CN116861779A - Intelligent anti-unmanned aerial vehicle simulation system and method based on digital twinning - Google Patents
Intelligent anti-unmanned aerial vehicle simulation system and method based on digital twinning Download PDFInfo
- Publication number
- CN116861779A CN116861779A CN202310812136.1A CN202310812136A CN116861779A CN 116861779 A CN116861779 A CN 116861779A CN 202310812136 A CN202310812136 A CN 202310812136A CN 116861779 A CN116861779 A CN 116861779A
- Authority
- CN
- China
- Prior art keywords
- aerial vehicle
- unmanned aerial
- equipment
- combat
- simulation
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Pending
Links
- 238000004088 simulation Methods 0.000 title claims abstract description 94
- 238000000034 method Methods 0.000 title claims abstract description 15
- 238000001514 detection method Methods 0.000 claims abstract description 27
- 238000005457 optimization Methods 0.000 claims abstract description 6
- 238000012545 processing Methods 0.000 claims description 42
- 238000007418 data mining Methods 0.000 claims description 13
- 230000000007 visual effect Effects 0.000 claims description 6
- 239000000203 mixture Substances 0.000 claims description 5
- 230000005540 biological transmission Effects 0.000 claims description 4
- 238000009472 formulation Methods 0.000 claims description 4
- 238000009527 percussion Methods 0.000 claims description 4
- 230000003416 augmentation Effects 0.000 claims description 3
- 230000001629 suppression Effects 0.000 claims description 3
- 238000011156 evaluation Methods 0.000 abstract description 4
- 238000005516 engineering process Methods 0.000 description 10
- 230000000694 effects Effects 0.000 description 4
- 238000012986 modification Methods 0.000 description 3
- 230000004048 modification Effects 0.000 description 3
- 238000012800 visualization Methods 0.000 description 3
- 150000001875 compounds Chemical class 0.000 description 2
- 238000010276 construction Methods 0.000 description 2
- 238000011161 development Methods 0.000 description 2
- 230000004927 fusion Effects 0.000 description 2
- 238000013473 artificial intelligence Methods 0.000 description 1
- 238000013528 artificial neural network Methods 0.000 description 1
- 230000009286 beneficial effect Effects 0.000 description 1
- 230000007812 deficiency Effects 0.000 description 1
- 238000010586 diagram Methods 0.000 description 1
- 238000007654 immersion Methods 0.000 description 1
- 238000005065 mining Methods 0.000 description 1
- 238000005381 potential energy Methods 0.000 description 1
- 238000004904 shortening Methods 0.000 description 1
- 238000005728 strengthening Methods 0.000 description 1
- 230000001360 synchronised effect Effects 0.000 description 1
Classifications
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F30/00—Computer-aided design [CAD]
- G06F30/20—Design optimisation, verification or simulation
- G06F30/27—Design optimisation, verification or simulation using machine learning, e.g. artificial intelligence, neural networks, support vector machines [SVM] or training a model
-
- Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
- Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
- Y02T—CLIMATE CHANGE MITIGATION TECHNOLOGIES RELATED TO TRANSPORTATION
- Y02T10/00—Road transport of goods or passengers
- Y02T10/10—Internal combustion engine [ICE] based vehicles
- Y02T10/40—Engine management systems
Landscapes
- Engineering & Computer Science (AREA)
- Physics & Mathematics (AREA)
- Evolutionary Computation (AREA)
- Theoretical Computer Science (AREA)
- Computer Vision & Pattern Recognition (AREA)
- Medical Informatics (AREA)
- Software Systems (AREA)
- Artificial Intelligence (AREA)
- Computer Hardware Design (AREA)
- Geometry (AREA)
- General Engineering & Computer Science (AREA)
- General Physics & Mathematics (AREA)
- Management, Administration, Business Operations System, And Electronic Commerce (AREA)
Abstract
The application provides an intelligent anti-unmanned aerial vehicle simulation system and method based on digital twinning, wherein the intelligent anti-unmanned aerial vehicle simulation system comprises the following components: the application collects battle equipment information through battle field multi-element sensing equipment, deploys the battle equipment information on detection sensing equipment and countering interception equipment, comprehensively senses a real counterunmanned plane battle field, can input information into a twin data body in real time, synchronously generates a high-fidelity virtual counterunmanned plane battle field, completes equipment deployment optimization, equipment efficiency evaluation, comprehensive command battle and other application service requirements, and can be applied to improving the intelligent and transparent battle capability of the counterunmanned plane battle.
