Weapon target assignment method based on kill chain

Weapon target assignment method based on kill chain aims to change the status quo of the traditional method that did not consider enough the process of intelligence reconnaissance, command and control as well as information transfer in the combat process, which integrates the process of intelligence reconnaissance, command and control as well as information transfer in the kill chain into the traditional method of weapon target assignment, and searches and corrects the probability-of-destruction matrix through the kill chain and combines with the Gurobi solver to realize a more accurate weapon target assignment. The experimental part uses simulation data to verify the effectiveness of the method, and the results show that the Johnson-KC algorithm significantly outperforms the traditional DFS, BFS algorithm, and A* algorithm in terms of the efficiency of the kill chain search, and compared with the traditional weapon target assignment method, the kill chain-based weapon target assignment method reduces the target threat by nearly 50%, and streamlines the number of the remaining edges of the kill net by nearly 80%.

Traditional methods in the study of weapon target assignment mainly focus on the weapon to the target of the process of fire, for the actual combat process of the exact existence of the reconnaissance unit on the target of the process of intelligence reconnaissance can not be ignored, the command and control unit on how to combat the target of the command decision-making process as well as the intelligence unit and the reconnaissance unit between the information transfer process and did not focus on the process of consideration, the lack of consideration of these factors, may be the target is within the range of the weapon strike, the weapon is assigned to strike the target, but due to the lack of target intelligence information leads to the situation that the weapon can not strike the target, this situation will have a negative impact on the combat process, and even disrupt the overall combat planning, therefore, it is necessary to integrate the intelligence reconnaissance, information transfer and command and decision-making process into the modeling method of the weapon target assignment problem, so as to improve the weapon target assignment process, so that it can better fit the real combat environment.

Kill net modeling: The combat system is abstracted into four types of nodes: target nodes, intelligence reconnaissance nodes, command and control nodes and fire strike nodes, and the “kill net” is established through four kinds of interactive relationships: intelligence reconnaissance, information transmission, command and decision-making and fire strike.

Weapon target assignment problem modeling: The weapon target assignment problem based on kill chain is modeled as an integer programming problem, and the final result is obtained by modifying the damage probability matrix, introducing the constraints such as ammunition constraints, existence constraints of kill chain, length constraints of kill chain, and constraints on the number of ammunition borne by the target node.

Kill chain search algorithm: An improved Johnson algorithm (Johnson-KC algorithm) is proposed, which is specialized for kill chain search. The algorithm is based on the traditional Johnson algorithm with additional improvements such as kill chain node number limitation, deletion of illegal sub-chains and search vertex constraints.

The integer programming model is solved: using the Gurobi solver for the modified destruction probability matrix to achieve the optimal assignment of weapon targets.

Kill chain search efficiency improvement: The Johnson-KC algorithm significantly outperforms the traditional DFS, BFS and A* algorithms in kill chain search efficiency. Experiments show that when the node size reaches 90, the search time of Johnson-KC algorithm still does not exceed 0.1 seconds, while the search time of other algorithms increases exponentially.

Target Threat Degree Reduction: the kill chain-based weapon target assignment method reduces the target threat degree by nearly two times. The target threat degree of the traditional method is 47.66290, while that of the kill chain-based method is 27.30594, indicating that the method can more closely match the real combat situation.

Streamlining the number of remaining edges of the kill net: The method streamlines the number of remaining edges of the kill net by nearly 5 times. The initial number of remaining edges in the kill net is 543, while the traditional method is 325 and the kill chain-based method is 73, indicating that the method can more effectively utilize the information of the kill net and remove redundant information.

Method effectiveness: The weapon target assignment method based on kill chain can effectively reduce the target threat level and significantly streamline the number of remaining edges of the kill net, which improves the combat effectiveness.

Future research directions: It is necessary to further validate the effectiveness and feasibility of the method in actual battlefield environments; explore how to combine advanced technologies, such as artificial intelligence and big data, with the kill chain assignment optimization method; and validate the universality of the method in dynamic weapon target assignment problems.