摘要
为解决高超声速导弹协同作战效能评估优化问题,提出基于多维评估模型的多波次智能决策方法。首先,构建了将导弹毁伤概率、防御拦截概率、攻防效能优势、空间态势优势4个维度相结合的复合评估体系;其次,面向反舰作战需求,建立了以目标毁伤概率、威胁度为优化目标的任务决策模型,采用适用于单波次和多波次协同打击的遗传粒子混合算法(genetic algorithm-based particle swarm optimization,GAPSO)实现火力分配优化,通过动态威胁评估、自适应权重调整、全局最优解保护策略等改善传统算法性能;最后,以典型海战场景为例进行算法验证。结果表明:GAPSO能够显著降低目标威胁度,其中单波次打击威胁度最大下降56.92%,相较传统PSO方法提升40.63%,验证了复合评估体系对复杂战场态势的适用性;多波次打击中威胁度下降倍数逐步提高,单位迭代效能提升3.9倍;在分散态势下求解质量较PSO算法提升15.12%,展现出良好的适应能力和抗环境退化的自适应机制;三波次总威胁下降率达87.47%,单位导弹效能提升41.08%,且单波次决策耗时不超过1.55 s,满足实时性需求。验证了智能决策方法在高超声速导弹协同作战中的有效性。
To solve the optimization problems in evaluating cooperative combat effectiveness of hypersonic missiles,a multi-wave intelligent decision-making method based on a multidisional evaluation model was proposed.First,a composite evaluation system that incorporated four dimensions,namely missile damage probability,defense and interception probability,offensive and defensive efficiency advantages,and space situation advantages,was constructed.Second,in response to the requirements of anti-ship operations,a mission decision-making model was established with the target damage probability and threat degree as optimization goals.The genetic algorithm-based particle swarm optimization(GAPSO),which was suitable for single-wave and multi-wave coordinated strikes,was used to optimize firepower allocation.The performance of traditional algorithms was improved through dynamic threat assessment,adaptive weight adjustment,and a global optimal solution protection strategy.Finally,the algorithm was validated using a typical naval battlefield scenario as an example.The results show that GAPSO significantly reduces the target threat degree,with a maximum reduction of 56.92%for single waves—40.63%higher than that of traditional methods,demonstrating the applicability of the composite evaluation system in complex battlefield situations.In multi-wave attacks,the threat degree reduction multiple gradually increases,and the unit iterative efficiency increases by 3.9 times.The solution quality increases by 15.12%in dispersed situations,indicating good adaptability and resilience mechanism to environmental degradation.Across three waves,the total threat reduction rate reaches 87.47%,unit missile efficiency increases by 41.08%,and the decision-making time of a single wave is not more than 1.55 s,meeting real-time requirements.The effectiveness of the intelligent decision-making method for hypersonic missile collaborative operations is validated.
作者
熊婧伊
秦伟伟
冯倩
呼卫军
马先龙
XIONG Jingyi;QIN Weiwei;FENG Qian;HU Weijun;MA Xianlong(Rocket Force University of Engineering,Xi’an 710025,China;School of Astronautics,Northwestern Polytechnical University,Xi’an 710072,China)
出处
《火箭军工程大学学报》
2025年第6期64-74,共11页
Journal of Rocket Force University of Engineering
基金
国家自然科学基金(62125305)。
关键词
集群智能决策
作战效能评估
启发式融合算法
高超声速巡航弹
多波次攻击
cluster intelligent decision-making
combat effectiveness evaluation
heuristic fusion algorithm
hypersonic cruise missile
multiple wave attack
