Air defense weapon cooperative multi-target distribution method and system based on bipartite graph

Abstract

The invention provides an air defense weapon cooperative multi-target distribution method and system based on a bipartite graph. The method comprises the following steps: uniformly numbering air defense weapon nodes and targets participating in target distribution; constructing an interception favorable degree model according to the interception strategy, and calculating the interception favorable degree of the air defense weapon to all targets; the interception favorable degree and the firepower channel number are shared; the firepower channels of all the air defense weapons are combined in sequence to form a firepower channel set, and a target interception favorable degree matrix of the firepower channels is constructed; establishing a bipartite graph model according to the available firepower channel set and solving the bipartite graph model; and converting a bipartite graph matching result into a target allocation scheme. According to the air defense weapon target distribution method based on the bipartite graph, the air defense target distribution problem is converted into the bipartite graph maximum weight matching problem, the optimal target distribution problem during cooperative combat of multiple air defense weapons is solved, and the method can be suitable for centralized command and distributed self-organizing modes.

Description

Technical Field

[0001] The present invention relates to the technical field of target assignment, and more particularly, to a collaborative multi-target assignment method and system for air defense weapons based on a bipartite graph; more specifically, to a method for assigning multiple air defense weapon fire units to multiple targets. Background Art

[0002] Air defense weapon systems play a crucial role in modern warfare. Assigning suitable targets to each air defense weapon is an important task in air defense combat command. As the types of air defense weapons continue to increase and the multi-target capabilities of air defense weapons become stronger, the coordination of multiple air defense weapons has become a typical pattern in air defense combat when confronting large-scale air targets. Driven by information technology and new combat concepts, the organization mode of air defense equipment has also changed from centralized to distributed. Therefore, the target assignment method of air defense weapons needs to adapt to the coordinated use of multiple types of equipment, possess the ability of many-to-many target assignment, and also adapt to distributed use in a networked environment. In the face of high-intensity continuous confrontation, target assignment should also consider the optimal combination of resources of all equipment to enable each fire unit to exert its maximum effectiveness.

[0003] The current target assignment method mainly adopted by air defense equipment is to make a comprehensive judgment based on information such as the type, position, and threat level of the target, combined with the range and firepower reserve of the weapon. The command system within a single weapon uniformly assigns targets to the affiliated interception equipment. This target assignment method is convenient for engineering implementation and easy for personnel to understand, but it cannot meet the requirements of coordinated target assignment for multiple types of air defense weapons. For networked operations and the situation of mixed multiple types of weapons, CN104933279A proposes a networked operation target assignment method for an air defense missile weapon system, and CN10786184A proposes an optimization method for target assignment of a mixed firepower group of multiple types of air defense weapons. The above methods can be used for combined target assignment of multiple air defense weapons under centralized command, but do not consider the multi-target capabilities of the weapons and are not applicable to distributed environments.

[0004] In distributed use, air defense equipment needs to be able to independently determine the targets to be dealt with by each air defense weapon node without relying on central nodes such as the command system, and form a consensus mechanism to ensure that the targets selected by each node do not conflict or are omitted, that is, the same target is not assigned to multiple nodes, and there are no unassigned targets when there are available nodes. For distributed target assignment, currently mainly based on agent-based bidding mechanisms, auction algorithms, etc., the target assignment results formed by these methods need to reach a consensus among multiple nodes, which requires multiple information exchanges among multiple nodes, has a high demand for network resources, and requires multiple iterations to converge, and is not applicable to fast-paced air defense combat scenarios. Summary of the Invention

[0005] Aiming at the defects in the prior art, the purpose of the present invention is to provide a collaborative multi-target allocation method and system for air defense weapons based on a bipartite graph.

