A Nonlinear Situation-Driven APF-Coupled UAV Swarm Confrontation Strategy

As an emerging combat form in modern warfare, unmanned aerial vehicle (UAV) swarms have demonstrated unique strategic advantages. With the evolution of combat missions to multi-dimensional and strongly dynamic scenarios, there is an increasingly urgent need for efficient swarm confrontation strate-gies. However, existing strategies are mostly based on linear situational awareness frameworks, which may have limitations in perceiving the environment. To this end, this paper proposes an artificial potential field(APF)confrontation strategy based on nonlinear situation driving(NS-APF). First, a nonlinear situation-driven confrontation strategy generation mechanism is constructed by introducing a quadratic nonlinear term of the situational-awareness function; second, an APF method is integrated on the basis of nonlinear situation decision-making, so that the strategy combines both situational-awareness and conflict-processing capabili-ties; and lastly, simulation experiments are conducted to evaluate the performance of these two confrontation strategies. The experiments show that under the same parameter conditions, the win rate of the nonlinear situation strategy over the linear situation strategy is about 65%, and the combined win rate of the NS-APF strategy is about 58 %.