A cross-domain unmanned cluster cooperative task network modeling method based on empowerment coloring

Abstract

To address the problems existing in the prior art, this invention provides a weighted coloring-based method for cross-domain unmanned swarm collaborative mission network modeling. The method includes: using combat elements in a cross-domain collaborative combat system as nodes in a cross-domain collaborative combat network model. These nodes include perception nodes, decision-making nodes, execution nodes, and target nodes. The information interaction relationships between combat elements in the cross-domain collaborative combat system are used as edges. Attribute sets for each node and attribute sets for each edge in the cross-domain collaborative combat network model are constructed. Multiple quantitative attributes of the information corresponding to nodes and edges are represented by weights, and multiple qualitative attributes of the information corresponding to nodes and edges are represented by different colors, resulting in a weighted coloring-based cross-domain collaborative combat network model. The weighted coloring-based cross-domain collaborative combat model constructed by this invention not only has excellent visualization capabilities but also provides decision-makers with a clear and accurate object structure and attributes, effectively improving the speed and accuracy of decision-making.

Description

Technical Field

[0001] This invention belongs to the field of equipment system technology, specifically relating to a cross-domain unmanned cluster collaborative task network modeling method based on weighted coloring. Background Technology

[0002] In modern warfare, the operational environment is becoming increasingly complex and volatile, with diverse types of information. Commanders need to acquire accurate battlefield information in real time to adapt to the ever-changing battlefield situation. This has led to the need for system modeling, which aims to achieve a structured representation of battlefield information through comprehensive modeling of operational elements. This provides a simple data search structure and a good visualization environment for subsequent command and decision-making, thereby improving the efficiency of command and control.

[0003] System modeling aims to provide a structured description of various elements within a combat system, such as functional modules for perception, decision-making, and execution. It clarifies their functional attributes, spatial locations, and collaborative relationships. Establishing a comprehensive and dynamic system model enables commanders to clearly and quickly understand the battlefield layout and element distribution, thereby making more scientific operational decisions. Furthermore, system modeling provides a basic framework for subsequent task allocation and kill chain generation, ensuring seamless integration between various stages. Therefore, the need for system and mission modeling stems from the urgent requirement for rapid and accurate command and decision support. Establishing sound system and mission models is a crucial guarantee for ensuring efficient and rational command and decision-making.

[0004] Cross-domain collaborative combat systems are characterized by numerous combat platforms and elements, large scale, and complex and diverse inter-element collaborative relationships. Clear and accurate mathematical expressions are the foundation for effective modeling and efficient algorithm design of collaborative combat systems. Existing cross-domain collaborative combat systems suffer from a lack of sufficient structural and attribute descriptions of combat elements and their inter-element collaborative relationships. This prevents decision-makers from quickly, clearly, and accurately obtaining information on combat elements, their inter-element collaborative relationships, and attributes from the system information, thus affecting the speed and accuracy of decision-making. Summary of the Invention

[0005] To address the problems existing in the prior art, this invention provides a method for cross-domain unmanned cluster cooperative task network modeling based on weighted coloring, comprising: Step 1: Using operational elements within the cross-domain collaborative combat system as nodes in the cross-domain collaborative combat network model. These nodes include sensing nodes. Decision nodes Execution Node and target node .

[0006] Step 2: The information interaction relationships between combat elements in the cross-domain collaborative combat system are used as edges between corresponding nodes in the cross-domain collaborative combat network model. These information interaction relationships include: command and control relationships, information transmission relationships, and status feedback relationships.

[0007] Step 3: Construct the attribute sets of each node and the attribute sets of each edge in the cross-domain collaborative combat network model.

[0008] Step 4: Use weights to represent the various quantitative attributes of the combat elements corresponding to nodes and the information interaction relationships corresponding to edges, and use different colors to represent the various qualitative attributes of the combat elements corresponding to nodes and the information interaction relationships corresponding to edges, to obtain a weighted and colored cross-domain collaborative combat network model.

[0009] Furthermore, the command and control relationship described in step 2 includes the relationship where the decision-making node sends instructions to the sensing node to acquire target and environmental information, represented as follows: The relationship between the decision-making node and the execution node in sending instructions to conduct combat operations against the enemy is represented as follows: .

[0010] The information transmission relationship includes the relationship between nodes of the same or different types that send target and environmental information for information fusion and sharing, wherein nodes of the same type are represented as follows: , , Different types of nodes are represented as follows: , , , .

[0011] The state feedback relationship includes the collaborative state feedback relationship between nodes of the same or different types. The relationship between nodes of the same type is represented as follows: , , Different types of nodes are represented as follows: , , , .

[0012] Furthermore, the method for constructing the attribute sets of each node and the attribute sets of edges in the cross-domain collaborative combat network model described in step 3 includes: Step 3.1 Mark the combat elements and the relationships between them with unique identifiers that reflect the characteristics of the target to form an identifier attribute set.