[0006] A collaborative multi-target allocation method for air defense weapons based on a bipartite graph provided by the present invention includes:

[0007] Step S1: Uniformly number the air defense weapon nodes and targets participating in the target allocation;

[0008] Step S2: Construct an interception favorability model according to the interception strategy, and calculate the interception favorability of air defense weapons for all targets;

[0009] Step S3: Share the interception favorability and the number of fire channels;

[0010] Step S4: Combine the fire channels of all air defense weapons in sequence to form a fire channel set, and construct an interception favorability matrix of the fire channels for the targets;

[0011] Step S5: Establish a bipartite graph model and solve it according to the available fire channel set;

[0012] Step S6: Convert the bipartite graph matching result into a target allocation plan.

[0013] Preferably, in the step S2:

[0014] Calculate the interception favorability. The air defense weapon node constructs an interception favorability model based on the unified target information, its own resource status and interception ability, and calculates the interception favorability of the air defense weapon for all targets;

[0015] The interception favorability model is a function of multiple interception factors, which is determined before allocating targets according to the mission purpose. The interception factors include the target threat level, the damage probability, the interception time, the interception cost, or new factors are introduced according to the mission characteristics;

[0016] The interception favorability of node i for all targets 1 to m is denoted as a vector:

[0017] P i =[p i1 p i2 …p ij …p im

[0018] p ij represents the interception favorability of air defense weapon i for target j, 0≤p ij <1, for targets beyond the range or with insufficient damage ability and unable to be intercepted, p ij =0.

[0019] Preferably, in the step S3: ​

[0020] Under the centralized command mode, each air defense weapon sends the interception advantage vector and the number of fire channels to the command system, and the command system establishes and solves a bipartite graph model;

[0021] Under the distributed self-organizing mode, each air defense weapon shares the interception advantage vector and the number of fire channels with other weapon nodes, and each weapon node separately establishes a bipartite graph model and independently solves it.

[0022] Preferably, in the step S4:

[0023] Considering the multi-target ability of air defense weapons, the fire channels of all air defense weapons are sequentially combined to form a fire channel set F, and an interception advantage matrix P of the fire channels against the targets is constructed;

[0024] For a weapon with only one available fire channel, the interception advantage of the fire channel is the interception advantage of the air defense weapon; for an air defense weapon with multiple available fire channels, it is disassembled into the corresponding number of fire channels, and the interception advantage of each fire channel is the interception advantage of the air defense weapon;

[0025] According to the fire channels, the corresponding air defense weapons combine the interception advantage vectors to form an overall interception advantage matrix P, and at the same time record the corresponding relationship between fire channels 1 to f and the air defense weapon numbers in the form of a vector, expressed as R = [r1 r2…r k …r f , r k represents the air defense weapon number corresponding to the kth fire channel.

[0026] Preferably, in the step S5:

[0027] At the solution node, with the available fire channel set F of all air defense weapons and the target set T as the vertex sets, and the interception advantage matrix P as the edge set, a weighted bipartite graph model G=(F, T, P) is constructed, and a suitable algorithm is used to solve the maximum weight matching of the bipartite graph model; the form of the solution is:

[0028] X = [x1 x2…x k …x f

[0029] x k represents the target number matched by the kth fire channel.

[0030] According to an air defense weapon cooperative multi-target allocation system based on a bipartite graph provided by the present invention, including:

[0031] Module M1: uniformly numbers the air defense weapon nodes and targets participating in the target allocation;

[0032] ​Module M2: Construct an interception advantage model according to the interception strategy, and calculate the interception advantage of air defense weapons against all targets;

[0033] Module M3: Share the interception advantage and the number of fire channels;

[0034] Module M4: Combine the fire channels of all air defense weapons in sequence to form a fire channel set, and construct an interception advantage matrix of the fire channels against targets;

[0035] Module M5: Establish a bipartite graph model and solve it according to the available fire channel set;

[0036] Module M6: Convert the bipartite graph matching result into a target allocation plan.

