Intelligent decision-making of airborne terminal infrared composite jamming based on DACTM-PPO

With the continuous improvement in the guidance accuracy and maneuverability of infrared-guided air-to-air missiles, combat aircraft find it increasingly difficult to effectively evade the risk of infrared missile hits through maneuvering avoidance or single infrared countermeasures alone. As a result, composite infrared countermeasures have become a critical means to ensure aircraft survivability. To address the challenge of airborne terminal composite infrared countermeasures, this study proposes an intelligent decision-making method based on an improved Proximal Policy Optimization (PPO) algorithm. From the perspective of the airborne terminal confrontation scenario, the decision constraints faced by combat aircraft under infrared-guided missile attacks are analyzed, and models for infrared decoy flares and laser directional jamming are established. An improved PPO algorithm incorporating a dynamic asymmetric clipping mechanism and a fusion of temporal memory and attention mechanisms is proposed to enhance convergence efficiency and solution quality. Furthermore, a reward function integrating the characteristics of jamming means is designed, incorporating overuse and ineffective-use penalty terms to achieve a rational balance between jamming effectiveness and resource consumption. Simulation results demonstrate that the intelligent decision-making method for infrared composite jamming can organize infrared jamming measures in a reasonably coordinated manner, exhibiting excellent performance under various typical aircraft-missile confrontation scenarios. Compared with the original near-end strategy optimization algorithm, the flexible action-evaluation algorithm, and the preset rule-based method, this method shows significant advantages in metrics such as aircraft survivability, missile miss distance, and resource utilization efficiency, demonstrating good application value.