[0013] Step 3.2 Construct a state attribute set. The state attribute set is used to describe the behavioral state, working state, and capability state of combat elements or the relationships between combat elements at a certain moment, reflecting the real-time operation of the combat system.

[0014] Step 3.3 Construct a set of functional attributes. The set of functional attributes is used to describe the capabilities of combat elements and the relationships between them. It covers the functions of combat elements, specific types of combat elements, capability attributes, and types of combat elements that can cooperate with them.

[0015] Step 3.4 Construct a task attribute set. The task attribute set is used to describe the tasks assigned to combat elements and the execution status of the tasks. In the information interaction or coordination relationship between combat elements, it is reflected in the importance of the relationship in the task execution process.

[0016] Furthermore, the method for obtaining the weighted coloring cross-domain cooperative combat network model includes: Step 4.1 Divide the combat nodes into layers and regions according to their functions.

[0017] Step 4.2 Based on the information content, divide the edges between nodes into: combat edges, control command edges, information transmission edges, and status feedback edges. Treat the undirected edges between each type of node as two directed edges with opposite directions and color them accordingly, using different colors to represent the interaction type when information is exchanged between each type of node.

[0018] Repeat the above steps until all nodes and edges in each layer and region of the cross-domain collaborative combat network are colored.

[0019] Furthermore, the method for obtaining the weighted and colored cross-domain collaborative combat network model further includes: step 4.3 coloring the combat network collaborative sub-communication networks, including: Step 4.3.1 Initialize and cluster the colors available for combat network coloring into color classes. Define the combat network Where G is the layer of the combat network and E is the region of the combat network.

[0020] Step 4.3.2 Separate the different layers Nodes within The nodes are colored differently, meaning nodes in different layers have different colors. The nodes that have already been colored are clustered according to the colors used. .

[0021] Step 4.3.3 Select any node Choose any color Determine whether each of its neighbor sets is cooperative: If possible, connect the edges and color them. Color. If they cannot be combined, then color them gray.

[0022] Step 4.3.4 Select any node The associated ones have been dyed For each endpoint of a colored edge, determine whether its neighbor set is cooperative: If possible, connect the edges and color them. If colors cannot be combined, then they should be dyed gray.

[0023] Step 4.3.5 Select any node For any node in the set of cooperative neighbors, repeat step 4.3.4 until no related edge can be found through the neighbors to perform coloring.

[0024] Step 4.3.6 Arbitrarily select the uncolored endpoint of a node with an associated edge that has not yet been colored, and choose any color. ,by As Repeat steps 4.3.3 through 4.3.5.

[0025] Step 4.3.7 Repeat steps 4.3.2 to 4.3.6 until all nodes and edges in the combat network have been colored.

[0026] Furthermore, the weighted coloring cross-domain collaborative combat network model described in step 4... ,in: A collection of all combat elements, through Obtained. Among them. For the set of sensing nodes, For the set of decision nodes, For the set of execution nodes.

[0027] It is a collection of information exchange and coordination relationships among all combat elements, through... ,in It is a collection of information exchange relationships between combat elements. It is a set of synergistic relationships between combat elements.

[0028] For the weights on all nodes, through Received, among which This represents the weight vector of the node numbered n.

[0029] For the weights of all edges, by Received, among which This represents the edge weight vector with the number m.

[0030] For the color of all nodes, by Received, among which This represents the color vector of the node with number n.

[0031] For the color of all edges, by Received, among which This represents the edge color vector with the number m.

[0032] Furthermore, the set of information interaction relationships among the aforementioned combat elements. ,in Let be the set of edges corresponding to command and control relationships. It is the set of edges corresponding to information transmission relationships. It is the set of edges corresponding to the state feedback relationship.

[0033] Furthermore, the set of synergistic relationships among the aforementioned combat elements. ={ , , , , , , },in: , , This refers to the collaborative relationship between nodes of the same type.

[0034] , , , This refers to the collaborative relationships between different types of nodes.

[0035] in , , These represent the subsets of perception nodes, decision nodes, and execution nodes in a single collaborative edge, respectively.

[0036] Furthermore, methods for determining information exchange between operational elements within a cross-domain collaborative combat system include: Step 2.1 Calculate the communication distance between combat element i and combat element j based on Equation 1. : Formula 1 Where x, y, and z are the coordinate values ​​of the nodes corresponding to combat element i and combat element j in the same XYZ coordinate system.

[0037] Step 2.2 Obtain the judgment value of communication distance based on Equation 2 : Formula 2 in, This represents the minimum communication distance for each of combat element i and combat element j.

[0038] Step 2.3 When If the value is 1, it indicates that there is information exchange between combat element i and combat element j. If the value is 0, it is determined that there is no information exchange between combat element i and combat element j.

