Anti-unmanned aerial vehicle system performance evaluation simulation method, system and device based on ABMS and medium

Abstract

The invention discloses an anti-unmanned aerial vehicle system performance evaluation simulation method, system and device based on an ABMS and a medium. The method comprises the steps that an anti-unmanned aerial vehicle cooperative combat system is constructed; according to different roles and functions in the anti-unmanned aerial vehicle cooperative combat system, constructing corresponding Agent models; defining performance, functions and behavior rules of each Agent model and an interaction mode between the Agent models; obtaining a to-be-simulated task scene and corresponding performance data and performance indexes; performance data are input into all the Agent models to execute the task scene to be simulated, a simulation result is obtained, the simulation result is evaluated based on the efficiency index, and an efficiency evaluation result corresponding to the task scene to be simulated is obtained. According to the method, the performance of internal equipment of the anti-unmanned aerial vehicle system, the overall mission task efficiency of the system and the internal emergence efficiency of the system can be obtained at the same time, so that the efficiency evaluation of the anti-unmanned aerial vehicle system is more scientific and reasonable.

Description

Technical Field

[0001] The present invention belongs to the technical field of unmanned aerial vehicle systems, and in particular relates to an anti-unmanned aerial vehicle system effectiveness evaluation simulation method, system, equipment and medium based on ABMS. Background Art

[0002] Agent-based modeling and simulation (ABMS) is a method for modeling a system composed of independent, autonomous, and interacting "agents". The method originated from the idea of ​​agent-based modeling (ABM). In the 1980s, researchers began to use ABM to simulate complex systems, such as urban transportation, ecosystems, and economic markets. These models are usually based on simple rules and simulate the interactions between individuals to show the behavior of the system as a whole. With the advancement of computer technology, the development of ABM has accelerated rapidly. In the 1990s, the method was widely used in various fields, such as social sciences, ecology, economics, epidemiology, etc.

[0003] However, the existing simulation methods based on ABMS focus more on the interaction relationship within the system, and the consideration of a single equipment agent is mostly focused on the agent's behavior logic, with less consideration of equipment performance. At the same time, there is no mature effectiveness evaluation simulation technology application in the field of anti-UAV. Summary of the invention

[0004] The purpose of the present invention is to provide an ABMS-based anti-UAV system effectiveness evaluation simulation method, system, equipment and medium to solve the problems existing in the above-mentioned prior art.

[0005] To achieve the above objectives, the present invention provides an anti-UAV system effectiveness evaluation simulation method based on ABMS, comprising:

[0006] Construct an anti-UAV collaborative combat system and the tasks and processes of the anti-UAV collaborative combat system for corresponding scenarios;

[0007] According to the different roles and functions in the anti-UAV collaborative combat system, the corresponding Agent model is constructed;

[0008] Define the performance, functions, behavior rules of each Agent model and the interaction mode between Agent models;

[0009] Obtain the task scenario to be simulated and the corresponding performance data and efficiency indicators;

[0010] Input the performance data into each of the Agent models to execute the task scenario to be simulated, obtain the simulation result, evaluate the simulation result based on the performance index, and obtain the performance evaluation result corresponding to the task scenario to be simulated.

[0011] Optionally, the UAV collaborative combat system includes a layered collaborative system and a distributed collaborative system.

[0012] Optionally, the hierarchical collaborative system specifically includes:

[0013] Use radar and radio monitoring equipment to conduct routine monitoring, identify targets and send target intelligence to the command and control center;

[0014] Use the command and control center to perform information fusion and threat assessment on the received target intelligence, and assign strike missions to optoelectronic drones based on the assessment results;

[0015] Control the optoelectronic drone to conduct a preliminary attack on the target based on the strike mission. If it fails, keep tracking and feedback the situation data to the command and control center;

[0016] Based on the feedback situation data and real-time tracking data, strike drones are used to carry out precise strikes on targets, and air defense vehicles are controlled to intercept in the second-level warning area.

[0017] Optionally, the distributed collaborative system specifically includes:

[0018] Use radar, radio monitoring equipment and optoelectronic equipment to monitor the target area on a regular basis, identify the target and send target intelligence to the command and control center;

[0019] Use the command and control center to conduct information fusion and threat assessment on the received target intelligence, and assign strike missions to the navigation decoy equipment, jammers and air defense vehicles closest to the target based on the assessment results;

[0020] After receiving the mission, the navigation decoy equipment, omnidirectional jamming equipment and air defense vehicles attack the target in turn.