Description
[ field of technology ]
The application relates to the technical field of unmanned aerial vehicle simulation, in particular to an intelligent anti-unmanned aerial vehicle simulation system and method based on digital twinning.
[ background Art ]
As early as 2005, people in the field put forward the development direction of unmanned aerial vehicle swarm, and the unmanned aerial vehicle combat technology including the low-cost unmanned aerial vehicle swarm technology and the cross-domain swarm combat technology is greatly developed. The 2020 unmanned plane is applied to military as main combat equipment for the first time; the 2022 unmanned aerial vehicle is widely equipped in a army, deeply blends into a battle system, executes various battle tasks such as battle field reconnaissance, firepower guiding, accurate striking and the like, has the advantages of optimizing the striking chain flow and shortening the closing time of the striking chain, and greatly improves the battle efficiency. Development of unmanned aerial vehicle combat technology also puts higher demands on anti-unmanned aerial vehicle combat.
In the anti-unmanned aerial vehicle combat, single type equipment has hardly dealt with the unmanned aerial vehicle combat technology that is becoming mature now, and this also makes the anti-unmanned aerial vehicle combat progress towards intelligent, pluralism, family system, systemization now, has formed the comprehensive combat mode that collects early warning detection, compound interception, cooperation control as an organic whole.
In the face of a complex and changeable real anti-unmanned aerial vehicle combat environment, the traditional combat simulation technology is difficult to support the combat demands of the anti-unmanned aerial vehicle with complex trend, and the main reason is that the construction of elements of a battlefield by the traditional combat simulation is only designed according to certain actual conditions, depends on artificial ideas, has no direct connection with actual combat conditions, the combat model precision basically depends on knowledge reserves of modeling staff, and the traditional combat simulation is in an off-line simulation mode, the simulation deduction result only provides reference for the actual combat scene, cannot respond in real time according to the combat situation, and is difficult to bring immersion experience to a commander in the simulation combat without paying attention to the enhancement of the simulation deduction picture, so that the combat demands of the anti-unmanned aerial vehicle combat are difficult to meet. The construction of the anti-unmanned aerial vehicle simulation system based on the digital twin technology is beneficial to strengthening information fusion between a real battlefield and a simulation system, and a more comprehensive database is created by means of strong deduction capability of artificial intelligence to assist a commander in making scientific and reasonable command decisions.
Accordingly, there is a need to develop a digital twinning-based intelligent anti-drone simulation system and method that addresses the deficiencies of the prior art to solve or mitigate one or more of the problems described above.
[ application ]
In view of the above, the application provides an intelligent anti-unmanned aerial vehicle simulation system and method based on digital twinning, which collects battle equipment information through battlefield multi-element sensing equipment, deploys the battlefield information on detection sensing equipment and anti-control interception equipment, comprehensively senses a real anti-unmanned aerial vehicle battlefield and can input the information into a twinning data body in real time, synchronously generates a high-fidelity virtual anti-unmanned aerial vehicle battlefield, completes application service requirements such as equipment deployment optimization, equipment efficiency evaluation, comprehensive command battle and the like, and can be applied to improving the intelligent and transparent battle capability of the anti-unmanned aerial vehicle battle.
In one aspect, the application provides an intelligent anti-unmanned aerial vehicle simulation system and method based on digital twinning, wherein the intelligent anti-unmanned aerial vehicle simulation system comprises:
battlefield multielement sensing equipment for collecting battle information in real time;
the data processing module is used for carrying out data processing and analysis on the real-time combat information, providing a target feature library, acquiring enemy unmanned aerial vehicle data according to the target feature library and a data processing and analysis result, and collecting the enemy unmanned aerial vehicle data;
the deduction simulation module is used for performing simulation deduction through enemy unmanned aerial vehicle data, my unmanned aerial vehicle data and real GIS geographic information;
virtual twin anti-unmanned battlefield, carrying out three-dimensional visual display on the virtual twin anti-unmanned battlefield by reality augmentation on a simulation deduction result;
the data mining module is used for carrying out association rule and sequence mode analysis on the simulation deduction result;
the knowledge decision module provides optional combat decisions according to association rules and sequence mode analysis results and sends the combat decisions to the data processing module and the deduction simulation module according to final combat decisions so as to optimally update a target feature library and a virtual twin anti-unmanned plane battlefield;
and the application service terminal is used for enabling the commander to determine a final combat decision according to the optional combat decision.