[0037] Preferably, in the said Module M2:

[0038] Calculate the interception advantage. The air defense weapon node constructs an interception advantage model according to the interception strategy based on unified target information, its own resource status and interception ability, and calculates the interception advantage of the air defense weapon against all targets;

[0039] The interception advantage model is a function of multiple interception factors, which is determined before allocating targets according to the mission purpose. The interception factors include target threat level, damage probability, interception time, interception cost, or new factors are introduced according to the mission characteristics;

[0040] The interception advantage of node i against all targets from 1 to m is denoted as a vector:

[0041] P i =[p i1 p i2 …p ij …p im

[0042] p ij represents the interception advantage of air defense weapon i against target j, 0≤p ij <1, for targets that are out of range or have insufficient damage ability and cannot be intercepted, p ij =0.

[0043] Preferably, in the said Module M3:

[0044] In the centralized command mode, each air defense weapon sends the interception advantage vector and the number of fire channels to the command system, and the command system establishes a bipartite graph model and solves it;

[0045] In the distributed self-organizing mode, each air defense weapon shares the interception advantage vector and the number of fire channels to other weapon nodes, and each weapon node establishes a bipartite graph model respectively and solves it independently.

[0046] ​Preferably, in the module M4:

[0047] Considering the multi-target ability of air defense weapons, the firepower channels of all air defense weapons are combined in sequence to form a firepower channel set F, and an interception favorability matrix P of the firepower channels for the targets is constructed;

[0048] For weapons with only one available firepower channel, the interception favorability of the firepower channel is the interception favorability of the air defense weapon; for air defense weapons with multiple available firepower channels, they are disassembled into the corresponding number of firepower channels, and the interception favorability of each firepower channel is the interception favorability of the air defense weapon;

[0049] According to the firepower channels, the corresponding air defense weapons combine the interception favorability vectors to form an overall interception favorability matrix P, and at the same time record the corresponding relationship between firepower channels 1 to f and the air defense weapon numbers in the form of a vector, expressed as R = [r1 r2 … r k … r f , r k represents the air defense weapon number corresponding to the kth firepower channel.

[0050] Preferably, in the module M5:

[0051] At the solution node, taking the available firepower channel set F of all air defense weapons and the target set T as the vertex sets, and the interception favorability matrix P as the edge set, a weighted bipartite graph model G=(F, T, P) is constructed, and a suitable algorithm is used to solve the maximum weight matching of the bipartite graph model; the form of the solution is:

[0052] X = [x1 x2 … x k … x f

[0053] x k represents the target number matched by the kth firepower channel.

[0054] Compared with the prior art, the present invention has the following beneficial effects:

[0055] 1. The present invention proposes a method for target assignment of air defense weapons based on a bipartite graph, which converts the air defense target assignment problem into a maximum weight matching problem of a bipartite graph, solves the optimal target assignment problem in the coordinated operation of multiple air defense weapons, and this method can be applied to centralized command and distributed self-organizing modes.

[0056] 2. Each air defense weapon of the present invention calculates the interception favorability separately, which can give full play to the accuracy and real-time nature of the air defense weapon's grasp of its own resource situation and ability state, and at the same time can share the computational workload brought by centralized calculation by one node, and can obtain the target assignment result in a timely and accurate manner.

[0057] ​3. The present invention is applicable to distributed applications without a central node. By sharing the interception favorability to all nodes at once, each node creates a consistent bipartite graph model based on unified data, and then uses the same matching algorithm to solve it, which can ensure that the target allocation results obtained by distributed calculation are consistent, without multiple iterations, reducing the dependence on communication resources while improving efficiency.

[0058] 4. The maximum weight matching result of the bipartite graph in the present invention has the characteristics of global optimality. Under the determined interception strategy, the target allocation result obtained by this method can form an optimal interception combination, which can give full play to the capabilities of weapons and equipment and obtain high-level combat effectiveness. BRIEF DESCRIPTION OF THE DRAWINGS

[0059] By reading the detailed description of the non-limiting embodiments with reference to the following drawings, other features, objects, and advantages of the present invention will become more apparent:

[0060] Figure 1 is the flowchart of the steps of the present invention;

[0061] Figure 2 is a schematic diagram showing the relationship between air defense weapons and targets provided by an embodiment of the present invention;