[0039] The advantages of this invention are: 1. This invention constructs attribute sets to characterize the various features of each combat element and the relationships between combat elements, which can more accurately depict the information interaction and collaborative relationships between combat elements, thereby expressing the cross-domain collaborative combat system more clearly and accurately.

[0040] 2. This invention provides a comprehensive structural and attribute description of combat elements and the collaborative relationships between them. It also constructs a weighted coloring hypergraph where each node and each edge is accompanied by a quantitative and qualitative attribute vector that reflects the corresponding combat element and the relationship between combat elements. Therefore, the weighted coloring cross-domain collaborative combat model constructed by this invention not only has good visualization capabilities but also provides decision-makers with a clear and accurate object structure and attributes, which can effectively improve the decision-making speed and accuracy. Attached Figure Description

[0041] To more clearly illustrate the specific embodiments of the present invention or the technical solutions in the prior art, the drawings used in the description of the specific embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are some embodiments of the present invention. For those skilled in the art, other drawings can be obtained from these drawings without creative effort.

[0042] Figure 1 This is a schematic diagram illustrating the relationship between identifiers, states, functions, and tasks in an example of the present invention; Figure 2 This is a schematic diagram of the combat element partitioning and node coloring in the example of the present invention; Figure 3 This is a schematic diagram of the information interaction between combat elements in this invention, with colored edges. Figure 4 This is a schematic diagram with colored edges illustrating the collaborative relationship between combat elements in this invention. Figure 5 This is a schematic diagram of a multi-layered coloring cooperative combat network as exemplified by the present invention; Figure 6 This is a schematic diagram of a multi-layered coloring cooperative combat network plane, as exemplified by the present invention. Detailed Implementation

[0043] To make the objectives, technical solutions, and advantages of the embodiments of the present invention clearer, the technical solutions of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0044] This invention provides an exemplary method for cross-domain unmanned cluster cooperative task network modeling based on weighted coloring, comprising: Step 1: Using operational elements within the cross-domain collaborative combat system as nodes in the cross-domain collaborative combat network model. These nodes include sensing nodes. Decision nodes Execution Node and target node .

[0045] Step 2: The information interaction relationships between combat elements in the cross-domain collaborative combat system are used as edges between corresponding nodes in the cross-domain collaborative combat network model. These information interaction relationships include: command and control relationships, information transmission relationships, and status feedback relationships.

[0046] Step 3: Construct the attribute sets of each node and the attribute sets of each edge in the cross-domain collaborative combat network model.

[0047] Step 4: Use weights to represent the various quantitative attributes of the combat elements corresponding to nodes and the information interaction relationships corresponding to edges, and use different colors to represent the various qualitative attributes of the combat elements corresponding to nodes and the information interaction relationships corresponding to edges, to obtain a weighted and colored cross-domain collaborative combat network model.

[0048] This invention first models the nodes of the combat network to clarify the types and functions of elements in the combat system, so as to achieve clear identification and classification of these combat elements.

[0049] Next, the operational network edges are modeled to define the relationships between elements, such as synergy and information transmission. The interaction methods of the elements are analyzed to model the edges.

[0050] Then, by constructing attribute sets to characterize the various features of each combat element and the relationships between combat elements, we can more accurately depict the information interaction and coordination relationships between combat elements and combat elements, thereby expressing the cross-domain collaborative combat system more clearly and accurately.

[0051] Finally, a weighted coloring model of the cross-domain collaborative combat system is constructed. The weights of nodes and hyperedges represent various quantitative attributes of corresponding elements and relationships, and the colors of nodes and hyperedges represent various qualitative attributes of corresponding elements and relationships.

[0052] This invention provides a comprehensive structural and attribute description of combat elements and their collaborative relationships. It also constructs a weighted coloring hypergraph where each node and each edge is accompanied by a quantitative and qualitative attribute vector that reflects the corresponding combat element and the relationship between combat elements. Therefore, the weighted coloring cross-domain collaborative combat model constructed by this invention not only has excellent visualization capabilities but also provides decision-makers with a clear and accurate object structure and attributes, which can effectively improve the decision-making speed and accuracy.

[0053] This invention provides an exemplary command and control relationship as described in step 2, comprising: a relationship in which a decision node sends instructions to a perception node to acquire target and environmental information, represented as follows: This relationship mainly refers to the relationship between the decision-making node and the sensing node in sending commands to acquire target and environmental information, such as search, tracking, and guidance.

[0054] The relationship between the decision-making node and the execution node in sending instructions to conduct combat activities against the enemy is represented as follows: This relationship primarily involves the decision-making node sending instructions to the execution node to carry out combat activities such as execution, interference, and suppression against the enemy.

[0055] This invention provides an exemplary information transmission relationship as described in step 2, comprising: a relationship in which nodes of the same or different types send target and environmental information for information fusion and sharing, wherein nodes of the same type are represented as follows: , , Different types of nodes are represented as follows: , , , .

