Trajectory planning for uncrewed combat aircraft penetration with dynamic radar cross section constraint

The survivability and mission effectiveness of uncrewed combat aircraft (UCAV) is directly dependent on the probability of detection as determined by radar cross section (RCS) characteristics. This article presents a trajectory optimization method incorporating dynamic RCS constraints, addressing the limitation of existing approaches that model radar threats as static regions, thereby improving the adaptability of UCAVs to complex battlefield penetration scenarios. It develops a dynamic RCS model to calculate the detection probability, thereby overcoming the limitation of existing radar threat models that rely solely on distance or static RCS interpolation table. Furthermore, an improved black-winged kite algorithm incorporating dynamic selection scoring mechanism, random cross-up update strategy is presented. The proposed method combines multi-structural optimization to modify the position update strategy for hovering predation. Simulation results validate that the algorithm efficiently determines optimal trajectories under dynamic RCS constraints in multi-objective environments, ensuring rapid and accurate path planning for UCAV penetration.