Aspects and any of the possible implementations described above, further provide an implementation in which the battlefield multi-sensing device is disposed on a detection sensing device and a countering interception device.
Aspects and any of the possible implementations as described above, further providing an implementation, the detection sensing equipment includes unmanned aerial vehicle signal detection equipment, photoelectric detection equipment, and radar detection equipment.
Aspects and any of the possible implementations described above, further providing an implementation, the countering interception equipment includes a fraud suppression equipment, a directional energy interception percussion equipment, and a fire percussion equipment.
Aspects and any one of the possible implementations described above, further providing an implementation, the combat information including enemy objective information and own equipment information.
In the aspects and any possible implementation manner as described above, there is further provided an implementation manner, where the deduction simulation module deducts that the enemy unmanned aerial vehicle data is an enemy target model and that the my unmanned aerial vehicle data is a my equipment model.
In the aspects and any possible implementation manner described above, there is further provided an implementation manner, where the data processing module has a function of autonomously identifying a target type, and obtains the enemy unmanned aerial vehicle equipment information through model information and data processing and analysis results of corresponding targets in the target feature library, and at the same time, the data processing module also receives and gathers the enemy unmanned aerial vehicle equipment information.
Aspects and any one of the possible implementations described above, further providing an implementation, the final combat decision including combat strategy formulation, equipment optimization deployment, equipment effectiveness assessment, and situational comprehensive analysis.
The aspects and any possible implementation manner described above further provide an implementation manner, wherein the battlefield multielement sensing device completes information transmission through a cable, a 5G network and a Beidou mode, and the virtual twin unmanned battlefield, the data processing module, the deduction simulation module, the data mining module, the knowledge decision module and the application service terminal are respectively communicated with each other by means of the inside of a computer.
The aspects and any possible implementation manner as described above further provide a digital twinning-based intelligent anti-unmanned aerial vehicle simulation method, the intelligent anti-unmanned aerial vehicle simulation method comprising the following steps:
s1: collecting combat information in real time;
s2: performing data processing and analysis on the real-time combat information, providing a target feature library, acquiring enemy unmanned aerial vehicle data according to the target feature library and a data processing and analysis result, and collecting the enemy unmanned aerial vehicle data;
s3: simulation deduction is carried out through enemy unmanned aerial vehicle data, my unmanned aerial vehicle data and real GIS geographic information;
s4: carrying out three-dimensional visual display on a virtual twin anti-unmanned aerial vehicle battlefield through reality enhancement on a simulation deduction result;
s5: carrying out association rule and sequence pattern analysis on the simulation deduction result;
s6: providing optional combat decisions according to association rules and sequence mode analysis results, and sending the combat decisions to a data processing module and a deduction simulation module according to final combat decisions so as to optimize and update a target feature library and a virtual twin anti-unmanned plane battlefield;
s7: the commander determines the final combat decision according to the optional combat decision.
Compared with the prior art, the application can obtain the following technical effects:
the application builds a high fidelity virtual twin anti-unmanned plane battlefield based on the real battlefield geographic data information based on the digital twin technology, combines the battlefield real-time operation data, realizes the fusion of the real battlefield and the simulation deduction, has the capability of three-dimensionally displaying the battlefield state potential energy in real time, and achieves the effect of transparentizing the battlefield; meanwhile, the intelligent combat capability is provided for the system, the type and threat of an attack target can be autonomously judged, combat decision making is realized according to the equipment capability of the host, and compared with the traditional simulation deduction system, the intelligent combat decision making system can be applied to actual combat, improve the combat control capability and decision making capability of commanders, and enhance the combat capability of the anti-unmanned aerial vehicle.