[0062] Figure 3 is a schematic diagram showing the interception of air defense weapon node 1 and a target provided by an embodiment of the present invention;

[0063] Figure 4 is a schematic diagram showing the construction of the interception favorability matrix provided by an embodiment of the present invention;

[0064] Figure 5 is a schematic diagram of the bipartite graph model provided by an embodiment of the present invention. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0065] The present invention will be described in detail below with reference to specific embodiments. The following embodiments will help those skilled in the art to further understand the present invention, but do not limit the present invention in any form. It should be noted that for those of ordinary skill in the art, without departing from the concept of the present invention, several changes and improvements can still be made. These all belong to the protection scope of the present invention.

[0066] Embodiment 1:

[0067] The present invention discloses a method for collaborative multi-target allocation of air defense weapons based on a bipartite graph, which converts the air defense target allocation problem into a maximum weight matching problem of a bipartite graph to solve the optimal target allocation problem in the collaborative operation of multiple air defense weapons.

[0068] The present invention is a collaborative multi-target allocation method for air defense weapons based on a bipartite graph. This method places air defense weapons and targets into two sets respectively, then calculates the interception favorability of air defense weapons towards targets, constructs a weighted bipartite graph between the two sets, and then finds the optimal matching solution through the maximum perfect matching algorithm of the bipartite graph to achieve the optimal matching of air defense weapons and target allocation. This method can quickly and efficiently allocate multiple air defense weapons to multiple targets, and can be used for the fire control of multiple air defense weapon equipment groups. It is applicable to target allocation in both centralized command architectures and distributed command architectures. The present invention details the principle and implementation steps of the method, and proves the effectiveness and application prospects of the bipartite graph model in collaborative target allocation of multiple air defense weapons.

[0069] A collaborative multi-target allocation method for air defense weapons based on a bipartite graph provided by the present invention, as Figures 1 - 5 shown, includes:

[0070] Step S1: Uniformly number the air defense weapon nodes and targets participating in target allocation;

[0071] Step S2: Construct an interception favorability model according to the interception strategy, and calculate the interception favorability of air defense weapons towards all targets;

[0072] Specifically, in the said Step S2:

[0073] Calculate the interception favorability. The air defense weapon node constructs an interception favorability model based on unified target information, its own resource status and interception ability, and calculates the interception favorability of air defense weapons towards all targets;

[0074] The interception favorability model is a function of multiple interception factors, which is determined before allocating targets according to the mission purpose. The interception factors include target threat level, kill probability, interception time, interception cost, or new factors are introduced according to the mission characteristics;

[0075] The interception favorability of node i towards all targets from 1 to m is denoted as a vector:

[0076] P i =[p i1 p i2 …p ij …p im

[0077] p ij represents the interception favorability of air defense weapon i towards target j, 0 ≤ p ij <1, and for targets that are out of range or have insufficient damage ability and cannot be intercepted, p ij =0.

[0078] Step S3: Share the interception favorability and the number of fire channels; ​

[0079] Specifically, in the step S3:

[0080] In the centralized command mode, each air defense weapon sends the interception favorability vector and the number of fire channels to the command system, and the command system establishes and solves a bipartite graph model.

[0081] In the distributed self-organizing mode, each air defense weapon shares the interception favorability vector and the number of fire channels with other weapon nodes. Each weapon node respectively establishes a bipartite graph model and independently solves it.

[0082] Step S4: Combine the fire channels of all air defense weapons in sequence to form a fire channel set, and construct an interception favorability matrix of the fire channels against the targets.

[0083] Specifically, in the step S4:

[0084] Considering the multi-target ability of air defense weapons, combine the fire channels of all air defense weapons in sequence to form a fire channel set F, and construct an interception favorability matrix P of the fire channels against the targets.

[0085] For a weapon with only one available fire channel, the interception favorability of the fire channel is the interception favorability of the air defense weapon. For an air defense weapon with multiple available fire channels, it is disassembled into the corresponding number of fire channels, and the interception favorability of each fire channel is the interception favorability of the air defense weapon.

