Resilience Assessment Method for Drone Swarm Command and Control System Based on Multilayer Supernetwork Model

The structure of command and control (C2) system has a critical impact on the survivability of drone swarms, yet there is a lack of resilience assessment methods for C2 system of drone swarms with different structures under sustained attacks. This study proposes a resilience assessment method for drone swarm C2 system based on multilayer supernetwork model. First, a three‐layer supernetwork model–comprising a command and control layer, a relay communication layer, and a combat strike layer–is constructed based on the architecture diagram of the drone swarm C2 system to accurately characterize the hierarchical, interdependent, and complex features of the system. Then, a network recovery strategy based on dynamic LRCD is designed to suppress cascading failures. Additionally, a two‐dimensional resilience analysis method for communication and operational performance, along with a resilience assessment model integrating invulnerability, recoverability, and adaptability indicators, is proposed to establish a wave attack‐based resilience assessment framework. Finally, the effectiveness of the proposed method is verified through case analysis. Simulation results show that, for the three parameters of inter‐layer connection rate, node capacity, and node destruction probability, increasing the ‐ connection rate, expanding the capacity of , or protecting yields the optimal effect in improving system resilience. Compared with similar methods, the proposed network modeling method has advantages in describing complex and hierarchical system, and the assessment method is more consistent with actual application scenarios, thus providing a quantitative basis for the design of swarm C2 system.