Of course, it is not necessary for any of the products embodying the application to achieve all of the technical effects described above at the same time.
[ description of the drawings ]
In order to more clearly illustrate the technical solutions of the embodiments of the present application, the drawings that are needed in the embodiments will be briefly described below, and it is obvious that the drawings in the following description are only some embodiments of the present application, and that other drawings can be obtained according to these drawings without inventive effort for a person skilled in the art.
Fig. 1 is a block diagram of an intelligent anti-unmanned aerial vehicle simulation system based on digital twinning according to an embodiment of the present application.
Wherein, in the figure:
1. battlefield multielement sensing equipment; 2. a data processing module; 3. a deduction simulation module; 4. a data mining module; 5. virtual twinning anti-unmanned battlefield; 6. a knowledge decision module; 7. and (5) applying the service terminal.
[ detailed description ] of the application
For a better understanding of the technical solution of the present application, the following detailed description of the embodiments of the present application refers to the accompanying drawings.
It should be understood that the described embodiments are merely some, but not all, embodiments of the application. All other embodiments, which can be made by those skilled in the art based on the embodiments of the application without making any inventive effort, are intended to be within the scope of the application.
The terminology used in the embodiments of the application is for the purpose of describing particular embodiments only and is not intended to be limiting of the application. As used in this application and the appended claims, the singular forms "a," "an," and "the" are intended to include the plural forms as well, unless the context clearly indicates otherwise.
The application provides an intelligent anti-unmanned aerial vehicle simulation system and method based on digital twinning, wherein the intelligent anti-unmanned aerial vehicle simulation system comprises the following components:
battlefield multielement sensing equipment for collecting battle information in real time;
the data processing module is used for carrying out data processing and analysis on the real-time combat information, providing a target feature library, acquiring enemy unmanned aerial vehicle data according to the target feature library and a data processing and analysis result, and collecting the enemy unmanned aerial vehicle data;
the deduction simulation module is used for performing simulation deduction through enemy unmanned aerial vehicle data, my unmanned aerial vehicle data and real GIS geographic information;
virtual twin anti-unmanned battlefield, carrying out three-dimensional visual display on the virtual twin anti-unmanned battlefield by reality augmentation on a simulation deduction result;
the data mining module is used for carrying out association rule and sequence mode analysis on the simulation deduction result;
the knowledge decision module provides optional combat decisions according to association rules and sequence mode analysis results and sends the combat decisions to the data processing module and the deduction simulation module according to final combat decisions so as to optimally update a target feature library and a virtual twin anti-unmanned plane battlefield;
and the application service terminal is used for enabling the commander to determine a final combat decision according to the optional combat decision.
The battlefield multielement sensing device is arranged on the detection sensing equipment and the countercheck interception equipment. The detection sensing equipment comprises unmanned aerial vehicle signal detection equipment, photoelectric detection equipment and radar detection equipment. The countering interceptor apparatus includes a fraud jamming fixture, a directional energy interceptor striking apparatus, and a fire striking apparatus. The combat information includes enemy objective information and own equipment information. The deduction simulation module deducts the enemy unmanned aerial vehicle data as an enemy target model and the My unmanned aerial vehicle data as a My equipment model.
The data processing module has the function of autonomously identifying the type of the target, acquires the equipment information of the enemy unmanned aerial vehicle through the model information and the data processing and analysis results of the corresponding target in the target feature library, and receives and gathers the equipment information of the enemy unmanned aerial vehicle.
The final combat decision comprises combat strategy formulation, equipment optimization deployment, equipment efficiency evaluation and situation comprehensive analysis.
The battlefield multielement sensing device completes information transmission in a cable, a 5G network and Beidou mode, and the virtual twin anti-unmanned battlefield, the data processing module, the deduction simulation module, the data mining module, the knowledge decision module and the application service terminal are respectively interconnected and intercommunicated by means of the inside of a computer.