[0086] According to the fire channels, combine the interception favorability vectors of the corresponding air defense weapons to form an overall interception favorability matrix P. At the same time, record the corresponding relationship between fire channels 1 to f and the air defense weapon numbers in the form of a vector, denoted as R = [r1 r2 … r k … r f , where r k represents the air defense weapon number corresponding to the kth fire channel.

[0087] Step S5: Establish and solve a bipartite graph model according to the available fire channel set.

[0088] Specifically, in the step S5:

[0089] At the solution node, construct a weighted bipartite graph model G = (F, T, P) with the available fire channel set F of all air defense weapons and the target set T as the vertex sets and the interception favorability matrix P as the edge set, and use a suitable algorithm to solve the maximum weight matching of the bipartite graph model. The form of the solution is:

[0090] X = [x1 x2 … x k … x f

[0091] x k ​Denote the target number matched for the k-th fire channel.

[0092] Step S6: Convert the bipartite graph matching result into a target allocation scheme.

[0093] Embodiment 2:

[0094] Embodiment 2 is a preferred example of Embodiment 1 to illustrate the present invention more specifically.

[0095] The present invention also provides a collaborative multi-target allocation system for air defense weapons based on a bipartite graph. The collaborative multi-target allocation system for air defense weapons based on a bipartite graph can be implemented by executing the process steps of the collaborative multi-target allocation method for air defense weapons based on a bipartite graph. That is, those skilled in the art can understand the collaborative multi-target allocation method for air defense weapons based on a bipartite graph as a preferred implementation manner of the collaborative multi-target allocation system for air defense weapons based on a bipartite graph.

[0096] According to a collaborative multi-target allocation system for air defense weapons based on a bipartite graph provided by the present invention, it includes:

[0097] Module M1: Uniformly number the air defense weapon nodes and targets participating in target allocation;

[0098] Module M2: Construct an interception favorability model according to the interception strategy and calculate the interception favorability of air defense weapons for all targets;

[0099] Specifically, in Module M2:

[0100] Calculate the interception favorability. The air defense weapon node constructs an interception favorability model based on the unified target information, its own resource status, and interception ability according to the interception strategy, and calculates the interception favorability of the air defense weapon for all targets;

[0101] The interception favorability model is a function of multiple interception factors, which is determined before allocating targets according to the mission purpose. The interception factors include target threat level, kill probability, interception time, interception cost, or new factors are introduced according to the mission characteristics;

[0102] The interception favorability of node i for all targets 1 to m is denoted as a vector:

[0103] P i =[p i1 p i2 …p ij …p im

[0104] p ij represents the interception favorability of air defense weapon i for target j, 0 ≤ p ij <1. For targets beyond the range or with insufficient damage ability and unable to be intercepted, p​ij = 0。

[0105] Module M3: Share the interception advantage degree and the number of fire channels;

[0106] Specifically, in the said Module M3:

[0107] In the centralized command mode, each air defense weapon sends the interception advantage degree vector and the number of fire channels to the command system, and the command system establishes and solves a bipartite graph model;

[0108] In the distributed self-organizing mode, each air defense weapon shares the interception advantage degree vector and the number of fire channels to other weapon nodes, and each weapon node respectively establishes a bipartite graph model and independently solves it.

[0109] Module M4: Combine the fire channels of all air defense weapons in sequence to form a fire channel set, and construct an interception advantage degree matrix of the fire channels against the targets;

[0110] Specifically, in the said Module M4:

[0111] Considering the multi-target ability of air defense weapons, combine the fire channels of all air defense weapons in sequence to form a fire channel set F, and construct an interception advantage degree matrix P of the fire channels against the targets;

[0112] For a weapon with only one available fire channel, the interception advantage degree of the fire channel is the interception advantage degree of the air defense weapon; for an air defense weapon with multiple available fire channels, disassemble it into the corresponding number of fire channels, and the interception advantage degree of each fire channel is the interception advantage degree of the air defense weapon;

[0113] According to the fire channels, combine the interception advantage degree vectors of the corresponding air defense weapons to form an overall interception advantage degree matrix P, and at the same time record the corresponding relationship between fire channels 1 to f and the air defense weapon numbers in the form of a vector, expressed as R = [r1r2…r k …r f , r k represents the air defense weapon number corresponding to the kth fire channel.