[0021] Optionally, the construction process of each Agent model specifically includes:

[0022] An agent model is established based on three levels: performance layer, behavior layer, and communication layer. The performance layer includes the physical properties of each equipment agent in the anti-UAV collaborative combat system, the behavior layer includes the behavioral characteristics of each equipment agent in the anti-UAV collaborative combat system, and the communication layer includes the logical interaction relationship of each equipment agent in the anti-UAV collaborative combat system.

[0023] An ABMS-based anti-UAV system effectiveness evaluation simulation system includes:

[0024] The anti-UAV system task construction module is used to build the anti-UAV collaborative combat system and the anti-UAV collaborative combat system tasks and processes for the corresponding scenarios;

[0025] The Agent model building module is used to build corresponding Agent models according to different roles and functions in the anti-UAV collaborative combat system; define the performance, function, behavior rules of each Agent model and the interaction mode between Agent models;

[0026] The simulation evaluation module is used to obtain the task scenario to be simulated and the corresponding performance data and efficiency indicators, input the performance data into each Agent model to execute the task scenario to be simulated, obtain the simulation result, evaluate the simulation result based on the efficiency indicator, and obtain the efficiency evaluation result corresponding to the task scenario to be simulated.

[0027] An electronic device comprises a memory and a processor, wherein the memory is used to store a computer program, and the processor runs the computer program to enable the electronic device to execute the ABMS-based anti-UAV system effectiveness evaluation simulation method.

[0028] A computer-readable storage medium stores a computer program, which, when executed by a processor, implements the ABMS-based anti-UAV system effectiveness evaluation simulation method.

[0029] The technical effects of the present invention are:

[0030] The present invention defines a commonly used anti-UAV system architecture, and can comprehensively consider system nodes and organizational relationships when constructing a simulation model. Therefore, when evaluating the effectiveness of the anti-UAV system, the performance of the anti-UAV system's internal equipment, the system's overall mission effectiveness, and the system's internal emergent effectiveness can be obtained at the same time, making the effectiveness evaluation of the anti-UAV system more scientific and reasonable. BRIEF DESCRIPTION OF THE DRAWINGS

[0031] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings required for use in the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0032] The drawings constituting a part of the present application are used to provide a further understanding of the present application. The illustrative embodiments and descriptions of the present application are used to explain the present application and do not constitute an improper limitation on the present application. In the drawings:

[0033] Figure 1Schematic diagram of the Agent conceptual model in the embodiment of the present invention;

[0034] Figure 2 Schematic diagram of the structure of the anti-UAV system and the adversary Agent model in an embodiment of the present invention;

[0035] Figure 3 A flow chart for constructing a performance evaluation simulation model in an embodiment of the present invention;

[0036] Figure 4 4 is a simulation evaluation flow chart in an embodiment of the present invention. DETAILED DESCRIPTION

[0037] Various exemplary embodiments of the present invention will now be described in detail. This detailed description should not be considered as limiting the present invention, but should be understood as a more detailed description of certain aspects, features, and embodiments of the present invention.

[0038] It should be understood that the terms described in the present invention are only for describing special embodiments and are not intended to limit the present invention. In addition, for the numerical range in the present invention, it should be understood that each intermediate value between the upper and lower limits of the scope is also specifically disclosed. Each smaller range between the intermediate value in any stated value or stated range and any other stated value or intermediate value in the described range is also included in the present invention. The upper and lower limits of these smaller ranges can be independently included or excluded in the scope.

[0039] It will be apparent to those skilled in the art that various modifications and variations may be made to the specific embodiments of the present invention description without departing from the scope or spirit of the present invention. Other embodiments derived from the present invention description will be apparent to those skilled in the art. The present application description and examples are exemplary only.

[0040] The words “include,” “including,” “have,” “contain,” etc. used in this article are open-ended terms, meaning including but not limited to.

[0041] It should be noted that, in the absence of conflict, the embodiments and features in the embodiments of the present application can be combined with each other. The present application will be described in detail below with reference to the accompanying drawings and in combination with the embodiments.