The application also provides an intelligent anti-unmanned aerial vehicle simulation method based on digital twinning, which comprises the following steps:
s1: collecting combat information in real time;
s2: performing data processing and analysis on the real-time combat information, providing a target feature library, acquiring enemy unmanned aerial vehicle data according to the target feature library and a data processing and analysis result, and collecting the enemy unmanned aerial vehicle data;
s3: simulation deduction is carried out through enemy unmanned aerial vehicle data, my unmanned aerial vehicle data and real GIS geographic information;
s4: carrying out three-dimensional visual display on a virtual twin anti-unmanned aerial vehicle battlefield through reality enhancement on a simulation deduction result;
s5: carrying out association rule and sequence pattern analysis on the simulation deduction result;
s6: providing optional combat decisions according to association rules and sequence mode analysis results, and sending the combat decisions to a data processing module and a deduction simulation module according to final combat decisions so as to optimize and update a target feature library and a virtual twin anti-unmanned plane battlefield;
s7: the commander determines the final combat decision according to the optional combat decision.
As shown in fig. 1, the application provides an intelligent anti-unmanned aerial vehicle simulation system based on digital twinning, which comprises battlefield multielement sensing equipment, a virtual twinning anti-unmanned battlefield, a data processing module, a deduction simulation module, a data mining module, a knowledge decision module and an application service terminal;
the battlefield multielement sensing equipment acquires battlefield information in real time and transmits the battlefield information to the data processing module, and then a virtual twin anti-unmanned aerial vehicle battlefield is generated through the simulation deduction module, so that a commander is visually assisted to comprehensively control the battlefield; the data generated by the simulation deduction are synchronously transmitted to the data mining module, and then the combat decision is intelligently generated by the knowledge decision module.
The battlefield multielement sensing device completes information transmission in a cable, a 5G network, beidou and other modes, and all the other parts rely on the inside of a computer to realize interconnection and intercommunication of data.
In a specific embodiment, battlefield multi-element sensing equipment is responsible for collecting and collecting battlefield information and is mainly deployed on detection sensing equipment and countercheck equipment, wherein the detection sensing equipment comprises unmanned aerial vehicle signal detection equipment, photoelectric detection equipment, radar detection equipment and the like, the countercheck equipment comprises deception jamming suppression equipment, directional energy interception striking equipment, fire striking equipment and the like, and transmitted information comprises enemy target information and own equipment information and comprehensively senses battlefield information.
In a specific embodiment, the data processing module has a function of autonomously identifying the type of the target, can call the model information of the corresponding target in the target feature library and transmit the model information to the deduction simulation module, and meanwhile, the data processing module also receives and gathers the working information of the my equipment and transmits the working information to the deduction simulation module together with the model of the my equipment.
In a specific embodiment, the simulation deduction module can be combined with the real GIS geographic information of the battlefield, the my equipment model and the enemy target model to quickly construct a twin simulation battlefield environment synchronous with the real battlefield, and the three-dimensional visualization of the virtual twin anti-unmanned aerial vehicle battlefield is realized through the reality enhancement module, so that a commander is visually assisted to comprehensively control the battlefield.
In a specific embodiment, data generated by simulation deduction are synchronously transmitted to a data mining module for association rule and sequence pattern analysis, and then knowledge decision-making modules are used for intelligently assisting commanders in completing the making of combat decisions, and the data generated by the knowledge decision-making modules are synchronously transmitted to a data processing module and a deduction simulation module for optimizing and updating a target feature library and a virtual twin anti-unmanned plane battlefield environment.
In a specific embodiment, a commander can complete customized services such as combat strategy formulation, equipment optimization deployment, equipment efficiency evaluation, situation comprehensive analysis and the like through an application service terminal.
The data processing module, the deduction simulation module, the data mining module and the knowledge decision module are integrated into a twin data body of the system, and are core data flow components of the system.
Example 1
The intelligent anti-unmanned aerial vehicle simulation system based on digital twinning is different from the traditional simulation system, can access real-time data of the combat equipment, achieves the function of real-time controlling the battlefield situation and intelligently making the combat strategy, and has the deduction capability of the traditional simulation system and the instant anti-unmanned aerial vehicle combat capability.
Taking an anti-unmanned aerial vehicle fight with Beijing five rings as a range as an example, when a group of unidentified flying object targets are intruded into the area, firstly, the unmanned aerial vehicle signal detection equipment judges the general azimuth of the targets, then the radar detection equipment is guided to position specific position information of the targets, finally, the photoelectric detection equipment accurately locks the targets, and information such as the types, the number, the azimuth, the height, the speed, the pitch angle and the like of the targets is transmitted to a system data processing module.
