＝λ_GS*100％＝33.3％

the threat value is therefore 33.3%.

In some embodiments, step C1-step C2 are also included in step 102.

Step C1: and acquiring a training sample, wherein the training sample comprises a historical threat factor and a historical threat value of the flyer.

Step C2: and training the neural network model according to the training samples.

In this embodiment of the present application, optionally, the neural network model is trained by using a feedforward neural network model.

In the embodiment of the application, the command control system self-defines and divides the threat level according to the threat value, and carries out disposal work according to various environments and threat levels and a set processing flow. And carrying out user-defined division through the trained neural network model.

In the embodiment of the application, the historical threat factor and the historical threat value of the grenade in each training sample are stored in the command and control system along with the accumulated times of grenade throwing training. In the historical threat factor, any one of data of target attributes, motion parameters, time and positions is changed, or in the historical threat value, the empirical value is changed due to the change of the target application scene, and the threat levels are self-defined and divided by the command control system according to the threat values, wherein the threat levels comprise a first-level threat level, a second-level threat level and a third-level threat level.

In the embodiment of the application, manual intervention is performed in a man-machine interaction mode to obtain a disposal strategy. And carrying out intelligent scheduling by the command control system according to the disposal strategy. Meanwhile, the photoelectric tracking guides intelligent scheduling, and the intelligent scheduling guides each response mechanism in the whole range to carry out quick linkage and carry out emergency treatment.

The intelligent scheduling also conducts whistling or red early warning through the alarm device combined with sound and light to guide other people in the target range to leave the scene. And in the process of personnel evacuation, synchronously carrying out photoelectric tracking, carrying out target identification on the personnel, and carrying out image recording on the process of personnel evacuation through a camera device.

In the embodiment of the application, a disposal flow in the emergency treatment process is matched according to the threat level, the disposal flow comprises a primary response, a secondary response and a tertiary response, and the primary threat level, the secondary threat level and the tertiary threat level in the threat level correspond to the primary response, the secondary response and the tertiary response in the disposal flow one to one.

For example, if the command control system makes a threat assessment of a first level of threat to a certain mine dumb, the command control system outputs a disposal flow of a first level response. The processing flow of the primary response comprises the following steps: the comprehensive processing system for the dummy ammunition, which consists of the explosion-proof operation vehicle, the explosion-proof discharging vehicle and the explosion-proof excavator, realizes the remote control command scheduling of the whole process of the dummy ammunition processing and the rapid processing and reporting of the damage data of the target range.

Further, a disposal flow of primary response is started, a real-time communication command of the dummy bomb disposal in the target range, image transmission and time-efficient high-speed starting of the dummy bomb information comprehensive management application are achieved, the dummy bomb search detection and positioning can be conducted in a long distance and a large range, and the disposal speed and disposal resources with the highest specification are matched.

The disposal resources comprise inspection vehicle equipment such as an explosion-removing inspection instrument and an explosion-removing vehicle; transportation equipment such as an explosive-handling robot (explosive-handling vehicle), an explosion-proof working vehicle and the like, and safety guarantee equipment such as a frequency interference meter for explosive handling and the like; and hazardous substance portable water cutting systems and other destroying equipment.

If the command control system makes a threat assessment of the second level threat or the third level threat aiming at a certain dumb mine, the handling speed and the handling resources of the handling process are decreased along with the increase of the threat level progression.

For example, the command control system makes a threat assessment of three levels of threats aiming at a certain mine dumb mine, and the command control system starts photoelectric positioning and unmanned aerial vehicle positioning to perform target display control. And after the target is obtained, only the explosive ordnance disposal vehicle is driven to obtain the path guide to approach the target for explosive ordnance disposal, if the path guide is successful, the command system is controlled to output an event report, and if the path guide is failed, the command system is controlled to output an accident report.