[0056] This invention provides an exemplary state feedback relationship as described in step 2, comprising: a collaborative state feedback relationship between nodes of the same or different types. The relationship between nodes of the same type is represented as follows: , , Different types of nodes are represented as follows: , , , .

[0057] This invention structures the information interaction relationships between combat elements into three types of relationships as shown in the above example, covering almost all relationship types between combat elements. This can effectively meet the data integrity requirements during subsequent modeling, forming as comprehensive an edge between corresponding nodes of combat elements as possible, and avoiding the problem of missing model information due to missing edges caused by relationship omissions.

[0058] This invention provides, by way of example, a method for constructing the attribute sets of each node and the attribute sets of edges in the cross-domain collaborative combat network model described in step 3, comprising: Step 3.1 Mark the combat elements and the relationships between them with unique identifiers that reflect the characteristics of the target to form an identifier attribute set.

[0059] Step 3.2 Construct a state attribute set. The state attribute set is used to describe the behavioral state, working state, and capability state of combat elements or the relationships between combat elements at a certain moment, reflecting the real-time operation of the combat system.

[0060] Step 3.3 Construct a set of functional attributes. The set of functional attributes is used to describe the capabilities of combat elements and the relationships between them. It covers the functions of combat elements, specific types of combat elements, capability attributes, and types of combat elements that can cooperate with them.

[0061] Step 3.4 Construct a task attribute set. The task attribute set is used to describe the tasks assigned to combat elements and the execution status of the tasks. In the information interaction or coordination relationship between combat elements, it is reflected in the importance of the relationship in the task execution process.

[0062] In operational networks, operational elements, their information interaction relationships, and collaborative relationships possess various characteristics. This invention characterizes these characteristics to establish a multi-attribute network for cross-domain collaborative operational systems. By employing attribute sets to describe relevant core characteristics, a representative attribute set is constructed, thereby more accurately depicting the information interaction relationships and collaborative relationships between operational elements, and ultimately expressing the cross-domain collaborative operational system more clearly and accurately.

[0063] Furthermore, these four types of attributes in the example of this invention form a close interaction and interdependence, together constituting a complete description and operational mechanism of the cross-domain collaborative combat system.

[0064] This invention provides, by way of example, a method for obtaining a weighted coloring cross-domain cooperative combat network model, comprising: Step 4.1 Divide the combat nodes into layers and regions according to their functions.

[0065] Step 4.2 Based on the information content, divide the edges between nodes into: combat edges, control command edges, information transmission edges, and status feedback edges. Treat the undirected edges between each type of node as two directed edges with opposite directions and color them accordingly, using different colors to represent the interaction type when information is exchanged between each type of node.

[0066] Repeat the above steps until all nodes and edges in each layer and region of the cross-domain collaborative combat network are colored.

[0067] Based on steps 4.1 and 4.2 of the example of this invention, a multi-layered colored combat network model can be constructed. The applicant further considers the collaborative sub-communication network and introduces step 4.3, coloring the combat network's collaborative sub-communication network, thereby finally completing the construction of the multi-layered colored collaborative combat network model. The method for coloring the combat network's collaborative sub-communication network includes: Step 4.3.1 Initialize and cluster the colors available for combat network coloring into color classes. Define the combat network Where G is the layer of the combat network and E is the region of the combat network.

[0068] Step 4.3.2 Separate the different layers Nodes within The nodes are colored differently, meaning nodes in different layers have different colors. The nodes that have already been colored are clustered according to the colors used. .

[0069] Step 4.3.3 Select any node Choose any color Determine whether each of its neighbor sets is cooperative: If possible, connect the edges and color them. Color. If they cannot be combined, then color them gray.

[0070] Step 4.3.4 Select any node The associated ones have been dyed For each endpoint of a colored edge, determine whether its neighbor set is cooperative: If possible, connect the edges and color them. If colors cannot be combined, then they should be dyed gray.

[0071] Step 4.3.5 Select any node For any node in the set of cooperative neighbors, repeat step 4.3.4 until no related edge can be found through the neighbors to perform coloring.

[0072] Step 4.3.6 Arbitrarily select the uncolored endpoint of a node with an associated edge that has not yet been colored, and choose any color. ,by As Repeat steps 4.3.3 through 4.3.5.

[0073] Step 4.3.7 Repeat steps 4.3.2 to 4.3.6 until all nodes and edges in the combat network have been colored.

[0074] The above method can be used to associate and extend the coloring area of ​​each layer and region in the combat network with nodes as the base and edges as the guide. This allows the multi-layer coloring collaborative combat network model to be extended to coloring the collaborative sub-communication network, thereby completing the coloring of the entire cross-domain collaborative combat network.

[0075] This invention provides, exemplarily, a cross-domain collaborative combat network model with weighted coloring as described in step 4. ,in: A collection of all combat elements, through Obtained. Among them. For the set of sensing nodes, For the set of decision nodes, For the set of execution nodes.