The data processing module is used for preliminarily judging the threat level of the target by comparing the target feature library through the neural network target system according to the type and the number of the targets, calling the target unmanned aerial vehicle model and transmitting information to the simulation deduction module, and meanwhile, the data processing module is also used for receiving and collecting the working information of the equipment on the my side, and transmitting the working information to the deduction simulation module together with the model of the equipment on the my side.
The simulation deduction module invokes three-dimensional GIS geographic data information of the Beijing five-ring range from a geographic information database, combines the information of the my equipment to quickly and virtually form a battlefield environment, deducts a target situation according to the information of the target unmanned aerial vehicle azimuth, altitude, speed, pitch angle and the like, obtains the possible path azimuth of the target unmanned aerial vehicle, constructs a virtual twin anti-unmanned aerial vehicle battlefield with virtual and real synchronization, realizes three-dimensional visualization of the virtual twin anti-unmanned aerial vehicle battlefield based on the reality enhancement module, and finally presents the three-dimensional visualization to the application service terminal.
Meanwhile, target situation information generated by simulation deduction is transmitted to a data mining module, equipment tactics and behavior rule data are combined through a correlation rule and sequence mode mining system, the configuration and the combat mode of the equipment are mined and optimized, the data are transmitted to a knowledge decision module, the expert knowledge map is controlled by the optimized equipment, the potential threat possibility of the target unmanned plane is judged and evaluated through a decision support system, intelligent combat decision generation is completed by combining the situation of the equipment of the user, and finally the intelligent combat decision is presented to an application service terminal.
And a commander realizes comprehensive control of battlefield situations of the Beijing five-ring anti-unmanned aerial vehicle by means of the application service terminal, judges and selects an optimal countercheck decision, and schedules the my countercheck device to carry out compound treatment on the unmanned aerial vehicle target.
And acquiring the fight information of the my countering equipment through the multielement sensing equipment arranged on the countering device, transmitting the fight information of the my countering equipment and the latest detection equipment information to the data processing module, updating the battlefield of the virtual twin counterunmanned aerial vehicle through the deduction simulation module, re-analyzing the battlefield situation and optimizing the strategy decision through the data mining module and the knowledge decision module until the target threat is eliminated, and completing the counterunmanned aerial vehicle fight of the Beijing five-ring.
The intelligent anti-unmanned aerial vehicle simulation system and the intelligent anti-unmanned aerial vehicle simulation method based on digital twinning provided by the embodiment of the application are described in detail. The above description of embodiments is only for aiding in the understanding of the method of the present application and its core ideas; meanwhile, as those skilled in the art will have variations in the specific embodiments and application scope in accordance with the ideas of the present application, the present description should not be construed as limiting the present application in view of the above.
Certain terms are used throughout the description and claims to refer to particular components. Those of skill in the art will appreciate that a hardware manufacturer may refer to the same component by different names. The description and claims do not take the form of an element differentiated by name, but rather by functionality. As referred to throughout the specification and claims, the terms "comprising," including, "and" includes "are intended to be interpreted as" including/comprising, but not limited to. By "substantially" is meant that within an acceptable error range, a person skilled in the art is able to solve the technical problem within a certain error range, substantially achieving the technical effect. The description hereinafter sets forth a preferred embodiment for practicing the application, but is not intended to limit the scope of the application, as the description is given for the purpose of illustrating the general principles of the application. The scope of the application is defined by the appended claims.
It should also be noted that the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a product or system that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such product or system. Without further limitation, an element defined by the phrase "comprising one … …" does not exclude the presence of other like elements in a commodity or system comprising such elements.
It should be understood that the term "and/or" as used herein is merely one relationship describing the association of the associated objects, meaning that there may be three relationships, e.g., a and/or B, may represent: a exists alone, A and B exist together, and B exists alone. In addition, the character "/" herein generally indicates that the front and rear associated objects are an "or" relationship.