It should be noted that, for simplicity of description, the above-mentioned method embodiments are described as a series of acts or combination of acts, but those skilled in the art will recognize that the present application is not limited by the order of acts described, as some steps may occur in other orders or concurrently depending on the application. Further, those skilled in the art should also appreciate that the embodiments described in the specification are exemplary embodiments and that the acts and modules referred to are not necessarily required in this application.

The above is a description of method embodiments, and the embodiments of the present application are further described below by way of apparatus embodiments.

Fig. 2 is a block diagram illustrating a threat level assessment and handling device for a flying object according to an embodiment of the present application. Referring to fig. 2, the device for assessing and treating the threat level of a flying object comprises an acquisition module 201, a calculation module 202 and a setting module 203.

The obtaining module 201 is configured to obtain threat factors of a flying object, where the threat factors include a distance, an altitude, an initial speed, a landing speed, and a flight time.

A calculating module 202, configured to calculate a threat value of the flying object according to the threat factor.

And the setting module 203 is configured to set a corresponding treatment process through the trained neural network model according to the threat factor and the threat value of the flying object, where the treatment process includes a primary response, a secondary response, and a tertiary response.

In some embodiments, the obtaining module 201 is specifically configured to:

In some embodiments, the calculation module 202 is specifically configured to:

calculating a threat value for the flying object using:

θ＝λ_GS*100％

f(d)＝1000/d(0<d<30)

f(d)＝1/d(30<d<100)

f(h)＝5h(0<h<50)

f(v1)＝2v1(0<v1<30)

f(v2)＝5v2(0<v2<30)

f(t)＝t(0<t<10)

In some embodiments, the setting module 203 further comprises:

the acquisition unit is used for acquiring training samples, and the training samples comprise historical threat factors and historical threat values of the flyer.

It can be clearly understood by those skilled in the art that, for convenience and brevity of description, the specific working process of the described module may refer to the corresponding process in the foregoing method embodiment, and is not described herein again.

Fig. 3 shows a schematic structural diagram of an electronic device suitable for implementing embodiments of the present application. As shown in fig. 3, the electronic device 300 shown in fig. 3 includes: a processor 301 and a memory 303. Wherein the processor 301 is coupled to the memory 303. Optionally, the electronic device 300 may also include a transceiver 304. It should be noted that the transceiver 304 is not limited to one in practical applications, and the structure of the electronic device 300 is not limited to the embodiment of the present application.

The Processor 301 may be a CPU (Central Processing Unit), a general-purpose Processor, a DSP (Digital Signal Processor), an ASIC (Application Specific Integrated Circuit), an FPGA (Field Programmable Gate Array) or other Programmable logic device, a transistor logic device, a hardware component, or any combination thereof. Which may implement or perform the various illustrative logical blocks, modules, and circuits described in connection with the disclosure. The processor 301 may also be a combination of computing functions, e.g., comprising one or more microprocessors, a combination of a DSP and a microprocessor, or the like.

Bus 302 may include a path that transfers information between the above components. The bus 302 may be a PCI (Peripheral Component Interconnect) bus, an EISA (Extended Industry Standard Architecture) bus, or the like. The bus 302 may be divided into an address bus, a data bus, a control bus, and the like. For ease of illustration, only one thick line is shown in FIG. 3, but this does not mean only one bus or one type of bus.

The Memory 303 may be a ROM (Read Only Memory) or other type of static storage device that can store static information and instructions, a RAM (Random Access Memory) or other type of dynamic storage device that can store information and instructions, an EEPROM (Electrically Erasable Programmable Read Only Memory), a CD-ROM (Compact Disc Read Only Memory) or other optical Disc storage, optical Disc storage (including Compact Disc, laser Disc, optical Disc, digital versatile Disc, blu-ray Disc, etc.), a magnetic Disc storage medium or other magnetic storage device, or any other medium that can be used to carry or store desired program code in the form of instructions or data structures and that can be accessed by a computer, but is not limited to these.

