A set of unmanned aerial vehicle (UAV) swarm combat effectiveness evaluation methods based on combat process simulation is constructed to address the issue of UAV swarm combat effectiveness evaluation in uncertain situations. Firstly, analyze the operational process of unmanned aerial vehicle (UAV) reconnaissance and strike missions from the perspective of closed-loop combat environment. Secondly, design a combat method calculation module based on the various steps of the closed-loop combat environment, and combine the designed parameter setting module, battlefield situation generation and recording module, global progress controller, and combat data recording module to form a complete simulation system for unmanned aerial vehicle group observation and combat process. Then, based on the available simulation data of the combat process, construct core effectiveness indicators and auxiliary effectiveness indicators, and provide a calculation and coupling method for each indicator. Finally, a scenario is set up to simulate the combat process of unmanned aerial vehicle swarms using different deployment schemes, evaluate and analyze the combat effectiveness, verify the feasibility of the proposed method, and achieve effective evaluation of the combat effectiveness of unmanned aerial vehicle swarms under uncertain situations.

With the widespread application of cruise missile technology and the increasing complexity of mission execution,the mission planning of cruise missile formations is facing new challenges.A multi patrol missile pre war planning task alloca-tion model based on multiple constraints is constructed,with the optimization objectives of mission value return and mission loss cost,while considering various practical constraints such as task execution timing.To solve the model,an improved ge-netic algorithm based on simulated annealing is designed,which adjusts the adaptive selection strategy and adaptive crossover strategy based on the population fitness of different periods,ensuring convergence while increasing population diversity.Fi-nally,the effectiveness of the designed improved algorithm in solving the task allocation problem of multiple patrol missiles was verified through a case study.

针对空战中飞机如何根据实时态势进行快速智能决策问题,提出基于改进DDPG算法的空战行为决策框架(Air Combat Behavior Decision-making Framework on Improve DDPG,ACBDF_DDPG).框架中的主要改进如下:1.设计一种针对动态目标的嵌入式人工经验奖励机制,缓解深度强化学习算法在训练过程中,由于状态空间巨大且奖励稀疏导致的收敛困难问题;2.对框架中的Actor网络更新机制进行改进,解决Critic网络评估效果差时,更新Actor网络导致的模型训练不稳定问题;3.采用优先采样机制确保训练价值高的经验样本得到充分利用.最后基于MaCA平台搭建仿真实验环境,通过消融实验验证了所提出框架中改进机制的有效性和优越性.

两栖编队指挥信息系统是两栖作战力量形成基于信息系统的一体化作战能力的关键,具备跨平台、规模庞大、组成结构复杂和作战方式灵活多变等特点,为此必须加强系统的顶层体系结构设计,以确保两栖作战装备同步协调发展.DoDAF是指导美军军事电子信息系统和武器装备架构开发的框架和指南,各国也跟随研究并开发适合国情的武备标准规范.以DoDAF2.0为体系结构设计方法,结合两栖编队遂行登陆登岛作战场景,开发指挥信息系统的体系结构模型,开展体系结构模型验证试验,试验结果表明,所设计的体系结构模型与预期一致,其研究结果可为两栖编队指挥信息系统方案设计和技术设计提供参考.

Aim at the situation of naval ship group costing a mass of ammo and long time when going fast place to execute firepower support task,research on the subsection replenishment of naval ship group.The rules of ammunition consumption are analyzed,the subsection replenishment cost model is built,bring forward optimize replenishment measure to get lowest cost.Finally,to use the measure on a representative case and analyze main parameters affecting the replenishment cost,calculation result show that this measure can satisfy the replenishment demand of naval ship group.The results of this paper can provide quantity basis and theory guidance for Subsection replenishment of naval ship group.

According to modern aerial defense presenting the network characteristics,the paper uses the method of complex network,builds up the network model of aerial defense system,and reaches the result of formation aircrafts breaking through the aerial defense systems having different network characteristics.The result has well theory guidelines foundation and optimization of aerial defense system.

For fast,accurate decision-making requirements in actual operations,this paper models operational plans using the entity-oriented approach in the concept of EBO,and puts forward evaluation network based on DBN as the evaluation engine for optimization,searches in the evaluation results using GA to get the best operational plans.Finally a landing operation is used as an example to verify the effectiveness of the method.This method takes the uncertainty into account during operational process to ensure the optimized plan to achieve the best results and also has a high robustness,which provides a scientific basis in operational optimization for operational commanders.