[0114] Module M5: Establish and solve a bipartite graph model according to the available fire channel set;

[0115] Module M6: Convert the bipartite graph matching result into a target allocation scheme.

[0116] Specifically, in the said Module M5:

[0117] At the solving node, a weighted bipartite graph model G=(F, T, P) is constructed with the set F of all available fire channels of air defense weapons and the set T of targets as the vertex sets and the interception advantage matrix P as the edge set, and the maximum weight matching of the bipartite graph model is solved using an appropriate algorithm; the form of the solution is:

[0118] X = [x1 x2…x k …x f

[0119] x k represents the target number matched by the k-th fire channel.

[0120] Embodiment 3:

[0121] Embodiment 3 is a preferred example of Embodiment 1 to illustrate the present invention more specifically.

[0122] The object of the present invention is to provide an air defense weapon target allocation method based on a bipartite graph. By establishing a bipartite graph model for cooperative target allocation of air defense weapons, based on the maximum weight matching algorithm of the bipartite graph, the many-to-many target allocation problem of air defense weapons is solved, and a consensus mechanism is formed using the global optimal characteristics of the maximum weight matching result to quickly provide effective target allocation results for each air defense weapon node in a distributed environment.

[0123] Step S1: Number the air defense weapons and targets. The air defense weapon nodes and targets participating in target allocation are uniformly numbered to ensure the consistency of the numbers of air defense weapons and targets during the calculation process.

[0124] Referring to Figure 2 the embodiment scenario shown, the air defense weapons are numbered 1 to 4 and the targets are numbered 1 to 5.

[0125] Step S2: Calculate the interception advantage. Each air defense weapon node calculates the interception advantage for all targets using the same interception advantage calculation model according to the interception strategy, based on the unified target data, combined with its own weapon interception ability and status. Referring to Example Figure 3 shown, the interception advantage of air defense weapon node 1 is denoted as the vector P1 = [p 11 p 12 p 13 p 14 p 15 , where p 13 = 0, p 15 = 0. Calculate P2 to P4 for air defense weapons 2 to 4 in the same way.

[0126] Step S3: Share the interception advantage. According to the command mode, in the centralized command mode, each air defense weapon node will use the vector P i ​and the number of firepower channels are sent to the command node. In the distributed mode, each air defense weapon node will represent the vector P of its own interception advantage. i Shared with all nodes.

[0127] Step S4: Establish an interception advantage matrix. According to the command mode, the command node or the air defense weapon node collects the interception advantage vectors P1~P n Combine and construct the interception advantage matrix P of all fire channels to the target. For weapon nodes with multi-target capabilities, the interception advantage vector is repeated according to the number of fire channels of the node. Figure 4 In the example shown, the number of fire channels of air defense weapon node 3 is 3, and the interception advantage matrix The corresponding firepower channel and air defense weapon number correspondence vector R = [123334].

[0129] Step S5: Establish a bipartite graph model and solve it. Figure 5 As shown in the figure, with the fire channel set F and the target set T as the vertex set and P as the edge set, a weighted bipartite graph model is constructed, and the maximum weight matching of the bipartite graph is solved by using a suitable method such as the KM algorithm, and the matching vector D = [d1 d2 d3 d4 d5 d6] is obtained, which represents the target number matched by the fire channels 1 to 6.

[0130] Step S6: Convert the bipartite graph matching result into a target allocation scheme. Combine the vector R to group the targets matched to the firepower channel into the corresponding air defense weapon nodes, and obtain the matching relationship between the air defense weapons and the targets, i.e., the target allocation scheme. In this example, the target allocation results of each air defense weapon are shown in Table 1.