[0042] Embodiment 1

[0043] like Figure 1 - Figure 4As shown, in this embodiment, an anti-UAV system effectiveness evaluation simulation method based on ABMS is provided, including: constructing an anti-UAV collaborative combat system and anti-UAV collaborative combat system tasks and processes for corresponding scenarios; constructing corresponding Agent models according to different roles and functions in the anti-UAV collaborative combat system; defining the performance, function, behavior rules of each Agent model and the interaction mode between each Agent model; obtaining the task scenario to be simulated and the corresponding performance data and effectiveness index; inputting the performance data into each Agent model to execute the task scenario to be simulated, obtaining the simulation result, evaluating the simulation result based on the effectiveness index, and obtaining the effectiveness evaluation result corresponding to the task scenario to be simulated.

[0044] In the current background technology, the effectiveness evaluation simulation method mainly considers the construction of the internal structure of the equipment and ignores the interaction between the system equipment; while the simulation method based on ABMS mainly focuses on the interaction relationship within the system, and the consideration of a single equipment agent is mostly concentrated on the agent's behavior logic, with less consideration of equipment performance. At the same time, in the field of anti-UAV, there is no mature application of effectiveness evaluation simulation technology. Therefore, the purpose of the present invention is to provide an anti-UAV system effectiveness evaluation simulation method based on ABMS, which combines the performance model construction of a single agent with the overall behavior logic interaction construction to achieve a more practical and scientific effectiveness evaluation of the anti-UAV system.

[0045] In the application of the anti-UAV system effectiveness evaluation method based on ABMS, the anti-UAV equipment Agent is required to have the following characteristics:

[0046] (1) Independence, also known as autonomy. In the structure of the system, each component unit is a complete system equipment with independent functional performance. It can be used in conjunction with other equipment in the task environment, or it can be used independently without relying on other equipment. The equipment agent should also have independent and complete configuration functions, and operate according to its own logical rules during simulation operation, without relying on the external environment or other operations;

[0047] (2) Intelligence, also known as responsiveness. As the basic component of the system, the equipment agent is an abstract simulation of each actual equipment. It has the ability to perceive, make decisions or execute. Therefore, it also has the ability to receive external information and respond according to its own logical rules. It can even show some intelligent characteristics.

[0048] (3) Interactivity, also known as sociality. In physical equipment, each device has communication capabilities, thereby achieving various synergistic effects. Equipment agents also have communication capabilities. Different agents communicate with each other through this communication capability and constantly adjust their behaviors, thus showing the social characteristics of agents.

[0049] The system agent conceptual model including the above agent characteristics is as follows Figure 1 shown.

[0050] After setting the Agent performance parameters, the simulation model is run. Under the action of the emergent relationship within the system, the running results of the Agent simulation model will produce changes with complex characteristics, that is, it may produce an effect of 1+1>2, or it may produce an effect of 1+1<2. By observing and analyzing the running results of the Agent simulation model and comparing them with the modification of the performance parameters, it is possible to understand and predict the emergence of the system. The technical solution of the present invention is to understand and predict the emergence relationship of the system by observing the performance and efficiency results, and thereby achieve the result of improving efficiency.

[0051] Anti-UAV collaborative combat system: For the anti-UAV system, regulations are set for the equipment contained within it and the forms of collaboration of the tasks performed, including hierarchical collaboration and distributed collaboration.

[0052] (1) Hierarchical collaboration

[0053] 1. Radar and radio monitoring equipment conduct regular monitoring of the target area, identify targets entering the area, and send information to the command and control center;

[0054] 2. After receiving the intelligence, the command and control center integrates the received information and makes a threat assessment. When it is determined that the target is threatening, the task is assigned to the optoelectronic UAV;

[0055] 3. After receiving the mission, the optoelectronic UAV moves from its current position to the target position for further perception. When it senses the target, it launches a preliminary attack on it. If it fails, it reports the situation to the command and control center and keeps tracking the target. If it succeeds, it returns to the command and control center.

[0056] 4. If the electro-optical drone is unsuccessful, the command and control center will receive the information and assign the task to the strike drone;

[0057] 5. After receiving the mission, the strike drone will move from its current position to the target position and strike the target. If the ammunition it carries is exhausted or the enemy target is shot down, it will return to the command and control platform;

[0058] 6. If the target enters the second-level warning area, it will be intercepted by an air defense vehicle.

[0059] (2) Distributed Collaboration

[0060] 1. Radar, radio monitoring equipment and optoelectronic equipment conduct regular monitoring of the target area, identify targets entering the area, and send information to the command and control center;

[0061] 2. After receiving the intelligence, the command and control center integrates the information received and makes a threat assessment. When it is determined that the target is a threat, the task is assigned to the navigation decoy equipment, jammer equipment and air defense vehicle closest to the target;

[0062] 3. After receiving the mission, the navigation decoy equipment, omnidirectional jamming equipment and air defense vehicles will attack the target in turn.