While the foregoing description illustrates and describes the preferred embodiments of the present application, it is to be understood that the application is not limited to the forms disclosed herein, but is not to be construed as limited to other embodiments, and is capable of numerous other combinations, modifications and environments and is capable of changes or modifications within the scope of the inventive concept as expressed herein, either as a result of the foregoing teachings or as a result of the knowledge or technology of the relevant art. And that modifications and variations which do not depart from the spirit and scope of the application are intended to be within the scope of the appended claims.
Claims (10)
1. Digital twinning-based intelligent anti-unmanned aerial vehicle simulation system, which is characterized by comprising:
battlefield multielement sensing equipment for collecting battle information in real time;
the data processing module is used for carrying out data processing and analysis on the real-time combat information, providing a target feature library, acquiring enemy unmanned aerial vehicle data according to the target feature library and a data processing and analysis result, and collecting the enemy unmanned aerial vehicle data;
the deduction simulation module is used for performing simulation deduction through enemy unmanned aerial vehicle data, my unmanned aerial vehicle data and real GIS geographic information;
virtual twin anti-unmanned battlefield, carrying out three-dimensional visual display on the virtual twin anti-unmanned battlefield by reality augmentation on a simulation deduction result;
the data mining module is used for carrying out association rule and sequence mode analysis on the simulation deduction result;
the knowledge decision module provides optional combat decisions according to association rules and sequence mode analysis results and sends the combat decisions to the data processing module and the deduction simulation module according to final combat decisions so as to optimally update a target feature library and a virtual twin anti-unmanned plane battlefield;
and the application service terminal is used for enabling the commander to determine a final combat decision according to the optional combat decision.
2. The intelligent anti-unmanned aerial vehicle simulation system of claim 1, wherein the battlefield multi-component sensing device is disposed on a detection sensing equipment and a countering interception equipment.
3. The intelligent anti-drone simulation system of claim 2, wherein the detection sensing equipment includes drone signal detection equipment, photoelectric detection equipment, and radar detection equipment.
4. The intelligent anti-unmanned aerial vehicle simulation system of claim 2, wherein the countering interception equipment comprises a fraud suppression equipment, a directional energy interception percussion equipment, and a fire percussion equipment.
5. The intelligent anti-drone simulation system of claim 2, wherein the combat information includes enemy objective information and own equipment information.
6. The intelligent anti-drone simulation system of claim 1, wherein the enemy drone data deduced by the deduction simulation module is an enemy target model and the my drone data is a my equipment model.
7. The intelligent anti-unmanned aerial vehicle simulation system of claim 1, wherein the data processing module has a function of autonomously identifying the type of the target, obtains enemy unmanned aerial vehicle equipment information through model information and data processing and analysis results of corresponding targets in the target feature library, and receives and gathers the enemy unmanned aerial vehicle equipment information.
8. The intelligent anti-drone simulation system of claim 1, wherein the final combat decision comprises combat strategy formulation, equipment optimization deployment, equipment effectiveness assessment, and situational comprehensive analysis.
9. The intelligent anti-unmanned aerial vehicle simulation system according to claim 1, wherein the battlefield multielement sensing device completes information transmission through a cable, a 5G network and a Beidou mode, and data interconnection and intercommunication are achieved among the virtual twin anti-unmanned battlefield, the data processing module, the deduction simulation module, the data mining module, the knowledge decision module and the application service terminal by means of the inside of a computer.