[0131] Table 1

[0132] Air defense weapon number Assigned target number 1 d1 2 d2 3 d3, d4, d5 4 d6

[0133] Those skilled in the art know that, in addition to realizing the system and its various devices, modules, and units provided by the present invention in a purely computer-readable program code, it is entirely possible to realize the same functions in the form of logic gates, switches, application-specific integrated circuits, programmable logic controllers, and embedded microcontrollers by logically programming the method steps. Therefore, the system and its various devices, modules, and units provided by the present invention can be considered as a hardware component, and the devices, modules, and units included therein for realizing various functions can also be regarded as structures within the hardware component; the devices, modules, and units for realizing various functions can also be regarded as both software modules for realizing the method and structures within the hardware component.

[0134] The specific embodiments of the present invention have been described above. It should be understood that the present invention is not limited to the above specific embodiments, and those skilled in the art can make various changes or modifications within the scope of the claims, which do not affect the essence of the present invention. Without conflict, the embodiments of the present application and the features in the embodiments can be combined with each other arbitrarily.

Claims

1. A collaborative multi-target allocation method for air defense weapons based on a bipartite graph, characterized in that Including: Step S1: Uniformly number the air defense weapon nodes and targets participating in target assignment; Step S2: Construct an interception favorability model according to the interception strategy, and calculate the interception favorability of air defense weapons for all targets; Step S3: Share the interception favorability and the number of fire channels; Step S4: Combine the fire channels of all air defense weapons in sequence to form a fire channel set, and construct an interception favorability matrix of the fire channels for the targets; Step S5: Establish a bipartite graph model based on the available fire channel set and solve it; Step S6: Convert the bipartite graph matching result into a target assignment plan.

2. The collaborative multi-target allocation method for air defense weapons based on a bipartite graph according to claim 1, wherein In the said Step S2: Calculate the interception favorability. The air defense weapon node constructs an interception favorability model according to the interception strategy based on the unified target information, its own resource status and interception ability, and calculates the interception favorability of the air defense weapon for all targets; The interception favorability model is a function of multiple interception factors, which is determined before target assignment according to the mission purpose. The interception factors include target threat level, kill probability, interception time, interception cost, or new factors are introduced according to the mission characteristics; The interception favorability of node i for all targets from 1 to m is denoted as a vector: P i = [p i1 p i2 …p ij …p im ​ p ij represents the interception favorability of air defense weapon i against target j, where 0 ≤ p ij < 1. For targets that are beyond the range or have insufficient damage ability and cannot be intercepted, p ij = 0.

3. The collaborative multi-target allocation method for air defense weapons based on a bipartite graph according to claim 1, characterized in that In the said Step S3: In the centralized command mode, each air defense weapon sends the interception favorability vector and the number of fire channels to the command system, and the command system establishes a bipartite graph model and solves it; In the distributed self-organizing mode, each air defense weapon shares the interception favorability vector and the number of fire channels with other weapon nodes, and each weapon node establishes a bipartite graph model respectively and solves it independently.

4. The collaborative multi-target allocation method for air defense weapons based on a bipartite graph according to claim 1, wherein, In the said Step S4: Considering the multi-target ability of air defense weapons, combine the fire channels of all air defense weapons in sequence to form a fire channel set F, and construct an interception favorability matrix P of the fire channels for the targets; For a weapon with only one available fire channel, the interception favorability of the fire channel is the interception favorability of the air defense weapon; for an air defense weapon with multiple available fire channels, it is disassembled into the corresponding number of fire channels, and the interception favorability of each fire channel is the interception favorability of the air defense weapon; According to the firepower channels, the corresponding air defense weapons combine the intercept advantage vectors to form the overall intercept advantage matrix P. At the same time, the corresponding relationship between firepower channels 1 to f and the air defense weapon numbers is recorded in the form of a vector, expressed as R = [r1 r2…r k …r f , where r k represents the air defense weapon number corresponding to the k-th firepower channel.