[0076] It is a collection of information exchange and coordination relationships among all combat elements, through... ,in It is a collection of information exchange relationships between combat elements. It is a set of synergistic relationships between combat elements.

[0077] For the weights on all nodes, through Received, among which This represents the weight vector of the node numbered n.

[0078] For the weights of all edges, by Received, among which This represents the edge weight vector with the number m.

[0079] For the color of all nodes, by Received, among which This represents the color vector of the node with number n.

[0080] For the color of all edges, by Received, among which This represents the edge color vector with the number m.

[0081] This invention provides, by way of example, a set of information interaction relationships among the aforementioned combat elements. ,in Let be the set of edges corresponding to command and control relationships. It is the set of edges corresponding to information transmission relationships. It is the set of edges corresponding to the state feedback relationship.

[0082] This invention provides, by way of example, a set of collaborative relationships among the aforementioned combat elements. ={ , , , , , , },in: , , This refers to the collaborative relationship between nodes of the same type.

[0083] , , , This refers to the collaborative relationships between different types of nodes.

[0084] in , , These represent the subsets of perception nodes, decision nodes, and execution nodes in a single collaborative edge, respectively.

[0085] The cross-domain cooperative combat network model with weighted coloring as an example of this invention It includes the weight vectors of nodes and edges, as well as various quantitative attributes of the combat elements and relationships corresponding to the weight vectors, and the color vectors of nodes and edges, as well as various qualitative attributes of the combat elements and relationships corresponding to the color vectors. This makes the weighted coloring cross-domain collaborative combat model constructed by this invention not only have good visualization capabilities, but also provide decision-makers with clear and accurate object structures and attributes, which can effectively improve the decision-making speed and accuracy of decision-makers.

[0086] This invention provides, by way of example, a method for determining the information interaction between combat elements in a cross-domain collaborative combat system, including: Step 2.1 Calculate the communication distance between combat element i and combat element j based on Equation 1. : Formula 1 Where x, y, and z are the coordinate values ​​of the nodes corresponding to combat element i and combat element j in the same XYZ coordinate system.

[0087] Step 2.2 Obtain the judgment value of communication distance based on Equation 2 : Formula 2 in, This represents the minimum communication distance for each of combat element i and combat element j.

[0088] Step 2.3 When If the value is 1, it indicates that there is information exchange between combat element i and combat element j. If the value is 0, it is determined that there is no information exchange between combat element i and combat element j.

[0089] This method uses the spatial distance between nodes as the criterion to quickly classify the possibility of information interaction between nodes, thereby quickly confirming whether edges can be formed between nodes, so as to avoid forming associations between obviously unrelated node information, which would lead to distortion of model information.

[0090] The technical solution of the present invention will be further illustrated below with specific examples.

[0091] A small-scale cluster consisting of 11 multi-functional UAV nodes was used as the simulation object. This cluster has various functions including reconnaissance and detection, decision-making and fire execution.

[0092] Step 1: Modeling of combat network nodes.

[0093] The set of nodes is used , , , Each node represents a set of perception nodes, decision nodes, execution nodes, and target nodes, respectively.

[0094] In this example, the node modeling includes: 4 reconnaissance nodes, 3 decision-making nodes (D1, D2, D3), 4 fire support nodes (E1, E2, E3, E4), and 2 enemy targets (T1, T2). The reconnaissance nodes include 2 early warning and detection nodes (S1, S2) and 2 tracking and guidance nodes (S3, S4).

[0095] Step 2: Modeling the edge of the combat network.

[0096] Step 2.1: Modeling the information interaction relationships between combat elements.

[0097] Step 2.1.1: Modeling the command and control relationship.

[0098] Command and control relationships involve decision-making nodes sending instructions to sensing nodes to acquire target and environmental information, such as search, tracking, and guidance commands. This is symbolically represented as... The decision-making node sends instructions to the execution node to carry out combat activities such as execution, interference, and suppression against the enemy, denoted by the symbol . .

[0099] Step 2.1.2: Modeling information transmission relationships.

[0100] Information transmission relationships encompass the exchange of target and environmental information between nodes of the same or different functional categories, enabling information fusion and sharing. Symbolically, "same category" refers to... , , Different categories: , , , .

[0101] Step 2.1.3: Modeling state feedback relationships.

[0102] State feedback relationships encompass the collaborative state feedback relationships between functional nodes of the same or different types. Symbolically, they are represented as: [symbol missing - likely "same type"]. , , Different categories: , , , .

[0103] This project determines whether there is a communication edge between our various elements by measuring the communication distance between them, as shown in Equations 1 to 3.

[0104] Formula 1 Formula 2 Formula 3 Based on the information interaction connection type and distance judgment between each element described in step 2.1, the communication connection between each element in the set instance is shown in Table 1.