The memory 303 is used for storing application program codes for executing the scheme of the application, and the processor 301 controls the execution. The processor 301 is configured to execute application program code stored in the memory 303 to implement the aspects illustrated in the foregoing method embodiments.

Among them, electronic devices include but are not limited to: mobile terminals such as mobile phones, notebook computers, digital broadcast receivers, PDAs (personal digital assistants), PADs (tablet computers), PMPs (portable multimedia players), in-vehicle terminals (e.g., in-vehicle navigation terminals), and the like, and fixed terminals such as digital TVs, desktop computers, and the like. The electronic device shown in fig. 3 is only an example, and should not bring any limitation to the functions and the scope of use of the embodiments of the present application.

The present application provides a computer-readable storage medium, on which a computer program is stored, which, when running on a computer, enables the computer to execute the corresponding content in the foregoing method embodiments. Compared with the prior art, in the embodiment of the application, the threat factor of the flyer is obtained, the threat value of the flyer is calculated, the corresponding disposal process is set through the trained neural network model according to the threat factor and the threat value of the flyer, the problems that the threat degree of the unexploded article thrown by the grenade is not high in evaluation accuracy, and the disposal process matching degree of the unexploded article is low can be solved, and the effects that the threat degree of the unexploded article thrown by the grenade is improved, and the more appropriate disposal process is matched are achieved.

It should be understood that, although the steps in the flowcharts of the figures are shown in order as indicated by the arrows, the steps are not necessarily performed in order as indicated by the arrows. The steps are not performed in the exact order shown and may be performed in other orders unless explicitly stated herein. Moreover, at least a portion of the steps in the flow chart of the figure may include multiple sub-steps or multiple stages, which are not necessarily performed at the same time, but may be performed at different times, which are not necessarily performed in sequence, but may be performed alternately or alternately with other steps or at least a portion of the sub-steps or stages of other steps.

The foregoing is only a partial embodiment of the present application, and it should be noted that, for those skilled in the art, several modifications and decorations can be made without departing from the principle of the present application, and these modifications and decorations should also be regarded as the protection scope of the present application.

Claims

1. A method for assessing and disposing threat level of a flying object is characterized by comprising the following steps:

calculating a threat value of the flying object according to the threat factor;

and setting a corresponding treatment process through a trained neural network model according to the threat factor and the threat value of the flying object, wherein the treatment process comprises a primary response, a secondary response and a tertiary response.

2. The method of claim 1, wherein the obtaining threat factors for multiple targets comprises:

3. The method of claim 2, wherein said calculating a threat value for said flying object based on said threat factor comprises:

calculating a threat value for the flying object using:

θ＝λ_GS*100％

f(d)＝1000/d(0<d<30)

f(d)＝1/d(30<d<100)

f(h)＝5h(0<h<50)

f(v1)＝2v1(0<v1<30)

f(v2)＝5v2(0<v2<30)

f(t)＝t(0<t<10)

4. The method of claim 3, wherein the step of training the neural network model comprises:

and training a neural network model according to the training samples.

5. A device for threat assessment and handling of a flying object, comprising:

6. The apparatus of claim 5, wherein the obtaining module is specifically configured to:

7. The apparatus of claim 5, wherein the computing module is specifically configured to:

calculating a threat value for the flying object using:

θ＝λ_GS*100％

f(d)＝1000/d(0<d<30)

f(d)＝1/d(30<d<100)

f(h)＝5h(0<h<50)

f(v1)＝2v1(0<v1<30)

f(v2)＝5v2(0<v2<30)

f(t)＝t(0<t<10)

8. The apparatus of claim 5, wherein the setting module further comprises:

9. An electronic device comprising a memory and a processor, the memory having stored thereon a computer program, wherein the processor, when executing the computer program, implements the method of any of claims 1-4.

10. A computer-readable storage medium, on which a computer program is stored, which, when being executed by a processor, carries out the steps of the method according to any one of claims 1 to 4.