5. The collaborative multi-target allocation method for air defense weapons based on a bipartite graph according to claim 1, characterized in that In the said Step S5: At the solution node, construct a weighted bipartite graph model G=(F, T, P) with the available fire channel set F of all air defense weapons and the target set T as the vertex sets and the interception favorability matrix P as the edge set, and use a suitable algorithm to solve the maximum weight matching of the bipartite graph model; the form of the solution is: X = [x1 x2…x k …x f ​ x k Denotes the target number matching the k-th fire channel.

6. An air defense weapon collaborative multi-target assignment system based on a bipartite graph, characterized in that, Including: Module M1: Uniformly number the air defense weapon nodes and targets participating in target assignment; Module M2: Construct an interception favorability model according to the interception strategy, and calculate the interception favorability of air defense weapons for all targets; Module M3: Share the interception favorability and the number of fire channels; Module M4: Combine the fire channels of all air defense weapons in sequence to form a fire channel set, and construct an interception favorability matrix of the fire channels for the targets; Module M5: Establish a bipartite graph model based on the available fire channel set and solve it; Module M6: Convert the bipartite graph matching result into a target assignment plan.

7. The bipartite graph-based air defense weapon collaborative multi-target allocation system according to claim 6, characterized in that, In the said Module M2: Calculate the interception favorability. Based on unified target information, its own resource status, and interception capabilities, the air defense weapon node constructs an interception favorability model according to the interception strategy and calculates the interception favorability of the air defense weapon for all targets. The interception favorability model is a function of multiple interception factors, which is determined before target allocation according to the mission purpose. The interception factors include the threat level of the target, the kill probability, the interception time, the interception cost, or new factors are introduced according to the mission characteristics. The interception favorability of node i for all targets from 1 to m is denoted as a vector: P i = [p i1 p i2 …p ij …p im ​ p ij Indicates the interception favorability of air defense weapon i against target j, where 0 ≤ p ij < 1. For targets that are beyond the range or have insufficient damage capabilities and cannot be intercepted, p ij = 0.

8. The bipartite graph-based air defense weapon collaborative multi-target allocation system according to claim 6, characterized in that, In the module M3: In the centralized command mode, each air defense weapon sends the interception favorability vector and the number of fire channels to the command system, and the command system establishes and solves a bipartite graph model. In the distributed self-organizing mode, each air defense weapon shares the interception favorability vector and the number of fire channels with other weapon nodes. Each weapon node establishes a bipartite graph model separately and solves it independently.

9. The bipartite graph-based air defense weapon cooperative multi-target allocation system according to claim 6, characterized in that In the module M4: Considering the multi-target ability of the air defense weapon, the fire channels of all air defense weapons are combined in sequence to form a fire channel set F, and an interception favorability matrix P of the fire channels for the targets is constructed. For a weapon with only one available fire channel, the interception favorability of the fire channel is the interception favorability of the air defense weapon. For an air defense weapon with multiple available fire channels, it is disassembled into the corresponding number of fire channels, and the interception favorability of each fire channel is the interception favorability of the air defense weapon. According to the firepower channels, the corresponding air defense weapons combine the intercept advantage vectors to form the overall intercept advantage matrix P. At the same time, the corresponding relationship between firepower channels 1 to f and the air defense weapon numbers is recorded in the form of a vector, expressed as R = [r1 r2…r k …r f , where r k represents the air defense weapon number corresponding to the kth firepower channel.

10. The bipartite graph-based air defense weapon collaborative multi-target allocation system according to claim 6, characterized in that, In the module M5: At the solution node, a weighted bipartite graph model G=(F, T, P) is constructed with the available fire channel set F of all air defense weapons and the target set T as the vertex sets and the interception favorability matrix P as the edge set, and a suitable algorithm is used to solve the maximum weight matching of the bipartite graph model. The form of the solution is: X = [x1 x2…x k …x f ​ x k Indicates the target number matched for the k-th fire channel.

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