[0105] Table 1. Communication and Edge Connections Between Elements Step 2.2: Modeling the collaborative relationships among operational elements; Define the collaborative relationships among all combat elements as collaborative edges between combat nodes, and the set of collaborative edges is: , ={ , , , , , , The synergistic relationship between similar functional elements is represented as follows: , , The collaborative relationships between different types of functional elements are represented as follows: , , , ,in , , These represent the subsets of perception nodes, decision nodes, and execution nodes in a single collaborative edge, respectively.

[0106] In this example, the collaborative relationships between combat elements are set as shown in Table 2.

[0107] Table 2. Connection details of collaborative relationships between elements Step 3: Construction of combat network nodes and edge attribute sets.

[0108] In operational networks, operational elements, information interaction relationships, and collaborative relationships between elements possess multiple characteristics. Characterizing these characteristics allows for the establishment of a multi-attribute network for cross-domain collaborative operational systems. By employing attribute sets to describe relevant core characteristics, a representative attribute set can be constructed, thereby more accurately depicting the information interaction relationships and collaborative relationships between elements. This leads to a clearer and more accurate complex hypergraph representation method for cross-domain collaborative operational systems.

[0109] Step 3.1: Construct the set of identifier attributes.

[0110] Identification attributes must be able to reflect the uniqueness of the individual they represent in order to enable rapid identification and communication on the battlefield. The description methods for identification attributes of elements and the relationships between elements are as follows: {Operational Domain, Platform ID, Element ID, Mission ID, Time}.

[0111] {Relationship type <Information interaction, collaboration>, Relationship subtype <Control command edge, Intelligence transmission edge, Status feedback edge, collaboration>, Element set, Time}.

[0112] Step 3.2: Constructing the state attribute set.

[0113] The state attribute set describes the behavioral, operational, and capability states of elements or relationships between elements at a given moment, reflecting the real-time operation of the combat system. The state attribute description method for elements and their relationships is as follows: {Behavior <position, direction, speed>, work <idle, performing tasks>, ability <normal, damaged, malfunctioning>, time}.

[0114] {Work <Success, Failure>, Moment}.

[0115] Step 3.3: Constructing the functional attribute set.

[0116] The functional attribute set describes the capabilities of elements and the relationships between elements, covering the functions possessed by the elements, their specific element types, their capability attributes, and the types of elements they can collaborate with. The functional attribute description method for elements and the relationships between elements is as follows: {Functional type <perception, decision-making, execution, goal>, model type, capability index, collaboration type, time}.

[0117] {Interactive capability <probability of successful information exchange, collaborative efficiency>, time}.

[0118] Step 3.4: Construct the task attribute set.

[0119] The task attribute set describes the tasks assigned to a feature and the execution status of those tasks. In information exchange or collaboration relationships between features, it reflects the importance of that relationship during task execution. The attribute description method for features is as follows: {Task list, currently executing task, task completion status, time}.

[0120] {Importance, Moment}.

[0121] Table 3-7 provides an example of the typical functional and task attribute sets of four types of elements. These four types of attributes form a close interaction and interdependence relationship, and together constitute a complete description and operation mechanism of the cross-domain collaborative combat system. The four major categories of attributes—identification, status, function, and task—are interconnected. Figure 1 It shows the basic relationships between the four types of attributes.

[0122] Table 3 Our Factors General properties Table 4 Perceptual Elements Function and task attribute table Table 5 Decision Factors Function and task attribute table Table 6 Implementation Elements Function and task attribute table Table 7. Status, Function, and Task Attributes of Target Elements Based on the above settings of our elements and enemy target attributes, the model types of our elements are shown in Table 8, the numbers and location information of some of our elements are shown in Table 9, and the information of enemy targets is shown in Table 10.

[0123] Table 8. Types of Our Element Models Table 9. Partial Data Information of Our Side Table 10: Data Information Table of Some Target Elements Based on the given friendly and target elements, the existence of communication edges between friendly elements can be determined by measuring the communication distance between them, thus obtaining the combat network in this typical scenario, as follows: Figure 2 As shown. Based on this, the present invention establishes a multi-layer collaborative coloring network based on step 4.

[0124] Step 4: Constructing a weighted and colored unmanned cluster collaborative task network model.

[0125] The weighted coloring network model of the cross-domain collaborative combat system is defined as follows: The weights of nodes and hyperedges represent various quantitative attributes of corresponding elements and relationships, while the colors of nodes and hyperedges represent various qualitative attributes of corresponding elements and relationships. ,in: (1) : A collection of all elements , , and These represent the sets of perception nodes, decision nodes, and execution nodes, respectively.

[0126] (2) : It is the collection of information interaction and collaborative relationships among all elements. , and These are collections of information interaction relationships and collaborative relationships between elements.

[0127] (3) : For the weights on all nodes, the node The weight vector on is: ={ , , ,time}.