10. An intelligent anti-unmanned aerial vehicle simulation method based on digital twinning, which is realized by the intelligent anti-unmanned aerial vehicle simulation system according to one of the claims 1 to 9, and is characterized in that the intelligent anti-unmanned aerial vehicle simulation method comprises the following steps:
s1: collecting combat information in real time;
s2: performing data processing and analysis on the real-time combat information, providing a target feature library, acquiring enemy unmanned aerial vehicle data according to the target feature library and a data processing and analysis result, and collecting the enemy unmanned aerial vehicle data;
s3: simulation deduction is carried out through enemy unmanned aerial vehicle data, my unmanned aerial vehicle data and real GIS geographic information;
s4: carrying out three-dimensional visual display on a virtual twin anti-unmanned aerial vehicle battlefield through reality enhancement on a simulation deduction result;
s5: carrying out association rule and sequence pattern analysis on the simulation deduction result;
s6: providing optional combat decisions according to association rules and sequence mode analysis results, and sending the combat decisions to a data processing module and a deduction simulation module according to final combat decisions so as to optimize and update a target feature library and a virtual twin anti-unmanned plane battlefield;
s7: the commander determines the final combat decision according to the optional combat decision.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202310812136.1A CN116861779A (en) | 2023-07-04 | 2023-07-04 | Intelligent anti-unmanned aerial vehicle simulation system and method based on digital twinning |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202310812136.1A CN116861779A (en) | 2023-07-04 | 2023-07-04 | Intelligent anti-unmanned aerial vehicle simulation system and method based on digital twinning |
Publications (1)
| Publication Number | Publication Date |
|---|---|
| CN116861779A true CN116861779A (en) | 2023-10-10 |
Family
ID=88228097
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202310812136.1A Pending CN116861779A (en) | 2023-07-04 | 2023-07-04 | Intelligent anti-unmanned aerial vehicle simulation system and method based on digital twinning |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN116861779A (en) |
Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN117574693A (en) * | 2024-01-17 | 2024-02-20 | 江西联创精密机电有限公司 | Method and device for generating simulation training target data of anti-unmanned aerial vehicle |
-
2023
- 2023-07-04 CN CN202310812136.1A patent/CN116861779A/en active Pending
Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN117574693A (en) * | 2024-01-17 | 2024-02-20 | 江西联创精密机电有限公司 | Method and device for generating simulation training target data of anti-unmanned aerial vehicle |
| CN117574693B (en) * | 2024-01-17 | 2024-04-16 | 江西联创精密机电有限公司 | Method and device for generating simulation training target data of anti-unmanned aerial vehicle |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN113495578B (en) | Digital twin training-based cluster track planning reinforcement learning method | |
| KR101537759B1 (en) | Simulator for ground unmaned system, and its operating method | |
| CN101118654B (en) | Machine vision computer simulation emulation system based on sensor network | |
| CN106530897A (en) | Flight simulation training device | |
| CN109740283A (en) | Autonomous multiple agent confronting simulation method and system | |
| CN116861779A (en) | Intelligent anti-unmanned aerial vehicle simulation system and method based on digital twinning | |
| CN105893656A (en) | Platform-level Agent interactive simulation-oriented army unit combat test method | |
| CN111766901A (en) | Multi-unmanned aerial vehicle cooperative target distribution attack method | |
| CN111598232B (en) | Method for estimating complex jog space cone target parameters by using deep learning convolutional neural network | |
| CN111488992A (en) | Simulator adversary reinforcing device based on artificial intelligence | |
| Liu et al. | Task assignment in ground-to-air confrontation based on multiagent deep reinforcement learning | |
| Cui et al. | UAV target tracking algorithm based on task allocation consensus | |
| CN115951695A (en) | Dynamic tactical control domain resolving method based on three-party game in air combat simulation environment | |
| CN113110110B (en) | Semi-physical simulation system for missile defense and attack confrontation and implementation method thereof | |
| Schlecht et al. | Decentralized Search by Unmanned Air Vehicles Using Local Communication. | |
| CN114372603A (en) | Pigeon-group-imitated multi-learning-intelligence unmanned target drone collaborative route dynamic planning method | |
| CN109597309A (en) | A kind of motor-driven synchronous method of target drone and system of actual situation combination | |
| CN110095751A (en) | The target localization and tracking system of data-driven modeling is realized based on Method Using Relevance Vector Machine | |
| CN114047783A (en) | Unmanned aerial vehicle system and unmanned aerial vehicle simulation system | |
| Ming Chen et al. | An agent‐based simulation for multi‐UAVs coordinative sensing | |
| Li et al. | Multi-domain cooperative action planning strategy based on reinforcement learning | |
| Ji et al. | Research on simulation experiment of underwater cluster multi-source information fusion | |
| Ma et al. | Mission Capability Evaluation Testing System for Unmanned Aerial Vehicle Swarm | |
| KR102655962B1 (en) | Remote Drone Tactical Training System | |
| CN112527011B (en) | Construction method of unified framework of guidance technology in formation collaboration |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication |