This paper analyzes and models the core logic of a strike chain in terms of time sensitivity, reconfiguration and coverage, thereby providing model and method support for improving the dynamic management ability of naval combat resources under confrontation conditions.

First, the typical combat platforms and elements related to the cross-domain cooperative combat of naval battlefields, such as escort ships, UAVs and unmanned boats, are abstracted into four types of resource nodes, namely detection, processing, decision-making and strike. Next, taking the shortest delay as the goal and considering constraints such as wide battlespace, low transmission rate between nodes and limited communication distance, the dynamic integration optimization mathematical model of the strike chain is established. A typical air defense scenario is then designed to demonstrate the shortest delay analysis of the strike chain and the destruction reconstruction analysis under the absence or attack of nodes, and quantitatively describe the changes of the shortest delay and sector coverage index of the reorganized strike chain under countermeasure conditions. Finally, based on a typical combat example of a Ukrainian unmanned cluster attack on the Black Sea Fleet, the ability of the fleet to resist the attack is analyzed on basis of the strike chain model.

The simulation results show that the model can be used to generate multiple strike chains with the shortest delays, and the responsibility division of each strike chain can be optimized, forming a multi-target killing network at sea. The destruction reconstruction of the strike chain often needs to pay such costs as increased delay and decreased sector coverage. The model can also be used to test anti-saturation attack ability under different formations.

This paper studies and validates the feasibility of analyzing the naval warfare system based on the strike chain model, and can provide theoretical model support for the subsequent design of future naval joint combat systems oriented to the killing network.