[0128] (4) : For the weights of all superedges, the superedges The weight vector on is: ={ , }

[0129] (5) : For the color of all nodes, the node The color vector on is: ={ , , , , , , , }

[0130] (6) : For the color of all edges, the edges The color vector on is: ={ }

[0131] The construction of a weighted coloring unmanned swarm cooperative task network model can be divided into the following three steps: Step 4.1: Coloring of combat network nodes.

[0132] This invention hierarchically and partitions combat elements in a multi-layered network based on the functions of combat nodes. Essentially, it involves coloring the combat elements, similarly coloring each layer and region to form a structure like... Figure 3 The diagram shows the coloring of the combat network nodes.

[0133] Step 4.2: Edge coloring for combat network information interaction.

[0134] This invention categorizes the edges between nodes into four main types based on information content: combat edges, control command edges, information transmission edges, and status feedback edges. Undirected edges between nodes of each functional type are treated as two directed edges with opposite directions and colored accordingly to characterize the interaction type when information is exchanged between various elements.

[0135] Formation as Figure 3 The colored graph of the combat network information interaction edge shown, and as follows Figure 4 The diagram shown is a colored graph of the operational network information coordination edges.

[0136] Based on steps 4.1 and 4.2, the multi-layer coloring combat network model is constructed. The following steps further consider the construction of the collaborative sub-communication network, and finally the multi-layer coloring collaborative combat network model is constructed.

[0137] Step 4.3: Coloring of the combat network coordination sub-communication network.

[0138] The specific coloring steps are as follows: Step 4.3.1: Initialization: Color class is Combat network .

[0139] Step 4.3.2: Separate the different layers Nodes within The nodes are colored differently, meaning nodes on different layers have different colors. Let's assume the color class of the node coloring is... .

[0140] Step 4.3.3: Select any node Choose any Determine whether each of its neighbor sets is cooperative. If cooperative, connect the edges and color them accordingly. If colors cannot be combined, then they should be dyed gray.

[0141] Step 4.3.4: Select any node The associated ones have been dyed For the other endpoint of the colored edge (i.e., its cooperative neighbor), check whether the neighbor set of that endpoint is cooperative. If it is cooperative, connect the edges and color them accordingly. If a color cannot be coordinated, it is colored gray. This process is repeated for nodes. Perform operations on all collaborating neighbor sets, but avoid operating on non-collaborating neighbors.

[0142] Step 4.3.5: Select any node For any node in the set of cooperative neighbors, perform step 4.3.4, that is, based on its adjacency cooperative relationship, from the node... Spread outwards, coloring the associated edges. The color or gray is used until no related edge can be found through neighbors to color it.

[0143] Step 4.3.6: Randomly select any endpoints with associated edges that have not yet been colored. Repeat the above steps.

[0144] Step 4.3.7: Repeat the above operation until all edges in the multi-layer network have been colored.

[0145] By combining the above-mentioned node and edge coloring methods, we can form a real-time, multi-layered coloring collaborative combat network, the three-dimensional coloring graph of which is shown below. Figure 5 As shown, its planar schematic diagram is as follows: Figure 6 As shown.

[0146] Based on the above-described preferred embodiments of the present invention, and through the foregoing description, those skilled in the art can make various changes and modifications without departing from the inventive concept. The technical scope of this invention is not limited to the contents of the specification, but must be determined according to the scope of the claims.

Claims

1. A method for modeling cross-domain unmanned cluster cooperative task networks based on weighted coloring, characterized in that, include: Step 1: Using operational elements within the cross-domain collaborative combat system as nodes in the cross-domain collaborative combat network model; the nodes include sensing nodes. Decision nodes Execution Node and target node ; Step 2: The information interaction relationships between combat elements in the cross-domain collaborative combat system are used as the edges between corresponding nodes in the cross-domain collaborative combat network model; The information interaction relationships include: command and control relationships, information transmission relationships, and status feedback relationships; Step 3: Construct the attribute sets of each node and the attribute sets of each edge in the cross-domain collaborative combat network model; Step 4: Use weights to represent the various quantitative attributes of the combat elements corresponding to nodes and the information interaction relationships corresponding to edges, and use different colors to represent the various qualitative attributes of the combat elements corresponding to nodes and the information interaction relationships corresponding to edges, to obtain a weighted and colored cross-domain collaborative combat network model.

2. The method of claim 1, wherein, The command and control relationship described in step 2 includes a relationship in which the decision node sends an instruction to obtain a target, environment information to the perception node, denoted as , and a relationship in which the decision node sends an instruction to carry out combat activities on the enemy to the execution node, denoted as . The information transmission relationship includes the relationship between nodes of the same or different types that send target and environmental information for information fusion and sharing, wherein nodes of the same type are represented as follows: , , Different types of nodes are represented as follows: , , , ; The state feedback relationship includes the collaborative state feedback relationship between nodes of the same or different types; the relationship between nodes of the same type is represented as follows: , , Different types of nodes are represented as follows: , , , .

3. The method of claim 1, wherein, Step 3 describes the method for constructing the attribute sets of each node and the attribute sets of edges in the cross-domain collaborative combat network model, which includes: Step 3.1 Use unique identifiers that reflect the characteristics of the target to mark the combat elements and the relationships between them to form an identifier attribute set; Step 3.2 Construct a state attribute set. The state attribute set is used to describe the behavioral state, working state, and capability state of combat elements or the relationships between combat elements at a certain moment, reflecting the real-time operation of the combat system. Step 3.3 Construct a set of functional attributes. The set of functional attributes is used to describe the capabilities of combat elements and the relationships between them. It covers the functions of combat elements, specific types of combat elements, capability attributes, and types of combat elements that can cooperate with them. Step 3.4 Construct a task attribute set. The task attribute set is used to describe the tasks assigned to combat elements and the execution status of the tasks. In the information interaction or coordination relationship between combat elements, it is reflected in the importance of the relationship in the task execution process.

4. The method for cross-domain unmanned cluster cooperative task network modeling based on weighted coloring according to claim 1, characterized in that, The method for obtaining the weighted coloring cross-domain cooperative combat network model includes: Step 4.1 Divide the combat nodes into layers and regions based on their functions; Step 4.2 Divide the edges between nodes into: enemy combat edges, control command edges, information transmission edges, and status feedback edges according to the information content; treat the undirected edges between each type of node as two directed edges with opposite directions and color them, and use different colors to represent the interaction type when information is exchanged between each type of node. Repeat the above steps until all nodes and edges in each layer and region of the cross-domain collaborative combat network are colored.

5. The cross-domain unmanned cluster cooperative task network modeling method based on weighted coloring according to claim 4, characterized in that, The method for obtaining the weighted coloring of the cross-domain collaborative combat network model further includes: Step 4.3 Coloring the combat network collaborative sub-communication networks, including: Step 4.3.1 Initialize colors available for coloring the operational network and cluster them into color classes , define the operational network where G is a layer of the operational network, E is a region of the operational network; Step 4.3.2 Color the nodes in different layers differently Color the nodes in different layers differently, i.e. the colors of the nodes in different layers are different from each other, cluster the colors used for the already colored nodes as ;​ Step 4.3.3 Arbitrarily select a node , arbitrarily select a color , respectively determine whether its neighbor set is synergistic: If possible, join them with a line Color; if not possible, make them gray. Step 4.3.4 Arbitrarily select a node The other end point of the edge colored The other end point of the edge colored If it is possible to coordinate, it is colored with the same color as the edge If it is not possible to coordinate, it is colored in gray. Step 4.3.5 Select any node For any node in the set of cooperative neighbors, repeat step 4.3.4 until no related edge can be found through the neighbors to perform coloring; Step 4.3.6 Arbitrarily select the uncolored endpoint of a node with an associated edge that has not yet been colored, and choose any color. ,by As Repeat steps 4.3.3 to 4.3.5; Step 4.3.7 Repeat steps 4.3.2 to 4.3.6 until all nodes and edges in the combat network have been colored.

6. The method of claim 1, wherein, The cross-domain cooperative combat network model of empowerment coloring described in step 4 wherein: is a set of all combatants, by is obtained; wherein is a set of perception nodes, is a set of decision nodes, is a set of execution nodes; is a collection of information interaction relations and coordination relations among all combat elements, and is obtained by wherein is a collection of information interaction relations among combat elements, is a collection of coordination relations among combat elements; For the weights on all nodes, through Received, among which This represents the weight vector of the node numbered n; For all edges, the weight is given by where denotes the edge weight vector of number m. For all nodes, the color is obtained by where denotes the color vector of node number n; For all edges, the color is given by where denotes the edge color vector numbered m.

7. The method of claim 6, wherein, The set of information interaction relationships among the combat elements ,in Let be the set of edges corresponding to command and control relationships. It is the set of edges corresponding to information transmission relationships. It is the set of edges corresponding to the state feedback relationship.

8. The method of claim 6, wherein, The set of synergistic relationships among the combat elements ={ , , , , , , },in: , , is a cooperative relationship between nodes of the same kind; , , , the cooperative relationship between different types of nodes; wherein , , respectively represent a subset of sensing nodes, a subset of decision nodes and a subset of execution nodes in a single collaborative edge.

9. The method of claim 1, wherein, Methods for determining information exchange between operational elements in a cross-domain collaborative combat system include: Step 2.1 Calculate the communication distance between operational element i and operational element j based on the formula one : Set 1 Where x, y, z are the coordinate values ​​of the nodes corresponding to combat element i and combat element j in the same XYZ coordinate system; Step 2.2 Obtain the judgment value of communication distance based on Equation 2 : Formula 2 wherein, is the minimum value of the communication distance for each of the combat element i and the combat element j; Step 2.3 When = 1, it is determined that there is information interaction between the combat element i and the combat element j, = 0, it is determined that there is no information interaction between the combat element i and the combat element j.

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