[0063] In summary, the method of using the ABMS method to evaluate the effectiveness of the anti-UAV system includes the following steps:

[0064] 1. According to the conceptual model of the anti-UAV system, determine the type, performance and function of the Agent to be built, and obtain the simulation Agent model;

[0065] 2. According to the conceptual model of the anti-UAV system, determine the simulation task environment and the interaction relationship between agents, and obtain the simulation task scenario of the anti-UAV system;

[0066] 3. According to the conceptual model and index system of the anti-UAV system, determine the input performance data and output efficiency data of the simulation mission scenario, as well as the range of variation of the input performance data;

[0067] 4. Input different performance data, run simulation scenarios, obtain the final performance evaluation results, and conduct in-depth analysis.

[0068] The main content of the anti-UAV system effectiveness evaluation method based on ABMS in this embodiment is to establish an agent-based effectiveness evaluation scenario model, including the construction of the internal logical structure of the agent, the interaction between the agent and the external environment, and the construction of the logical interaction relationship between agents. Therefore, the present invention proposes to establish an agent model from three levels: performance layer, behavior layer, and communication layer. Figure 2 As shown, the internal logical structure of the Agent, the logical interaction relationship with the environment and each other are hierarchically constructed, and the physical characteristics, behavioral characteristics and communication characteristics of the equipment are reflected.

[0069] Among them, the performance layer refers to the physical properties of each equipment agent, including detection range, detection probability, response time, etc.; the behavior layer refers to the behavioral characteristics of each equipment agent, including its own state and response to the external environment. In this scenario, its main meaning is the various dynamic behaviors made to the agent of the other camp; the communication layer refers to the logical interaction relationship of each equipment agent. In this scenario, its main meaning is the process of information transmission and command transmission with the agents of the same camp, which is manifested as the topological relationship of the system network structure from a macro perspective.

[0070] In summary, the process of building a performance evaluation simulation model is as follows: Figure 3 shown.

[0071] Among them, the mathematical structure of the Agent model of the i-th equipment is as follows:

[0072] Agent i =f(x i1 ,x i2 ,...,x in ;function i1 ,function i2 ,...,function in ,State Machine Diagram; Communication Topology)

[0073] x i Represents various performance parameters of the equipment.

[0074] The mathematical structure of the anti-UAV system Agent model is:

[0075] Agent=f(parameter,variable;function,statechart;connections)

[0076] In the formula, Parameter is parameter, Variable is variable, Function is function, Statechart is state chart, and Connections is connection.

[0077] The complex network structure of the anti-UAV system Agent model is expressed as:

[0078] G=(V1,E1;V2,E2;V3)

[0079] {V1, V2, V3} refer to the representative nodes of the communication layer, structure layer and performance layer, and {E1, E2} refer to the edges between nodes in the communication layer and structure layer.

[0080] The present invention defines a commonly used anti-UAV system architecture, and can comprehensively consider system nodes and organizational relationships when constructing a simulation model. Therefore, when evaluating the effectiveness of the anti-UAV system, the performance of the anti-UAV system's internal equipment, the system's overall mission effectiveness, and the system's internal emergent effectiveness can be obtained at the same time, making the effectiveness evaluation of the anti-UAV system more scientific and reasonable.

[0081] An ABMS-based anti-UAV system effectiveness evaluation simulation system includes:

[0082] The anti-UAV system task construction module is used to build the anti-UAV collaborative combat system and the anti-UAV collaborative combat system tasks and processes for the corresponding scenarios;

[0083] The Agent model building module is used to build corresponding Agent models according to different roles and functions in the anti-UAV collaborative combat system; define the performance, function, behavior rules of each Agent model and the interaction mode between Agent models;

[0084] The simulation evaluation module is used to obtain the task scenario to be simulated and the corresponding performance data and efficiency indicators, input the performance data into each Agent model to execute the task scenario to be simulated, obtain the simulation result, evaluate the simulation result based on the efficiency indicator, and obtain the efficiency evaluation result corresponding to the task scenario to be simulated.

[0085] An electronic device comprises a memory and a processor, wherein the memory is used to store a computer program, and the processor runs the computer program to enable the electronic device to execute the ABMS-based anti-UAV system effectiveness evaluation simulation method.

[0086] A computer-readable storage medium stores a computer program, which, when executed by a processor, implements the ABMS-based anti-UAV system effectiveness evaluation simulation method.

[0087] The above is only a preferred specific implementation of the present application, but the protection scope of the present application is not limited thereto. Any changes or substitutions that can be easily thought of by a person skilled in the art within the technical scope disclosed in the present application should be included in the protection scope of the present application. Therefore, the protection scope of the present application should be based on the protection scope of the claims.

Claims

1. A simulation method for evaluating the effectiveness of an anti-UAV system based on ABMS, characterized in that: include: Construct an anti-UAV collaborative combat system and the tasks and processes of the anti-UAV collaborative combat system for corresponding scenarios; According to the different roles and functions in the anti-UAV collaborative combat system, the corresponding Agent model is constructed; Define the performance, functions, behavior rules of each Agent model and the interaction mode between Agent models; Obtain the task scenario to be simulated and the corresponding performance data and efficiency indicators; Input the performance data into each of the Agent models to execute the task scenario to be simulated, obtain the simulation result, evaluate the simulation result based on the performance index, and obtain the performance evaluation result corresponding to the task scenario to be simulated.

2. The ABMS-based anti-UAV system effectiveness evaluation simulation method according to claim 1 is characterized in that: The UAV collaborative combat system includes a layered collaborative system and a distributed collaborative system.

3. The ABMS-based anti-UAV system effectiveness evaluation simulation method according to claim 2 is characterized in that: The hierarchical collaborative system specifically includes: Use radar and radio monitoring equipment to conduct routine monitoring, identify targets and send target intelligence to the command and control center; Use the command and control center to perform information fusion and threat assessment on the received target intelligence, and assign strike missions to optoelectronic drones based on the assessment results; Control the optoelectronic drone to conduct a preliminary attack on the target based on the strike mission. If it fails, keep tracking and feedback the situation data to the command and control center; Based on the feedback situation data and real-time tracking data, strike drones are used to carry out precise strikes on targets, and air defense vehicles are controlled to intercept in the second-level warning area.

4. The ABMS-based anti-UAV system effectiveness evaluation simulation method according to claim 2 is characterized in that: The distributed collaborative system specifically includes: Use radar, radio monitoring equipment and optoelectronic equipment to monitor the target area on a regular basis, identify the target and send target intelligence to the command and control center; Use the command and control center to conduct information fusion and threat assessment on the received target intelligence, and assign strike missions to the navigation decoy equipment, jammers and air defense vehicles closest to the target based on the assessment results; After receiving the mission, the navigation decoy equipment, omnidirectional jamming equipment and air defense vehicles attack the target in turn.

5. The anti-UAV system effectiveness evaluation simulation method based on ABMS according to claim 1 is characterized in that: The construction process of each Agent model specifically includes: An agent model is established based on three levels: performance layer, behavior layer, and communication layer. The performance layer includes the physical properties of each equipment agent in the anti-UAV collaborative combat system, the behavior layer includes the behavioral characteristics of each equipment agent in the anti-UAV collaborative combat system, and the communication layer includes the logical interaction relationship of each equipment agent in the anti-UAV collaborative combat system.

6. An ABMS-based anti-UAV system effectiveness evaluation simulation system, characterized in that: include: The anti-UAV system task construction module is used to build the anti-UAV collaborative combat system and the anti-UAV collaborative combat system tasks and processes for the corresponding scenarios; The Agent model building module is used to build corresponding Agent models according to different roles and functions in the anti-UAV collaborative combat system; define the performance, function, behavior rules of each Agent model and the interaction mode between Agent models; The simulation evaluation module is used to obtain the task scenario to be simulated and the corresponding performance data and efficiency indicators, input the performance data into each Agent model to execute the task scenario to be simulated, obtain the simulation result, evaluate the simulation result based on the efficiency indicator, and obtain the efficiency evaluation result corresponding to the task scenario to be simulated.

7. An electronic device, characterized in that: It includes a memory and a processor, the memory is used to store a computer program, and the processor runs the computer program to enable the electronic device to execute an ABMS-based anti-UAV system effectiveness evaluation simulation method according to any one of claims 1 to 5.

8. A computer-readable storage medium, characterized in that: It stores a computer program, which, when executed by a processor, implements an ABMS-based anti-UAV system effectiveness evaluation simulation method as described in any one of claims 1 to 5.

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